%0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e28956 %T Designing Better Exposure Notification Apps: The Role of Persuasive Design %A Oyibo,Kiemute %A Morita,Plinio Pelegrini %+ School of Public Health Sciences, Faculty of Health, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada, 1 5198884567 ext 41372, plinio.morita@uwaterloo.ca %K contact tracing app %K exposure notification app %K COVID Alert %K COVID-19 %K persuasive technology %K behavior change %D 2021 %7 16.11.2021 %9 Viewpoint %J JMIR Public Health Surveill %G English %X Background: Digital contact tracing apps have been deployed worldwide to limit the spread of COVID-19 during this pandemic and to facilitate the lifting of public health restrictions. However, due to privacy-, trust-, and design-related issues, the apps are yet to be widely adopted. This calls for an intervention to enable a critical mass of users to adopt them. Objective: The aim of this paper is to provide guidelines to design contact tracing apps as persuasive technologies to make them more appealing and effective. Methods: We identified the limitations of the current contact tracing apps on the market using the Government of Canada’s official exposure notification app (COVID Alert) as a case study. Particularly, we identified three interfaces in the COVID Alert app where the design can be improved. The interfaces include the no exposure status interface, exposure interface, and diagnosis report interface. We propose persuasive technology design guidelines to make them more motivational and effective in eliciting the desired behavior change. Results: Apart from trust and privacy concerns, we identified the minimalist and nonmotivational design of exposure notification apps as the key design-related factors that contribute to the current low uptake. We proposed persuasive strategies such as self-monitoring of daily contacts and exposure time to make the no exposure and exposure interfaces visually appealing and motivational. Moreover, we proposed social learning, praise, and reward to increase the diagnosis report interface’s effectiveness. Conclusions: We demonstrated that exposure notification apps can be designed as persuasive technologies by incorporating key persuasive features, which have the potential to improve uptake, use, COVID-19 diagnosis reporting, and compliance with social distancing guidelines. %M 34783673 %R 10.2196/28956 %U https://publichealth.jmir.org/2021/11/e28956 %U https://doi.org/10.2196/28956 %U http://www.ncbi.nlm.nih.gov/pubmed/34783673 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e30399 %T Defining Digital Public Health and the Role of Digitization, Digitalization, and Digital Transformation: Scoping Review %A Iyamu,Ihoghosa %A Xu,Alice X T %A Gómez-Ramírez,Oralia %A Ablona,Aidan %A Chang,Hsiu-Ju %A Mckee,Geoff %A Gilbert,Mark %+ Clinical Prevention Services, British Columbia Centre for Disease Control, 655 W 12th Ave, Vancouver, BC, V5Z4R4, Canada, 1 604 707 5619, mark.gilbert@bccdc.ca %K digital public health %K digital transformation %K digitalization %K scoping review %K digitization %K definition %K mobile phone %D 2021 %7 26.11.2021 %9 Review %J JMIR Public Health Surveill %G English %X Background: The recent proliferation and application of digital technologies in public health has spurred interest in digital public health. However, as yet, there appears to be a lack of conceptual clarity and consensus on its definition. Objective: In this scoping review, we seek to assess formal and informal definitions of digital public health in the literature and to understand how these definitions have been conceptualized in relation to digitization, digitalization, and digital transformation. Methods: We conducted a scoping literature search in Ovid MEDLINE, Embase, Google Scholar, and 14 government and intergovernmental agency websites encompassing 6 geographic regions. Among a total of 409 full articles identified, we reviewed 11 publications that either formally defined digital public health or informally described the integration of digital technologies into public health in relation to digitization, digitalization, and digital transformation, and we conducted a thematic analysis of the identified definitions. Results: Two explicit definitions of digital public health were identified, each with divergent meanings. The first definition suggested digital public health was a reimagination of public health using new ways of working, blending established public health wisdom with new digital concepts and tools. The second definition highlighted digital public health as an asset to achieve existing public health goals. In relation to public health, digitization was used to refer to the technical process of converting analog records to digital data, digitalization referred to the integration of digital technologies into public health operations, and digital transformation was used to describe a cultural shift that pervasively integrates digital technologies and reorganizes services on the basis of the health needs of the public. Conclusions: The definition of digital public health remains contested in the literature. Public health researchers and practitioners need to clarify these conceptual definitions to harness opportunities to integrate digital technologies into public health in a way that maximizes their potential to improve public health outcomes. International Registered Report Identifier (IRRID): RR2-10.2196/preprints.27686 %M 34842555 %R 10.2196/30399 %U https://publichealth.jmir.org/2021/11/e30399 %U https://doi.org/10.2196/30399 %U http://www.ncbi.nlm.nih.gov/pubmed/34842555 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e25976 %T Long-Term Survival Among Histological Subtypes in Advanced Epithelial Ovarian Cancer: Population-Based Study Using the Surveillance, Epidemiology, and End Results Database %A Yang,Shi-Ping %A Su,Hui-Luan %A Chen,Xiu-Bei %A Hua,Li %A Chen,Jian-Xian %A Hu,Min %A Lei,Jian %A Wu,San-Gang %A Zhou,Juan %+ Department of Obstetrics and Gynecology, The First Affiliated Hospital of Xiamen University, 55 Zhenhai Road, Xiamen, 361003, China, 86 5922139531, zhoujuan@xmu.edu.cn %K ovarian epithelial carcinoma %K survivors %K histology %K survival rate %K survival %K ovarian %K cancer %K surveillance %K epidemiology %K women’s health %K reproductive health %K Surveillance, Epidemiology, and End Results %K ovary %K oncology %K survivorship %K long-term outcome %K epithelial %D 2021 %7 17.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Actual long-term survival rates for advanced epithelial ovarian cancer (EOC) are rarely reported. Objective: This study aimed to assess the role of histological subtypes in predicting the prognosis among long-term survivors (≥5 years) of advanced EOC. Methods: We performed a retrospective analysis of data among patients with stage III-IV EOC diagnosed from 2000 to 2014 using the Surveillance, Epidemiology, and End Results cancer data of the United States. We used the chi-square test, Kaplan–Meier analysis, and multivariate Cox proportional hazards model for the analyses. Results: We included 8050 patients in this study, including 6929 (86.1%), 743 (9.2%), 237 (2.9%), and 141 (1.8%) patients with serous, endometrioid, clear cell, and mucinous tumors, respectively. With a median follow-up of 91 months, the most common cause of death was primary ovarian cancer (80.3%), followed by other cancers (8.1%), other causes of death (7.3%), cardiac-related death (3.2%), and nonmalignant pulmonary disease (3.2%). Patients with the serous subtype were more likely to die from primary ovarian cancer, and patients with the mucinous subtype were more likely to die from other cancers and cardiac-related disease. Multivariate Cox analysis showed that patients with endometrioid (hazard ratio [HR] 0.534, P<.001), mucinous (HR 0.454, P<.001), and clear cell (HR 0.563, P<.001) subtypes showed better ovarian cancer-specific survival than those with the serous subtype. Similar results were found regarding overall survival. However, ovarian cancer–specific survival and overall survival were comparable among those with endometrioid, clear cell, and mucinous tumors. Conclusions: Ovarian cancer remains the primary cause of death in long-term ovarian cancer survivors. Moreover, the probability of death was significantly different among those with different histological subtypes. It is important for clinicians to individualize the surveillance program for long-term ovarian cancer survivors. %M 34787583 %R 10.2196/25976 %U https://publichealth.jmir.org/2021/11/e25976 %U https://doi.org/10.2196/25976 %U http://www.ncbi.nlm.nih.gov/pubmed/34787583 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e29693 %T Prevalence of Multimorbidity of Chronic Noncommunicable Diseases in Brazil: Population-Based Study %A Shi,Xin %A Lima,Simone Maria da Silva %A Mota,Caroline Maria de Miranda %A Lu,Ying %A Stafford,Randall S %A Pereira,Corintho Viana %+ Management Engineering Department, Universidade Federal de Pernambuco, Av Prof Moraes Rego, 1235, Cidade Universitaria, Recife, 50670-901, Brazil, 55 8138795574, caroline.mota@ufpe.br %K multimorbidity %K prevalence %K health care %K public health %K Brazil %K logistic regression %D 2021 %7 25.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Multimorbidity is the co-occurrence of two or more chronic diseases. Objective: This study, based on self-reported medical diagnosis, aims to investigate the dynamic distribution of multimorbidity across sociodemographic levels and its impacts on health-related issues over 15 years in Brazil using national data. Methods: Data were analyzed using descriptive statistics, hypothesis tests, and logistic regression. The study sample comprised 679,572 adults (18-59 years of age) and 115,699 elderly people (≥60 years of age) from the two latest cross-sectional, multiple-cohort, national-based studies: the National Sample Household Survey (PNAD) of 1998, 2003, and 2008, and the Brazilian National Health Survey (PNS) of 2013. Results: Overall, the risk of multimorbidity in adults was 1.7 times higher in women (odds ratio [OR] 1.73, 95% CI 1.67-1.79) and 1.3 times higher among people without education (OR 1.34, 95% CI 1.28-1.41). Multiple chronic diseases considerably increased with age in Brazil, and people between 50 and 59 years old were about 12 times more likely to have multimorbidity than adults between 18 and 29 years of age (OR 11.89, 95% CI 11.27-12.55). Seniors with multimorbidity had more than twice the likelihood of receiving health assistance in community services or clinics (OR 2.16, 95% CI 2.02-2.31) and of being hospitalized (OR 2.37, 95% CI 2.21-2.56). The subjective well-being of adults with multimorbidity was often worse than people without multiple chronic diseases (OR=12.85, 95% CI: 12.07-13.68). These patterns were similar across all 4 cohorts analyzed and were relatively stable over 15 years. Conclusions: Our study shows little variation in the prevalence of the multimorbidity of chronic diseases in Brazil over time, but there are differences in the prevalence of multimorbidity across different social groups. It is hoped that the analysis of multimorbidity from the two latest Brazil national surveys will support policy making on epidemic prevention and management. %M 34842558 %R 10.2196/29693 %U https://publichealth.jmir.org/2021/11/e29693 %U https://doi.org/10.2196/29693 %U http://www.ncbi.nlm.nih.gov/pubmed/34842558 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e27626 %T Evaluation of the National Tuberculosis Surveillance System in Sana’a, Yemen, 2018: Observational Study %A Al kalali,Fadwa Salem Ahmed %A Mahyoub,Essam %A Al-Hammadi,Abdulbary %A Anam,Labiba %A Khader,Yousef %+ Yemen Field Epidemiology Training Program, Ministry of Public Health and Population, Mazda St, Al Hasaba, Sana’a, 12093, Yemen, 967 778005123, fadwa20102011@yahoo.com %K evaluation %K surveillance system %K tuberculosis %K Yemen %D 2021 %7 30.