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Long-term control of SARS-CoV-2 outbreaks depends on the widespread coverage of effective vaccines. In Australia, $>90\% $ two-dose vaccination coverage of the adult population was achieved. However, between August 2020 and August 2021, hesitancy fluctuated dramatically. This left the question whether settings with low naturally derived immunity like Queensland, where $Covasim. We simulated outbreak scenariosThis article is part of the theme issue ‘Technical challenges of modelling real-life epidemics and examples of overcoming these’.

Additional file 1. Additional model details.

Background In settings with zero community transmission, any new SARS-CoV-2 outbreaks are likely to be the result of random incursions. The level of restrictions in place at the time of the incursion is likely to considerably affect possible outbreak trajectories, but the probability that a large outbreak eventuates is not known. Methods We used an agent-based model to investigate the relationship between ongoing restrictions and behavioural factors, and the probability of an incursion causing an outbreak and the resulting growth rate. We applied our model to the state of Victoria, Australia, which has reached zero community transmission as of November 2020. Results We found that a future incursion has a 45% probability of causing an outbreak (defined as a 7-day average of > 5 new cases per day within 60 days) if no restrictions were in place, decreasing to 23% with a mandatory masks policy, density restrictions on venues such as restaurants, and if employees worked from home where possible. A drop in community symptomatic testing rates was associated with up to a 10-percentage point increase in outbreak probability, highlighting the importance of maintaining high testing rates as part of a suppression strategy. Conclusions Because the chance of an incursion occurring is closely related to border controls, outbreak risk management strategies require an integrated approaching spanning border controls, ongoing restrictions, and plans for response. Each individual restriction or control strategy reduces the risk of an outbreak. They can be traded off against each other, but if too many are removed there is a danger of accumulating an unsafe level of risk. The outbreak probabilities estimated in this study are of particular relevance in assessing the downstream risks associated with increased international travel.

In 2014, city leaders from around the world endorsed the Paris Declaration on Fast‐Track Cities, pledging to achieve the 2020 and 2030 HIV targets championed by UNAIDS. The City of Johannesburg – one of South Africa's metropolitan municipalities and also a health district – has over 600,000 people living with HIV (PLHIV), more than any other city worldwide. We estimate what it would take in terms of programmatic targets and costs for the City of Johannesburg to meet the Fast‐Track targets, and demonstrate the impact that this would have.

International investment in the response to HIV and AIDS has plateaued and its future level is uncertain. With many countries committed to ending the epidemic, it is essential to allocate available resources efficiently over different response periods to maximize impact. The objective of this study is to propose a technique to determine the optimal allocation of funds over time across a set of HIV programs to achieve desirable health outcomes. We developed a technique to determine the optimal time‐varying allocation of funds (1) when the future annual HIV budget is pre‐defined and (2) when the total budget over a period is pre‐defined, but the year‐on‐year budget is to be optimally determined. We use this methodology with Optima, an HIV transmission model that uses non‐linear relationships between program spending and associated programmatic outcomes to quantify the expected epidemiological impact of spending. We apply these methods to data collected from Zambia to determine the optimal distribution of resources to fund the right programs, for the right people, at the right time.