Population and Health Impact Surveillance Group, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya; Department of Public Health, Institute of Tropical Medicine, Antwerp.
Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
Geospat Health. 2024 May 27;19(1). doi: 10.4081/gh.2024.1266.
Google Maps Directions Application Programming Interface (the API) and AccessMod tools are increasingly being used to estimate travel time to healthcare. However, no formal comparison of estimates from the tools has been conducted. We modelled and compared median travel time (MTT) to comprehensive emergency obstetric care (CEmOC) using both tools in three Nigerian conurbations (Kano, Port-Harcourt, and Lagos). We compiled spatial layers of CEmOC healthcare facilities, road network, elevation, and land cover and used a least-cost path algorithm within AccessMod to estimate MTT to the nearest CEmOC facility. Comparable MTT estimates were extracted using the API for peak and non-peak travel scenarios. We investigated the relationship between MTT estimates generated by both tools at raster celllevel (0.6 km resolution). We also aggregated the raster cell estimates to generate administratively relevant ward-level MTT. We compared ward-level estimates and identified wards within the same conurbation falling into different 15-minute incremental categories (<15/15-30/30-45/45-60/+60). Of the 189, 101 and 375 wards, 72.0%, 72.3% and 90.1% were categorised in the same 15- minute category in Kano, Port-Harcourt, and Lagos, respectively. Concordance decreased in wards with longer MTT. AccessMod MTT were longer than the API's in areas with ≥45min. At the raster cell-level, MTT had a strong positive correlation (≥0.8) in all conurbations. Adjusted R2 from a linear model (0.624-0.723) was high, increasing marginally in a piecewise linear model (0.677-0.807). In conclusion, at <45-minutes, ward-level estimates from the API and AccessMod are marginally different, however, at longer travel times substantial differences exist, which are amenable to conversion factors.
谷歌地图导航应用程序接口（API）和 AccessMod 工具越来越多地被用于估计前往医疗保健机构的出行时间。然而，这些工具的估计值尚未进行正式比较。我们使用这两种工具，在尼日利亚的三个城市（卡诺、哈科特港和拉各斯）建模并比较了前往综合产科急诊（CEmOC）的中位数出行时间（MTT）。我们编译了 CEmOC 医疗机构、道路网络、海拔和土地覆盖的空间层，并在 AccessMod 中使用最小成本路径算法来估计到最近的 CEmOC 设施的 MTT。在高峰和非高峰出行场景中，使用 API 提取可比的 MTT 估计值。我们在栅格单元（分辨率为 0.6 公里）级别调查了这两种工具生成的 MTT 估计值之间的关系。我们还将栅格单元估计值汇总，以生成具有管理意义的行政区级 MTT。我们比较了行政区级别的估计值，并确定了属于同一城市的不同 15 分钟增量类别的行政区（<15/15-30/30-45/45-60/+60）。在卡诺、哈科特港和拉各斯，189、101 和 375 个行政区中，分别有 72.0%、72.3%和 90.1%被归类为同一 15 分钟类别。在 MTT 较长的行政区，一致性降低。在≥45 分钟的区域，AccessMod 的 MTT 比 API 长。在栅格单元级别，所有城市的 MTT 之间都存在很强的正相关（≥0.8）。线性模型的调整 R2 为 0.624-0.723，分段线性模型的 R2 略有增加（0.677-0.807）。总之，在<45 分钟时，API 和 AccessMod 的行政区级估计值略有不同，然而，在较长的出行时间，存在着显著的差异，可以通过转换因子来解决。
