Characterizing spatiotemporal variation in transmission heterogeneity during the 2022 mpox outbreak in the USA

Transmission heterogeneity plays a critical role in the dynamics of an epidemic. During an outbreak of an emerging infectious disease, efforts to characterize transmission heterogeneity are generally limited to quantifications during a small outbreak or a limited number of generations of a larger outbreak. Understanding how transmission heterogeneity itself varies over the course of a large enduring outbreak not only improves understanding of observed disease dynamics but also informs public health strategy and response. In this study, we employ a method, adaptable to other emerging infectious disease outbreaks, to quantify spatiotemporal variation in transmission heterogeneity for the 2022 mpox outbreak in the United States. Based on past research on mpox and following reports of potential superspreading events early in this outbreak, we expected to find high transmission heterogeneity as quantified by the dispersion parameter of the offspring distribution, k. Our methods use maximum likelihood estimation to fit a negative binomial distribution to transmission chain offspring distributions informed by a large mpox contact tracing dataset. We find that, while estimates of transmission heterogeneity varied across the outbreak with spatiotemporal pockets of higher heterogeneity, overall transmission heterogeneity was low. When testing our methods on simulated data from an outbreak with high transmission heterogeneity, k estimate accuracy depended on the contact tracing data completeness. Because the actual contact tracing data had high incompleteness, our values of k estimated from the empirical data may be artificially high. However, it is also possible that our estimates accurately reflect low transmission heterogeneity for the United States mpox outbreak. ### Competing Interest Statement JL, TRS, GGVY, AT, MHS, LTK, and DJT acknowledge research support by the Centers for Disease Control and Prevention (1U01CK000585; 75D30121F00003) ### Funding Statement JL, TRS, GGVY, AT, MHS, LTK, and DJT acknowledge research support by the Centers for Disease Control and Prevention (1U01CK000585; 75D30121F00003) ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This activity was reviewed by CDC and conducted consistent with applicable federal law and CDC policy. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Code to replicate the simulation-based methods will be made publicly available upon acceptance for publication. Data used in the empirical analysis is individually identifiable and will not be made publicly available.