TY - JOUR AU - Sloan, Robert AU - Visentini-Scarzanella, Marco AU - Sawada, Susumu AU - Sui, Xuemei AU - Myers, Jonathan PY - 2022/7/6 TI - Estimating Cardiorespiratory Fitness Without Exercise Testing or Physical Activity Status in Healthy Adults: Regression Model Development and Validation JO - JMIR Public Health Surveill SP - e34717 VL - 8 IS - 7 KW - nonexercise estimated cardiorespiratory fitness KW - public health KW - surveillance KW - epidemiology KW - electronic health record KW - EHR KW - fitness KW - cardiorespiratory KW - physical activity KW - regression model KW - nonexercise equation N2 - Background: Low cardiorespiratory fitness (CRF) is an independent predictor of morbidity and mortality. Most health care settings use some type of electronic health record (EHR) system. However, many EHRs do not have CRF or physical activity data collected, thereby limiting the types of investigations and analyses that can be done. Objective: This study aims to develop a nonexercise equation to estimate and classify CRF (in metabolic equivalent tasks) using variables commonly available in EHRs. Methods: Participants were 42,676 healthy adults (female participants: n=9146, 21.4%) from the Aerobics Center Longitudinal Study examined from 1974 to 2005. The nonexercise estimated CRF was based on sex, age, measured BMI, measured resting heart rate, measured resting blood pressure, and smoking status. A maximal treadmill test measured CRF. Results: After conducting nonlinear feature augmentation, separate linear regression models were used for male and female participants to calculate correlation and regression coefficients. Cross-classification of actual and estimated CRF was performed using low CRF categories (lowest quintile, lowest quartile, and lowest tertile). The multiple correlation coefficient (R) was 0.70 (mean deviation 1.33) for male participants and 0.65 (mean deviation 1.23) for female participants. The models explained 48.4% (SE estimate 1.70) and 41.9% (SE estimate 1.56) of the variance in CRF for male and female participants, respectively. Correct category classification for low CRF (lowest tertile) was found in 77.2% (n=25,885) of male participants and 74.9% (n=6,850) of female participants. Conclusions: The regression models developed in this study provided useful estimation and classification of CRF in a large population of male and female participants. The models may provide a practical method for estimating CRF derived from EHRs for population health research. UR - https://publichealth.jmir.org/2022/7/e34717 UR - http://dx.doi.org/10.2196/34717 UR - http://www.ncbi.nlm.nih.gov/pubmed/35793133 ID - info:doi/10.2196/34717 ER - TY - JOUR AU - Tay, Wesley AU - Quek, Rina AU - Kaur, Bhupinder AU - Lim, Joseph AU - Henry, Jeyakumar Christiani PY - 2022/7/18 TI - Use of Facial Morphology to Determine Nutritional Status in Older Adults: Opportunities and Challenges JO - JMIR Public Health Surveill SP - e33478 VL - 8 IS - 7 KW - malnutrition KW - facial recognition KW - facial morphology KW - telemonitoring KW - 3D scans KW - digital health KW - digital nutrition KW - public health nutrition KW - mobile phone UR - https://publichealth.jmir.org/2022/7/e33478 UR - http://dx.doi.org/10.2196/33478 UR - http://www.ncbi.nlm.nih.gov/pubmed/35849429 ID - info:doi/10.2196/33478 ER - TY - JOUR AU - Francombe, Joseph AU - Ali, Gemma-Claire AU - Gloinson, Ryen Emily AU - Feijao, Carolina AU - Morley, I. Katherine AU - Gunashekar, Salil AU - de Carvalho Gomes, Helena PY - 2022/7/6 TI - Assessing the Implementation of Digital Innovations in Response to the COVID-19 Pandemic to Address Key Public Health Functions: Scoping Review of Academic and Nonacademic Literature JO - JMIR Public Health Surveill SP - e34605 VL - 8 IS - 7 KW - digital technologies KW - COVID-19 KW - key public health functions KW - scoping review KW - digital health KW - pandemic KW - surveillance KW - mobile phone N2 - Background: Digital technologies have been central to efforts to respond to the COVID-19 pandemic. In this context, a range of literature has reported on developments regarding the implementation of new digital technologies for COVID-19?related surveillance, prevention, and control. Objective: In this study, scoping reviews of academic and nonacademic literature were undertaken to obtain an overview of the evidence regarding digital innovations implemented to address key public health functions in the context of the COVID-19 pandemic. This study aimed to expand on the work of existing reviews by drawing on additional data sources (including nonacademic sources) by considering literature published over a longer time frame and analyzing data in terms of the number of unique digital innovations. Methods: We conducted a scoping review of the academic literature published between January 1, 2020, and September 15, 2020, supplemented by a further scoping review of selected nonacademic literature published between January 1, 2020, and October 13, 2020. Both reviews followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach. Results: