Despite the elimination of endemic measles in the United States in the 1990s, the number of measles cases and outbreaks in the United States has begun to rise in recent years, as measles-mumps-rubella (MMR) vaccination rates in the US are declining and transmission internationally is on the rise. Measles is a highly infectious illness that can cause serious symptoms and even death in susceptible individuals, and cases imported to the US often result in large outbreaks that can be devastating to vulnerable populations. The majority of these imported cases reach the US via international passenger air travel through major metropolitan hubs. As a result, a significant proportion of US measles outbreak behavior can be modeled by connecting air travel data with location-specific measles transmission and prevalence statistics. This study sought to develop quantitative parameters for measles outbreak development in large US cities that are significant transit hubs, as influenced by case importation through plane travel. Assessing the probability of an individual’s contact with and subsequent contraction of measles required data input from World Health Organization and Centers from Disease Control and Prevention (CDC) case and disease incidence reports in conjunction with open access global air network projections, which facilitated the establishment of country-specific importation probabilities using maximum likelihood estimation methods. Parameters were verified by comparison of model output, given an 80% data input, to existing CDC outbreak statistics, and revised accordingly.
Results/Conclusions
The resulting calibrated model has sufficient predictive abilities to assess the likelihood of a measles importation event and a resulting outbreak given situational and environmental data. It generated predictions showing strong correlation with observed imported case numbers as well as consistency with seasonal trends, and was used to make further predictions regarding the influence of the 2017 Venezuela outbreak on measles flow between Venezuela and the United States. As such, this model’s performance emphasizes the relationship between global connectedness and the spread of disease, with potential implications for future intervention strategies.