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Background: Air pollution has been a serious health issue in Beijing for years. Airborne antibiotic-resistant bacteria could be a potential health crisis as reserve of antibiotic resistance transmission in environment. The composition and antibiotic resistance pattern of culturable bacterial community and how these are affected by air pollution remain unclear.Objectives: This study aimed to compare the compositions and antibiotic resistance patterns of culturable bacteria in polluted and non-polluted weather conditions in Beijing. Methods: Air samples were collected indoors and outdoors during polluted and non-polluted weather using sixstage Andersen Samplers. For each isolated bacterium, the 16S ribosomal RNA gene was amplified, sequenced, and blasted against the National Center for Biotechnology Information database Antibiotic resistance was conducted by antimicrobial susceptibility testing. Results: Bacterial concentration in polluted weather was significantly higher than in non-polluted weather, both indoors and outdoors (P < 0.05). Gram-positive bacteria (GPB) were dominant in both weathers but gramnegative bacteria (GNB) were more abundant in polluted weather than non-polluted weather both indoors and outdoors. Multidrug-resistant (MDR) bacteria occupied 23.7% of all bacterial isolates, 22.4% of isolates from polluted weather and 27.8% of isolates from non-polluted weather. Penicillins were resisted by 72.4% and 83.3% of isolates from polluted and non-polluted weather, respectively. Conclusions: The bacterial concentration was significantly higher in polluted weather, compared to non-polluted weather. Polluted weather is correlated with changes in the bacterial composition in the air, with a greater abundance of GNB. Penicillins was resisted by over 70% of bacterial isolates. The abundance of MDR bacteria suggested potential risks for human health.

From June 11, 2020, a surge in new cases of coronavirus disease 2019 (COVID-19) in the largest wholesale market of Beijing, the Xinfadi Market, leading to a second wave of COVID-19 in Beijing, China. Understanding the transmission modes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the personal behaviors and environmental factors contributing to viral transmission is of utmost important to curb COVID-19 rise. However, currently these are largely unknown in food markets. To this end, we completed field investigations and on-site simulations in areas with relatively high infection rates of COVID-19 at Xinfadi Market. We found that if goods were tainted or personnel in market was infected, normal transaction behaviors between sellers and customers, daily physiological activities, and marketing activities could lead to viral contamination and spread to the surroundings via fomite, droplet or aerosol routes. Environmental factors such as low temperature and high humidity, poor ventilation, and insufficient hygiene facilities and disinfection practices may contribute to viral transmission in Xinfadi Market. In addition, precautionary control strategies were also proposed to effectively reduce the clustering cases of COVID-19 in large-scale wholesale markets.

More and more studies have evaluated the associations between ambient temperature and coronavirus disease 2019 (COVID-19). However, most of these studies were rushed to completion, rendering the quality of their findings questionable. We systematically evaluated 70 relevant peer-reviewed studies published on or before 21 September 2020 that had been implemented from community to global level. Approximately 35 of these reports indicated that temperature was significantly and negatively associated with COVID-19 spread, whereas 12 reports demonstrated a significantly positive association. The remaining studies found no association or merely a piecewise association. Correlation and regression analyses were the most commonly utilized statistical models. The main shortcomings of these studies included uncertainties in COVID-19 infection rate, problems with data processing for temperature, inappropriate controlling for confounding parameters, weaknesses in evaluation of effect modification, inadequate statistical models, short research periods, and the choices of research areal units. It is our viewpoint that most studies of the identified 70 publications have had significant flaws that have prevented them from providing a robust scientific basis for the association between temperature and COVID-19.

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