THE ROLE OF THE MATHEMATICAL SCIENCES IN SUPPORTING THE COVID-19 RESPONSE IN AUSTRALIA AND NEW ZEALAND

Author:

MCCAW JAMES M.ORCID,PLANK MICHAEL J.ORCID

Abstract

AbstractMathematical modelling has been used to support the response to the COVID-19 pandemic in countries around the world including Australia and New Zealand. Both these countries have followed similar pandemic response strategies, using a combination of strict border measures and community interventions to minimize infection rates until high vaccine coverage was achieved. This required a different set of modelling tools to those used in countries that experienced much higher levels of prevalence throughout the pandemic.In this article, we provide an overview of some of the mathematical modelling and data analytics work that has helped to inform the policy response to the pandemic in Australia and New Zealand. This is a reflection on our experiences working at the modelling–policy interface and the impact this has had on the pandemic response. We outline the various types of model outputs, from short-term forecasts to longer-term scenario models, that have been used in different contexts. We discuss issues relating to communication between mathematical modellers and stakeholders such as health officials and policymakers. We conclude with some future challenges and opportunities in this area.

Funder

National Health and Medical Research Council

Te Pūnaha Matatini

Ministry of Business, Innovation and Employment

Ministry of Health, New Zealand

Australian Research Council

Publisher

Cambridge University Press (CUP)

Subject

Mathematics (miscellaneous)

Reference91 articles.

1. Improving the evidence base for decision making during a pandemic: the example of 2009 influenza A/H1N1;Lipsitch;Biosecurity Bioterrorism,2011

2. [69] Price, D. J. , Shearer, F. M. , Meehan, M. , McBryde, E. , Golding, N. , McVernon, J. and McCaw, J. M. , “Estimating the case detection rate and temporal variation in transmission of COVID-19 in Australia: Technical Report 14th April 2020”, IDDU Technical Report, 2020. https://mspgh.unimelb.edu.au/data/assets/pdffile/0007/4230646/2020-04-14-Technicalreport-public-release.pdf.

3. Short-term Projections based on Early Omicron Variant Dynamics in England

4. [11] Datta, S. et al., “Modelling the effect of changes to the COVID-19 case isolation policy”, COVID-19 Modelling Aotearoa, 2023. https://www.covid19modelling.ac.nz/modelling-the-effect-of-changes-to610the-covid-19-case-isolation-policy/.

5. [25] Golding, N. et al., “Estimating the temporal variation in transmission of SARS-CoV-2 and physical distancing behaviour in Australia: Technical Report 17th July 2020”, IDDU Technical Report, 2020. https://mspgh.unimelb.edu.au/data/assets/pdffile/0009/4231188/2020-07-17-Technicalreport-public-release.pdf.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3