A Descriptive Analysis of the Scientific Literature on Meteorological and Air Quality Factors and COVID‐19. (20th July 2021)

• Record Type: Journal Article
• Authors: Quintana, Amanda V.; Clemons, Meredith; Hoevemeyer, Krista; Liu, Ann; Balbus, John
• Is Part Of: GeoHealth. Volume 5:Number 7(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-07-20
• Subjects: climate -- weather -- public health -- COVID‐19; Environmental health -- Periodicals; Electronic journals; Periodicals; 616.98
• DOI: 10.1029/2020GH000367
• Languages: English
• ISSNs: 2471-1403

Abstract

Abstract: The role of meteorological and air quality factors in moderating the transmission of SARS‐CoV‐2 and severity of COVID‐19 is a critical topic as an opportunity for targeted intervention and relevant public health messaging. Studies conducted in early 2020 suggested that temperature, humidity, ultraviolet radiation, and other meteorological factors have an influence on the transmissibility and viral dynamics of COVID‐19. Previous reviews of the literature have found significant heterogeneity in associations but did not examine many factors relating to epidemiological quality of the analyses such as rigor of data collection and statistical analysis, or consideration of potential confounding factors. To provide greater insight into the current state of the literature from an epidemiological standpoint, the authors conducted a rapid descriptive analysis with a strong focus on the characterization of COVID‐19 health outcomes and use of controls for confounding social and demographic variables such as population movement and age. We have found that few studies adequately considered the challenges posed by the use of governmental reporting of laboratory testing as a proxy for disease transmission, including timeliness and consistency. In addition, very few studies attempted to control for confounding factors, including timing and implementation of public health interventions and metrics of population compliance with those interventions. Ongoing research should give greater consideration to the measures used to quantify COVID‐19 transmission and health outcomes as well as how to control for the confounding influences of public health measures and personal behaviors. Plain Language Summary: The role of meteorological and air quality factors in the transmission of SARS‐CoV‐2 is a critical topic. Studies conducted in early 2020 suggested that temperature, humidity, ultraviolet radiation, and other meteorological factors have an influence on the spread of COVID‐19. While previous literature reviews varying results, most of them did not focus on how well studies were designed. To provide greater insight into these concerns about study design, the authors conducted a rapid descriptive analysis focusing on how studies dealt with issues with health data and the influence, known as "confounding", of important factors other than meteorological and air quality factors, such as social factors and public health measures. We found few studies adequately considered the challenges posed by the use of laboratory testing as a proxy for disease transmission. In addition, very few studies attempted to control for confounding factors, including timing and implementation of public health interventions and metrics of population compliance with those interventions. Ongoing research should give greater consideration to the measures used to quantify COVID‐19 transmission and health outcomes as well as how to control for the confounding influences of public health measures and personal behaviors. Key Points: The 61 peer‐reviewed epidemiological studies described in this analysis used a wide variety of methods to explore associations between meteorological and air quality factors and COVID‐19 health outcomes associated with the pandemic The majority of studies did not adequately account for temporal and geographic uncertainty when using proxy measures of SARS‐COV‐2 transmission, such as laboratory testing reports Future studies should appropriately account for assumptions about transmission timing and control for a baseline set of confounders