Evidence map›Paper›PMID 32433685›Full record

ArticlePloS one2020

Disaggregated level child morbidity in Bangladesh: An application of small area estimation method.

Sumonkanti Das, Bappi Kumar, Luthful Alahi Kawsar

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Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Sumonkanti DasDepartment of Quantitative Economics, Maastricht University, Maastricht, The Netherlands.
Bappi KumarDepartment of Statistics, Shahjalal University of Science & Technology, Sylhet, Bangladesh.
Luthful Alahi KawsarDepartment of Statistics, Shahjalal University of Science & Technology, Sylhet, Bangladesh.ORCID 0000-0002-8010-6379

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute respiratory infection (ARI) and diarrhoea are two major causes of child morbidity and mortality in Bangladesh. National and regional level prevalence of ARI and diarrhoea are calculated from nationwide surveys; however, prevalence at micro-level administrative units (say, district and sub-district) is not possible due to lack of sufficient data at those levels. In such a case, small area estimation (SAE) methods can be applied by combining survey data with census data. Using an SAE method for the dichotomous response variable, this study aims to estimate the proportions of under-5 children experienced with ARI and diarrhoea separately as well as either ARI or diarrhoea within a period of two-week preceding the survey. The ARI and diarrhoea data extracted from Bangladesh Demographic and Health Survey 2011 are used to develop a random effect logistic model for each of the indicators, and then the prevalence is estimated adapting the World Bank SAE approach for the dichotomous response variable using a 5% sample of the Census 2011. The estimated prevalence of each indicator significantly varied by district and sub-district (1.4-11.3% for diarrhoea, 2.2-11.8% for ARI and 4.3-16.5% for ARI/diarrhoea at sub-district level). In many sub-districts, the proportions are found double of the national level. District and sub-district levels spatial distributions of the indicators might help the policymakers to identify the vulnerable disaggregated and remote hotspots. Particularly, aid industries can provide effective interventions at the highly vulnerable spots to overcome the gaps between micro and macro level administrative units.

Indexed as

BangladeshCensusesChildChild, PreschoolDiarrheaHealth SurveysHumansLogistic ModelsPrevalenceRespiratory Tract Infections

Identifiers

PMID32433685
PMCPMC7239471

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