Building ventilation as an effective disease intervention strategy in a dense indoor contact network in an Ideal City

Xiaolei Gao, Jianjian Wei, Hao Lei, Pengcheng Xu, Benjamin J. Cowling, Yuguo Li

Research output: Contribution to journalArticleResearchpeer-review

43 Citations (Scopus)

Abstract

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 theWells-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.

Original languageEnglish
Article numbere0162481
Number of pages10
JournalPLoS ONE
Volume11
Issue number9
DOIs
Publication statusPublished - 9 Sept 2016
Externally publishedYes

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