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Association between meteorological variations and the superspreading potential of SARS-CoV-2 infections
Background: While many investigations examined the association between environmental covariates and COVID-19 incidence, none have examined their relationship with superspreading, a characteristic describing very few individuals disproportionally infecting a large number of people. Methods: Contact tracing data of all the laboratory-confirmed COVID-19 cases in Hong Kong from February 16, 2020 to April 30, 2021 were used to form the infection clusters for estimating the time-varying dispersion parameter (kt), a measure of superspreading potential. Generalized additive models with identity link function were used to examine the association between negative-log kt (larger means higher superspreading potential) and the environmental covariates, adjusted with mobility metrics that account for the effect of social distancing measures. Results: A total of 6,645 clusters covering 11,717 cases were reported over the study period. After centering at the median temperature, a lower ambient temperature at 10th percentile (18.2 °C) was significantly associated with a lower estimate of negative-log kt (adjusted expected change: −0.239 [95 % CI: −0.431 to −0.048]). While a U-shaped relationship between relative humidity and negative-log kt was observed, an inverted U-shaped relationship with actual vapour pressure was found. A higher total rainfall was significantly associated with lower estimates of negative-log kt. Conclusions: This study demonstrated a link between meteorological factors and the superspreading potential of COVID-19. We speculated that cold weather and rainy days reduced the social activities of individuals minimizing the interaction with others and the risk of spreading the diseases in high-risk facilities or large clusters, while the extremities of relative humidity may favor the stability and survival of the SARS-CoV-2 virus.
Association between meteorological variations and the superspreading potential of SARS-CoV-2 infections
Background: While many investigations examined the association between environmental covariates and COVID-19 incidence, none have examined their relationship with superspreading, a characteristic describing very few individuals disproportionally infecting a large number of people. Methods: Contact tracing data of all the laboratory-confirmed COVID-19 cases in Hong Kong from February 16, 2020 to April 30, 2021 were used to form the infection clusters for estimating the time-varying dispersion parameter (kt), a measure of superspreading potential. Generalized additive models with identity link function were used to examine the association between negative-log kt (larger means higher superspreading potential) and the environmental covariates, adjusted with mobility metrics that account for the effect of social distancing measures. Results: A total of 6,645 clusters covering 11,717 cases were reported over the study period. After centering at the median temperature, a lower ambient temperature at 10th percentile (18.2 °C) was significantly associated with a lower estimate of negative-log kt (adjusted expected change: −0.239 [95 % CI: −0.431 to −0.048]). While a U-shaped relationship between relative humidity and negative-log kt was observed, an inverted U-shaped relationship with actual vapour pressure was found. A higher total rainfall was significantly associated with lower estimates of negative-log kt. Conclusions: This study demonstrated a link between meteorological factors and the superspreading potential of COVID-19. We speculated that cold weather and rainy days reduced the social activities of individuals minimizing the interaction with others and the risk of spreading the diseases in high-risk facilities or large clusters, while the extremities of relative humidity may favor the stability and survival of the SARS-CoV-2 virus.
Association between meteorological variations and the superspreading potential of SARS-CoV-2 infections
Ka Chun Chong (Autor:in) / Shi Zhao (Autor:in) / Chi Tim Hung (Autor:in) / Katherine Min Jia (Autor:in) / Janice Ying-en Ho (Autor:in) / Holly Ching Yu Lam (Autor:in) / Xiaoting Jiang (Autor:in) / Conglu Li (Autor:in) / Guozhang Lin (Autor:in) / Carrie Ho Kwan Yam (Autor:in)
2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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