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Message # 1 Disaster impacts on LDCs and subsequent graduation
Message # 1
Disaster impacts on LDCs and subsequent
graduation
Key Messages
1 2
Asia-Pacific is a region highly impacted by
disasters- and LDCs are the most affected
Disasters widen existing inequalities
in LDCs through impacts on critical sectors like education, health, and employment
Solution- Risk informed
investments in critical sectors
needed to outpace disaster
risk in critical sectors
3
Asia-Pacific is a region highly impacted by disasters- and LDCs are the most affected
Message # 1
LDCs have high disaster impacts
Message # 1 LDCs have higher mortality rates from disasters
Between 2000 and 2015, in Asia and the Pacific, the low‐ and lower middle income countries experienced by far the most disaster deaths
The LDC also lost more people per disaster event: on average, more than 8,000 people died per disaster in the low income countries‐ almost 15 times the average toll than the high and middle income countries
LDCs have high disaster impacts
Message # 1
• Looking to the future, studies show that the impacts on mortality and affected population, while decreasing, will decrease less for LDCs.
• Among the 43 countries studied, those listed as most seriously affected were the, Bangladesh, Lao People's Democratic Republic, Myanmar, Bhutan, and Cambodia; all were expected to see only small decreases, either in fatalities or in the number of people affected.
LDCs may also have higher mortality rates and affected population from disasters in the future
LDCs have high disaster impacts
Message # 1LDCs make up almost half of the top 15 countries with highest Average
Annual Losses considering GDP
Beyond measuring the human cost, there have been efforts to predict future economic costs.
Average annual loss is a probabilistic calculation of future economic loss from multiple‐hazard for each country.
When looking at the absolute numbers, the higher income countries in the region seem to lose more.
Changes when looking as a percentage of GDP
LDCs are much more likely to have their GDP impacted by disaster losses
ESCAP, based on probabilistic risk assessment
LDCs have high disaster impacts
Message # 1
• Many countries at high risk still lack capacities to absorb and manage disaster risks.
• Analyzing data from the World Risk Report shows than out of the 10 countries at greatest disaster risk all LDCs have extremely low coping capacity.
• Even when countries have capacities to forecast and warn citizens of potential disasters, their capabilities can be overwhelmed by the scale and intensity of the event.
Of the 10 countries with highest exposure to hazards, LDCs have the lowest coping capacity
Message # 2
Disasters widen existing inequalities in LDCs through impacts on critical sectors like
education, health, and employment
Disasters widen inequalities In LDCs
Message # 2Message #2
Disasters have been shown to widen inequalities.
The Asia-Pacific Disaster Report in 2017 showed that countries in Asia and the Pacific, a natural disaster increases the Gini coefficient by 0.13 in the next year. This may be even more significant for LDCs.
The vicious cycle of poverty, inequalities of income and opportunity and disasters
Viciouscycle
Inequalityof wealthandincome
Multi-dimensional
poverty
Vulnerability to disasters
Disasters widen inequalities In LDCs
Message # 2Message #2
32.1Myanmar
Cambodia
Nepal
Lao PDR
Vanuatu
Timor‐Leste
Bhutan
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
25 30 35 40 45 50Average D
GiniHigh GiniLow
Gini
High
D‐
inde
xLow D‐
inde
x
Afghanistan
• Most of the LDC countries have very high levels of disaster risk as shown by the bubble sizes
• Like the Gini index, the D‐Index measures the inequality of opportunity including education, health, and livelihood
• Almost all of the LDC are in the High‐D index and High Gini quadrant
• They also are the countries most likely to have significant overlaps between inequalities and disasters
LDCs have high overlaps between disaster risk, income inequalities and inequality of opportunities
Disasters widen inequalities In LDCs
Message # 2
• Poor populations typically lose more because they are overexposed to disasters and have less ability to cope and recover, especially if they have little social protection or post‐disaster support.
• Uses Human Development Index combined with GAR 2015 hazard exposure models and data on land degradation
• High socioeconomic‐hazard risk amongst the LDC countries
• The most vulnerable population are those with a high overlap of low HDI and disaster risk
Hotspots of low HDI, high population density, and hazard risks
Disasters widen inequalities In LDCs
Message # 2
We see this in how disasters impactwhen they hit an country.
In Nepal, for example, we note a similartrend when examining the overlaps ofdisaster impacts and poverty.
The impacts of disasters are the highestin areas with high poverty.
In addition to hitting the poorest,disasters can also cause the near poor –those living on between $1.90 and $3.10per day – to fall into poverty.
The overlaps of poverty and disaster impacts in
Nepal, 2000-2015
Disasters widen inequalities In LDCs
Message # 2
Moreover, disasters often have permanent impacts on their education and health thereby locking people into intergenerational poverty traps.
A few post‐disaster needs assessments show that in Myanmar for example, the 2015 floods and landslides damaged estimated 4,116 schools.
