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Integrated Quantification of the Health and Economic Impacts of Differing Strategies to Control the COVID-19 Pandemic

31 Pages Posted: 17 Jun 2020

See all articles by Tony Blakely

Tony Blakely

University of Melbourne - Population Interventions Unit; The University of Melbourne - Centre for Epidemiology and Biostatistics

Laxman Bablani

University of Melbourne - Population Interventions Unit

Natalie Carvalho

University of Melbourne - Health Economics Group

Patrick Andersen

University of Melbourne - Population Interventions Unit

Patrick Abraham

University of Melbourne - Health Economics Group

Ameera Katar

University of Melbourne - Population Interventions Unit

Marie-Anne Boujaoude

University of Melbourne - Health Economics Group

Edifofon Akpan

University of Melbourne - Health Economics Group

Nick Wilson

University of Otago - Burden of Disease Epidemiology, Equity and Cost-Effectiveness Programme

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Abstract

Background: Countries can decide between one of three COVID-19 control strategies: 1) elimination (e.g., some island countries); 2) suppression, to low infection rates; 3) or mitigation, as per pandemic influenza strategies with ensuing herd immunity. This paper quantifies the health (direct COVID-19 impact, and indirect through unemployment onto self-harm and road traffic crash) and cost (health system and societal) consequences for these strategies across Australia, New Zealand (NZ) and Sweden.

Methods: We used proportional multistate lifetable (PMSLT) models for each country, with mortality and morbidity data from the Global Burden of Disease Study and health system expenditure from country-specific sources. Feeding into the PMSLT were monthly SARS-CoV-2 infection rates (0.1%/2.5%/60% for elimination/suppression/mitigation by 18 months), and anticipated changes in unemployment rates that generated changes in suicide/self-harm and RTC injury rates. For Australia and NZ, we also estimated fixed health system costs by strategy and GDP loss for societal costing. We used a 3% per annum discount rate, over a 20-year time horizon. FINDINGS Compared to the pre-pandemic baseline, health adjusted life year (HALY) losses were 15.0/ 11.0/ 23.0 per million population under elimination for Australia/ NZ/ Sweden, 1,540/ 1,500/ 1,820 per million for suppression, and 19,800/ 19,500/ 22,400 for mitigation.

For Australia and NZ, the optimal policy from a health system perspective was mitigation up to a US$20,000 willingness-to-pay (WTP) per HALY gained. For higher WTP, elimination (or suppression if elimination is not feasible) was favoured. From a societal perspective (health system costs plus GDP losses), mitigation was optimal up to US$240,000 per HALY, then elimination (or suppression).

Interpretation: This modelling analysis suggests that elimination or suppression is optimal across the usual range of WTP from a health system perspective in high-income countries (HICs). But from a societal perspective, mitigation is favoured unless a HALY is valued at over US$240,000.

Funding Statement: Health Research Council of New Zealand (16/443) for core model development). Strategic and COVID-19 specific funding for this research was provided by the Melbourne School of Population and Global Health, University of Melbourne. Carvalho is supported by the University of Melbourne McKenzie Postdoctoral Fellowship.

Declaration of Interest: None.

Keywords: SARS-CoV-2; Policy; Elimination; Suppression; Mitigation; Epidemiology; Health economics; net monetary benefit; simulation modelling; cost-effectiveness

Suggested Citation

Blakely, Tony and Bablani, Laxman and Carvalho, Natalie and Andersen, Patrick and Abraham, Patrick and Katar, Ameera and Boujaoude, Marie-Anne and Akpan, Edifofon and Wilson, Nick, Integrated Quantification of the Health and Economic Impacts of Differing Strategies to Control the COVID-19 Pandemic (5/8/2020). Available at SSRN: https://ssrn.com/abstract=3605136 or http://dx.doi.org/10.2139/ssrn.3605136

Tony Blakely (Contact Author)

University of Melbourne - Population Interventions Unit ( email )

Melbourne
Australia

The University of Melbourne - Centre for Epidemiology and Biostatistics ( email )

Laxman Bablani

University of Melbourne - Population Interventions Unit ( email )

Melbourne
Australia

Natalie Carvalho

University of Melbourne - Health Economics Group

Melbourne
Australia

Patrick Andersen

University of Melbourne - Population Interventions Unit

Melbourne
Australia

Patrick Abraham

University of Melbourne - Health Economics Group

Melbourne
Australia

Ameera Katar

University of Melbourne - Population Interventions Unit

Melbourne
Australia

Marie-Anne Boujaoude

University of Melbourne - Health Economics Group

Melbourne
Australia

Edifofon Akpan

University of Melbourne - Health Economics Group

Melbourne
Australia

Nick Wilson

University of Otago - Burden of Disease Epidemiology, Equity and Cost-Effectiveness Programme ( email )

New Zealand

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