---
title: "Meteorological drivers of childhood diarrhea in Tanzania: seasonal patterns and short-term associa"
id: "plos-one-9-seasonal-trends-and-short-term-association-between-meteorological-factors-and"
canonical_url: "https://medichelpline.com/clinical-feed/plos-one-9-seasonal-trends-and-short-term-association-between-meteorological-factors-and"
content_type: "clinical_feed_article"
specialty: "Pediatrics"
source_name: "PLOS ONE (Medicine)"
source_url: "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0357174"
published_at: "2026-08-28T14:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Meteorological drivers of childhood diarrhea in Tanzania: seasonal patterns and short-term associa
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/plos-one-9-seasonal-trends-and-short-term-association-between-meteorological-factors-and
- **Specialty:** [Pediatrics](https://medichelpline.com/clinical-feed/pediatrics.md)
- **Primary Source:** PLOS ONE (Medicine)
- **Source URL:** [Original Journal Publication](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0357174)
- **Published At:** 2026-08-28T14:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- Childhood **diarrhea** remains a leading cause of morbidity and mortality in Tanzanian children under five and is climate-sensitive, with transmission influenced by temperature, rainfall and humidity. - This study analysed routine surveillance data from 10 healthcare facilities across seven Tanzanian regions between 1 May 2023 and 30 April 2024, linking health records with meteorological data from the Tanzania Meteorological Authority. - A total of 898 children under five were included; median age was 13.9 months (IQR 8.8–25.3 months). - Seasonal prevalence differed by regional rainfall regime: in **unimodal** rainfall regions the highest prevalence occurred in the dry season (58%), while in **bimodal** regions prevalence peaked in the wet season (41%). - Multilevel mixed-effects **Poisson regression** with robust standard errors was used to estimate short-term associations between meteorological factors and diarrheal prevalence. - Higher average monthly **temperature** and greater total monthly **rainfall** were significantly associated with higher prevalence of childhood diarrhea across both rainfall-pattern regions. - Younger child age and maternal primary education were additional sociodemographic factors associated with higher diarrheal prevalence in the final model. - The authors conclude that integrating meteorological information into diarrheal surveillance and public health planning could support timely interventions to reduce childhood diarrhea. - Data were drawn from the Seq-Tanzania project and stored in **DHIS2**; de-identified data access requires approval from the Seq-Tanzania project and KCRI. Funding was provided by DANIDA via the Seq-Tanzania project. - Details not reported in the source excerpt: full description of data linkage procedures, specific meteorological variables beyond monthly temperature and rainfall, model coefficients and effect sizes, and detailed ethical approval information were not provided in the available text.
## Clinical Analysis & Structured Key Points
Seasonal trends and short-term association between meteorological factors and diarrheal diseases among children under five in Tanzania | PLOS One Browse Subject Areas ? Click through the PLOS taxonomy to find articles in your field. For more information about PLOS Subject Areas, click here . Article Authors Metrics Comments Media Coverage Peer Review Reader Comments Figures Figures Abstract Childhood Diarrhea remains one of the leading causes of morbidity and mortality among children under five in Tanzania. Although meteorological factors are known to influence childhood diarrhea, evidence on their short-term associations across different regions of Tanzania remains limited. This study aimed to determine the seasonal prevalence of childhood diarrhea and its short-term associations with meteorological factors among children under five years in Tanzania between 1 May 2023 and 30 April 2024. Methodology This retrospective analysis of repeated cross-sectional surveillance data included children under five years attending 10 selected healthcare facilities across seven regions of Tanzania between 1 May 2023 and 30 April 2024. Routinely collected health data from the Seq-Tanzania project, stored in the District Health Information System 2 (DHIS2), were linked with meteorological data obtained from the Tanzania Meteorological Authority (TMA). A multilevel mixed-effects Poisson regression model with a log link and robust standard errors was fitted to identify the short-term associations between meteorological and sociodemographic factors and childhood diarrhea. Results A total of 898 children under five were included in the analysis, with a median age (IQR) of 13.9 (8.8–25.3) months. The prevalence of childhood diarrhea was highest during the dry season (58%) in regions experiencing unimodal rainfall patterns and during the wet season (41%) in the regions experiencing bimodal rainfall patterns. In the final multilevel mixed-effects Poisson regression model, higher average monthly temperature, increased total monthly rainfall, younger child age, and maternal primary education were significantly associated with the prevalence of childhood diarrhea. Conclusion Average monthly temperature and total monthly rainfall were significantly associated with the prevalence of childhood diarrhea across regions with both unimodal and bimodal rainfall patterns in Tanzania. These findings highlight the importance of integrating meteorological information into diarrheal disease surveillance and