The effect of temperature, humidity, precipitation and cloud coverage on the risk of COVID-19 infection in temperate regions of the USA—A case-crossover study

• Published in: PloS one Vol. 17; no. 9; p. e0273511
• Main Authors: Jansson, Moritz K, Yamamoto, Shelby
• Format: Journal Article
• Language: English
• Published: San Francisco Public Library of Science 15.09.2022; Public Library of Science (PLoS)
• Subjects: Analysis; Climate; Cloud cover; Coronaviruses; COVID-19; Disease transmission; Earth Sciences; Engineering and Technology; Health risks; Humidity; Infections; Influenza; Medical research; Medicine and Health Sciences; Pandemics; Pathogens; Physical Sciences; Precipitation; Rain; Research and Analysis Methods; Risk management; Seasonal variations; Severe acute respiratory syndrome coronavirus 2; Specific humidity; Temperature; Temperature effects; Tropical environment; Tropical environments; Viral diseases; Warm climates; United States; Indiana; United States > US; Baltimore County Maryland; Ohio; Maryland; Baltimore Maryland; New York City New York
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0273511

Observations based on the spread of SARS-CoV-2 early into the COVID-19 pandemic have suggested a reduced burden in tropical regions leading to the assumption of a dichotomy between cold and dry and wet and warm climates. Analyzing more than a whole year of COVID-19 infection data, this study intents to refine the understanding of meteorological variables (temperature, humidity, precipitation and cloud coverage) on COVID-19 transmission in settings that experience distinct seasonal changes. A time stratified case-crossover design was adopted with a conditional Poisson model in combination with a distributed lag nonlinear model to assess the short-term impact of mentioned meteorological factors on COVID-19 infections in five US study sites (New York City (NYC); Marion County, Indiana (MCI); Baltimore and Baltimore County, Maryland (BCM); Franklin County, Ohio (FCO); King County, Washington (KCW)). Higher-than-average temperatures were consistently associated with a decreased relative risk (RR) of COVID-19 infection in four study sites. At 20 degrees Celsius COVID-19 infection was associated with a relative risk of 0.35 (95%CI: 0.20-0.60) in NYC, 1.03 (95%CI:0.57-1.84) in MCI, 0.34 (95%CI: 0.20-0.57) in BCM, 0.52 (95%CI: 0.31-0.87) in FCO and 0.21 (95%CI: 0.10-0.44) in KCW. Higher-than-average humidity levels were associated with an increased relative risk of COVID-19 infection in four study sites. Relative to their respective means, at a humidity level of 15 g/kg (specific humidity) the RR was 5.83 (95%CI: 2.05-16.58) in BCM, at a humidity level of 10 g/kg the RR was 3.44 (95%CI: 1.95-6.01) in KCW. The results of this study suggest opposed effects for higher-than-average temperature and humidity concerning the risk of COVID-19 infection. While a distinct seasonal pattern of COVID-19 has not yet emerged, warm and humid weather should not be generally regarded as a time of reduced risk of COVID-19 infections.