{"title":"Temperature and humidity as drivers for the transmission of zoonotic diseases","authors":"Li Zhang, Chenrui Lv, Wenqiang Guo, Zhenzhuo Li","doi":"10.1002/aro2.75","DOIUrl":null,"url":null,"abstract":"<p>Zoonotic diseases remain a persistent threat to global public health. Many major zoonotic pathogens exhibit seasonal patterns associated with climatic variations. Quantifying the impacts of environmental variables such as temperature and humidity on disease transmission dynamics is critical for improving prediction and control measures. This review synthesizes current evidence on the relationships between temperature and humidity and major zoonotic diseases, including malaria, dengue, rabies, anisakiasis, and influenza. Overall, this review highlighted some overarching themes across the different zoonotic diseases examined. Higher temperatures within suitable ranges were generally associated with increased transmission risks, while excessively high or low temperatures had adverse effects. Humidity exhibited complex nonlinear relationships, facilitating transmission in certain temperature zones but inhibiting it in others. Heavy rainfall and high humidity were linked to vector-borne disease outbreaks such as malaria by enabling vector breeding. However, reduced incidence of some diseases like dengue fever was observed with high rainfall. To address existing knowledge gaps, future research efforts should prioritize several key areas: enhancing data quality through robust surveillance and the integration of high-resolution microclimate data; standardizing analytical frameworks and leveraging advanced methodologies such as machine learning; conducting mechanistic studies to elucidate pathogen, vector, and host responses to climatic stimuli; adopting interdisciplinary approaches to account for interacting drivers; and projecting disease impacts under various climate change scenarios to inform adaptation strategies. Investing in these research priorities can propel the development of evidence-based climate-aware disease prediction and control measures, ultimately safeguarding public health more effectively.</p>","PeriodicalId":100086,"journal":{"name":"Animal Research and One Health","volume":"2 3","pages":"323-336"},"PeriodicalIF":0.0000,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aro2.75","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Animal Research and One Health","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/aro2.75","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Zoonotic diseases remain a persistent threat to global public health. Many major zoonotic pathogens exhibit seasonal patterns associated with climatic variations. Quantifying the impacts of environmental variables such as temperature and humidity on disease transmission dynamics is critical for improving prediction and control measures. This review synthesizes current evidence on the relationships between temperature and humidity and major zoonotic diseases, including malaria, dengue, rabies, anisakiasis, and influenza. Overall, this review highlighted some overarching themes across the different zoonotic diseases examined. Higher temperatures within suitable ranges were generally associated with increased transmission risks, while excessively high or low temperatures had adverse effects. Humidity exhibited complex nonlinear relationships, facilitating transmission in certain temperature zones but inhibiting it in others. Heavy rainfall and high humidity were linked to vector-borne disease outbreaks such as malaria by enabling vector breeding. However, reduced incidence of some diseases like dengue fever was observed with high rainfall. To address existing knowledge gaps, future research efforts should prioritize several key areas: enhancing data quality through robust surveillance and the integration of high-resolution microclimate data; standardizing analytical frameworks and leveraging advanced methodologies such as machine learning; conducting mechanistic studies to elucidate pathogen, vector, and host responses to climatic stimuli; adopting interdisciplinary approaches to account for interacting drivers; and projecting disease impacts under various climate change scenarios to inform adaptation strategies. Investing in these research priorities can propel the development of evidence-based climate-aware disease prediction and control measures, ultimately safeguarding public health more effectively.