Modeling the 2022 mpox outbreak with a mechanistic network model.

BACKGROUND: The 2022 outbreak of mpox affected more than 80,000 individuals worldwide, most of whom were gay, bisexual, and other men who have sex with men (GBMSM) who likely contracted the disease through close contact during sex. Given the unprecedented number of mpox infections and the new route of infection, there was substantial uncertainty about how best to manage the outbreak. METHODS: We implemented a dynamic agent-based network model to simulate the spread of mpox in a United States-based GBMSM population. This model allowed us to implement data-informed dynamic network evolution to simulate realistic disease spreading and behavioral adaptations. RESULTS: We found that behavior change, the reduction in one-time partnerships, and widespread vaccination are effective in preventing the transmission of mpox, and that earlier vaccination and behavior adaptation has a greater effect, even when only a high-activity portion of the population participates. With no vaccination or behavior adaptation, 16% of the population was infected (25th percentile, 75th percentiles of simulations: 15.3%, 16.6%). With vaccination and behavior change in only the 25% of GBMSM most likely to have a one-time partner, cumulative infections were reduced by 30%, or a total reduction in nearly 500 infections (mean: 11.3%, [Formula: see text] and [Formula: see text]: 9.4%, 13.4%). Earlier vaccination and behavior adaptation further reduce cumulative infections; beginning vaccination a year before the outbreak results in only 2.6% of GBMSM being infected, averting 1300 infections or nearly 13% of the total population in our model. We also show that sustained partnerships drive the early outbreak, while one-time partnerships drive transmission after the first initial weeks. The median effective reproductive number, [Formula: see text], at [Formula: see text] days is 1.40 for casual partnerships, 1.00 for main, and 0.35 for one-time. By [Formula: see text], the median [Formula: see text] for one-time partnerships more than tripled to 1.47, while it decreases for casual and main partnerships: 0.37 and 0.19, respectively. CONCLUSION: With the ability to model individuals' behavior, mechanistic networks are particularly well suited to studying sexually transmitted infections, the spread and control of which are often governed by individual-level action. Our results contribute valuable insights into the role of different outbreak mitigation strategies and relationship types in mpox transmission dynamics.