public health planning to support timely interventions aimed at reducing childhood diarrhea. Citation: Mwing’a GP, Shayo M, Kimu P, Beti M, Wadugu B, Pashet L, et al. (2026) Seasonal trends and short-term association between meteorological factors and diarrheal diseases among children under five in Tanzania. PLoS One 21(8): e0357174. https://doi.org/10.1371/journal.pone.0357174 Editor: James Colborn, Clinton Health Access Initiative, UNITED STATES OF AMERICA Received: July 24, 2025; Accepted: August 13, 2026; Published: August 28, 2026 Copyright: © 2026 Mwing’a et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: The data analysed in this study were obtained from the Seq-Tanzania project and are subject to data ownership and sharing agreements. Therefore, the authors are not permitted to deposit the dataset in a public repository. De-identified data may be made available upon request, subject to approval from the Seq-Tanzania project and the relevant institutional authorities, and in accordance with applicable ethical and data-sharing policies. Interested researchers may submit requests for data access, together with ethical approval, to the data custodian, the Kilimanjaro Clinical Research Institute (KCRI), via kcriadmin@kcri.ac.tz . Funding: This study was funded by the Danish International Development Agency (DANIDA) through the Seq-Tanzania project (Grant No. 20-12-TAN) to cover the costs of data collection. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. Background Diarrheal diseases remain a major public health challenge and are the second leading cause of childhood mortality worldwide, accounting for about 1.7 billion cases and 525,000 deaths in children under five, annually [ 1 ]. The disease contributes to approximately 9% of all under-five mortality worldwide, with nearly 90% occurring in Sub-Saharan Africa [ 2 ]. In Tanzania, diarrhea accounts for approximately 9% of all under-five mortality, positioning the country at number 10 among the 15 nations with the highest burden of diarrhea-related fatalities among children under five [ 3 ]. Children under five are particularly vulnerable because of their immature immune systems, increased exposure to environmental contaminants, and limited ability to protect themselves from adverse environmental conditions [ 4 ]. They are also less knowledgeable about the health effects of climate change, with less ability to remove themselves from the threat [ 4 ]. Diarrhea diseases are among the climate-sensitive diseases caused by bacterial, viral, and parasitic pathogens, which are transmitted primarily through the fecal–oral route [ 5 ]. Their transmission dynamics are influenced by meteorological factors, including humidity, rainfall and temperature [ 6 , 7 ]. Increased temperatures mostly enhance the proliferation of bacteria in water and food, prolong pathogen survival, and elevate the probability of an outbreak [ 8 ]. On the other hand, floods and heavy rainfall may overwhelm sanitation infrastructures and contaminate drinking water sources, while drought reduces water availability and compromises hygiene practices [ 9 ]. Climatic conditions such as warmer and humid conditions may also indirectly facilitate by favouring vectors such as flies and other insects that contribute to the spread of diarrheal pathogens. Tanzania experiences two distinct rainfall regimes: bimodal and unimodal rainfall patterns [ 10 , 11 ]. Bimodal regions receive two rainy seasons annually, from March to May, and from November to December, separated by the dry seasons between June and October, and January and February. In contrast, unimodal regions experience one rainy season from November to April, followed by a prolonged dry season from May to October [ 11 ]. These climatic differences may influence the seasonal distribution of childhood diarrhea across regions. Evidence from East Africa and other sub-Saharan African countries demonstrates that climatic variability plays an important role in the epidemiology of childhood diarrhea. Studies from Ethiopia have reported that increasing temperature and rainfall are associated with higher childhood diarrhea incidence, although the magnitude of these associations varies across ecological settings and seasons [ 7 , 12 ]. Similarly, studies conducted in Kenya have shown that climatic variability, together with socioeconomic factors and access to water, sanitation and hygiene (WASH) services, significantly influences childhood diarrhea [ 13 ]. Across sub-Saharan Africa, disparities in water supply, sanitation infrastructure, and hygiene practices further modify the relationship between climate variability and childhood diarrhea, particularly during periods of heavy rainfall and drought [ 14 , 15 ]. Previous studies have shown that seasonal variation, rainfall, and temperature influence childhood diarrhea, although the magnitude and direction of these associations vary across countries because of differences in geographical, climatic, socioeconomic, and hygiene conditions [ 16 – 21 ]. Despite this evidence, studies examining the seasonal prevalence and short-term associations between meteorological factors and childhood diarrhea across Tanzania’s diverse climatic zones remain limited. Understanding these relationships is important for strengthening disease surveillance, improving preparedness, and guiding timely public health interventions. Therefore, this study aimed to determine the seasonal prevalence of childhood diarrhea and its short-term associations with meteorological factors among children under five years in Tanzania. Materials and methods Data sources The dataset comprised routinely collected surveillance data from healthcare