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Diagnostic tests for respiratory infections can be costly and time-consuming. Improved characterization of specific respiratory pathogens by identifying frequent signs, symptoms and demographic characteristics, along with improving our understanding of coinfection rates and seasonality, may improve treatment and prevention measures. Febrile respiratory illness (FRI) and severe acute respiratory infection (SARI) surveillance was conducted from October 2011 through March 2013 among three US populations: civilians near the US-Mexico border, Department of Defense (DoD) beneficiaries, and military recruits. Clinical and demographic questionnaire data and respiratory swabs were collected from participants, tested by PCR for nine different respiratory pathogens and summarized. Age stratified characteristics of civilians positive for influenza and recruits positive for rhinovirus were compared to other and no/unknown pathogen. Seasonality and coinfection rates were also described. A total of 1444 patients met the FRI or SARI case definition and were enrolled in this study. Influenza signs and symptoms varied across age groups of civilians. Recruits with rhinovirus had higher percentages of pneumonia, cough, shortness of breath, congestion, cough, less fever and longer time to seeking care and were more likely to be male compared to those in the no/unknown pathogen group. Coinfections were found in 6% of all FRI/SARI cases tested and were most frequently seen among children and with rhinovirus infections. Clear seasonal trends were identified for influenza, rhinovirus, and respiratory syncytial virus. The age-stratified clinical characteristics associated with influenza suggest that age-specific case definitions may improve influenza surveillance and identification. Improving identification of rhinoviruses, the most frequent respiratory infection among recruits, may be useful for separating out contagious individuals, especially when larger outbreaks occur. Overall, describing the epidemiology of pathogen specific respiratory diseases can help improve clinical diagnoses, establish baselines of infection, identify outbreaks, and help prioritize the development of new vaccines and treatments.

Surveillance plays a vital role in disease detection, but traditional methods of collecting patient data, reporting to health officials, and compiling reports are costly and time consuming. In recent years, syndromic surveillance tools have expanded and researchers are able to exploit the vast amount of data available in real time on the Internet at minimal cost. Many data sources for infoveillance exist, but this study focuses on status updates (tweets) from the Twitter microblogging website. The aim of this study was to explore the interaction between cyberspace message activity, measured by keyword-specific tweets, and real world occurrences of influenza and pertussis. Tweets were aggregated by week and compared to weekly influenza-like illness (ILI) and weekly pertussis incidence. The potential effect of tweet type was analyzed by categorizing tweets into 4 categories: nonretweets, retweets, tweets with a URL Web address, and tweets without a URL Web address. Tweets were collected within a 17-mile radius of 11 US cities chosen on the basis of population size and the availability of disease data. Influenza analysis involved all 11 cities. Pertussis analysis was based on the 2 cities nearest to the Washington State pertussis outbreak (Seattle, WA and Portland, OR). Tweet collection resulted in 161,821 flu, 6174 influenza, 160 pertussis, and 1167 whooping cough tweets. The correlation coefficients between tweets or subgroups of tweets and disease occurrence were calculated and trends were presented graphically. Correlations between weekly aggregated tweets and disease occurrence varied greatly, but were relatively strong in some areas. In general, correlation coefficients were stronger in the flu analysis compared to the pertussis analysis. Within each analysis, flu tweets were more strongly correlated with ILI rates than influenza tweets, and whooping cough tweets correlated more strongly with pertussis incidence than pertussis tweets. Nonretweets correlated more with disease occurrence than retweets, and tweets without a URL Web address correlated better with actual incidence than those with a URL Web address primarily for the flu tweets. This study demonstrates that not only does keyword choice play an important role in how well tweets correlate with disease occurrence, but that the subgroup of tweets used for analysis is also important. This exploratory work shows potential in the use of tweets for infoveillance, but continued efforts are needed to further refine research methods in this field.

Periodontitis is a progressive disease of the periodontium with a complex, polymicrobial etiology. Recent Next-Generation Sequencing (NGS) studies of the microbial diversity associated with periodontitis have revealed strong, community-level differences in bacterial assemblages associated with healthy or diseased periodontal sites. In this study, we used NGS approaches to characterize changes in periodontal pocket bacterial diversity after standard periodontal treatment. Despite consistent changes in the abundance of certain taxa in individuals whose condition improved with treatment, post-treatment samples retained the highest similarity to pre-treatment samples from the same individual. Deeper phylogenetic analysis of periodontal pathogen-containing genera Prevotella and Fusobacterium found both unexpected diversity and differential treatment response among species. Our results highlight how understanding interpersonal variability among microbiomes is necessary for determining how polymicrobial diseases respond to treatment and disturbance.

