Roles and Challenges of Mathematical Modellers in the Era of Coronavirus Disease 2019 (COVID-19) Pandemic
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Abstract
The emergence of Coronavirus Disease 2019 (COVID-19) creates huge opportunity for mathematical modellers to play a pivotal role in policy decision making towards pandemic suppression and containment. Modelling studies can serve as a tool to measure the impact of policies and identify leverage point where the policies will be most effective. Economic evaluation studies combined with epidemic modelling help gauge the economic impact of COVID-19 as well as the monetary benefit and payoff given various COVID-19 measures. The models can also project future end-game scenarios of the pandemic. The academic modellers mostly work with theory-driven research questions, while the service-oriented modellers usually deal with day-to-day operational questions and need to validate the findings against policy direction in equal importance with scientific validation. A platform to finetune diverse understandings and interests between policy-makers and modellers should be established.
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References
Gnanvi JE, Salako KV, Kotanmi GB, Glèlè Kakaï R. On the reliability of predictions on Covid-19 dynamics: A systematic and critical review of modelling techniques. Infectious Disease Modelling. 2021;6:258-72.
George DB, Taylor W, Shaman J, Rivers C, Paul B, O'Toole T, et al. Technology to advance infectious disease forecasting for outbreak management. Nature communications. 2019;10(1):3932.
McBryde ES, Meehan MT, Adegboye OA, Adekunle AI, Caldwell JM, Pak A, et al. Role of modelling in COVID-19 policy development. Paediatr Respir Rev. 2020;35:57-60.
Rhodes T, Lancaster K. Mathematical models as public troubles in COVID-19 infection control: following the numbers. Health sociology review : the journal of the Health Section of the Australian Sociological Association. 2020;29(2):177-94.
De Salazar PM, Niehus R, Taylor A, Buckee CO, Lipsitch M. Identifying Locations with Possible Undetected Imported Severe Acute Respiratory Syndrome Coronavirus 2 Cases by Using Importation Predictions. Emerging infectious diseases. 2020;26(7):1465-9.
Shearer FM, Walker J, Tellioglu N, McCaw JM, McVernon J, Black A, et al. Assessing the risk of spread of COVID-19 to the Asia Pacific region. medRxiv. 2020:2020.04.09.20057257.
Meehan MT, Rojas DP, Adekunle AI, Adegboye OA, Caldwell JM, Turek E, et al. Modelling insights into the COVID-19 pandemic. Paediatr Respir Rev. 2020;35:64-9.
Ferguson N, Laydon D, Nedjati-Gilani G, Imai N, Ainslie KB, M., Bhati S, et al. Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. Imperial College COVID-19 Response Team: Imperial College; 2020 [cited 2021 Mar 3]. Available from: https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf.
James LP, Salomon JA, Buckee CO, Menzies NA. The Use and Misuse of Mathematical Modeling for Infectious Disease Policymaking: Lessons for the COVID-19 Pandemic. Medical decision making : an international journal of the Society for Medical Decision Making. 2021:272989x21990391.
Eker S. Validity and usefulness of COVID-19 models. Humanities and Social Sciences Communications. 2020;7(1):54.
Lancet COVID-19 Commission Statement on the occasion of the 75th session of the UN General Assembly. Lancet (London, England). 2020;396(10257):1102-24.
Aguas R, White L, Hupert N, Shretta R, Pan-Ngum W, Celhay O, et al. Modelling the COVID-19 pandemic in context: an international participatory approach. BMJ Glob Health. 2020;5(12):e003126.
Shea K, Runge MC, Pannell D, Probert WJM, Li S-L, Tildesley M, et al. Harnessing multiple models for outbreak management. Science. 2020;368(6491):577.