A National, County-Level Evaluation of the Association Between COVID-19 and Sexually Transmitted Infections Within the United States in 2020.

BACKGROUND: Shifts in public health infrastructure to respond to one emerging health threat may have unanticipated consequences for preexisting diseases. Previous research evaluating the impact of COVID-19 on sexually transmitted infections (STIs) has been conducted nationally, with little exploration of the impact on a granular geospatial level. This ecological study seeks to quantify the association between COVID-19 cases or deaths and chlamydia, gonorrhea, and syphilis cases for all US counties in 2020. METHODS: Separate, adjusted multivariable quasi-Poisson models with robust standard errors modeled the county-level association between 2020 COVID-19 cases and deaths per 100,000 and 2020 chlamydia, gonorrhea, or syphilis cases per 100,000. Models were adjusted for sociodemographic characteristics. RESULTS: Every 1000 additional COVID-19 cases per 100,000 was associated with a 1.80% increase in the average number of chlamydia cases ( P < 0.001) and a 5.00% increase in the average number of gonorrhea cases ( P < 0.001). Every 1000 additional COVID-19 deaths per 100,000 was associated with a 57.9% increase in the average number gonorrhea cases ( P < 0.001) and a 74.2% decrease in the average number of syphilis cases ( P = 0.004). CONCLUSIONS: Higher rates of COVID-19 cases and deaths were associated with increased rates of some STIs at the US county level. The underlying reasons for these associations could not be established by this study. The emergency response to an emerging threat may have unanticipated influence on preexisting diseases that varies by level of governance.

Obesity-Related Discourse on Facebook and Instagram Throughout the COVID-19 Pandemic: Comparative Longitudinal Evaluation.

BACKGROUND: COVID-19 severity is amplified among individuals with obesity, which may have influenced mainstream media coverage of the disease by both improving understanding of the condition and increasing weight-related stigma. OBJECTIVE: We aimed to measure obesity-related conversations on Facebook and Instagram around key dates during the first year of the COVID-19 pandemic. METHODS: Public Facebook and Instagram posts were extracted for 29-day windows in 2020 around January 28 (the first US COVID-19 case), March 11 (when COVID-19 was declared a global pandemic), May 19 (when obesity and COVID-19 were linked in mainstream media), and October 2 (when former US president Trump contracted COVID-19 and obesity was mentioned most frequently in the mainstream media). Trends in daily posts and corresponding interactions were evaluated using interrupted time series. The 10 most frequent obesity-related topics on each platform were also examined. RESULTS: On Facebook, there was a temporary increase in 2020 in obesity-related posts and interactions on May 19 (posts +405, 95% CI 166 to 645; interactions +294,930, 95% CI 125,986 to 463,874) and October 2 (posts +639, 95% CI 359 to 883; interactions +182,814, 95% CI 160,524 to 205,105). On Instagram, there were temporary increases in 2020 only in interactions on May 19 (+226,017, 95% CI 107,323 to 344,708) and October 2 (+156,974, 95% CI 89,757 to 224,192). Similar trends were not observed in controls. Five of the most frequent topics overlapped (COVID-19, bariatric surgery, weight loss stories, pediatric obesity, and sleep); additional topics specific to each platform included diet fads, food groups, and clickbait. CONCLUSIONS: Social media conversations surged in response to obesity-related public health news. Conversations contained both clinical and commercial content of possibly dubious accuracy. Our findings support the idea that major public health announcements may coincide with the spread of health-related content (truthful or otherwise) on social media.

Evolving Face Mask Guidance During a Pandemic and Potential Harm to Public Perception: Infodemiology Study of Sentiment and Emotion on Twitter.

BACKGROUND: Throughout the COVID-19 pandemic, US Centers for Disease Control and Prevention policies on face mask use fluctuated. Understanding how public health communications evolve around key policy decisions may inform future decisions on preventative measures by aiding the design of communication strategies (eg, wording, timing, and channel) that ensure rapid dissemination and maximize both widespread adoption and sustained adherence. OBJECTIVE: We aimed to assess how sentiment on masks evolved surrounding 2 changes to mask guidelines: (1) the recommendation for mask use on April 3, 2020, and (2) the relaxation of mask use on May 13, 2021. METHODS: We applied an interrupted time series method to US Twitter data surrounding each guideline change. Outcomes were changes in the (1) proportion of positive, negative, and neutral tweets and (2) number of words within a tweet tagged with a given emotion (eg, trust). Results were compared to COVID-19 Twitter data without mask keywords for the same period. RESULTS: There were fewer neutral mask-related tweets in 2020 (ß=-3.94 percentage points, 95% CI -4.68 to -3.21; P<.001) and 2021 (ß=-8.74, 95% CI -9.31 to -8.17; P<.001). Following the April 3 recommendation (ß=.51, 95% CI .43-.59; P<.001) and May 13 relaxation (ß=3.43, 95% CI 1.61-5.26; P<.001), the percent of negative mask-related tweets increased. The quantity of trust-related terms decreased following the policy change on April 3 (ß=-.004, 95% CI -.004 to -.003; P<.001) and May 13 (ß=-.001, 95% CI -.002 to 0; P=.008). CONCLUSIONS: The US Twitter population responded negatively and with less trust following guideline shifts related to masking, regardless of whether the guidelines recommended or relaxed mask usage. Federal agencies should ensure that changes in public health recommendations are communicated concisely and rapidly.

