The impact of temperature and absolute humidity on the coronavirus disease 2019 (COVID-19) outbreak - evidence from China

Abstract

Background:The medical, health service, societal and economic impact of the COVID-19 emergency has unknown effects on overall population mortality. Previous models of population mortality are based on death over days among infected people, nearly all of whom (to date at least) have underlying conditions. Models have not incorporated information on high risk conditions or their longer term background (pre-COVID-19) mortality. We estimated the excess number of deaths over 1 year under different COVID-19 incidence rates and differing mortality impacts. Methods:Using population based linked primary and secondary care electronic health records in England (HDR UK -CALIBER), we report the prevalence of underlying conditions defined by UK Public Health England COVID-19 guidelines (16 March 2020) in 3,862,012 individuals aged ≥30 years from 1997-2017. We used previously validated phenotypes, openly available (https://caliberresearch.org/portal), for each condition using ICD-10 diagnosis, Read, procedure and medication codes. We estimated the 1-year mortality in each condition, and developed simple models of excess COVID-19-related deaths assuming relative risk (RR) of the impact of the emergency (compared to background mortality) of 1.2, 1.5 and 2.0.

Globalized low-income countries may experience higher COVID-19 mortality rates

“…Our findings thus indicate that globalized countries could have experienced multiple and recurrent introductions of the virus via imported goods, tourists, or international exchanges of students or academics (Anzai et al, 2020;Chinazzi et al, 2020). Importantly, local climate (represented by mean temperature, precipitation and vapor pressure) was not found associated with infection rates, supporting a recent study (Luo et al, 2020) and contradicting an evaluation from 31 provincial-level regions in mainland China (Shi et al, 2020) and a global analysis (Ficetola & Rubolini, 2020). The discrepancy between our results and those from Ficetola and Rubolini (2020) may be due to the fact that they calculated exponential growth rates over a period of five days, and assessed a more limited number of predictor variables.…”

Impact of mitigating interventions and temperature on the instantaneous reproduction number in the COVID-19 epidemic among 30 US metropolitan areas

“…Without effective interventions, the peak of epidemic will reach higher and the epidemic process will last longer [25]. Thus, the reproduction numbers will not decline until a large proportion of It has been suggested that like many other respiratory virus infections, a seasonal pattern may exist for SARS like coronavirus [26,27]. However, as demonstrated in this study, the association between reproduction number and temperature was deeply confounded by interventions and other external factors (including altitudes and humidity).…”

Causal empirical estimates suggest COVID-19 transmission rates are highly seasonal

“…These empirical frameworks conflate location-specific characteristics -such as testing capacity, population density, and health services -with temperature variation. [8][9][10] Because temperature is correlated with many (often unobservable) confounding factors, such cross-sectional comparisons may not have a causal interpretation. [11][12][13] For example, countries that are cooler on average also tend to have higher income per capita 14 which may affect the number of new COVID-19 cases by enabling more public health measures such as testing and hospitalizations.…”