A total of 226 academic articles and 406 nonacademic articles were included. The included articles provided evidence of 561 (academic literature) and 497 (nonacademic literature) unique digital innovations. The most common implementation settings for digital innovations were the United States, China, India, and the United Kingdom. Technologies most commonly used by digital innovations were those belonging to the high-level technology group of integrated and ubiquitous fixed and mobile networks. The key public health functions most commonly addressed by digital innovations were communication and collaboration and surveillance and monitoring. Conclusions: Digital innovations implemented in response to the COVID-19 pandemic have been wide ranging in terms of their implementation settings, the digital technologies used, and the public health functions addressed. However, evidence gathered through this study also points to a range of barriers that have affected the successful implementation of digital technologies for public health functions. It is also evident that many digital innovations implemented in response to the COVID-19 pandemic are yet to be formally evaluated or assessed. UR - https://publichealth.jmir.org/2022/7/e34605 UR - http://dx.doi.org/10.2196/34605 UR - http://www.ncbi.nlm.nih.gov/pubmed/35605152 ID - info:doi/10.2196/34605 ER - TY - JOUR AU - Fu, Leiwen AU - Tian, Tian AU - Yao, Kai AU - Chen, Xiang-Feng AU - Luo, Ganfeng AU - Gao, Yanxiao AU - Lin, Yi-Fan AU - Wang, Bingyi AU - Sun, Yinghui AU - Zheng, Weiran AU - Li, Peiyang AU - Zhan, Yuewei AU - Fairley, K. Christopher AU - Grulich, Andrew AU - Zou, Huachun PY - 2022/7/6 TI - Global Pattern and Trends in Penile Cancer Incidence: Population-Based Study JO - JMIR Public Health Surveill SP - e34874 VL - 8 IS - 7 KW - global burden KW - penile cancer KW - incidence KW - average annual percentage change KW - epidemiology N2 - Background: Penile cancer is a relatively rare genital malignancy whose incidence and mortality are rising in many countries. Objective: This study aims to assess the recent incidence and mortality patterns and incidence trends of penile cancer. Methods: The age-standardized incidence and mortality rates (ASIR and ASMR, respectively) of penile cancer in 2020 were estimated from the Global Cancer Registries (GLOBOCAN) database. Incidence trends of penile cancer from 1973 to 2012 were assessed in 44 populations from 43 countries using the Cancer Incidence in Five Continents plus (CI5plus) and the Nordic Cancer Registries (NORDCAN) databases. Average annual percentage change was calculated to quantify trends in ASIR using joinpoint regression. Results: Globally, the estimated ASIR and ASMR of penile cancer were 0.80 (per 100,000) and 0.29 (per 100,000) in 2020, equating to 36,068 new cases and 13,211 deaths in 2020, respectively. There was no significant correlation between the ASIR (P=.05) or ASMR (P=.90) and Human Development Index. In addition, 15 countries saw increasing ASIR for penile cancer, 13 of which were from Europe (United Kingdom, Lithuania, Norway, Estonia, Finland, Sweden, Cyprus, Netherlands, Italy, Croatia, Slovakia, Russia, and the Czech), and 2 from Asia (China and Israel). Conclusions: Although the developing countries still bear the higher incidence and mortality of penile cancer, the incidence is on the rise in most European countries. To mitigate the disease burden resulting from penile cancer, measures to lower the risk for penile cancers, including improving penile hygiene and male human papillomavirus vaccination, may be warranted. UR - https://publichealth.jmir.org/2022/7/e34874 UR - http://dx.doi.org/10.2196/34874 UR - http://www.ncbi.nlm.nih.gov/pubmed/35793140 ID - info:doi/10.2196/34874 ER - TY - JOUR AU - Chang, Yung-Chun AU - Chiu, Yu-Wen AU - Chuang, Ting-Wu PY - 2022/7/13 TI - Linguistic Pattern?Infused Dual-Channel Bidirectional Long Short-term Memory With Attention for Dengue Case Summary Generation From the Program for Monitoring Emerging Diseases?Mail Database: Algorithm Development Study JO - JMIR Public Health Surveill SP - e34583 VL - 8 IS - 7 KW - ProMED-mail KW - natural language processing KW - dengue KW - dual channel KW - bidirectional long short-term memory N2 - Background: Globalization and environmental changes have intensified the emergence or re-emergence of infectious diseases worldwide, such as outbreaks of dengue fever in Southeast Asia. Collaboration on region-wide infectious disease surveillance systems is therefore critical but difficult to achieve because of the different transparency levels of health information systems in different countries. Although the Program for Monitoring Emerging Diseases (ProMED)?mail is the most comprehensive international expert?curated platform providing rich disease outbreak information on humans, animals, and plants, the unstructured text content of the reports makes analysis for further application difficult. Objective: To make monitoring the epidemic situation in Southeast Asia more efficient, this study aims to develop an automatic summary of the alert articles from ProMED-mail, a huge textual data source. In this paper, we proposed a text summarization method that uses natural language processing technology to automatically extract important sentences from alert articles in ProMED-mail emails to generate summaries. Using our method, we can quickly capture crucial information to help make important decisions regarding epidemic surveillance. Methods: Our data, which span a period from 1994 to 2019, come from the ProMED-mail website. We analyzed the collected data to establish a unique Taiwan dengue corpus that was validated with professionals? annotations to achieve almost perfect agreement (Cohen ?