Estimating the syphilis epidemic among gay, bisexual and other men who have sex with men in Australia following changes in HIV care and prevention.

Background Syphilis control remains a challenge in many high-income countries, including Australia, where diagnoses are concentrated among gay, bisexual men and other men who have sex with men (GBM). The aim of this study is to project the syphilis epidemic among GBM under a range of scenarios. METHODS: A dynamic coinfection model of HIV and syphilis transmission among GBM in Victoria, Australia, was parametrised to test data from clinics in Melbourne and syphilis case notifications in Victoria. Projected outcomes were new syphilis infections between 2018 and 2025 under seven testing and behaviour change scenarios. RESULTS: Among HIV-negative GBM, the model estimated that increasing syphilis testing coverage (69% - 75%) and frequency (~8-monthly - 6-monthly) could prevent 5% and 13% of syphilis cases respectively between 2018 and 2025 compared to the status quo. Among HIV-positive GBM, less syphilis testing due to changes in HIV care increased syphilis cases by 29% between 2018 and 2025 compared to the status quo. Under a scenario of 20% HIV pre-exposure prophylaxis (PrEP) coverage among HIV-negative GBM (and associated increased serodiscordant sex, reduced condom use and increased syphilis testing), syphilis cases were estimated to decrease by 6% among HIV-negative GBM and by 3% among HIV-positive GBM compared to the status quo, driven by increased testing among PrEP users. CONCLUSION: The present study findings support syphilis control policies focusing on increased testing among GBM. Current Australian PrEP guidelines of quarterly syphilis testing are likely to negate any increases in syphilis due to risk compensation occurring with PrEP scale-up.

A global investment case for hepatitis B elimination: a modelling study.

Hepatitis B is estimated to cause 500 000-900 000 deaths globally each year. WHO has targets for elimination by 2030; however, progress has stalled due to multiple barriers, notably a paucity of global funding and insufficient evidence on the economic burden of disease. Using a dynamic mathematical model of hepatitis B transmission, disease progression, and mortality in the six WHO regions, we estimate the costs and benefits of reaching 90% vaccination, 90% diagnosis, and 80% treatment coverage by either 2030 (as targeted), 2040, or 2050. Without increased intervention coverage, hepatitis B mortality was estimated to cost US$784·35 billion (95% Crl 731·63-798·33 billion) globally in lost productivity over 2022-50. Achieving targets by 2030 averted 25·64 million infections (95% Crl 17·39-34·55 million) and 8·63 million hepatitis B-attributable deaths (95% Crl 7·12-9·74 million) over 2022-50. This achievement incurred an incremental cost of $2934·55 (95% Crl 2778·55-3173·52) per disability-adjusted life year averted by 2050 under a health systems perspective, and was cost-saving with a net economic benefit of $99·03 billion (95% Crl 78·66-108·96 billion) by 2050 from a societal perspective. Delayed achievement of intervention coverage targets had reduced health and economic benefits. These findings highlight that hepatitis B is an underappreciated cause of economic burden and show investment toward elimination will probably yield substantial returns.

Application of a computational model in simulating an endovascular clot retrieval service system within regional Australia.

INTRODUCTION: The global demand for endovascular clot retrieval (ECR) has grown rapidly in recent years creating challenges to healthcare system planning and resource allocation. This study aims to apply our established computational model to predict and optimise the performance and resource allocation of ECR services within regional Australia, and applying data from the state of South Australia as a modelling exercise. METHOD: Local geographic information obtained using the Google Maps application program interface and real-world data was input into the discrete event simulation model we previously developed. The results were obtained after the simulation was run over 5 years. We modelled and compared a single-centre and two-centre ECR service delivery system. RESULTS: Based on the input data, this model was able to simulate the ECR delivery system in the state of South Australia from the moment when emergency services were notified of a potential stroke patient to potential delivery of ECR treatment. In the model, ECR delivery improved using a two-centre system compared to a one-centre system, as the percentage of stroke patients requiring ECR was increased. When 15% of patients required ECR, the proportion of 'failure to receive ECR' cases for a single-centre system was 17.35%, compared to 3.71% for a two-centre system. CONCLUSIONS: Geolocation and resource utilisation within the ECR delivery system are crucial in optimising service delivery and patient outcome. Under the model assumptions, as the number of stroke cases requiring ECR increased, a two-centre ECR system resulted in increased timely ECR delivery, compared to a single-centre system. This study demonstrated the flexibility and the potential application of our DES model in simulating the stroke service within any location worldwide.

Geographic Service Delivery for Endovascular Clot Retrieval: Using Discrete Event Simulation to Optimize Resources.

BACKGROUND: Endovascular clot retrieval (ECR) is the standard of care for acute ischemic stroke caused by large vessel occlusion. Reducing stroke symptom onset to reperfusion time is associated with improved functional outcomes. This study aims to develop a computational model to predict and identify time-related outcomes of community stroke calls within a geographic area based on variable parameters to support planning and coordination of ECR services. METHODS: A discrete event simulation (DES) model to simulate and predict ECR service was designed using SimPy, a process-based DES framework written in Python. Geolocation data defined by the user, as well as that used by the model, were sourced using the Google Maps application programming interface. Variables were customized by the user on the basis of their local environment to provide more accurate prediction. RESULTS: A DES model can estimate the delay between the time that emergency services are notified of a potential stroke and potential cerebral reperfusion using ECR at a capable hospital. Variables can be adjusted to observe the effect of modifying each parameter input. By varying the percentage of stroke patients receiving ECR, we were able to define the levels at which our existing service begins to fail in service delivery and assess the effect of adding centers. CONCLUSIONS: This novel computational DES model can aid the optimization of delivery of a stroke service within a city, state, or country. By varying geographic, population, and other user-defined inputs, the model can be applied to any location worldwide.