Quantifying Resilience in Single-Host/Single-Virus Infections

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Abstract

Developing metrics for quantifying the virulence of pathogens (e.g., viruses) is a historical and recently reinvigorated topic of research interest with both theoretical and practical applications in medical, industrial, and environmental microbiology. In the wake of several recent pandemics and outbreaks (e.g., COVID-19, Zika, Dengue, Avian Influenza), where multiple strains of a virus propagated through host populations, methods for assessing relative virulence (VR) between strains has re-emerged as a “hot topic”. Recent publications have considered metrics for determining VR that extend beyond the practice of calculating differences in maximum specific growth rates (mmax) from growth curves of a virus-infected hosts versus uninfected host controls. While some metrics appear best-suited for single-virus/single-host (SVSH) infections that feature canonical host growth with well-defined lag, exponential, stationary, and mortality phases, others may be more robust for infections exhibiting non-canonical infected host growth patterns. Regardless of the metric used, one feature that most approaches have in common is a focus on the exponential growth phase of the virus-host interaction (i.e., from late lag to early stationary phase). Often neglected is the back-half of the growth curve. Following a recent report introducing the Stacy-Ceballos Inhibition Index (ISC), a metric for quantifying relative virulence (VR) between viruses, we have turned our attention to the equally important parameter of relative resilience (RR) between hosts infected in SVSH infections. Although host resilience during a viral infection impacts the entire growth curve, RR has a particular biological significance during extinction (i.e., the mortality phase). Specifically, it is important to assess how long a host (or population) will remain viable post-infection. In this report, we argue that calculating RR using a modification of ISC provides a robust metric for comparisons between SVSH infections. Data from fusellovirus infections in Sulfolobales and bacteriophage infections in Mycobacteriales form the basis for applying this approach for quantifying host resilience.

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