Health & Place 13 (2007) 577–587 Geographic analysis of vaccine uptake in a cluster-randomized controlled trial in Hue, Vietnam Mohammad Ali a, , Vu Dinh Thiem b , Jin-Kyung Park a , Rion Leon Ochiai a , Do Gia Canh b , M. Carolina Danovaro-Holliday a,1 , Linda M. Kaljee a,2 , John D. Clemens a , Camilo J. Acosta a,3 a International Vaccine Institute, San 4-8, Bongcheon-7 dong, Kwanak-ku, Seoul 151-818, Republic of Korea b National Institute of Hygiene and Epidemiology, No. 1, Yersin Street, Hanoi, Vietnam Received 16 August 2005; received in revised form 21 June 2006; accepted 4 July 2006 Abstract This paper identifies spatial patterns and predictors of vaccine uptake in a cluster-randomized controlled trial in Hue, Vietnam. Data for this study result from the integration of demographic surveillance, vaccine record, and geographic data of the study area. A multi-level cross-classified (non-hierarchical) model was used for analyzing the non-nested nature of individual’s ecological data. Vaccine uptake was unevenly distributed in space and there was spatial variability among predictors of vaccine uptake. Vaccine uptake was higher among students with younger, male, or not literate family heads. Students from households with higher per-capita income were less likely to participate in the trial. Residency south of the river or further from a hospital/polyclinic was associated with higher vaccine uptake. Younger students were more likely to be vaccinated than older students in high- or low-risk areas, but not in the entire study area. The findings are important for the management of vaccine campaigns during a trial and for interpretation of disease patterns during vaccine-efficacy evaluation. r 2006 Elsevier Ltd. All rights reserved. Keywords: Vaccine coverage; Vaccine trial; Ecology; Spatial analysis Introduction Vaccine efficacy/effectiveness trials are the cor- nerstone for vaccine introduction in the developing countries. Conduction of such trial efforts is made to deliver the vaccines in a short period of time, similar to somewhat like a mass-vaccination cam- paign. A vaccine trial mass campaign in developing ARTICLE IN PRESS www.elsevier.com/locate/healthplace 1353-8292/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.healthplace.2006.07.004 Corresponding author. Tel.: +82 2 872 2801; fax: +82 2 872 2803. E-mail addresses: [email protected] (M. Ali), [email protected] (V.D. Thiem), [email protected] (J.-K. Park), [email protected](R.L. Ochiai), [email protected] (D.G. Canh), [email protected] (M.C. Danovaro-Holliday), [email protected] (L.M. Kaljee), [email protected] (J.D. Clemens), [email protected] (C.J. Acosta). 1 Present address: Pan American Health Organization, 525 Twenty-third Street, NW, Washington DC 20037, USA. 2 Present address: University of Maryland Baltimore, School of Medicine, Department of Pediatrics, 737 West Lombard Street, Baltimore, MD 21201, USA. 3 Present address: GlaxoSmithKline, 2301 Renaissance Boulevard RN0220, P.O. Box 61540, King of Prussia, PA 19406-2772, USA.
Geographic analysis of vaccine uptake in a cluster-randomizedcontrolled trial in Hue, Vietnam
Mohammad Alia,�, Vu Dinh Thiemb, Jin-Kyung Parka, Rion Leon Ochiaia,Do Gia Canhb, M. Carolina Danovaro-Hollidaya,1, Linda M. Kaljeea,2,
John D. Clemensa, Camilo J. Acostaa,3
aInternational Vaccine Institute, San 4-8, Bongcheon-7 dong, Kwanak-ku, Seoul 151-818, Republic of KoreabNational Institute of Hygiene and Epidemiology, No. 1, Yersin Street, Hanoi, Vietnam
Received 16 August 2005; received in revised form 21 June 2006; accepted 4 July 2006
Abstract
This paper identifies spatial patterns and predictors of vaccine uptake in a cluster-randomized controlled trial in Hue,
Vietnam. Data for this study result from the integration of demographic surveillance, vaccine record, and geographic data
of the study area. A multi-level cross-classified (non-hierarchical) model was used for analyzing the non-nested nature of
individual’s ecological data. Vaccine uptake was unevenly distributed in space and there was spatial variability among
predictors of vaccine uptake. Vaccine uptake was higher among students with younger, male, or not literate family heads.
