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Background The 2022 monkeypox (mpox) outbreak in Los Angeles County (LAC) emphasized the need to prepare for emergent infectious disease outbreaks. Vaccination and promotion of sexual risk reduction practices appeared successful in LAC, as mpox cases declined starting in August. Nonetheless, questions persisted regarding the effectiveness of targeting vaccinations and the role of sexual risk reduction in reducing mpox cases. Methods We collaborated with the LAC Department of Public Health to develop a microsimulation for men who have sex with men (MSM). This model tracked mpox dynamics by age, race/ethnicity, and HIV status and was calibrated and validated against surveillance data. We simulated counterfactual scenarios to understand the effects of variation in vaccination rates, timing of vaccination rollout, vaccine allocation, and sexual contact rates. Results In the simulation, doubling the vaccination rate reduced cumulative cases over a 40-week time horizon by 13% but would necessitate 88 995 additional doses. Initiating vaccination 2 weeks earlier decreased cases by 11%, while an 8-week delay yielded a 20% increase in cases. A 3-week earlier decrease in sexual contact rates reduced cumulative cases by 60%, while a 3-week delay resulted in a 95% increase. Prioritizing people with HIV (PWH) for vaccination reduced cumulative cases, while allocating vaccines to a single racial/ethnic group was not effective. Conclusions Our study highlights the significance of policies to support timely vaccination and sexual partnership reduction to address mpox outbreaks among MSM. These findings also underscore the need to target vulnerable risk groups, such as PWH. 

Sequential decision-making problems in the context of uncertainty naturally arise in healthcare settings. In general, the frequency at which decisions can be made or changed is determined by physical limitations, such as the frequency of doctor’s visits or transplantation offers. Quantifying the benefits of increasing the frequency of decision-making allows us to quantify the value of changing these physical constraints and thus improve the quality of care. In this article, we study the value provided by having additional decision-making opportunities in each epoch. We model this problem using a Markov Decision Process (MDP) framework. We provide structural properties of the optimal policies and quantify the difference in optimal values between MDP problems of different decision-making frequencies. We analyze numerical examples using liver transplantation in high-risk patients and treatment initiation in chronic kidney disease to illustrate our findings.