Zimbabwe Vulnerability Assessment Committee (ZimVAC)

2017 Rural Livelihoods Assessment Report

1

ForewordThe National Food and Nutrition Security Information System is essential for understanding the breadth and scope of food and nutrition insecurity thereby assisting in prioritising and

planning food and nutrition interventions and broader livelihoods. In its endeavour to ‘promote and ensure adequate food and nutrition security for all people at all times’, the

Government of Zimbabwe has continued to exhibit its commitment for reducing food and nutrition insecurity, improving livelihoods and reducing poverty amongst the vulnerable

populations in Zimbabwe. In this light ZimVAC, acting as the technical advisory committee on assessments, undertook the 17th edition of the Rural Livelihoods Assessment in May

2017.

The 2017 Rural Livelihoods Assessment (RLA) provides updates on pertinent rural livelihoods issues such as education, food and income sources, income levels, expenditure patterns

and food security among other issues. It recognises and draws from other contemporary surveys that define the socio-economic context of rural livelihoods.

This report provides a summation of the results of the processes undertaken and focuses on the following thematic areas: Household demographics, social protection,

Education, food consumption patterns, food sources and nutrition, income and expenditure patterns and levels, agriculture, markets, household food security , health and nutrition,

water, sanitation and hygiene, community livelihood challenges and development priorities, resilience, shocks and hazards and gender based violence. The report concludes by giving

specific recommendations on each of the thematic areas outlined in the report. It is our hope that these recommendations will aide to your development of response strategies.

The active participation of all food and nutrition structures at National, Provincial, District and the community at large is greatly appreciated. The Government of Zimbabwe and

Development partners’ financial support provided all the impetus the ZimVAC required to meet the cost for this exercise. We also want to thank our staff at the Food and Nutrition

Council (FNC) for providing leadership, coordination and management to the whole survey.

We submit this report to you all for your use and reference in your invaluable work. We hope it will light your way as you search for lasting measures in addressing priority issues

keeping many of our rural households vulnerable to food and nutrition insecurity.

2

George D. Kembo

FNC Director/ ZimVAC ChairpersonDr. Leonard Madzingaidzo

Interim Chief Executive Officer - SIRDC

Table of Contents

3

Foreword ………………………………………………………………………………………………………………………………………………………………………………………………..…………..…………..………………………………………………….…..2Acknowledgements ………………………………………………………………………………………………………………………………………………………..…………………………..…………..…………………………………………………..…….……4Acronyms ………………………………………………………………………………………………………………………………………………………………………………………………..…………..………………………………………………..…………..………5Background and Introduction ………………………………………………………………………………………………………………………………………………………………..…………..……………………………………………..…………………..…6Assessment Purpose ……………………………………………………………………………………………………………………………………………………………………………..…………..………………………………………………..…………………13Assessment Methodology ……………………………………………………………………………………………………………………………………………………………………..…………..……………………………………………..…………………..16Demographic Description of the Sample ……………………………………………………………………………………………………………………………………………..…………..…………………………………………..…………………………21Social Protection …………………………………………………………………………………………………………………………………………………………………………………..…………..……………………………………………..…………………….28Education …………………………………………………………………………………………………………………………………….................. …………………………………..…………..………………………………………………..…………………...34Access to Extension Services ……………………………………………………………………………………………………………………..……………………………………..…………..………………………………………………..…………………...39Effects of the Fall Armyworm……………………......…………………………………………………………………………………………………………………………………………………………………………………………………………………………48Crop Production …..………………………………………………………..…………………………………………………….……….…….……...... …………………………………..…………..………………………………………………..……………….…58Households Access to Irrigation ……………………………………………………………………………………………………………………………………………………………..…………..……………………………………………..…………………….65Livestock Production ………………………………………………………………………………………………………………………..……….…………………………………………..…………..…………………………………………..…………………….…68Market Access…………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………..78Agricultural Commodity Prices…………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………83Incomes and Expenditure ……………………………………………………..……………………………………………….………………………………………..…………..……………………………………………..…………………..………………….89Livelihoods Based Coping Strategies ………………………………………………………………………………………………………………………………………………………..…………..…………………………………………..…………………..…97ISALS/ Mukando……………………………………………………………………………………………….……………..……..…………………………………………………………..…………..…………………………..………………………………………..104Household Consumption Patterns…………………………………………………………………….……………..……..………………………………………………………..…………..……………………………..………………………………………108Resilience………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………121Household Food Security Status Projections………..……......................................... ………………………………………………………………………..……………..…………..………………………………………………………….....131Nutrition ………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………149Feeding Practices in Children 6-59 months ..……………………………………………………………………………..………………………………………………... ………..…………..…......................................………………….......150Women Dietary Diversity………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………157Community Health Services……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………160Water, Sanitation and Hygiene ……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………….165Child Nutrition Status……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………..180Gender Based Violence ………………………………………………………………………..………………………………………………………………………………………………..…………..……..………………………………………………………..…185Community Challenges and Development Priorities . ………………………………………………………………………..…………………. ………………..... ………..…………..….................................…………....................190Conclusions and Recommendations …..…………………………………………………………………………………………………..……………………………………………..…………..……………………………………………………..………….195Annexes …..………………………………………………………………………………………………………………………………………………..…………………………………………..…………..…………………………………..……………………………205

Acknowledgements

• Office of the President and Cabinet

• Food and Nutrition Council

• SIRDC

• Ministry of Finance

• SADC RVAC

• Zimbabwe National Statistics Agency (ZIMSTAT)

• Ministry of Agriculture, Mechanisation and IrrigationDevelopment

• Ministry of Public Service, Labour and Social Welfare

• Ministry of Health and Child Care

• Ministry of Local Government, Public Works and NationalHousing

• Ministry of Rural Development, Promotion andPreservation of National Culture and Heritage

• Ministry of Primary and Secondary Education

• United Nations Development Programme (UNDP -ZRBF)

• United States Agency for International Development(USAID)

• UN Women

• Food and Agriculture Organization (FAO)

• National AIDS Council

• Mwenezi Development Training Centre

• World Vision

• ENSURE

• Sustainable Agriculture Trust (SAT)

• Development Aid from People to People (DAPP)

• Cluster Agricultural Development Services(CADS)

• United Methodist Committee on Relief (UMCOR)

• Community Technology DevelopmentOrganization (CTDO)

• Red Cross

• Christian Care

• Caritas

• Plan International

• Family Aids Caring Trust (FACT)

• Action Aid

• CARE International

• Lower Guruve Development Association (LGDA)

• Aquaculture Trust

The technical and financial support received from the following is greatly appreciated:

• United Nations Children’s fund (UNICEF)

• Famine Early Warning System Network(FEWSNET)

• World Food Programme (WFP)

• Rural District Councils

• Adventist Development and Relief Agency (ADRA)

• Save the Children

• Amalima

• SNV/Environment Africa/CAFOD

• Hope for Child in Christ (HOCIC)

• Catholic Relief Services (CRS)

• GOAL

• Hand in Hand

• AFRICAID

• Tony White

• Action Contre la Faim (ACF)

• Welthungerhilfe

• CATCH

• DOMCCP

• Higher Life Foundation4

Acronyms

5

EA Enumeration Area

FGD Focus Group Discussion

FNC Food and Nutrition Council

FNSP Food and nutrition Security Policy

GAM Global Acute Malnutrition

HDDS Household Dietary Diversity

HHS Household Hunger Score

MAD Minimum Acceptable Diet

MDD Minimum Dietary Diversity

MMF Minimum Meal Frequency

RLA Rural Livelihoods Assessment

SAM Severe Acute Malnutrition

ZimVAC Zimbabwe Vulnerability Assessment Committee

Background and Introduction

6

Zimbabwe Vulnerability Assessment Committee (ZimVAC)

ZimVAC is a consortium of Government, UN agencies, NGOs and other international organisations established in 2002, led and regulated by Government. It

is chaired by FNC, a department in the Office of the President and Cabinet whose mandate is to promote a multi-sectoral response to food insecurity and

nutrition problems in a manner that ensures that every Zimbabwean is free from hunger and malnutrition.

ZimVAC supports Government, particularly the FNC in:

• Convening and coordinating national food and nutrition security issues in Zimbabwe

• Charting a practical way forward for fulfilling legal and existing policy commitments in food and nutrition security

• Advising Government on strategic directions in food and nutrition security

• Undertaking a “watchdog role” and supporting and facilitating action to ensure commitments in food and nutrition are kept on track by different sectors

through a number of core functions such as:

▪ Undertaking food and nutrition assessments, analysis and research,

▪ Promoting multi-sectoral and innovative approaches for addressing food and nutrition insecurity, and:

▪ Supporting and building national capacity for food and nutrition security including at sub-national levels.

7

Background • Since 2011, Zimbabwe’s Gross Domestic Product growth rate has been declining from a high of 11.9% to 1.5% in 2015. It was estimated at 0.6% in 2016 but is now

projected to rise to 3.7% in 2017 and to taper off slightly to 3.4% in 2018 mainly on the back of improved performance of the agricultural sector (Ministry of Finance,

2017; World Bank, 2017).

• Year on year inflation rate has been in the negative for the whole of 2016 but has accelerated into the positive, from -0.7% in January 2017 to 0.5% in April 2017. The

increase in annual headline inflation was mainly driven by food inflation (ZIMSTAT, 2017).

• Decent and secure employment remain subdued and the economy continues to be gripped in the throes of deep and widespread cash shortages that have mainly

arisen from sustained higher imports against lower export earnings. As of May 2017, the country was experiencing a cash shortage of USD347 million, which is an

improvement from an average shortage of USD450 million experienced during the greater part of 2016 (Reserve Bank of Zimbabwe, 2017).

• The ZimSTAT 2011/2012 Poverty Income and Consumption Survey estimated 76% of rural households to be poor and 23% were deemed extremely poor. This

situation is likely to have worsened given the economic performance in the intervening period up to 2016.

• The normal to above normal 2016/17 rainfall season, coming after a devastating El Nino induced drought, coupled with support from both Government and Private

sector through the Special Maize Programme as well as other supportive initiatives such as contract farming had a positive impact on the agriculture sector.

• Given the importance of the agricultural sector to rural livelihoods as well as the Zimbabwean economy, this significant improvement in the agricultural sector

denotes improvements in rural livelihoods in general.

• Most dams in the seven catchment areas were full and spilling over. Average national dam levels as at 5 May 2017 were 81.3%, up from 71.5% reported in February

(Zimbabwe National Water Authority, 2017).

8

Background - The 2016/17 Rainfall and Agricultural Season Quality

Zimbabwe Calculated SOS (used as planting dekad for maize) for 2016/17 season as of dekad 2 of April 2017.

Zimbabwe Start of Season Anomaly (compared to average) 2016/17 season as of dekad 2 of April 2017.

• The 2016/17 rainfall season started in November 2016 for most parts of

the country. The bulk of the country received effective rainfall during

the 2nd dekad of November.

• The rains were generally on time for most parts of the country

and slightly early in some parts of the country and it was 10-30

days late in most of the areas where its onset was in December

2016.9

Background - The 2016/17 Rainfall and Agricultural Season Quality

• Generally, the rainfall distributions in space and time over

the season were good. By the end of the rainfall season in

April 2017, most areas across the country had received

normal to above normal rains.

• Given the normal to above normal rains received across the

country as well as the generally good distribution, the maize

crop performance ranged from good to very good for most

areas and was average in the southern part of the country. A

few isolated areas had mediocre maize crop performance.10

Background - 2016/17 Rainfall and Agriculture Season Challenges

• Zimbabwe faced critical shortages of fertilizers this season as fertilizer companies experienced liquidity challenges to pay for raw materials.

As a result, most communal farmers planted without basal fertilizers.

• The Fall Armyworm wreaked havoc initially in the western parts of the country but spread to all provinces and some peri-urban areas,

attacking crops (maize, small grains and others).

• The worm proved more difficult to control compared to the common African Armyworm. Shortage of the right chemicals and poor liquidity

among farmers made it difficult to contain the outbreak. However, the pest’s impact on crop yields were minimal. Nonetheless, this pest

has potential to undermine future crop production and overall national food security if no effective control strategies are not put in place

urgently.

• In mid-February, the southern parts of the country (mainly Masvingo, southern Midlands and the Matabeleland Provinces) were hit by the

effects of the tropical depression Dineo, which precipitated flooding that destroyed crops, livestock, property, infrastructure (roads,

bridges, dams etc.), worsening the preceding damage from the persistent rains that had been received across the country (FEWSNET, 2017).

• Due to the extent of the problem, His Excellency the President of the Republic of Zimbabwe Cde. R.G. Mugabe, in accordance with

Subsection (1) of Section 27 of the Civil Protection Act of 1989 declared a State of Flood Disaster on 2 March 2017. The declaration covered

severely flood affected areas in communal, resettlement lands and urban areas of Zimbabwe. 11

Background - Areas Most Affected by the Effects of the Tropical Depression Dineo

• Areas most affected by flooding and waterlogging

include Tsholotsho, Lupane, Nkayi, Binga, Umguza,

Hwange urban, Matobo, Umzingwane, Bulilima,

Insiza, Beitbridge, Gwanda, Gokwe North, Gokwe

South, and Mberengwa, Chivi, Mwenezi, Chiredzi,

Masvingo rural, Bikita, Kariba, Zvimba, Hurungwe,

Mutare rural, Mutasa, Buhera, Chipinge,

Chimanimani, Guruve, Mt. Darwin ,Mutoko and

Marondera (rural) District.

• The worst affected district was Tsholotsho where a

total of 859 people were left homeless.

12

Assessment Purpose

• The overall purpose of the 2017 Rural Livelihoods Assessment was to provide an annual update on rural livelihoods for the

purposes of informing policy formulation and programming appropriate interventions.

13

Specific Objectives

The 2017 ZimVAC Rural Livelihoods Assessment was conducted with the broad objective of assessing the prevailing food and nutrition insecurity situation,

impact of the food assistance and input support programmes on rural livelihoods in Zimbabwe. The assessment’s specific objectives were:

• To estimate the population that is likely to be food insecure in the 2017/18 consumption year, their geographic distribution, gender distribution and the

severity of their food insecurity;

• To assess the nutrition status of children of 6 – 59 months in rural households;

• To describe the socio-economic profiles of rural households in terms of such characteristics as their demographics, access to basic services (education,

health services and water and sanitation facilities), income sources, incomes and expenditure patterns, food consumption patterns, consumption coping

strategies and livelihoods coping strategies;

• To determine the coverage and impact of livelihoods interventions in rural households;

• To identify viable response interventions to community challenges in rural households;

• To identify development priorities for rural communities in rural provinces of the country; and

• To measure household resilience and identify constraints to improving community resilience and rural livelihoods including opportunities and pathways

of addressing them in the face of prevailing and unpredictable shocks and stresses. 14

Technical Scope

• Household demographics

• Social Protection

• Education

• Food consumption patterns

• Income and expenditure patterns and levels

• Agriculture

• Markets

• Household food security

• Nutrition

• Water, Sanitation and Hygiene

• Community livelihood challenges and development priorities.