Students from households with higher per-capita income were less likely to participate in the trial. Residency south of the
river or further from a hospital/polyclinic was associated with higher vaccine uptake. Younger students were more likely
to be vaccinated than older students in high- or low-risk areas, but not in the entire study area. The findings are important
for the management of vaccine campaigns during a trial and for interpretation of disease patterns during vaccine-efficacy
countries. Conduction of such trial efforts is madeto deliver the vaccines in a short period of time,similar to somewhat like a mass-vaccination cam-paign. A vaccine trial mass campaign in developing
ARTICLE IN PRESSM. Ali et al. / Health & Place 13 (2007) 577–587578
countries is challenging because both individual andsocial/ecological factors may influence vaccineuptake. The latter, for instance, may result inspatial variation of vaccine uptake (Sammarcoet al., 2004; Alfredsson et al., 2004; Dannetunet al., 2003; Harmanci et al., 2003). Ali et al. (2005a)suggested that higher vaccine coverage of an areamay bias the vaccine-efficacy estimates downward.Understanding spatial variation of vaccine uptakeis, therefore, important for evaluating effectivenessor efficacy of a vaccine.
People’s perception, as an individual or as agroup, about vaccine trials is not quite well knownto the trialists. The acceptability of the vaccinesamong the study population, even offered at free ofcost in a vaccine trial, may not be satisfactory.Factors such as household head’s education, livingcondition, and gender can influence vaccine uptake(Bishai et al., 2002) suggesting non-monetaryfactors may play a role in determining whether anindividual will take vaccine or not (Kenyon et al.,1998). Recently, Chen et al. (2002) suggested forexploring geographic variations of social andenvironmental factors that may influence vaccineuptake. These studies suggest investigating indivi-dual as well as ecological factors of vaccine uptakefor the management of vaccine campaign andinterpretation of results during vaccine-efficacyevaluation.
Analyses of vaccine uptake have traditionallybeen conducted at either the ecological or theindividual level (Jones et al., 1991). Jones et al.(1991) explored potential of a hierarchical multi-level model taking simultaneously both the levels,and showed benefits of the multi-level approach inevaluating compositional and contextual effects onvaccine uptake. Such approach has rarely beenexplored for evaluating the factors of vaccineuptake in a mass campaign of a vaccine trial.
We conducted a cluster-randomized controlledtrial in Hue central Vietnam in December 2003 aspart of the multi-disciplinary Diseases of the MostImpoverished (DOMI) program, designed to accel-erate the introduction of Vi polysaccharide typhoidfever vaccine in Asian countries (Acosta et al., 2004;Clemens and Jodar, 2004; Acosta et al., 2005). Thevaccine campaign was conducted in schools target-ing students between grade 1 and 12 (age 5–18years). The overall coverage rate was 58% butvaried from 22% to 99% across schools, asobtained from our campaign report (Thiem et al.,2006). This study is to identify spatial variations of
vaccine uptake and to evaluate individual as well asecological factors influenced to vary vaccine uptakein the vaccine trial using a cross-classified multi-level linear model.
Methods
The study area, Hue City, consisting of 25communes, is one of the nine districts of the ThuaThien Hue Province in central coastal Vietnam andcovers 71.87 km2. The city is bisected by thePerfume River, with approximately equal numbersof communes in each river basin (Fig. 1). Hue is anincreasingly prosperous area and a preferred desti-nation for both Vietnamese and internationaltourists.
Census surveys
In 2001, a census was conducted by the projectstaff to enumerate all the people of the study area.Before vaccination, the population was updated bythe second census. Prior to each census survey, thelist of households living in a social unit (calledgroup) was obtained from the local leaders’ office,and accordingly the households were surveyed.Since the local leaders maintain updated list ofhouseholds, the census surveys ensured highestpossible coverage of the study population. How-ever, few households (o2%) could not be found inthe first census that were captured in the secondcensus.
