Effect of precipitation on clinic-diagnosed enteric infections in children in Rwanda: an observational study. (May 2018)

• Record Type: Journal Article
• Authors: Kirby, Miles; Nagel, Corey; Uejio, Christopher; Okull, Phillip; Nsabimana, Jean Aime; Habyarimana, James; Clasen, Thomas
• Is Part Of: Lancet. Volume 2(2018)Supplement 1
• Page Start: S14
• Publication Date: 2018-05
• Subjects: Global environmental change -- Periodicals; Climatic changes -- Government policy -- Periodicals; Ecology -- Periodicals; Human ecology -- Periodicals; Public health administration -- Periodicals; 304.2
• DOI: 10.1016/S2542-5196(18)30099-8
• Languages: English
• ISSNs: 2542-5196

Abstract

Abstract: Background: Enteric infections are a major cause of morbidity and mortality in low-income and middle-income countries, particularly among children younger than 5 years. Climate change projections for Rwanda predict increases in average temperature, along with increases in total precipitation and frequency of extreme rainfall events. Previous research in Rwanda has found that extreme rainfall events increase the risk of contaminated drinking water, a substantial contributor to diarrhoea in this setting. Relatively little is known about the effect of precipitation on more severe clinic-diagnosed infections in rural, low-income settings such as Rwanda. In the context of a randomised controlled trial to assess the effect of a national environmental health campaign in Rwanda, we did a substudy to assess the effect of total and extreme rainfall on enteric infections in children younger than 5 years. Methods: For this observational study, we collected data from all government health facilities in Rusizi District, Western Province, for the year 2015. Patient data for children younger than 5 years from 150 study villages were extracted from paper-based registers. Gridded daily precipitation data were downloaded from the Tropical Applications of Meteorology using SATellite and ground based observations (TAMSAT) rainfall dataset in addition to local weather station data. We modelled the effect of total rainfall (in mm) and occurrence of an extreme rainfall event (95th percentile in the past 2 years) on daily health facility visits for enteric symptoms (diarrhoea, gastroenteritis, or vomiting), using Poisson regression with a Newey-West estimator to adjust for serial autocorrelation. We examined total and extreme rainfall within the previous 1, 2, 3, and 4 weeks, controlling for weekend day because we observed a consistent reduction in case counts on weekends. Findings: Data were extracted from 46 facilities, with a study catchment area of approximately 12 812 children younger than 5 years. Preliminary results showed 3530 cases of clinic-reported enteric symptoms in 2015, with an estimated annual incidence of 276 cases per 1000 children. Number of daily enteric visits were not significantly affected by preceding total rainfall or extreme events within the past 1, 2, 3, or 4 weeks using the TAMSAT dataset, and only slightly affected by total rainfall in the past 4 weeks using the weather station dataset (incidence rate ratio [IRR] 1·001, 95% CI 1·000–1·003; p=0·037). However, using the weather station dataset, a 10% increase in daily enteric cases occurred when an extreme rainfall event had occurred in the previous 3 weeks (IRR 1·121, 0·994–1·265; p=0·064), and an 18% increase occurred when an extreme event had occurred in the previous 4 weeks (IRR 1·184, 1·044–1·343; p=0·009). Interpretation: Clinic data from low-income settings are a rich and underused resource, which can have broad applications for improving planetary health at the household, community, and regional levels. These data add objectivity over self-reported conditions and capture the more serious outcomes that affect health-care systems. Our results are consistent with previous studies in showing increased risk of infections from rainfall events, probably due to flushed contaminants and water supply vulnerabilities. Understanding the effects and mechanisms of precipitation on infectious diseases can help inform the design of locally relevant intervention and adaptation strategies. Funding: The Bill & Melinda Gates Foundation