The COVID-19 pandemic has created an urgent need for models that can project epidemic trends, explore intervention scenarios, and estimate resource needs. Here we describe the methodology of Covasim (COVID-19 Agent-based Simulator), an open-source model developed to help address these questions. Covasim includes country-specific demographic information on age structure and population size; realistic transmission networks in different social layers, including households, schools, workplaces, long-term care facilities, and communities; age-specific disease outcomes; and intrahost viral dynamics, including viral-load-based transmissibility. Covasim also supports an extensive set of interventions, including non-pharmaceutical interventions, such as physical distancing and protective equipment; pharmaceutical interventions, including vaccination; and testing interventions, such as symptomatic and asymptomatic testing, isolation, contact tracing, and quarantine. These interventions can incorporate the effects of delays, loss-to-follow-up, micro-targeting, and other factors. Implemented in pure Python, Covasim has been designed with equal emphasis on performance, ease of use, and flexibility: realistic and highly customized scenarios can be run on a standard laptop in under a minute. In collaboration with local health agencies and policymakers, Covasim has already been applied to examine epidemic dynamics and inform policy decisions in more than a dozen countries in Africa, Asia-Pacific, Europe, and North America.

As vaccination coverage against SARS-CoV-2 increases amidst the emergence and spread of more infectious and potentially more deadly viral variants, decisions on timing and extent of relaxing effective, but unsustainable, non-pharmaceutical interventions (NPIs) need to be made. An individual-based transmission model of SARS-CoV-2 dynamics, OpenCOVID, was developed to compare the impact of various vaccination and NPI strategies on the COVID-19 epidemic in Switzerland. OpenCOVID uses the Oxford Containment Health Index (OCHI) to quantify the stringency of NPIs. Even if NPIs in place in March 2021 were to be maintained and the vaccine campaigns rollout rapidly scaled-up, a ‘third wave’ was predicted. However, we find a cautious phased relaxation can substantially reduce population-level morbidity and mortality. We find that a faster vaccination campaign can offset the size of such a wave, allowing more flexibility for NPIs to be relaxed sooner. Model outcomes were most sensitive to the level of infectiousness of variants of concern observed in Switzerland. A rapid vaccination rollout can allow the sooner relaxation of NPIs, however ongoing surveillance of - and swift responses to - emerging viral variants is of utmost importance for epidemic control.

Introduction: With limited funds available, meeting global health targets requires countries to both mobilize and prioritize their health spending. Within this context, countries have recognized the importance of allocating funds forHIVas efficiently as possible to maximize impact. Over the past six years, the governments of 23 countries in Africa, Asia, Eastern Europe and Latin America have used the OptimaHIVtool to estimate the optimal allocation ofHIVresources.Methods: Each study commenced with a request by the national government for technical assistance in conducting anHIVallocative efficiency study using OptimaHIV. Each study team validated the required data, calibrated the OptimaHIVepidemic model to produceHIVepidemic projections, agreed on cost functions for interventions, and used the model to calculate the optimal allocation of available funds to best address national strategic plan targets. From a review and analysis of these 23 country studies, we extract common themes around the optimal allocation ofHIVfunding in different epidemiological contexts.Results and discussion: The optimal distribution ofHIVresources depends on the amount of funding available and the characteristics of each country's epidemic, response and targets. Universally, the modelling results indicated that scaling up treatment coverage is an efficient use of resources. There is scope for efficiency gains by targeting theHIVresponse towards the populations and geographical regions whereHIVincidence is highest. Across a range of countries, the model results indicate that a more efficient allocation ofHIVresources could reduce cumulative newHIVinfections by an average of 18% over the years to 2020 and 25% over the years to 2030, along with an approximately 25% reduction in deaths for both timelines. However, in most countries this would still not be sufficient to meet the targets of the national strategic plan, with modelling results indicating that budget increases of up to 185% would be required.Conclusions: Greater epidemiological impact would be possible through better targeting of existing resources, but additional resources would still be required to meet targets. Allocative efficiency models have proven valuable in improving theHIVplanning and budgeting process.