The project introduced a hierarchal personalidentification system using of community, hamlet,group, household, and individual identifications forthe study population. Note that the household andindividual-level identifications were assigned arbi-trarily by the project people. During the censussurvey in 2003, the schooling information such asname of the school, class, and grade of the studentswere also updated. At the time of census, vaccina-tion card with census ID number were distributed tothe students, which were collected at school beforevaccination. After verifying schooling informationthrough teachers, the final list of the students wasprepared for vaccination. According to the census2003, the population of Hue was 285,155, and thetarget students for vaccination were 56,076 of which46.4% in the primary school (grades 1 to 5), 37.4%in the middle school (grades 6–9), and the rest16.2% in the high school (grades 10 to 12). Thesestudents were from 68 schools inside the study area
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Fig. 1. The geographic features of the study area.
M. Ali et al. / Health & Place 13 (2007) 577–587 579
of which 40 were primary, 19 middle, and the restwere high schools.
Trial design and vaccines
This vaccine trial was regarded as evaluation-
blinded, because the investigators (clinicians andkey lab persons) were blind to which vaccine thestudy participants were assigned. Given that thevaccine and control agents were physically different,the information on the differences (suspensionvs. clear liquid) was never emphasized to trialparticipants. Additionally, two letter codes wereassigned on the labels: A or T, and each team wasresponsible for vaccinating either A or T in a schoolfollowing a rigorous training on the importance ofmaintaining the assigned vaccine code in eachschool.
Schools were regarded as clusters, and theseschools were randomly assigned to the Vi poly-sacharide typhoid (Typherixs) vaccine group or tothe hepatitis A (Havrixs) vaccine group. To ensure
balance among clusters, a stratified randomizationscheme was used, and the type of school (primaryvs. middle/high) was the principal stratificationfactor. An independent statistician carried outrandomization of the clusters to one of the twoassigned vaccine codes. Hence, the statisticians andinvestigators were blind to the actual assignment ofclusters to the type of vaccines.
Information dissemination
The promotion of the vaccine campaign wascoordinated by the Hue Preventive Medical Center2 months prior to the vaccination. Information onthe campaign was distributed through schools,posters in public areas, community leaders (people’scommittees), and local medias (newspapers, TV,and radio stations). School teachers distributedinformation sheets and consent forms to be signedby the students’ parents/guardians. Parents wereinformed about the campaign through the informa-tion sheets and mass media. Queries from parents
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were addressed in discussions and were reported inmass media.
Vaccine campaign
The vaccine campaign, which delivered singledose of each vaccine (typhoid or hepatitis A withdelivery of a second dose of hepatitis A 2 years afterthe initial dose), was conducted during December2–21, 2003. A 3-day ‘mop-up’ was carried out tovaccinate students missed during the regular cam-paign. Information related to vaccination status wasrecorded in a pre-printed register book. The bookcontained students’ name, age, gender, school-levelinformation, and assigned vaccine type, which weregenerated from the project’s census database. Whenthe campaign was over, the register books withvaccination status were delivered to the datamanagement for updating the database. Routinechecks such as keypunching errors, outliers, incon-sistencies, and linkage were performed to ensureaccuracy of the vaccination status before updatingthe master database.
Population, socioeconomic, and vaccine uptake data
For this study, demographic and socioeconomicdata were extracted from the project’s populationdatabase. The database contains both individual-and household-level information. Individual-leveldata (e.g., student’s age, gender, and schoolingstatus), and literacy, age, and gender of the house-hold head were obtained from the census database.Socioeconomic status, per-capita income, andhousehold size were obtained from the household-level data. Information on vaccine uptake wasobtained from the population-linked vaccinationdatabase.
Geographic data and ecological variables
In 2003, a global positioning system (GPS) surveywas conducted using handheld GPS receivers torecord the geographic position of all study areahouseholds. Of 58,465 households registered duringthe updated census, 324 households could not belocated either because they had moved or theiraddresses were incorrect. A total of 58,141 house-holds were included in the GIS database with 11,235spatially referenced points. Households sharing asingle structure or closely connected structures werereferenced as a single spatial referenced point.