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Tuberculosis remains a public problem that is considered one of the top causes of morbidity and mortality worldwide. The National Tuberculosis Control Program in Yemen was established in 1970 and included in the national health policy under the leadership of the Ministry of Public Health and Population to monitor tuberculosis control. The surveillance system must be evaluated periodically to produce recommendations for improving performance and usefulness. Objective: This study aims to assess the usefulness and the performance of the tuberculosis surveillance system attributes and to identify the strengths and weaknesses of the system. Methods: A quantitative and qualitative evaluation of the national tuberculosis surveillance system was conducted using the Centers for Disease Control and Prevention’s updated guidelines. The study was carried out in 10 districts in Sana’a City. A total of 28 public health facilities providing tuberculosis services for the whole population in their assigned catchment areas were purposively selected. All participants were interviewed based on their involvement with key aspects of tuberculosis surveillance activities. Results: The tuberculosis surveillance system was found to have an average performance in usefulness (57/80, 71%), flexibility (30/40, 75%), acceptability (174/264, 66%), data quality (4/6, 67%), and positive predictive value (78/107, 73%), and poor performance in simplicity (863/1452, 59%) and stability (15%, 3/20). In addition, the system also had a good performance in sensitivity (78/81, 96%). Conclusions: The tuberculosis surveillance system was found to be useful. The flexibility, positive predictive value, and data quality were average. Stability and simplicity were poor. The sensitivity was good. The main weaknesses in the tuberculosis surveillance system include a lack of governmental financial support, a paper-based system, and a lack of regular staff training. Developing an electronic system, securing governmental finances, and training the staff on tuberculosis surveillance are strongly recommended to improve the system performance. %M 34851294 %R 10.2196/27626 %U https://publichealth.jmir.org/2021/11/e27626 %U https://doi.org/10.2196/27626 %U http://www.ncbi.nlm.nih.gov/pubmed/34851294 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e29319 %T Association of Substance Use With Behavioral Adherence to Centers for Disease Control and Prevention Guidelines for COVID-19 Mitigation: Cross-sectional Web-Based Survey %A Monnig,Mollie A %A Treloar Padovano,Hayley %A Sokolovsky,Alexander W %A DeCost,Grace %A Aston,Elizabeth R %A Haass-Koffler,Carolina L %A Szapary,Claire %A Moyo,Patience %A Avila,Jaqueline C %A Tidey,Jennifer W %A Monti,Peter M %A Ahluwalia,Jasjit S %+ Department of Behavioral and Social Sciences, Brown University, Box G-S121-5, Providence, RI, 02912, United States, 1 4018633491, mollie_monnig@brown.edu %K SARS-CoV-2 %K novel coronavirus %K COVID-19 %K alcohol use %K alcohol drinking %K opioid use %K stimulant use %K nicotine %K smoking %K survey %K substance abuse %K addiction %K mental health %K pandemic %D 2021 %7 9.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Substance use is a risk factor for COVID-19 infection and adverse outcomes. However, reasons for elevated risk for COVID-19 in substance users are not well understood. Objective: The aim of this study was to evaluate whether alcohol or other drug use is associated with adherence to Centers for Disease Control and Prevention (CDC) guidelines for COVID-19 mitigation. Preregistered analyses tested the hypothesis that greater use of alcohol and other drugs would be associated with lower CDC guideline adherence. A secondary objective was to determine whether substance use was associated with the likelihood of COVID-19 testing or outcome. Methods: A cross-sectional web-based survey was administered to a convenience sample recruited through Amazon’s Mechanical Turk platform from June 18 to July 19, 2020. Individuals aged 18 years or older and residing in Connecticut, Massachusetts, New Jersey, New York, or Rhode Island were eligible to participate. The exposure of interest was past 7-day use of alcohol, cigarettes, electronic cigarettes, cannabis, stimulants, and nonmedical opioids. The primary outcome was CDC guideline adherence measured using a scale developed from behaviors advised to reduce the spread of COVID-19. Secondary outcomes were likelihood of COVID-19 testing and a positive COVID-19 test result. All analyses accounted for the sociodemographic characteristics. Results: The sample consisted of 1084 individuals (mean age 40.9 [SD 13.4] years): 529 (48.8%) men, 543 (50.1%) women, 12 (1.1%) other gender identity, 742 (68.5%) White individuals, 267 (24.6%) Black individuals, and 276 (25.5%) Hispanic individuals. Daily opioid users reported lower CDC guideline adherence than nondaily users (B=–0.24, 95% CI –0.44 to –0.05) and nonusers (B=–0.57, 95% CI –0.76 to –0.38). Daily alcohol drinkers reported lower adherence than nondaily drinkers (B=–0.16, 95% CI –0.30 to –0.02). Nondaily alcohol drinkers reported higher adherence than nondrinkers (B=0.10, 95% CI 0.02-0.17). Daily opioid use was related to greater odds of COVID-19 testing, and daily stimulant use was related to greater odds of a positive COVID-19 test. Conclusions: In a regionally-specific, racially, and ethnically diverse convenience sample, adults who engaged in daily alcohol or opioid use reported lower CDC guideline adherence for COVID-19 mitigation. Any opioid use was associated with greater odds of COVID-19 testing, and daily stimulant use was associated with greater odds of COVID-19 infection. Cigarettes, electronic cigarettes, cannabis, or stimulant use were not statistically associated with CDC guideline adherence, after accounting for sociodemographic covariates and other substance use variables. Findings support further investigation into whether COVID-19 testing and vaccination should be expanded among individuals with substance-related risk factors. %M 34591780 %R 10.2196/29319 %U https://publichealth.jmir.org/2021/11/e29319 %U https://doi.org/10.2196/29319 %U http://www.ncbi.nlm.nih.gov/pubmed/34591780 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e28317 %T Impact of the COVID-19 Pandemic on Objectively Measured Physical Activity and Sedentary Behavior Among Overweight Young Adults: Yearlong Longitudinal Analysis %A Lawhun Costello,Victoria %A Chevance,Guillaume %A Wing,David %A Mansour-Assi,Shadia J %A Sharp,Sydney %A Golaszewski,Natalie M %A Young,Elizabeth A %A Higgins,Michael %A Ibarra,Anahi %A Larsen,Britta %A Godino,Job G %+ Center for Wireless and Population Health Systems, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, United States, 1 8582463302, jobg@fhcsd.org %K COVID-19 %K young adults %K physical activity %K sedentary behavior %K activity monitor %K public health %K wearable %K activity monitors %K wrist worn %K sedentary %K lifestyle %K pandemic %D 2021 %7 24.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: The COVID-19 pandemic has impacted multiple aspects of daily living, including behaviors associated with occupation, transportation, and health. It is unclear how these changes to daily living have impacted physical activity and sedentary behavior. Objective: In this study, we add to the growing body of research on the health impact of the COVID-19 pandemic by examining longitudinal changes in objectively measured daily physical activity and sedentary behavior among overweight or obese young adults participating in an ongoing weight loss trial in San Diego, California. Methods: Data were collected from 315 overweight or obese (BMI: range 25.0-39.9 kg/m2) participants aged from 18 to 35 years between November 1, 2019, and October 30, 2020, by using the Fitbit Charge 3 (Fitbit LLC). After conducting strict filtering to find valid data on consistent wear (>10 hours per day for ≥250 days), data from 97 participants were analyzed to detect multiple structural changes in time series of physical activity and sedentary behavior. An algorithm was designed to detect multiple structural changes. This allowed for the automatic identification and dating of these changes in linear regression models with CIs. The number of breakpoints in regression models was estimated by using the Bayesian information criterion and residual sum of squares; the optimal segmentation corresponded to the lowest Bayesian information criterion and residual sum of squares. To quantify the changes in each outcome during the periods identified, linear mixed effects analyses were conducted. In terms of key demographic characteristics, the 97 participants included in our analyses did not differ from the 210 participants who were excluded. Results: After the initiation of the shelter-in-place order in California on March 19, 2021, there were significant decreases in step counts (−2872 steps per day; 95% CI −2734 to −3010), light physical activity times (−41.9 minutes; 95% CI −39.5 to −44.3), and moderate-to-vigorous physical activity times (−12.2 minutes; 95% CI −10.6 to −13.8), as well as significant increases in sedentary behavior times (+52.8 minutes; 95% CI 47.0-58.5). The decreases were greater than the expected declines observed during winter holidays, and as of October 30, 2020, they have not returned to the levels observed prior to the initiation of shelter-in-place orders. Conclusions: Among overweight or obese young adults, physical activity times decreased and sedentary behavior times increased concurrently with the implementation of COVID-19 mitigation strategies. The health conditions associated with a sedentary lifestyle may be additional, unintended results of the COVID-19 pandemic. %M 34665759 %R 10.2196/28317 %U https://publichealth.jmir.org/2021/11/e28317 %U https://doi.org/10.2196/28317 %U http://www.ncbi.nlm.nih.gov/pubmed/34665759 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e31635 %T Impact of the COVID-19 Pandemic on the Health Status and Behaviors of Adults in Korea: National Cross-sectional Web-Based Self-report Survey %A Kang,EunKyo %A Lee,Hyejin %A Sohn,Jee Hoon %A Yun,Jieun %A Lee,Jin Yong %A Hong,Yun-Chul %+ Department of Preventive Medicine, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea, 82 2 740 8394, ychong1@snu.ac.kr %K COVID-19 %K health status %K health behavior %K self-reported online survey %K pandemic %K epidemiology %K public health %K sociodemographic factors %K health interventions %K lockdown %D 2021 %7 26.