The Influence of Media Coverage and Governmental Policies on Google Queries Related to COVID-19 Cutaneous Symptoms: Infodemiology Study

BackgroundDuring COVID-19, studies have reported the appearance of internet searches for disease symptoms before their validation by the World Health Organization. This suggested that monitoring of these searches with tools including Google Trends may help monitor the pandemic itself. In Europe and North America, dermatologists reported an unexpected outbreak of cutaneous acral lesions (eg, chilblain-like lesions) in April 2020. However, external factors such as public communications may also hinder the use of Google Trends as an infodemiology tool.ObjectiveThe study aimed to assess the impact of media announcements and lockdown enforcement on internet searches related to cutaneous acral lesions during the COVID-19 outbreak in 2020.MethodsTwo searches on Google Trends, including daily relative search volumes for (1) “toe” or “chilblains” and (2) “coronavirus,” were performed from January 1 to May 16, 2020, with the United States, the United Kingdom, France, Italy, Spain, and Germany as the countries of choice. The ratio of interest over time in “chilblains” and “coronavirus” was plotted. To assess the impact of lockdown enforcement and media coverage on these internet searches, we performed an interrupted time-series analysis for each country.ResultsThe ratio of interest over time in “chilblains” to “coronavirus” showed a constant upward trend. In France, Italy, and the United Kingdom, lockdown enforcement was associated with a significant slope change for “chilblain” searches with a variation coefficient of 1.06 (SE 0.42) (P=0.01), 1.04 (SE 0.28) (P<.01), and 1.21 (SE 0.44) (P=0.01), respectively. After media announcements, these ratios significantly increased in France, Spain, Italy, and the United States with variation coefficients of 18.95 (SE 5.77) (P=.001), 31.31 (SE 6.31) (P<.001), 14.57 (SE 6.33) (P=.02), and 11.24 (SE 4.93) (P=.02), respectively, followed by a significant downward trend in France (–1.82 [SE 0.45]), Spain (–1.10 [SE 0.38]), and Italy (–0.93 [SE 0.33]) (P<.001, P=0.004, and P<.001, respectively). The adjusted R² values were 0.311, 0.351, 0.325, and 0.305 for France, Spain, Italy, and the United States, respectively, suggesting an average correlation between time and the search volume; however, this correlation was weak for Germany and the United Kingdom.ConclusionsTo date, the association between chilblain-like lesions and COVID-19 remains controversial; however, our results indicate that Google queries of “chilblain” were highly influenced by media coverage and government policies, indicating that caution should be exercised when using Google Trends as a monitoring tool for emerging diseases.     

Reporting and Availability of COVID-19 Demographic Data by US Health Departments (April to October 2020): Observational Study

BackgroundThere is an urgent need for consistent collection of demographic data on COVID-19 morbidity and mortality and sharing it with the public in open and accessible ways. Due to the lack of consistency in data reporting during the initial spread of COVID-19, the Equitable Data Collection and Disclosure on COVID-19 Act was introduced into the Congress that mandates collection and reporting of demographic COVID-19 data on testing, treatments, and deaths by age, sex, race and ethnicity, primary language, socioeconomic status, disability, and county. To our knowledge, no studies have evaluated how COVID-19 demographic data have been collected before and after the introduction of this legislation.ObjectiveThis study aimed to evaluate differences in reporting and public availability of COVID-19 demographic data by US state health departments and Washington, District of Columbia (DC) before (pre-Act), immediately after (post-Act), and 6 months after (6-month follow-up) the introduction of the Equitable Data Collection and Disclosure on COVID-19 Act in the Congress on April 21, 2020.MethodsWe reviewed health department websites of all 50 US states and Washington, DC (N=51). We evaluated how each state reported age, sex, and race and ethnicity data for all confirmed COVID-19 cases and deaths and how they made this data available (ie, charts and tables only or combined with dashboards and machine-actionable downloadable formats) at the three timepoints.ResultsWe found statistically significant increases in the number of health departments reporting age-specific data for COVID-19 cases (P=.045) and resulting deaths (P=.002), sex-specific data for COVID-19 deaths (P=.003), and race- and ethnicity-specific data for confirmed cases (P=.003) and deaths (P=.005) post-Act and at the 6-month follow-up (P<.05 for all). The largest increases were race and ethnicity state data for confirmed cases (pre-Act: 18/51, 35%; post-Act: 31/51, 61%; 6-month follow-up: 46/51, 90%) and deaths due to COVID-19 (pre-Act: 13/51, 25%; post-Act: 25/51, 49%; and 6-month follow-up: 39/51, 76%). Although more health departments reported race and ethnicity data based on federal requirements (P<.001), over half (29/51, 56.9%) still did not report all racial and ethnic groups as per the Office of Management and Budget guidelines (pre-Act: 5/51, 10%; post-Act: 21/51, 41%; and 6-month follow-up: 27/51, 53%). The number of health departments that made COVID-19 data available for download significantly increased from 7 to 23 (P<.001) from our initial data collection (April 2020) to the 6-month follow-up, (October 2020).ConclusionsAlthough the increased demand for disaggregation has improved public reporting of demographics across health departments, an urgent need persists for the introduced legislation to be passed by the Congress for the US states to consistently collect and make characteristics of COVID-19 cases, deaths, and vaccinations available in order to allocate resources to mitigate disease spread.     