Half of the most‐affected of the 40 townships were in the poorest states in Myanmar.
Disasters widen inequalities In LDCs
Message # 2
The 2017 Asia Pacific Disaster Report shows that in Bangladesh, for example, during and after floods, poorer households have less food available, reduce their meals and rely on less expensive food, and sell their assets at a much higher rate than their wealthier counterparts.
Poorer households also have greater losses in wellbeing because they have fewer assets (which are worth more to them), their consumption is closer to subsistence levels, they cannot rely on savings to smooth disaster impacts, and their health and education are at greater risk.
Disasters widen inequalities In LDCs
Message # 2
Discrimination and exclusion – who will be left behind
when disaster hits?
Groups that are left behind can be profiled using a ‘classification tree,’ a predictive model commonly used in data mining and machine learning.
In each iteration, the classification tree ascertains groups that are most or least advantaged in disaster prone areas.
The algorithm determines additional branches for the tree branched, to show that the same worst-off group are the poorer older populations, who have limited access to healthcare, are not empowered to make household decisions, and work in agriculture.
Education levels and vulnerability in high-multi-hazard risk areas in Bangladesh
ESCAP, based on Global Assessment Report on Disaster Risk Reduction (GAR) Risk Atlas 2015, and DHS Household survey
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Population size: 77.6%Access rate 54.6%
Top 20% wealthSize : 32.2%
Access rate 74.4%
Women empowered to make household
decisionsSize: 4.7%
Access rate: 86.3%
Bottom 20% wealthSize: 45.4%
Access rate: 40.4%
BANGLADESH Have access to healthcareSize: 0.6%
Access rate: 92%
UrbanSize: 7.2%
Access rate: 63.9%
Empowered to make household decisions
Size: 1.1% Access rate: 53.4%
Have access to healthcare Size: 1.8%
Access rate: 41.1%
Agricultural occupationSize: 9.3%
Access rate: 24.7%
OlderSize: 20.9% Access rate:
29.0%
YoungerSize: 25.1% Access rate:
49.6%More than two children
Size: 8.0% Access rate: 42.2%
Least vulnerable in disaster prone areas for access to education
Most vulnerable in disaster prone areas for access to education
Message # 3
Solution- Investing to outpace disaster risk in critical sectors to empower and include
vulnerable commuties
Message # 3Investing to outpace disaster risk Investing in new technologies to support gaps in data disaggregation
to geo-locate vulnerable populations
The statistical geo-spatial data have been combined with DHS data to estimate the poor’s exposure to disaster risks.
Empowering and including the most vulnerable communities for disaster risk reduction calls for good baseline data that help policy makers count and identify people.
Such data needs to be disaggregated by gender, age, and disabilities, income profiles, asset ownership among others.
Such data are often scarce or completely missing.
But with advances in geo-statistical interpolation techniques, it is now possible to determine who is most exposed, where, and what exposes them
Message # 3Investing to outpace disaster risk
Geo-locating the most vulnerable with data
integration
Figure shows that the concentration of risk is greatest in the eastern parts of Nepal, where many primary care hospitals are situated.
Building or upgrading these in a resilient and risk-sensitive manner and expanding their reach in more rural and remote areas can support the most vulnerable populations during disaster shocks.
Similar trends can be seen in Bangladesh
Mapping vulnerable communities and health facilities in Nepal
ESCAP, based on DHS Programme Household Survey and Service Provision Assessment Survey for Nepal, and multi-hazard data from Global Assessment Report on Disaster Risk Reduction (GAR) Risk Atlas 2015.
Mapping vulnerable communities and health facilities in Bangladesh
Message # 3Investing to outpace disaster risk Breaking the link between disasters, poverty and inequality
Policymakers can enhance the quality of investments by applying empowerment and inclusion approaches, to ensure that poor and vulnerable
groups are not excluded from the benefits of investments due to barriers in accessing land, reliable early warning systems, finance, and decision-making structures.
Policymakers can enhance thequality of investments by applyingempowerment and inclusionapproaches, to ensure that poor andvulnerable groups are not excludedfrom the benefits of investments dueto barriers in accessing land, reliableearly warning systems, finance, anddecision-making structures.
Policy coherence for SDGs among LDC
Disaster risk reduction and resilience is not one of the larger goals, but it it linked to at least 14 SDG’s and embedded explicitly in at least 3 goals
One last word….
Policy coherence for SDGs among LDC
Disaster resilience in SDGs and the global frameworks
At the heart of the sustainable development agenda is disaster resilience.
A critical and urgent re-examinationof how we deal with risk is needed
An interconnected approach isneeded to ensure policy coherencebetween the global 2030 agendasand translating them to on ground tobenefit the LDCs to gradute.
Message # 3
Thank you
Madhurima Sarkar-SwaisgoodEconomics Affairs Officer, ICT and Disaster Risk Reduction Division
Email: [email protected]