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: The COVID-19 pandemic has radically shifted living practices, thereby influencing changes in the health status and behaviors of every person. Objective: The aim of this study was to investigate the impact of COVID-19 on the self-reported health status and health behaviors along with any associated factors in adults in the Republic of Korea wherein no stringent lockdown measures were implemented during the pandemic. Methods: We conducted a web-based self-reported survey from November 2020 to December 2020. The study participants (N=2097) were identified through quota sampling by age, sex, and geographical regions among residents aged 19 years or older in Korea. The survey collected information on basic demographics, changes in self-reported health status, and health behaviors during the COVID-19 pandemic. Self-reported health status and health behaviors were categorized into 3 groups: unchanged, improved, or worsened. A chi-square test and logistic regression analyses were conducted. Results: With regard to changes in the self-reported health status, the majority (1478/2097, 70.5%) of the participants reported that their health was unchanged, while 20% (420/2097) of the participants reported having worser health after the COVID-19 outbreak. With regard to changes in health behaviors, the proportion of participants who increased tobacco consumption was similar to that of those who decreased tobacco consumption (110/545, 20.2% vs 106/545, 19.5%, respectively), while the proportion of those who decreased their drinking frequency was more than twice as many as those who increased their drinking frequency (578/1603, 36.1% vs 270/1603, 16.8%, respectively). Further, those who decreased their exercising frequency were more than those who increased their exercising frequency (333/823, 15.9% vs 211/823, 10%, respectively). The factor that had the greatest influence on lifestyle was age. In the subgroup analysis, the group aged 20-29 years had the highest number of individuals with both a worsened (100/377, 26.5%) and an improved (218/377, 15.7%) health status. Further, individuals aged 20-29 years had greater odds of increased smoking (6.44, 95% CI 2.15-19.32), increased alcohol use (4.64, 95% CI 2.60-8.28), and decreased moderate or higher intensity aerobic exercise (3.39, 95% CI 1.82-6.33) compared to individuals aged 60 years and older. Younger adults showed deteriorated health behaviors, while older adults showed improved health behaviors. Conclusions: The health status and the behavior of the majority of the Koreans were not found to be heavily affected by the COVID-19 outbreak. However, in some cases, changes in health status or health behavior were identified. This study highlighted that some groups were overwhelmingly affected by COVID-19 compared to others. Certain groups reported experiencing both worsening and improving health, while other groups reported unchanged health status. Age was the most influential factor for behavior change; in particular, the younger generation’s negative health behaviors need more attention in terms of public health. As COVID-19 prolongs, public health interventions for vulnerable groups may be needed. %M 34653017 %R 10.2196/31635 %U https://publichealth.jmir.org/2021/11/e31635 %U https://doi.org/10.2196/31635 %U http://www.ncbi.nlm.nih.gov/pubmed/34653017 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e32936 %T The Impact of Public Health Events on COVID-19 Vaccine Hesitancy on Chinese Social Media: National Infoveillance Study %A Zhang,Zizheng %A Feng,Guanrui %A Xu,Jiahong %A Zhang,Yimin %A Li,Jinhui %A Huang,Jian %A Akinwunmi,Babatunde %A Zhang,Casper J P %A Ming,Wai-kit %+ Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, To Yuen Building, 31 To Yuen Street, Hong Kong, China (Hong Kong), 852 34426956, wkming2@cityu.edu.hk %K COVID-19 %K vaccine %K hesitancy %K social media %K China %K sentiment analysis %K infoveillance %K public health %K surveillance %K Weibo %K data mining %K sentiment %K attitude %D 2021 %7 9.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: The ongoing COVID-19 pandemic has brought unprecedented challenges to every country worldwide. A call for global vaccination for COVID-19 plays a pivotal role in the fight against this virus. With the development of COVID-19 vaccines, public willingness to get vaccinated has become an important public health concern, considering the vaccine hesitancy observed worldwide. Social media is powerful in monitoring public attitudes and assess the dissemination, which would provide valuable information for policy makers. Objective: This study aimed to investigate the responses of vaccine positivity on social media when major public events (major outbreaks) or major adverse events related to vaccination (COVID-19 or other similar vaccines) were reported. Methods: A total of 340,783 vaccine-related posts were captured with the poster’s information on Weibo, the largest social platform in China. After data cleaning, 156,223 posts were included in the subsequent analysis. Using pandas and SnowNLP Python libraries, posts were classified into 2 categories, positive and negative. After model training and sentiment analysis, the proportion of positive posts was computed to measure the public positivity toward the COVID-19 vaccine. Results: The positivity toward COVID-19 vaccines in China tends to fluctuate over time in the range of 45.7% to 77.0% and is intuitively correlated with public health events. In terms of gender, males were more positive (70.0% of the time) than females. In terms of region, when regional epidemics arose, not only the region with the epidemic and surrounding regions but also the whole country showed more positive attitudes to varying degrees. When the epidemic subsided temporarily, positivity decreased with varying degrees in each region. Conclusions: In China, public positivity toward COVID-19 vaccines fluctuates over time and a regional epidemic or news on social media may cause significant variations in willingness to accept a vaccine. Furthermore, public attitudes toward COVID-19 vaccination vary from gender and region. It is crucial for policy makers to adjust their policies through the use of positive incentives with prompt responses to pandemic-related news to promote vaccination acceptance. %M 34591782 %R 10.2196/32936 %U https://publichealth.jmir.org/2021/11/e32936 %U https://doi.org/10.2196/32936 %U http://www.ncbi.nlm.nih.gov/pubmed/34591782 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e30642 %T COVID-19 Vaccine Hesitancy on Social Media: Building a Public Twitter Data Set of Antivaccine Content, Vaccine Misinformation, and Conspiracies %A Muric,Goran %A Wu,Yusong %A Ferrara,Emilio %+ Information Sciences Institute, University of Southern California, 4676 Admiralty Way, Suite 1001, Marina del Rey, CA, 90292, United States, 1 213 740 2467, gmuric@isi.edu %K vaccine hesitancy %K COVID-19 vaccines %K dataset %K COVID-19 %K SARS-CoV-2 %K social media %K network analysis %K hesitancy %K vaccine %K Twitter %K misinformation %K conspiracy %K trust %K public health %K utilization %D 2021 %7 17.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: False claims about COVID-19 vaccines can undermine public trust in ongoing vaccination campaigns, posing a threat to global public health. Misinformation originating from various sources has been spreading on the web since the beginning of the COVID-19 pandemic. Antivaccine activists have also begun to use platforms such as Twitter to promote their views. To properly understand the phenomenon of vaccine hesitancy through the lens of social media, it is of great importance to gather the relevant data. Objective: In this paper, we describe a data set of Twitter posts and Twitter accounts that publicly exhibit a strong antivaccine stance. The data set is made available to the research community via our AvaxTweets data set GitHub repository. We characterize the collected accounts in terms of prominent hashtags, shared news sources, and most likely political leaning. Methods: We started the ongoing data collection on October 18, 2020, leveraging the Twitter streaming application programming interface (API) to follow a set of specific antivaccine-related keywords. Then, we collected the historical tweets of the set of accounts that engaged in spreading antivaccination narratives between October 2020 and December 2020, leveraging the Academic Track Twitter API. The political leaning of the accounts was estimated by measuring the political bias of the media outlets they shared. Results: We gathered two curated Twitter data collections and made them publicly available: (1) a streaming keyword–centered data collection with more than 1.8 million tweets, and (2) a historical account–level data collection with more than 135 million tweets. The accounts engaged in the antivaccination narratives lean to the right (conservative) direction of the political spectrum. The vaccine hesitancy is fueled by misinformation originating from websites with already questionable credibility. Conclusions: The vaccine-related misinformation on social media may exacerbate the levels of vaccine hesitancy, hampering progress toward vaccine-induced herd immunity, and could potentially increase the number of infections related to new COVID-19 variants. For these reasons, understanding vaccine hesitancy through the lens of social media is of paramount importance. Because data access is the first obstacle to attain this goal, we published a data set that can be used in studying antivaccine misinformation on social media and enable a better understanding of vaccine hesitancy. %M 34653016 %R 10.2196/30642 %U https://publichealth.jmir.org/2021/11/e30642 %U https://doi.org/10.2196/30642 %U http://www.ncbi.nlm.nih.gov/pubmed/34653016 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e29600 %T Characteristics of and User Engagement With Antivaping Posts on Instagram: Observational Study %A Gao,Yankun %A Xie,Zidian %A Sun,Li %A Xu,Chenliang %A Li,Dongmei %+ Department of Clinical & Translational Research, University of Rochester Medical Center, 265 Crittenden Boulevard CU 420708, Rochester, NY, 14642-0708, United States, 1 585 276 7285, Dongmei_Li@urmc.rochester.edu %K anti-vaping %K Instagram %K user engagement %K e-cigarettes %K vaping %K social media %K content analysis %K public health %K lung health %D 2021 %7 25.