Modeling control measure effects to reduce indoor transmission of pandemic H1N1 2009 virus

Abstract

The pandemic H1N1 2009 (p-H1N1) spreading worldwide has led to severe morbidity and mortality. This study aimed to quantify the impacts on disease control by applying various control strategies for p-H1N1 in an elementary school indoor setting. Indoor disease transmissibility was explored by a general Wells-Riley equation. To better contain influenza outbreak, a multi-control measure model was developed. A non-extinction branching process was presented to quantify the indoor epidemic probability for seasonal influenza and p-H1N1. The infection risk, quantum generation rate (quanta d−1), basic reproduction number (R0), generation time (d), and asymptomatic infectious proportion (%) were, respectively, estimated to be 0.020 (95% CI: 0.010–0.043), 494 (140–1292), 3.30 (0.75–11.47), 3.54 (3.15–3.99), and 15 (8–59) for p-H1N1. By implementing all non-engineering interventions, seasonal influenza could be well controlled, whereas for p-H1N1, engineering and non-engineering control measure combinations were effective for complete outbreak containment. Indoor epidemic probability of p-H1N1 increases with increments in R0 and introductions of infected individual. The proposed control strategies combined with non-engineering and engineering interventions could effectively control p-H1N1 outbreak. A multi-control measure model developed here could be implemented in more complex infectious circumstances. Our study can be incorporated into the relationship among influenza virus, host, and indoor environment for better understanding the complex dynamics of environmental processes and to achieve optimal indoor control measures.