Modelling insights into the COVID-19 pandemic

Meehan, Michael T., Rojas, Diana P., Adekunle, Adeshina I., Adegboye, Oyelola A., Caldwell, Jamie M., Turek, Evelyn, Williams, Bridget, Trauer, James M., and McBryde, Emma S. (2020) Modelling insights into the COVID-19 pandemic. Paediatric Respiratory Reviews, 35. pp. 64-69.

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Coronavirus disease 2019 (COVID-19) is a newly emerged infectious disease caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) that was declared a pandemic by the World Health Organization on 11th March, 2020. Response to this ongoing pandemic requires extensive collaboration across the scientific community in an attempt to contain its impact and limit further transmission. Mathematical modelling has been at the forefront of these response efforts by: (1) providing initial estimates of the SARS-CoV-2 reproduction rate, R0 (of approximately 2–3); (2) updating these estimates following the implementation of various interventions (with significantly reduced, often sub-critical, transmission rates); (3) assessing the potential for global spread before significant case numbers had been reported internationally; and (4) quantifying the expected disease severity and burden of COVID-19, indicating that the likely true infection rate is often orders of magnitude greater than estimates based on confirmed case counts alone. In this review, we highlight the critical role played by mathematical modelling to understand COVID-19 thus far, the challenges posed by data availability and uncertainty, and the continuing utility of modelling-based approaches to guide decision making and inform the public health response.

Item ID: 64224
Item Type: Article (Research - C1)
ISSN: 1526-0550
Keywords: Mathematical modelling; COVID-19; Review; Emerging infectious diseases; Pandemic
Copyright Information: © 2020 Published by Elsevier Ltd.
Date Deposited: 02 Sep 2020 01:15
FoR Codes: 42 HEALTH SCIENCES > 4202 Epidemiology > 420205 Epidemiological modelling @ 100%
SEO Codes: 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920109 Infectious Diseases @ 100%
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