Simulating Human Host Interventions to Control Intra-urban Dengue Outbreaks with a Spatially Individual-based Model

Qiao Wan, Ling Yin, Liang Mao, Li Wang, Shujiang Mei, Qinglan Li, Kang Liu

Abstract: The incidence of dengue fever, a mosquito-borne disease, has significantly increased throughout the world in recent decades, which urgently requires more effective dengue intervention strategies. Although both mosquitos and humans play critical roles in dengue transmission, commonly used dengue intervention strategies mainly depend on the control of the mosquito vector. Since intervention simulations by computers offer important scientific support for disease intervention policy-making, this study aims to simulate and evaluate the intervention strategies from the perspective of the human host. This study first develops a spatially-explicit, individual-based model that can simulate an intra-urban dengue outbreak by integrating the daily activities and travels of urban populations. Then, we examined two human host intervention strategies: a dengue vaccination program and early isolation of symptomatic infected people. Taking the dengue outbreak of Shenzhen in 2014 as a case study, our simulation results show that the reduction of symptomatic infected people increases from 60.21% to 94.39% as the proportion of the immunized population increases from 25% to 50%, while early isolation of symptomatic infected people can reduce total symptomatic infected people by 46.78%. Overall, this study provides an effective, spatially-explicit, individual-based model that allows dengue transmission simulations and human host intervention simulations, which can help guide policy-making to control dengue outbreaks at an urban scale.