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| Home > Publications database > Application of geospatial analysis for mapping the distribution of severe maternal morbidities in eastern Ethiopia: The case of the Ethiopian obstetric surveillance system. |
| Home > Publications database > Application of geospatial analysis for mapping the distribution of severe maternal morbidities in eastern Ethiopia: The case of the Ethiopian obstetric surveillance system. |
| Journal Article | DKFZ-2026-00808 |
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2026
Wiley
Hoboken, NJ
Abstract: The disparity in maternal mortality and severe morbidity between high- and low-income countries is well established. Previously, we highlighted within-country disparities in Ethiopia using demographic and health survey data. This study used enhanced obstetric surveillance data to detect subnational hotspot areas and factors associated with disparities in severe maternal morbidity in eastern Ethiopia.This study used data from the Ethiopian Obstetric Surveillance System (EthOSS) study, which collected data for all women who experienced severe maternal morbidity in 13 hospitals in eastern Ethiopia between April 2021 and March 2022. Women whose geographical location was not recorded were excluded. We used optimized hotspot analysis to identify areas with higher rates of severe maternal morbidity while controlling for population density and conducted linear and geographically weighted regression analyses to assess factors associated with the distribution.Of all 2043 women with severe maternal outcomes, 1775 (87%) women with severe maternal morbidity with complete geographical information were included for analysis. Less than half (47%) lived within the recommended 2-h travel time to the nearest emergency obstetric and newborn care (EmONC) facility, with significant geographic variation. Hotspot analysis identified clusters of high rates near urban centers such as Dire Dawa and Harari even after controlling for the population density, while lower rates were found in eastern Oromia. Geographically weighted regression analysis showed that proximity to health facilities, especially to a basic or comprehensive EmONC facility, was associated with higher maternal complication rates.This study highlights the value of leveraging geocoded surveillance data to conduct geospatial analyses to uncover spatial patterns. We found a higher rate of severe maternal morbidity in the larger cities, indicating that the urban population had better access to care during obstetric complications, while rural and remote areas with limited access might fail to come to hospitals when complications arise or die at home or lower-level facilities.
Keyword(s): Ethiopia ; geospatial analysis ; maternal complications ; obstetric surveillance
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