Zika Virus-Related News Coverage and Online Behavior, United States, Guatemala, and Brazil.
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ABSTRACT:
SUBMITTER: Southwell BG
PROVIDER: S-EPMC4918164 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Younger and older generations are differently motivated in relation to news consumption and online political expression. In this paper, we suggest that different modes of citizenship characterize younger and older generations. To test the differential role of political interest in news consumption and online political expression, we use a survey of 3,210 people from the United States, 3,043 from the United Kingdom, and 3,031 from France. Our findings suggest that young citizens are more frequent users of online news overall and that the rank order of different news activities replicates cross-nationally. The frequency of online political expression is negatively related to age, with older people less likely to post online. Age moderates the relationship between political interest and news consumption as well as news consumption and online political expression. The correlations of these sets of variables are stronger for younger respondents compared to older respondents. These findings hold across the three countries under study. We explain these patterns in terms of changing citizenship norms and discuss the implications for democracy.
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Project description:The United States is engaged in ongoing dialogue around mental illness. To assess trends in this national discourse, we studied the volume and content of a random sample of 400 news stories about mental illness from the period 1995-2014. Compared to news stories in the first decade of the study period, those in the second decade were more likely to mention mass shootings by people with mental illnesses. The most frequently mentioned topic across the study period was violence (55 percent overall) divided into categories of interpersonal violence or self-directed (suicide) violence, followed by stories about any type of treatment for mental illness (47 percent). Fewer news stories, only 14 percent, described successful treatment for or recovery from mental illness. The news media's continued emphasis on interpersonal violence is highly disproportionate to actual rates of violence among those with mental illnesses. Research suggests that this focus may exacerbate social stigma and decrease support for public policies that benefit people with mental illnesses.
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Project description:We used latent class analysis to examine Zika virus-related information-accessing behavior of US residents during the 2016 international outbreak. We characterized 3 classes of information-accessing behavior patterns: universalists, media seekers, and passive recipients. Understanding these patterns is crucial to planning risk communication during an emerging health threat.
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Project description:In recent years, many studies have drawn attention to the important role of collective awareness and human behaviour during epidemic outbreaks. A number of modelling efforts have investigated the interaction between the disease transmission dynamics and human behaviour change mediated by news coverage and by information spreading in the population. Yet, given the scarcity of data on public awareness during an epidemic, few studies have relied on empirical data. Here, we use fine-grained, geo-referenced data from three online sources-Wikipedia, the GDELT Project and the Internet Archive-to quantify population-scale information seeking about the 2016 Zika virus epidemic in the U.S., explicitly linking such behavioural signal to epidemiological data. Geo-localized Wikipedia pageview data reveal that visiting patterns of Zika-related pages in Wikipedia were highly synchronized across the United States and largely explained by exposure to national television broadcast. Contrary to the assumption of some theoretical epidemic models, news volume and Wikipedia visiting patterns were not significantly correlated with the magnitude or the extent of the epidemic. Attention to Zika, in terms of Zika-related Wikipedia pageviews, was high at the beginning of the outbreak, when public health agencies raised an international alert and triggered media coverage, but subsequently exhibited an activity profile that suggests nonlinear dependencies and memory effects in the relation between information seeking, media pressure, and disease dynamics. This calls for a new and more general modelling framework to describe the interaction between media exposure, public awareness and disease dynamics during epidemic outbreaks.
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Project description:There is a positive correlation between recall of tobacco-related television news and perceived risks of smoking and thoughts about quitting. The authors used Cision US, Inc., to create a sampling frame (N = 61,027) of local and national television news coverage of tobacco from October 1, 2008, to September 30, 2009, and to draw a nationally representative sample (N = 730) for content analysis. The authors conducted a descriptive study to determine the frequency and proportion of stories containing specified tobacco topics, frames, sources, and action messages, and the valence of the coverage. Valence was generally neutral; 68% of stories took a balanced stance, with 26% having a tenor supportive of tobacco control and 6% opposing tobacco control. The most frequently covered topics included smoking bans (n = 195) and cessation (n = 156). The least covered topics included hookah (n = 1) and menthol (n = 0). The majority of coverage lacked quoting any source (n = 345); government officials (n = 144) were the most quoted sources. Coverage lacked action messages or resources; 29 stories (<4%) included a message about cessation or advocacy, and 8 stories (1%) contained a resource such as a quitline. Television news can be leveraged by health communication professionals to increase awareness of underrepresented topics in tobacco control.