Cross-Verification of COVID-19 Information Obtained From Unofficial Social Media Accounts and Associated Changes in Health Behaviors: Web-Based Questionnaire Study Among Chinese Netizens

BackgroundAs social media platforms have become significant sources of information during the pandemic, a significant volume of both factual and inaccurate information related to the prevention of COVID-19 has been disseminated through social media. Thus, disparities in COVID-19 information verification across populations have the potential to promote the dissemination of misinformation among clustered groups of people with similar characteristics.ObjectiveThis study aimed to identify the characteristics of social media users who obtained COVID-19 information through unofficial social media accounts and were (1) most likely to change their health behaviors according to web-based information and (2) least likely to actively verify the accuracy of COVID-19 information, as these individuals may be susceptible to inaccurate prevention measures and may exacerbate transmission.MethodsAn online questionnaire consisting of 17 questions was disseminated by West China Hospital via its official online platforms, between May 18, 2020, and May 31, 2020. The questionnaire collected the sociodemographic information of 14,509 adults, and included questions surveying Chinese netizens’ knowledge about COVID-19, personal social media use, health behavioral change tendencies, and cross-verification behaviors for web-based information during the pandemic. Multiple stepwise regression models were used to examine the relationships between social media use, behavior changes, and information cross-verification.ResultsRespondents who were most likely to change their health behaviors after obtaining web-based COVID-19 information from celebrity sources had the following characteristics: female sex (P=.004), age ≥50 years (P=.009), higher COVID-19 knowledge and health literacy (P=.045 and P=.03, respectively), non–health care professional (P=.02), higher frequency of searching on social media (P<.001), better health conditions (P<.001), and a trust rating score of more than 3 for information released by celebrities on social media (P=.005). Furthermore, among participants who were most likely to change their health behaviors according to social media information released by celebrities, female sex (P<.001), living in a rural residence rather than first-tier city (P<.001), self-reported medium health status and lower health care literacy (P=.007 and P<.001, respectively), less frequent search for COVID-19 information on social media (P<.001), and greater level of trust toward celebrities’ social media accounts with a trust rating score greater than 1 (P≤.04) were associated with a lack of cross-verification of information.ConclusionsThe findings suggest that governments, health care agencies, celebrities, and technicians should combine their efforts to decrease the risk in vulnerable groups that are inclined to change health behaviors according to web-based information but do not perform any fact-check verification of the accuracy of the unofficial information. Specifically, it is necessary to correct the false information related to COVID-19 on social media, appropriately apply celebrities’ star power, and increase Chinese netizens’ awareness of information cross-verification and eHealth literacy for evaluating the veracity of web-based information.     

The Influence of Social Distancing on COVID-19 Mortality in US Counties: Cross-sectional Study

BackgroundPrevious studies on the impact of social distancing on COVID-19 mortality in the United States have predominantly examined this relationship at the national level and have not separated COVID-19 deaths in nursing homes from total COVID-19 deaths. This approach may obscure differences in social distancing behaviors by county in addition to the actual effectiveness of social distancing in preventing COVID-19 deaths.ObjectiveThis study aimed to determine the influence of county-level social distancing behavior on COVID-19 mortality (deaths per 100,000 people) across US counties over the period of the implementation of stay-at-home orders in most US states (March-May 2020).MethodsUsing social distancing data from tracked mobile phones in all US counties, we estimated the relationship between social distancing (average proportion of mobile phone usage outside of home between March and May 2020) and COVID-19 mortality (when the state in which the county is located reported its first confirmed case of COVID-19 and up to May 31, 2020) with a mixed-effects negative binomial model while distinguishing COVID-19 deaths in nursing homes from total COVID-19 deaths and accounting for social distancing– and COVID-19–related factors (including the period between the report of the first confirmed case of COVID-19 and May 31, 2020; population density; social vulnerability; and hospital resource availability). Results from the mixed-effects negative binomial model were then used to generate marginal effects at the mean, which helped separate the influence of social distancing on COVID-19 deaths from other covariates while calculating COVID-19 deaths per 100,000 people.ResultsWe observed that a 1% increase in average mobile phone usage outside of home between March and May 2020 led to a significant increase in COVID-19 mortality by a factor of 1.18 (P<.001), while every 1% increase in the average proportion of mobile phone usage outside of home in February 2020 was found to significantly decrease COVID-19 mortality by a factor of 0.90 (P<.001).ConclusionsAs stay-at-home orders have been lifted in many US states, continued adherence to other social distancing measures, such as avoiding large gatherings and maintaining physical distance in public, are key to preventing additional COVID-19 deaths in counties across the country.     

