Pathogen-Specific Impacts of the 2011–2012 La Niña-Associated Floods on Enteric Infections in the MAL-ED Peru Cohort: A Comparative Interrupted Time Series Analysis

Abstract

Extreme floods pose multiple direct and indirect health risks. These risks include contamination of water, food, and the environment, often causing outbreaks of diarrheal disease. Evidence regarding the effects of flooding on individual diarrhea-causing pathogens is limited, but is urgently needed in order to plan and implement interventions and prioritize resources before climate-related disasters strike. This study applied a causal inference approach to data from a multisite study that deployed broadly inclusive diagnostics for numerous high-burden common enteropathogens. Relative risks (RRs) of infection with each pathogen during a flooding disaster that occurred at one of the sites—Loreto, Peru—were calculated from generalized linear models using a comparative interrupted time series framework with the other sites as a comparison group and adjusting for background seasonality. During the early period of the flood, increased risk of heat-stable enterotoxigenic E. coli (ST-ETEC) was identified (RR = 1.73 [1.10, 2.71]) along with a decreased risk of enteric adenovirus (RR = 0.36 [0.23, 0.58]). During the later period of the flood, sharp increases in the risk of rotavirus (RR = 5.30 [2.70, 10.40]) and sapovirus (RR = 2.47 [1.79, 3.41]) were observed, in addition to increases in transmission of Shigella spp. (RR = 2.86 [1.81, 4.52]) and Campylobacter spp. (RR = 1.41 (1.01, 1.07). Genotype-specific exploratory analysis reveals that the rise in rotavirus transmission during the flood was likely due to the introduction of a locally atypical, non-vaccine (G2P[4]) strain of the virus. Policy-makers should target interventions towards these pathogens—including vaccines as they become available—in settings where vulnerability to flooding is high as part of disaster preparedness strategies, while investments in radical, transformative, community-wide, and locally-tailored water and sanitation interventions are also needed.

La Niña weather impacts dietary patterns and dietary diversity among children in the Peruvian Amazon

“…For example, children consumed significantly less servings of meat, fruits and vegetables, and grains (32) . Previous studies in Peru have shown that El Niño is associated with diarrhoeal incidence in Lima and reduced linear growth among children in coastal regions, and our findings suggest that La Niña affects dietary intake, which may negatively interact with differential burdens of diarrhoeal pathogens, resulting in greater-than-additive impacts on child linear growth (18,39,40) . Taken together, these studies and the presented analysis indicate that in addition to intra-annual (seasonal) shifts in diets and nutritional shifts due to weather, there are also inter-annual changes in diets and nutritional status due to weather also, which may be predicted and targeted through the use of ENSO indices.…”

“…This study aimed to explore the associations between ENSO exposure and food consumption patterns in the Peruvian Amazon from 2010 to 2014. During 2011-12, severe floods were observed during La Niña, and as a result, an estimated half of the study population was temporarily displaced (18) . Under La Niña conditions, there was decreased consumption of grains, rice, dairy and sugar, and increased consumption of plantains.…”

Understanding the Impact of Rainfall on Diarrhea: Testing the Concentration-Dilution Hypothesis Using a Systematic Review and Meta-Analysis

“…(1) Yes (2) Unable to test (1a) These associations were strongest for bacterial and all-cause diarrhea (1b) The strongest positive associations were 4-7 days after flood events (2) Studies often did not report the length of flood events in the literature 26 articles (Abu and Codjoe 2018, Cash et al 2014, Cesa et al 2016, Colston et al 2020, Deilami et al 2017, Fredrick et al 2015Gao et al 2016, Gertler et al 2015, Gong et al 2019, Jones et al 2016, Koley et al 2014, Liu X et al 2016, Liu Z et al 2018, Martinez et al 2016, Natuzzi et al 2016, Rosinger 2018, Saulnier et al 2018, Song Q et al 2018, Thompson et al 2015…”

Predicting social and health vulnerability to floods in Bangladesh

“…Flood forecasts have clear value; however, producing local-scale information may pose challenges in countries with limited resources; existing global-scale forecasts may be able to fill this role and should be evaluated (Alfieri et al, 2013;Emerton et al, 2018). Understanding the prospects for extending forecast lead times is also warranted and may facilitate more proactive disaster management practices (Coughlan de Perez et al, 2015). Finally, integrating more physical flood information and models to estimate the affected population may enhance flood impact predictions.…”