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Although government agencies acknowledge that messages about the adverse health effects of e-cigarette use should be promoted on social media, effectively delivering those health messages is challenging. Instagram is one of the most popular social media platforms among US youth and young adults, and it has been used to educate the public about the potential harm of vaping through antivaping posts. Objective: We aim to analyze the characteristics of and user engagement with antivaping posts on Instagram to inform future message development and information delivery. Methods: A total of 11,322 Instagram posts were collected from November 18, 2019, to January 2, 2020, by using antivaping hashtags including #novape, #novaping, #stopvaping, #dontvape, #antivaping, #quitvaping, #antivape, #stopjuuling, #dontvapeonthepizza, and #escapethevape. Among those posts, 1025 posts were randomly selected and 500 antivaping posts were further identified by hand coding. The image type, image content, and account type of antivaping posts were hand coded, the text information in the caption was explored by topic modeling, and the user engagement of each category was compared. Results: Analyses found that antivaping images of the educational/warning type were the most common (253/500; 50.6%). The average likes of the educational/warning type (15 likes/post) were significantly lower than the catchphrase image type (these emphasized a slogan such as “athletesdontvape” in the image; 32.5 likes/post; P<.001). The majority of the antivaping posts contained the image content element text (n=332, 66.4%), followed by the image content element people/person (n=110, 22%). The images containing people/person elements (32.8 likes/post) had more likes than the images containing other elements (13.8-21.1 likes/post). The captions of the antivaping Instagram posts covered topics including “lung health,” “teen vaping,” “stop vaping,” and “vaping death cases.” Among the 500 antivaping Instagram posts, while most posts were from the antivaping community (n=177, 35.4%) and personal account types (n=182, 36.4%), the antivaping community account type had the highest average number of posts (1.69 posts/account). However, there was no difference in the number of likes among different account types. Conclusions: Multiple features of antivaping Instagram posts may be related to user engagement and perception. This study identified the critical elements associated with high user engagement, which could be used to design antivaping posts to deliver health-related information more efficiently. %M 34842553 %R 10.2196/29600 %U https://publichealth.jmir.org/2021/11/e29600 %U https://doi.org/10.2196/29600 %U http://www.ncbi.nlm.nih.gov/pubmed/34842553 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e29020 %T Population Health Surveillance Using Mobile Phone Surveys in Low- and Middle-Income Countries: Methodology and Sample Representativeness of a Cross-sectional Survey of Live Poultry Exposure in Bangladesh %A Berry,Isha %A Mangtani,Punam %A Rahman,Mahbubur %A Khan,Iqbal Ansary %A Sarkar,Sudipta %A Naureen,Tanzila %A Greer,Amy L %A Morris,Shaun K %A Fisman,David N %A Flora,Meerjady Sabrina %+ Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, ON, M5T 3M7, Canada, 1 416 978 0901, isha.berry@mail.utoronto.ca %K mobile telephone survey %K health surveillance %K survey methodology %K Bangladesh %D 2021 %7 12.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Population-based health surveys are typically conducted using face-to-face household interviews in low- and middle-income countries (LMICs). However, telephone-based surveys are cheaper, faster, and can provide greater access to hard-to-reach or remote populations. The rapid growth in mobile phone ownership in LMICs provides a unique opportunity to implement novel data collection methods for population health surveys. Objective: This study aims to describe the development and population representativeness of a mobile phone survey measuring live poultry exposure in urban Bangladesh. Methods: A population-based, cross-sectional, mobile phone survey was conducted between September and November 2019 in North and South Dhaka City Corporations (DCC), Bangladesh, to measure live poultry exposure using a stratified probability sampling design. Data were collected using a computer-assisted telephone interview platform. The call operational data were summarized, and the participant data were weighted by age, sex, and education to the 2011 census. The demographic distribution of the weighted sample was compared with external sources to assess population representativeness. Results: A total of 5486 unique mobile phone numbers were dialed, with 1047 respondents completing the survey. The survey had an overall response rate of 52.2% (1047/2006) and a co-operation rate of 89.0% (1047/1176). Initial results comparing the sociodemographic profile of the survey sample to the census population showed that mobile phone sampling slightly underrepresented older individuals and overrepresented those with higher secondary education. After weighting, the demographic profile of the sample population matched well with the latest DCC census population profile. Conclusions: Probability-based mobile phone survey sampling and data collection methods produced a population-representative sample with minimal adjustment in DCC, Bangladesh. Mobile phone–based surveys can offer an efficient, economic, and robust way to conduct surveillance for population health outcomes, which has important implications for improving population health surveillance in LMICs. %M 34766914 %R 10.2196/29020 %U https://publichealth.jmir.org/2021/11/e29020 %U https://doi.org/10.2196/29020 %U http://www.ncbi.nlm.nih.gov/pubmed/34766914 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e32951 %T Digitization and Health in Germany: Cross-sectional Nationwide Survey %A De Santis,Karina Karolina %A Jahnel,Tina %A Sina,Elida %A Wienert,Julian %A Zeeb,Hajo %+ Department of Prevention and Evaluation, Leibniz Institute for Prevention Research and Epidemiology-BIPS, Achterstrasse 30, Bremen, 28359, Germany, 49 42121856 ext 908, desantis@leibniz-bips.de %K digital health %K literacy %K survey %K attitude %K usage %K eHEALS %K COVID-19 %K physical activity %K general population %K misinformation %D 2021 %7 22.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Digital technologies are shaping medicine and public health. Objective: The aim of this study was to investigate the attitudes toward and the use of digital technologies for health-related purposes using a nationwide survey. Methods: We performed a cross-sectional study using a panel sample of internet users selected from the general population living in Germany. Responses to a survey with 28 items were collected using computer-assisted telephone interviews conducted in October 2020. The items were divided into four topics: (1) general attitudes toward digitization, (2) COVID-19 pandemic, (3) physical activity, and (4) perceived digital health (eHealth) literacy measured with the eHealth Literacy Scale (eHEALS; sum score of 8=lowest to 40=highest perceived eHealth literacy). The data were analyzed in IBM-SPSS24 using relative frequencies. Three univariate multiple regression analyses (linear or binary logistic) were performed to investigate the associations among the sociodemographic factors (age, gender, education, and household income) and digital technology use. Results: The participants included 1014 internet users (n=528, 52.07% women) aged 14 to 93 years (mean 54, SD 17). Among all participants, 66.47% (674/1014) completed up to tertiary (primary and secondary) education and 45.07% (457/1017) reported a household income of up to 3500 Euro/month (1 Euro=US $1.18). Over half (579/1014, 57.10%) reported having used digital technologies for health-related purposes. The majority (898/1014, 88.56%) noted that digitization will be important for therapy and health care, in the future. Only 25.64% (260/1014) reported interest in smartphone apps for health promotion/prevention and 42.70% (433/1014) downloaded the COVID-19 contact-tracing app. Although 52.47% (532/1014) reported that they come across inaccurate digital information on the COVID-19 pandemic, 78.01% (791/1014) were confident in their ability to recognize such inaccurate information. Among those who use digital technologies for moderate physical activity (n=220), 187 (85.0%) found such technologies easy to use and 140 (63.6%) reported using them regularly (at least once a week). Although the perceived eHealth literacy was high (eHEALS mean score 31 points, SD 6), less than half (43.10%, 400/928) were confident in using digital information for health decisions. The use of digital technologies for health was associated with higher household income (odds ratio [OR] 1.28, 95% CI 1.11-1.47). The use of digital technologies for physical activity was associated with younger age (OR 0.95, 95% CI 0.94-0.96) and more education (OR 1.22, 95% CI 1.01-1.46). A higher perceived eHealth literacy score was associated with younger age (β=–.22, P<.001), higher household income (β=.21, P<.001), and more education (β=.14, P<.001). Conclusions: Internet users in Germany expect that digitization will affect preventive and therapeutic health care in the future. The facilitators and barriers associated with the use of digital technologies for health warrant further research. A gap exists between high confidence in the perceived ability to evaluate digital information and low trust in internet-based information on the COVID-19 pandemic and health decisions. %M 34813493 %R 10.2196/32951 %U https://publichealth.jmir.org/2021/11/e32951 %U https://doi.org/10.2196/32951 %U http://www.ncbi.nlm.nih.gov/pubmed/34813493 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e29970 %T Demographics Associated With Stress, Severe Mental Distress, and Anxiety Symptoms During the COVID-19 Pandemic in Japan: Nationwide Cross-sectional Web-Based Survey %A Midorikawa,Haruhiko %A Tachikawa,Hirokazu %A Taguchi,Takaya %A Shiratori,Yuki %A Takahashi,Asumi %A Takahashi,Sho %A Nemoto,Kiyotaka %A Arai,Tetsuaki %+ Department of Disaster and Community Psychiatry, University of Tsukuba, Igakukei Gakukeitou 873, 1-1-1 Tennoudai, Tsukuba, 305-8577, Japan, 81 29 853 3057, tachikawa@md.tsukuba.ac.jp %K COVID-19 %K mental health %K stress %K depression %K anxiety %K occupation %K public health %K demographic factors %K epidemiology %K occupational health %D 2021 %7 22.