Social Media Use,Unhealthy Lifestyles,and the Risk of Miscarriage Among Pregnant Women During the COVID-19 Pandemic: Prospective Observational Study

BackgroundThe COVID-19 pandemic has resulted in changes to normal life and disrupted social and economic function worldwide. However, little is known about the impact of social media use, unhealthy lifestyles, and the risk of miscarriage among pregnant women during the COVID-19 pandemic.ObjectiveThis study aims to assess the association between social media use, unhealthy lifestyles, and the risk of miscarriage among pregnant women in the early stage of the COVID-19 pandemic in China.MethodsIn this prospective cohort study, 456 singleton pregnant women in mainland China were recruited during January and February 2020. Sociodemographic characteristics, history of previous health, social media use, and current lifestyles were collected at baseline, and we followed up about the occurrence of miscarriage. Log-binomial regression models were used to estimate the risk ratios (RRs) of miscarriage for women with different exposures to COVID-19–specific information.ResultsAmong all the 456 pregnant women, there were 82 (18.0%) who did no physical activities, 82 (18.0%) with inadequate dietary diversity, 174 (38.2%) with poor sleep quality, and 54 (11.8%) spending >3 hours on reading COVID-19 news per day. Women with excessive media use (>3 hours) were more likely to be previously pregnant (P=.03), have no physical activity (P=.003), have inadequate dietary diversity (P=.03), and have poor sleep quality (P<.001). The prevalence of miscarriage was 16.0% (n=73; 95% CI 12.6%-19.4%). Compared with women who spent 0.5-2 hours (25/247, 10.1%) on reading COVID-19 news per day, miscarriage prevalence in women who spent <0.5 hours (5/23, 21.7%), 2-3 hours (26/132, 19.7%), and >3 hours (17/54, 31.5%) was higher (P<.001). Miscarriage prevalence was also higher in pregnant women with poor sleep quality (39/174, 22.4% vs 34/282, 12.1%; P=.003) and a high education level (66/368, 17.9% vs 7/88, 8.0%; P=.02). In the multivariable model, poor sleep quality (adjusted RR 2.06, 95% CI 1.24-3.44; P=.006), 2-3 hours of media use daily (adjusted RR 1.74, 95% CI 1.02-2.97; P=.04), and >3 hours of media use daily (adjusted RR 2.56, 95% CI 1.43-4.59; P=.002) were associated with miscarriage. In the sensitivity analysis, results were still stable.ConclusionsPregnant women with excessive media use were more likely to have no physical activity, inadequate dietary diversity, and poor sleep quality. Excessive media use and poor sleep quality were associated with a higher risk of miscarriage. Our findings highlight the importance of healthy lifestyles during the COVID-19 pandemic.     

Using the Novel Mortality-Prevalence Ratio to Evaluate Potentially Undocumented SARS-CoV-2 Infection: Correlational Study

BackgroundThe high prevalence of COVID-19 has resulted in 200,000 deaths as of early 2020. The corresponding mortality rate among different countries and times varies.ObjectiveThis study aims to investigate the relationship between the mortality rate and prevalence of COVID-19 within a country.MethodsWe collected data from the Johns Hopkins Coronavirus Resource Center. These data included the daily cumulative death count, recovered count, and confirmed count for each country. This study focused on a total of 36 countries with over 10,000 confirmed COVID-19 cases. Mortality was the main outcome and dependent variable, and it was computed by dividing the number of COVID-19 deaths by the number of confirmed cases.ResultsThe results of our global panel regression analysis showed that there was a highly significant correlation between prevalence and mortality (ρ=0.8304; P<.001). We found that every increment of 1 confirmed COVID-19 case per 1000 individuals led to a 1.29268% increase in mortality, after controlling for country-specific baseline mortality and time-fixed effects. Over 70% of excess mortality could be attributed to prevalence, and the heterogeneity among countries’ mortality-prevalence ratio was significant (P<.001). Further, our results showed that China had an abnormally high and significant mortality-prevalence ratio compared to other countries (P<.001). This unusual deviation in the mortality-prevalence ratio disappeared with the removal of the data that was collected from China after February 17, 2020. It is worth noting that the prevalence of a disease relies on accurate diagnoses and comprehensive surveillance, which can be difficult to achieve due to practical or political concerns.ConclusionsThe association between COVID-19 mortality and prevalence was observed and quantified as the mortality-prevalence ratio. Our results highlight the importance of constraining disease transmission to decrease mortality rates. The comparison of mortality-prevalence ratios between countries can be a powerful method for detecting, or even quantifying, the proportion of individuals with undocumented SARS-CoV-2 infection.     

Differences in Clinical Presentation With Long COVID After Community and Hospital Infection and Associations With All-Cause Mortality: English Sentinel Network Database Study