facilities participating in the Seq-Tanzania project. These data were prospectively collected during routine healthcare encounters between 1 May 2023 and 30 April 2024 and entered into the District Health Information System (DHIS2) managed by the Kilimanjaro Clinical Research Institute (KCRI). For the present study, the records were retrospectively extracted from DHIS2 on 3 June 2024 for secondary analysis. Daily rainfall (mm) and daily mean temperature (°C) were obtained from the Tanzania Meteorological Authority (TMA). Meteorological data, including daily average rainfall (mm) and daily mean temperature ( 0 C), were obtained from the Tanzania Meteorological Authority (TMA) for weather stations corresponding to each study region. Daily observations were aggregated into monthly average temperature and total monthly rainfall and linked to the health surveillance data using the healthcare facility location and month of patient presentation to evaluate short-term associations between weather conditions and childhood diarrheal diseases. Permission to access and analyse the surveillance data was obtained from the Seq-Tanzania project management and the Kilimanjaro Clinical Research Institute. The corresponding author was an authorised member of the Seq-Tanzania Project team and had permission to access the de-identified data for research purposes. Study design and settings The study was a retrospective analysis of a repeated cross-sectional study collected through the Seq-Tanzania project between 1 May 2023 and 30 April 2024. The Seq-Tanzania project integrated routinely collected health data from children under five years attending selected healthcare facilities with corresponding meteorological data obtained from the Tanzania Meteorological Authority (TMA) before storing the linked dataset in the District Health Information System 2 (DHIS2). The present study involved a secondary analysis of these linked surveillance data. The study was implemented in the seven regions of Tanzania, namely Kaskazini Unguja, Mjini Magharibi, Mwanza, Tanga, Dodoma, Tabora, and Mbeya, representing both unimodal and bimodal rainfall patterns. Ten healthcare facilities participating in the Seq-Tanzania surveillance project were purposively selected based on their geographical distribution, patient volume, laboratory capacity for molecular analyses, and ability to provide continuous surveillance data throughout the study period. These facilities were distributed across regions to capture the diversity of climatic conditions across Tanzania and facilitate the assessment of seasonal variations in childhood diarrheal diseases. Study population The study used data from the District Health Information System (DHIS2), which was extracted from the system on 03 June 2024. A total of 1361 participants were extracted from the system; of them, 457, who were aged greater than 60 months, and those with duplicate information (n = 6) were excluded. Therefore, each observation included in this study represents a cross-sectional assessment recorded at the time of the healthcare visit. The present analysis aggregated these repeated cross-sectional observations over 12 months to assess seasonal trends and short-term associations between climatic variables and childhood diarrhea. Thus, the analysis took place on a total of 898 children who met the inclusion criteria ( Fig 1 ). Download: PNG larger image TIFF original image Fig 1. The flow chart for the selection of the study participants. https://doi.org/10.1371/journal.pone.0357174.g001 Study variables Dependent (outcome) variable. The outcome variable was childhood diarrhea, assessed during routine healthcare visits using the standardised Seq-Tanzania surveillance tool. Trained healthcare workers interviewed parents or legal guardians and recorded diarrhea status (Yes/No) according to the World Health Organisation (WHO) case definition, defined as the passage of three or more loose or liquid stools within 24 hours [ 5 ]. The information was subsequently entered into the DHIS2 surveillance database for routine monitoring. Independent variables. Independent variables were classified based on the multilevel framework into individual-level and community-level (meteorological) variables based on biological plausibility and previous literature [ 22 – 24 ]. Individual-level variables included child age (months), sex, maternal education, mother’s hand washing practices, food preservation, exclusive breastfeeding, drinking water sources, latrine type, and type of residence. Drinking water sources were categorised as improved (covered hand-dug wells, Municipality water supply, private water tap/pump, public water tap/pump, protected home water, and harvesting rainwater) or unimproved (uncovered hand-dug wells, ponds, rivers/streams, and dams) according to established classification [ 25 , 26 ]. Residences were classified as formal or informal settlements based on the availability of basic infrastructure and services [ 27 ]. Community-level variables comprised monthly average temperature (°C) and total monthly rainfall (mm), obtained from regional meteorological stations through the Tanzania Meteorological Authority (TMA). Data management and statistical analysis Data were exported from the DHIS2 system into Microsoft Excel for quick view, cleaning and preliminary visualisation before being analysed using STATA version 17 software (StataCorp LLC, College Station, TX, USA). Descriptive statistics were applied to summarise participant characteristics, with Pearson’s chi-square test being used to compare the distributions of childhood diarrhea across categories of independent variables. Factors associated with childhood diarrhea