AI Article Synopsis

  • Weather and climate significantly affect infectious disease outbreaks, and early warning systems using environmental data can help predict these events and guide resource allocation for public health.* -
  • Improved seasonal climate forecasting and understanding of disease exposure-response relationships allow for advance identification of conditions conducive to outbreaks, helping public health officials focus surveillance efforts.* -
  • While early warning systems for diseases like dengue and cholera exist, overall research in this area is lacking, and developing these systems could enhance early detection and proactive responses to potential health threats.*

Article Abstract

Purpose Of Review: Weather and climate influence multiple aspects of infectious disease ecology. Creating and applying early warning systems based on temperature, precipitation, and other environmental data can identify where and when outbreaks of climate-sensitive infectious diseases could occur and can be used by decision makers to allocate resources. Whether an outbreak actually occurs depends heavily on other social, political, and institutional factors.

Recent Findings: Improving the timing and confidence of seasonal climate forecasting, coupled with knowledge of exposure-response relationships, can identify prior conditions conducive to disease outbreaks weeks to months in advance of outbreaks. This information could then be used by public health professionals to improve surveillance in the most likely areas for threats. Early warning systems are well established for drought and famine. And while weather- and climate-driven early warning systems for certain diseases, such as dengue fever and cholera, are employed in some regions, this area of research is underdeveloped. Early warning systems based on temperature, precipitation, and other environmental data provide an opportunity for early detection leading to early action and response to potential pathogen threats, thereby reducing the burden of disease when compared with passive health indicator-based surveillance systems.

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Source
http://dx.doi.org/10.1007/s40572-018-0221-0DOI Listing

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