BackgroundMost studies of long COVID (symptoms of COVID-19 infection beyond 4 weeks) have focused on people hospitalized in their initial illness. Long COVID is thought to be underrecorded in UK primary care electronic records.ObjectiveWe sought to determine which symptoms people present to primary care after COVID-19 infection and whether presentation differs in people who were not hospitalized, as well as post–long COVID mortality rates.MethodsWe used routine data from the nationally representative primary care sentinel cohort of the Oxford–Royal College of General Practitioners Research and Surveillance Centre (N=7,396,702), applying a predefined long COVID phenotype and grouped by whether the index infection occurred in hospital or in the community. We included COVID-19 infection cases from March 1, 2020, to April 1, 2021. We conducted a before-and-after analysis of long COVID symptoms prespecified by the Office of National Statistics, comparing symptoms presented between 1 and 6 months after the index infection matched with the same months 1 year previously. We conducted logistic regression analysis, quoting odds ratios (ORs) with 95% CIs.ResultsIn total, 5.63% (416,505/7,396,702) and 1.83% (7623/416,505) of the patients had received a coded diagnosis of COVID-19 infection and diagnosis of, or referral for, long COVID, respectively. People with diagnosis or referral of long COVID had higher odds of presenting the prespecified symptoms after versus before COVID-19 infection (OR 2.66, 95% CI 2.46-2.88, for those with index community infection and OR 2.42, 95% CI 2.03-2.89, for those hospitalized). After an index community infection, patients were more likely to present with nonspecific symptoms (OR 3.44, 95% CI 3.00-3.95; P<.001) compared with after a hospital admission (OR 2.09, 95% CI 1.56-2.80; P<.001). Mental health sequelae were more strongly associated with index hospital infections (OR 2.21, 95% CI 1.64-2.96) than with index community infections (OR 1.36, 95% CI 1.21-1.53; P<.001). People presenting to primary care after hospital infection were more likely to be men (OR 1.43, 95% CI 1.25-1.64; P<.001), more socioeconomically deprived (OR 1.42, 95% CI 1.24-1.63; P<.001), and with higher multimorbidity scores (OR 1.41, 95% CI 1.26-1.57; P<.001) than those presenting after an index community infection. All-cause mortality in people with long COVID was associated with increasing age, male sex (OR 3.32, 95% CI 1.34-9.24; P=.01), and higher multimorbidity score (OR 2.11, 95% CI 1.34-3.29; P<.001). Vaccination was associated with reduced odds of mortality (OR 0.10, 95% CI 0.03-0.35; P<.001).ConclusionsThe low percentage of people recorded as having long COVID after COVID-19 infection reflects either low prevalence or underrecording. The characteristics and comorbidities of those presenting with long COVID after a community infection are different from those hospitalized. This study provides insights into the presentation of long COVID in primary care and implications for workload.     

Willingness to Receive COVID-19 Vaccination Among People Living With HIV and AIDS in China: Nationwide Cross-sectional Online Survey

BackgroundHIV infection is a significant independent risk factor for both severe COVID-19 presentation at hospital admission and in-hospital mortality. Available information has suggested that people living with HIV and AIDS (PLWHA) could benefit from COVID-19 vaccination. However, there is a dearth of evidence on willingness to receive COVID-19 vaccination among PLWHA.ObjectiveThe aim of this study was to investigate willingness to receive COVID-19 vaccination among a national sample of PLWHA in China.MethodsThis cross-sectional online survey investigated factors associated with willingness to receive COVID-19 vaccination among PLWHA aged 18 to 65 years living in eight conveniently selected Chinese metropolitan cities between January and February 2021. Eight community-based organizations (CBOs) providing services to PLWHA facilitated the recruitment. Eligible PLWHA completed an online survey developed using a widely used encrypted web-based survey platform in China. We fitted a single logistic regression model to obtain adjusted odds ratios (aORs), which involved one of the independent variables of interest and all significant background variables. Path analysis was also used in the data analysis.ResultsOut of 10,845 PLWHA approached by the CBOs, 2740 completed the survey, and 170 had received at least one dose of the COVID-19 vaccine. This analysis was performed among 2570 participants who had never received COVID-19 vaccination. Over half of the participants reported willingness to receive COVID-19 vaccination (1470/2570, 57.2%). Perceptions related to COVID-19 vaccination were significantly associated with willingness to receive COVID-19 vaccination, including positive attitudes (aOR 1.11, 95% CI 1.09-1.12; P<.001), negative attitudes (aOR 0.96, 95% CI 0.94-0.97; P<.001), perceived support from significant others (perceived subjective norm; aOR 1.53, 95% CI 1.46-1.61; P<.001), and perceived behavioral control (aOR 1.13, 95% CI 1.11-1.14; P<.001). At the interpersonal level, receiving advice supportive of COVID-19 vaccination from doctors (aOR 1.99, 95% CI 1.65-2.40; P<.001), CBO staff (aOR 1.89, 95% CI 1.51-2.36; P<.001), friends and/or family members (aOR 3.22, 95% CI 1.93-5.35; P<.001), and PLWHA peers (aOR 2.38, 95% CI 1.85-3.08; P<.001) was associated with higher willingness to receive COVID-19 vaccination. The overall opinion supporting COVID-19 vaccination for PLWHA on the internet or social media was also positively associated with willingness to receive COVID-19 vaccination (aOR 1.59, 95% CI 1.31-1.94; P<.001). Path analysis indicated that interpersonal-level variables were indirectly associated with willingness to receive COVID-19 vaccination through perceptions (β=.43, 95% CI .37-.51; P<.001).ConclusionsAs compared to PLWHA in other countries and the general population in most parts of the world, PLWHA in China reported a relatively low willingness to receive COVID-19 vaccination. The internet and social media as well as interpersonal communications may be major sources of influence on PLWHA’s perceptions and willingness to receive COVID-19 vaccination.     