Delayed medical care and underlying health in the United States during the COVID-19 pandemic: A cross-sectional study.

This study assesses the association between underlying health conditions and delaying medical care during the COVID-19 pandemic. An online cross-sectional survey administered by OutbreaksNearMe.org on Momentive.ai collected self-reported data from April 27 to June 2, 2020 and May 10 to June 13, 2021. We used weighted multivariable logistic regressions to assess the association between delaying care and self-reported health status, adjusting for demographics. Of 312,661 total responses (99.6% completion rate), 17.1% reported delayed medical care. Compared to good health, those with poor health were more likely to delay care (AOR = 2.62, 95% CI [2.47, 2.78]). Individuals with any underlying condition (AOR = 1.62, 95% CI [1.58, 1.65]) and each of the conditions were more likely to delay care. Differences in delaying care were observed across region, year, and demographics. Our finding is that those at higher risk of severe COVID-19 were more likely to delay medical care in 2020 and 2021, which could exacerbate existing health conditions and existing disparities.

Prevalence and comparisons of alcohol, candy, energy drink, snack, soda, and restaurant brand and product marketing on Twitch, Facebook Gaming and YouTube Gaming.

OBJECTIVE: To compare and evaluate the prevalence of food and beverage marketing on the livestreaming platforms Twitch, Facebook Gaming and YouTube Gaming, as well as examine growth of food and beverage marketing on these platforms over a 17-month period of data collection. DESIGN: Cross-sectional data were analysed across three livestreaming platforms and six food and beverage categories: alcohol, candy, energy drinks, snacks, sodas and restaurants. SETTING: Stream titles of livestreamed events as well as corresponding hours watched on Twitch, Facebook Gaming and YouTube Gaming. PARTICIPANTS: None. RESULTS: There were significant differences between the use of food and beverage brand mentions in stream titles across all three studied platforms (P < 0·05), as well as hours watched across platforms (P < 0·05). Energy drinks dominated food and beverage brand mentions across platforms, followed by restaurants, soda and snacks. All platforms demonstrated growth over the 17-month data collection period. Post-hoc analyses revealed that the COVID-19 pandemic impacted both immediate and sustained growth across all platforms, with the greatest impact observed on the Twitch platform. CONCLUSIONS: Food and beverage marketing as measured through stream titles is widely prevalent across the three most popular livestreaming platforms, particularly for energy drinks. Food marketing on these platforms experienced growth over the past 17 months which was accelerated substantially by the COVID-19 pandemic. Future work should assess the sustained impact this growth may have on marketing practices and eating behaviour.

Language and Sentiment Regarding Telemedicine and COVID-19 on Twitter: Longitudinal Infodemiology Study.

BACKGROUND: The COVID-19 pandemic has necessitated a rapid shift in how individuals interact with and receive fundamental services, including health care. Although telemedicine is not a novel technology, previous studies have offered mixed opinions surrounding its utilization. However, there exists a dearth of research on how these opinions have evolved over the course of the current pandemic. OBJECTIVE: This study aims to evaluate how the language and sentiment surrounding telemedicine has evolved throughout the COVID-19 pandemic. METHODS: Tweets published between January 1, 2020, and April 24, 2021, containing at least one telemedicine-related and one COVID-19-related search term ("telemedicine-COVID") were collected from the Twitter full archive search (N=351,718). A comparator sample containing only COVID-19 terms ("general-COVID") was collected and sampled based on the daily distribution of telemedicine-COVID tweets. In addition to analyses of retweets and favorites, sentiment analysis was performed on both data sets in aggregate and within a subset of tweets receiving the top 100 most and least retweets. RESULTS: Telemedicine gained prominence during the early stages of the pandemic (ie, March through May 2020) before leveling off and reaching a steady state from June 2020 onward. Telemedicine-COVID tweets had a 21% lower average number of retweets than general-COVID tweets (incidence rate ratio 0.79, 95% CI 0.63-0.99; P=.04), but there was no difference in favorites. A majority of telemedicine-COVID tweets (180,295/351,718, 51.3%) were characterized as "positive," compared to only 38.5% (135,434/351,401) of general-COVID tweets (P<.001). This trend was also true on a monthly level from March 2020 through April 2021. The most retweeted posts in both telemedicine-COVID and general-COVID data sets were authored by journalists and politicians. Whereas the majority of the most retweeted posts within the telemedicine-COVID data set were positive (55/101, 54.5%), a plurality of the most retweeted posts within the general-COVID data set were negative (44/89, 49.4%; P=.01). CONCLUSIONS: During the COVID-19 pandemic, opinions surrounding telemedicine evolved to become more positive, especially when compared to the larger pool of COVID-19-related tweets. Decision makers should capitalize on these shifting public opinions to invest in telemedicine infrastructure and ensure its accessibility and success in a postpandemic world.