Designated Market Areas Research Articles

Identifying the geographic leading edge of Lyme disease in the United States with internet searches: A spatiotemporal analysis of Google Health Trends data.

The geographic footprint of Lyme disease is expanding in the United States, which calls for novel methods to identify emerging endemic areas. The ubiquity of internet use coupled with the dominance of Google's search engine makes Google user search data a compelling data source for epidemiological research. We evaluated the potential of Google Health Trends to track spatiotemporal patterns in Lyme disease and identify the leading edge of disease risk in the United States. We analyzed internet search rates for Lyme disease-related queries at the designated market area (DMA) level (n = 206) for the 2011-2019 and 2020-2021 (COVID-19 pandemic) periods. We used maps and other exploratory methods to characterize changes in search behavior. To assess statistical correlation between searches and Lyme disease cases reported to Centers for Disease Control and Prevention (CDC) between 2011 and 2019, we performed a longitudinal ecological analysis with modified Poisson generalized estimating equation regression models. Mapping DMA-level changes in "Lyme disease" search rates revealed an expanding area of higher rates occurring along the edges of the northeastern focus of Lyme disease. Bivariate maps comparing search rates and CDC-reported incidence rates also showed a stronger than expected signal from Google Health Trends in some high-risk adjacent states such as Michigan, North Carolina, and Ohio, which may be further indication of a geographic leading edge of Lyme disease that is not fully apparent from routine surveillance. Searches for "Lyme disease" were a significant predictor of CDC-reported disease incidence. Each 100-unit increase in the search rate was significantly associated with a 10% increase in incidence rates (RR = 1.10, 95% CI: 1.07, 1.12) after adjusting for environmental covariates of Lyme disease identified in the literature. Google Health Trends data may help track the expansion of Lyme disease and inform the public and health care providers about emerging risks in their areas.

The Validity of Impressions as a Media Dose Metric in a Tobacco Public Education Campaign Evaluation: Observational Study.

Evaluation research increasingly needs alternatives to target or gross rating points to comprehensively measure total exposure to modern multichannel public education campaigns that use multiple channels, including TV, radio, digital video, and paid social media, among others. Ratings data typically only capture delivery of broadcast media (TV and radio) and excludes other channels. Studies are needed to validate objective cross-channel metrics such as impressions against self-reported exposure to campaign messages. This study aimed to examine whether higher a volume of total media campaign impressions is predictive of individual-level self-reported campaign exposure in California. We analyzed over 3 years of advertisement impressions from the California Tobacco Prevention Program's statewide tobacco education campaigns from August 2019 through December 2022. Impressions data varied across designated market areas (DMAs) and across time. These data were merged to individual respondents from 45 waves of panel survey data of Californians aged 18-55 years (N=151,649). Impressions were merged to respondents based on respondents' DMAs and time of survey completion. We used logistic regression to estimate the odds of respondents' campaign recall as a function of cumulative and past 3-month impressions delivered to each respondent's DMA. Cumulative impressions were positively and significantly associated with recall of each of the Flavors Hook Kids (odds ratio [OR] 1.15, P<.001), Dark Balloons and Apartment (OR 1.20, P<.001), We Are Not Profit (OR 1.36, P<.001), Tell Your Story (E-cigarette, or Vaping, product use Associated Lung Injury; OR 1.06, P<.05), and Thrown Away and Little Big Lies (OR 1.05, P<.01) campaigns. Impressions delivered in the past 3 months were associated with recall of the Flavors Hook Kids (OR 1.13, P<.001), Dark Balloons and Apartment (OR 1.08, P<.001), We Are Not Profit (OR 1.14, P<.001), and Thrown Away and Little Big Lies (OR 1.04, P<.001) campaigns. Past 3-month impressions were not significantly associated with Tell Your Story campaign recall. Overall, magnitudes of these associations were greater for cumulative impressions. We visualize recall based on postestimation predicted values from our multivariate logistic regression models. Variation in cumulative impressions for California Tobacco Prevention Program's long-term multichannel tobacco education campaign is predictive of increased self-reported campaign recall, suggesting that impressions may be a valid proxy for potential campaign exposure. The use of impressions for purposes of evaluating public education campaigns may help address current methodological limitations arising from the fragmented nature of modern multichannel media campaigns.