Enhancing COVID-19 Epidemic Forecasting Accuracy by Combining Real-time and Historical Data From Multiple Internet-Based Sources: Analysis of Social Media Data,Online News Articles,and Search Queries

BackgroundThe SARS-COV-2 virus and its variants pose extraordinary challenges for public health worldwide. Timely and accurate forecasting of the COVID-19 epidemic is key to sustaining interventions and policies and efficient resource allocation. Internet-based data sources have shown great potential to supplement traditional infectious disease surveillance, and the combination of different Internet-based data sources has shown greater power to enhance epidemic forecasting accuracy than using a single Internet-based data source. However, existing methods incorporating multiple Internet-based data sources only used real-time data from these sources as exogenous inputs but did not take all the historical data into account. Moreover, the predictive power of different Internet-based data sources in providing early warning for COVID-19 outbreaks has not been fully explored.ObjectiveThe main aim of our study is to explore whether combining real-time and historical data from multiple Internet-based sources could improve the COVID-19 forecasting accuracy over the existing baseline models. A secondary aim is to explore the COVID-19 forecasting timeliness based on different Internet-based data sources.MethodsWe first used core terms and symptom-related keyword-based methods to extract COVID-19–related Internet-based data from December 21, 2019, to February 29, 2020. The Internet-based data we explored included 90,493,912 online news articles, 37,401,900 microblogs, and all the Baidu search query data during that period. We then proposed an autoregressive model with exogenous inputs, incorporating real-time and historical data from multiple Internet-based sources. Our proposed model was compared with baseline models, and all the models were tested during the first wave of COVID-19 epidemics in Hubei province and the rest of mainland China separately. We also used lagged Pearson correlations for COVID-19 forecasting timeliness analysis.ResultsOur proposed model achieved the highest accuracy in all 5 accuracy measures, compared with all the baseline models of both Hubei province and the rest of mainland China. In mainland China, except for Hubei, the COVID-19 epidemic forecasting accuracy differences between our proposed model (model i) and all the other baseline models were statistically significant (model 1, t₁₉₈=–8.722, P<.001; model 2, t₁₉₈=–5.000, P<.001, model 3, t₁₉₈=–1.882, P=.06; model 4, t₁₉₈=–4.644, P<.001; model 5, t₁₉₈=–4.488, P<.001). In Hubei province, our proposed model''s forecasting accuracy improved significantly compared with the baseline model using historical new confirmed COVID-19 case counts only (model 1, t₁₉₈=–1.732, P=.09). Our results also showed that Internet-based sources could provide a 2- to 6-day earlier warning for COVID-19 outbreaks.ConclusionsOur approach incorporating real-time and historical data from multiple Internet-based sources could improve forecasting accuracy for epidemics of COVID-19 and its variants, which may help improve public health agencies'' interventions and resource allocation in mitigating and controlling new waves of COVID-19 or other relevant epidemics.     

The Differential Effects of Social Media on Depressive Symptoms and Suicidal Ideation Among the Younger and Older Adult Population in Hong Kong During the COVID-19 Pandemic: Population-Based Cross-sectional Survey Study

BackgroundSocial media has become a ubiquitous part of daily life during the COVID-19 pandemic isolation. However, the role of social media use in depression and suicidal ideation of the general public remains unclear. Related empirical studies were limited and reported inconsistent findings. Little is known about the potential underlying mechanisms that may illustrate the relationship between social media use and depression and suicidal ideation during the COVID-19 pandemic.ObjectiveThis study tested the mediation effects of social loneliness and posttraumatic stress disorder (PTSD) symptoms on the relationship between social media use and depressive symptoms and suicidal ideation, as well as the moderation effect of age on the mediation models.MethodsWe administered a population-based random telephone survey in May and June 2020, when infection control measures were being vigorously implemented in Hong Kong. A total of 1070 adults (658 social media users and 412 nonusers) completed the survey. Structural equation modeling (SEM) and multigroup SEM were conducted to test the mediation and moderation effects.ResultsThe weighted prevalence of probable depression was 11.6%; 1.6% had suicidal ideation in the past 2 weeks. Both moderated mediation models of depressive symptoms (χ²₆₂=335.3; P<.05; comparative fit index [CFI]=0.94; nonnormed fit index [NNFI]=0.92; root mean square error of approximation [RMSEA]=0.06) and suicidal ideation (χ²₃₄=50.8; P<.05; CFI=0.99; NNFI=0.99; RMSEA=0.02) showed acceptable model fit. There was a significantly negative direct effect of social media use on depressive symptoms among older people (β=–.07; P=.04) but not among younger people (β=.04; P=.55). The indirect effect via PTSD symptoms was significantly positive among both younger people (β=.09; P=.02) and older people (β=.10; P=.01). The indirect effect via social loneliness was significant among older people (β=–.01; P=.04) but not among younger people (β=.01; P=.31). The direct effect of social media use on suicidal ideation was not statistically significant in either age group (P>.05). The indirect effects via PTSD symptoms were statistically significant among younger people (β=.02; P=.04) and older people (β=.03; P=.01). Social loneliness was not a significant mediator between social media use and suicidal ideation among either age group (P>.05).ConclusionsSocial media may be a “double-edged sword” for psychosocial well-being during the COVID-19 pandemic, and its roles vary across age groups. The mediators identified in this study can be addressed by psychological interventions to prevent severe mental health problems during and after the COVID-19 pandemic.     