Background Vaccinations have reduced severe burden of COVID-19 and allowed for lifting of non-pharmaceutical interventions. However, with immunity waning alongside emergence of more transmissible variants of concern, vaccination strategies must be examined. Methods Here we apply a SARS-CoV-2 transmission model to identify preferred frequency, timing, and target groups for vaccine boosters to reduce public health burden and health systems risk. We estimated new infections and hospital admissions averted over 2 years through annual or biannual boosting of those eligible (those who received doses one and two) who are (1) most vulnerable (60+ or living with comorbidities) or (2) those 5+, at universal (98% of eligible) or lower coverage (85% of those 50+ or with comorbidities and 50% of 5–49 year olds) representing moderate vaccine fatigue and/or hesitancy. We simulated three emerging variant scenarios: (1) no new variants; (2) 25% more infectious and immune-evading Omicron-level severity variants emerge annually and become dominant; (3) emerge biannually. We further explored the impact of varying seasonality, variant immune-evading capacity, infectivity, severity, timing, and vaccine infection blocking assumptions. Results To reduce COVID-19-related hospitalisations over the next 2 years, boosters should be provided for all those eligible annually 3–4 months ahead of peak winter whether or not new variants of concern emerge. Only boosting those most vulnerable is unlikely to ensure reduced stress on health systems. Moreover, boosting all eligible better protects those most vulnerable than only boosting the vulnerable group. Conversely, while this strategy may not ensure reduced stress on health systems, as an indication of cost-effectiveness, per booster dose more hospitalisations could be averted through annual boosting of those most vulnerable versus all eligible, since those most vulnerable are more likely to seek hospital care once infected, whereas increasing to biannual boosting showed diminishing returns. Results were robust when key model parameters were varied. However, we found that the more frequently variants emerge, the less the effect boosters will have, regardless of whether administered annually or biannually. Conclusions Delivering well-timed annual COVID-19 vaccine boosters to all those eligible, prioritising those most vulnerable, can reduce infections and hospital admissions. Findings provide model-based evidence for decision-makers to plan for administering COVID-19 boosters ahead of winter 2022–2023 to help mitigate the health burden and health system stress.

Introduction: The COVID-19 pandemic has caused widespread disruptions including to health services. In the early response to the pandemic many countries restricted population movements and some health services were suspended or limited. In late 2020 and early 2021 some countries re-imposed restrictions. Health authorities need to balance the potential harms of additional SARS-CoV-2 transmission due to contacts associated with health services against the benefits of those services, including fewer new HIV infections and deaths. This paper examines these trade-offs for select HIV services. Methods: We used four HIV simulation models (Goals, HIV Synthesis, Optima HIV and EMOD) to estimate the benefits of continuing HIV services in terms of fewer new HIV infections and deaths. We used three COVID-19 transmission models (Covasim, Cooper/Smith and a simple contact model) to estimate the additional deaths due to SARS-CoV-2 transmission among health workers and clients. We examined four HIV services: voluntary medical male circumcision, HIV diagnostic testing, viral load testing and programs to prevent mother-to-child transmission. We compared COVID-19 deaths in 2020 and 2021 with HIV deaths occurring now and over the next 50 years discounted to present value. The models were applied to countries with a range of HIV and COVID-19 epidemics. Results: Maintaining these HIV services could lead to additional COVID-19 deaths of 0.002 to 0.15 per 10,000 clients. HIV-related deaths averted are estimated to be much larger, 19–146 discounted deaths per 10,000 clients. Discussion: While there is some additional short-term risk of SARS-CoV-2 transmission associated with providing HIV services, the risk of additional COVID-19 deaths is at least 100 times less than the HIV deaths averted by those services. Ministries of Health need to take into account many factors in deciding when and how to offer essential health services during the COVID-19 pandemic. This work shows that the benefits of continuing key HIV services are far larger than the risks of additional SARS-CoV-2 transmission.