Household data were mapped in groups (thesmallest geographic unit of the study area), andtheir geographic boundaries were verified by groundtruthing. We recorded the coordinates of allhealthcare providers and schools within the studyarea and included them in the GIS database. A basemap of commune boundaries and rivers, roads,railways, and lakes was acquired in digital formatprior to the GPS survey. The GPS survey data wereprojected in the same geographic referencing systemas the base map (i.e., Transverse Mercator) so thatGPS coordinates could be accurately integrated intothe study area GIS database.
After linking the geographic data to the popula-tion and disease surveillance databases, we com-puted the distribution of ecological variables for thegeographically referenced points. There were threehospitals, four polyclinics, and 49 private practi-tioners in the study area. We arbitrarily defined theneighborhood of each household by includingpopulation within a 500-m radius around it. The500-m distance was chosen considering that theecological data obtained from that size of neighbor-hood might well affect vaccine uptake amongstudents. By use of this definition, we computedthe 2-year cumulative neighborhood typhoid fever(blood culture confirmed) incidence rate (per 10,000people) before vaccination (November 2001–October 2003). We also computed the density ofprivate practitioners in the 500-m neighborhood(per 10,000 people) for each of the geographicallyreferenced points. Distances to the closest hospitalor polyclinic were obtained in Euclidian (linear)distance for the geographically referenced points.The distance to the school from resident was alsocalculated for the study population.
Spatial pattern of vaccine uptake
We used a geostatistical method, called kriging,to define the spatial pattern of vaccine uptake in thestudy area. Kriging is an optimal interpolator and issuitable for mapping spatial patterns of diseases andenvironmental phenomena (Cressie, 1991; Oliverand Webster, 1990). To employ the data in kriging,we computed vaccine coverage rates (either typhoidor hepatitis A) for the 9913 spatially referencedhousehold points of the study subjects using a250-m radius neighborhood. Because our goal wasto map local geographic variation of vaccineuptake (neither individualistic nor flat over thestudy area), we used a methodology described
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elsewhere (Ali et al., 2005b) to obtain an optimalscale for mapping local geographic variation ofvaccine uptake. The methodology is based onthe homogeneity of variance test (Hartley’s Fmax
test). Starting from a 50m radius and increasingthe scale stepwise by 50m, the data variance for the20 scales (50–1000-m radius neighborhoods) wereevaluated. From these data, we found that 250mwas an optimal scale for addressing local variationof vaccine uptake in the study area.
By the use of ordinary kriging, the data wereextrapolated at a regularly spaced interval to makethe surface map of vaccine coverage. Ordinarykriging relies on the spatial correlation structure ofthe data to determine the weighting values of thesampled data points. Furthermore, ordinary krigingmakes the assumption of normality among the datapoints. The resulting map of vaccine coverage wasclassified in quintiles of household points (Fig. 3). Atotal of 1947 household points (20% of the totalpoints) were in the highest quintile coverage surface;the surface was defined as the high-coverage areas.The high-coverage areas comprised 10 geographicclusters with a total area of 29.54 km2. The lowestquintile surface of the map was defined as the low-coverage areas. Of 1788 household points, 18% ofthe total points fell into low-coverage areas. Thelow-coverage areas were consisted of four geo-graphic clusters (6.63 km2).
Statistical analysis
We considered school as well as neighborhood asimportant source of variations for vaccine uptake.In our data, the school attended by a student wasnot necessarily within his/her neighborhood sug-gesting no hierarchical structure in the data, butthe data were contained within the cross-classifica-tion of neighborhood by school. Therefore, we useda general cross-classified random effects model(Rasbash and Goldstein, 1994) to evaluate indivi-dual as well as ecological factors of vaccine uptakeafter adjusting for the effects of the neighborhoodand school. A general random cross-classifiedmodel consists of two sub-models: level-1 (within-cell) and level-2 (between-cell) models. The cellsrefer to the cross-classifications by the twohigher-level units. In our case, the students werecross-classified by schools and neighborhoods.There were i ¼ 1, 2,y, nijk level-1 units (students)cross-classified by j ¼ 1,y, J first level-2 units(neighborhoods) designated as rows, and
k ¼ 1,y,K second level-2 units (schools), desig-nated as columns.
