Persistence of geographic barriers to maternal care services following a health system strengthening initiative in rural Madagascar

Background Geographic access to healthcare continues to pose a significant challenge for pregnant women in rural areas of sub-Saharan Africa, resulting in consistently high rates of maternal mortality. Geographic barriers can persist even in settings where financial barriers have been reduced and health system strengthening (HSS) efforts are in place. The aim of this study is to combine analyses of a population-representative cohort and geolocated maternal consultation data at the village level to gain a precise understanding of spatiotemporal changes in the utilization of maternal care services in a rural district of Madagascar benefiting from HSS support. Methods We collected monthly information on antenatal care visits, deliveries and postnatal visits from the registries of 18 primary care health centers in Ifanadiana District, from 2016 to 2018. Similar data were collected from a district-representative cohort via surveys on over 1500 households done in 2016 and 2018. We estimated precise travel time from each village to the nearest health center to understand spatio-temporal variations in maternal care access, and to assess the impact of geographic barriers via statistical analyses. Results Women who lived within a one-hour walk from a health facility in the HSS catchment area had rates of per capita utilization of most maternal health services were roughly twice that those who lived 1-2 hours away and three times higher than those who lived over 2 hours away. The exception was the first antenatal care visit (ANC1), for which travel time had more modest effect. Improvements to primary care services due to HSS in this setting were only observed among women living within two hours from health centers. Statistical models revealed that women’s travel time from a health facility was the strongest determinant of maternal care service utilization. Conclusion This study shows how a combination of geo-located health system information and population-representative data can help assess the impact of geographical barriers to maternal care in rural areas of sub-Saharan Africa. It highlights that women who live more than 2 hours from a health facility had virtually no access to maternal health services despite efforts in place to reduce financial barriers to care and strengthen the health system. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by internal funding from NGO Pivot and Herrnstein Family Foundation. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study was approved by Madagascar National Ethics Committee (062-MSANP/CE and 041-MSANP/CERBM) and The Harvard Medical School Institutional Review Board. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data are available on OpenStreetMap () and on the Shinny app ()