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The seasonality of diarrheal pathogens: A retrospective study of seven sites over three years
Dennis L Chao1, Anna Roose2, Min Roh1
1Institute for Disease Modeling, Bellevue, Washington, United States of America.
Insights
Diarrheal pathogen seasonality varies by location, with rotavirus peaking in dry seasons and bacteria in rainy seasons. Understanding local patterns is crucial for controlling pediatric diarrhea in tropical regions.
Area of Science:
- Global Health
- Infectious Disease Epidemiology
- Environmental Health
Background:
- Pediatric diarrhea is a major cause of mortality in tropical, resource-limited settings.
- Seasonality of diarrheal pathogens is poorly understood in these high-burden regions.
- Previous studies primarily focused on temperate climates.
Purpose of the Study:
- To analyze the seasonal prevalence of diarrheal pathogens in children with moderate-to-severe diarrhea (MSD).
- To investigate the association between pathogen seasonality and local weather patterns across multiple sites.
- To assess the consistency of pathogen seasonality across different geographical locations.
Main Methods:
- Retrospective analysis of data from the Global Enteric Multicenter Study (GEMS).
- Utilized signal processing for pathogen seasonality analysis.
- Applied machine learning to define site-specific weather-based seasons and correlate with pathogen prevalence.
Main Results:
- Pathogen seasonality varied across study sites, with no universal pattern observed.
- Rotavirus prevalence peaked during drier, cooler months ('winter').
- Bacterial pathogens showed increased prevalence during hotter, wetter periods ('monsoon'/'rainy'/'summer' seasons).
Conclusions:
- Diarrheal pathogen epidemiology is complex and site-specific, necessitating local data for understanding.
- Local weather patterns are associated with the prevalence of specific diarrheal pathogens.
- Understanding local seasonality can inform targeted control strategies and clinical diagnosis in vulnerable populations.
Background:
Pediatric diarrhea can be caused by a wide variety of pathogens, from bacteria to viruses to protozoa. Pathogen prevalence is often described as seasonal, peaking annually and associated with specific weather conditions. Although many studies have described the seasonality of diarrheal disease, these studies have occurred predominantly in temperate regions. In tropical and resource-constrained settings, where nearly all diarrhea-associated mortality occurs, the seasonality of many diarrheal pathogens has not been well characterized. As a retrospective study, we analyze the seasonal prevalence of diarrheal pathogens among children with moderate-to-severe diarrhea (MSD) over three years from the seven sites of the Global Enteric Multicenter Study (GEMS), a case-control study. Using data from this expansive study on diarrheal disease, we characterize the seasonality of different pathogens, their association with site-specific weather patterns, and consistency across study sites.
Methodology/Principal Findings:
Using traditional methodologies from signal processing, we found that certain pathogens peaked at the same time every year, but not at all sites. We also found associations between pathogen prevalence and weather or "seasons," which are defined by applying modern machine-learning methodologies to site-specific weather data. In general, rotavirus was most prevalent during the drier "winter" months and out of phase with bacterial pathogens, which peaked during hotter and rainier times of year corresponding to "monsoon," "rainy," or "summer" seasons.
Conclusions/Significance:
Identifying the seasonally-dependent prevalence for diarrheal pathogens helps characterize the local epidemiology and inform the clinical diagnosis of symptomatic children. Our multi-site, multi-continent study indicates a complex epidemiology of pathogens that does not reveal an easy generalization that is consistent across all sites. Instead, our study indicates the necessity of local data to characterizing the epidemiology of diarrheal disease. Recognition of the local associations between weather conditions and pathogen prevalence suggests transmission pathways and could inform control strategies in these settings.
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