ArticleeLife2023
A modelling approach to estimate the transmissibility of SARS-CoV-2 during periods of high, low, and zero case incidence.
Article in eLife, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Viral genotype and the pace of epidemic waves: an assessment from SARS-CoV 2 genomics and wastewater surveillance data.Archives of virology · 2026Article
- Ensemble forecasts of COVID-19 activity to support Australia's pandemic response: 2020-22.PLoS computational biology · 2026Article
- Enhancing time-varying reproduction number estimates for COVID-19 with behavior and surveillance data in South Korea, 2020-2022.Archives of public health = Archives belges de sante publique · 2026Article
- Health impact and cost-effectiveness of COVID-19 booster vaccination strategies in the early post-Omicron era: a dynamic modelling study.BMJ global health · 2025Article
- A modular approach to forecasting COVID-19 hospital bed occupancy.Communications medicine · 2025Article
- The importance of playing the long game when it comes to pandemic surveillance.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Simulation-based inference of the time-dependent reproduction number from temporally aggregated and under-reported disease incidence time series data.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Article
- Quantifying age-specific household contacts in Aotearoa New Zealand for infectious disease modelling.Royal Society open science · 2024Article
- Structured methods for parameter inference and uncertainty quantification for mechanistic models in the life sciences.Royal Society open science · 2024Article
- Jointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New Zealand.Communications medicine · 2024Article
- Is SARS-CoV-2 elimination or mitigation best? Regional and disease characteristics determine the recommended strategy.Royal Society open science · 2024Article
- Key Challenges for Respiratory Virus Surveillance while Transitioning out of Acute Phase of COVID-19 Pandemic.Emerging infectious diseases · 2024Article
- Near-term forecasting of Covid-19 cases and hospitalisations in Aotearoa New Zealand.PLoS computational biology · 2024Article
- COVID-19 vaccine coverage targets to inform reopening plans in a low incidence setting.Proceedings. Biological sciences · 2023Article
- Forecasting COVID-19 activity in Australia to support pandemic response: May to October 2020.Scientific reports · 2023Article
- Article
- Modelling the dynamics of infection, waning of immunity and re-infection with the Omicron variant of SARS-CoV-2 in Aotearoa New Zealand.Epidemics · 2022Article
- Using mechanistic model-based inference to understand and project epidemic dynamics with time-varying contact and vaccination rates.Scientific reports · 2022Article
- Minimising the use of costly control measures in an epidemic elimination strategy: A simple mathematical model.Mathematical biosciences · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Against a backdrop of widespread global transmission, a number of countries have successfully brought large outbreaks of COVID-19 under control and maintained near-elimination status. A key element of epidemic response is the tracking of disease transmissibility in near real-time. During major outbreaks, the effective reproduction number can be estimated from a time-series of case, hospitalisation or death counts. In low or zero incidence settings, knowing the potential for the virus to spread is a response priority. Absence of case data means that this potential cannot be estimated directly. We present a semi-mechanistic modelling framework that draws on time-series of both behavioural data and case data (when disease activity is present) to estimate the transmissibility of SARS-CoV-2 from periods of high to low - or zero - case incidence, with a coherent transition in interpretation across the changing epidemiological situations. Of note, during periods of epidemic activity, our analysis recovers the effective reproduction number, while during periods of low - or zero - case incidence, it provides an estimate of transmission risk. This enables tracking and planning of progress towards the control of large outbreaks, maintenance of virus suppression, and monitoring the risk posed by re-introduction of the virus. We demonstrate the value of our methods by reporting on their use throughout 2020 in Australia, where they have become a central component of the national COVID-19 response.
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