High Work-Related Stress and Anxiety as a Response to COVID-19 Among Health Care Workers in South Korea: Cross-sectional Online Survey Study

BackgroundThe COVID-19 outbreak had a severe impact on health care workers'' psychological health. It is important to establish a process for psychological assessment and intervention for health care workers during epidemics.ObjectiveWe investigated risk factors associated with psychological impacts for each health care worker group, to help optimize psychological interventions for health care workers in countries affected by the COVID-19 pandemic.MethodsRespondents (n=1787) from 2 hospitals in Korea completed a web-based survey during the period from April 14 to 30, 2020. The web-based survey collected demographic information, psychiatric history, and responses to the 9-item Stress and Anxiety to Viral Epidemics (SAVE-9), 9-item Patient Health Questionnaire (PHQ-9), and 7-item Generalized Anxiety Disorder-7 (GAD-7) scales. We performed logistic regression to assess contributing factors as predictor variables, using health care workers’ depression as outcome variables.ResultsAmong 1783 health care workers, nursing professionals had significantly higher levels of depression (PHQ-9 score: meannurse 5.5, SD 4.6; meanother 3.8, SD 4.2; P<.001), general anxiety (GAD-7 score: meannurse 4.0, SD 4.1; meanother 2.7, SD 3.6; P<.001), and virus-related anxiety symptoms (SAVE-9 score: meannurse 21.6, SD 5.9; meanother 18.6, SD 6.3; P<.001). Among nursing professionals, single workers reported more severe depressive symptoms than married workers (PHQ-9 score ≥10; meannurse 20.3%; meanother 14.1%; P=.02), and junior (<40 years) workers reported more anxiety about the viral epidemic (SAVE-9 anxiety score; meannurse 15.6, SD 4.1; meanother 14.7, SD 4.4; P=.002). Logistic regression revealed that hospital (adjusted odds ratio [OR] 1.45, 95% CI 1.06-1.99), nursing professionals (adjusted OR 1.37, 95% CI 1.02-1.98), single workers (adjusted OR 1.51, 95% CI 1.05-2.16), higher stress and anxiety to the viral infection (high SAVE-9 score, adjusted OR 1.20, 95% CI 1.17-1.24), and past psychiatric history (adjusted OR 3.26, 95% CI 2.15-4.96) were positively associated with depression.ConclusionsPsychological support and interventions should be considered for health care workers, especially nursing professionals, those who are single, and those with high SAVE-9 scores.     

Increases in Naloxone Administrations by Emergency Medical Services Providers During the COVID-19 Pandemic: Retrospective Time Series Study

BackgroundThe opioid crisis in the United States may be exacerbated by the COVID-19 pandemic. Increases in opioid use, emergency medical services (EMS) runs for opioid-related overdoses, and opioid overdose deaths have been reported. No study has examined changes in multiple naloxone administrations, an indicator of overdose severity, during the COVID-19 pandemic.ObjectiveThis study examines changes in the occurrence of naloxone administrations and multiple naloxone administrations during EMS runs for opioid-related overdoses during the COVID-19 pandemic in Guilford County, North Carolina (NC).MethodsUsing a period-over-period approach, we compared the occurrence of opioid-related EMS runs, naloxone administrations, and multiple naloxone administrations during the 29-week period before (September 1, 2019, to March 9, 2020) and after NC’s COVID-19 state of emergency declaration (ie, the COVID-19 period of March 10 to September 30, 2020). Furthermore, historical data were used to generate a quasi-control distribution of period-over-period changes to compare the occurrence of each outcome during the COVID-19 period to each 29-week period back to January 1, 2014.ResultsAll outcomes increased during the COVID-19 period. Compared to the previous 29 weeks, the COVID-19 period experienced increases in the weekly mean number of opioid-related EMS runs (25.6, SD 5.6 vs 18.6, SD 6.6; P<.001), naloxone administrations (22.3, SD 6.2 vs 14.1, SD 6.0; P<.001), and multiple naloxone administrations (5.0, SD 1.9 vs 2.7, SD 1.9; P<.001), corresponding to proportional increases of 37.4%, 57.8%, and 84.8%, respectively. Additionally, the increases during the COVID-19 period were greater than 91% of all historical 29-week periods analyzed.ConclusionsThe occurrence of EMS runs for opioid-related overdoses, naloxone administrations, and multiple naloxone administrations during EMS runs increased during the COVID-19 pandemic in Guilford County, NC. For a host of reasons that need to be explored, the COVID-19 pandemic appears to have exacerbated the opioid crisis.     

