About: Abstract Little is known about the environmental conditions that drive the spatiotemporal patterns of SARS-CoV-2, and preliminary research suggests an association with weather parameters. However, the relationship with temperature and humidity is not yet apparent for COVID-19 cases in US cities first impacted. The objective of this study is to evaluate the association between COVID-19 cases and weather parameters in select US cities. A case-crossover design with a distributed lag nonlinear model was used to evaluate the contribution of ambient temperature and specific humidity on COVID-19 cases in select US cities. The case-crossover examines each COVID case as its own control at different time periods (before and after transmission occurred). We modeled the effect of temperature and humidity on COVID-19 transmission using a lag period of 7 days. A subset of 8 cities were evaluated for the relationship with weather parameters and 5 cities were evaluated in detail. Short-term exposure to humidity was positively associated with COVID-19 transmission in 4 cities. The associations were small with ¾ cities exhibiting higher COVID19 transmission with specific humidity that ranged from 6 to 9 g/kg. Our results suggest that weather should be considered in infectious disease modeling efforts and future work is needed over a longer time period and across different locations to clearly establish the weather-COVID19 relationship.   Goto Sponge  NotDistinct  Permalink

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  • Abstract Little is known about the environmental conditions that drive the spatiotemporal patterns of SARS-CoV-2, and preliminary research suggests an association with weather parameters. However, the relationship with temperature and humidity is not yet apparent for COVID-19 cases in US cities first impacted. The objective of this study is to evaluate the association between COVID-19 cases and weather parameters in select US cities. A case-crossover design with a distributed lag nonlinear model was used to evaluate the contribution of ambient temperature and specific humidity on COVID-19 cases in select US cities. The case-crossover examines each COVID case as its own control at different time periods (before and after transmission occurred). We modeled the effect of temperature and humidity on COVID-19 transmission using a lag period of 7 days. A subset of 8 cities were evaluated for the relationship with weather parameters and 5 cities were evaluated in detail. Short-term exposure to humidity was positively associated with COVID-19 transmission in 4 cities. The associations were small with ¾ cities exhibiting higher COVID19 transmission with specific humidity that ranged from 6 to 9 g/kg. Our results suggest that weather should be considered in infectious disease modeling efforts and future work is needed over a longer time period and across different locations to clearly establish the weather-COVID19 relationship.
Subject
  • Zoonoses
  • Viral respiratory tract infections
  • Climate
  • COVID-19
  • Information theory
  • Atmospheric thermodynamics
  • Occupational safety and health
  • Systems ecology
  • Physical quantities
  • Time series models
  • Humidity and hygrometry
  • Psychrometrics
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