Analysis of cigar marketing expenditures by product category, placement strategy and geolocation in the USA, from 2017 to 2022

SignificanceThe marketing of cigars, little cigars and cigarillos (CLCCs) and cigar wraps is under-regulated and understudied in the USA. To describe strategies CLCC manufacturers and vendors used to advertise their...

The Long-Term Impact of the Tips From Former Smokers® Campaign on Calls to 1-800-QUIT-NOW, 2012-2023.

There is substantial evidence that mass media campaigns increase calls to quitlines and smoking cessation. In 2012, the Centers for Disease Control and Prevention launched the first federally funded national tobacco education campaign, Tips From Former Smokers® (i.e. Tips), which has since aired television advertisements annually. To date, no studies have examined the long-term effect of a national smoking cessation campaign on quitline calls. This study examined the long-term impact of Tips television ads on calls to 1-800-QUIT-NOW from 2012 through 2023. Exposure to the Tips campaign was measured using weekly television gross rating points (GRPs) in each U.S. designated market area. We obtained data on calls to 1-800-QUIT-NOW from the National Cancer Institute and used linear regression to model calls to 1-800-QUIT-NOW, from 2012 through 2023, as a function of weekly media market-level GRPs for Tips television ads. Using the regression model results, we calculated predicted values of calls to 1-800-QUIT-NOW across observed GRP values to determine the total additional calls to 1-800-QUIT-NOW that were attributable to the Tips campaign during 2012-2023. Tips GRPs were positively and significantly associated with calls to 1-800-QUIT-NOW across all years (b = 39.94, p < 0.001). Based on this association, we estimate the Tips campaign generated nearly 2.1 million additional calls to 1-800-QUIT-NOW during 2012-2023. Exposure to the Tips campaign has consistently and significantly increased calls to tobacco quitlines. Quitlines provide evidence-based support to help people quit smoking. They have been shown to increase the likelihood of successfully quitting. Mass media campaigns have promoted quitline services, and quitline calls have increased significantly with media promotion. The long-term effect of campaigns - like the Centers for Disease Control and Prevention's Tips From Former Smokers® (i.e. Tips) - on quitline calls has not been determined. From 2012 through 2023, exposure to the Tips campaign is estimated to have generated nearly 2.1 million additional calls to 1-800-QUIT-NOW. This study supports continued use of mass media to promote quitlines.

The Impact of Incentives on Data Collection for Online Surveys: Social Media Recruitment Study.

The use of targeted advertisements on social media platforms (eg, Facebook and Instagram) has become increasingly popular for recruiting participants for online survey research. Many of these surveys offer monetary incentives for survey completion in the form of gift cards; however, little is known about whether the incentive amount impacts the cost, speed, and quality of data collection. This experiment addresses this gap in the literature by examining how different incentives in paid advertising campaigns on Instagram for completing a 10-minute online survey influence the response rate, recruitment advertising cost, data quality, and length of data collection. This experiment tested three incentive conditions using three Instagram campaigns that were each allocated a US $1400 budget to spend over a maximum of 4 days; ads targeted users aged 15-24 years in three nonadjacent designated market areas of similar size to avoid overlapping audiences. Four ad creatives were designed for each campaign; all ads featured the same images and text, but the incentive amount varied: no incentive, US $5 gift card, and US $15 gift card. All ads had a clickable link that directed users to an eligibility screener and a 10-minute online survey, if eligible. Each campaign ran for either the full allotted time (4 days) or until there were 150 total survey completes, prior to data quality checks for fraud. The US $15 incentive condition resulted in the quickest and cheapest data collection, requiring 17 hours and ad spending of US $338.64 to achieve 142 survey completes. The US $5 condition took more than twice as long (39 hours) and cost US $864.33 in ad spending to achieve 148 survey completes. The no-incentive condition ran for 60 hours, spending nearly the full budget (US $1398.23), and achieved only 24 survey completes. The US $15 and US $5 incentive conditions had similar levels of fraudulent respondents, whereas the no-incentive condition had no fraudulent respondents. The completion rate for the US $15 and US $5 incentive conditions were 93.4% (155/166) and 89.8% (149/166), respectively, while the completion rate for the no-incentive condition was 43.6% (24/55). Overall, we found that a higher incentive resulted in quicker data collection, less money spent on ads, and higher response rates, despite some fraudulent cases that had to be dropped from the sample. However, when considering the total incentive amounts in addition to the ad spending, a US $5 incentive appeared to be the most cost-effective data collection option. Other costs associated with running a campaign for a longer period should also be considered. A longer experiment is warranted to determine whether fraud varies over time across conditions.

