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How accurate are modelled birth and pregnancy estimates? Comparison of four models using high resolution maternal health census data in southern Mozambique

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dc.contributor.author Dube, Yolisa Prudence
dc.contributor.author Ruktanonchai, Corrine Warren
dc.contributor.author Sacoor, Charfudin
dc.contributor.author Tatem, Andrew J
dc.contributor.author Munguambe, Khatia
dc.contributor.author Boene, Helena
dc.contributor.author Vilanculo, Faustino Carlos
dc.contributor.author Sevene, Esperanca
dc.contributor.author Matthews, Zoe
dc.contributor.author von Dadelszen, Peter
dc.contributor.author Makanga, Prestige Tatenda
dc.date.accessioned 2021-06-07T13:37:48Z
dc.date.available 2021-06-07T13:37:48Z
dc.date.issued 2019
dc.identifier.issn 2059-7908
dc.identifier.uri https://gh.bmj.com/content/bmjgh/4/Suppl_5/e000894.full.pdf
dc.identifier.uri http://hdl.handle.net/11408/4394
dc.description.abstract Background Existence of inequalities in quality and access to healthcare services at subnational levels has been identified despite a decline in maternal and perinatal mortality rates at national levels, leading to the need to investigate such conditions using geographical analysis. The need to assess the accuracy of global demographic distribution datasets at all subnational levels arises from the current emphasis on subnational monitoring of maternal and perinatal health progress, by the new targets stated in the Sustainable Development Goals. Methods The analysis involved comparison of four models generated using Worldpop methods, incorporating regionspecific input data, as measured through the Community Level Intervention for Pre-eclampsia (CLIP) project. Normalised root mean square error was used to determine and compare the models’ prediction errors at different administrative unit levels. Results The models’ prediction errors are lower at higher administrative unit levels. All datasets showed the same pattern for both the live birth and pregnancy estimates. The effect of improving spatial resolution and accuracy of input data was more prominent at higher administrative unit levels. Conclusion The validation successfully highlighted the impact of spatial resolution and accuracy of maternal and perinatal health data in modelling estimates of pregnancies and live births. There is a need for more data collection techniques that conduct comprehensive censuses like the CLIP project. It is also imperative for such projects to take advantage of the power of mapping tools at their disposal to fill the gaps in the availability of datasets for populated areas. en_US
dc.language.iso en en_US
dc.publisher BMJ Publishing Group en_US
dc.relation.ispartofseries BMJ Global Health;Vol.4
dc.subject modelled birth and pregnancy estimates en_US
dc.subject high resolution maternal health census data en_US
dc.subject southern Mozambique en_US
dc.title How accurate are modelled birth and pregnancy estimates? Comparison of four models using high resolution maternal health census data in southern Mozambique en_US
dc.type Article en_US


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