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Objective. To propose and test a model for analyzing municipalities’ level of risk of reintroduction and transmission of the measles virus in the post-elimination period in the Americas. Methods. An ecological-analytical study was conducted using data on the measles epidemic that occurred in 2013–2015 in northeastern Brazil. The variables for analysis were selected after an extensive review of scientific literature on the risk of importation of measles cases. A univariate analysis considering the presence or absence of confirmed cases of measles in 184 municipalities in the state of Ceará, Brazil, was carried out to evaluate the association between the dependent variable and 23 independent variables, grouped into four categories: 1) characteristics of the municipalities; 2) quality indicators for immunization programs and epidemiological surveillance; 3) organizational structure for the public health response; and 4) selected impact indicators. A P value < 0.05 was considered significant. All variables with P < 0.200 were analyzed using multivariate logistic regression. Based on the results, the municipalities were categorized by four levels of risk (“low,” “medium,” “high,” and “very high”). Results. The model sensitivity was 95% for concordance between municipalities classified as “high risk” and “very high risk” and those that had an epidemic between 2013 and 2015 in Ceará. Of the 38 municipalities that had an epidemic, 76% (29/38) were classified as “high risk” and “very high risk”; 146 municipalities did not report cases (P < 0.0002). Conclusions. Given the imminent risk of reintroduction of measles circulation in the post-elimination period in the Americas, this model may be useful in identifying areas at greater risk for reintroduction and continued transmission of measles. Knowledge of vulnerable areas could trigger appropriate surveillance and monitoring to prevent sustained transmission.

s / International Journal of Infectious Diseases 79(S1) (2019) 1-150 125 account vaccine efficacy. A range of vaccine coverages were generated using an algorithm controlled by two parameters that specify the size and depth of heterogeneities. Transmission dynamics were performed on a highly resolved spatial description of the human geographical distribution at a resolution of 5 km which included individual mobility.Results: We found that, assuming an average vaccine coverage of 92%, corresponding to the seroprevalence measured in the United States in 2015, the number of annual cases and outbreak sizes reported in recent years is compatible with the number of estimated importations combined with a highly subcritical reproductive number and a moderately heterogeneous vaccine coverage. Under these conditions, outbreaks of the size of the 2015 California outbreak are not rare. We also show that localized drops in vaccine coverage may lead to a catastrophic failure of herd immunity if they exceed a heterogeneity dependent threshold.Conclusion: Given the current average level of vaccine coverage, outbreaks with sizes similar to the 2015 California one may occur in the future. However, the fact that the effective reproductive number is highly subcritical confirms the high level of control over measles currently enforced in the United States.Purpose: Epidemics pose a significant risk for human and economic losses, yet this risk is challenging to quantify. Current methods for assessing epidemic risk are typically based on observational data, which are often sparse and incomplete. Global simulation models of infectious disease spread allow us to simulate spatiotemporal dynamics of hypothetical epidemic scenarios. Sovereign nations in Africa are at risk of experiencing filovirus epidemics, which can have devastating financial impacts. These models can help fill in the gaps in observational data and provide a clearer picture of epidemic risk. Methods & Materials:We used a stochastic epidemic model to simulate over 200,000 filovirus epidemics, with varying initial parameters and differing availability and efficacy of intervention measures. Probability distributions of model parameters such as spark location, transmissibility, and case-fatality ratio were derived from the primary literature and historic case data. We constructed an event catalog by selecting simulated events using a sampling algorithm that accounted for the joint probability of each parameter combination for each scenario and the inter-arrival time distribution between filovirus epidemics. The event catalog was then used to generate exceedance probability metrics, which estimate the likelihood of observing an event of a given severity (e.g., expected deaths), or worse, in any given year.Results: Based on our analysis, there is a 1.5% probability that a filovirus epidemic similar to or worse than the 2014 West Africa Ebola epidemic (based on global deaths) will occur in any given year. The countries that are predicted to most commonly experience filovir...