In 2017, diarrheal diseases were responsible for 1.57 million deaths, of which 534 000 concerned children under 5-years (GBD, 2017; Troeger et al. 2020). This situation is due to domestic and recreational use of polluted surface waters, deficits in hygiene, access to healthcare and drinking water, and to weak environmental and health monitoring infrastructures. The highest health burden, 606 024 deaths, occurs in Sub-Saharan Africa where only 56.8% of the population has currently access to piped water, mainly in urban center (Reiner et al. 2018). In this region, in 2017, 85 million people, the large majority of whom live in rural areas, were still using unfiltered surface water as their drinking and domestic water source and 29% of the rural population practice open defecation (JMP, 2019). Moreover, climate change is expected to impact water resources both in quantity and quality and to potentially boost the presence, dissemination and transmission of pathogens (Carlton et al. 2014, 2016). The resulting impact of climate change is expected to increase the relative risk of diarrhea illness in the tropics and subtropics: 8% to 11% by 2010-2039 and 22% to 29% by 2070-2099 (Kolstad & Johansson, 2011). Furthermore, the extension of cultivated areas promotes surface runoff that increases suspended particulate matter (SPM, Robert et al. 2016, 2017) and possibly microbial pathogens occurrences in surface waters (Rochelle-Newall et al. 2015; Cecchi et al. 2020). Finally, Sub-Saharan Africa is undergoing major changes in terms of demographic growth especially in rural areas (Mercandalli & Losch, 2018) and political insecurity. All of these factors challenge access to clean water and healthcare and highlight the need to monitor water quality at the large scale.
In the study area located in Burkina Faso, diarrheal diseases represent the 3rd cause of consultation, with children under 5 years old the most impacted.
The most common diarrheal diseases are caused by the presence of microorganisms (bacteria, viruses) in surface water. Escherichia coli (E. coli) is an indicator for the enteric pathogens that cause many diarrheal diseases. The links between E. coli, diarrheal diseases and environmental parameters have not received much attention in West Africa. This case study, carried out Bagre Reservoir, aims at filling this knowledge gap by analyzing the environmental variables that play a role in the dynamics of E. coli, and cases of diarrhea (Robert et al. 2021).
A particular focus is given to satellite-derived parameters to assess whether remote sensing can provide a useful tool to assess health hazard: rainfall (GPM IMERGHHV6 data product), water level (Altimetry data from Jason-3), surface water reflectance and area, as well as NDVI (Sentinel 2), Land Surface Temperature (MODIS LST 8-day composite data for daily and nightly overpasses). Indeed, tele-epidemiology appears as a powerful tool to study climate-environment-health relationship and to both understand and predict the spatio-temporal distribution of pathogens through the use of satellite data. Thus, the implementation of a tele-epidemiological project integrating environmental, microbiological and epidemiological variables will represent a major asset in regions where in situ measurements are scarce and where the impacts of climate change are most strongly felt (Niang et al. 2014).
Samples of surface water were routinely collected to measure E. coli, enterococci and suspended particulate matter (SPM) at a monitoring point (Kapore) during one year. In addition, satellite data were used to estimate precipitation, water level, Normalized Difference Vegetation Index (NDVI) and SPM. Monthly epidemiological data for cases of diarrhea from three health centers were also collected and compared with microbiological and environmental data.
A positive correlation between E. coli and enterococci in surface waters was found indicating that E. coli is an acceptable indicator of fecal contamination in this region.
E. coli and diarrheal diseases were strongly correlated with monsoonal precipitation, in situ SPM, and Near Infra-Red (NIR) band between March and November. Partial least squares regression showed that E. coli concentration was strongly associated with precipitation, Sentinel-2 reflectance in the NIR and SPM, and that the cases of diarrhea were strongly associated with precipitation, NIR, E. coli, SPM, and to a lesser extent with NDVI. Therefore intervention though public education/awareness should be increased as the rainy season approaches.
Moreover, E. coli dynamics were reproduced using satellite data alone, particularly from February to mid-December (R² = 0.60) as were cases of diarrhea throughout the year (R² = 0.76). This implies that tele-epidemiology approach through the use of satellite data could provide an important contribution to water quality monitoring, and thus contribute to the establishment of warning systems.
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