Diarrheal diseases are a major public health burden for children under five worldwide and remain an important cause of childhood morbidity and mortality in Tanzania. Globally, diarrheal illnesses account for hundreds of millions of cases and hundreds of thousands of deaths among under-fives annually; in Tanzania diarrhea contributes substantially to under-five mortality. Transmission of diarrheal pathogens is climate sensitive and influenced by meteorological conditions such as temperature, rainfall, and humidity. Temperature can increase pathogen proliferation in water and food, while heavy rainfall and flooding can overwhelm sanitation systems and contaminate water supplies. Conversely, drought may reduce water availability and compromise hygiene practices. Tanzania’s heterogenous climate includes regions with bimodal and unimodal rainfall regimes, which plausibly alter seasonal patterns of diarrheal disease.
This retrospective analysis used repeated cross-sectional surveillance data collected between 1 May 2023 and 30 April 2024 from ten selected healthcare facilities located across seven regions of Tanzania. Routine health records were obtained through the Seq-Tanzania project and stored within the District Health Information System 2 (DHIS2). Meteorological data for the same period were provided by the Tanzania Meteorological Authority (TMA) and linked to the health records for analysis. The authors applied a multilevel mixed-effects modelling approach to evaluate short-term associations between meteorological variables and childhood diarrhea.
The analysed sample comprised 898 children aged under five who attended the selected facilities during the study period. The median age was 13.9 months with an interquartile range of 8.8–25.3 months. Outcome measures and predictors reported in the available text include clinical surveillance-recorded diarrheal status, average monthly temperature, and total monthly rainfall. Sociodemographic covariates included child age and maternal education level; maternal primary education was associated with higher diarrheal prevalence in adjusted models. The source notes that data linkage procedures involved combining routine health information with meteorological records, but full technical details of linkage were not reported in the provided excerpt.
Seasonal patterns of childhood diarrhea varied by regional rainfall regime. In regions with a unimodal rainfall pattern (one rainy season annually with a prolonged dry season), the highest prevalence of childhood diarrhea occurred during the dry season (reported as 58%). In regions with a bimodal rainfall pattern (two rainy seasons annually), prevalence peaked during the wet season (reported as 41%). These contrasting seasonal peaks reflect how local climatology may shift the timing of highest diarrheal burden.
The authors fitted a multilevel mixed-effects Poisson regression model with a log link and robust standard errors to assess short-term associations between meteorological and sociodemographic factors and the prevalence of childhood diarrhea. The multilevel approach accounts for clustering by facility or region inherent in surveillance data. Specific model coefficients, measures of effect size, lag structures, or model fit statistics were not provided in the excerpt available for this rewrite.
Key findings reported include:
Higher average monthly temperature was significantly associated with increased prevalence of childhood diarrhea across the study regions.
Increased total monthly rainfall was also significantly associated with higher diarrheal prevalence.
Younger child age was associated with higher prevalence of diarrhea.
Maternal primary education level was associated with higher diarrheal prevalence compared with other maternal education categories in the final adjusted model.
Together, temperature and rainfall were identified as significant meteorological drivers of childhood diarrhea in both unimodal and bimodal rainfall regions of Tanzania.
The results support the view that short-term meteorological variability influences the occurrence of diarrheal diseases among children under five. The contrasting seasonal peaks between unimodal and bimodal rainfall regions indicate that interventions may need to be timed differently across climatic zones. The authors emphasise that integrating meteorological information into disease surveillance and public health planning could improve preparedness and enable more timely, location-appropriate interventions to reduce childhood diarrhea.
The available article excerpt notes that the data originate from the Seq-Tanzania project and are subject to data ownership and sharing agreements; de-identified data may be made available on request to the data custodian (Kilimanjaro Clinical Research Institute) subject to approvals. The excerpt does not include detailed model coefficients, confidence intervals, lagged exposure analyses, or other granular methodological specifics. Ethical approval details, the exact set of meteorological variables used beyond average monthly temperature and total monthly rainfall, and finer-grained descriptions of facility selection and data linkage procedures were not reported in the provided text.
In this retrospective surveillance analysis of ten Tanzanian health facilities (May 2023–April 2024), higher monthly temperature and greater monthly rainfall were significantly associated with increased prevalence of childhood diarrhea. Seasonal peaks differed by regional rainfall regime, with dry-season peaks in unimodal regions and wet-season peaks in bimodal regions. The authors recommend incorporating meteorological information into diarrheal disease surveillance and public health planning to support timely interventions; operational details for that integration and specific intervention strategies were not provided in the excerpt.