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: With the spread of COVID-19, the deterioration of public mental health has become a major global and social problem. Objective: The purpose of this study was to elucidate the relationship between the 3 mental health problems associated with COVID-19, that is, perceived stress, severe mental distress, and anxiety symptoms, and the various demographic factors, including occupation. Methods: A nationwide web-based questionnaire survey was conducted in Japan from August 4 to 31, 2020. In addition to sociodemographic data, the degrees of perceived stress, severe mental distress, and anxiety symptoms associated with COVID-19 were measured. After performing a descriptive statistical analysis, factors related to stress, severe mental distress, and anxiety symptoms were analyzed using logistic regression analysis. Results: A total of 8203 respondents submitted survey responses, among whom 34.9% (2861/8203) felt intense stress associated with COVID-19, 17.1% (1403/8203) were depressed, and 13.5% (1110/8203) had severe anxiety symptoms. The logistic regression analysis showed that each of the 3 mental health problems were prevalent in females, nonbinary gender, people in their 50s, 60s and older, respondents who visited psychiatrists, and those currently in psychiatric care. Severe mental distress and anxiety symptoms were associated with the number of effective lifestyle coping strategies during the lockdown period. Severe mental distress was only prevalent in teenagers and respondents in their 20s, as students tended to develop stress and severe mental distress. With regard to occupation, working in nursing care and welfare, education and research, and medical and health sectors was associated with stress; however, working in these occupations was not associated with severe mental distress and anxiety symptoms. Unemployment was associated with severe mental distress and anxiety symptoms. All 3 mental health problems were prevalent in part-time workers and those working in entertainment and arts sectors. Conclusions: Gender, age, occupation, history of psychiatric visits, and stress coping mechanisms were associated with mental health during the COVID-19 pandemic, but their associations with stress, severe mental distress, and anxiety symptoms differed. In addition, the actual state of mental health varied according to the respondents’ occupation. It is necessary to consider the impact of the COVID-19 pandemic on mental health not only at the individual level but also at the occupational level. %M 34653018 %R 10.2196/29970 %U https://publichealth.jmir.org/2021/11/e29970 %U https://doi.org/10.2196/29970 %U http://www.ncbi.nlm.nih.gov/pubmed/34653018 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e26660 %T Obesity-Related Communication in Digital Chinese News From Mainland China, Hong Kong, and Taiwan: Automated Content Analysis %A Chang,Angela %A Schulz,Peter Johannes %A Jiao,Wen %A Liu,Matthew Tingchi %+ Faculty of Social Sciences, University of Macau, E21 FSS Bldg, 2nd Fl., Taipa, 100, Macao, 853 88228991, wychang@um.edu.mo %K public health %K computational content %K digital research methods %K obesity discourse %K gene disorders %K noncommunicable disease %D 2021 %7 23.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: The fact that the number of individuals with obesity has increased worldwide calls into question media efforts for informing the public. This study attempts to determine the ways in which the mainstream digital news covers the etiology of obesity and diseases associated with the burden of obesity. Objective: The dual objectives of this study are to obtain an understanding of what the news reports on obesity and to explore meaning in data by extending the preconceived grounded theory. Methods: The 10 years of news text from 2010 to 2019 compared the development of obesity-related coverage and its potential impact on its perception in Mainland China, Hong Kong, and Taiwan. Digital news stories on obesity along with affliction and inferences in 9 Chinese mainstream newspapers were sampled. An automatic content analysis tool, DiVoMiner was proposed. This computer-aided platform is designed to organize and filter large sets of data on the basis of the patterns of word occurrence and term discovery. Another programming language, Python 3, was used to explore connections and patterns created by the aggregated interactions. Results: A total of 30,968 news stories were identified with increasing attention since 2016. The highest intensity of newspaper coverage of obesity communication was observed in Taiwan. Overall, a stronger focus on 2 shared causative attributes of obesity is on stress (n=4483, 33.0%) and tobacco use (n=3148, 23.2%). The burdens of obesity and cardiovascular diseases are implied to be the most, despite the aggregated interaction of edge centrality showing the highest link between the “cancer” and obesity. This study goes beyond traditional journalism studies by extending the framework of computational and customizable web-based text analysis. This could set a norm for researchers and practitioners who work on data projects largely for an innovative attempt. Conclusions: Similar to previous studies, the discourse between the obesity epidemic and personal afflictions is the most emphasized approach. Our study also indicates that the inclination of blaming personal attributes for health afflictions potentially limits social and governmental responsibility for addressing this issue. %M 34817383 %R 10.2196/26660 %U https://publichealth.jmir.org/2021/11/e26660 %U https://doi.org/10.2196/26660 %U http://www.ncbi.nlm.nih.gov/pubmed/34817383 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e26523 %T Novel Methods in the Surveillance of Influenza-Like Illness in Germany Using Data From a Symptom Assessment App (Ada): Observational Case Study %A Cawley,Caoimhe %A Bergey,François %A Mehl,Alicia %A Finckh,Ashlee %A Gilsdorf,Andreas %+ Ada Health GmbH, Karl-Liebknecht Strasse 1, Berlin, 10178, Germany, 49 17680765335, caoimhecawley@gmail.com %K ILI %K influenza %K syndromic surveillance %K participatory surveillance %K digital surveillance %K mobile phone %D 2021 %7 4.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Participatory epidemiology is an emerging field harnessing consumer data entries of symptoms. The free app Ada allows users to enter the symptoms they are experiencing and applies a probabilistic reasoning model to provide a list of possible causes for these symptoms. Objective: The objective of our study is to explore the potential contribution of Ada data to syndromic surveillance by comparing symptoms of influenza-like illness (ILI) entered by Ada users in Germany with data from a national population-based reporting system called GrippeWeb. Methods: We extracted data for all assessments performed by Ada users in Germany over 3 seasons (2017/18, 2018/19, and 2019/20) and identified those with ILI (report of fever with cough or sore throat). The weekly proportion of assessments in which ILI was reported was calculated (overall and stratified by age group), standardized for the German population, and compared with trends in ILI rates reported by GrippeWeb using time series graphs, scatterplots, and Pearson correlation coefficient. Results: In total, 2.1 million Ada assessments (for any symptoms) were included. Within seasons and across age groups, the Ada data broadly replicated trends in estimated weekly ILI rates when compared with GrippeWeb data (Pearson correlation—2017-18: r=0.86, 95% CI 0.76-0.92; P<.001; 2018-19: r=0.90, 95% CI 0.84-0.94; P<.001; 2019-20: r=0.64, 95% CI 0.44-0.78; P<.001). However, there were differences in the exact timing and nature of the epidemic curves between years. Conclusions: With careful interpretation, Ada data could contribute to identifying broad ILI trends in countries without existing population-based monitoring systems or to the syndromic surveillance of symptoms not covered by existing systems. %M 34734836 %R 10.2196/26523 %U https://publichealth.jmir.org/2021/11/e26523 %U https://doi.org/10.2196/26523 %U http://www.ncbi.nlm.nih.gov/pubmed/34734836 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e33576 %T Digital SARS-CoV-2 Detection Among Hospital Employees: Participatory Surveillance Study %A Leal-Neto,Onicio %A Egger,Thomas %A Schlegel,Matthias %A Flury,Domenica %A Sumer,Johannes %A Albrich,Werner %A Babouee Flury,Baharak %A Kuster,Stefan %A Vernazza,Pietro %A Kahlert,Christian %A Kohler,Philipp %+ Department of Economics, University of Zurich, Schönberggasse 1, Zurich, 8001, Switzerland, 41 783242116, onicio@gmail.com %K digital epidemiology %K SARS-CoV-2 %K COVID-19 %K health care workers %D 2021 %7 22.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: The implementation of novel techniques as a complement to traditional disease surveillance systems represents an additional opportunity for rapid analysis. Objective: The objective of this work is to describe a web-based participatory surveillance strategy among health care workers (HCWs) in two Swiss hospitals during the first wave of COVID-19. Methods: A prospective cohort of HCWs was recruited in March 2020 at the Cantonal Hospital of St. Gallen and the Eastern Switzerland Children’s Hospital. For data analysis, we used a combination of the following techniques: locally estimated scatterplot smoothing (LOESS) regression, Spearman correlation, anomaly detection, and random forest. Results: From March 23 to August 23, 2020, a total of 127,684 SMS text messages were sent, generating 90,414 valid reports among 1004 participants, achieving a weekly average of 4.5 (SD 1.9) reports per user. The symptom showing the strongest correlation with a positive polymerase chain reaction test result was loss of taste. Symptoms like red eyes or a runny nose were negatively associated with a positive test. The area under the receiver operating characteristic curve showed favorable performance of the classification tree, with an accuracy of 88% for the training data and 89% for the test data. Nevertheless, while the prediction matrix showed good specificity (80.0%), sensitivity was low (10.6%). Conclusions: Loss of taste was the symptom that was most aligned with COVID-19 activity at the population level. At the individual level—using machine learning–based random forest classification—reporting loss of taste and limb/muscle pain as well as the absence of runny nose and red eyes were the best predictors of COVID-19. %M 34727046 %R 10.2196/33576 %U https://publichealth.jmir.org/2021/11/e33576 %U https://doi.org/10.2196/33576 %U http://www.ncbi.nlm.nih.gov/pubmed/34727046 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e27385 %T Using Google Trends to Inform the Population Size Estimation and Spatial Distribution of Gay, Bisexual, and Other Men Who Have Sex With Men: Proof-of-concept Study %A Card,Kiffer G %A Lachowsky,Nathan J %A Hogg,Robert S %+ Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada, 1 2502131743, kiffercard@gmail.com %K gay, bisexual, and other men who have sex with men %K spatial distribution %K population size estimation %K pornography %K technology-aided surveillance %D 2021 %7 29.