=90%). To generate a ProMED-mail summary, we developed a dual-channel bidirectional long short-term memory with attention mechanism with infused latent syntactic features to identify key sentences from the alerting article. Results: Our method is superior to many well-known machine learning and neural network approaches in identifying important sentences, achieving a macroaverage F1 score of 93%. Moreover, it can successfully extract the relevant correct information on dengue fever from a ProMED-mail alerting article, which can help researchers or general users to quickly understand the essence of the alerting article at first glance. In addition to verifying the model, we also recruited 3 professional experts and 2 students from related fields to participate in a satisfaction survey on the generated summaries, and the results show that 84% (63/75) of the summaries received high satisfaction ratings. Conclusions: The proposed approach successfully fuses latent syntactic features into a deep neural network to analyze the syntactic, semantic, and contextual information in the text. It then exploits the derived information to identify crucial sentences in the ProMED-mail alerting article. The experiment results show that the proposed method is not only effective but also outperforms the compared methods. Our approach also demonstrates the potential for case summary generation from ProMED-mail alerting articles. In terms of practical application, when a new alerting article arrives, our method can quickly identify the relevant case information, which is the most critical part, to use as a reference or for further analysis. UR - https://publichealth.jmir.org/2022/7/e34583 UR - http://dx.doi.org/10.2196/34583 UR - http://www.ncbi.nlm.nih.gov/pubmed/35830225 ID - info:doi/10.2196/34583 ER - TY - JOUR AU - Zhao, Zixuan AU - Du, Lingbin AU - Li, Yuanyuan AU - Wang, Le AU - Wang, Youqing AU - Yang, Yi AU - Dong, Hengjin PY - 2022/7/6 TI - Cost-Effectiveness of Lung Cancer Screening Using Low-Dose Computed Tomography Based on Start Age and Interval in China: Modeling Study JO - JMIR Public Health Surveill SP - e36425 VL - 8 IS - 7 KW - cost-effectiveness analysis KW - low-dose computed tomography KW - screening KW - lung cancer KW - China N2 - Background: Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related death in China. The effectiveness of screening for lung cancer has been reported to reduce lung cancer?specific and overall mortality, although the cost-effectiveness, optimal start age, and screening interval remain unclear. Objective: This study aimed to assess the cost-effectiveness of lung cancer screening among heavy smokers in China by incorporating start age and screening interval. Methods: A Markov state-transition model was used to assess the cost-effectiveness of a lung cancer screening program in China. The evaluated screening strategies were based on a screening start age of 50-74 years and a screening interval of once or annually. Transition probabilities were obtained from the literature and validated, while cost parameters were derived from databases of local medical insurance bureaus. A societal perspective was adopted. The outputs of the model included costs, quality-adjusted life years (QALYs), and lung cancer?specific mortality, with future costs and outcomes discounted by 5%. A currency exchange rate of 1 CNY=0.1557 USD is applicable. The incremental cost-effectiveness ratio (ICER) was calculated for different screening strategies relative to nonscreening. Results: The proposed model suggested that screening led to a gain of 0.001-0.042 QALYs per person as compared with the findings in the nonscreening cohort. Meanwhile, one-time and annual screenings were associated with reductions in lung cancer?related mortality of 0.004%-1.171% and 6.189%-15.819%, respectively. The ICER ranged from 119,974.08 to 614,167.75 CNY per QALY gained relative to nonscreening. Using the World Health Organization threshold of 212,676 CNY per QALY gained, annual screening from a start age of 55 years and one-time screening from the age of 65 years can be considered as cost-effective in China. Deterministic and probabilistic sensitivity analyses were conducted. Conclusions: This economic evaluation revealed that a population-based lung cancer