Investigating Linkages Between Spatiotemporal Patterns of the COVID-19 Delta Variant and Public Health Interventions in Southeast Asia: Prospective Space-Time Scan Statistical Analysis Method

BackgroundThe COVID-19 Delta variant has presented an unprecedented challenge to countries in Southeast Asia (SEA). Its transmission has shown spatial heterogeneity in SEA after countries have adopted different public health interventions during the process. Hence, it is crucial for public health authorities to discover potential linkages between epidemic progression and corresponding interventions such that collective and coordinated control measurements can be designed to increase their effectiveness at reducing transmission in SEA.ObjectiveThe purpose of this study is to explore potential linkages between the spatiotemporal progression of the COVID-19 Delta variant and nonpharmaceutical intervention (NPI) measures in SEA. We detected the space-time clusters of outbreaks of COVID-19 and analyzed how the NPI measures relate to the propagation of COVID-19.MethodsWe collected district-level daily new cases of COVID-19 from June 1 to October 31, 2021, and district-level population data in SEA. We adopted prospective space-time scan statistics to identify the space-time clusters. Using cumulative prospective space-time scan statistics, we further identified variations of relative risk (RR) across each district at a half-month interval and their potential public health intervention linkages.ResultsWe found 7 high-risk clusters (clusters 1-7) of COVID-19 transmission in Malaysia, the Philippines, Thailand, Vietnam, and Indonesia between June and August, 2021, with an RR of 5.45 (P<.001), 3.50 (P<.001), 2.30 (P<.001), 1.36 (P<.001), 5.62 (P<.001), 2.38 (P<.001), 3.45 (P<.001), respectively. There were 34 provinces in Indonesia that have successfully mitigated the risk of COVID-19, with a decreasing range between –0.05 and –1.46 due to the assistance of continuous restrictions. However, 58.6% of districts in Malaysia, Singapore, Thailand, and the Philippines saw an increase in the infection risk, which is aligned with their loosened restrictions. Continuous strict interventions were effective in mitigating COVID-19, while relaxing restrictions may exacerbate the propagation risk of this epidemic.ConclusionsThe analyses of space-time clusters and RRs of districts benefit public health authorities with continuous surveillance of COVID-19 dynamics using real-time data. International coordination with more synchronized interventions amidst all SEA countries may play a key role in mitigating the progression of COVID-19.     

Multilevel Determinants of COVID-19 Vaccine Uptake Among South Asian Ethnic Minorities in Hong Kong: Cross-sectional Web-Based Survey

BackgroundThe COVID-19 pandemic continues to have a disproportionate effect on ethnic minorities. Across countries, greater vaccine hesitancy has been observed among ethnic minorities. After excluding foreign domestic helpers, South Asians make up the largest proportion of ethnic minorities in Hong Kong. It is necessary to plan for COVID-19 vaccination promotional strategies that cater to the unique needs of South Asians in Hong Kong.ObjectiveThis study investigated the prevalence of COVID-19 vaccine uptake among a sample of South Asians in Hong Kong. We examined the effects of sociodemographic data and factors at individual level (perceptions), interpersonal level (information exposure on social media), and sociostructural level (cultural) based on the socioecological model.MethodsA cross-sectional web-based survey was conducted on May 1-31, 2021. Participants were South Asian people aged 18 years or older living in Hong Kong; able to comprehend English, Hindi, Nepali, or Urdu; and having access to a smartphone. Three community-based organizations providing services to South Asians in Hong Kong facilitated the data collection. The staff of the community-based organizations posted the study information in WhatsApp groups involving South Asian clients and invited them to participate in a web-based survey. Logistic regression models were fit for data analysis.ResultsAmong 245 participants, 81 (33.1%) had taken at least one dose of the COVID-19 vaccine (one dose, 62/245, 25.2%; and both doses, 19/245, 7.9%). After adjusting for significant background characteristics, cultural and religious reasons for COVID-19 vaccine hesitancy were associated with lower COVID-19 vaccine uptake (adjusted odds ratio [AOR] 0.83, 95% CI 0.71-0.97; P=.02). At the individual level, having more positive attitudes toward COVID-19 vaccination (AOR 1.31, 95% CI 1.10-1.55; P=.002), perceived support from significant others (AOR 1.29, 95% CI 1.03-1.60; P=.03), and perceived higher behavioral control to receive COVID-19 vaccination (AOR 2.63, 95% CI 1.65-4.19; P<.001) were associated with higher COVID-19 vaccine uptake, while a negative association was found between negative attitudes and the dependent variable (AOR 0.73, 95% CI 0.62-0.85; P<.001). Knowing more peers who had taken the COVID-19 vaccine was also associated with higher uptake (AOR 1.39, 95% CI 1.11-1.74; P=.01). At the interpersonal level, higher exposure to information about deaths and other serious conditions caused by COVID-19 vaccination was associated with lower uptake (AOR 0.54, 95% CI 0.33-0.86; P=.01).ConclusionsIn this study, one-third (81/245) of our participants received at least one dose of the COVID-19 vaccine. Cultural or religious reasons, perceptions, information exposure on social media, and influence of peers were found to be the determinants of COVID-19 vaccine uptake among South Asians. Future programs should engage community groups, champions, and faith leaders, and develop culturally competent interventions.     

