RT Journal Article
SR Electronic
T1 How accurate are modelled birth and pregnancy estimates? Comparison of four models using high resolution maternal health census data in southern Mozambique
JF BMJ Global Health
JO BMJ Global Health
FD BMJ Publishing Group Ltd
SP e000894
DO 10.1136/bmjgh-2018-000894
VO 4
IS Suppl 5
A1 Dube, Yolisa Prudence
A1 Ruktanonchai, Corrine Warren
A1 Sacoor, Charfudin
A1 Tatem, Andrew J
A1 Munguambe, Khatia
A1 Boene, Helena
A1 Vilanculo, Faustino Carlos
A1 Sevene, Esperanca
A1 Matthews, Zoe
A1 von Dadelszen, Peter
A1 Makanga, Prestige Tatenda
A1 
YR 2019
UL http://gh.bmj.com/content/4/Suppl_5/e000894.abstract
AB 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 region-specific 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.