Level-1 or ‘within-cell’ model
We represent in the level-1 or within-cell modelthe outcome for student i in individual cells cross-classified by level-2 units j and k.
where yp is the model intercept, the expected valueof ppjk when all explanatory variables are set to zero;bpq are the fixed effects of column-specific predictorsXqk, q ¼ 1,y,Qp; bpqj are the random effectsassociated with column-specific predictors Xqk.They vary randomly over rows j ¼ 1,y, J; gpr arethe fixed effects of row-specific predictors Wrj,r ¼ 1,y,Rp; cprk are the random effects associatedwith row-specific predictors Wrj. They vary ran-domly over columns k ¼ 1,y,K; dpijk are the fixedeffects of cell-specific predictors Zjk, which are theinteraction terms created as the products of Xqk andWrj, s ¼ 1,y,Sp and SppRp�Qp; and bp0j, cp0k,and dp0jk are residual row, column, and cell-specificrandom effects, respectively, on ppjk, after takinginto account Xqk, Wrj, and Zsjk. We assume thatbp0j�N(0, tpb00), cp0j�N(0, tpc00), and that the effectsare independent of each other.
We used HLM for Windows version 6.02a(Scientific Software International, Inc., Lincoln-wood, USA) to analyze the data. Three cross-classified random effects models were created withsamples from the entire study area, the low-cover-age area and the high-coverage area (definedabove). The notion behind modeling with high-and low-coverage areas was to see whether or notthere are variations in predictors of vaccine uptakebetween these two areas. Modeling the entire area
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allowed us evaluate variations in predicting vaccineuptake between local (low or high vaccine-coverageareas) and broader (entire study area) geographicscales. All three models took vaccine uptake status(vaccinated or not of the assigned agent) of eachanalyzed individual as the dependent variable andfitted covariates as independent variables in themodels. Coefficients of independent variables in themodels were exponentiated to estimate the oddsratio of vaccine uptake. Standard errors for thecoefficients were used to estimate p-values andassociated 95% confidence intervals for the oddsratios.
Results
The CONSORT chart of the study population isgiven in Fig. 2. Of 55,668 children analyzed, 31,908students were vaccinated (received either typhoid orhepatitis A vaccine) resulting in a 57% coveragerate. Vaccine uptake varied from as high as 80% inthe high-coverage area to as low as 42% in the low-
Total popul(n=285,155
Individuals atteschools within H(n=56,076)
Participated in the vaccination campaign(n=32,267)
Excluded: Students living in boardinghouses (socioeconomic data are not available) (n=359)
Analyzed (n=31,908)
Fig. 2. CONSORT diagram for the flow of subjects in the typhoid Vi p
2003.
coverage area (Table 1). There were four prominentclusters of high vaccine coverage, all located in theperiphery of the study area. In contrast, the low-coverage areas were located in the central part ofthe study area where most of the hospitals andprivate practitioners are located (Fig. 3).
The descriptive statistics of the study variables arepresented in Table 2, and the results of the cross-classified multi-level model that included individualand ecological variables are given in Table 3.Vaccine uptake was higher in female students, andstudents whose household head was younger, male,or non-literate (no or o6 years of schooling) thanthose of non-participated children, and differencesare statistically significant (po.01). Vaccine uptakein students from households with higher per-capitaincome was significantly lower (po.01) than stu-dents from lower per-capita income households.Students living in the south of the Perfume Riverhad significantly higher vaccine uptake (po.01)compared to students living in the north of the river.At ecological level, the higher the distance to the
ation )
ndingue City
Did not participate in the vaccination campaign (n=23,809)
Excluded: Students living in boarding houses (socioeconomic data are not available) (n=49)
Analyzed (n=23,760)
olysaccharide vaccine efficacy evaluation project in Hue, Vietnam,
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Table 1
The metadata of the low and the high vaccine-coverage areas in Hue, Vietnam, 2003
Metadata Low-coverage areas High-coverage areas
Number of household points 1788 1947
Percent of total household points 18.0 20.0
Number of geographic clusters 4 10
Total area (km2) 6.63 29.54
Percent area of the total study area 9.2 41.1
Target population 11,996 6560
Number of vaccines (typhoid or hepatitis A) 5034 5265
Coverage rate (%) 42.0 80.2
M. Ali et al. / Health & Place 13 (2007) 577–587 583
hospital from household the higher the uptake wasnoticed, which is statistically significant (po.01).
