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BackgroundExisting 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. ObjectiveThere 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. MethodsTweets 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. ResultsCorrelations varied by city but general trends were observed. Non-retweets and tweets without a URL had higher and more significant (P

BackgroundSurveillance 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. ObjectiveThe 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. MethodsTweets 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. ResultsCorrelations 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. ConclusionsThis 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.

Introduction and aimsPatterns of polydrug use among people who inject drugs (PWID) may be differentially associated with overdose and unique human immunodeficiency virus (HIV) risk factors. Subgroups of PWID in Tijuana, Mexico, were identified based on substances used, route of administration, frequency of use and co-injection indicators.Design and methodsParticipants were PWID residing in Tijuana age ≥18 years sampled from 2011 to 2012 who reported injecting an illicit substance in the past month (n = 735). Latent class analysis identified discrete classes of polydrug use characterised by 11 indicators of past 6 months substance use. Multinomial logistic regression examined class membership association with HIV risk behaviours, overdose and other covariates using an automated three-step procedure in mplus to account for classification error.ResultsParticipants were classified into five subgroups. Two polydrug and polyroute classes were defined by use of multiple substances through several routes of administration and were primarily distinguished from each other by cocaine use (class 1: 5%) or no cocaine use (class 2: 29%). The other classes consisted primarily of injectors: cocaine, methamphetamine and heroin injection (class 3: 4%); methamphetamine and heroin injection (class 4: 10%); and heroin injection (class 5: 52%). Compared with the heroin-only injection class, memberships in the two polydrug and polyroute use classes were independently associated with both HIV injection and sexual risk behaviours.Discussion and conclusionsSubstance use patterns among PWID in Tijuana are highly heterogeneous, and polydrug and polyroute users are a high-risk subgroup who may require more tailored prevention and treatment interventions. [Meacham MC, Roesch SC, Strathdee SA, Lindsay S, Gonzalez-Zuniga P, Gaines TL. Latent classes of polydrug and polyroute use and associations with human immunodeficiency virus risk behaviours and overdose among people who inject drugs in Tijuana, Baja California, Mexico. Drug Alcohol Rev 2018;37:128-136].

Every year billions of chickens are shipped thousands of miles around the globe in order to meet the ever increasing demands for this cheap and nutritious protein source. Unfortunately, transporting chickens internationally can also increase the chance for introducing zoonotic viruses, such as highly pathogenic avian influenza A (H5N1) to new countries. Our study used a retrospective analysis of poultry trading data from 2003 through 2011 to assess the risk of H5N1 poultry infection in an importing country. We found that the risk of infection in an importing country increased by a factor of 1.3 (95% CI: 1.1-1.5) for every 10-fold increase in live chickens imported from countries experiencing at least one H5N1 poultry case during that year. These results suggest that the risk in a particular country can be significantly reduced if imports from countries experiencing an outbreak are decreased during the year of infection or if biosecurity measures such as screening, vaccination, and infection control practices are increased. These findings show that limiting trade of live chickens or increasing infection control practices during contagious periods may be an important step in reducing the spread of H5N1 and other emerging avian influenza viruses.

ObjectiveThe Farmers' Market Fresh Fund Incentive Program is a policy, systems and environmental intervention to improve access to fresh produce for participants on governmental assistance in the USA. The current study examined factors associated with ongoing participation in this matched monetary incentive programme.DesignRelationship of baseline factors with number of Fresh Fund visits was assessed using Poisson regression. Mixed-effects modelling was used to explore changes in consumption of fruits and vegetables and diet quality.SettingSan Diego, California.SubjectsRecipients of Supplemental Nutrition Assistance Program (SNAP), Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) and Supplemental Security Income (SSI) who attended participating farmers' markets from 2010 to 2012 (n 7298).ResultsAmong those with participation for ≤6 months, factors associated with increased visits included reporting more daily servings of fruits and vegetables (F&V) at baseline, being Vietnamese or Asian/Pacific Islander, and eligibility because of SNAP/CalFresh or SSI (v. WIC). Among those who came for 6-12 months, being Asian/Pacific Islander, eligibility because of SNAP/CalFresh and enrolling in the autumn, winter or spring were associated with a greater number of Fresh Fund visits. Among those who came for >12 months, being male and eligibility because of SSI were associated with a greater number of visits. Overall, the odds of increasing number of servings of F&V consumed increased by 2 % per month, and the odds of improved perception of diet quality increased by 10 % per month.ConclusionsSustaining and increasing Fresh Fund-type programme operations should be a top priority for future policy decisions concerning farmers' market use in low-income neighbourhoods.

Objective: Examine the relationship of family meals to children's consumption of fruit and vegetables as well as soda and chips. Additionally, to assess the relationship between viewing TV during family meals and children's diet. Design: Cross-sectional study that used a questionnaire completed by parents. Setting: Thirteen schools in San Diego, California. Participants: Seven hundred ninety-four children and their parents. Analysis: Ordinal regression assessed associations between children's intake of fruit, vegetables, soda, and chips with family meal frequency and TV viewing during family meals. Results: Children who consumed breakfast, lunch, or dinner with their family at least 4 days per week ate fruit and vegetables 5 or more times a week 84%, 85%, and 80%, respectively. Of those children who ate breakfast, lunch, or dinner with their family at least 4 days per week, 40%, 44%, and 43% consumed soda and chips 5 or more times a week, respectively. Children who ate breakfast with their families at least 4 times a week were more likely to consume fruit and vegetables, and children whose TV was never or rarely on during family meals were less likely to consume soda and chips (P = 0.04 and P less than 0.001, respectively). Conclusions: Interventions geared at increasing the frequency of eating breakfast as a family and decreasing the amount of TV watched during family meals are needed, especially among acculturating Latino families. (Contains 3 tables.)

Abstract: Objectives: No studies have focused on socioeconomic disparities in obesity within and between cohorts. Our objectives were to examine income gradients in obesity between birth‐cohorts (inter‐cohort variations) and within each birth‐cohort (intra‐cohort variations) by gender and race/ethnicity. Methods: Our sample includes 56,820 white and black adults from pooled, cross‐sectional National Health and Nutrition Examination Surveys (1971–2012). We fit a series of logistic hierarchical Age‐Period‐Cohort models to control for the effects of age and period, simultaneously. Predicted probabilities of obesity by poverty‐to‐income ratio were estimated and graphed for 5‐year cohort groups from 1901–1990. We also stratified this relationship for four gender and racial/ethnic subgroups. Results: Obesity disparities due to income were weaker for post‐World War I and II generations, specifically the mid‐1920s and the mid‐1940s to 1950s cohorts, than for other cohorts. In contrast, we found greater income gradients in obesity among cohorts from the 1930s to mid‐1940s and mid‐1960s to 1970s. Moreover, obesity disparities due to income across cohorts vary markedly by gender and race/ethnicity. White women with higher income consistently exhibited a lower likelihood of obesity than those with lower income since early 1900s cohorts; whereas, black men with higher income exhibited higher risks of obesity than those with lower income in most cohorts. Conclusions: Our findings suggest that strategies that address race and/or gender inequalities in obesity should be cognizant of significant historical factors that may be unique to cohorts. Period‐based approaches that ignore life‐course experiences captured in significant cohort‐based experiences may limit the utility of policies and interventions. [ABSTRACT FROM AUTHOR]