• Resilience, Shocks and hazards

• Gender Based Violence

The 2017 RLA collected and analysed information on the following thematic areas:

15

Assessment Methodology

16

Methodology and Assessment Process• The assessment design was informed by the multi-sectoral objectives generated through a multi-stakeholder consultation process.

• An appropriate survey design and protocol, informed by the survey objectives, was developed.

• The assessment used a structured household questionnaire, a community Focus Group Discussion questionnaire and 2 District key

informant questionnaires as the primary data collection instruments.

• ZimVAC national supervisors and enumerators were recruited from Government, United Nations, Technical partners and Non-

Governmental Organisations. These underwent training in all aspects of the assessment (background, data collection tools, assessment

sampling strategy and assessment supervision).

• The Ministry of Rural Development, Promotion and Preservation of National Culture and Heritage through the Provincial Administrators’

offices coordinated the recruitment of district level enumerators and mobilisation of vehicles in each of the 60 rural districts of Zimbabwe.

• District enumeration teams comprised of officers from Government and local NGOs. Each district enumeration team had one

Anthropometrist who had the responsibility of measuring children aged 6-59 months. District enumeration teams were trained by national

supervisors.

• Primary data collection took place from 11 to 23 May 2017, followed by data entry and cleaning from the 26th to the 28th of May 2017.

• Data analysis and report writing ran from the 29th of May 2017 to the 5th of June 2017. Various secondary data sources were used to

contextualise the analysis and reporting.

• Data analysis and report writing was done by a team of 30 technical officers from Government, United Nations and technical partners

under the leadership and coordination of FNC. 17

Data Collection Methods and Sample Size• The sample was drawn from the ZIMSTAT 2012 Master sample.

• The sampling design was multi-pronged and comprised of;

• non-probability sampling (purposive sampling) for district level key informant interviews and community level focus group discussions

• probability sampling for household surveys where

• household food insecurity prevalence was used as the key indicator for sample size determination

• results for the key indicators are statistically representative at district, provincial and national level at 95% level of confidence

• a two stage cluster sampling was employed with

• the first stage involved EA selection using the PPS principle

• the second stage involved household selection using systematic random sampling

• Primary data collection was undertaken in 25 Enumeration Areas (EAs) in each district, selected usingsystematic random sampling applying the proportion to population size principle.

• Households were systematically randomly sampled in one randomly selected village in each of thesampled EAs.

• The final sample of households was 11 858 and that for children aged 6 to 59 months was 4 422

• One community key informant Focus Group Discussion (FGD) was held in each of the selected wards,bringing the total community key informant FDGs to 1 170.

• Two district level key informant interviews on food assistance and school feeding interventions wereadministered in each of the 60 rural districts.

• In addition to the above, field observations and systematic secondary data review yielded valuableinformation that was used in the analysis and writing of the assessment report.

Province Households Children under 5 Community

FGDs

Manicaland1379 447 155

Mashonaland

Central

1579 660 173

Mashonaland East

1795 675 159

Mashonaland West

1376 470 119

Matabeleland

North

1387 523 134

Matabeleland

South

1384 550 123

Midlands

1568 610 158

Masvingo

1390 487 149

Total11858 4422 1170

18

Sampled Wards

19

Data Preparation and Analysis

• All primary data was captured using CSPro and was consolidated and converted into SPSS datasets for:

• Household analysis

• Child Nutrition

• Community key informant interviews

• District key informant interviews

• Data cleaning and analysis were done using SPSS, ENA, Stata, Microsoft Excel and GIS packages.

• Analyses of the different thematic areas covered by the assessment were informed and guided by relevant local and international

frameworks, where they exist.

• Gender, as a cross cutting issue, was recognised throughout the analysis.

20

Demographic Description of the Sample

21

Population Distribution by Age and Sex

12,4

38,6 40,6

8,411,8

34,9

43,4

9,9

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

90,0

100,0

0-4 years 5-17 years 18-59 years 60 years +

Per

cen

t P

op

ula

tio

n (

%)

Male Female

• The highest population group in the sampled households was in the 18-59 years age category.

• The pattern is similar to the one observed last year and in previous surveys.22

Population Distribution by Age

12,5 13,2 12,1 12,6 11,2 11,5 12,1 11,7 12,1

37,0 35,5 35,5 34,537,8 36,3 37,6 39,5

36,741,6

44,0 42,345,6

40,7 41,5 41,538,9

42,0

8,9 7,310,2

7,410,3 10,7 8,8 9,9 9,2

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

90,0

100,0

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f P

op

ula

tio

n (

%)

0-4 yrs 5-17 yrs 18-59 yrs 60 yrs +

• Nationally, the 18 – 59 age group had the highest proportion (42.0%) of the sampled households followed by age group 5 - 17 (36.7%).

• Children aged 0-4 years constituted 12.1% while the elderly age group 60 years and above were 9.2%.

23

Sex and Age of Household Head

6476

6875

6557

7063 67

3624

3225

3543

3037 33

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Male Female

• Most households (67%) were headed by males while 33% were female headed.

• Of these household heads, 0.5% represented child headed households while 32% represented the elderly headed households.

• There is a decrease in child headed households from 2% (2016) whereas the elderly headed households increased from 27%.

• The average age of household heads was 50 years.

• The average household size was 5. 24

Marital Status of Household Head

• A greater proportion of household heads (64.3%) were married and living together with their spouses while (21.5%) were widows and

widowers.

64,773,3

64,072,8

62,6

50,8

66,158,4

64,3

6,4

2,9

7,8

3,4

8,3

10,0

6,0

10,26,8

5,6

6,15,4

4,4

4,9

5,7

4,73,7

5,1

21,216,3

20,7 17,121,7

29,1

21,326,1 21,5

2,1 1,4 2,1 2,3 2,5 4,3 1,9 1,5 2,2

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

Hea

ds

(%)

Married living together Married living apart Divorced/seperated Widow/widower Never married

25

Vulnerability Attributes

6

8

22

5,9 5,5

21,5

2,5

4,3

15

0

5

10

15

20

25

Chronically Ill Physically/Mentally challenged Orphans

Pro

po

rtio

n o

f H

ou

seh

old

s w

ith

at

leas

t a

mem

ber

(%

)

2015 2016 2017

• The above results show a declining trend in households’ burden of vulnerability from 2015 to 2017.

26

Dependency Ratio

• Household dependency ratio was calculated as follows:

Number of economically inactive members/

number of economically active members.

• The average household dependency ratio was 1.7.

• The highest dependency ratio was recorded in

Masvingo, Matabeleland North and Matabeleland South

(1.8).

• The lowest dependency ratio was recorded in

Mashonaland West at 1.5.

Province 2016 Dependency Ratio 2017 Dependency

Ratio

Manicaland 1.8 1.7

Mashonaland Central 1.6 1.6

Mashonaland East 1.7 1.6

Mashonaland West 1.5 1.5

Matabeleland North 1.9 1.8

Matabeleland South 1.9 1.8

Midlands 1.9 1.7

Masvingo 2.0 1.8

National 1.8 1.7

27

Social Protection

28

Background to 2016/17 Social Assistance and ProtectionBeneficiaries of food assistance at a distribution point. Workers stacking bags of maize grain at a GMB depot.

• The 2015/16 production year was affected by adverse weather conditions (El-Nino) which resulted in the nation declaring a state of emergency as well as

launching the Domestic and International Appeal for food supply assistance in February 2016.

• The 2016 Rural Livelihoods Assessment estimated that 4.1 million rural people would be food insecure in the peak hunger period (Jan-March 2017).

• Government and partners mobilised resources from both within and outside the country and supported the vulnerable and food insecure populations.

• Over the period October 2015 through to May 2017, Government had distributed more than 550 000 Mt of maize grain to food insecure households (Ministry

of Public Service, Labour and Social Welfare) while UN/NGO partners imported and distributed 39 423.20Mt of maize grain between February 2016 and May

2017 (WFP).

29

Households which Received Support

51

65

58

7067

7067 68

6560

75

62

68

80 7875 74

71

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

2016 2017

• During 2016/17 consumption year, about 71% of rural households received some support in at least one of the following forms; food, cash, crop inputs, livestock

inputs as well as Water, Sanitation and Hygiene.

• There has been an increase in the proportion of households that received support during the 2016/17 consumption year compared to the previous one.

• All the rural provinces reported an increase in the proportion of households that received support except for Mashonaland West which had a slight drop from 70%

in 2015/16 to 68% in 2016/17.30

Sources of Support

Province Government % UN/NGO % Churches %

Relatives within rural

areas %

Relatives within urban

areas %

Remittances outside

Zimbabwe %

2015/16 2016/17 2015/16 2016/17 2015/16 2016/17 2015/16 2016/17 2015/16 2016/17 2015/16 2016/17

Manicaland 49 74.1 18.7 44.3 3.1 3.6 10.7 10 13.6 13.9 4.6 5.8

Mash Central 71.1 90.5 14.3 24.5 1.3 2.7 6.5 11 5.3 12 1.5 1.8

Mash East 42.6 64.1 5.9 30.6 2.7 2.8 14.8 16.7 25.4 30.3 7.8 9.2

Mash West 67.7 93.3 8.5 9.6 1.3 2.7 6.7 8.8 11.6 10.7 3.9 1.8

Mat North 43.5 77.9 24.9 32.2 1.1 2 9.2 5.9 12.4 10.4 8.3 11.2

Mat South 29.4 75.2 20.6 37.5 2.7 3.4 8.8 10.8 13 16.2 24 31.4

Midlands 51.9 75.0 14.9 36.6 1.7 2.5 9.1 13.7 15.1 18.8 7.1 9.9

Masvingo 36 63.4 24.7 40.3 2 2.5 13.9 9.7 14.9 16.2 8.1 9.1

National 48.5 76.7 16.4 32 2 2.7 10.1 10.9 14.2 16.3 8.3 10.3

• There was a remarkable increase in Government support from 48.5% (2015/16) to 76.7% (2016/17).

• Mashonaland West (93.3%) had the highest proportion of households receiving support from Government followed by Mashonaland Central (90.5%).

• UN/NGOs support was highest in Manicaland (44.3%) followed by Masvingo (40.3%).

• Matabeleland South (31.4%) had the highest percentage of remittances from outside Zimbabwe followed by Matabeleland North (11.2%).

• UN/NGO support also doubled from 16.4% (2015/16) to 32% (2016/17).

• Support from churches, from relatives within and outside Zimbabwe marginally in 2016/17 increased from their 2015/16 levels. 31

Forms of Support

• Food as a form of support to vulnerable households increased from 40% (2015) to 59% (2017) whereas cash support dropped from 31% (2015) to 24% (2016 and

2017).

• Crop input support has also been fluctuating from a high of 72% in 2015 down to 30% in 2016 then rising to 34% in 2017.

• Livestock inputs and WASH inputs as forms of support have been on a downward trend since 2015.

40

31

72

6 6

48

24

30

3 3

59

24

34

2 2

0

10

20

30

40

50

60

70

80

90

100

Food Support Cash Support Crop Support Livestock Support WASH support

Pro

po

rtio

no

f H

ou

seh

old

s (%

)

2015 2016 2017

32

Forms of Support

• The most common form of support received by households was food (59.0%) followed by crop inputs (34.2%).

• Matabeleland North had the highest proportion of households receiving Food (69.4%) followed by Matabeleland South (66.9%).

• Livestock support remained very low across all provinces.

• Crop Inputs support was high in Mashonaland Central (49.5%) followed by Midlands (40.4%).

Province

Food Support % Cash support % Crop Input support % Livestock support % WASH support %

2015 2016 2017 2015 2016 2017 2015 2016 2017 2015 2016 2017 2015 2016 2017

Manicaland 31.9 39 44.1 25.6 18 17.9 72.4 21.9 28.3 4.1 1.7 1.4 1.8 0.9 0.7Mash Central 15.9 43.1 65.8 11.3 13.4 19.3 87.6 46.2 49.5 3.9 2.8 1.1 4.7 2.6 0.9

Mash East 45 39.3 51.9 37.4 28.3 19.9 80.2 36.2 29.8 5.8 3.3 3.0 3 1.4 2.1

Mash West 25.7 53.8 58.4 25.7 13.6 8.6 80.2 46 37.8 6.9 1.9 1.2 3.2 3.3 1.3

Mat North 54 60.3 69.4 32.3 21.8 23.1 49.5 12.9 29.2 5.3 1.3 2.2 2.6 3.5 2.9

Mat South 54 53.6 66.9 45.5 39 41.5 58.2 16 29.3 4.7 2.8 2.2 4 1.8 5.9

Midlands 33.9 42.4 57.5 23.3 27.5 34.1 72.7 36 40.4 6 3.1 1.6 8.7 3.1 1.8

Masvingo 63.3 54.2 59.4 46 31.3 28.2 59.9 20.2 27.6 11.1 2.7 2.3 22.3 4.6 1.5

National 40.4 47.8 59.0 31.4 24.1 24.0 72 30.1 34.2 6.1 2.5 1.9 6.4 2.6 2.1

33

Education

34

School Attendance by Children

• About 88.4% of the children of school going age were in school during the survey period.

• The proportion of children out of school during the survey period decreased from 15.3% in 2016 to 11.6% in 2017.

84,7

15,3

88,4

11,6

0

10

20

30

40

50

60

70

80

90

100

In school Not in school

Pro

po

rtio

n o

f sc

ho

ol g

oin

g ag

e ch

ildre

n (

%)

2016 2017

35

School Attendance by Sex

88

12

89,3

10,7

0

10

20

30

40

50

60

70

80

90

100

In school Not in school

Pro

po

rtio

n o

f sc

ho

ol g

oin

g ag

e ch

ildre

n (

%)

Male Female

• About 89.3% of female children and 88% of male children were in school at the time of the survey.

36

Reasons for not Attending School

• Of those children who were not in school during the survey period, 42% were not in school due to financial constraints followed by 23% who

were considered too young.

• The reason that children were being considered too young to go to school and that of schools being too far may be suggestive of limited

physical access to school, particularly those that cater for Early Child Development levels.

• About 7% were not in school due to illness.37

42

23

7

6

5

5

3

2

32

24

5

4

3

2

1

0 5 10 15 20 25 30 35 40 45

Expensive or no money

Child considered too young

Illness

Distance to school too far

Arrears/Non-payment of school fees

Not interested in school

Pregnancy/marriage

Disability

Proportion of school going age children (%)

2016 2017

Children Turned Away From School Due to Non-Payment of Fees

• This graph shows the proportion of children of school going age who were turned away from school, at one time or another, during the first term

of 2017 due to non-payment of school fees.