Existing influenza surveillance in the United States is focused on the collection of data from sentinel physicians and hospitals; however, the compilation and distribution of reports are usually delayed by up to 2 weeks. With the popularity of social media growing, the Internet is a source for syndromic surveillance due to the availability of large amounts of data. In this study, tweets, or posts of 140 characters or less, from the website Twitter were collected and analyzed for their potential as surveillance for seasonal influenza. There were three aims: (1) to improve the correlation of tweets to sentinel-provided influenza-like illness (ILI) rates by city through filtering and a machine-learning classifier, (2) to observe correlations of tweets for emergency department ILI rates by city, and (3) to explore correlations for tweets to laboratory-confirmed influenza cases in San Diego. Tweets containing the keyword \"flu\" were collected within a 17-mile radius from 11 US cities selected for population and availability of ILI data. At the end of the collection period, 159,802 tweets were used for correlation analyses with sentinel-provided ILI and emergency department ILI rates as reported by the corresponding city or county health department. Two separate methods were used to observe correlations between tweets and ILI rates: filtering the tweets by type (non-retweets, retweets, tweets with a URL, tweets without a URL), and the use of a machine-learning classifier that determined whether a tweet was \"valid\", or from a user who was likely ill with the flu. Correlations varied by city but general trends were observed. Non-retweets and tweets without a URL had higher and more significant (P<.05) correlations than retweets and tweets with a URL. Correlations of tweets to emergency department ILI rates were higher than the correlations observed for sentinel-provided ILI for most of the cities. The machine-learning classifier yielded the highest correlations for many of the cities when using the sentinel-provided or emergency department ILI as well as the number of laboratory-confirmed influenza cases in San Diego. High correlation values (r=.93) with significance at P<.001 were observed for laboratory-confirmed influenza cases for most categories and tweets determined to be valid by the classifier. Compared to tweet analyses in the previous influenza season, this study demonstrated increased accuracy in using Twitter as a supplementary surveillance tool for influenza as better filtering and classification methods yielded higher correlations for the 2013-2014 influenza season than those found for tweets in the previous influenza season, where emergency department ILI rates were better correlated to tweets than sentinel-provided ILI rates. Further investigations in the field would require expansion with regard to the location that the tweets are collected from, as well as the availability of more ILI data.

Hookah use is gaining popularity nationwide. We determined the correlates and trends for hookah use from the California Tobacco Survey. Between 2005 and 2008 hookah use increased more than 40%, and in 2008, 24.5% of young men reported ever using a hookah. Hookah use was more common among the young (18–24 years), the educated, the non-Hispanic Whites, and the cigarette smokers. Hookah use is increasing in California, especially among young adults, and in 2008 reached the highest prevalence ever reported for both genders.

Introduction: Hookah use is increasing among young people, but there are limited data on its use among high school-age populations. We examined hookah use initiation, prevalence, cessation, and psychosocial risk factors of hookah use among high school students. Methods: A cross-sectional survey of 689 students from three high schools in San Diego County was used to compare characteristics of hookah ever-users to nonusers and factors associated with current and former hookah use. Results: Hookah ever-use in the study population was 26.1%, previous month hookah use was 10.9%, and current hookah use was 10.3%. Most students first learned about hookah from friends (50.3%) or saw a hookah lounge (20.9%). Students believed hookah to be more socially acceptable than cigarettes and less harmful than cigarettes, cigars, and smokeless tobacco. Hookah ever-users were significantly more likely than nonusers to have smoked cigarettes, to know of a hookah lounge in their community, and to believe hookah is safer and more socially acceptable than cigarettes. In comparison to former users, current users were more likely to have recently smoked a cigarette, to know of a hookah lounge in their community, and to believe hookah is more socially acceptable than cigarettes. Conclusions: Hookah use is becoming a commonly acceptable behavior among adolescents, and risk perception is a significant factor. Presence of hookah lounges are associated with increased hookah use among high school students and should be a target of further regulation.

There is evidence to suggest that Latino day laborers experience higher levels of acculturative stress than Latinos in employment sectors in the US. Given the stress-buffering role that social support plays in minimizing the negative physical and mental health outcomes of stress, this study examined this relationship in a sample of 70 Latino Day laborers in the northern San Diego area (100% male, mean age = 27.7, SD = 9.1). Results from multivariate regression analyses showed that there was a significant interaction effect between social support and acculturative stress ( P  = 0.025) on physical health, indicating that higher levels of social support buffered the negative effects of acculturative stress on physical health. Acculturative stress and social support were not associated with mental health status. Overall, these findings suggest that fostering social support may be an essential strategy for promoting health among Latino male day laborers.

Limited research exists on the relationship between physical injury and PTSD within military populations. The present study assessed postinjury rates of PTSD and other psychological correlates among battle and non-battle injuries. A total of 1,968 men (831 battle injuries and 1,137 nonbattle injuries) injured between September 2004 and February 2005 during Operation Iraqi Freedom (OIF) composed the study sample. Patients were followed through November 2006 for mental health diagnosis (ICD-9 290-319). Compared with nonbattle injuries, those with battle injuries had a greater risk of PTSD and other mental health diagnosis, and there was a positive association with injury severity. Self-reported mental health symptoms were significantly higher for both minor and moderate-severe battle injury in comparison to nonbattle injury and previous population estimates from an earlier OIF period. More research is needed to further define this relationship by examining potential mechanisms and addressing the possible contributing effect of combat exposure.

Intimate partner violence is a universal public health and public safety problem. Its disproportionate infliction on women may be influenced by patriarchal beliefs that dismiss violence against the female partner as a socially rationalized act. This is a secondary analysis of a domestic violence survey conducted in a Spanish-speaking community. The relationship between patriarchal beliefs and attitudes toward violence was examined. Agreement with the statement \"some women like to be hit\" was equal for both men and women. This response was also associated with having known someone abused. Sharing a common language, culture, or heritage can also mean sharing common beliefs, attitudes, and experiences. A researcher, educator, or responder who is familiar with these matters can hold a deeper appreciation of a victim's community construct. [PUBLICATION ABSTRACT]