In the sub-area analysis, student’s age andhousehold per-capita income were found statisti-cally significant both in high- and low-coverageareas; the lower the age or the per-capita incomethe higher the vaccine uptake. Additionally, inlow-coverage areas, vaccine uptake was significantlyhigher (p ¼ .02) in students whose household headwere male compared to students whose familyhead were female. However, this was not true inthe high-coverage areas. In contrast, typhoidincidence rates in the neighborhood and thedistance to school from resident played significantrole in vaccine uptake among students living in thehigh vaccine-coverage areas. In these areas, vaccineuptake was higher in students from low typhoidincidence neighborhoods and from shorterdistance to school than the students from highertyphoid incidence neighborhoods or longer schooldistance.
Discussion
The results of our analysis illustrate that vaccine(typhoid or hepatitis A as active control agent)uptake by the students of Hue, Vietnam, wasinfluenced by a variety of factors including indivi-dual characteristics, household socioeconomic sta-tus, and ecological variables. Some predictors ofvaccine uptake varied between low- and high-coverage areas and by geographic scale, suggestingthat vaccine uptake is influenced by ecologicdifferences across neighborhoods irrespective ofthe school of attendance. With such geographicvariations of the predictors of vaccine uptake in thestudy area, a global solution may not be applicableto resolve problems of lower vaccine coverageduring vaccine trials in similar setting.
The negative association of vaccine uptake withhousehold economic condition may suggest thatpoorer families considered the campaign as anopportunity to get free vaccines. Vaccine coverageappeared to be inversely related to household head’sliteracy. This finding could be confounded with thehousehold economic condition, as we observed ahousehold with non-literate head had significantlylower per-capita household income than theircounterpart (results not shown), and the vaccineuptake was lower in students with higher per-capitahousehold income. Younger parents were keen tovaccinate their children, which is promising. Sur-rounding the vaccination campaign was a publicdebate regarding the risks and benefits of participa-tion in the vaccination campaign. Informationprovided to parents as part of the informed consentprocess was discussed in the local newspaper andmay have resulted in less enthusiasm amongeconomically well-off households.
The positive relationship between vaccine uptakeand hospital/polyclinic distance may be viewed asan indication of the health-seeking behavior of thecommunity. Since typhoid was not a major threat inHue City, people who lived near healthcare facilitiesmight not have worried about typhoid-illnessprevention as treatment was readily availablenearby. In contrast, those who lived far fromhospitals/polyclinics might have considered thevaccination program an opportunity to protecttheir children against typhoid illness, as accessibilityto healthcare is cumbersome for them.
The inverse relationship between student’s ageand vaccine uptake in the sub-area analysis may berelated to perceptions of typhoid illness amongthose subpopulations. If typhoid fever is thought ofas a disease of young children, it makes more senseto vaccinate younger children than older ones. Inthe high-coverage areas, the inverse relationship
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Fig. 3. Spatial pattern of vaccine coverage in a cluster randomized trial in Hue, Vietnam, 2003.
M. Ali et al. / Health & Place 13 (2007) 577–587584
between vaccine uptake and typhoid incidence ratesis contrary to our perception, as we expected highervaccine uptake in the higher typhoid incidenceareas.
