Abstract
Mathematical models of transmission of viral infections have become an integral part of public health decision-making. Models help inform estimates of the burden of disease and the potential impact of possible or actual interventions. Model construction requires a precise definition of the question to be answered or decision to be made, knowledge of the virus and the disease it causes, the mode and mechanism of transmission, the available interventions, and the potential effectiveness of those interventions. An elementary model of person-to-person viral transmission consists of categorizing individuals into one of three groups – susceptible, ill-and-infectious, and recovered. However, models can range widely in their complexity. A model can incorporate concepts such as reproduction number, herd immunity, seasonality, host heterogeneity, waning immunity, and uncertainty. For available treatment, vaccination, quarantine and isolation, or other interventions, it can be critical to know their basic effectiveness, how they are being used, and their acceptance. All of these factors determine the structure of the selected model, how it is implemented, its accuracy, and its utility. Ultimately, however simple or complex the selected models are, careful validation, accessibility, and effective communication to its intended audience(s) will determine its public health impact.
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Greening, B., Meltzer, M.I. (2023). Modeling Viral Distribution: Transmission and Control. In: Kaslow, R.A., Stanberry, L.R., Powers, A.M. (eds) Viral Infections of Humans. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-9544-8_60-1
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