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The Effects of Intervention Strategies for COVID-19 Transmission Control on Campus Activity
7th China National Conference on Big Data and Social Computing, BDSC 2022 ; 1640 CCIS:23-39, 2022.
Article in English | Scopus | ID: covidwho-2173950
ABSTRACT
University is one of the most likely environments for the cluster infection due to the long-time close contact in house and frequent communication. It is critical to understand the transmission risk of COVID-19 under various scenario, especially during public health emergency. Taking the Tsinghua university's anniversary as a representative case, a set of prevention and control strategies are established and investigated. In the case study, an alumni group coming from out of campus is investigated whose activities and routes are designed based on the previous anniversary schedule. The social closeness indicator is introduced into the Wells-Riley model to consider the factor of contact frequency. Based on the anniversary scenario, this study predicts the number of the infected people in each exposure indoor location (including classroom, dining hall, meeting room and so on) and evaluates the effects of different intervention measures on reducing infection risk using the modified Wells-Riley model, such as ventilation, social distancing and wearing mask. The results demonstrate that when applying the intervention measure individually, increasing ventilation rate is found to be the most effective, whereas the efficiency of increased ventilation on reducing infection cases decreases with the increase of the ventilation rate. To better prevent COVID-19 transmission, the combined intervention measures are necessary to be taken, which show the similar effectiveness on the reduction of infected cases under different initial infector proportion. The results provide the insights into the infection risk on university campus when dealing with public health emergency and can guide university to formulate effective operational strategies to control the spread of COVID-19. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Experimental Studies Language: English Journal: 7th China National Conference on Big Data and Social Computing, BDSC 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Experimental Studies Language: English Journal: 7th China National Conference on Big Data and Social Computing, BDSC 2022 Year: 2022 Document Type: Article