Seasonal variation in geographical access to maternal health services in regions of southern Mozambique

Abstract

BackgroundGeographic proximity to health facilities is a known determinant of access to maternal care. Methods of quantifying geographical access to care have largely ignored the impact of precipitation and flooding. Further, travel has largely been imagined as unimodal where one transport mode is used for entire journeys to seek care. This study proposes a new approach for modeling potential spatio-temporal access by evaluating the impact of precipitation and floods on access to maternal health services using multiple transport modes, in southern Mozambique.MethodsA facility assessment was used to classify 56 health centres. GPS coordinates of the health facilities were acquired from the Ministry of Health while roads were digitized and classified from high-resolution satellite images. Data on the geographic distribution of populations of women of reproductive age, pregnancies and births within the preceding 12 months, and transport options available to pregnant women were collected from a household census. Daily precipitation and flood data were used to model the impact of severe weather on access for a 17-month timeline. Travel times to the nearest health facilities were calculated using the closest facility tool in ArcGIS software.ResultsForty-six and 87 percent of pregnant women lived within a 1-h of the nearest primary care centre using walking or public transport modes respectively. The populations within these catchments dropped by 9 and 5% respectively at the peak of the wet season. For journeys that would have commenced with walking to primary facilities, 64% of women lived within 2 h of life-saving care, while for those that began journeys with public transport, the same 2-hour catchment would have contained 95% of the women population. The population of women within two hours of life-saving care dropped by 9% for secondary facilities and 18% for tertiary facilities during the wet season.ConclusionsSeasonal variation in access to maternal care should not be imagined through a dichotomous and static lens of wet and dry seasons, as access continually fluctuates in both. This new approach for modelling spatio-temporal access allows for the GIS output to be utilized not only for health services planning, but also to aid near real time community-level delivery of maternal health services.

Improving geographical accessibility modeling for operational use by local health actors

“…Second, we only considered a model of travel time by foot, which could lead to biases if part of the population travels to PHCs by vehicle. Other studies have indeed estimated travel time by vehicle in settings with good road networks [34,69], or by both foot and vehicle in low-resource settings [80]. In this context, less than 3% of the population of Ifanadiana has a vehicle, and there is only one paved road (< 1% of the…”

“…Geographical access to health care has been previously characterized in other contexts using a variety of methods [13,[34][35][36], aimed at estimating distance or travel time to reach health facilities for populations [37,38]. A common approach consists of estimating travel time through population surveys, but this method is resource-intensive and prone to biases related to subjective measures of time [23,26,34].…”

“…A common approach consists of estimating travel time through population surveys, but this method is resource-intensive and prone to biases related to subjective measures of time [23,26,34]. An alternative approach is the use of geomatics with available geographic information [39][40][41], either estimating Euclidean distance ("as the crow flies") or using more precise algorithms that account for terrain characteristics and road networks through friction surfaces [35,39,42,43]. To increase the adoption of geographic accessibility analyses into health planning, the WHO integrated those algorithms into an easy to use, freely available tool ("AccessMod") that includes multiple functionalities [44,45].…”

Guidelines for developing geographically sensitive mobile health applications

“…Wet and dry period access models were produced using "Modelbuilder in ArcGIS", using the closest facility and the route layer tools. The process for producing these models is highlighted in detail in [4].The location of the pregnant woman and that of the driver would be initiated from the mobile application where it is determined in real-time using the mobile inbuilt "Global Positioning System". The access model was published as a service on the ArcGIS Server hosted on "Microsoft Azure" cloud services.…”

“…However, distance is not the only factor that affects travel time. Long travel times due to poor road infrastructure and adverse weather conditions remain key geographic barriers to seek healthcare [4]. The condition of roads in rural regions in most LMICs deteriorates during the wet season due to precipitation and ooding, leaving many pregnant women more vulnerable to poor health outcomes as a result of delays in seeking care.…”