Correlation of Population SARS-CoV-2 Cycle Threshold Values to Local Disease Dynamics: Exploratory Observational Study

BackgroundDespite the limitations in the use of cycle threshold (CT) values for individual patient care, population distributions of CT values may be useful indicators of local outbreaks.ObjectiveWe aimed to conduct an exploratory analysis of potential correlations between the population distribution of cycle threshold (CT) values and COVID-19 dynamics, which were operationalized as percent positivity, transmission rate (R_t), and COVID-19 hospitalization count.MethodsIn total, 148,410 specimens collected between September 15, 2020, and January 11, 2021, from the greater El Paso area were processed in the Dascena COVID-19 Laboratory. The daily median CT value, daily R_t, daily count of COVID-19 hospitalizations, daily change in percent positivity, and rolling averages of these features were plotted over time. Two-way scatterplots and linear regression were used to evaluate possible associations between daily median CT values and outbreak measures. Cross-correlation plots were used to determine whether a time delay existed between changes in daily median CT values and measures of community disease dynamics.ResultsDaily median CT values negatively correlated with the daily R_t values (P<.001), the daily COVID-19 hospitalization counts (with a 33-day time delay; P<.001), and the daily changes in percent positivity among testing samples (P<.001). Despite visual trends suggesting time delays in the plots for median CT values and outbreak measures, a statistically significant delay was only detected between changes in median CT values and COVID-19 hospitalization counts (P<.001).ConclusionsThis study adds to the literature by analyzing samples collected from an entire geographical area and contextualizing the results with other research investigating population CT values.     

Exploring the Risk of Suicide in Real Time on Spanish Twitter: Observational Study

BackgroundSocial media is now a common context wherein people express their feelings in real time. These platforms are increasingly showing their potential to detect the mental health status of the population. Suicide prevention is a global health priority and efforts toward early detection are starting to develop, although there is a need for more robust research.ObjectiveWe aimed to explore the emotional content of Twitter posts in Spanish and their relationships with severity of the risk of suicide at the time of writing the tweet.MethodsTweets containing a specific lexicon relating to suicide were filtered through Twitter''s public application programming interface. Expert psychologists were trained to independently evaluate these tweets. Each tweet was evaluated by 3 experts. Tweets were filtered by experts according to their relevance to the risk of suicide. In the tweets, the experts evaluated: (1) the severity of the general risk of suicide and the risk of suicide at the time of writing the tweet (2) the emotional valence and intensity of 5 basic emotions; (3) relevant personality traits; and (4) other relevant risk variables such as helplessness, desire to escape, perceived social support, and intensity of suicidal ideation. Correlation and multivariate analyses were performed.ResultsOf 2509 tweets, 8.61% (n=216) were considered to indicate suicidality by most experts. Severity of the risk of suicide at the time was correlated with sadness (ρ=0.266; P<.001), joy (ρ=–0.234; P=.001), general risk (ρ=0.908; P<.001), and intensity of suicidal ideation (ρ=0.766; P<.001). The severity of risk at the time of the tweet was significantly higher in people who expressed feelings of defeat and rejection (P=.003), a desire to escape (P<.001), a lack of social support (P=.03), helplessness (P=.001), and daily recurrent thoughts (P=.007). In the multivariate analysis, the intensity of suicide ideation was a predictor for the severity of suicidal risk at the time (β=0.311; P=.001), as well as being a predictor for fear (β=–0.009; P=.01) and emotional valence (β=0.007; P=.009). The model explained 75% of the variance.ConclusionsThese findings suggest that it is possible to identify emotional content and other risk factors in suicidal tweets with a Spanish sample. Emotional analysis and, in particular, the detection of emotional variations may be key for real-time suicide prevention through social media.     

The Influence of Average Temperature and Relative Humidity on New Cases of COVID-19: Time-Series Analysis

BackgroundThe influence of meteorological factors on the transmission and spread of COVID-19 is of interest and has not been investigated.ObjectiveThis study aimed to investigate the associations between meteorological factors and the daily number of new cases of COVID-19 in 9 Asian cities.MethodsPearson correlation and generalized additive modeling (GAM) were performed to assess the relationships between daily new COVID-19 cases and meteorological factors (daily average temperature and relative humidity) with the most updated data currently available.ResultsThe Pearson correlation showed that daily new confirmed cases of COVID-19 were more correlated with the average temperature than with relative humidity. Daily new confirmed cases were negatively correlated with the average temperature in Beijing (r=–0.565, P<.001), Shanghai (r=–0.47, P<.001), and Guangzhou (r=–0.53, P<.001). In Japan, however, a positive correlation was observed (r=0.416, P<.001). In most of the cities (Shanghai, Guangzhou, Hong Kong, Seoul, Tokyo, and Kuala Lumpur), GAM analysis showed the number of daily new confirmed cases to be positively associated with both average temperature and relative humidity, especially using lagged 3D modeling where the positive influence of temperature on daily new confirmed cases was discerned in 5 cities (exceptions: Beijing, Wuhan, Korea, and Malaysia). Moreover, the sensitivity analysis showed, by incorporating the city grade and public health measures into the model, that higher temperatures can increase daily new case numbers (beta=0.073, Z=11.594, P<.001) in the lagged 3-day model.ConclusionsThe findings suggest that increased temperature yield increases in daily new cases of COVID-19. Hence, large-scale public health measures and expanded regional research are still required until a vaccine becomes widely available and herd immunity is established.