screening program in China for heavy smokers using low-dose computed tomography was cost-effective for annual screening of smokers aged 55-74 years and one-time screening of those aged 65-74 years. Moreover, annual lung cancer screening should be promoted in China to realize the benefits of a guideline-recommended screening program. UR - https://publichealth.jmir.org/2022/7/e36425 UR - http://dx.doi.org/10.2196/36425 UR - http://www.ncbi.nlm.nih.gov/pubmed/35793127 ID - info:doi/10.2196/36425 ER - TY - JOUR AU - Sigalo, Nekabari AU - St Jean, Beth AU - Frias-Martinez, Vanessa PY - 2022/7/5 TI - Using Social Media to Predict Food Deserts in the United States: Infodemiology Study of Tweets JO - JMIR Public Health Surveill SP - e34285 VL - 8 IS - 7 KW - social media KW - Twitter KW - food deserts KW - food insecurity N2 - Background: The issue of food insecurity is becoming increasingly important to public health practitioners because of the adverse health outcomes and underlying racial disparities associated with insufficient access to healthy foods. Prior research has used data sources such as surveys, geographic information systems, and food store assessments to identify regions classified as food deserts but perhaps the individuals in these regions unknowingly provide their own accounts of food consumption and food insecurity through social media. Social media data have proved useful in answering questions related to public health; therefore, these data are a rich source for identifying food deserts in the United States. Objective: The aim of this study was to develop, from geotagged Twitter data, a predictive model for the identification of food deserts in the United States using the linguistic constructs found in food-related tweets. Methods: Twitter?s streaming application programming interface was used to collect a random 1% sample of public geolocated tweets across 25 major cities from March 2020 to December 2020. A total of 60,174 geolocated food-related tweets were collected across the 25 cities. Each geolocated tweet was mapped to its respective census tract using point-to-polygon mapping, which allowed us to develop census tract?level features derived from the linguistic constructs found in food-related tweets, such as tweet sentiment and average nutritional value of foods mentioned in the tweets. These features were then used to examine the associations between food desert status and the food ingestion language and sentiment of tweets in a census tract and to determine whether food-related tweets can be used to infer census tract?level food desert status. Results: We found associations between a census tract being classified as a food desert and an increase in the number of tweets in a census tract that mentioned unhealthy foods (P=.03), including foods high in cholesterol (P=.02) or low in key nutrients such as potassium (P=.01). We also found an association between a census tract being classified as a food desert and an increase in the proportion of tweets that mentioned healthy foods (P=.03) and fast-food restaurants (P=.01) with positive sentiment. In addition, we found that including food ingestion language derived from tweets in classification models that predict food desert status improves model performance compared with baseline models that only include socioeconomic characteristics. Conclusions: Social media data have been increasingly used to answer questions related to health and well-being. Using Twitter data, we found that food-related tweets can be used to develop models for predicting census tract food desert status with high accuracy and improve over baseline models. Food ingestion language found in tweets, such as census tract?level measures of food sentiment and healthiness, are associated with census tract?level food desert status. UR - https://publichealth.jmir.org/2022/7/e34285 UR - http://dx.doi.org/10.2196/34285 UR - http://www.ncbi.nlm.nih.gov/pubmed/35788108 ID - info:doi/10.2196/34285 ER - TY - JOUR AU - Gao, Yankun AU - Xie, Zidian AU - Li, Dongmei PY - 2022/7/8 TI - Investigating the Impact of the New York State Flavor Ban on e-Cigarette?Related Discussions on Twitter: Observational Study JO - JMIR Public Health Surveill SP - e34114 VL - 8 IS - 7 KW - New York State flavor ban KW - e-cigarettes KW - twitter KW - topic modeling KW - sentiment analysis N2 - Background: On May 18, 2020, the New York State Department of Health implemented a statewide flavor ban to prohibit the sales of all flavored vapor products, except for tobacco or any other authorized flavor. Objective: This study aims to investigate the discussion changes in e-cigarette?related tweets over time with the implementation of the New York State flavor ban. Methods: Through the Twitter streaming application programming interface, 59,883 e-cigarette?related tweets were collected within the New York State from February 6, 2020, to May 17, 2020 (period 1, before the implementation of the flavor ban), May 18, 2020-June 30, 2020 (period 2, between the implementation of the