Airborne disease transmission during indoor gatherings over multiple time scales: Modeling framework and policy implications.
Airborne disease transmission during indoor gatherings over multiple time scales: Modeling framework and policy implications.
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DOI:
10.1073/pnas.2216948120
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发表时间:
2023-04-18
影响因子:
11.1
通讯作者:
Marathe, Madhav, V
中科院分区:
文献类型:
--
作者:
Dixit, Avinash K.;Espinoza, Baltazar;Qiu, Zirou;Vullikanti, Anil;Marathe, Madhav, V
关键词:
Group gathering in enclosed spaces (e.g., classrooms, conferences) is an important route for the spread of respiratory diseases such as COVID-19. Based on the proposed modeling framework, we examine airborne disease transmission among a group of people, under scenarios of indoor meetings involving multiple time scales. Our framework captures the feedback loop between infected individuals’ viral shedding, the venue’s viral dynamics, and the group composition and behavioral characteristics. We study the epidemiological trade-offs emerging by implementing control measures aimed at controlling the viral load. Numerical analysis suggests that ventilation and break times are critical in preventing high viral load levels. Moreover, we found that their impact would equal or exceed that of masking and moderate isolation of infected individuals. Indoor superspreading events are significant drivers of transmission of respiratory diseases. In this work, we study the dynamics of airborne transmission in consecutive meetings of individuals in enclosed spaces. In contrast to the usual pairwise-interaction models of infection where effective contacts transmit the disease, we focus on group interactions where individuals with distinct health states meet simultaneously. Specifically, the disease is transmitted by infected individuals exhaling droplets (contributing to the viral load in the closed space) and susceptible ones inhaling the contaminated air. We propose a modeling framework that couples the fast dynamics of the viral load attained over meetings in enclosed spaces and the slow dynamics of disease progression at the population level. Our modeling framework incorporates the multiple time scales involved in different setups in which indoor events may happen, from single-time events to events hosting multiple meetings per day, over many days. We present theoretical and numerical results of trade-offs between the room characteristics (ventilation system efficiency and air mass) and the group’s behavioral and composition characteristics (group size, mask compliance, testing, meeting time, and break times), that inform indoor policies to achieve disease control in closed environments through different pathways. Our results emphasize the impact of break times, mask-wearing, and testing on facilitating the conditions to achieve disease control. We study scenarios of different break times, mask compliance, and testing. We also derive policy guidelines to contain the infection rate under a certain threshold.
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影响因子:
9.8
作者:
Althouse BM;Wenger EA;Miller JC;Scarpino SV;Allard A;Hébert-Dufresne L;Hu H
通讯作者:
Hu H
DOI:
10.1073/pnas.2123355119
发表时间:
2022-06-28
影响因子:
11.1
作者:
通讯作者:
--
DOI:
10.1073/pnas.2116165119
发表时间:
2022-05-31
影响因子:
11.1
作者:
通讯作者:
--
影响因子:
5.8
作者:
Qian, Hua;Miao, Te;Li, Yuguo
通讯作者:
Li, Yuguo
影响因子:
5.2
作者:
Curtius, J.;Granzin, M.;Schrod, J.
通讯作者:
Schrod, J.