评估和比较用于预测腹泻病因的模型估计数据和直接观测的天气数据。

IF 2.5 4区 医学 Q3 INFECTIOUS DISEASES Epidemiology and Infection Pub Date : 2024-10-09 DOI:10.1017/S0950268824001183
Ben J Brintz, Josh M Colston, Sharia M Ahmed, Dennis L Chao, Benjamin F Zaitchik, Daniel T Leung
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引用次数: 0

摘要

中低收入国家在腹泻病因临床预测方面的最新进展表明,在临床数据中加入天气数据可提高预测效果。然而,气象数据的最佳来源仍不明确。我们旨在比较使用模型估计的卫星和地面观测数据与气象站直接观测数据对腹泻病因进行预测的效果。我们使用了一项针对中重度腹泻患儿的大型多中心研究中的临床和病原学数据来比较它们的预测性能。我们发现,这两种天气条件来源在大多数地方的表现相似。我们的结论是,虽然模型估计数据是公共卫生干预和疾病预测的可行、可扩展工具,但由于其易于获取,直接观测的气象站数据可能足以预测中低收入国家儿童的腹泻病因。
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Assessment and comparison of model estimated and directly observed weather data for prediction of diarrhoea aetiology.

Recent advances in clinical prediction for diarrhoeal aetiology in low- and middle-income countries have revealed that the addition of weather data to clinical data improves predictive performance. However, the optimal source of weather data remains unclear. We aim to compare the use of model estimated satellite- and ground-based observational data with weather station directly observed data for the prediction of aetiology of diarrhoea. We used clinical and etiological data from a large multi-centre study of children with moderate to severe diarrhoea cases to compare their predictive performances. We show that the two sources of weather conditions perform similarly in most locations. We conclude that while model estimated data is a viable, scalable tool for public health interventions and disease prediction, given its ease of access, directly observed weather station data is likely adequate for the prediction of diarrhoeal aetiology in children in low- and middle-income countries.

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来源期刊
Epidemiology and Infection
Epidemiology and Infection 医学-传染病学
CiteScore
4.10
自引率
2.40%
发文量
366
审稿时长
3-6 weeks
期刊介绍: Epidemiology & Infection publishes original reports and reviews on all aspects of infection in humans and animals. Particular emphasis is given to the epidemiology, prevention and control of infectious diseases. The scope covers the zoonoses, outbreaks, food hygiene, vaccine studies, statistics and the clinical, social and public-health aspects of infectious disease, as well as some tropical infections. It has become the key international periodical in which to find the latest reports on recently discovered infections and new technology. For those concerned with policy and planning for the control of infections, the papers on mathematical modelling of epidemics caused by historical, current and emergent infections are of particular value.
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