Modelling the estimated likelihood of eliminating the SARS-CoV-2 pandemic in Australia and New Zealand under public health policy settings: an agent-based-SEIR approach.

20 Pages Posted: 7 May 2020 Last revised: 13 Jul 2020

See all articles by Jason Thompson

Jason Thompson

University of Melbourne - Transport, Health and Urban Design Research Hub

Roderick McClure

Rod McClure

Tony Blakely

University of Melbourne - Population Interventions Unit; University of Melbourne

Nick Wilson

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

Michael Baker

University of Otago

Jasper S. Wijnands

University of Melbourne - Transport, Health and Urban Design Research Hub

Thiago Herick de Sa

Thiago Herick de Sa

Kerry Nice

University of Melbourne - Transport, Health and Urban Design Research Hub

Camilo Cruz-Gambardella

Camilo Cruz-Gambardella

Gideon Aschwanden

University of Melbourne - Transport, Health and Urban Design Research Hub

Mark Stevenson

University of Melbourne - Transport, Health and Urban Design Research Hub

Date Written: April 29, 2020

Abstract

Background: For countries with strong border control and an epidemic that is not yet advanced, there is an opportunity to eliminate SARS-CoV-2 that is causing the COVID-19 pandemic. We show how public health policies and their effects can be modelled to estimate the probability of elimination of SARS-COV-2 under i) strict physical distancing policies implemented in New Zealand and Australia on the 26th and 28th March, respectively, continuing until such time that elimination is achieved; and ii) the same policy, but with physical distancing decaying over 60 days to 26th and 28th of May.

Methods: We developed an agent-based SEIR model that simulated key aspects of both country’s populations, disease, spatial and behavioural dynamics, as well as the mechanism and effect of public health policy responses on the transmission of SARS-CoV-2.

Findings: Under maintained strong physical distancing, we estimated a median elimination date of July 12th for Australia (95% SI: June 5th to August 28th) and June 3rd for New Zealand (95% SI May 4th to June 27th). A 90% probability of elimination is achievable in Australia on August 17th (95% SI: August 8th – August 30th) and on June 14th (95% SI: June 17th – June 29th) in New Zealand.

However, under our scenario of decaying adherence to physical distancing from implementation to 60 days post restrictions, a rebound in SARS-CoV-2 infections (i.e., a second wave) was likely in Australia and possibly in New Zealand. At 100 days, the probability of elimination was reduced to 10% in Australia and 68% in New Zealand.

Interpretation: The findings suggest that with the effective implementation and maintenance of public health policies limiting physical interaction, it was possible to estimate a pattern the elimination of SARS-CoV-2 transmission in both countries. It seems highly likely NZ will have successfully eliminated as of 8 June, but not in Australia; the latter is consistent with our lower probabilities that modelled less stringent restrictions applied in Australia.

Note: Funding: MS is funded by a NHMRC Fellowship (APP1136250), JT is funded by an ARC DECRA Fellowship (DE180101411).

Conflict of Interest: The authors declare no competing interests.

Keywords: COVID-19, SARS-CoV-2, Policy Shutdown

Suggested Citation

Thompson, Jason and McClure, Roderick and Blakely, Tony and Wilson, Nick and Baker, Michael and Wijnands, Jasper S. and de Sa, Thaigo Herick and Nice, Kerry and Cruz-Gambardella, Camilo and Aschwanden, Gideon and Stevenson, Mark, Modelling the estimated likelihood of eliminating the SARS-CoV-2 pandemic in Australia and New Zealand under public health policy settings: an agent-based-SEIR approach. (April 29, 2020). Available at SSRN: https://ssrn.com/abstract=3588074 or http://dx.doi.org/10.2139/ssrn.3588074

Jason Thompson

University of Melbourne - Transport, Health and Urban Design Research Hub ( email )

Carlton, Victoria
Australia

Roderick McClure

Rod McClure ( email )

11 Hills Beach Road
Biddeford, ME 04005
United States

Tony Blakely

University of Melbourne - Population Interventions Unit ( email )

Melbourne
Australia

University of Melbourne ( email )

185 Pelham Street
Carlton, Victoria 3053
Australia

Nick Wilson

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

New Zealand

Michael Baker

University of Otago ( email )

P.O. Box 56
Dunedin, Otago 9010
New Zealand

Jasper S. Wijnands

University of Melbourne - Transport, Health and Urban Design Research Hub

Carlton, Victoria
Australia

Thaigo Herick De Sa

Thiago Herick de Sa ( email )

Kerry Nice

University of Melbourne - Transport, Health and Urban Design Research Hub

Carlton, Victoria
Australia

Camilo Cruz-Gambardella

Camilo Cruz-Gambardella ( email )

185 Pelham Street
Carlton, Victoria 3053
Australia

Gideon Aschwanden

University of Melbourne - Transport, Health and Urban Design Research Hub

Carlton, Victoria
Australia

Mark Stevenson (Contact Author)

University of Melbourne - Transport, Health and Urban Design Research Hub

Carlton, Victoria
Australia

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