were assessed using a multilevel mixed-effects Poisson regression model with a log link function and robust standard errors. Because childhood diarrhea was a common outcome (>10%), adjusted prevalence ratios (APR) were estimated instead of odds ratios, as prevalence ratios provide more accurate and interpretable measures of association for common outcomes. A healthcare facility was included as a random intercept to account for clustering of children within facilities. Fixed effects included child age (months), sex, maternal education level, breastfeeding status, drinking water source, monthly average temperature, and total monthly rainfall. Results were presented as adjusted prevalence ratios (APR) with 95% confidence intervals (CI). Model building followed a hierarchical approach. Model I was an empty (null) model containing only facility-level random effects. Model II included meteorological variables, Model III included individual-level variables, and Model IV included both meteorological and individual-level variables. Multicollinearity was assessed using the variance inflation factor (VIF), with values <10 indicating no evidence of problematic multicollinearity. The missing data were handled using a complete case analysis [ 28 ]. Model performance was evaluated using the Akaike Information Criterion (AIC), log-likelihood, deviance, intraclass correlation coefficient (ICC), and median prevalence ratio (MPR) [ 29 ]. The model with the lowest AIC and deviance and the highest log-likelihood was considered the best-fitting model. Statistical significance was assessed using a two-sided p-value <0.05. Ethical approval This study was a secondary analysis of routinely collected surveillance data from the Seq-Tanzania project. Ethical approval for the Seq-Tanzania project was obtained from the Tanzania National Institute for Medical Research’s Medical Research Coordinating Committee (Ref. No. NIMR/HQ/R.8a/Vol.IX/3859). During the original data collection, written informed consent was obtained from adult participants and from the parents or legal guardians of children, while assent was obtained from children where applicable. The present study analysed de-identified data and did not involve direct participant contact or collection of additional information. Permission to access and analyse the data was obtained from the Seq-Tanzania project and the relevant institutional authorities. Results Characteristics of study participants A total of 898 children under five were included in the analysis. The median age (IQR) was 13.9 (8.8–25.3) months, with 30.4% aged 6–11 months. More than half (57%) were male, and 90.9% had received the rotavirus vaccine. Among infants aged <6 months with available breastfeeding information, 62.9% were not exclusively breastfed for six months. Most households (90.6%) used improved drinking water sources, and 36.5% of mothers had completed primary education. During the study period, the mean monthly temperature was 24.3°C (SD ± 2.7; range: 18.5–31.2°C), while the mean total monthly rainfall was 110.4 mm (SD ± 145.2; range: 0–775.9 mm) ( Table 1 ). Download: PNG larger image TIFF original image Table 1. Characteristics of the study participants (N = 898). https://doi.org/10.1371/journal.pone.0357174.t001 Prevalence of childhood diarrhea by participant characteristics Overall, 622 of the 898 children under five (69.3%) had childhood diarrhea during the study period. The prevalence of childhood diarrhea differed significantly across age groups, maternal education levels, and drinking water sources (p < 0.05). Children aged 6–11 months, those whose mothers had college or higher education, and those from households using unimproved drinking water sources had the highest prevalence of childhood diarrhea ( Table 2 ). Download: PNG larger image TIFF original image Table 2. Prevalence of childhood diarrhea by participant characteristics (N = 898). https://doi.org/10.1371/journal.pone.0357174.t002 Seasonal prevalence of childhood diarrhea by rainfall pattern Among the 898 children, 437 (48.7%) resided in regions with unimodal rainfall patterns and 461 (51.3%) in regions with bimodal rainfall patterns. In the unimodal regions, childhood diarrhea was more prevalent during the dry season (58%; 95% CI: 53.3–62.8) than during the rainy season, with the Mbeya region contributing the highest regional prevalence (33.6%; 95% CI: 29.2–38.3). Conversely, in the bimodal regions, childhood diarrhea was highest during the rainy season (41%; 95% CI: 33.5–42.4), largely driven by the Mwanza region (27.1%; 95% CI: 23.1–31.4), followed by the Tanga and Mjini magharibi regions (approximately 7% each). No childhood diarrhea cases were recorded in Kaskazini Unguja during the rainy seasons ( Fig 2 ). Download: PNG larger image TIFF original image Fig 2. Seasonal prevalence of childhood diarrhea in regions with unimodal and bimodal rainfall patterns. https://doi.org/10.1371/journal.pone.0357174.g002 Seasonal trends of childhood diarrhea in relation to meteorological factors Regions with unimodal rainfall patterns. Fig 3 shows the monthly trends in childhood diarrhea alongside average monthly temperature and total monthly rainfall in the unimodal regions. The highest prevalence was observed in October (22%; 95% CI: 18.2–26.1%) during the dry season, predominantly in Mbeya region (18.1%; 95% CI: 14.6–22.0%), when the average monthly temperature was 26 0 C and rainfall was negligible. Higher temperatures coincided with increased childhood diarrhea prevalence, whereas diarrhea prevalence generally declined during months with increased rainfall, except for a slight increase obs
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