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1.
Innovation (Camb) ; 2(3): 100139, 2021 Aug 28.
Article in English | MEDLINE | ID: covidwho-1275767

ABSTRACT

The evidence for the effects of environmental factors on COVID-19 case fatality remains controversial, and it is crucial to understand the role of preventable environmental factors in driving COVID-19 fatality. We thus conducted a nationwide cohort study to estimate the effects of environmental factors (temperature, particulate matter [PM2.5, PM10], sulfur dioxide [SO2], nitrogen dioxide [NO2], and ozone [O3]) on COVID-19 case fatality. A total of 71,808 confirmed COVID-19 cases were identified and followed up for their vital status through April 25, 2020. Exposures to ambient air pollution and temperature were estimated by linking the city- and county-level monitoring data to the residential community of each participant. For each participant, two windows were defined: the period from symptom onset to diagnosis (exposure window I) and the period from diagnosis date to date of death/recovery or end of the study period (exposure window II). Cox proportional hazards models were used to estimate the associations between these environmental factors and COVID-19 case fatality. COVID-19 case fatality increased in association with environmental factors for the two exposure windows. For example, each 10 µg/m3 increase in PM2.5, PM10, O3, and NO2 in window I was associated with a hazard ratio of 1.11 (95% CI 1.09, 1.13), 1.10 (95% CI 1.08, 1.13), 1.09 (95 CI 1.03, 1.14), and 1.27 (95% CI 1.19, 1.35) for COVID-19 fatality, respectively. A significant effect was also observed for low temperature, with a hazard ratio of 1.03 (95% CI 1.01, 1.04) for COVID-19 case fatality per 1°C decrease. Subgroup analysis indicated that these effects were stronger in the elderly, as well as in those with mild symptoms and living in Wuhan or Hubei. Overall, the sensitivity analyses also yielded consistent estimates. Short-term exposure to ambient air pollution and low temperature during the illness would play a nonnegligible part in causing case fatality due to COVID-19. Reduced exposures to high concentrations of PM2.5, PM10, O3, SO2, and NO2 and low temperature would help improve the prognosis and reduce public health burden.

2.
Innovation (N Y) ; 1(2): 100022, 2020 Aug 28.
Article in English | MEDLINE | ID: covidwho-692819

ABSTRACT

An increasing number of patients are being killed by coronavirus disease 2019 (COVID-19), however, risk factors for the fatality of COVID-19 remain unclear. A total of 21,392 COVID-19 cases were recruited in the Hubei Province of China between December 2019 and February 2020, and followed up until March 18, 2020. We adopted Cox regression models to investigate the risk factors for case fatality and predicted the death probability under specific combinations of key predictors. Among the 21,392 patients, 1,020 (4.77%) died of COVID-19. Multivariable analyses showed that factors, including age (≥60 versus <45 years, hazard ratio [HR] = 7.32; 95% confidence interval [CI], 5.42, 9.89), sex (male versus female, HR = 1.31; 95% CI, 1.15, 1.50), severity of the disease (critical versus mild, HR = 39.98; 95% CI, 29.52, 48.86), comorbidity (HR = 1.40; 95% CI, 1.23, 1.60), highest body temperature (>39°C versus <39°C, HR = 1.28; 95% CI, 1.09, 1.49), white blood cell counts (>10 × 109/L versus (4-10) × 109/L, HR = 1.69; 95% CI, 1.35, 2.13), and lymphocyte counts (<0.8 × 109/L versus (0.8-4) × 109/L, HR = 1.26; 95% CI, 1.06, 1.50) were significantly associated with case fatality of COVID-19 patients. Individuals of an older age, who were male, with comorbidities, and had a critical illness had the highest death probability, with 21%, 36%, 46%, and 54% within 1-4 weeks after the symptom onset. Risk factors, including demographic characteristics, clinical symptoms, and laboratory factors were confirmed to be important determinants of fatality of COVID-19. Our predictive model can provide scientific evidence for a more rational, evidence-driven allocation of scarce medical resources to reduce the fatality of COVID-19.

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