Post-Pandemic Hiring Practices and Skills Requested by Local U.S. TV Stations

ABSTRACT Job ads are meant to capture the daily responsibilities of the position, as well as let candidates know the skills and qualities the right candidate for the job needs to demonstrate from the employer’s perspective. While Aupperle and Grzeslo (2020) studied job ads of legacy media stations, Deavours and Grzeslo (2020) were among the first to explore local broadcast television station job ads. Yet, after the “Great Resignation” following the COVID-19 pandemic, as well as recent technology and business model changes, researchers need to continue to update and monitor the rapidly evolving needs of local newsrooms. This study seeks to provide insight through a content analysis of job postings from U.S. local television stations, exploring the experience, skills, and experience requirements necessary to be competitive in today’s market, while also looking at how companies are working harder to attract talent. Using the theoretical lens of skills theory of leadership, the study also provides insight in hiring differences in station ownership, market size, and position type. Through content analysis of 349 job ads from 21 local news Designated Market Areas, findings suggest the field is embracing more convergent, digital reporting tactics, while still emphasizing the foundations of broadcast writing and visual storytelling. However, some of the most dramatic shifts in the industry toward innovation, emerging media, digital legal and ethical skills, and diversity are not reflected in job ads, creating little guidance for individuals and educators on how to prepare for an ever-changing job market.

Big data in crime statistics: Using Google Trends to measure victimization in designated market areas across the United States

Google Trends (GT) data could potentially supplement traditional crime measurement strategies, allowing criminologists to better understand crime statistics on a macro level. This study assesses the validity of GT crime estimates. The findings indicate that GT data are reliable for estimating MVT, larceny, and rape. Additionally, we illustrate how to use GT to identify places with high rates of unreported offenses. The results of this study demonstrate the feasibility of leveraging open-source big data such as GT to supplement traditional sources of crime data, particularly for categories of crime with substantial underreporting rates. Results suggest the GT rape measure may be a more accurate estimate of the true incidence of rape than the measure drawn from the Uniform Crime Report (UCR). The limitations associated with the use of GT to generate estimates of crime are also discussed.

The Initial Relationship Between the United States Department of Health and Human Services' Digital COVID-19 Public Education Campaign and Vaccine Uptake: Campaign Effectiveness Evaluation.