• Nationally, at least 63% of the children experienced being turned away for non payment of school fees. Generally, the proportion of children who

were turned away from school during the first term of 2017 was high in all provinces. This is so despite there being in place a policy that

discourages this practice.

76

5760

7064

6165

50

63

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f sc

ho

ol g

oin

g ag

e c

hild

ren

(%

)

38

Access to Agricultural Extension Services

39

Households which Received Agricultural Training

46

29

46

29

3935 35 37 38

42

34 3528

3630

3933 35

4134 32

28

39

3134 34 34

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

2015 2016 2017

• The proportion of households receiving agricultural training has remained relatively low for the past 3 years at 38% in 2014/15, 35% in

2015/16 and 34% in 2016/17.

• This calls for the need to capacitate extension services.

40

Access to Agricultural Training by Household Characteristics

29

42 41

59

31 3143 39 39

49

37 43

27

49 5541 49 44

17 1614 11

139 13 9

13

2 3 1 1 3 2 1 1 2

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Father Mother Both mother and father Daughter Son Other relative

• Mothers and fathers participated more in agricultural training at 44% and 39% respectively.

• With the exception of Mashonaland West province, households with mothers that participated in the trainings were more than those with fathers that did

so across all provinces.

• Matabeleland South and Matabeleland North had the highest proportion of households with mothers who participated in training at 55% and 49%

respectively.

• Mashonaland West had the highest proportion of households with fathers who participated in the training at 59%.

41

Households which Received Extension Visits

3329 27 25 26 25

3125

28

34 3630 30 32

2531 29 31

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

2016 2017

• The proportion of households that received extension visits marginally increased from 28% to 31% between 2015/16 and

2016/17, but generally remained low across all provinces.

• The proportion of households that received extension visits increased in all provinces except Midlands where it remained

unchanged.42

Households which Sought Agricultural Advice

3226 25 21 24

1925 24 25

29 30 28 25 2419

27 24 26

0102030405060708090

100

2015/16 2016/17

• The proportion of households which sought cropping advice was high in Mashonaland Central and Manicaland.

• The proportion of households which sought livestock advice was high in Matabeleland North and Matabeleland South, Midlands and

Masvingo Provinces.

• There was no significant increase in the proportion of households that sought cropping advice out of their own initiative from 25% in

the 2015/16 season to 26% in the 2016/17 season.

Agricultural Advice Cropping Advice

26 23 24 2128 24 28 24 25

29 30 28 25 2419

27 24 26

0102030405060708090

100

Livestock advice Cropping advice

43

Crop Extension Providers

8982

91 88 8883

88 91 88

8

7

3 5 810

75

7

18

3 6 22

3 2 31 2 2 1 2 4 3 1 2

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Government NGOs Private companies Research organization Lead farmer

• Government was reported as the most common provider of crop extension services in all provinces (88%) followed by NGOs (7%).

• The highest proportion of households which received support services from Lead Farmers was reported in Matabeleland South (4%).

44

Livestock Extension Providers

95 92 97 9689 87 90 93 92

34

2 19

65 5 4

1 3 0 2 11

1 0 10 1 2 1 1

7 3 2 2

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Government NGOs Private companies Research organization Lead farmer

• Government was reported as the major provider of livestock extension services in all provinces (92%) followed by NGOs (4%)

• The highest proportion of households which received support services from Lead Farmers was recorded in Matabeleland South (7%)

45

Households with Livestock that were Vaccinated

5751 53

62

7165 64

6762

56

47 48

56 57 6056

64

55

37

50

33

42

35 37 3841 39

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

FMD Anthrax New Castle

• About 62% of rural households with cattle reported that their cattle were vaccinated against Foot and Mouth Disease (FMD) and 55 % reported vaccination

against Anthrax

• About 39% of households with chickens reported their flock was vaccinated against New Castle disease.

• The highest proportion of households with cattle that were vaccinated against FMD was in Matabeleland North (71%), Masvingo had the highest vaccinations

against anthrax (64%) and Mashonaland Central had the highest vaccinations against New Castle disease (50%).

46

Households Trained in Participatory Disease Surveillance

6367

6458

50

57 59 59 60

3733

3642

50

44 42 41 41

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

No Yes

• About 41% of the households owning cattle received training in participatory disease surveillance between April 2016 and March 2017.

• Matabeleland South had the highest proportion of households that received training (50%) and Mashonaland Central had the lowest

proportion of households (33%).47

Effects of the Fall Armyworm

Maize Crop Damaged by the Fall Armyworm

Fall Armyworm on Growing Cob Premature Drying on Damaged Cob

48

Proportion of Households Affected by the Fall Armyworm 2016/17

16

53

23

32

45

37

45

38 36

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

• At least 36% of households were affected by the Fall Armyworm in the 2016/17 agricultural season.

• Mashonaland Central had highest proportion of affected households (53%) while Manicaland had the least affected (16%).49

Crops Affected by the Fall Armyworm96

62 1,5 2,6

0

10

20

30

40

50

60

70

80

90

100

Maize Sorghum Finger millet Pearl millet Cowpeas

Per

cen

tage

of

Ho

use

ho

lds

(%)

• About 96% of the households reported that their maize crop was affected by the Fall armyworm.

• Other crops of major agricultural importance attacked by the pest include sorghum, millets, cowpeas, groundnuts, potatoes, soyabean and

cotton. 50

Crop Development Stage Affected

• About 63.8% of the households whose crops were infested by fall armyworm indicated that their crops were mostly first attacked

when they were in their vegetative stage.

8,8

63,8

37,1

0

10

20

30

40

50

60

70

80

90

100

Emergency Vegetative Reproductive

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

51

Period the Fall Armyworm was First Observed

,1 ,1 1,6

7,8

37,243,1

8,9

1,2 ,00,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

90,0

100,0

Sep-16 Oct-16 Nov-16 Dec-16 Jan-17 Feb-17 Mar-17 Apr-17 May-17

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

• The Fall armyworm was observed for the first time in September 2016 in isolated cases and became more prevalent in January and February 2017 when most

households observed it across all the provinces.

• Infestation levels of the pest were highest in February 2017 when about 43.1% those households that were affected by fall armyworm first observed the worm on

their crop. As the majority of the crop was planted mid November 2016, in February the crop was at its optimum vegetative stage.

• Infestation in April (12%) decreased as most crops had reached physiological maturity although the pest feeds on kernels as well. 52

Measures Taken to Control Fall Armyworm

62,5

17,8

9,113,5

2,3 3,2 10

10

20

30

40

50

60

70

80

90

100

nothing traditional control applied commercialpesticides (more

than recommended)

applied commercialpesticides

(recommended)

applied commercialpesticides (less than

recommended)

applied othersubstances

other methods

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

• Of the households whose crops were attacked by fall armyworm, about 62.5% of the households did not take any measures to control

the pest resulting in extensive damage to crops.

• Other households used commercial pesticides(including recommended ones) while others applied other substances like sand and

ground amaranthus. Yet other households resorted to handpicking and squashing the worms in an attempt` to control them. 53

Success of Control Measures

• About 47.2% of the affected households reported that the methods used were not effective. This includes those who applied

pesticides at different levels which were less than the recommended dosage, the recommended dosage and more than the

recommended dosage.

18,8

42,447,2

0

10

20

30

40

50

60

70

80

90

100

Extremely effective Somewhat effective Not effective

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

54

Reasons for not Using Pesticides

4 4

77

4

18

0

10

20

30

40

50

60

70

80

90

100

the pest damage was insignificant pesticides were not available at localshops

no money to purchase the pesticides did not know which pesticides to apply other specify

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

• About 77% of households that did nothing did so because of lack of money to purchase chemicals, 4% the households could not find the

pesticides and 4% did not know the pesticides to apply . 55

Methods Used to Apply Pesticide or Substance

• About 69% of the households that sprayed the pest used knapsack sprayers to apply pesticides against the recommended method of pouring

used by 29% of the households.

• Spot spraying of affected plants directly into the funnel increases chances of contact between pest and insecticide. Drenching funnels also

increases chances of drowning and suffocating the pest. 56

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

90,0

100,0

Pouring/splashing no equipment Knapsack sprayer Other

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

Provision of Extension Advice to Households Affected by Fall Armyworm

69

26

2 3

0

10

20

30

40

50

60

70

80

90

100

Extension Officer Neighbour or friend Pesticide seller or agro dealer Others

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

• About 36% of the households affected by the fall armyworm received extension advice.

• Of these 69% received it from Government extension officers and 26% from neighbours or friends.

• Some households also received relevant information on the Fall armyworm through the mass media (radios, television, flyers and newspapers).57

Crop Production

58

Proportion of Households which Planted Crops

• Maize (88%), groundnuts (47%) and cowpeas (40%) were the most common crops planted by households. The proportion of households

growing small grains remains low, despite all the efforts and rhetoric to promote the growing of these crops.

• The was a general increase in the proportion of households that planted all crops. The greatest increase was in the proportion of

households that grew tobacco and cotton due to support these crops got from the private sector and the Government, respectively.

84

43

34

28 26

20

12 10

4 3

10

2 2

88

47

40

2831

27

12 10

26

20

11

2 3

0

10

20

30

40

50

60

70

80

90

100

Maize Groundnuts Cowpeas Sorghum Roundnuts Tubers P. Millets Sugar beans Tobacco Cotton F. Millet Soyabeans Sunflowers

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

2015/2016 2016/17

59

Proportion of Households which Planted Cereals by Province

• Over 80% of households in all the provinces planted maize.

• As in the previous seasons, Matabeleland South, Matabeleland North and Masvingo had high proportions of households which grew small grains in the

2016/2017 agricultural season.

8688 89

8684

82

9693

88

2326

19

9

41

47

28

35

28

10

46

1

36

25

5

141211

2

13

2

711 12

26

11

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

Maize Sorghum P. Millet F. Millet

60

Adequacy of Agricultural Labour

• Nationally, 92% of the households practiced agriculture. Of these, 54% of the households reported inadequacy of agricultural labour during the

agricultural season.

• The inadequacy of agricultural labour across all provinces calls for increased use of agricultural labour saving technologies.

91 92 90 8992 92

96 94 92

55 57

4853

4953

62

53 54

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

Practiced Inadequate labour

61

Hiring of Agricultural labour

• About 19% of the households hired casual labour for agricultural purposes.

• Mashonaland East and Mashonaland West had the highest proportion of households that reported to have hired labour (22%) and Masvingo the

least (15%).

• About 17% of the households accessed agricultural labour from relatives and friends.

91 9290 89

92 9296

9492

18 1922 22

17 18 1715

1915

1115

1922 22

1815

17

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

Practiced Hired Assisted

62

Sources of Seeds Used by Households During the 2016/2017 Agricultural Season

CropsPurchase

(%)Government

(%)NGOs

(%)Carryover

(%)Retained

(%)Remittance

(%)

Private Companies

(%)

Labour exchange

(%)Other

(%)

Maize 41.8 28.5 2.3 4.2 14.2 6 0.2 1.9 1.0

Sorghum 15.3 5.3 6.7 8.5 42.1 17.2 0.6 2.5 1.9

F. Millet 12.8 0.7 1.2 11.6 52.0 16.3 0.3 1.6 3.5

P. Millet 9.2 1.2 2.6 11.5 56.0 16.4 0 1.1 2.0

Tubers 16.8 1.1 0.4 15.0 46.0 15.6 0 2.1 3.2

Cowpeas 19.9 18 2.5 8.8 47.5 15.7 0.1 1.7 2.1

Groundnuts 25.0 1.4 0.8 10.0 47.5 11.6 0.1 2.4 1.1

Roundnuts 24.0 1.3 0.4 10.8 46.5 12.8 0 2.8 1.3

Sugar Beans 45.3 3.9 1.2 8.5 31.9 6.7 0.2 1.2 1.2

Soyabeans 8.3 0 8.3 8.3 41.7 0 0 0 33.3

Tobacco 72.0 3.2 0.8 0.5 1.3 2.7 15.1 2.4 1.9

Cotton 16.5 46.0 1.9 2.9 2.3 2.6 25.9 1.3 0.6

Paprika 59.3 7.4 0 0 9.3 1.9 20.4 0 1.9

Sunflower 19.9 5.8 1.0 9.3 42.6 14.1 1.4 0.7 5.2

• Purchases were the main

source of seed for maize,

tobacco, paprika and sugar

beans.

• Retained seed was the

major source for small

grains, cowpeas, tubers,

groundnuts and round nuts.

• The main source of inputs

for cotton was Government.

63

Average Household Cereal Production by ProvinceProvince Maize (kg) Small grains (kg)

2014/2015 2015/2016 2016/2017 2014/2015 2015/2016 2016/2017

Manicaland 292.4 108.6 335.1 24.8 4.9 30.9

Mash Central 525.8 136.2 517.5 32.8 7.7 45.9

Mash East 367.0 124.1 378.7 15.1 2.9 23.7

Mash West 462.2 397.6 739.2 5.4 6.2 1.1

Mat North 142.8 48.1 240.5 127.1 57.1 88.1

Mat South 74.6 22.8 174.5 15.3 19.1 68.4

Midlands 292.7 132.3 522.9 10.1 11.4 29.0

Masvingo 136.4 42.3 356.7 14.7 21.9 86.1

National 293.5 126.5 480.9 29.5 16.4 42.2

• Nationally there was a 266% increase in average household cereal production, 280% increase in average household maize production and 157% increase in average

household small grains production from last season.

• The average household production was highest in Mashonaland West 739.2kg and the least in Matabeleland South with 174.5kg.

• Masvingo had the highest increase from 42.3kg to 356.7kg and Mashonaland West had the least from 397.6kg to 739.2kg.

• Considering the high household cereal production and findings from previous ZimVAC assessments which indicated that most households use improper facilities to store their

grain, there is need to foster good post harvest management to minimize potentially high post harvest losses. 64

Household Access to Irrigation

65

Proportion of Wards with Irrigation Schemes

• About 22.1% of the wards had irrigation schemes

• Of these, 55.4% of the irrigation schemes were functional, 22.0% partially functional and 22.6% were non-functional.

66

Reasons for Non- Functionality of Irrigation Schemes

• Equipment breakdown, the need for infield works habilitation and seasonality of water source, lack of capital and failure to afford inputs continue to be the main

challenges faced in most irrigation schemes.

20,6

13,5

9

8,1

8,1

7,2

6,3

5,4

4,9

4,5

3,1

3,1

1,8

1,3

0,9

0,9

0,9

0,4

13,8

14,111,8

2,9

4,7

10,2

2,9

4,7

4,7

11,2

2,5

4,1

10

1,20,6

0,6

0 5 10 15 20 25

Pumping unit broken down

In-field works need rehabilitation/maintenance

Lack of capital

Theft of produce

Infrastructure or equipment not yet installed or incomplete installation

Fencing broken down

Vandalism

Dam/weir silted

No electricity - transformer broken down or other fault

Seasonality of water source

Poor leadership

Dam/Weir not big enough

Dam wall washed away/collapsed

Cannot afford inputs

Unavailability of inputs at the market

ZINWA bills

Conflicts

Not yet commisioned

Proportion of wards (%)

Partially functional non- functional

67

Livestock Production

68

Cattle Ownership

• About 45% of rural households own cattle, a 9% increase from last year with 32% owning more than 2 beasts and 13% owning 1 or 2

beasts.

