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Quantifying the impact of early-stage contact tracing on controlling Ebola diffusion

. Department of Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66506, USA

Recent experience of the Ebola outbreak in 2014 highlighted the importance of immediate response measure to impede transmission in the early stage. To this aim, efficient and effective allocation of limited resources is crucial. Among the standard interventions is the practice of following up with the recent physical contacts of the infected individuals -- known as contact tracing. In an effort to understand the effects of contact tracing protocols objectively, we explicitly develop a model of Ebola transmission incorporating contact tracing. Our modeling framework is individual-based, patient-centric, stochastic and parameterizable to suit early-stage Ebola transmission. Notably, we propose an activity driven network approach to contact tracing, and estimate the basic reproductive ratio of the epidemic growth in different scenarios. Exhaustive simulation experiments suggest that early contact tracing paired with rapid hospitalization can effectively impede the epidemic growth. Resource allocation needs to be carefully planned to enable early detection of the contacts and rapid hospitalization of the infected people.

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Keywords Contact tracing; Ebola; compartmental model; activity-driven network; epidemic model

Citation: Narges Montazeri Shahtori, Tanvir Ferdousi, Caterina Scoglio, Faryad Darabi Sahneh. Quantifying the impact of early-stage contact tracing on controlling Ebola diffusion. Mathematical Biosciences and Engineering, 2018, 15(5): 1165-1180. doi: 10.3934/mbe.2018053

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