Over 1 million people in the United States have died of COVID-19. In response to this public health crisis, the US Department of Health and Human Services launched the We Can Do This public education campaign in April 2021 to increase vaccine confidence. The campaign uses a mix of digital, television, print, radio, and out-of-home channels to reach target audiences. However, the impact of this campaign on vaccine uptake has not yet been assessed. We aimed to address this gap by assessing the association between the We Can Do This COVID-19 public education campaign's digital impressions and the likelihood of first-dose COVID-19 vaccination among US adults. A nationally representative sample of 3642 adults recruited from a US probability panel was surveyed over 3 waves (wave 1: January to February 2021; wave 2: May to June 2021; and wave 3: September to November 2021) regarding COVID-19 vaccination, vaccine confidence, and sociodemographics. Survey data were merged with weekly paid digital campaign impressions delivered to each respondent's media market (designated market area [DMA]) during that period. The unit of analysis was the survey respondent-broadcast week, with respondents nested by DMA. Data were analyzed using a multilevel logit model with varying intercepts by DMA and time-fixed effects. The We Can Do This digital campaign was successful in encouraging first-dose COVID-19 vaccination. The findings were robust to multiple modeling specifications, with the independent effect of the change in the campaign's digital dose remaining practically unchanged across all models. Increases in DMA-level paid digital campaign impressions in a given week from -30,000 to 30,000 increased the likelihood of first-dose COVID-19 vaccination by 125%. Results from this study provide initial evidence of the We Can Do This campaign's digital impact on vaccine uptake. The size and length of the Department of Health and Human Services We Can Do This public education campaign make it uniquely situated to examine the impact of a digital campaign on COVID-19 vaccination, which may help inform future vaccine communication efforts and broader public education efforts. These findings suggest that campaign digital dose is positively associated with COVID-19 vaccination uptake among US adults; future research assessing campaign impact on reduced COVID-19-attributed morbidity and mortality and other benefits is recommended. This study indicates that digital channels have played an important role in the COVID-19 pandemic response. Digital outreach may be integral in addressing future pandemics and could even play a role in addressing nonpandemic public health crises.

The Role of Advertising in High-Tech Medical Procedures: Evidence from Robotic Surgeries

Hospital advertising has grown more than five-fold in the past two decades. However, unlike detailing and advertising for prescription drugs, the topic of hospital advertising has been understudied. This research introduces a customer-centric view to this market by investigating the role of advertising in patients’ choice of high-tech medical procedures, with a focus on robotic surgery. The authors analyze approximately 140,000 individual patient records and television advertising data from Florida during 2011–2015 to investigate how hospital advertising of robotic surgery affects patients’ choice of robotic surgery over more conventional laparoscopic and open surgeries. Using a variation of a designated market area border identification strategy, the authors find that this advertising leads to more robotic surgery choices. The advertising effect is especially strong for Medicaid patients, whose socioeconomic status tends to be lower. While robotic surgery is associated with a short-term health benefit (i.e., reduced length of hospital stay), it does not affect long-term health benefits and comes at a higher cost than other forms of surgery. Thus, understanding the effect of advertising robotic surgery has significant health, cost, and marketing implications for different stakeholders in the health care industry, such as patients, health care providers, surgical robot manufacturers, insurance providers, and policy makers.

Societal Spillovers of TV Advertising: Social Distancing During a Public Health Crisis

Can TV advertising affect societal outcomes beyond traditional marketing outcomes such as sales and brand awareness? The authors address this question in the context of the COVID-19 pandemic by analyzing daily advertising and mobility data for 2,194 counties across 204 designated market areas in the United States. By employing a border identification strategy that exploits discontinuities across television markets, the authors find a significant positive causal relationship between TV ads from brands containing COVID-19 narratives and people's social distancing behavior, while controlling for government policy interventions (e.g., shelter-in-place, mask mandates). The estimated effects are almost 11 times larger in counties without government policy interventions compared with counties with policy interventions. Notably, while the overall impact of government ads on social distancing behavior is nonsignificant, the effect becomes significantly negative (positive) in the presence (absence) of policy interventions. The results are robust to alternative model specifications, variable operationalizations, and other data considerations. The findings underscore the critical role that spillover effects from brand-sponsored TV ads can play during major public crises, including mitigating the lack of local governments' policy interventions. The findings bear substantive implications for managers and policy makers regarding how advertising strategies may help improve public health outcomes or advance social good.