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Project description:BackgroundThe civil war between the indigenous Mayans and other Guatemalans lasted for 36 years, killed civilians, decimated villages, and resulted in many refugees. The Guatemalan Peace Agreement of 1996 aimed to alleviate the ongoing conflict. Studies of peace agreements more typically evaluate local political outcomes while neglecting global health outcomes.ObjectiveOur research quantified associations between pre-migration exposure to the peace agreement in Guatemala and the post-migration health status of Guatemalan immigrants in the United States.MethodsWe used chi-square tests to compare the distribution of health status before and after peace. We used ordered probit regressions to estimate associations between peace in Guatemala and health in the United States, conditional on the observed distributions of age, age squared, age cubed, and linear time trends before and after peace.FindingsThe study sample included 4,115 female and 5,282 male Guatemalan immigrants between the ages of 15 and 85. The mean age was 38.8 years for females (standard deviation, 14.2) and 35.4 years for males (standard deviation, 12.6). Chi-square tests found statistically significant differences in the distribution of health status before and after the peace agreement, for females (P < .001) and males (P < .001). In unadjusted results, the peace agreement was associated with a 7.3 percentage point increase in excellent post-migration health for females (95% confidence interval, 4.9 to 9.8) and a 6.0 percentage point increase for males (95% confidence interval, 3.8 to 8.2). In adjusted results, we found that the peace agreement was associated with a 6.1 percentage point increase in excellent post-migration health for females (95% confidence interval, 0.8 to 11.4) and a 5.5-percentage point increase for males (95% confidence interval, 1.0 to 10.0).ConclusionsThe peace agreement in Guatemala was associated with statistically significant improvements in the health status of Guatemalan immigrants to the United States.
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Project description:BackgroundBefore the advent of an effective vaccine, nonpharmaceutical interventions, such as mask-wearing, social distancing, and lockdowns, have been the primary measures to combat the COVID-19 pandemic. Such measures are highly effective when there is high population-wide adherence, which requires information on current risks posed by the pandemic alongside a clear exposition of the rules and guidelines in place.ObjectiveHere we analyzed online news media coverage of COVID-19. We quantified the total volume of COVID-19 articles, their sentiment polarization, and leading subtopics to act as a reference to inform future communication strategies.MethodsWe collected 26 million news articles from the front pages of 172 major online news sources in 11 countries (available online at SciRide). Using topic detection, we identified COVID-19-related content to quantify the proportion of total coverage the pandemic received in 2020. The sentiment analysis tool Vader was employed to stratify the emotional polarity of COVID-19 reporting. Further topic detection and sentiment analysis was performed on COVID-19 coverage to reveal the leading themes in pandemic reporting and their respective emotional polarizations.ResultsWe found that COVID-19 coverage accounted for approximately 25.3% of all front-page online news articles between January and October 2020. Sentiment analysis of English-language sources revealed that overall COVID-19 coverage was not exclusively negatively polarized, suggesting wide heterogeneous reporting of the pandemic. Within this heterogenous coverage, 16% of COVID-19 news articles (or 4% of all English-language articles) can be classified as highly negatively polarized, citing issues such as death, fear, or crisis.ConclusionsThe goal of COVID-19 public health communication is to increase understanding of distancing rules and to maximize the impact of governmental policy. The extent to which the quantity and quality of information from different communication channels (eg, social media, government pages, and news) influence public understanding of public health measures remains to be established. Here we conclude that a quarter of all reporting in 2020 covered COVID-19, which is indicative of information overload. In this capacity, our data and analysis form a quantitative basis for informing health communication strategies along traditional news media channels to minimize the risks of COVID-19 while vaccination is rolled out.
