Jeffery Demers , William F. Fagan , Sriya Potluri , Justin M. Calabrese
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引用次数: 0
Abstract
Rapid identification and isolation of infected individuals with diagnostic testing plays a critical role in combating invasions of novel human pathogens. Unfortunately, unprepared health agencies may struggle to meet the massive testing capacity demands imposed by an outbreaking novel pathogen, potentially resulting in a failure of epidemic containment as occurred with COVID-19. Despite the critical importance of understanding the likelihood of such an outcome, it remains unclear how the particular characteristics of a novel disease will impact the magnitude of resource constraints on controllability. Specifically, is the failure of testing-isolation unique to COVID-19, or is this a likely outcome across the spectrum of disease traits that may constitute future epidemics? Here, using a generalized mathematical model parameterized for seven different human diseases and variants, we show that testing-isolation strategies will typically fail to contain epidemic outbreaks at practicably achievable testing capacities. From this analysis, we identify three key disease characteristics that govern controllability under resource constraints; the basic reproduction number, mean latent period, and non-symptomatic transmission index. Interactions among these characteristics play prominent roles in both explaining controllability differences among diseases and enhancing the efficacy of testing-isolation in combination with transmission-reduction measures. This study provides broad guidelines for managing controllability expectations during future novel disease invasions, describing which classes of diseases are most amenable to testing-isolation strategies alone and which will necessitate additional transmission-reduction measures like social distancing.
期刊介绍:
Mathematical Biosciences publishes work providing new concepts or new understanding of biological systems using mathematical models, or methodological articles likely to find application to multiple biological systems. Papers are expected to present a major research finding of broad significance for the biological sciences, or mathematical biology. Mathematical Biosciences welcomes original research articles, letters, reviews and perspectives.