COVID-19 threatens the world. Social distancing is a significant factor in determining the spread of this disease, and social distancing is strongly affected by the local travel behaviour of people in large cities. In this study, we analysed the changes in the local travel behaviour of various population groups in Hong Kong, between 1 January and 31 March 2020, by using second-by-second smartcard data obtained from the Mass Transit Railway Corporation (MTRC) system. Due to the pandemic, local travel volume decreased by 43%, 49% and 59% during weekdays, Saturdays and Sundays, respectively. The local travel volumes of adults, children, students and senior citizens decreased by 42%, 86%, 73% and 48%, respectively. The local travel behaviour changes for adults and seniors between non-pandemic and pandemic times were greater than those between weekdays and weekends. The opposite was true for children and students. During the pandemic, the daily commute flow decreased by 42%. Local trips to shopping areas, amusement areas and borders decreased by 42%, 81% and 99%, respectively. The effective reproduction number ( R t ) of COVID-19 had the strongest association with daily population use of the MTR 7-8 days earlier.

To explain the observed phenomenon that most SARS‐CoV‐2 transmission occurs indoors whereas its outdoor transmission is rare, a simple macroscopic aerosol balance model is developed to link short‐ and long‐range airborne transmission. The model considers the involvement of exhaled droplets with initial diameter ≤50 µm in the short‐range airborne route, whereas only a fraction of these droplets with an initial diameter within 15 µm or equivalently a final diameter within 5 µm considered in the long‐range airborne route. One surprising finding is that the room ventilation rate significantly affects the short‐range airborne route, in contrast to traditional belief. When the ventilation rate in a room is insufficient, the airborne infection risks due to both short‐ and long‐range transmission are high. A ventilation rate of 10 L/s per person provides a similar concentration vs distance decay profile to that in outdoor settings, which provides additional justification for the widely adopted ventilation standard of 10 L/s per person. The newly obtained data do not support the basic assumption in the existing ventilation standard ASHRAE 62.1 (2019) that the required people outdoor air rate is constant if the standard is used directly for respiratory infection control. Instead, it is necessary to increase the ventilation rate when the physical distance between people is less than approximately 2 m.

To differentiate between respiratory infections caused by SARS-CoV-2 and other respiratory pathogens during the COVID-19 outbreak in Wuhan, we simultaneously tested for SARS-CoV-2 and pathogens associated with CAP to determine the incidence and impact of respiratory coinfections in COVID-19 patients. Patients and Methods: We included 250 patients who were diagnosed with COVID-19. RT-PCR was used to detect influenza A, influenza B and respiratory syncytial viruses. Chemiluminescence immunoassays were used to detect IgM antibodies for adenovirus, Chlamydia pneumoniae and Mycoplasma pneumoniae in the serum of patients. Based on these results, we divided the patients into two groups, the simple SARS-CoV-2-infected group and the coinfected SARS-COV-2 group. Coinfected patients were then further categorized as having a coinfection of viral pathogen (CoIV) or coinfection of atypical bacterial pathogen (CoIaB). Results: No statistically significant differences were found in age, gender, the time taken to return negative SARS-CoV-2 nucleic acid test results, length of hospital stays, and mortality between the simple SARS-CoV-2 infection group and the coinfection group. Of the 250 hospitalized COVID-19 patients, 39 (15.6%) tested positive for at least one respiratory pathogen in addition to SARS-CoV-2. A third of these pathogens were detected as early as the 1st week after symptom onset and another third were identified after more than three weeks. The most detected CAP pathogen was C. pneumoniae (5.2%), followed by the respiratory syncytial virus (4.8%), M. pneumoniae (4.4%) and adenovirus (2.8%). Patients coinfected with viral pathogens (CoIV) (n=18) had longer hospital stays when compared to patients coinfected with atypical bacterial pathogens (CoIaB) (n=21). Except for one fatality, the remaining 38 coinfected patients all recovered with favourable outcomes. Conclusion: Coinfections in COVID-19 patients are common. The coinfecting pathogens can be detected at variable intervals during COVID-19 disease course and remain an important consideration in targeted treatment strategies for COVID-19 patients.