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Competing Interests: VV-V reports personal fees and non-financial support from Novo Nordisk and Merck, not related to this manuscript; VV-V is also the head of Obesidades, a non-profit community in Mexico. All other authors declare no competing interests. FCS is the recipient of National Institutes of Health NIDDK grants P30 DK040561 and U24 DK132733. This funder played no role in the writing of the manuscript nor the decision to submit it for publication. JRJ and LK contributed equally to this work. No author has been paid to write this article by a pharmaceutical company or other agency. Authors were not precluded from accessing data in the study, and they accept responsibility for submitting it for publication.

Understanding the effect of media on disease spread can help improve epidemic forecasting and uncover preventive measures to slow the spread of disease. Most previously introduced models have approximated media effect through disease incidence, making media influence dependent on the size of epidemic. We propose an alternative approach, which relies on real data about disease coverage in the news, allowing us to model low incidence/high interest diseases, such as SARS, Ebola or H1N1. We introduce a network-based model, in which disease is transmitted through local interactions between individuals and the probability of transmission is affected by media coverage. We assume that media attention increases self-protection (e.g. hand washing and compliance with social distancing), which, in turn, decreases disease model. We apply the model to the case of H1N1 transmission in Mexico City in 2009 and show how media influence-measured by the time series of the weekly count of news articles published on the outbreak-helps to explain the observed transmission dynamics. We show that incorporating the media attention based on the observed media coverage of the outbreak better estimates the disease dynamics from what would be predicted by using media function that approximate the media impact using the number of cases and rate of spread. Finally, we apply the model to a typical influenza season in Washington, DC and estimate how the transmission pattern would have changed given different levels of media coverage., Competing Interests: The authors declare the following interests: LK, SF, and NM are employed by the commercial company, The Charles Stark Draper Laboratory (https://www.draper.com/). There are no patents, products in development, or marketed products to declare related to this study. This does not alter the authors’ adherence to all PLOS ONE policies on sharing data and materials.

Rationale: The etiology of recurrent tuberculosis is typically presumed to be reactivation of residual Mycobacterium tuberculosis infection, but reinfection may account for a greater proportion of recurrent tuberculosis than previously recognized., Objective: To use M. tuberculosis genotyping to characterize the etiology of recurrent tuberculosis occurring 12 months or more after treatment completion., Methods: The study population for this national population-based cohort was drawn from the estimated 3,039 persons reported to the National Tuberculosis Surveillance System with two episodes of tuberculosis in the United States during 1993-2011, 194 of whom had genotyping results from both the initial and subsequent episode. We analyzed the proportion of recurrent tuberculosis attributable to and risk factors associated with reinfection., Measurements and Main Results: Among 136 recurrences meeting inclusion criteria, genotypes between episodes were the same for 116 (85%) recurrences during 1996-2011; the 20 (15%) with differing genotypes were categorized as reinfections. Using exact logistic regression, factors associated with reinfection included Mexican birth with both TB episodes diagnosed in the United States within 12 years of immigration (adjusted odds ratio, 10.7; 95% confidence interval, 1.7-86.3) and exclusive use of directly observed therapy for treatment of the first episode (adjusted odds ratio, 4.5; 95% confidence interval, 1.0-29.2)., Conclusions: Reinfection was the cause of 15% of late recurrent tuberculosis cases in this U.S. cohort. The proportion caused by reinfection increased to 60% in certain subpopulations, such as recent immigrants from Mexico, suggesting that, despite successful treatment for tuberculosis during their first episode, these individuals remain in a social environment where they are reexposed to M. tuberculosis. Public health interventions to prevent novel reinfection might require a broader focus in these communities.