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Project description:Terrorism is a major problem worldwide, causing thousands of fatalities and billions of dollars in damage every year. To address this threat, we propose a novel feature representation method and evaluate machine learning models that learn from localized news data in order to predict whether a terrorist attack will occur on a given calendar date and in a given state. The best model (a Random Forest aided by a novel variable-length moving average method) achieved area under the receiver operating characteristic (AUROC) of ≥ 0.667 (statistically significant w.r.t. random guessing with p ≤ .0001) on four of the five states that were impacted most by terrorism between 2015 and 2018. These results demonstrate that treating terrorism as a set of independent events, rather than as a continuous process, is a fruitful approach-especially when historical events are sparse and dissimilar-and that large-scale news data contains information that is useful for terrorism prediction. Our analysis also suggests that predictive models should be localized (i.e., state models should be independently designed, trained, and evaluated) and that the characteristics of individual attacks (e.g., responsible group or weapon type) were not correlated with prediction success. These contributions provide a foundation for the use of machine learning in efforts against terrorism in the United States and beyond.
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Project description:BackgroundConfirmed local transmission of Zika Virus (ZIKV) in Texas and Florida have heightened the need for early and accurate indicators of self-sustaining transmission in high risk areas across the southern United States. Given ZIKV's low reporting rates and the geographic variability in suitable conditions, a cluster of reported cases may reflect diverse scenarios, ranging from independent introductions to a self-sustaining local epidemic.MethodsWe present a quantitative framework for real-time ZIKV risk assessment that captures uncertainty in case reporting, importations, and vector-human transmission dynamics.ResultsWe assessed county-level risk throughout Texas, as of summer 2016, and found that importation risk was concentrated in large metropolitan regions, while sustained ZIKV transmission risk is concentrated in the southeastern counties including the Houston metropolitan region and the Texas-Mexico border (where the sole autochthonous cases have occurred in 2016). We found that counties most likely to detect cases are not necessarily the most likely to experience epidemics, and used our framework to identify triggers to signal the start of an epidemic based on a policymakers propensity for risk.ConclusionsThis framework can inform the strategic timing and spatial allocation of public health resources to combat ZIKV throughout the US, and highlights the need to develop methods to obtain reliable estimates of key epidemiological parameters.
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Project description:OBJECTIVES:To determine the distribution of influenza vaccine coverage in the United States in 2008. DESIGN:Cross-sectional analysis. SETTING:The 2008 Behavioral Risk Factor Surveillance Survey, which employs random-digit dialing to interview noninstitutionalized adults in the United States and territories. PARTICIPANTS:Two hundred forty-nine thousand seven hundred twenty-three persons aged 50 and older. MEASUREMENTS:Participants were asked whether they had had an influenza vaccination during the previous 12 months. RESULTS:In 2008, 42.0% of adults aged 50 to 64 and 69.5% of adults aged 65 and older reported receiving an influenza vaccination in the past 12 months. Vaccine coverage generally increased with advancing age (P<.001), higher levels of education (P<.001) and total household income (P<.001), and greater morbidity (P<.001). In participants aged 50 to 64, vaccine prevalence was lower in men (39.9%) than in women (44.1%; P<.001), although no significant differences were observed in older adults. Within each 5-year interval of age, non-Hispanic blacks and Hispanics had significantly lower vaccine prevalence than non-Hispanic whites (P<.001 for all comparisons). For participants aged 65 and older, non-Hispanic blacks and Hispanics were 56% (adjusted prevalence ratio (PR)=1.56, 95% confidence interval (CI)=1.48, 1.64) and 44% (adjusted PR=1.44, 95% CI=1.35, 1.54) more likely, respectively, to be unvaccinated than non-Hispanic whites, adjusting for age and sex. Racial and ethnic disparities in vaccine coverage narrowed with increasing number of diseases, although these disparities remained significant in older adults with two or more diseases (P<.05). CONCLUSION:There were large disparities in influenza vaccine coverage in 2008, particularly across race and ethnicity and socioeconomic position. Accordingly, more targeted interventions are needed to improve vaccine delivery to disadvantaged segments of the U.S. population.
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