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

Date Published: November 8, 2018

Publisher: Public Library of Science

Author(s): Kathleen A. Alexander, Alexandra K. Heaney, Jeffrey Shaman, Jonathan A. Patz

Abstract: BackgroundThe 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 findingsUsing 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.ConclusionsIn 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.

Partial Text: Across land types, the flow of water (ground water, surface water, and rainfall) has been demonstrated to influence infectious disease transmission dynamics across scales, from microbial to host levels [1–4]. Degradation of freshwater ecosystems and declines in water quality in surface water represent a growing public health threat across Africa [5]. Worldwide, degraded water quality, waterborne disease, and infectious diarrhea remain prominent and persistent concerns that are expected to worsen under future climate change projections [6,7]. In 2015, diarrheal disease was estimated to cause 1.31 million deaths per year [8]. Of these, nearly half a million deaths occurred in children under 5 years of age, with the greatest burden of disease focused in sub-Saharan Africa and South Asia [9,10]. Diarrheal disease in children can have lasting population effects, such as stunting and cognitive deficiencies [11]. Chronic oral exposure to fecal contaminates is also linked to environmental enteropathy, a subclinical disorder marked by chronic gut inflammation, small bowel structural change, decreased gut permeability, and gut immune dysfunction, which can influence oral vaccine efficacy [12]. The societal impact of diarrheal disease in children can be lasting, underscoring the need to advance our understanding of environmental couplings to develop effective public health strategies that will not only reduce current disease burdens but minimize future climate change impacts.

To analyze the relationships between variables, we used multimodel inference, which allowed quantification of model uncertainty among different candidate models and unconditional inference across those different models [23]. These methods permit inference of important predictor variables, estimation of the average effects of predictor variables on an outcome, and generation of multimodel weighted averaged predictions of that outcome.

IDSR weekly cases of under-5 diarrhea in Chobe District exhibited strong seasonal dynamics over the decade of observation (2007–2017), with 2 outbreaks occurring regularly each year (Fig 2). The first outbreak period occurred on average in late January during the wet season, and the second, in August during the dry season. The diarrheal attack rate was greater, on average, for dry season outbreaks (average number of cases = 615, SD = 333) than for wet season outbreaks (average number of cases = 407, SD = 232). The number of outpatient diarrhea cases reported per month (all ages) for the same area exhibited a similar seasonal pattern. As with under-5 diarrhea, the all-age outpatient attack rate tended to be higher on average in the dry season (average = 725, SD = 381) than in the wet season (average = 466, SD = 226).

Source:

http://doi.org/10.1371/journal.pmed.1002688

 

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