title: Contact tracing and antiviral prophylaxis in the early stages of a pandemic: the probability of a major outbreak.
abstract: Antiviral prophylaxis forms a significant component of health management plans for many countries around the world. A number of studies have shown that the delays typically encountered in distributing these antivirals to households, following the first infectious case, can result in their efficacy being severely reduced. Here, we investigate the use of contact tracing as a method to reduce the delays and hence mitigate the reduction in efficacy of antivirals. We assess the usefulness of contact tracing in terms of the probability of a major outbreak. It is found, with parameter distributions appropriate to the 2009 H1N1 pandemic and distributions reflecting commonly experienced delays, that standard contact tracing renders an outbreak impossible approximately one in five times compared with approximately one in ten times in its absence. A contact-tracing efficiency of 50% would see further improvements with an outbreak being impossible approximately one in four times, and a reduction of the median probability of a major outbreak from 0.41 to below 0.27.
authors.affiliation: School of Mathematical Sciences, The University of Adelaide, Adelaide SA 5005, Australia joshua.ross@adelaide.edu.au.
authors.forename: Joshua V
authors.initials: JV
authors.lastname: Ross
authors.affiliation: School of Mathematical Sciences, The University of Adelaide, Adelaide SA 5005, Australia.
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Black
mesh_terms: D000998:Antiviral Agents / Q000627:therapeutic use*; D006801:Humans; D053118:Influenza A Virus, H1N1 Subtype; D007251:Influenza, Human / Q000635:transmission*; D015233:Models, Statistical; D058873:Pandemics / Q000517:prevention & control* / Q000706:statistics & numerical data; D056990:Post-Exposure Prophylaxis / Q000706:statistics & numerical data*; D011336:Probability; D013269:Stochastic Processes
chemical_list: D000998:Antiviral Agents
keywords: antivirals; households; influenza; probability of a major outbreak; stochastic model