Air pollution and temperature are associated with increased COVID-19 incidence: A time series study.

OBJECTIVES: Although COVID-19 is known to be caused by human-to-human transmission, it remains largely unclear whether ambient air pollutants and meteorological parameters could promote its transmission. METHODS: A retrospective study was conducted to study whether air quality index (AQI), four ambient air pollutants (PM2.5, PM10, NO2 and CO) and five meteorological variables (daily temperature, highest temperature, lowest temperature, temperature difference and sunshine duration) could increase COVID-19 incidence in Wuhan and XiaoGan between Jan 26th to Feb 29th in 2020. RESULTS: First, a significant correlation was found between COVID-19 incidence and AQI in both Wuhan (R2=0.13, p<0.05) and XiaoGan (R2=0.223, p<0.01). Specifically, among four pollutants, COVID-19 incidence was prominently correlated with PM2.5 and NO2 in both cities. In Wuhan, the tightest correlation was observed between NO2 and COVID-19 incidence (R2=0.329, p<0.01). In XiaoGan, in addition to the PM2.5 (R2=0.117, p<0.01) and NO2 (R2=0.015, p<0.05), a notable correlation was also observed between the PM10 and COVID-19 incidence (R2=0.105, p<0.05). Moreover, temperature is the only meteorological parameter that constantly correlated well with COVID-19 incidence in both Wuhan and XiaoGan, but in an inverse correlation (p<0.05). CONCLUSIONS: AQI, PM2.5, NO2, and temperature are four variables that could promote the sustained transmission of COVID-19.

Effect of ambient air pollutants and meteorological variables on COVID-19 incidence.

OBJECTIVE: To determine whether ambient air pollutants and meteorological variables are associated with daily COVID-19 incidence. DESIGN: A retrospective cohort from January 25 to February 29, 2020. SETTING: Cities of Wuhan, Xiaogan, and Huanggang, China. PATIENTS: The COVID-19 cases detected each day. METHODS: We collected daily data of COVID-19 incidence, 8 ambient air pollutants (particulate matter of ≤2.5 µm [PM2.5], particulate matter ≤10 µm [PM10], sulfur dioxide [SO2], carbon monoxide [CO], nitrogen dioxide [NO2], and maximum 8-h moving average concentrations for ozone [O3-8h]) and 3 meteorological variables (temperature, relative humidity, and wind) in China's 3 worst COVID-19-stricken cities during the study period. The multivariate Poisson regression was performed to understand their correlation. RESULTS: Daily COVID-19 incidence was positively associated with PM2.5 and humidity in all cities. Specifically, the relative risk (RR) of PM2.5 for daily COVID-19 incidences were 1.036 (95% confidence interval [CI], 1.032-1.039) in Wuhan, 1.059 (95% CI, 1.046-1.072) in Xiaogan, and 1.144 (95% CI, 1.12-1.169) in Huanggang. The RR of humidity for daily COVID-19 incidence was consistently lower than that of PM2.5, and this difference ranged from 0.027 to 0.111. Moreover, PM10 and temperature also exhibited a notable correlation with daily COVID-19 incidence, but in a negative pattern The RR of PM10 for daily COVID-19 incidence ranged from 0.915 (95% CI, 0.896-0.934) to 0.961 (95% CI, 0.95-0.972, while that of temperature ranged from 0.738 (95% CI, 0.717-0.759) to 0.969 (95% CI, 0.966-0.973). CONCLUSIONS: Our data show that PM2.5 and humidity are substantially associated with an increased risk of COVID-19 and that PM10 and temperature are substantially associated with a decreased risk of COVID-19.

Prevalence of stress and its determinants among residents enrolled in China Standardized Training Program for Resident Doctor (C-STRD) program: A cross-sectional study.

BACKGROUND: It has been widely understood that well-trained doctors are crucial for a high-quality public health system and safe patient care. Thus, in 2011, China initiated its first national residency training program, called the China Standardized Training for Resident Doctor (C-STRD), for medical graduates to prepare qualified doctors for the medical care system with increasing demands. So far, no studies have specifically address the prevalence of stress and its determinants among residents enrolled in the C-STRD. PARTICIPANTS AND METHODS: The research is performed in two stages. In stage I, the authors conducted a pilot study and met 112 C-STRD residents in person. Based on the preliminary data, a revised questionnaire was adopted in stage II, during which the authors conducted a multi-institutional, cross-sectional survey of 340 participants from 11 hospitals in Shanghai in a self-administered manner. RESULTS: The results showed that C-STRD residents were overall under severe stress as their mean PSS score was 27.5 ± 4.9, which was higher than the threshold of high stress (PSS = 20). Specifically, the PSS score for the residents with Bachelor (MB), Master (MM) and Doctoral of Medicine (MD) educational degree were 26.6 ± 4.1, 27.8 ± 3.5 and 27.1 ± 5.2, respectively (P>0.05). Their stress was mainly associated with their financial income status and workload, as these two factors caused more severe burden than other listed stressors (P<0.05). Specially, the residents indicated that their montly payroll amout were as low as $590.2 ± 127 while no benefit package and allowance were given. Surprisingly, wage arrears up to 5.3 month were reported by 36 (10%) participants. Workload survey showed the residents has high work intensity and inadequate rest. Since no stress management program was provided, the majority of residents tended to cope their stress with unhealthy strategies, such as mesmerizing in TV/computer (88.2%) and overeating (59.7%). CONCLUSION: The C-STRD residents are at high risk of perceived stress. Although there was a difference in perception of stress for workload and career future among different educational degree owners, low financial income is the major stressor among all C-STRD residents. Unhealthy stress management strategies were adopted by all residents due to lack of appropriate stress-relieving intervention.