Athletes Drink Gatorade: DMA Advertising Expenditures, Ad Recall, and Athletic Identity Influence Energy and Sports Drink Consumption

ABSTRACT Understanding why sports and energy drinks remain increasingly popular among adolescents despite declines in other sugar sweetened beverages is critical. This study points to memory for advertising exposure and adolescent athletic identity as two aspects that together help to explain consumption. An online survey of U.S. adolescents aged 14–18 (n = 503) was combined with Nielsen data for television and social media advertising expenditures by sports and energy drink brands in participants’ designated market areas (DMAs). Advertisement recall mediates the relationship between social media DMA expenditures and sports and energy drink consumption. Recall for television advertisements is related to consumption but is unrelated to television DMA expenditures. Athletic identity moderated the relationship between recall and consumption such that consumption increased as both recall and athletic identity increased, suggesting a role for motivated memory and motivated processing of ad messages based on athletic identity consistent with the limited capacity model of motivated media message processing. Based on these results, we conclude that effectiveness of expenditures in influencing behavior is dependent upon both ad recall and ad relevance, and that athletic identity is an important factor in ad effectiveness in the context of sports and energy drinks advertising.

Hydroxychloroquine for COVID-19: Variation in Regional Political Preferences Predicted New Prescriptions after President Trump's Endorsement.

On March 19, 2020, President Donald Trump endorsed using hydroxychloroquine for COVID-19 treatment despite inconclusive evidence of the drug's effectiveness. This study sought to understand the influence of political preferences on prescription uptake by quantifying the relationship between a geographic area's partisan leaning and hydroxychloroquine prescription rates following Trump's endorsement. We analyzed hydroxychloroquine prescriptions filled in 205 continental US designated market areas (DMAs) between March 1, 2018, and July 31, 2020, and the percentage of votes for Donald Trump in the 2016 presidential election in each DMA. We estimated associations by using an empirical strategy resembling a difference-in-differences estimation. Before President Trump's endorsement, mean weekly hydroxychloroquine prescription rates were similar across DMAs with the highest and lowest Trump vote percentages (0.56 and 0.49 scripts per 100,000). After Trump's endorsement, although both high- and low-Trump-supportive DMAs experienced sharp increases in weekly hydroxychloroquine prescription rates, results indicated a 1-percentage-point increase in share of Trump votes was associated with 0.013, or 2%, more weekly hydroxychloroquine prescriptions per 100,000 people (b = 0.013, t = 2.20, p = .028). President Trump's endorsement of an untested therapy influenced prescribing behavior, especially when that endorsement aligned with communities' political leanings.

Educating Young Adults about Opioid Misuse: Evidence from a Mass Media Intervention.

The US opioid epidemic is a serious public health problem. Rates of opioid misuse and dependence are highest for young adults ages 18–25. Prevention strategies that reduce prescription opioid misuse while decreasing stigma around dependence and treatment are critical components of addressing the epidemic. The Truth About Opioids, a mass media public education campaign, was designed to prevent opioid misuse and dependence among young adults. This study examined the intervention’s effectiveness to shift opioid-related knowledge, attitudes, and beliefs within targeted designated market areas (DMAs) over time. A sample of young adults (N = 1434) in DMAs with varying levels of media exposure was surveyed at baseline (June–September 2019) and post-intervention (July–August 2020). Logistic regression assessed associations between campaign awareness and campaign-targeted knowledge and attitudes, controlling for baseline variables. Those with any awareness had significantly higher odds of campaign-targeted opioid-related knowledge (versus no awareness) (low awareness OR = 1.52 (95% CI: 1.04, 2.24); high awareness OR = 2.47 (95% CI: 1.58, 3.87)). Those with campaign awareness were also more likely to report lower levels of opioid-related stigma and higher intentions to share information and talk to a friend about the epidemic. Mass media public education campaigns can help influence young adults’ opioid-related knowledge and attitudes.

