Hydrometeorology and flood pulse dynamics drive diarrheal disease outbreaks and increase vulnerability to climate change in surface-water-dependent populations: A retrospective analysis

Abstract

Background: The impacts of climate change on surface water, waterborne disease, and human health remain a growing area of concern, particularly in Africa, where diarrheal disease is one of the most important health threats to children under 5 years of age. Little is known about the role of surface water and annual flood dynamics (flood pulse) on waterborne disease and human health nor about the expected impact of climate change on surface-water-dependent populations.

Methods and findings: Using the Chobe River in northern Botswana, a flood pulse river-floodplain system, we applied multimodel inference approaches assessing the influence of river height, water quality (bimonthly counts of Escherichia coli and total suspended solids [TSS], 2011-2017), and meteorological variability on weekly diarrheal case reports among children under 5 presenting to health facilities (n = 10 health facilities, January 2007-June 2017). We assessed diarrheal cases by clinical characteristics and season across age groups using monthly outpatient data (January 1998-June 2017). A strong seasonal pattern was identified, with 2 outbreaks occurring regularly in the wet and dry seasons. The timing of outbreaks diverged from that at the level of the country, where surface water is largely absent. Across age groups, the number of diarrheal cases was greater, on average, during the dry season. Demographic and clinical characteristics varied by season, underscoring the importance of environmental drivers. In the wet season, rainfall (8-week lag) had a significant influence on under-5 diarrhea, with a 10-mm increase in rainfall associated with an estimated 6.5% rise in the number of cases. Rainfall, minimum temperature, and river height were predictive of E. coli concentration, and increases in E. coli in the river were positively associated with diarrheal cases. In the dry season, river height (1-week lag) and maximum temperature (1- and 4-week lag) were significantly associated with diarrheal cases. During this period, a 1-meter drop in river height corresponded to an estimated 16.7% and 16.1% increase in reported diarrhea with a 1- and 4-week lag, respectively. In this region, as floodwaters receded from the surrounding floodplains, TSS levels increased and were positively associated with diarrheal cases (0- and 3-week lag). Populations living in this region utilized improved water sources, suggesting that hydrological variability and rapid water quality shifts in surface waters may compromise water treatment processes. Limitations include the potential influence of health beliefs and health seeking behaviors on data obtained through passive surveillance.

Conclusions: In flood pulse river-floodplain systems, hydrology and water quality dynamics can be highly variable, potentially impacting conventional water treatment facilities and the production of safe drinking water. In Southern Africa, climate change is predicted to intensify hydrological variability and the frequency of extreme weather events, amplifying the public health threat of waterborne disease in surface-water-dependent populations. Water sector development should be prioritized with urgency, incorporating technologies that are robust to local environmental conditions and expected climate-driven impacts. In populations with high HIV burdens, expansion of diarrheal disease surveillance and intervention strategies may also be needed. As annual flood pulse processes are predominantly influenced by climate controls in distant regions, country-level data may be inadequate to refine predictions of climate-health interactions in these systems.

Fig 1. The study was conducted in northern Botswana in Southern Africa.

The Chobe River (blue line) is a transboundary waterway and 1 of only 3 perennial sources of water within Botswana, with water flow (light blue arrow) moving from the national park towards the urban areas, where the water treatment facility is located (blue X). Water quality samples were collected biweekly at established transect points (black triangles). Surface waters are abstracted to produce drinking water through centralized water treatment facilities and distributed to the population. Circles represent buildings color coded by the type of infrastructure (agricultural, commercial, residential, or tourism related; see legend). In this system, annual floods are driven by distant and regional wet season precipitation, with the largest input arising from floodwaters that occur in association with tropical rains in the upper watersheds of the Zambian and Angolan Highlands (inset, northern aspect of the Cuando-Chobe River Basin). The peak of the flood pulse arrives in the Chobe River at the end of the wet season/beginning of the dry season, after traversing more than 1,000 km from the highland areas.

Fig 2. Seasonal plots of all variables.

All plots represent the average weekly values across all years of data. The shaded portion represents the dry season, and the dashed black line is a cubic spline fit through the data to show seasonal trend. Average weekly number of under-5 diarrheal cases reported for 2007–2017 is shown in (A); (B—E) provide the average weekly values for environmental variables over the study period from January 2007 to June 2017 (full time series data are provided in S1 Fig), and (F) and (G) are average biweekly water quality measurements in the Chobe River for 2011–2017. CFU, colony-forming units; TSS, total suspended solids.

Fig 3. Dry season and wet season average coefficients and variable importance.

(A) Summary of multimodel inference predicting under-5 diarrhea. The rows of the tables represent each environmental variable at 1-, 4-, and 8-week lags. The columns of the tables represent different model selection criteria, i.e., average coefficient estimates for each environmental variable derived from different model subsets. The numbers in parentheses indicate the number of models that were averaged in a given model subset. Lastly, the shading indicates the weighted importance of each variable within the model subset, with 1 being the highest possible weighted importance. “NaN” indicates that a variable was not used in any of the models within a model subset. (A.1) shows results from the dry season, and (A.2) shows wet season results. (B and C) As for (A), but for models predicting E. coli and total suspended solids (TSS), respectively, with 0- and 4-week lags. Tmax, maximum temperature; Tmin, minimum temperature.

Fig 4. Schematic of rainfall and flood pulse influences on surface water quality and diarrheal disease outbreaks in a flood pulse river system.

In these systems, the flood pulse uniquely links aquatic and terrestrial habitats and microbial communities including potential pathogens. During the wet season (panel 1), rainfall moves fecal E. coli (a marker for fecal bacteria) overland from riparian areas into the river channel. As in-river E. coli increases, the number of diarrheal disease case reports increases in the population using municipal water that was obtained from the river (wet season outbreak). During this same period, seasonal pans are filled with rainfall, and water-dependent animals (wildlife and, to a lesser extent, livestock) move out of the riparian area into the interior to utilize forage and water resources. Floodwaters (panel 2) rise and inundate floodplains, incorporating fecal microbial communities on previously dry land areas. With progression of the dry season and no rainfall, water pans in the interior dry up, and water-dependent animals move back to the river’s edge, concentrating fecal material along river floodplains while utilizing the only permanent surface water in the system. Floodwaters begin to recede from the inundated land areas (panel 3), and TSS levels increase, as does the number of diarrheal case reports (dry season outbreak). In the rare event of rainfall in the dry season, E. coli levels in the water channel increase and are positively associated with diarrheal case reports (not shown). TSS, total suspended solids.

Fig 5. Schematic of linked processes across the aquatic—terrestrial interface in a flood pulse river—floodplain system like the Chobe River in Botswana.

Hydrological, geomorphological, sedimentary, and ecological processes influence fecal microbial dynamics, water quality, and human waterborne disease risk in surface-water-dependent populations. These interactions are coupled to sociocultural and economic processes, influencing landscape change and exposure to waterborne disease, feeding back to further environmental degradation and pathogen pollution potential.