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

Understanding how transmission heterogeneity varies over the course of an enduring infectious disease outbreak improves understanding of observed disease dynamics and informs public health strategy. We quantified the spatiotemporal variation in transmission heterogeneity for the 2022 mpox outbreak in the US using the dispersion parameter of the offspring distribution, k . Our methods fit negative binomial distributions to transmission chain offspring distributions informed by a large mpox contact tracing dataset. We found that estimates of transmission heterogeneity varied across the outbreak, but overall estimated transmission heterogeneity was low. When testing our methods on simulated data, estimate accuracy depended on contact tracing data accuracy and completeness. Because the actual contact tracing data had high incompleteness, the values of k estimated from the empirical data may therefore be artificially high. Through simulation, we explore a method to correct estimated k for data incompleteness and, further, explore baseline expectations for temporal dynamics of k . ### 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I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the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.