Seasonal variation access to maternal health services at primary health care facilities (PHCs) in the CLIP study area in Mozambique. 49% of reproductive age women live within 1 hr walking time to PHCs in the dry season and this drops to 31% in the wet season, due to disruption of traffic infrastructure by rainfall and flooding
Mapping Outcomes for Mothers (MOM) was awarded a Stars in Global Health grant by Grand Challenges Canada to support “bold ideas with big impact.” The project aims to develop a mobile health (mHealth) application for use by community health workers to predict local maternal risk. Underpinned by the social determinants of health framework, maternal risk will be evaluated in four dimensions: maternal characteristics, health systems and services factors, socio-economic and environmental determinants. While community level factors (such as health systems and services factors and certain social and environmental variables) will inform individual maternal risk, the project will also develop an index for community resilience. Community resilience is described as the ability of a community to cope in the face of significant adversity and risk.
To display an integrated picture of local maternal health risk, MOM will use Geographic Information Systems (GIS) a uniquely integrative mix of hardware, software and analyses that enable spatial epidemiology, or the geo-visualization of the distribution and determinants of health phenomena. This will allow policy makers to take targetted and individualised action at the community level.
We developed a novel method for modeling geographical access to maternal health services. Access to care is a known determinant for adverse maternal outcomes and in our study region of southern Mozambique; perennial floods are known to isolate communities from health facilities. We took an approach of modeling spatio-temporal access by accounting for 1) the seasonal variation in access using empirical data on precipitation and floods, and 2) the daily transport realities that characterise women’s journeys in the study area, based on the transport options known to be available to them. The new access model further incorporates the realities of travel to health facilities through a design that respects the hierarchy of the facility referral network.
CLIP, GIS and Spatial Analysis
The risk and resilience models developed by MOM will be tested and recalibrated the other CLIP cRCT sites. GIS will facilitate the spatial and temporal characterization of maternal morbidity and mortality, as well as the structural, social, and environmental correlates known to be associated with adverse maternal outcomes. The resulting analyses would develop a framework that would model community‐specific risk profiles to assist local policy makers to prioritise efforts to address modifiable structural, social and environmental risks. Over the past year, contacts have been established with key mapping experts and agencies in the other CLIP sites.
The project, in collaboration with the Mozambique National Mapping Agency has also developed a set of guidelines that address some of the challenges around accessing good quality framework Geographical Information Systems (GIS) data. This work highlights the importance of manual digitalisation in generating meaningful spatial analyses in a typical data poor setting.
The core lessons learned from MOM were also shared with the First Nations Health Authority in British Columbia, Canada. This engagement is part of initiating a conversation on ‘reverse innovation’ how experiences from resource-poor settings can be translated to solve problems in high resource settings. Our work has informed discussion on addressing poor access to maternal health services, and high rates of maternal mortality in isolated First Nations communities in northern British Columbia.
A number of peer-reviewed papers related to the work in MOM have been accepted for publication and a number of other papers are currently in progress. Future work will involve using data from the CLIP Trials to further develop the MOM application, and move towards integrating it with the other suite of PRE-EMPT’s mobile tools, as part of an integrated platform.
- Makanga PT, Schuurman N, Sacoor C, Boene H, von Dadelszen P, Firoz T. Guidelines for creating framework data for GIS analysis in low‐and middle‐income countries. The Canadian Geographer/Le Géographe Canadien. 2016 Sep 1;60(3):320-32.
- Makanga PT, Schuurman N, von Dadelszen P, Firoz T. A scoping review of geographic information systems in maternal health. International Journal of Gynecology & Obstetrics. 2016 Apr 1.