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: We must triangulate data sources to understand best the spatial distribution and population size of marginalized populations to empower public health leaders to address population-specific needs. Existing population size estimation techniques are difficult and limited. Objective: We sought to identify a passive surveillance strategy that utilizes internet and social media to enhance, validate, and triangulate population size estimates of gay, bisexual, and other men who have sex with men (gbMSM). Methods: We explored the Google Trends platform to approximate an estimate of the spatial heterogeneity of the population distribution of gbMSM. This was done by comparing the prevalence of the search term “gay porn” with that of the search term “porn.” Results: Our results suggested that most cities have a gbMSM population size between 2% and 4% of their total population, with large urban centers having higher estimates relative to rural or suburban areas. This represents nearly a double up of population size estimates compared to that found by other methods, which typically find that between 1% and 2% of the total population are gbMSM. We noted that our method was limited by unequal coverage in internet usage across Canada and differences in the frequency of porn use by gender and sexual orientation. Conclusions: We argue that Google Trends estimates may provide, for many public health planning purposes, adequate city-level estimates of gbMSM population size in regions with a high prevalence of internet access and for purposes in which a precise or narrow estimate of the population size is not required. Furthermore, the Google Trends platform does so in less than a minute at no cost, making it extremely timely and cost-effective relative to more precise (and complex) estimates. We also discuss future steps for further validation of this approach. %M 34618679 %R 10.2196/27385 %U https://publichealth.jmir.org/2021/11/e27385 %U https://doi.org/10.2196/27385 %U http://www.ncbi.nlm.nih.gov/pubmed/34618679 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e29504 %T Algorithm for Individual Prediction of COVID-19–Related Hospitalization Based on Symptoms: Development and Implementation Study %A Murtas,Rossella %A Morici,Nuccia %A Cogliati,Chiara %A Puoti,Massimo %A Omazzi,Barbara %A Bergamaschi,Walter %A Voza,Antonio %A Rovere Querini,Patrizia %A Stefanini,Giulio %A Manfredi,Maria Grazia %A Zocchi,Maria Teresa %A Mangiagalli,Andrea %A Brambilla,Carla Vittoria %A Bosio,Marco %A Corradin,Matteo %A Cortellaro,Francesca %A Trivelli,Marco %A Savonitto,Stefano %A Russo,Antonio Giampiero %+ Epidemiology Unit, Agency for the Protection of Health of the Metropolitan Area of Milan, Via Conca del Naviglio 45, Milan, 20123, Italy, 39 0285782111, agrusso@ats-milano.it %K COVID-19 %K severe outcome %K prediction %K monitoring system %K symptoms %K risk prediction %K risk %K algorithms %K prediction models %K pandemic %K digital data %K health records %D 2021 %7 15.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: The COVID-19 pandemic has placed a huge strain on the health care system globally. The metropolitan area of Milan, Italy, was one of the regions most impacted by the COVID-19 pandemic worldwide. Risk prediction models developed by combining administrative databases and basic clinical data are needed to stratify individual patient risk for public health purposes. Objective: This study aims to develop a stratification tool aimed at improving COVID-19 patient management and health care organization. Methods: A predictive algorithm was developed and applied to 36,834 patients with COVID-19 in Italy between March 8 and the October 9, 2020, in order to foresee their risk of hospitalization. Exposures considered were age, sex, comorbidities, and symptoms associated with COVID-19 (eg, vomiting, cough, fever, diarrhea, myalgia, asthenia, headache, anosmia, ageusia, and dyspnea). The outcome was hospitalizations and emergency department admissions for COVID-19. Discrimination and calibration of the model were also assessed. Results: The predictive model showed a good fit for predicting COVID-19 hospitalization (C-index 0.79) and a good overall prediction accuracy (Brier score 0.14). The model was well calibrated (intercept –0.0028, slope 0.9970). Based on these results, 118,804 patients diagnosed with COVID-19 from October 25 to December 11, 2020, were stratified into low, medium, and high risk for COVID-19 severity. Among the overall study population, 67,030 (56.42%) were classified as low-risk patients; 43,886 (36.94%), as medium-risk patients; and 7888 (6.64%), as high-risk patients. In all, 89.37% (106,179/118,804) of the overall study population was being assisted at home, 9% (10,695/118,804) was hospitalized, and 1.62% (1930/118,804) died. Among those assisted at home, most people (63,983/106,179, 60.26%) were classified as low risk, whereas only 3.63% (3858/106,179) were classified at high risk. According to ordinal logistic regression, the odds ratio (OR) of being hospitalized or dead was 5.0 (95% CI 4.6-5.4) among high-risk patients and 2.7 (95% CI 2.6-2.9) among medium-risk patients, as compared to low-risk patients. Conclusions: A simple monitoring system, based on primary care data sets linked to COVID-19 testing results, hospital admissions data, and death records may assist in the proper planning and allocation of patients and resources during the ongoing COVID-19 pandemic. %M 34543227 %R 10.2196/29504 %U https://publichealth.jmir.org/2021/11/e29504 %U https://doi.org/10.2196/29504 %U http://www.ncbi.nlm.nih.gov/pubmed/34543227 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e33509 %T Central COVID-19 Coordination Centers in Germany: Description, Economic Evaluation, and Systematic Review %A Schopow,Nikolas %A Osterhoff,Georg %A von Dercks,Nikolaus %A Girrbach,Felix %A Josten,Christoph %A Stehr,Sebastian %A Hepp,Pierre %+ Department for Orthopedics, Trauma Surgery and Plastic Surgery, University Hospital Leipzig, Liebigstr. 20, Leipzig, 04103, Germany, 49 341 9717849, schopow@medizin.uni-leipzig.de %K telemedical consultation %K patient allocation %K algorithm-based treatment %K telemedicine %K telehealth %K consultation %K allocation %K algorithm %K treatment %K COVID-19 %K coordination %K Germany %K economic %K review %K establishment %K management %D 2021 %7 18.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: During the COVID-19 pandemic, Central COVID-19 Coordination Centers (CCCCs) have been established at several hospitals across Germany with the intention to assist local health care professionals in efficiently referring patients with suspected or confirmed SARS-CoV-2 infection to regional hospitals and therefore to prevent the collapse of local health system structures. In addition, these centers coordinate interhospital transfers of patients with COVID-19 and provide or arrange specialized telemedical consultations. Objective: This study describes the establishment and management of a CCCC at a German university hospital. Methods: We performed economic analyses (cost, cost-effectiveness, use, and utility) according to the CHEERS (Consolidated Health Economic Evaluation Reporting Standards) criteria. Additionally, we conducted a systematic review to identify publications on similar institutions worldwide. The 2 months with the highest local incidence of COVID-19 cases (December 2020 and January 2021) were considered. Results: During this time, 17.3 requests per day were made to the CCCC regarding admission or transfer of patients with COVID-19. The majority of requests were made by emergency medical services (601/1068, 56.3%), patients with an average age of 71.8 (SD 17.2) years were involved, and for 737 of 1068 cases (69%), SARS-CoV-2 had already been detected by a positive polymerase chain reaction test. In 59.8% (639/1068) of the concerned patients, further treatment by a general practitioner or outpatient presentation in a hospital could be initiated after appropriate advice, 27.2% (291/1068) of patients were admitted to normal wards, and 12.9% (138/1068) were directly transmitted to an intensive care unit. The operating costs of the CCCC amounted to more than €52,000 (US $60,031) per month. Of the 334 patients with detected SARS-CoV-2 who were referred via EMS or outpatient physicians, 302 (90.4%) were triaged and announced in advance by the CCCC. No other published economic analysis of COVID-19 coordination or management institutions at hospitals could be found. Conclusions: Despite the high cost of the CCCC, we were able to show that it is a beneficial concept to both the providing hospital and the public health system. However, the most important benefits of the CCCC are that it prevents hospitals from being overrun by patients and that it avoids situations in which physicians must weigh one patient’s life against another’s. %M 34623955 %R 10.2196/33509 %U https://publichealth.jmir.org/2021/11/e33509 %U https://doi.org/10.2196/33509 %U http://www.ncbi.nlm.nih.gov/pubmed/34623955 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e25897 %T Online Newspaper Reports on Ambulance Accidents in Austria, Germany, and Switzerland: Retrospective Cross-sectional Review %A Boldt,Johanna %A Steinfort,Femke %A Müller,Martin %A Exadaktylos,Aristomenis K %A Klukowska-Roetzler,Jolanta %+ Department of Emergency Medicine, Inselspital, Bern University Hospital, Bern University, Freiburgerstrasse 16C, Berne, 3010, Switzerland, 41 31 632 33 96, jolanta.klukowska-roetzler@insel.ch %K ambulance accidents %K ambulance collisions %K ambulance crashes %K media-based %K media-based review %K newspaper review %K Austria %K Germany %K Switzerland %K German-speaking European countries %K retrospective %K cross-sectional %K review %K ambulance %K accident %K data %K media %K newspaper %D 2021 %7 12.11.2021 %9 Review %J JMIR Public Health Surveill %G English %X Background: Ambulance accidents are an unfortunate indirect result of ambulance emergency calls, which create hazardous environments for personnel, patients, and bystanders. However, in European German-speaking countries, factors contributing to ambulance accidents have not been optimally researched and analyzed. Objective: The objective of this study was to extract, analyze, and compare data from online newspaper articles on ambulance accidents for Austria, Germany, and Switzerland. We hope to highlight future strategies to offset the deficit in research data and official registers for prevention of ambulance and