Social Media Competitive Analysis and Text Mining

As more Americans use Facebook as one of their primary sources of news consumption, television broadcasters have increasingly added this social media platform in their distribution strategies for program optimization and audience engagement. Within a local market, media outlets not only need to monitor and analyze their own social media content and online audience behavior but also their competitors to increase competitive advantage. This study proposes a social media competitive analysis framework with three aspects: social media utilization, social media content strategy, and social media news engagement. By applying the analytics framework, this study examines the dynamic Facebook competition among five local television stations within a designated market area (DMA) in the U.S. The results show two divergent social media deployment patterns among these five local television broadcasters. Theoretical and practical implications are discussed to help media organizations develop their own social media strategies and gain competitive advantages over their opponents.

A comparative study of local broadcasters' Twitter utilization in different market conditions

Although the importance of over-the-air broadcasting has gradually dwindled in the entire media market, no one cannot deny local broadcasters' significant contribution to serving informational needs in local communities (FCC, 1999). Regarding local television's Twitter use for promotion and branding, Greer and Ferguson (2011) examined Twitter sites of 488 local television stations in the U.S. to identify the relationship between stations' status and content of stations' Twitter sites. They found that most local television stations offer news stories but barely direct viewers to their actual on-air programming. In their other study (Ferguson and Greer, 2011), they analyzed 111 local radio stations' Twitter sites to understand how regional radio stations use their business. The previous studies successfully demonstrate how local broadcasters use Twitter, but they do not capture any differences among broadcasters with different conditions. This study empirically analyzes how local broadcasters from different conditions utilize Twitter to adapt to the digitalized interactive media environment. Local broadcasters' social media performance can differ because American local broadcast markets differ in market size (Designated Market Area) and funding system (commercial vs. public), and station ownership. Thus, the scope of this study is limited to two extreme cases for comparison's sake. For comparative analysis, this study will analyze two different local different broadcasters groups – one group from Nielsen's top 20 DMA and another group from the bottom 20 DMA. Local broadcasters' Tweets from two other groups are analyzed to address the differences in Twitter uses 1) between public and commercial stations, and 2) between high-resourced (top DMA) and low-resourced (bottom DMA) market. This study will implement two methods to investigate the local broadcasters' local service activities in social network platforms, Twitter. First, website research collects qualitative and quantitative information directly from the studied websites. The website research will delineate the local broadcasters' current social media adoption. Second, network analysis of Twitter networks conducts to describe the complex conversational interaction within the Twitter network. Network analysis (Hanneman & Riddle, 2005) is one way to visualize and analyze how social media networks are connected, how they interact, and which agent is most influential in networks. The open-source program NodeXL will be used for network analysis and visualization of study results among the social network analysis tools. As a result, this study will address whether local broadcasters, which is often considered a thing of the past, still can justify their existence in the age of fiber-optic broadband and app-based mobile-centered media environment.

Final Evaluation Findings for This Free Life, a 3-Year, Multi-Market Tobacco Public Education Campaign for Gender and Sexual Minority Young Adults in the United States.

Introduction This Free Life was the first multi-market, primarily digital campaign designed to change tobacco-related beliefs among lesbian, gay, bisexual, and transgender (LGBT) young adults. Our evaluation sought to determine whether campaign exposure resulted in changes in tobacco-related beliefs. We summarize awareness and receptivity at the conclusion of the campaign and assess the effect of campaign exposure on tobacco-related beliefs in campaign treatment markets compared with control markets.Aims and MethodsTwenty-four US designated market areas were selected to receive the campaign or serve as control markets. A baseline survey was conducted in 2016, with six follow-up surveys conducted approximately 6 months apart over the course of the 3-year campaign. 12 324 LGBT young adult survey participants were recruited via intercept interviews and social media. Campaign effects on outcomes were estimated using difference-in-difference panel regression models, with p-values corrected for multiple comparisons.ResultsBrand and ad awareness peaked in treatment markets approximately 2.5 years into the 3-year campaign and were significantly higher in treatment than control markets. Brand equity and ad receptivity were generally high and similar across LGBT subgroups. There were small but significant campaign effects on five tobacco-related beliefs, with difference-in-difference estimates ranging from 1.9 to 5.6 percentage points.Conclusions This Free Life, the first multi-market tobacco public education campaign for LGBT young adults, reached and resonated with a large and diverse population, and had a small effect on beliefs involving social aspects of smoking. These findings should inform future communication efforts aimed at reducing tobacco use among LGBT young adults.ImplicationsModest overall campaign effects suggest that further research on effective campaign messaging and delivery to LGBT young adults is needed. Campaign messaging style, delivery channels, and targeted outcomes likely contributed to these findings. Health communication efforts for LGBT young adults should consider the limitations of digital media in achieving sufficient exposure. Ad style and content optimized for a digital environment is an area that will benefit from further development.

