Student close contact behavior and COVID-19 transmission in China's classrooms

Human behavior-based COVID-19 transmission in two dining spaces

Since December 2019, the COVID-19 pandemic has rapidly disseminated globally, posing significant threats to the world. The dining spaces are high-risk indoor environments for the transmission of SARS-CoV-2, posing challenges for intervention and control. This study, based on surveillance videos from two COVID-19 outbreak cases in restaurants, obtained real data on human behaviors of close contact and surface touch. A respiratory infectious disease transmission model was developed, incorporating four transmission routes: short-range airborne, long-range airborne, fomite and large droplet. The results indicate that diners and staff spent 21.9 %-28.7 % and 17.5 %-27.8 % of their time on speaking, respectively, while spending 85.9 %-90.7 % and 83.4 %-87.6 % of their time on surface touching. The primary transmission routes were short-range (contributing 5.8 %-70.9 %) and long-range airborne (contributing 28.4 %-93.0 %), with fomite and large droplet routes contributing less than 12.0 %. Staff-only mask wearing reduced infection risk by 12.8 %-31.8 %. It is recommended that mandatory mask wearing for staff is necessary, while diners should wear masks as much as possible, and that the equivalent ventilation rate of clean fresh air is suggested to 30.0 m3/ (h·person). This study provides a scientific support to make non-pharmaceutical interventions in dinning spaces.

The public health and economic burden of long COVID in Australia, 2022-24: a modelling study

OBJECTIVE

To estimate the number of people in Australia with long COVID by age group, and the associated medium term productivity and economic losses.

STUDY DESIGN

Modelling study: a susceptible-exposed-infected-recovered (SEIR) model to estimate the number of people with long COVID over time following single infections, and a labour supply model to estimate productivity losses as a proportion of gross domestic product (GDP).

SETTING

Australia, 2022-2024.

MAIN OUTCOME MEASURES

Estimated number of people infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during 2022-2023 (based on serosurvey data) who have long COVID, 2022-2024, by age group; estimated GDP loss during 2022 caused by reduced labour supply attributable to long COVID.

RESULTS

Our model projected that the number of people with long COVID following a single infection in 2022 would peak in September 2022, when 310 341-1 374 805 people (1.2-5.4% of Australians) would have symptoms of long COVID, declining to 172 530-872 799 people (0.7-3.4%) in December 2024, including 7902-30 002 children aged 0-4 years (0.6-2.2%). The estimated mean labour loss attributable to long COVID in 2022 was projected to be 102.4 million (95% confidence interval [CI], 50.4-162.2 million) worked hours, equivalent to 0.48% (95% CI, 0.24-0.76%) of total worked hours in Australia during the 2020-21 financial year. The estimated mean GDP loss caused by the projected decline in labour supply and reduced use of other production factors was $9.6 billion (95% CI, $4.7-15.2 billion), or 0.5% of GDP. The estimated labour loss was greatest for people aged 30-39 years (27.5 million [95% CI, 16.0-41.0 million] hours; 26.9% of total labour loss) and people aged 40-49 years (24.5 million [95% CI, 12.1-38.7 million] hours; 23.9% of total labour loss).

CONCLUSION

Widespread SARS-CoV-2 infections in Australia mean that even a small proportion of infected people developing long COVID-related illness and disability could have important population health and economic effects. A paradigm shift is needed, from a sole focus on the immediate effects of coronavirus disease 2019 (COVID-19) to preventing and treating COVID-19 and treating long COVID, with implications for vaccine and antiviral policy and other mitigation of COVID-19.

Analysis of SARS-CoV-2 transmission in a university classroom based on real human close contact behaviors

Due to high-population density, frequent close contact, possible poor ventilation, university classrooms are vulnerable for transmission of respiratory infectious diseases. Close contact and long-range airborne are possibly main routes for SARS-CoV-2 transmission. In this study, taking a university classroom in Beijing for example, close contact behaviors of students were collected through a depth-detection device, which could detect depth to each pixel of the image, based on semi-supervised learning. Finally, >23 h of video data were obtained. Using Computational Fluid Dynamics, the relationship between viral exposure and close contact behaviors (e.g. interpersonal distance, relative facial orientations, and relative positions) was established. A multi-route transmission model (short-range airborne, mucous deposition, and long-range airborne) of infectious diseases considering real close contact behaviors was developed. In the case of Omicron, the risk of infection in university classrooms and the efficacy of different interventions were assessed based on dose-response model. The average interpersonal distance in university classrooms is 0.9 m (95 % CI, 0.5 m-1.4 m), with the highest proportion of face-to-back contact at 87.0 %. The risk of infection of susceptible students per 45-min lesson was 1 %. The relative contributions of short-range airborne and long-range airborne transmission were 40.5 % and 59.5 %, respectively, and the mucous deposition was basically negligible. When all students are wearing N95 respirators, the infection risk could be reduced by 96 %, the relative contribution of long-range airborne transmission increases to 95.6 %. When the fresh air per capita in the classroom is 24 m3/h/person, the virus exposure could be decreased by 81.1 % compared to the real situation with 1.02 m3/h/person. In a classroom with an occupancy rate of 50 %, after optimized arrangement of student distribution, the infection risk could be decreased by 62 %.