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A review of geospatial methods for population estimation and their use in constructing reproductive, maternal, newborn, child and adolescent health service indicators

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dc.contributor.authorNilsen, Kristineen
dc.contributor.authorTejedor-Garavito, Nataliaen
dc.contributor.authorLeasure, Douglas R.en
dc.contributor.authorUtazi, C. Edsonen
dc.contributor.authorRuktanonchai, Corrine W.en
dc.contributor.authorWigley, Adelle S.en
dc.contributor.authorDooley, Claire A.en
dc.contributor.authorMatthews, Zoeen
dc.contributor.authorTatem, Andrew J.en
dc.date.accessioned2023-01-17T20:10:47Zen
dc.date.available2023-01-17T20:10:47Zen
dc.date.issued2021-09-01en
dc.date.updated2023-01-16T15:50:18Zen
dc.description.abstractBackground: Household survey data are frequently used to measure reproductive, maternal, newborn, child and adolescent health (RMNCAH) service utilisation in low and middle income countries. However, these surveys are typically only undertaken every 5 years and tend to be representative of larger geographical administrative units. Investments in district health management information systems (DHMIS) have increased the capability of countries to collect continuous information on the provision of RMNCAH services at health facilities. However, reliable and recent data on population distributions and demographics at subnational levels necessary to construct RMNCAH coverage indicators are often missing. One solution is to use spatially disaggregated gridded datasets containing modelled estimates of population counts. Here, we provide an overview of various approaches to the production of gridded demographic datasets and outline their potential and their limitations. Further, we show how gridded population estimates can be used as alternative denominators to produce RMNCAH coverage metrics in combination with data from DHMIS, using childhood vaccination as examples. Methods: We constructed indicators on the percentage of children one year old for diphtheria, pertussis and tetanus vaccine dose 3 (DTP3) and measles vaccine dose (MCV1) in Zambia and Nigeria at district levels. For the numerators, information on vaccines doses was obtained from each country’s respective DHMIS. For the denominators, the number of children was obtained from 3 different sources including national population projections and aggregated gridded estimates derived using top-down and bottom-up geospatial methods. Results: In Zambia, vaccination estimates utilising the bottom-up approach to population estimation substantially reduced the number of districts with > 100% coverage of DTP3 and MCV1 compared to estimates using population projection and the top-down method. In Nigeria, results were mixed with bottom-up estimates having a higher number of districts > 100% and estimates using population projections performing better particularly in the South. Conclusions: Gridded demographic data utilising traditional and novel data sources obtained from remote sensing offer new potential in the absence of up to date census information in the estimation of RMNCAH indicators. However, the usefulness of gridded demographic data is dependent on several factors including the availability and detail of input data.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier370 (Article number)en
dc.identifier.doihttps://doi.org/10.1186/s12913-021-06370-yen
dc.identifier.eissn1472-6963en
dc.identifier.issn1472-6963en
dc.identifier.issueSuppl 1en
dc.identifier.orcidRuktanonchai, Corrine [0000-0002-7889-3473]en
dc.identifier.other10.1186/s12913-021-06370-y (PII)en
dc.identifier.pmid34511089en
dc.identifier.urihttp://hdl.handle.net/10919/113204en
dc.identifier.volume21en
dc.language.isoenen
dc.publisherSpringeren
dc.relation.urihttps://www.ncbi.nlm.nih.gov/pubmed/34511089en
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectDenominatorsen
dc.subjectGeospatial modellingen
dc.subjectGridded data setsen
dc.subjectRMNCAHen
dc.subjectSubnational estimationen
dc.subjectUniversal coverageen
dc.subjectPreventionen
dc.subjectVaccine Relateden
dc.subjectImmunizationen
dc.subjectPediatricen
dc.subjectReproductive health and childbirthen
dc.subject3 Good Health and Well Beingen
dc.subject.meshHumansen
dc.subject.meshMeasles Vaccineen
dc.subject.meshVaccinationen
dc.subject.meshFamilyen
dc.subject.meshAdolescenten
dc.subject.meshChilden
dc.subject.meshInfanten
dc.subject.meshInfant, Newbornen
dc.subject.meshIncomeen
dc.subject.meshAdolescent Health Servicesen
dc.titleA review of geospatial methods for population estimation and their use in constructing reproductive, maternal, newborn, child and adolescent health service indicatorsen
dc.title.serialBMC Health Services Researchen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherJournal Articleen
dcterms.dateAccepted2021-04-09en
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Veterinary Medicineen
pubs.organisational-group/Virginia Tech/Veterinary Medicine/Population Health Sciencesen

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