emergency vehicle accidents. Methods: Ambulance accident data were collected from Austrian, German, and Swiss free web-based daily newspapers, as listed in Wikipedia, for the period between January 2014 and January 2019. All included newspapers were searched for articles reporting ambulance accidents using German terms representing “ambulance” and “ambulance accident.” Characteristics of the accidents were compiled and analyzed. Only ground ambulance accidents were covered. Results: In Germany, a total of 597 ambulance accidents were recorded, corresponding to 0.719 (95% CI 0.663-0.779) per 100,000 inhabitants; 453 of these accidents left 1170 people injured, corresponding to 1.409 (95% CI 1.330-1.492) per 100,000 inhabitants, and 28 of these accidents caused 31 fatalities, corresponding to 0.037 (95% CI 0.025-0.053) per 100,000 inhabitants. In Austria, a total of 62 ambulance accidents were recorded, corresponding to 0.698 (95% CI 0.535-0.894) per 100,000 inhabitants; 47 of these accidents left 115 people injured, corresponding to 1.294 (95% CI 1.068-1.553) per 100,000 inhabitants, and 6 of these accidents caused 7 fatalities, corresponding to 0.079 (95% CI 0.032-0.162) per 100,000 inhabitants. In Switzerland, a total of 25 ambulance accidents were recorded, corresponding to 0.293 (95% CI 0.189-0.432) per 100,000 inhabitants; 11 of these accidents left 18 people injured, corresponding to 0.211(95% CI 0.113-0.308) per 100,000 inhabitants. There were no fatalities. In each of the three countries, the majority of the accidents involved another car (77%-81%). In Germany and Switzerland, most accidents occurred at an intersection. In Germany, Austria, and Switzerland, 38.7%, 26%, and 4%, respectively, of ambulance accidents occurred at intersections for which the ambulance had a red light (P<.001). In all three countries, most of the casualties were staff and not uncommonly a third party. Most accidents took place on weekdays and during the daytime. Ambulance accidents were evenly distributed across the four seasons. The direction of travel was reported in 28%-37% of the accidents and the patient was in the ambulance approximately 50% of the time in all countries. The cause of the ambulance accidents was reported to be the ambulance itself in 125 (48.1% of accidents where the cause was reported), 22 (42%), and 8 (40%) accidents in Germany, Austria, and Switzerland, respectively (P=.02), and another vehicle in 118 (45.4%), 29 (56%), and 9 (45%) accidents, respectively (P<.001). A total of 292 accidents occurred while blue lights and sirens were used, which caused 3 deaths and 577 injuries. Conclusions: This study draws attention to much needed auxiliary sources of data that may allow for creation of a contemporary registry of all ambulance accidents in Austria, Germany, and Switzerland. To improve risk management and set European standards, it should be mandatory to collect standardized goal-directed and representative information using various sources (including the wide range presented by the press and social media), which should then be made available for audit, analysis, and research. %M 34766915 %R 10.2196/25897 %U https://publichealth.jmir.org/2021/11/e25897 %U https://doi.org/10.2196/25897 %U http://www.ncbi.nlm.nih.gov/pubmed/34766915 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e33022 %T Investigating Unhealthy Alcohol Use As an Independent Risk Factor for Increased COVID-19 Disease Severity: Observational Cross-sectional Study %A Bhalla,Sameer %A Sharma,Brihat %A Smith,Dale %A Boley,Randy %A McCluskey,Connor %A Ilyas,Yousaf %A Afshar,Majid %A Balk,Robert %A Karnik,Niranjan %A Keshavarzian,Ali %+ Center for Circadian Rhythm and Alcohol-Induced Tissue Injury, Rush University Medical Center, 1725 W Harrison St, Chicago, IL, United States, 1 (312) 942 5861, Ali_Keshavarzian@rush.edu %K unhealthy alcohol use %K COVID-19 %K SARS-CoV-2 %K acute respiratory distress syndrome %K substance misuse %K mechanical ventilation %K substance use %D 2021 %7 5.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Unhealthy alcohol use (UAU) is known to disrupt pulmonary immune mechanisms and increase the risk of acute respiratory distress syndrome in patients with pneumonia; however, little is known about the effects of UAU on outcomes in patients with COVID-19 pneumonia. To our knowledge, this is the first observational cross-sectional study that aims to understand the effect of UAU on the severity of COVID-19. Objective: We aim to determine if UAU is associated with more severe clinical presentation and worse health outcomes related to COVID-19 and if socioeconomic status, smoking, age, BMI, race/ethnicity, and pattern of alcohol use modify the risk. Methods: In this observational cross-sectional study that took place between January 1, 2020, and December 31, 2020, we ran a digital machine learning classifier on the electronic health record of patients who tested positive for SARS-CoV-2 via nasopharyngeal swab or had two COVID-19 International Classification of Disease, 10th Revision (ICD-10) codes to identify patients with UAU. After controlling for age, sex, ethnicity, BMI, smoking status, insurance status, and presence of ICD-10 codes for cancer, cardiovascular disease, and diabetes, we then performed a multivariable regression to examine the relationship between UAU and COVID-19 severity as measured by hospital care level (ie, emergency department admission, emergency department admission with ventilator, or death). We used a predefined cutoff with optimal sensitivity and specificity on the digital classifier to compare disease severity in patients with and without UAU. Models were adjusted for age, sex, race/ethnicity, BMI, smoking status, and insurance status. Results: Each incremental increase in the predicted probability from the digital alcohol classifier was associated with a greater odds risk for more severe COVID-19 disease (odds ratio 1.15, 95% CI 1.10-1.20). We found that patients in the unhealthy alcohol group had a greater odds risk to develop more severe disease (odds ratio 1.89, 95% CI 1.17-3.06), suggesting that UAU was associated with an 89% increase in the odds of being in a higher severity category. Conclusions: In patients infected with SARS-CoV-2, UAU is an independent risk factor associated with greater disease severity and/or death. %M 34665758 %R 10.2196/33022 %U https://publichealth.jmir.org/2021/11/e33022 %U https://doi.org/10.2196/33022 %U http://www.ncbi.nlm.nih.gov/pubmed/34665758 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e30462 %T The Influence of Normative Perceptions on the Uptake of the COVID-19 TraceTogether Digital Contact Tracing System: Cross-sectional Study %A Lee,Jeong Kyu %A Lin,Lavinia %A Kang,Hyunjin %+ Saw Swee Hock School of Public Health, National University of Singapore, Tahir Foundation Building, 12 Science Drive 2, 10-01, Singapore, 117549, Singapore, 65 66015838, lee.jeongkyu@gmail.com %K COVID-19 %K social norms %K TraceTogether %K Singapore %K contact tracing %K mobile app %K token %D 2021 %7 12.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: In 2020, the Singapore government rolled out the TraceTogether program, a digital system to facilitate contact tracing efforts in response to the COVID-19 pandemic. This system is available as a smartphone app and Bluetooth-enabled token to help identify close contacts. As of February 1, 2021, more than 80% of the population has either downloaded the mobile app or received the token in Singapore. Despite the high adoption rate of the TraceTogether mobile app and token (ie, device), it is crucial to understand the role of social and normative perceptions in uptake and usage by the public, given the collective efforts for contact tracing. Objective: This study aimed to examine normative influences (descriptive and injunctive norms) on TraceTogether device use for contact tracing purposes, informed by the theory of normative social behavior, a theoretical framework to explain how perceived social norms are related to behaviors. Methods: From January to February 2021, cross-sectional data were collected by a local research company through emailing their panel members who were (1) Singapore citizens or permanent residents aged 21 years or above; (2) able to read English; and (3) internet users with access to a personal email account. The study sample (n=1137) was restricted to those who had either downloaded the TraceTogether mobile app or received the token. Results: Multivariate (linear and ordinal logistic) regression analyses were carried out to assess the relationships of the behavioral outcome variables (TraceTogether device usage and intention of TraceTogether device usage) with potential correlates, including perceived social norms, perceived community, and interpersonal communication. Multivariate regression analyses indicated that descriptive norms (unstandardized regression coefficient β=0.31, SE=0.05; P<.001) and injunctive norms (unstandardized regression coefficient β=0.16, SE=0.04; P<.001) were significantly positively associated with the intention to use the TraceTogether device. It was also found that descriptive norms were a significant correlate of TraceTogether device use frequency (adjusted odds ratio [aOR] 2.08, 95% CI 1.66-2.61; P<.001). Though not significantly related to TraceTogether device use frequency, injunctive norms moderated the relationship between descriptive norms and the outcome variable (aOR 1.12, 95% CI 1.03-1.21; P=.005). Conclusions: This study provides useful implications for the design of effective intervention strategies to promote the uptake and usage of digital methods for contact tracing in a multiethnic Asian population. Our findings highlight that influence from social networks plays an important role in developing normative perceptions in relation to TraceTogether device use for contact tracing. To promote the uptake of the TraceTogether device and other preventive behaviors for COVID-19, it would be useful to devise norm-based interventions that address these normative perceptions by presenting high prevalence and approval of important social referents, such as family and close friends. %M 34623956 %R 10.2196/30462 %U https://publichealth.jmir.org/2021/11/e30462 %U https://doi.org/10.2196/30462 %U http://www.ncbi.nlm.nih.gov/pubmed/34623956 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e30968 %T Characterization of Unlinked Cases of COVID-19 and Implications for Contact Tracing Measures: Retrospective Analysis of Surveillance Data %A Chong,Ka Chun %A Jia,Katherine %A Lee,Shui Shan %A Hung,Chi Tim %A Wong,Ngai Sze %A Lai,Francisco Tsz Tsun %A Chau,Nancy %A Yam,Carrie Ho Kwan %A Chow,Tsz Yu %A Wei,Yuchen %A Guo,Zihao %A Yeoh,Eng Kiong %+ Centre for Health Systems and Policy Research, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Central Avenue, Hong Kong, Hong Kong, 852 22528716, yeoh_ek@cuhk.edu.hk %K COVID-19 %K contact tracing %K unlinked %K superspreading %K dispersion %K surveillance %K monitoring %K digital health %K testing %K transmission %K epidemiology %K outbreak %K spread %D 2021 %7 16.