We have identified several factors that seem toaffect vaccine uptake among students of the HueCity of Vietnam. These factors vary locally withinthe study area, and may be calling for a locally
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Table 2
Descriptive statistics of the study variables for predicting vaccine uptake in cluster randomized trial in Hue, Vietnam, 2003
Independent variables Entire study area Low-coverage areas High-coverage areas
Vaccinated
(n ¼ 31,908)
Not
vaccinated
(n ¼ 23,760)
Vaccinated
(n ¼ 5034)
Not
vaccinated
(n ¼ 6962)
Vaccinated
(n ¼ 5265)
Not
vaccinated
(n ¼ 1295)
Student age (mean, years) 10.62 11.69 10.93 11.63 10.46 12.00
Male students (%) 36.63 35.85 33.97 33.75 40.70 43.40
Household head age (mean, years) 49.46 50.13 51.15 50.96 48.02 48.43
Male household heads (%) 72.13 69.44 66.96 65.40 79.81 82.70
Household head literacy (X6 years of
schooling) (%)
62.84 71.18 74.75 77.64 57.40 65.10
Monthly per-capita household
income (mean, US dollar)
13.46 15.80 17.80 18.98 11.17 12.57
Household size (mean number of
people in the household)
6.09 5.97 6.13 5.93 5.78 5.64
Students living south of Perfume
River (%)
51.85 46.54 39.65 42.79 65.87 68.57
Had prior experienced with typhoid
fever (%)
0.13 0.21 0.14 0.17 0.04 0.08
Typhoid incidence rate in the
neighborhood (mean rate/10,000
people)a
0.83 0.85 0.63 0.62 0.20 0.21
Distance from nearest hospital (mean
kilometers)
1.24 0.99 0.65 0.64 2.44 2.39
Density of private practitioners in
neighborhood (mean density/10,000
people)a
1.52 2.03 3.37 3.49 0.07 0.08
Distance to school from student’s
residence (mean kilometers)
0.97 1.13 0.77 0.82 1.19 1.98
aNeighborhood was defined by a 500-m radius area around the household.
M. Ali et al. / Health & Place 13 (2007) 577–587 585
tailored campaign promotional program that couldbe useful for achieving good vaccine coverage. Thegeographic variations of vaccine coverage willeventually affect normal process of disease trans-mission in the study area, addressing of whichmay benefit vaccine effectiveness analysis. Manyvaccines confer herd protection. Even thoughthis has yet to be shown for Vi typhoid fevervaccine, it seems reasonable to expect people,vaccinated as well unvaccinated, to be exposedmore frequently in the low-coverage areas than inhigh-coverage areas. This could affect estimates ofprotective efficacy in individually randomized trialsat very low incidence rates and more so in clusterrandomized trials.
Limitations of the study
The study was originally designed to evaluateeffectiveness of a typhoid vaccine through a cluster-randomized trial delivering the vaccines (typhoid
fever and control agent) through a mass campaign,and not to identify the predictors of vaccine uptakein the campaign. In this study, we used availablehousehold socioeconomic data collected for thevaccine trial. Unlike real public health conditions todeliver vaccines, the campaign entailed informedconsent procedures at both community and indivi-dual levels. Such procedures might have influencedcommunity behavior in vaccine uptake. Furtherstudies including community behavior in vaccinetrial and health care would be useful.
The resulting map of vaccine coverage wasclassified in quintiles of household points. Onepotential problem of this classification method isthat since the features (household points) aregrouped by the number in each class, similarfeatures can be placed in adjacent classes or featureswith different values can be put in the same class.However, the classification method used here wasfound to the suitable over the other methodsavailable in the software (ArcMap, ESRIs Inc.).
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Table 3
Predictors of vaccine uptake in three multivariate models from the cluster randomized trial in Hue, Vietnam, 2003
Independent variables in
the model
Entire study area (n ¼ 55,668) Low-coverage areas (n ¼ 11,996) High-coverage areas (n ¼ 6560)
ORa p-value 95% CI ORa p-value 95% CI ORa p-value 95% CI
aMultivariate odds ratio for the cited variable in a model using multi-level cross-classified analysis with logit link function.bNeighborhood was defined by a 500-m radius area around the household.
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We had to exclude 408 students because they livedin school-boarding houses. In the census, thesestudents were identified as the members of school;thus no household socioeconomic data were col-lected for them. Since the coverage rate was veryhigh for those students (88%), including them couldhave some impact on the results of the analysis.
Acknowledgments
We thank GlaxoSmithKline for donating thevaccines for this project. This work was supportedby the Diseases of the Most Impoverished Program,funded by the Bill and Melinda Gates Foundation.We are grateful to the staff of the Hue PreventiveMedicine Center whose diligence and dedicationwere critical to the success of this project.
