The Use of Penalized Regression Analysis to Identify County-Level Demographic and Socioeconomic Variables Predictive of Increased COVID-19 Cumulative Case Rates in the State of Georgia.

Systemic inequity concerning the social determinants of health has been known to affect morbidity and mortality for decades. Significant attention has focused on the individual-level demographic and co-morbid factors associated with rates and mortality of COVID-19. However, less attention has been given to the county-level social determinants of health that are the main drivers of health inequities. To identify the degree to which social determinants of health predict COVID-19 cumulative case rates at the county-level in Georgia, we performed a sequential, cross-sectional ecologic analysis using a diverse set of socioeconomic and demographic variables. Lasso regression was used to identify variables from collinear groups. Twelve variables correlated to cumulative case rates (for cases reported by 1 August 2020) with an adjusted r squared of 0.4525. As time progressed in the pandemic, correlation of demographic and socioeconomic factors to cumulative case rates increased, as did number of variables selected. Findings indicate the social determinants of health and demographic factors continue to predict case rates of COVID-19 at the county-level as the pandemic evolves. This research contributes to the growing body of evidence that health disparities continue to widen, disproportionality affecting vulnerable populations.

Adopting YouTube to Promote Health: Analysis of State Health Departments.

INTRODUCTION: We describe videos posted to the YouTube video-sharing Web site by US state health departments (SHDs) and associated institutional factors. METHODS: YouTube channels from SHDs were identified, their data retrieved, and their videos saved to a playlist on January 10, 2016. Ten randomly sampled videos from each channel were manually coded for topics. The 2012 Association of State and Territorial Health Officials profile survey was used to obtain information on staff, expenditure, and top 5 priorities for each SHD. Descriptive statistics and univariable regression were conducted. RESULTS: Forty-three SHDs had YouTube channels. Together, all SHDs posted 3957 videos, accumulated 12,151,720 views, and gained 6302 subscribers. In total, 415 videos were manually coded. Information about the agency (17.6%), communicable diseases (12.5%), and mother/infant health (8.9%) comprised the largest share of topics. No statistically significant association was observed between the log-transformed number of videos posted on an SHD's YouTube channel and any of the explanatory variables of SHD staffing and expenditure in 2011. The number of full-time employees (r = 0.34, p = 0.03), number of epidemiologists and biostatisticians (r = 0.41, p = 0.01), and 2011 total year expenditure (r = 0.38, p = 0.02) were positively correlated with the log-transformed number of views per YouTube video posted by SHDs. No meaningful patterns of statistical association were observed between the percentage of expenditure on a specific program area and the topics of videos. CONCLUSION: Most SHDs are using YouTube, which provides a unique opportunity for SHDs to disseminate health messages.

World Pneumonia Day 2011-2016: Twitter contents and retweets.

BACKGROUND: Twitter is used for World Pneumonia Day (WPD; November 12) communication. We evaluate if themes of #pneumonia tweets were associated with retweet frequency. METHODS: A total of 28 181 original #pneumonia tweets were retrieved (21 November 2016), from which six subcorpora, 1 mo before and 1 mo after WPD 2011-2016, were extracted (n=6721). Underlying topics were identified via latent Dirichlet allocation and were manually coded into themes. The association of themes with retweet count was assessed via multivariable hurdle regression. RESULTS: Compared with personal experience tweets, tweets that both raised awareness and promoted intervention were 2.62 times as likely to be retweeted (adjusted odds ratio [aOR] 2.62 [95% 1.79 to 3.85]) and if retweeted had 37% more retweets (adjusted prevalence ratio [aPR] 1.37 [95% CI 1.06 to 1.78]). Tweets that raised concerns about vaccine price were twice as likely to be retweeted (aOR 2.29 [95% CI 1.36 to 3.84]) and if retweeted, had double the retweet count (aPR 2.05 [95% CI 1.27 to 3.29]) of tweets sharing personal experience. CONCLUSIONS: The #pneumonia tweets that both raised awareness and promoted interventions and those discussing vaccine price were more likely to engage users than tweets about personal experience. These results help health professionals craft WPD messages that will engage the audience.

Cost-effectiveness of alternative strategies for annual influenza vaccination among children aged 6 months to 14 years in four provinces in China.

BACKGROUND: To support policy making, we developed an initial model to assess the cost-effectiveness of potential strategies to increase influenza vaccination rates among children in China. METHODS: We studied on children aged 6 months to 14 years in four provinces (Shandong, Henan, Hunan, and Sichuan), with a health care system perspective. We used data from 2005/6 to 2010/11, excluding 2009/10. Costs are reported in 2010 U.S. dollars. RESULTS: In comparison with no vaccination, the mean (range) of Medically Attended Cases averted by the current self-payment policy for the two age groups (6 to 59 months and 60 months to 14 years) was 1,465 (23 ∼ 11,132) and 792 (36 ∼ 4,247), and the cost effectiveness ratios were $ 0 (-11-51) and $ 37 (6-125) per case adverted, respectively. In comparison with the current policy, the incremental cost effectiveness ratio (ICER) of alternative strategies, OPTION One-reminder and OPTION Two-comprehensive package, decreased as vaccination rate increased. The ICER for children aged 6 to 59 months was lower than that for children aged 60 months to 14 years. CONCLUSIONS: The model is a useful tool in identifying elements for evaluating vaccination strategies. However, more data are needed to produce more accurate cost-effectiveness estimates of potential vaccination policies.