• The highest proportion of households owning cattle was in Masvingo (54%) followed by Matabeleland North and Midlands (53%).

• The lowest proportion of households with cattle was in Manicaland (28%).

• Matabeleland North (25%) had the highest proportion of households with more than 5 cattle.

72

58 59 61

4753

47 4655

64

11

14 13 10

1110 18 19

13

11

10

16 16 14

1715

18 1816

13

713 13 16

25 2217 18 16 12

0

10

20

30

40

50

60

70

80

90

100

Manicaland MashCentral

Mash East Mash West Mat North Mat South Midlands Masvingo National2017

National2016

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Zero One to two Three to five More than five

69

Cattle Draft Power Ownership

7564 67 67

60

77

5058

64 69

5

78 4

5

4

74

65

2129 25 29

36

19

43 3830 26

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National2017

National2016

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Zero One Two plus

• About 36% of rural households own draft cattle, 5 % more than the previous season. 6 % owned 1 draft animal, and 30% owned

2 or more.

• Highest proportion of households with draft cattle were in Midlands at 50%. 70

Cattle Herd Dynamics92,0

5,41,7 0,9

-29,9

-56,5

-8,6-5,1

-60,0

-40,0

-20,0

0,0

20,0

40,0

60,0

80,0

100,0

Births Purchases assistance other sold deaths slaughter stolen/lost

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

• Increases in the cattle herd during the period April 2016 to March 2017 were due to births (92%), purchases (5.4%) and

assistance (1.7%).

• Losses in cattle were due to deaths (56%) and sales (30%).

• Stolen or lost cattle contributed 5% of the total attrition. 71

Causes of Cattle Deaths

36

2317 13

25

51

29

58

33

55

66 7676

64

41

62

37

58

1 34

5 65

11

34 2 2 2 2 5 1 2

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Drought Diseases Predators Lack of water Slaughter for own consumption Drowning/Floods Other

• About 58% of total cattle deaths were due to diseases, followed by 33% due to drought.

• Mashonaland East and Mashonaland West reported high deaths due to diseases (76%).

72

Reasons for Selling Cattle

31,3

18,7

10,9

10,5

10,4

3,4

3,2

3,2

2,7

2,2

1,7

1,2

0 5 10 15 20 25 30 35

Purchase food

Pay education expenses

Pay medical expenses

No longer needed

Other household costs

Other

Pay debt

Pay for transport expenses

Business of selling livestock

social event

Funeral related expenses

Business investment

Proportion of Households (%)

• Most households sold cattle to purchase food (31.3%) and pay education expenses (18.7%)

• About 10.5% of the households sold cattle because they were no-longer needed, and had exhausted their usefulness.

73

Goats Ownership

• About 46% of households owned goats, an increase from last year’s 38%. Of these, 34% own 3 or more goats , while 13% own 1 to 2 goats.

• The highest proportion of households which owned livestock was in Matabeleland South (60%) and the lowest proportion was in Manicaland

(34%).

66 65 62 64

42 40

5343

5462

11 1213 11

126

15

19

13

11

15 14 16 13

21

19

2023 18

15

8 9 9 12

2535

13 15 1613

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National 2017 National 2016

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Zero One to two Three to five More than five

74

Goat Dynamics91,9

6,50,7 0,8

-25,0

-43,4

-27,1

-4,5

-60,0

-40,0

-20,0

0,0

20,0

40,0

60,0

80,0

100,0

Births Purchases assistance other sold deaths slaughter stolen/lost

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

• The increases in goats during the period April 2016 to March 2017 were due to births (91.9%), purchases (6.5%) and

assistance (0.7%).

• About 43.4% of the total attrition was due to deaths, 27.1% due to slaughter and 25% due to sales.

• Stolen or lost goats contributed 4.5% of the total attrition.

75

Reasons for Selling Goats

• Most households sold goats to purchase food (46%) and pay education expenses (22.1%).

46,1

22,1

7,2

7,1

5,9

3,2

3,1

1,7

0,8

0,8

0,7

0,6

0,3

0 5 10 15 20 25 30 35 40 45 50

Purchase food

Pay education expenses

Other household costs

No longer needed

Pay medical expenses

Pay for transport expenses

Pay debt

Other

Funeral related expenses

Business of selling livestock

Business investment

Pay/donate to social event

Grinding mill costs

Proportion of Households (%)

76

Causes of Goats Deaths

13,8 14,58,4 6,3 11,0

24,1

9,518,7 14,6

70,6 72,773,3 81,1

77,0 49,871,1

66,767,6

8,3 6,47,6

6,3 8,5

19,0 9,18,8 10,6

0,9 0,93,8 2,1

0,5 1,6 6,2 1,2 2,33,7 1,8 3,9 4,2 1,5 2,9 2,9 4,1 3,1

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

90,0

100,0

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Drought Diseases Predators Lack of water Slaughter for own consumption Drowning/Floods Other

• About 67.6% of deaths were due to diseases, 14.6% due to drought and 10.6% due to predators.

• Mashonaland West reported the highest deaths due to diseases (81.1%)

• Cases of drowning were recorded in most provinces with high incidences recorded in Midlands (6.2%).

77

Agricultural Produce Market Access

78

Location of Main Markets for Crops-Buying

7872

85 8780

58

913

5 59

14

8 10 3 3 7

13

3 3 4 31 30 1 1 3 0

0

10

20

30

40

50

60

70

80

90

100

maize grain maize meal Sorghum Pearl millet Sugarbeans Irish potatoes

Pro

po

rtio

n o

f w

ard

s (%

)

Same ward Neighboring ward Within District Within Province Outside Province Outside Zimbabwe

• Most households accessed food crops from within their wards.

• About 3% of the wards had households which accessed pearl millet from outside Zimbabwe and 1% which accessed maize

meal and sorghum outside Zimbabwe.79

Type of Market for Crops - Selling

76 81 82 82

66

1411 10 12

26

5 2 1 12 2 5 4 9

0

10

20

30

40

50

60

70

80

90

100

Maize grain Sorghum grain Pearl Millet Sugarbeans Irish Potatoes

Pro

po

rtio

n o

f w

ard

s (%

)

Other households in the area Private Traders GMB Auction Floors

Local Millers Distant Markets Contracting Companies Other Specify

• Most households sold crops to other households in the area and private traders.

• About 5% of wards had households which sold maize to the Grain Marketing Board (GMB) while 2% had sold sorghum to

GMB.80

Cattle: Type of Market

4235

5752

28 23

48

75

45

43 6225 35

4947

30

15

38

33 12 24 5

16

123

15 13 126

1710 11

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f w

ard

s (%

)

Other households in the area Private Traders Sale pens/Auctions Abattoirs

• About 45% of the wards sold cattle to other households in the area whilst 38%, 11% and 6% sold to private traders, abattoirs

and auctions respectively.

• Matabeleland South (24%) had the highest proportion of wards with households which sold cattle through auctions.

81

Goats: Type of Market

91

64

97 93 91

76

9297

87

9

37

1 76

15

63

111

811 1 2 2 3 1

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Other households in the area Private Traders Sale pens/Auctions Abattoirs

• Goats were mostly sold to other households in the area and private traders.

• Matabeleland South had the largest proportion of households that sold goats through auctions (8%).

82

Agricultural Commodity Prices

83

Cereal Availability by District as at May 2017

Maize Grain Availability Maize Meal Availability

• At the time of the assessment, maize meal was readily available in more districts compared to maize grain.

84

District Average Maize Grain Prices (USD/kg) as at May 2017

• The highest maize grain prices were reported

in Mangwe, Tsholotsho and Bulilima at above

USD 0.50/kg

• Lowest prices were reported in Gokwe South,

Gokwe North, Zvimba, Makonde, Mhondoro

and Mwenezi ranging between USD 0.17/kg

and USD 0.21/kg

• The National average maize grain price

dropped slightly from USD 0.40 in 2016 to

USD 0.38 this year.

85

District Average Maize Meal Prices (USD/kg) as at May 2017

• High maize meal prices ranged between USD 0.52 to USD

0.70/kg

• The National average maize meal price changed,

insignificantly, from USD 0.61 in 2016 to USD 0.60 this

year.

86

District Average Cattle Prices (USD) as at May 2017

• The highest Cattle prices were reported in

Hwange, Masvingo, Umzingwane, Umguza and

Mberengwa ranging between USD 390 and

USD 400.

• Lowest Average price was reported in Mbire

(USD 151).

• Nationally, the average cattle price appreciated

from USD 306 in 2016 to USD 320 this year.

87

District Average Goats Prices (USD) as at May 2017

• Highest goat prices were reported in

Umzingwane, Bubi, Bulilima, Umguza, Insiza and

Matobo ranging between USD 41 and USD 48.

• Lowest Average price was reported in Mbire at

USD 13

• The National average goat price increased

slightly from USD 29 in 2016 to USD 30 this year.

88

Incomes and Expenditure

89

Current Most Important Sources of Income

• The most important sources of income were casual labour and food crop production.

• Vegetable production and sales and remittances were amongst the most important sources of income for about 7.8% of the households.

90

20,920,5

7,87,8

7,36,5

5,94,7

3,53,2

2,01,9

1,61,4

1,11,00,9

0,0 5,0 10,0 15,0 20,0 25,0

Casual labourFood crop production/sales

Remittance from withinVegetables production/sales

Food assistanceLivestock production/sales

Formal salary/wagesRemittance from outside

Cash crop productionPetty trade

Mineral salesSkilled trade/artisan

PensionGathering natural products

Own businessGifts

Other

Proportion of households (%)

Average Household Income as of April 2017

• Nationally, the average household income for the month of April was USD74, about 20% higher than the same time last year, April 2016.

• Mashonaland West (USD 120) had the highest average monthly income while Midlands (USD 55) had the lowest average monthly income.

• The biggest increase in average household income was observed in Mashonaland West (88%) followed by Mashonaland Central (64%).

91

5955

78

64

50

81

56 5562

56

90

73

120

62

79

55 58

74

0

20

40

60

80

100

120

140

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

USD

2016 2017

Expenditure

92

Average Household Expenditure for April 2017

• The national average household expenditure increased from USD 49 to USD 52.

• Mashonaland West (USD 61), Matabeleland South (USD 60) and Mashonaland East (USD 60) had the highest average expenditure while Matabeleland

North (USD 42) and Masvingo (USD 43) had the lowest average expenditure.

93

4743

60

55

36

59

4644

4949

55

60 61

42

60

49

43

52

0

10

20

30

40

50

60

70

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

USD

2016 2017

Proportion of Food Expenditure

• Nationally, the proportion of food expenditure decreased from 59% to 54%. This pattern was also observed across all provinces.

• Matabeleland South had the highest proportion of food expenditure (59%) followed by Matabeleland North (57%).

• Mashonaland East had the least proportion of food expenditure (49%).

94

60 58 56 5558

65 6358 59

5255

4951

57 5955 53 54

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f to

tal e

xpen

dit

ure

(%

)

2016 2017

Average Household Expenditure For November 2016 to April 2017

• Average household expenditure for six months was highest for agriculture (USD 56.73) followed by education expenditure

(USD51.77). Taxes (USD2.06) had the lowest expenditure.

• Other expenditure included expenditure on clothes, social occasions, funerals and loan repayment.

95

56,73

51,77

27,14

8,53 7,67

2,38 2,06

0,00

10,00

20,00

30,00

40,00

50,00

60,00

Agriculture Education Other Health Business Remittance Taxes

USD

Decision Making on Household Expenditure

• Generally, decision making on household expenditure was mostly made by mothers except in Mashonaland West where fathers (39%) were the

main decision makers compared to mothers (28%).

28 31 2639

21 1930 26 30

4632 40

28

41 4935 43 32

2435 31 29 34 27 33 28

22

1 1 1 2 1 2 1 1

5

1 1 2 2 2 1 1 16

1 1 1 1 1 1 0 1 2

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

Father Mother Both father and mother Daughter Son Other relative

96

97

Livelihoods Based Coping Strategies

Introduction

98

• Households engage in various methods of coping when faced with food access challenges.

• Livelihood coping strategies are employed in order to increase food availability outside of their normal livelihoods.

• The livelihood coping strategies have been classified into three categories namely stress, crisis and emergency as

according to WFP Technical Guidance note 2015.

Category Coping Strategy

Stress • Borrowing money, spending savings, selling assets and more livestock than usual.

Crisis • Selling productive assets directly reduces future productivity, including human capital formation.

• Withdrawing children from school

• Reducing non food expenditure.

Emergency • Selling one's land affects future productivity, but is more difficult to reverse or more dramatic in

nature.

• Begging for food.

• Selling last breeding stock to buy food.

Categorisation of Livelihoods Coping Strategies

99

Households Engaging at Least one Livelihoods Based Coping Strategy

38

46 44

33

42

29

43

52

41

7 9 6 8 5 5 6 6 6

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

2016 2017

• The proportion of households that engaged at least one livelihoods based coping strategy in April decreased from 41% in 2016 to 6% in 2017.

This indicates an improved food access situation which led to less coping than last year where households had experienced two consecutive

poor food crop production seasons.

• Mashonaland Central and Mashonaland West had the highest proportion of households which engaged at least one livelihood coping strategy

during the month of April 2017.100

Reasons for not Engaging Livelihoods Coping Strategies in April 2017

• The households that did not engage any coping strategy in April 2017 did not do so mainly because it was not necessary (71%) whilst

28% did not have any assets to dispose of and 1% had already disposed of the assets or done the activity prior to April and could no

longer continue to do so.101

71

1

28

0

10

20

30

40

50

60

70

80

90

100

it wasn't necessary households had already sold those assetsor done this activity within the last 12

months and could not continue to do it

households did not have assets

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

Proportion of Households Engaging at Least One Coping Strategy in Each Category

10 117 8 11

6 7 8 97 83 5 7

2 4 3 57 6 4 39

3 4 4 5

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Stress Crisis Emergency

• The proportion of households which engaged at least one coping strategy in the stress category was 9% with 5% of the households engaging crisis

and emergency strategies each.

• Matabeleland North and Mashonaland Central engaged the most stress strategies whilst Mashonaland Central engaged the highest crisis strategies.