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Contact tracing and intensive testing programs are essential for controlling the spread of COVID-19. However, conventional contact tracing is resource intensive and may not result in the tracing of all cases due to recall bias and cases not knowing the identity of some close contacts. Few studies have reported the epidemiological features of cases not identified by contact tracing (“unlinked cases”) or described their potential roles in seeding community outbreaks. Objective: For this study, we characterized the role of unlinked cases in the epidemic by comparing their epidemiological profile with the linked cases; we also estimated their transmission potential across different settings. Methods: We obtained rapid surveillance data from the government, which contained the line listing of COVID-19 confirmed cases during the first three waves in Hong Kong. We compared the demographics, history of chronic illnesses, epidemiological characteristics, clinical characteristics, and outcomes of linked and unlinked cases. Transmission potentials in different settings were assessed by fitting a negative binomial distribution to the observed offspring distribution. Results: Time interval from illness onset to hospital admission was longer among unlinked cases than linked cases (median 5.00 days versus 3.78 days; P<.001), with a higher proportion of cases whose condition was critical or serious (13.0% versus 8.2%; P<.001). The proportion of unlinked cases was associated with an increase in the weekly number of local cases (P=.049). Cluster transmissions from the unlinked cases were most frequently identified in household settings, followed by eateries and workplaces, with the estimated probability of cluster transmissions being around 0.4 for households and 0.1-0.3 for the latter two settings. Conclusions: The unlinked cases were positively associated with time to hospital admission, severity of infection, and epidemic size—implying a need to design and implement digital tracing methods to complement current conventional testing and tracing. To minimize the risk of cluster transmissions from unlinked cases, digital tracing approaches should be effectively applied in high-risk socioeconomic settings, and risk assessments should be conducted to review and adjust the policies. %M 34591778 %R 10.2196/30968 %U https://publichealth.jmir.org/2021/11/e30968 %U https://doi.org/10.2196/30968 %U http://www.ncbi.nlm.nih.gov/pubmed/34591778 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e32639 %T Public Health Surveillance Systems in the Eastern Mediterranean Region: Bibliometric Analysis of Scientific Literature %A Saad,Randa K %A Al Nsour,Mohannad %A Khader,Yousef %A Al Gunaid,Magid %+ Global Health Development|Eastern Mediterranean Public Health Network, Abdallah Ben Abbas St, Building No. 42, Amman, Jordan, 962 781665060, randaksaad@gmail.com %K public health %K surveillance %K Eastern Mediterranean Region %K bibliometric analysis %K literature %K research %K review %D 2021 %7 1.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: The Eastern Mediterranean Region (EMR) hosts some of the world’s worst humanitarian and health crises. The implementation of health surveillance in this region has faced multiple constraints. New and novel approaches in surveillance are in a constant state of high and immediate demand. Identifying the existing literature on surveillance helps foster an understanding of scientific development and thus potentially supports future development directions. Objective: This study aims to illustrate the scientific production, quantify the scholarly impact, and highlight the characteristics of publications on public health surveillance in the EMR over the past decade. Methods: We performed a Scopus search using keywords related to public health surveillance or its disciplines, cross-referenced with EMR countries, from 2011 to July 2021. Data were exported and analyzed using Microsoft Excel and Visualization of Similarities Viewer. Quality of journals was determined using SCImago Journal Rank and CiteScore. Results: We retrieved 1987 documents, of which 1927 (96.98%) were articles or reviews. There has been an incremental increase in the number of publications (exponential growth, R2=0.80) over the past decade. Publications were mostly affiliated with Iran (501/1987, 25.21%), the United States (468/1987, 23.55%), Pakistan (243/1987, 12.23%), Egypt (224/1987, 11.27%), and Saudi Arabia (209/1987, 10.52%). However, Iran only had links with 40 other countries (total link strength 164), and the biggest collaborator from the EMR was Egypt, with 67 links (total link strength 402). Within the other EMR countries, only Morocco, Lebanon, and Jordan produced ≥79 publications in the 10-year period. Most publications (1551/1987, 78.06%) were affiliated with EMR universities. Most journals were categorized as medical journals, and the highest number of articles were published in the Eastern Mediterranean Health Journal (SCImago Journal Rank 0.442; CiteScore 1.5). Retrieved documents had an average of 18.4 (SD 125.5) citations per document and an h-index of 66. The top-3 most cited documents were from the Global Burden of Diseases study. We found 70 high-frequency terms, occurring ≥10 times in author keywords, connected in 3 clusters. COVID-19, SARS-CoV-2, and pandemic represented the most recent 2020 cluster. Conclusions: This is the first research study to quantify the published literature on public health surveillance and its disciplines in the EMR. Research productivity has steadily increased over the past decade, and Iran has been the leading country publishing relevant research. Recurrent recent surveillance themes included COVID-19 and SARS-CoV-2. This study also sheds light on the gaps in surveillance research in the EMR, including inadequate publications on noncommunicable diseases and injury-related surveillance. %M 34723831 %R 10.2196/32639 %U https://publichealth.jmir.org/2021/11/e32639 %U https://doi.org/10.2196/32639 %U http://www.ncbi.nlm.nih.gov/pubmed/34723831 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e29789 %T Examining the Utility of Social Media in COVID-19 Vaccination: Unsupervised Learning of 672,133 Twitter Posts %A Liew,Tau Ming %A Lee,Cia Sin %+ Department of Psychiatry, Singapore General Hospital, Outram Road, Singapore, 169608, Singapore, 65 62223322, liew.tau.ming@singhealth.com.sg %K social media %K COVID-19 %K vaccine hesitancy %K natural language processing %K machine learning %K infodemiology %D 2021 %7 3.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Although COVID-19 vaccines have recently become available, efforts in global mass vaccination can be hampered by the widespread issue of vaccine hesitancy. Objective: The aim of this study was to use social media data to capture close-to-real-time public perspectives and sentiments regarding COVID-19 vaccines, with the intention to understand the key issues that have captured public attention, as well as the barriers and facilitators to successful COVID-19 vaccination. Methods: Twitter was searched for tweets related to “COVID-19” and “vaccine” over an 11-week period after November 18, 2020, following a press release regarding the first effective vaccine. An unsupervised machine learning approach (ie, structural topic modeling) was used to identify topics from tweets, with each topic further grouped into themes using manually conducted thematic analysis as well as guided by the theoretical framework of the COM-B (capability, opportunity, and motivation components of behavior) model. Sentiment analysis of the tweets was also performed using the rule-based machine learning model VADER (Valence Aware Dictionary and Sentiment Reasoner). Results: Tweets related to COVID-19 vaccines were posted by individuals around the world (N=672,133). Six overarching themes were identified: (1) emotional reactions related to COVID-19 vaccines (19.3%), (2) public concerns related to COVID-19 vaccines (19.6%), (3) discussions about news items related to COVID-19 vaccines (13.3%), (4) public health communications about COVID-19 vaccines (10.3%), (5) discussions about approaches to COVID-19 vaccination drives (17.1%), and (6) discussions about the distribution of COVID-19 vaccines (20.3%). Tweets with negative sentiments largely fell within the themes of emotional reactions and public concerns related to COVID-19 vaccines. Tweets related to facilitators of vaccination showed temporal variations over time, while tweets related to barriers remained largely constant throughout the study period. Conclusions: The findings from this study may facilitate the formulation of comprehensive strategies to improve COVID-19 vaccine uptake; they highlight the key processes that require attention in the planning of COVID-19 vaccination and provide feedback on evolving barriers and facilitators in ongoing vaccination drives to allow for further policy tweaks. The findings also illustrate three key roles of social media in COVID-19 vaccination, as follows: surveillance and monitoring, a communication platform, and evaluation of government responses. %M 34583316 %R 10.2196/29789 %U https://publichealth.jmir.org/2021/11/e29789 %U https://doi.org/10.2196/29789 %U http://www.ncbi.nlm.nih.gov/pubmed/34583316 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 11 %P e31707 %T Multilevel Determinants of COVID-19 Vaccine Uptake Among South Asian Ethnic Minorities in Hong Kong: Cross-sectional Web-Based Survey %A Singh,Akansha %A Lai,Angel Hor Yan %A Wang,Jingxuan %A Asim,Saba %A Chan,Paul Shing-Fong %A Wang,Zixin %A Yeoh,Eng Kiong %+ Centre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Room 508, School of Public Health, Prince of Wales Hospital, Shatin, N.T., Hong Kong, 666888, China (Hong Kong), 852 22528740, wangzx@cuhk.edu.hk %K COVID-19 %K South Asian ethnic minorities %K COVID-19 vaccination %K uptake %K cultural and religious reasons for vaccine hesitancy %K perceptions %K information exposure on social media %K influence of peers %K socioecological model %K Hong Kong %D 2021 %7 9.11.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: The 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. Objective: This 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. Methods: A 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. Results: Among 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). Conclusions: In 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. %M 34653014 %R 10.2196/31707 %U https://publichealth.jmir.org/2021/11/e31707 %U https://doi.org/10.2196/31707 %U http://www.ncbi.nlm.nih.gov/pubmed/34653014