Epidemiology of Pathogen-Specific Respiratory Infections Among Three US Populations

Respiratory infections make up a huge part of disease burden globally. However, confirmatory diagnostic tests can be costly and time-consuming. Therefore, identifying respiratory pathogens through signs, symptoms, and demographic characteristics, as well as improving our understanding of coinfection rates and seasonality, can improve treatment and prevention measures. Methods. Febrile respiratory illness (FRI) and severe acute respiratory infection (SARI) surveillance was conducted from October 2011 and March 2013 among three US populations: civilians near the US-Mexico border, DoD beneficiaries, and military recruits. Nasal or combination nasal/pharyngeal swabs and questionnaire data were collected from participants. A multinomial model was created to identify characteristics predictive of influenza, rhinovirus, other pathogens, and no/unknown pathogen. Additionally, coinfection rates, and seasonality were described. Results. A total of 1444 patients met the FRI case definition and were enrolled in this study. The multinomial model included study population, season, sore throat, cough, shortness of breath, congestion, body ache, headache, fever, and days to seeking care. Coinfections were found in 6% of all FRI/SARI cases tested and were most frequently seen with rhinovirus infections. Clear seasonality trends were seen for influenza, rhinovirus, and respiratory syncytial virus. Conclusions. The results of this study can help inform timeliness and accuracy of treatment plans, establish baselines of infection, identify outbreaks, and help prioritize the development of new vaccines and future treatments. Pub. in PLOS One, v9 n12 p1-16, 30 December 2014.