• Matabeleland North and Manicaland engaged the most emergency strategies.102

The Highest Severity of Livelihood Coping Engaged

• The proportion of households which did not engage any livelihood coping strategies was 87% followed by 5% of the household who engaged only

stress strategies

• About 3% engaged a combination of strategies but their most severe was crisis and 5% engaged in a combination but their most severe being

emergency strategies. 103

86 8489 86 84

92 88 88 87

4 55 6

4

45 6 53 5

3 53

1 3 2 37 6 4 3

93 4 4 5

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

Households not adopting coping strategies Stress coping strategies Crisis coping strategies Emergency coping strategies

ISALS/Mukando

104

Proportion of Households with a Member in an ISAL/Mukando Group

12

79

62 1 1

0

10

20

30

40

50

60

70

80

90

100

Father Mother Both fatherand mother

Daughter Son Otherrelative

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

86,7

13,3

0

10

20

30

40

50

60

70

80

90

100

NO YES

Pro

po

rtio

n o

f h

ou

seh

old

s (

%)

• About 13.3% of households had a member of their household who was in an ISAL/Mukando group.

• Of the households with members in ISAL groups, the majority of members were reported to be mothers (79%).105

ISAL/Mukando Groups by Province

• Manicaland had the highest proportion of households (18.3%) with a member in any ISAL/Mukando group.

• Mashonaland West had the lowest number (9.4%).

18,3

11,8 13,79,4

12,1 10,7

15,8 14,7

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

106

Types of Mukando/ISAL

• The largest proportion of ISAL groups reported were cash only groups (66%).

11

5

66

8 74

0

10

20

30

40

50

60

70

80

90

100

Groceries Food only Cash only Cash and Food Household utensils Productive Assets

Pro

po

rtio

n o

f gr

ou

ps

(%)

107

Household Consumption Patterns

108

Average Household Cereal Stocks as at 1 April 2017

Province Cereal Stocks 2016 (kgs)

Cereal Stocks 2017 (kgs)

Manicaland 53.2 145.7

Mashonaland Central 47.3 91.3

Mashonaland East 45.4 99.4

Mashonaland West 45.2 157.2

Matabeleland North 38.7 122.9

Matabeleland South 30.0 57.7

Midlands 39.0 101.9

Masvingo 49.5 108.0

National 43.2 109.6

• Average household cereal stocks were about 109.6kgs as at 1 April 2017.

• Mashonaland West had the highest average cereal stocks (157.2kgs), Matabeleland South had the least (57.7kgs).

• Generally, this year households had more stocks as compared to the same time the previous year. 109

Household Consumption Coping Strategies

28

22

19

33

3028

25

14

25

19

29

24

27

33

18

27

35

27

1617

13

17

1210

18

14 15

0

5

10

15

20

25

30

35

40

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Co

pin

g St

rate

gy In

dex

2015 2016 2017

• Coping Strategy Index (CSI) is an indicator used to compare the hardship faced by households by measuring the frequency and severity of the

behaviours they engage in when faced with food shortages.

• The (CSI) decreased greatly from 27 in 2016 to 15 in 2017. This shows improved food access from 2016 which is partly attributable to the emergency

food assistance by Government and its partners as well as the improved main harvest.

• All provinces showed an improvement in the consumption coping strategies employed from the extreme methods adopted last year to the less severe

and less frequent coping habits employed this year.110

The Food Consumption Score• The Household Food Consumption Score (FCS) is a food consumption indicator that is used as a proxy for household food security. Food consumption

indicators are designed to reflect the quantity and quality of people’s diet.

• The FCS is a measure of dietary diversity, food frequency and the relative nutritional importance of the food consumed. A high food consumption

score increases the possibility that a household achieves nutrient adequacy.

Food Consumption Score Groups

Score Description

Poor 0-21 An expected consumption of staple 7 days, vegetables 5-6 days, sugar 3-4 days, oil/fat 1 day a week, while animal proteins are totally absent

Borderline 21.5-35 An expected consumption of staple 7 days, vegetables 6-7 days, sugar 3-4 days, oil/fat 3 days, meat/fish/egg/pulses 1-2 days a week, while dairy products are totally absent

Acceptable >35 As defined for the borderline group with more number of days a week eating meat, fish, egg, oil, and complemented by other foods such as pulses, fruits, milk

111

Food Consumption Categories

• There has been a decrease in the proportion of households which are consuming an acceptable diet from 63% in 2015 to

55% in 2017.

• However, the proportion of households consuming a poor diet has increased from 8% in 2015 to 16% in 2017.

8

29

63

12

33

54

16

29

55

0

10

20

30

40

50

60

70

80

90

100

Poor Borderline Acceptable

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

2015 2016 2017

112

Food Consumption Categories by Province

2016 FCS 2017 FCS

• The proportion of households with acceptable food consumption scores improved from 54% in 2016 to 55% in 2017, those with

borderline consumption decreased from 33% to 29% and those with poor consumption patterns increased from 12% to 16%.

• Matabeleland North (25%) had the highest proportion of households consuming poor diets and had worsened from last year

where 19% had poor food consumption patterns.

18 1812

1725

14 14 13 16

31 33

2929

29

27 29 2729

51 4959

5446

59 58 6055

0

10

20

30

40

50

60

70

80

90

100

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Poor Borderline Acceptable

10 11 9 1119

12 13 13 12

36 3732 31

37

34 31 30 33

54 5259 58

4454 56 56 54

0

10

20

30

40

50

60

70

80

90

100

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

Poor Borderline Acceptable

113

Proportion of Households Consuming Iron-rich Foods

4049

40 36

52 4943 42 44

5246

5152

41 4450 50 48

8 5 9 12 7 6 7 7 8

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Never consumed Consumed sometimes Consumed at least daily

• The proportion of households consuming iron rich foods daily remained below 10% across all provinces except in Mashonaland West (12%).

• Matabeleland North had the highest proportion of households that were not consuming iron rich foods 7 days prior to the assessment (52%).

• As Iron deficiency continues to be of public health concern, nutrition sensitive livelihoods programming is recommended.

114

Proportion of Households Consuming Protein-rich Foods

15 1813 15 19 16 13 12 15

4848

46 4342

37 46 4344

37 3441 41 39

4741 45 41

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Never consumed Consumed sometimes Consumed at least daily

• The proportion of households that consumed protein rich foods at least daily in the 7 days prior to the survey was 41% whilst 44% consumed between 1 to

6 days and 15% had not consumed at all.

• Matabeleland South had the highest proportion of households which consumed protein rich foods at least daily (47%).115

Proportion of Households Consuming Vitamin A-Rich Foods

9 6 4 616 12

7 38

2324

2225

3230

26

19

25

68 71 7468

5258

67

79

67

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Never consumed Consumed sometimes Consumed at least daily

• About 67% of the households consumed Vitamin A rich foods at least daily, 25% consumed sometimes and 8% never consumed during the 7 days prior to

the survey. 116

Household Dietary Diversity Score

• The Dietary Diversity indicator is the number of different food groups consumed over a given reference period of time. It gives an estimation of the quality of the diet. The HouseholdDietary Diversity Score (HDDS) shows the number of food groups consumed by households out of a total of 12 food groups and is used as a proxy for food access. Even amonghouseholds that satisfy calorie requirements, those which consume a non-diversified, unbalanced and unhealthy diet can be classified as food insecure.

• Nationally, the HDDS was 5.8, a slight improvement from 2016 (5.6).• All provinces except for Mashonaland Central had improved HDDS from 2016.• On average, households consumed about 6 out of the 12 food groups within the seven day recall period.• Mashonaland East and Manicaland consumed the highest number of food groups (6.3 and 6.1 respectively) while Matabeleland North had the lowest score (5.4) This trend is similar

to that of 2016.

5,8

5,6

6,2

5,6

4,8

5,5 5,55,4

5,6

6,1

5,5

6,3

5,8

5,4

5,8 5,9 5,8 5,8

4

4,5

5

5,5

6

6,5

7

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

HD

DS

2016 2017

117

Average Number of Days Households Consumed Food from the Various Food Groups per Week

7

6

6

5

3

2

2

1

1

0 1 2 3 4 5 6 7

Cereals

Condiments

Oil

Sugar

Vegetables

Milk

Pulses

Fruits

Meat

Number of Days

Foo

d G

rou

ps

• The majority of households consumed mostly cereals while meat was consumed the least.

• This pattern is consistent with what has been observed in previous ZimVAC RLAs. 118

Household Hunger Score

91 86,993,8

83,190,9 90,7 91,2 92,1 90

9 13,16,2

16,99,1 9,3 8,8 7,9 10

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

Little to no hunger Moderate to severe hunger

• The Household Hunger Score is a household food deprivation scale which focuses on the food quantity dimension of food access.

• Most households in the rural communities were experiencing little to no hunger (90%) whilst 10% experienced moderate to severe hunger.

• Mashonaland West had the highest proportion of households facing moderate to severe hunger (16.9%) whilst Mashonaland East had the lowest

proportion (6.2%).119

Proportion of Households Using Iodized Salt by Province

91,2

72,8

93,290

81,777,9

81,3

90,3

84,8

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

• Nationally, 84.8% of households used iodised salt. This is above the 80% threshold for universal salt iodisation.

• Mashonaland Central (72.8%) and Matabeleland South (77.9%) had the least proportion of households that used iodised salt.120

Resilience

121

Introduction Why Resilience in Zimbabwe?

• Persistent food insecurity, stunting levels and poverty levels in the country remain topical issues despite huge investments made by

Government and its development partners to address them.

• This led the Government of Zimbabwe and its development partners to spearhead the development of the Resilience Strategic

Framework for Zimbabwe in 2015.

• The framework lays down what resilience means for Zimbabwe, provides a conceptual framework and key principles to be used in

resilience programming.

Definition of Terms

Resilience: The ability of at risk individuals, households, communities and systems to anticipate, cushion, adapt, bounce back better and

move on from the effects of shocks and hazards in a manner that protects livelihoods and recovery gains and supports sustainable

transformation’. (Zimbabwe Resilience Strategic Framework 2015).

Hazard: A process, phenomenon or human activity that may cause loss of life, injury or other health impacts, property damage, social and

economic disruption or environmental degradation (UNISDR, 2007). Hazards may be natural or anthropogenic in origin. Natural hazards are

predominantly associated with natural processes and phenomena. Anthropogenic hazards, or human-induced hazards, are induced by human

activities.

122

Resilience Conceptual Framework

Resilience Pathway

• Food Security• Adequate

Nutrition• Environmental

security

Vulnerability pathway

• Food Insecurity• Malnutrition• Environmental

Degradation

123

Shocks

Tsholotsho Siphepha Flood Disaster, Source: DCP

124

Proportions of Households which Reported Different Shocks

Between April 2016 and March 2017

• Cash shortages (46.9%), water logging (42.7%), drought (32.3%) and crop pests (29.9%) were reported as shocks which affected households

between April 2016 and March 2017.

• Some households experienced localised shocks which included flooding (9.6%), human wildlife conflict (4.8%) and veld fires (0.9%).

125

46,942,7

32,3 29,9

12,6 12,4 9,6 9,3 8,6 5,2 4,9 4,8 3,6 3,4 3,4 3 2,9 2,4 0,90

10

20

30

40

50

60

70

80

90

100

Severity of Impact of Shocks Experienced Between April 2016 and March 2017

• A proportion of households who experienced shocks reported severe impact of cash shortages (64%), water logging (59%) , impact of the

2015- 2016 El Nino induced drought (69%) and crop pests (50%).

• Less commonly experienced shocks which had severe impact include human wildlife conflict (62%), floods (59%), death of main income

earner (76%) veld fires (70%) and loss of employment by breadwinner (72%).

5 6 6 9 11 7 9 812

8 9 10 9 613 9

4 8 11

3136

25

4149

36 3240 37

28

43

28

48

2232

42

2029

19

6459

69

5041

57 5952 51

64

48

62

43

72

5549

76

6370

0

10

20

30

40

50

60

70

80

90

100

Minor Moderate Severe

126

Households’ Preparedness Levels for Anticipated Hazards In The Next 12 Months

• About 40% of the sampled households who indicated that they experienced shocks and hazards in the last 12 months reported that they will

be unable to cope with similar shocks and stressors if they recur in the next 12 months,

• At least 45% of the households reported that they will be able to cope but with difficulties.

• Only 16% indicated that they will be able to cope without difficulties.

40

45

16

Unable to cope Able to cope with difficulties Able to cope without difficulties

127

Households’ Perceived Ability to Cope with Future Hazards

• Without external assistance, the majority of households reported that they will either be unable to cope or may cope

with difficulties if they are to experience either drought, floods, livestock diseases, crop pests or crop diseases in the

next season.

4741

38

4642 43

39

23

1116

24

31

0

10

20

30

40

50

60

70

80

90

100

Drought Crop pests and disease outbreaks Livestock disease outbreak Floods

Unable to cope Able to cope with difficulties Able to cope without difficulties

Pro

po

rtio

n o

f h

ou

seh

old

s (

%)

128

Resilience Measurement

• Customised KPI4 Methodology –Measures the number of people/communities whose resilience has been improved as a result of

humanitarian and development support.

• The methodology was developed by DfID in one of its projects- Building Resilience and Adaptation to Climate Extremes and

Disasters (BRACED) in Ethiopia and Nepal.

• The methodology was customised to suit the Zimbabwean context and it taps from the existing resilience indicators in ZimVACsurveys to form a resilience score based on;

1. Livelihoods and assets based Coping Strategy Index score

2. Food Consumption Score

3. Average number of income sources per household

4. Average monthly household income per household

5. Perceived ability to cope with shocks and stresses

6. Households Hunger Scale (HHS)

129

Proportions of Households by Vulnerability and Resilient Pathways Categories

• The majority of the households were at the wellness threshold (60%), 38% were in the resilient category while 2% were in the

vulnerability trap.

4 1 0 1 3 0 2 1 2

6662

50

62

70

54

6359 60

30

37

50

37

28

45

3540 38

0

10

20

30

40

50

60

70

80

90

100

Manicaland MashonalandCentral

MashonalandEast

MashonalandWest

MatabelelandNorth

MatabelelandSouth

Midlands Masvingo National

Vulnerability Wellness Threshold Resilient

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

130

Household Food Security Status Projections

To estimate the rural population that is likely to be food insecure in the 2017/18 consumption year,

their geographic distribution and the severity of their food insecurity

131

Food Security Analytical Framework

132

• Food security exists when all people at all times, have physical, social and economic access to food which is safe and consumed in

sufficient quantity and quality to meet their dietary needs and food preferences and it is supported by an environment of

adequate sanitation, health services and care allowing for a healthy and active life (Food and Nutrition Security Policy, 2012).

• The four dimensions of food security include:

• Availability of food

• Access to food

• The safe and healthy utilization of food

• The stability of food availability, access and utilization

• Household food security status was determined by measuring a household’s potential access to enough food (from various

livelihood options available to the household) to give each member a minimum of 2100 kilocalories per day in the consumption

period 1 April 2017 to 31 March 2018.

