Building Ventilation as an Effective Disease Intervention Strategy in a Dense Indoor Contact Network in an Ideal City.
Emerging diseases may spread rapidly through dense and large urban contact networks, especially they are transmitted by the airborne route, before new vaccines can be made available. Airborne diseases may spread rapidly as people visit different indoor environments and are in frequent contact with others. We constructed a simple indoor contact model for an ideal city with 7 million people and 3 million indoor spaces, and estimated the probability and duration of contact between any two individuals during one day. To do this, we used data from actual censuses, social behavior surveys, building surveys, and ventilation measurements in Hong Kong to define eight population groups and seven indoor location groups. Our indoor contact model was integrated with an existing epidemiological Susceptible, Exposed, Infectious, and Recovered (SEIR) model to estimate disease spread and with the Wells-Riley equation to calculate local infection risks, resulting in an integrated indoor transmission network model. This model was used to estimate the probability of an infected individual infecting others in the city and to study the disease transmission dynamics. We predicted the infection probability of each sub-population under different ventilation systems in each location type in the case of a hypothetical airborne disease outbreak, which is assumed to have the same natural history and infectiousness as smallpox. We compared the effectiveness of controlling ventilation in each location type with other intervention strategies. We conclude that increasing building ventilation rates using methods such as natural ventilation in classrooms, offices, and homes is a relatively effective strategy for airborne diseases in a large city.
Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China.
Xiaolei
X
Gao
Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China.
Jianjian
http://orcid.org/0000-0001-8859-8462
J
Wei
Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China.
Hao
H
Lei
Institute of Applied Mathematics, Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, Beijing, China.
Pengcheng
P
Xu
WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China.
Benjamin J
BJ
Cowling
Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China.
Yuguo
Y
Li
D000392:Air Movements; D016902:Air Pollution, Indoor / Q000032:analysis; D003141:Communicable Diseases; D006723:Hong Kong; D006801:Humans; D008962:Models, Theoretical; D014691:Ventilation