PloS one · 2026
Seasonal trends and short-term association between meteorological factors and diarrheal diseases among children under five in Tanzania.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Mwing'a Gerald P, Shayo Mariana, Kimu Patrick, Beti Melkiory, Wadugu Boaz, Pashet Lameck, Juma Masoud A, Shirima Laura, Kuchaka Davis, Kumburu Happiness, Matemba Lucas, Kazyoba Paul E, Sindato Calvin, Lutambi Angelina M, Muro Florida, Mmbaga Blandina T, Alifrangis Michael, Aarestrup Frank M, Sonda Tolbert
Аннотация
UNLABELLED: 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.
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.