Food Security Analytical Framework• Each of the surveyed households’ potential food access was computed by estimating the household's likely disposable income (both cash and non cash) in

the 2017/18 consumption year from the following possible income sources;

• cereal stocks from the previous season;

• own food crop production from the 2016/17 agricultural season;

• potential income from own cash crop production;

• potential income from livestock ;

• Potential income from casual labour and remittances; and

• Income from other sources such as gifts, pensions, gardening and formal and informal employment.

• Total energy that could be acquired by the household from the cheapest available energy source (maize was used in this assessment) using its potential

disposable income was then computed and compared to the household’s minimum energy requirements.

• When the potential energy a household could acquire was greater than its minimum energy requirements, the household was deemed to be food secure.

When the converse was true, the household was defined as food insecure.

• The severity of household food insecurity was computed by the margin with which its potential energy access is below its minimum energy requirements.133

Main Assumptions Used in the Food Security Analytical Framework

134

• Households’ purchasing power will remain relatively stable from April 2017 through the end of March 2018, i.e. average household income levels are

likely to track households’ cost of living. This assumption is made on the premise that year-on-year inflation will remain stable throughout the

consumption year.

• The national average livestock to maize terms of trade will remain relatively stable throughout the 2017/18 consumption year.

• Staple cereals in the form of maize, small grains (sorghum and millets) or mealie meal will be available on the market for cereal deficit households with

the means to purchase to do so throughout the consumption year. This assumption is based on the Government maintaining the liberalised maize trade

regime.

• National cotton, tobacco and soya bean producer prices will average out at USD 0.36/kg, USD 2.75/kg and USD 0.50/kg respectively for the whole

2017/18 marketing season.

Food Insecurity Progression by Quarter

• Rural food insecurity for the period April to June 2017 was estimated at 1% and is projected to reach 11% during the peak hunger

period (January to March 2018).

• As expected, there is a progressive increase in the proportion of food insecure households as the consumption year progresses

toward the peak hunger period. 135

1

3

7

11

0

2

4

6

8

10

12

Apr-Jun Jul-Sept Oct-Dec Jan-Mar

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

Trend In Food Security Progression by Quarter

• The 2017/18 consumption year food insecurity prevalence is 11% and is lower than that for the 2016/17 consumption year during the

peak hunger period.

136

2

5

10

30

6

23

35

42

13

7

11

0

5

10

15

20

25

30

35

40

45

Apr-Jun Jul-Sept Oct-Dec Jan-Mar

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

2015 2016 2017

Food Insecure Rural Population by Quarter

• About 1.1 million rural people are estimated to be food insecure during the January – March peak hunger season.

137

92 988

304 175

647 630

1 052 768

-

200 000

400 000

600 000

800 000

1 000 000

1 200 000

Apr-Jun Jul-Sept Oct-Dec Jan-Mar

Po

pu

lati

on

Food Insecure Population by Quarter

138

• At least 1.1 million are projected to be food insecure during the peak hunger period.

150 888

462 096

924 192

2 829 159

986 452

2 199 223

3 390 224

4 071 233

92 988 304 175

647 630

1 052 768

0

500 000

1 000 000

1 500 000

2 000 000

2 500 000

3 000 000

3 500 000

4 000 000

4 500 000

Apr-Jun Jul-Sept Oct-Dec Jan-Mar

Po

pu

lati

on

2015 2016 2017

Food Insecurity Progression by Income Source

• All other potential sources of cereals (stocks, food and cash crops, casual labour and remittances and livestock) except incomes rendered

approximately 49% of rural households to be food secure.

• Adding all other incomes, the food insecurity prevalence is projected to be 11% in the 2017/18 consumption year.139

96

64 6257

51

11

0

10

20

30

40

50

60

70

80

90

100

Stocks Plus food crops Plus cash crops Plus cereals from casuallabour and remittances

Plus livestock Plus all other incomes

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

Trend in Food Insecurity Progression by Income Source

140

• Approximately 4% of the households had cereal stocks as at 1 April 2017 to last them the entire 2017/18 consumption year

compared to about 2% at the same time in 2016.

96

81 7871 68

30

98

87 85 82

73

42

96

64 6257

51

11

0

20

40

60

80

100

120

Stocks Plus food crops Plus cash crops Plus cereals fromcasual labour and

remittances

Plus livestock Plus all other incomes

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

2015 2016 2017

Food Insecurity by Quarter by Province

141

• A general increase in the proportion of food insecure households is projected across all provinces.

• Matabeleland North (18%), Matabeleland South (16%), Masvingo and Midlands (12%) are projected to have the highest proportions of

food insecure households at peak hunger period.

• Mashonaland East (7%) and Mashonaland West (8%) are projected to have the least proportions of food insecure households.

1 10 1

2 1 1 1 1

3 3

1

3

76

42

3

6 6

45

1210

7 7 7

11 10

78

18

16

12 1211

0

2

4

6

8

10

12

14

16

18

20

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

Apr-Jun Jul-Sept Oct-Dec Jan-Mar

Food Insecure Population by Quarter by Province

• Masvingo (176,956),Manicaland (175,285), and Midlands (156,936) are projected to have the highest number of people estimated to be

food insecure during the peak period.

142

13 206 11 434 5 283 8 486 13 764 9 455

17 246 14 113

50 425

33 540

15 848

33 002

48 174 37 347

50 013 35 825

103 250

77 753

52 074 62 233

85 231

67 603

97 438 102 048

175 285

121 203

89 808 98 064

132 876

101 641

156 936

176 956

-

20 000

40 000

60 000

80 000

100 000

120 000

140 000

160 000

180 000

200 000

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo

Po

pu

lati

on

Apr-Jun Jul-Sept Oct-Dec Jan-Mar

Districts with the Highest Food Insecurity Levels

143

District Jan - Mar 2017 Jan - Mar 2018 District Jan - Mar 2017 Jan - Mar 2018

Buhera 70 27 Goromonzi 25 19

Mangwe 45 27 Umzingwane 54 19

Binga 79 26 Chivi 57 18

Bulilima 52 25 Mutare 48 18

Nkayi 44 25 Bindura 41 17

Mbire 53 23 Insiza 42 15

Tsholotsho 54 21 Kariba 64 15

Gokwe North 49 21 Chirumanzu 65 15

Mwenezi 68 21 Umguza 75 14

Lupane 42 20 Zvishavane 68 14

Districts with the Lowest Food Insecurity Levels

144

District Jan-Mar 2017 Jan-Mar 2018 District Jan-Mar 2017 Jan-Mar 2018

Hurungwe 11 1 Masvingo 35 5

Marondera 14 2 Gwanda 40 5

Murewa 30 2 Hwedza 25 5

Kwekwe 30 3 Mazowe 20 5

Makonde 19 3 Chegutu 27 5

Mutasa 45 3 Gokwe South 41 5

Guruve 31 3 Shamva 34 6

Mutoko 53 4 Chipinge 41 6

Seke 20 4 Chikomba 45 6

Chimanimani 39 4 Gutu 44 7

145

Food Insecure Population During the Peak Hunger Period by Province

146

District Food Insecure Proportion During the Peak Hunger Period

147

Food Insecure Population by District

Livelihood Zone Food Insecure Proportion During the Peak Hunger Period

148

Nutrition

149

Feeding Practices in Children 6 – 59 Months

150

Feeding Practices in Children 6-59 Months

• Good feeding practices of children are among the most important determinants of their health, growth and development.

• Good feeding will prevent malnutrition and early growth retardation.

• At 6 months of age, children should start to receive nutritionally adequate and safe solid, semisolid and soft foods while breastfeeding

continues for up to two years of age or beyond.

• The solids, semi solid, soft foods should be from at least 4 out of 7 food groups (grains, roots and tubers, legumes and nuts, dairy products,

meat and fish, eggs, vitamin-A rich fruits and vegetables , other fruits and vegetables).

• Foods of animal origins such as meat, fish and milk are an important source of Iron and Vitamin A. While vegetables and fruits such as

pumpkin, carrots, squash, yellow/orange sweet potatoes dark green leafy vegetables; ripe mangoes, ripe paw-paws are vital sources of

vitamin A.

• Iron plays an important role in the prevention of anaemia while vitamin A prevents nutritional blindness, significantly reduces the severity

of illnesses and even death from such common childhood infections such as diarrhoea and measles.

151

Definitions of Key Child Feeding Terms

• Minimum Dietary Diversity (MDD): A child is considered consuming a diet of minimum dietary diversity if the diet is made up from 4 or more of

the 7 food groups below:

✓ grains, roots and tubers

✓ legumes and nuts

✓ dairy products (milk, yogurt, cheese)

✓ flesh foods (meat, fish, poultry and liver/organ meats)

✓ eggs

✓ vitamin A rich fruits and vegetables

✓ other fruits and vegetables

• Minimum Meal Frequency (MMF) refers to the minimum number of times solid, semi-solid, or soft foods or milk feeds are consumed by children of

a specific age group. The minimum recommended number of times (frequency) depends on whether a child 6-23 months of age is breastfed or non-

breastfed. The recommended minimum meal frequency for the specific age groups is given below:

✓ 2 times for breastfed infants 6–8 months

✓ 3 times for breastfed children 9–23 months

✓ 4 times for non-breastfed children 6–23 months

• Minimum Acceptable Diet (MAD) measures the quality of diets consumed by children aged 6-23 months by combining both MDD and MMF.152

Minimum Dietary Diversity Children 6-23months

• The proportion of children that consumed diets that met the minimum dietary diversity remained generally very low across all the

provinces of the country.

• Nationally, 13% of children aged 6 to 23 months consumed a minimum dietary diversity. This is lower than 18% reported in 2015.

15

23 26

1510

1519

1518

1218

21

10 10 10 128

13

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f c

hild

ren

(%)

2015 2017

153

Proportion of children 6-59 Consuming Iron-Rich Foods

• Compared to 2016, there has been a general decrease in the proportion of children consuming iron-rich foods across all provinces.

• About 29.1% of children aged 6-59 months consumed iron-rich foods 24 hours prior to the survey.

• Matabeleland North and Matabeleland South (23%) had the lowest proportion of children 6-59 months who consumed iron-rich foods.

34,2

28,0

36,239,9

29,6

23,2

30,6 30,831,931,0 28,9

34,935,5

23,0 23,024,9

30,7 29,1

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Masvingo Mat North Mat South Midlands National

Pro

po

rtio

n o

f C

hild

ren

(%

)

2016 2017

Proportion of Children 6-59 Consuming Vitamin A-Rich Foods

• Nationally, 93% of children 6-59months consumed Vitamin A-rich foods 24-hour prior to the survey and this is higher than what was

observed last year(90%).

• The lowest proportion of children 6-59months who consumed a vitamin A rich foods was in Matabeleland North and South (90%).

91

67

92 93 9387

9194

9095 95 96

93 91 90 9094 93

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Masvingo Mat North Mat South Midlands National

Pro

po

rtio

n o

f C

hild

ren

(%

)

2016 2017

Minimum Acceptable Diet for Children 6-23 Months

• The proportion of children 6-23 months consuming a minimum acceptable diet was very low across all the provinces since 2015

• Nationally, 8.6% received a minimum acceptable diet 24 hours prior to the survey.

• Mashonaland West had the lowest proportion at 4.8%.

6,810,6 12,9

6,9 6 8,4 7,5 6 8,311,3 8,9 10,6

4,810,0

6,3 7,9 9,5 8,6

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f ch

ildre

n(%

)

2015 2017

156

Minimum Dietary Diversity for Women of Child Bearing Age

• Women of child bearing age (WCBA) (15-49 years) are often nutritionally vulnerable because of the physiological demands of

pregnancy and lactation.

• Requirements for most nutrients are higher for pregnant and lactating women than for adult men.

• Outside of pregnancy and lactation, other than for iron women require a more nutrient-dense diet to meet their increased

micronutrient needs.

• Insufficient nutrient intakes before and during pregnancy and lactation can affect both women and their infants.

• The Minimum Dietary Diversity for WCBA (MDD-W) indicator is a food group diversity indicator that has been shown to reflect

one key dimension of diet quality, that is micronutrient adequacy.

157

Dietary Diversity for Women 15-49 years

Minimum Dietary Diversity (MDD-W) Dietary Diversity

42 4350

36 31 3038

44 40

58 5750

64 69 7062

56 60

0

10

20

30

40

50

60

70

80

90

100

Pro

po

rtio

n o

f w

om

en

(%)

Consumed 5 food groups & above Consumed less than 5 food groups

4,34,5 4,6

4,13,8 3,8

4,14,4 4,2

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

4,0

4,5

5,0

Ave

rage

Average dietary diversity for women

• Nationally 40% of women of childbearing age achieved a minimum dietary diversity (MDD) and therefore more likely to have adequate

micronutrient intakes.

• Matabeleland South and Matabeleland North had the least proportion of women whose diets met MDD.

• The average dietary diversity for women of child bearing age was 4 across all provinces.158

Average Number ofFood Groups Eaten 24hrs Prior to the Survey by WCBA

16 148

2024 26

16 15 17

2220

18

2423

23

21 21 21

2123

24

1922 21

2519

22

42 4350

3631 30

3844

40

0

10

20

30

40

50

60

70

80

90

100

Manicaland MashCentral Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f w

om

en

(%

)

1-2 Food Groups 3 food groups 4 food groups 5 or more food groups

• Nationally 17% of women consumed foods from 1-2 food groups indicating that they are not likely to receive adequate micronutrients

from their diets. 159

Community Health Services

• One strategy for stunting reduction is to scale up high impact interventions which include community health services

• Provision of individual Community Infant and Young Child Feeding (cIYCF) at community level has been shown to greatly

improve caring and feeding practices.

• Continued support within the first 1000 days, a window of opportunity for addressing stunting, at community level has been

proven to have positive health outcomes for the mother and child dyad

160

Proportion of Pregnant and Lactating Women Visited by a Village Health Worker

11,5 8,95,9

9 8,4 7,5 9,1 7,1 8,3

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f w

om

en (

%)

• Nationally, the proportion of pregnant and lactating women visited by a Village Health Worker was 8.3%.

• Manicaland (11.5%) had the highest proportion of pregnant and lactating women visited by a Village Health Worker whilst

Mashonaland East had the lowest (5.9%).

161

Community Health Services Received by Pregnant and Lactating Women

• Out of the 8.3% of women that received community health services from a Village Health Worker, 36% received general care services

and 24% received antenatal care.

37

18

35

14 15

2622

2724

18

26

10

28

20 21

12 10

1916

13

19

12

20 1917

2317

4 5 3 5 4 38

3 5

25

3832

42 41

32

4137 36

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f w

om

en (

%)

Ante Natal Care Maternal Nutrition Post Natal Care Family Planning General Care

162

Proportion of Households with Children Under 2 Years Visited by Village Health Worker

21

14

8

16 14 13 13 11 13

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f h

ou

seh

old

s (

%)

• Nationally, only 13% of households with children under 2 years of age were visited by a Village Health Worker.

