NGO PIVOT, Ranomafana, Madagascar.
Department of Global Health and Social Medicine, Harvard Medical School, Boston, USA.
Int J Health Geogr. 2020 Jul 6;19(1):27. doi: 10.1186/s12942-020-00220-6.
Geographical accessibility to health facilities remains one of the main barriers to access care in rural areas of the developing world. Although methods and tools exist to model geographic accessibility, the lack of basic geographic information prevents their widespread use at the local level for targeted program implementation. The aim of this study was to develop very precise, context-specific estimates of geographic accessibility to care in a rural district of Madagascar to help with the design and implementation of interventions that improve access for remote populations.
We used a participatory approach to map all the paths, residential areas, buildings and rice fields on OpenStreetMap (OSM). We estimated shortest routes from every household in the District to the nearest primary health care center (PHC) and community health site (CHS) with the Open Source Routing Machine (OSMR) tool. Then, we used remote sensing methods to obtain a high resolution land cover map, a digital elevation model and rainfall data to model travel speed. Travel speed models were calibrated with field data obtained by GPS tracking in a sample of 168 walking routes. Model results were used to predict travel time to seek care at PHCs and CHSs for all the shortest routes estimated earlier. Finally, we integrated geographical accessibility results into an e-health platform developed with R Shiny.
We mapped over 100,000 buildings, 23,000 km of footpaths, and 4925 residential areas throughout Ifanadiana district; these data are freely available on OSM. We found that over three quarters of the population lived more than one hour away from a PHC, and 10-15% lived more than 1 h away from a CHS. Moreover, we identified areas in the North and East of the district where the nearest PHC was further than 5 h away, and vulnerable populations across the district with poor geographical access (> 1 h) to both PHCs and CHSs.
Our study demonstrates how to improve geographical accessibility modeling so that results can be context-specific and operationally actionable by local health actors. The importance of such approaches is paramount for achieving universal health coverage (UHC) in rural areas throughout the world.
在发展中国家的农村地区，医疗设施的地理位置可达性仍然是获得医疗服务的主要障碍之一。尽管存在用于建模地理可达性的方法和工具，但基本地理信息的缺乏阻止了它们在当地层面上针对目标计划的实施广泛使用。本研究的目的是开发一种非常精确、特定于背景的马鲁古地区医疗可达性估计方法，以帮助设计和实施改善偏远地区人群获得医疗服务的干预措施。
我们使用参与式方法在 OpenStreetMap（OSM）上绘制了所有路径、居民区、建筑物和稻田。我们使用开源路由机（OSMR）工具，从区中的每个家庭到最近的初级保健中心（PHC）和社区卫生站点（CHS）估算最短路径。然后，我们使用遥感方法获取高分辨率土地覆盖图、数字高程模型和降雨数据来模拟行驶速度。行驶速度模型是通过在 168 条步行路线样本中使用 GPS 跟踪获得的实地数据进行校准的。使用先前估算的所有最短路径的模型结果来预测前往 PHC 和 CHS 就诊的旅行时间。最后，我们将地理可达性结果集成到使用 R Shiny 开发的电子健康平台中。
我们在 Ifanadiana 区绘制了超过 100,000 座建筑物、23,000 公里的人行道和 4925 个居民区；这些数据在 OSM 上免费提供。我们发现，超过四分之三的人口居住在离 PHC 一小时以上的地方，10-15%的人口居住在离 CHS 一小时以上的地方。此外，我们在区的北部和东部发现了离最近的 PHC 超过 5 小时的地方，以及全区内处于弱势地位的人群，他们到 PHC 和 CHS 的地理可达性都很差（超过 1 小时）。
我们的研究展示了如何改进地理可达性建模，以便结果能够具有特定背景且对当地卫生行为者具有可操作性。在全世界农村地区实现全民健康覆盖（UHC）的过程中，这种方法的重要性至关重要。