Understanding the role of religion in shaping cross-national and domestic attitudes and interest in abortion, homosexuality, and pornography using traditional and Google search data

Over the last 20 years, internet usage has increased substantially, providing an inexpensive source of data that may be less prone to bias and could provide a greater number of meso and macro units. However, validating big data and their usefulness has been challenging. This study uses established sources to validate Google Trends' search interest in the “Bible” across US Designated Market Areas and “Ramadan” across nations, establishing a potential new source of religion data. We then use these measures to show that people from religiously conservative US areas and countries are more likely to disapprove of homosexuality, abortion and pornography. Conversely, Americans from conservative religious areas are also more likely to search for these topics; and cross-national interest in Islam is associated with increased interest in pornography. Our study offers insight into Google Trends’ potential for social science research and a roadmap on how to use these data.

Information-seeking vs. sharing: Which explains regional health? An analysis of Google Search and Twitter trends

Users’ information-seeking and information-sharing behavior provide socioeconomic and psychological insights that are useful to understand regional trends in health. We study the spatial variations in aggregate Google Search and Twitter trends across 208 Designated Market Areas (DMAs) in the United States and their association with regional health. We find that information-seeking behavior from Google Trends data is better able to predict the prevalence of non-communicable diseases and impending behavioral risks, with an average gain of 19% over sociodemographics and regional controls, and of 15% over information-sharing behavior on Twitter. Both kinds of digital traces track cultural and socioeconomic contexts; however, information-seeking behavior provides insights into personal habits, while information-sharing provides psychological insights. Our findings can be applied to design online and offline human-centered health interventions that target at-risk populations through a knowledge of their lifestyle and concerns.

Tobacco 21 adoption decreased sales of cigarette brands purchased by young people: a translation of population health survey data to gain insight into market data for policy analysis

IntroductionPolicies raising the minimum age of sale of tobacco products to 21 (T21) proliferated at state and local levels across the USA before a federal policy was adopted. Evidence of...

Regional Infoveillance of COVID-19 Case Rates: Analysis of Search-Engine Query Patterns.

BackgroundTimely allocation of medical resources for coronavirus disease (COVID-19) requires early detection of regional outbreaks. Internet browsing data may predict case outbreaks in local populations that are yet to be confirmed.ObjectiveWe investigated whether search-engine query patterns can help to predict COVID-19 case rates at the state and metropolitan area levels in the United States.MethodsWe used regional confirmed case data from the New York Times and Google Trends results from 50 states and 166 county-based designated market areas (DMA). We identified search terms whose activity precedes and correlates with confirmed case rates at the national level. We used univariate regression to construct a composite explanatory variable based on best-fitting search queries offset by temporal lags. We measured the raw and z-transformed Pearson correlation and root-mean-square error (RMSE) of the explanatory variable with out-of-sample case rate data at the state and DMA levels.ResultsPredictions were highly correlated with confirmed case rates at the state (mean r=0.69, 95% CI 0.51-0.81; median RMSE 1.27, IQR 1.48) and DMA levels (mean r=0.51, 95% CI 0.39-0.61; median RMSE 4.38, IQR 1.80), using search data available up to 10 days prior to confirmed case rates. They fit case-rate activity in 49 of 50 states and in 103 of 166 DMA at a significance level of .05.ConclusionsIdentifiable patterns in search query activity may help to predict emerging regional outbreaks of COVID-19, although they remain vulnerable to stochastic changes in search intensity.