• Mashonaland East (8%) had the least proportion.

163

Community Health Services Received by Children Under 2 Years

• Of the 13% of households with children under 2 years of age visited by Village Health Workers, 45% received growth monitoring services.

164

39

1620

13 14

2822

2723

39

49 4843

54

4236

5045

2 1 1 1 1 1 13 4 412

37 4 5

18

30 2832

28 3034

18

27

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f h

ou

seh

old

s (%

)

cIYCF counselling Growth Monitorng Other Vitamin A Supplementation Health Counselling

165

Water, Sanitation and Hygiene (WASH)

166

167

Open Defecation Defecation in fields, forests, bushes, bodies of water or other open spaces or disposal of human faeces

with solid waste.

Unimproved sanitation facilities Unimproved sanitation facilities: Facilities that do not ensure hygienic separation of human excreta from

human contact. Unimproved facilities include pit latrines without a slab or platform, hanging latrines and

bucket latrines.

Improved sanitation facilities Improved sanitation facilities: Facilities that ensure hygienic separation of human excreta from human

contact. They include flush or pour flush toilet/latrine, Blair ventilated improved pit (BVIP), pit latrine with

slab and upgradeable Blair latrine.

Improved water sources Improved” drinking water sources are further defined by the quality of the water they produce, and are

protected from fecal contamination by the nature of their construction or through an intervention to

protect from outside contamination. Such sources include: piped water into dwelling, plot, or yard; public

tap/standpipe; tube well/borehole; protected dug well; protected spring; or rainwater collection

Unimproved water sources Unprotected dug well, unprotected spring, cart with small tank/drum, tanker truck, surface water (river,

dam, lake, pond, stream, canal, irrigation channel), and bottled water are not considered improved

sources.

Categories of Sanitation

Households’ Water Sources and Sanitation Facilities

• Nationally there was an improvement in access to safe drinking water and sanitation.

• Open defecation decreased from 37% to 30%.

168

71

47

37

73

68

30

0

10

20

30

40

50

60

70

80

Improved Water Source Improved Sanitation Open Defaecation

Pro

po

rtio

n o

f H

ou

seh

old

s (

%)

2016 2017

Access to Improved Water

• The national average for access to improved water sources increased marginally from 71% to 73% in 2016.

• There was a general increase in all provinces, with the exception of Mashonaland West, Matabeleland North and Masvingo.

7074 72

69

81

72

6569 71

77 76 79

65

78

72 71

65

73

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

2016 2017

169

Access to Improved Water Sources by District

• Districts such as Gokwe North, Hurungwe, Binga

and Chiredzi had the lowest proportion of

households with access to improved water

sources ranging from 36.4-50%

170

Households which Changed Main Water Source

• Nationally 10% of the households changed their main source of water during the 3 months preceding the survey.

88 90 91 9188

90 90 89 90

12 10 9 912

10 10 11 10

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

No Yes

171

Reasons for Change in Main Drinking Water Source

• Of the households that changed their main drinking water source, 42% of them did so as a result of the availability of alternative water sources

being closer by due to the good rains.

• Masvingo and Matabeleland South had the highest proportion of households accessing water from a nearer source at 53% and 51%

respectively.

45

31

44 42 4051

35

5342

19

8

17 17

10

18

16

13

15

18

43

16 21 37

19

30

1726

105 12

102 2

57 7

44

47

36

63 4

510 7 3

8 49 6 6

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Availability of alternative water sources close by Main water source has dried up Main water source has broken down /not functional

Main water source silted/polluted Main water source flooded Other (specify)

172

Distance Travelled to Main Water Source

5567

49 5365

73

5265

52 3932

42 4050

3547 46

55

26

22

3033

20

18

20

22

32 38

33

3428

30

35

31 29

28

1811

20 15 158

2214

3623

3424

3220

3023 25

17

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2016 2017 2016 2017 2016 2017 2016 2017 2016 2017 2016 2017 2016 2017 2016 2017 2016 2017

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Less than 500m More than 500m but less than 1 km 1km and above

• According to Sphere Standards, the maximum distance that any household should travel to the nearest safe water point is 500m.

• The proportion of households travelling more than 1km to fetch water decreased from 25% in 2016 to 17% in 2017.

• Nationally, 55% of households travelled less than 500m to the nearest water source, whilst 17% travelled more than 1km.

• Matabeleland South, Matabeleland North and Masvingo had the highest proportion of households that travelled more than 1 km at 24% and

23% respectively.

173

Household Member Fetching Water

• Adult women were the predominant household members reported to be fetching water. This scenario remained constant regardless of the

distance travelled to the water source.

82

95

2 2 0

78

116

3 31

74

15

5 4 2 1

79

105

3 2 00

10

20

30

40

50

60

70

80

90

100

Adult woman [18 yearsand above]

Adult man [18 years andabove]

Female child (under 18years)

Male child (under 18years)

Both Male and FemaleChild (under 18 years)

Other (specify)

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Less than 500m More than 500m but less than 1 km 1km and above National

174

Proportion of Households Treating their Water

• The practice of water treatment remains generally low across all rural provinces.

• Nationally, 12% of households that used water from unimproved sources did not treat their drinking water. This is of concern as it exposes

households to waterborne diseases, a situation which is exacerbated when there is excess rainfall and flooding.

6 57

5 4 4 4 4 5

12 1214

11 12 1410 11 12

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (

%)

Improved Water Source Unimproved Water Source

175

Household Sanitation Facilities

• The proportion of households which accessed improved sanitation facilities was 61%.

• Matabeleland North Province had the lowest proportion of households with access to improved sanitation (42%).

• Open defecation was practiced by 30% of households nationally, while Matabeleland North had the highest (55%.

7064

74

5442

6655 57 61

1718

8

8

3

3

9 69

13 18 18

38

55

3236 37

30

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

Improved Sanitation Unimproved Sanitation Open defecation

176

Prevalence of Open Defecation

• Most districts in Matabeleland North province

recorded the highest prevalence of open

defecation ranging from 56.1-75%.

• Most districts in Manicaland recorded the lowest

prevalence of open defecation ranging between

0.5-16%.

177

Households with Handwashing Facilities

• At least 16% of the households with sanitation facilities had handwashing facilities . Of these, 40% had water available at the handwashing facility,

25% had soap whilst 3% had both water and soap available at the handwashing facility.

• Mashonaland Central had the highest proportion of households without handwashing facilities (93%) whilst Matabeleland North and South had the

highest proportion of households with handwashing facilities where both water and soap or detergents were available.

13

7 9

16

3328

14

2116

0

10

20

30

40

50

60

70

80

90

100

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f H

ou

seh

old

s (%

)

178

Frequency of Handwashing at Critical Times

• The critical times most observed by households for handwashing were after using the toilet and before or eating (84%) and before handling food (63%).

• The least observed critical time was after assisting the sick (3%).

179

84

63

10

84

3 10

10

20

30

40

50

60

70

80

90

After using the toilet Before handling food After changingchildren's

nappies/diapers

Before/after eating After assisting the sick Other

Pro

po

rtio

n (

%)

Child Nutrition Status

180

Definition of Terms• Measurements of weight, height and age of a child are converted to nutritional indices to indicate the nutrition status of a child.

• Any of the two measurements are combined to form indices as follows: Weight for height, Weight for age, Height for age

• Weight for height is a measure of thinness or fatness which is sensitive to sudden change in energy balance.

• Weight for height index of between 2 and 3 standard deviation below the mean is called Moderate Acute Malnutrition (MAM) /Wasting.

• A child with weight for height of more than 3 standard deviation below the mean and or has oedema is classified as Severe Acute Malnourished (SAM).

• MAM or SAM are often due to acute starvation and or severe disease.

• For nutrition emergencies, children less than 5 years are measured since their measurements are more sensitive to factors that influence nutritional

status such as illness or food shortages.

• Global Acute Malnutrition (GAM) is a sum of Moderate Acute Malnutrition and Severe Acute Malnutrition.

• The prevalence of Global Acute Malnutrition is usually below 5% in any developing country, provided there is no food shortage.

• Height for Age is an index of growth and development. It is an expression of long term exposure to nutritional inadequacy and indicates chronic

malnutrition in children lacking essential nutrients but also related to poor sanitation, repeated infections, diarrhoea and inadequate care.

• Stunting is defined as Height for age index more than two standard deviation below the mean of the WHO reference population.

181

Prevalence of Global Acute Malnutrition (GAM) by Province

6

2,4 2,52

3,9

1,9

4,4

2,3

3,1

3,9 3,8

2,2 2,2

6,4

2,5

3,8

1,3

3,3

4,9

32,4

2,1

5,2

2,2

4,1

1,8

3,2

0

1

2

3

4

5

6

7

8

9

10

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f ch

ildre

n (

%)

Boys Girls All

• Nationally, the prevalence of GAM was 3.2%.

• The prevalence is lower than the 4.4% observed in the 2016 May ZimVAC RLA.

• Matabeleland North had the highest prevalence of GAM (5.2%) with girls (6.4%) more affected than boys (3.9%).

• Generally across most provinces, girls were most affected than boys except in Manicaland, Mashonaland East, Midlands and Masvingo. 182

Prevalence of Global Acute Malnutrition (GAM) by Year and Province

3

5

2,6

6,7

4,9

4

4,9

3

4,44,9

32,4

2,1

5,2

2,2

4,1

1,8

3,2

0

1

2

3

4

5

6

7

8

9

10

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f ch

ildre

n (

%)

2016 2017

• In comparison with findings from the 2016 ZimVAC RLA, there has been a general decrease in GAM across most provinces

except in Manicaland and Matabeleland North.

• There was a significant decrease in Mashonaland West from 6.7% in 2016 to 2.1% in 2017.

183

Prevalence of Severe Acute Malnutrition (SAM) by Province

2,8

0,3

0,6

0,4

1,6

0,7

2,5

1,2 1,2

1,7

1,9

0,6

1,3

1,1

0

1,7

0,9

1,1

2,2

1,1

0,6

0,9

1,3

0,4

2,1

1

1,2

0

0,5

1

1,5

2

2,5

3

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f ch

ildre

n (

%)

Boys Girls All

• The prevalence of severe acute malnutrition was 1.2%. This was lower than that of the 2016 ZimVAC RLA (1.9%).

• Manicaland (2.2%) and Midlands (2.1%) had prevalence above the World Health Organisation (WHO) emergency threshold of 2%.184

185

Gender Based Violence

186

Physical and Sexual Violence by Province

3,5

4,7

2,0

3,33,0

1,9

4,4

3,4 3,3

0,6

1,0

0,2

0,60,3

0,8 0,7

0,0

0,6

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

4,0

4,5

5,0

Pro

po

rtio

n o

f M

ales

(%

)

Male Physical Male Sexual

7,7

5,1

3,8

5,4

3,2

1,7

3,4

2,4

4,2

1,6

0,8 0,71,3 1,1

0,2

1,10,4

0,9

0,0

1,0

2,0

3,0

4,0

5,0

6,0

7,0

8,0

9,0

Pro

po

rtio

n o

f Fe

mal

es (

%)

Female Physical Female Sexual

• More males and females reported having experienced physical violence than sexual violence.

• Physical violence was experienced by about 3.3% of the men and 4.2% of the women.

• The highest proportion of men that experienced physical violence was in Mashonaland Central (4.7%) and that of women was inManicaland (7.7%).

• The highest proportion of men that experienced sexual violence was in Mashonaland Central (1.0%) and that of women was in Manicaland(1.6%).

187

Perpetrators of Physical and Sexual Violence

Perpetrator Males (%) Females (%)

Mother/Step Mother 4.4 6.6

Father/ Step Father 2.9 3.5

Sister/ Brother 2.9 6.0

Other Relative 18.2 13.3

Spouse 19.0 35.8

Former Boyfriend/Girlfriend 1.5 4.1

Employer 6.6 1.3

Other 19.0 11.4

Perpetrator Males (%) Females (%)

Current husband/ Partner 2.2 6.3

Former husband/ partner 2.2 1.6

Current/ former boyfriend 2.2

Other relative 19.6 24.4

In law 4.3 2.4

• Spouses were reported as the perpetrators by 35.8% of the females and 19% of the males who had experienced physical violence.

• Of concern were incidences of sexual violence in both males and females that were mostly perpetrated by other relatives (19.6% and 24.4%

respectively).

Physical Violence Sexual Violence

188

Prevalence of Spousal Violence by Sex and Province

3,02,8

1,8 1,81,6

2,2

2,72,2 2,3

5,75,4

4,1

5,4 5,3

2,3

3,3

2,6

4,2

0,0

1,0

2,0

3,0

4,0

5,0

6,0

7,0

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo National

Pro

po

rtio

n o

f m

ales

an

d f

emal

es (

%)

Male Female

• Nationally, about 4.2% of women reported having experienced spousal violence.

• Manicaland had the highest reports of spousal violence among both women and men (5.7% and 3.0% respectively).

189

Community Development Challenges and Development Priorities

190

Community Challenges

9

9

9

7

6

5

5

5

5

4

4

4

3

3

2

2

2

2

2

0 1 2 3 4 5 6 7 8 9 10

Drought

Shortage of cash

Poor road infrastructure

Lack of Irrigation infrastructure

Lack of income generating projects

Unemployment

Inadequate markets

Poor/ lack of Health and infrastructure

Poor Water and sanitation facilities

High cost of Inputs and implements

Lack of/ limited Water for domestic use

lack of /limited Water for crop and livestock production

No primary/secondary school in the ward

Draught Power shortage

Poverty

Unpredictable and unreliable rainfall patterns

Lack of /intermittent Electricity supply

Poor access to livestock/produce markets

Unavailability of crop/livestock inputs on the local market

Proportion of communities (%)

• The greatest proportion of communities indicated drought, shortage of cash, poor road infrastructure (9%) and lack of irrigation infrastructure (7%)

as their major development challenges.

191

Community Challenges by Province

192

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo

Lack of income generating projects 19 31 32 24 20 12 18 19

Draught Power shortage 5 10 10 12 10 8 16 10

Drought 25 37 35 14 24 46 51 59

No primary/secondary school in the

ward

10 20 16 8 16 24 13 3

Poor/ lack of Health and infrastructure 20 20 23 19 17 18 15 15

Inadequate markets 34 20 25 6 8 11 18 23

High cost of Inputs and implements 18 30 20 21 4 2 23 17

lack of Irrigation infrastructure 32 29 28 23 27 24 30 34

Shortage of cash 39 26 45 39 35 43 38 30

Poor road infrastructure 42 29 34 46 38 37 32 32

Unpredictable and unreliable rainfall

patterns

4 9 11 3 13 4 11 9

Poverty 16 5 11 5 5 13 4 11

Unemployment 18 16 15 25 19 22 22 28

Poor Water and sanitation facilities 24 22 14 18 14 18 19 14

Lack of/ limited Water for domestic use 16 20 8 24 29 18 14 10

lack of /limited Water for crop and

livestock production

10 12 8 5 33 36 11 5

• Matabeleland South and Midlands reported drought as their major development challenge (59% and 51%) respectively.

• Mashonaland West and Manicaland highlighted poor road infrastructure as their major challenge (46% and 42%) respectively.

Community Development Priorities

12

11

11

10

8

8

7

5

4

3

3

2

2

1

1

1

0 2 4 6 8 10 12 14

Income Generation Projects promotion

Road infrastructure development

Water Supply- boreholes, piped water scheme

Dams/Water reservoirs construction

Health services and related infrastructure improvement

Agricultural markets availability and access development

Education and related infrastructure improvement

Employment creation

Electricity infrastructure development

Livestock restocking

Other specify

Vocational Training Centres

Livestock disease surveillance and control

Control of wildlife

Skills and capacity Development

Revival and development of Industries

Proportion of communities (%)

• At least 12% of the communities reported income generation projects as their major development priority.

• Revival and development of industries, skills and capacity development and control of wildlife were considered less important on the priority list.

193

Development Priorities by Province

• Mashonaland Central cited water supply as their major development priority (64%).

• Matabeleland North and Matabeleland South indicated water reservoir construction as their major priority (57% and 58%) respectively.194

Manicaland Mash Central Mash East Mash West Mat North Mat South Midlands Masvingo

Dams/Water reservoirs construction 22 28 39 28 57 58 55 39

Education and related infrastructure

improvement

19 37 31 24 31 35 24 11

Electricity infrastructure development 19 18 19 25 4 5 10 14

Employment creation 21 17 16 17 19 24 19 26

Health services and related infrastructure

improvement

28 32 41 25 33 30 28 28

Income Generation Projects promotion 44 42 46 58 42 46 44 59

Irrigation infrastructure development 64 34 48 35 45 45 41 68

Agricultural markets availability and access

development

41 27 34 32 25 20 31 30

Road infrastructure development 44 40 45 57 45 34 47 38

Water Supply- boreholes, piped water

scheme

40 64 39 42 34 42 42 32

195

Conclusions and Recommendations

• Joint efforts by both Government and partners in food distribution through various interventions ensured that most vulnerable and

food insecure rural households had access to food. Government and UN/NGO support to vulnerable households increased remarkably

during the 2016/17 consumption period (71.6%) compared to the 2015/16 consumption period (65%).

• In 2016/2017, the bulk of resources from both Government and partners went towards emergency and immediate food requirements

for households. However, it is recommended that during the 2017/18 consumption year, more resources be channelled towards

Government input support, household economy strengthening and building productive community assets. Interventions that

strengthen households’ economy and resilience are thus recommended to ensure households remain food and nutrition secure.

• The proportion of children not attending school due to illness is a cause of concern. We recommend the prioritisation of resource

allocation towards the strengthening of the School Feeding and School Health Programmes.

• The proportion of children of school going age who were not in school due to financial constraints remains significant. There is need for

the Government to increase Basic Education Assistance Module (BEAM) funds so that vulnerable children can be supported.

• The high proportion of children who were turned away from school due to non-payment of school fees is worrisome. This calls for

stricter monitoring of the implementation of the Government Policy for universal primary education and its complementary policy

which states that no child should be denied access to schooling for failure to pay school fees.

196

Conclusions and Recommendations

Conclusions and Recommendations

• The proportion of households that grew the major food and cash crops increased as compared to last season. The good rainfall season coupled with

the different input programmes that were put in place resulted in increased household production. However some areas were affected by water

logging and some farmers failed to get enough fertiliser. This calls for efforts to urgently ensure that inputs are readily available on the market.

• Inadequate labour, coupled with use of unimproved seed varieties continue to constrain agriculture production and productivity among small-holder

farmers and hence the need for extension to capacitate farmers on the need for good agricultural practices

• There is need to promote labour saving technologies given the fact that many households had inadequate agricultural labour.

• The level of average household production this season was significantly high. This calls for good post-harvest handling techniques at household level

so as to reduce post-harvest losses.

• The increase in cereal production is likely to increase supply of grain on the market which in turn offers the country the opportunity to replenish its

Strategic Grain Reserves. Therefore the Grain Marketing Board should be capacitated to be able to collect, timeously pay farmers and properly store

the grain in the Strategic Grain Reserve.

• Equipment breakdown and seasonality of water have been cited as reasons for partial and non functionality of irrigation schemes. Given that climate

change is real and that the country has been experiencing droughts there is need for Government and partners to facilitate rehabilitation of partially

functional and non-functional irrigation schemes. This also calls for promotion of water harvesting technologies so as reduce the effects of climate

change and variability.

197

Conclusions and Recommendations

• There is need for capacity building for Government extension service providers to increase coverage of extension services for small-holder farmers.

• The proportion of Households selling livestock as a business is very low, raising issues on the quality of meat produced. There is need for Government

to come up with strategies and packages that support farming as a business.

• There is need for Government to increase sale pens and auctions across all provinces to reduce inclusion of middlemen.

• The household consumption indicators show an improved food access situation for the majority of households compared to last year.

• The coping strategies, Household Hunger Scores, Household Dietary Diversity as well as consumption of protein, iron and vitamin A rich foods

improved from last year mainly due to the presence of the diverse field crops and food assistance.

• The livelihood coping strategies engaged by households have decreased this year which shows that there is an improved food access situation. The

livelihood coping strategies however remain a cause of concern as depletion of assets directly reduces future productivity and affects households’

ability to cope with future shocks and may lead to future food consumption gaps. Resilient livelihood activities are therefore recommended for all

rural households.

198

• Water, Sanitation and Hygiene (WASH) education programmes need to be integrated to achieve improved public health by scaling up

sanitation-focused participatory hygiene and health education, schools health clubs, sanitation action groups and community health clubs.

• Specific material resources are needed to support national behaviour change programmes and to re-equip and enhance the impetus of the

Environmental Health Practitioners who are the primary extension officers for household sanitation, water supplies, hygiene promotion and

health education.

• A paradigm shift from primarily relying on unimproved drinking water sources to improved communal water points and improved piped

water into households using renewable energy sources (solar) is recommended.

• Elimination of open defecation through availing of resources (both soft and hardware) for the construction of latrines using locally

available resources is recommended. Customised service standards should reconcile with technology choice and service levels with the

economic capacity of user groups.

• Women were identified as the primary household member fetching water for household consumption. Participants within the WASH sector

should consider support and promotion of time and labour saving technologies such as ‘roller drums’ that reduce the burden on women

and therefore increase their time to engage in economically productive activities.

199

Conclusions and Recommendations

• Generally incomes for rural households are following a downwards trend since 2014. We therefore recommend some income generating projects

for rural households to be initiated.

• Casual labour and food crop production were been reported as the most important sources of income for the majority of rural households. We

therefore recommend that markets for crops should be made available.

• ISALs have proven successful as an approach that protects household assets, smooth cashflow, improves number of meals consumed, and

increases household incomes and expenditure. As such, ISAL groups should be scaled up in poor rural communities in all provinces to improve

food security and livelihoods.

• Communities continue to face challenges of drought, cash shortages and poor road infrastructure among other challenges. Efforts to address

rural community development challenges should focus on construction and rehabilitation of water bodies as well as promotion of climate smart

technologies.

200

Conclusions and Recommendations

Conclusions and Recommendations

• The national prevalence of GAM was 3.2% and this is below the 5% emergency threshold. Matabeleland North had the highest prevalence of GAM

(5.2%) with girls being more affected at 6.4%. Generally across most provinces girls were most affected than boys except in Manicaland, Midlands

and Masvingo.

• The minimum dietary diversity for children 6-23months remains below the cut-off to contribute to meaningful reduction to stunting. More

multisectoral efforts are recommended to improve on the quality of children’s diets.

• The minimum dietary diversity for women aged 15-49yeras was 40% and this reflects that most women are not consuming a quality diet that is

adequate to meet their micronutrient requirements. A multisectoral approach to address and strengthen interventions to enhance the nutritional

content of family diets is required. Strategies to employ include production of diverse plant and animal food sources, promotion of consumption of

diverse diets and value addition of locally available foods.

• The food consumption score reflects that there has been an increase in the proportion of rural households consuming poor diets. Multisectoral

efforts to improve consumption patterns are recommended to impact greatly on nutrition outcomes. Emphasis should be put on broadening

national agricultural programmes through diversification of both crop and livestock production.

201

Conclusions and Recommendations• The proportion of children under 2 and pregnant and lactating women who were reached by community health services is below the 80%

national target. cIYCF and similar community based interventions should be strengthened to scale-up coverage of stunting prevention

activities within their local context.

• More than 80% of rural households consumed iodised salt. Efforts to increase coverage is recommended for provinces with low coverage

and regular monitoring for those at the recommended coverage of 80%.

• Fall armyworm affected all the provinces with 36% of the households managing to identify it as a new pest. Maize is the crop most infested

and against the background that 88% of the households grew maize in 2016/17 season it is unlikely that farmers will want to abandon

maize. There is a likelihood of the new pest to affect wheat during the winter season.

• About 62.5% of the households affected by the new pest did not take any measures to control it. Households which took initiatives to

control it used a variety of methods which included biological control, application of commercial pesticides, traditional control and other

methods. However, these measures were generally not successful. It is therefore recommended to build capacity of;

• Extension agencies in providing the relevant and high quality information to farmers on Fall armyworm

• Research institutions to determine sustainable ways of managing the pest including efficacy of pesticides and indigenous control

measures, most effective, lowest-risk, economical, accessible and easily used by smallholders (without sophisticated machinery).202

Conclusions and Recommendations • The adult female moth of the Fall armyworm is a strong flyer and will continue to spread across the country. Populations of the pest may

continue to build as they find more host plants to multiply on and in the absence of natural biological enemies (general predators like ants

and earwigs), specialized parasitoids and a host of insect pathogens (virus, bacteria and fungi). It is therefore important to increase

awareness raising on the new pest among different stakeholders, strengthen monitoring mechanisms/capacities (identification, information

relaying systems) and response systems from national to sub-national levels.

• About 36.5% of households used various measures to control Fall armyworm both conventional and traditional. It is important to learn from

the experiences of farmers and researchers locally and internationally. The best recommended practices will be tried and adapted in the

field through Farmers’ Field Schools. It is therefore recommended that support for designing and testing of a sustainable pest management

programme for smallholders should be provided. The best recommendations will then be communicated and shared with farmers, farmers’

organizations and Government.

• The true extent of Gender Based Violence is difficult to measure as it is often under-reported in most cases. It is perceived that reported

cases in this report represent only a small fraction of the overall total that could be present. Gender Based Violence campaigns need to be

scaled-up to empower women and men and encourage them to report and seek help.

• Further research is required to understand the underpinning causes of physical violence which was reported more than sexual violence.

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Conclusions and Recommendations • Communities are faced with a host of shocks and hazards both natural and anthropogenic impacting negatively on their ability to access their food and non-food

requirements. The situation is being compounded by the recurrent under-performing macro-economic situation with cash shortages being one of the immediate

areas requiring the attention of Government and stakeholders.

• There is need for proactive multi-stake holder resilience building interventions to ensure that vulnerable communities meet their daily food and non-food

requirements before they venture into negative coping strategies that may lead to loss of their productive assets.

• Considering that communities have limited capacities to recover from disasters, Government and development partners should consider improving and broadening

community social protection and resilience building programmes to enhance early recovery from emergencies and disasters. This may include scaling up of

programmes such as Harmonised Social Cash transfers and Productive Community Works.

• Government with support from partners should consider scaling up structural and non-structural measures to deal with flooding and human wildlife conflict taking

advantage of the on-going land re-distribution programme to relocate communities at risk

• Rural food insecurity prevalence in June 2017 was estimated at 1% and is projected to reach 11% during the peak hunger period (January to March 2017). This is

lower compared to last year. This food insecurity prevalence translates to 1,052,768 rural people compared to 4.1 million in the previous consumption year.

• Food assistance programmes should be targeted to those households that have been found to be food insecure.

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Annexes

205

Manicaland

206

Mashonaland Central

207

Mashonaland East

208

Mashonaland West

209

Masvingo

210

Matabeleland North

211

Matabeleland South

212

Midlands

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Report Writing Team

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Name Organisation Email

George D. Kembo Food and Nutrition Council gkembo@sirdc.ac.zw

Blessing Butaumocho Food and Nutrition Council bbutaumocho@gmail.com

Herbert Zvirere Food and Nutrition Council hzvirere@fnc.org.zw

Margaret Tawodzera Ministry of Health and Child Care margaret.tawodzeragmail.com

Lameck Betera Ministry of Local Government lbetera@eprzim.co.zw

Banda Mirriam Food and Nutrition Council miriebanda@yahoo.com

Nester Gumbo Ministry of Agriculture, Mechanisation and Irrigation

Development

gumbo nester @gmail.com

Manyika Ngoni Ministry of Public Service, Labour and Social Welfare ngonnny@gmail.com

Rongai Machinga Ministry of Agriculture, Mechanisation and Irrigation

Development

rmachinga@gmail.com

Perpetual Nyadenga Food and Nutrition Council pnyadenga@fnc.org.zw

Carol Mukanduri Food and Nutrition Council cmukanduri@yahoo.com

Lloyd Chadzingwa Food and Nutrition Council lchadzingwa@fnc.org.zw

Arnold Damba ZIMSTAT dambaanro@gmail.com

Mildred Mapani Ministry of Public Service, Labour and Social Welfare milshanta@gmail.com

Ruramai Mpande Ministry of Primary and Secondary Education rurampande@gmail.com

Siboniso Chigova Food and Nutrition Council chigova.sibo@gmail.com

Report Writing Team Name Organisation Email

Shamiso Chikobvu Ministry of Agriculture, Mechanisation and Irrigation

Development

chikobvushamiso33@gmail.com

Alfa Ndlovu Food and Nutrition Council ndlovualfah@gmail.com

Yvonne Mavhunga Food and Nutrition Council yvonnemavhunga@gmail.com

Rutendo Nyahoda Ministry of Agriculture, Mechanisation and Irrigation

Development

rruwisi@yahoo.com

Disalice Kunaka Ministry of Rural Development, Promotion and

Preservation of National Culture and Heritage

disalicey@gmail.com

Innocent Mangwiro Food and Nutrition Council imangwiro@fnc.org.zw

Kudzi Mukudoka UNICEF kmukudoka@unicef.org

Tinashe Sande UNWOMEN tinashe.sande@unwomen.org

Themba Nduna USAID tnduna@usaid.gov

Shupikai Zimuto UNDP shupikayi.zimuto@undp.org

Tendai Mugara FAO tendai.mugara@fao.org

Angela Kafembe FEWSNET akafembe@fews.net

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Overall Coordination Team

• George D. Kembo

• Blessing Butaumocho

• Yvonne Mavhunga

216