flavor ban and the online sales ban), July 1, 2020-September 15, 2020 (period 3, the short term after the online sales ban), and September 16, 2020-November 30, 2020 (period 4, the long term after the online sales ban). Sentiment analysis and topic modeling were conducted to investigate the changes in public attitudes and discussions in e-cigarette?related tweets. The popularity of different e-cigarette flavor categories was compared before and after the implementation of the New York State flavor ban. Results: Our results showed that the proportion of e-cigarette?related tweets with negative sentiment significantly decreased (4305/13,246, 32.5% vs 3855/14,455, 26.67%, P<.001), and tweets with positive sentiment significantly increased (5246/13,246, 39.6% vs 7038/14,455, 48.69%, P<.001) in period 4 compared to period 3. ?Teens and nicotine products? was the most frequently discussed e-cigarette?related topic in the negative tweets. In contrast, ?nicotine products and quitting? was more prevalent in positive tweets. The proportion of tweets mentioning mint and menthol flavors significantly increased right after the flavor ban and decreased to lower levels over time. The proportions of fruit and sweet flavors were most frequently mentioned in period 1, decreased in period 2, and dominated again in period 4. Conclusions: The proportion of e-cigarette?related tweets with different attitudes and frequently discussed flavor categories changed over time after the implementation of the New York State ban of flavored vaping products. This change indicated a potential impact of the flavor ban on public discussions of flavored e-cigarettes. UR - https://publichealth.jmir.org/2022/7/e34114 UR - http://dx.doi.org/10.2196/34114 UR - http://www.ncbi.nlm.nih.gov/pubmed/35802417 ID - info:doi/10.2196/34114 ER - TY - JOUR AU - Parker, N. Jayelin AU - Choi, Ki Seul AU - Bauermeister, A. Jose AU - Bonar, E. Erin AU - Carrico, W. Adam AU - Stephenson, Rob PY - 2022/7/1 TI - HIV and Sexually Transmitted Infection Testing Among Substance-Using Sexual and Gender Minority Adolescents and Young Adults: Baseline Survey of a Randomized Controlled Trial JO - JMIR Public Health Surveill SP - e30944 VL - 8 IS - 7 KW - testing KW - substance use KW - sexual minority KW - social determinants N2 - Background: Gay, bisexual, and other men who have sex with men and transgender individuals are more heavily affected by HIV and other sexually transmitted infections (STIs) than their cisgender, heterosexual peers. In addition, sexual and gender minorities who use substances are often at a further increased risk of HIV and other STIs. Increasing testing for HIV and other STIs allows this hardly reached population to receive early intervention, prevention, and education. Objective: We explored HIV and STI testing patterns among 414 sexual and gender minority adolescents and young adults aged 15 to 29 years who self-reported substance use and lived in southeastern Michigan. Methods: We analyzed data from the baseline survey of a 4-arm randomized controlled trial that aimed to examine the efficacy of a brief substance use intervention for creating gains in engagement in HIV prevention. We fit multinomial logistic regression models to 2 categorical HIV and STI testing variables (lifetime and previous 12 months) based on self-reports of testing (never, STIs only, HIV only, or both). In addition, we compared HIV and STI testing behaviors across demographic characteristics, structural factors, psychosocial barriers, substance use, and sexual behaviors. Results: Our findings showed that 35.5% (147/414) of adolescents and young adults reported not being tested for either HIV or STIs in the previous year, and less than half (168/414, 40.6%) of the sample achieved the Centers for Disease Control and Prevention recommendation of HIV and STI testing once per year. We observed HIV and STI testing disparities across sociodemographic (eg, sexual identity, education, and income) and health (eg, substance use) correlates. Specifically, cisgender gay men who have sex with men were more likely to report being tested for HIV compared with bisexual men and transgender individuals, who were more likely to be tested for STIs. Conclusions: This study illustrates the results of an HIV prevention intervention in southeastern Michigan showing the need for HIV prevention interventions that leverage structural factors, psychosocial barriers, and substance use as key drivers to achieve HIV and STI testing rates to meet the Centers for Disease Control and Prevention guidelines. Trial Registration: ClinicalTrials.gov NCT02945436; http://clinicaltrials.gov/ct2/show/NCT02945436 International Registered Report Identifier (IRRID): RR2-10.2196/resprot.9414 UR - https://publichealth.jmir.org/2022/7/e30944 UR - http://dx.doi.org/10.2196/30944 UR - http://www.ncbi.nlm.nih.gov/pubmed/35776441 ID - info:doi/10.2196/30944 ER - TY - JOUR AU - Chabata, T. Sungai AU - Makandwa, Rumbidzo AU - Hensen, Bernadette AU - Mushati, Phillis AU - Chiyaka, Tarisai AU - Musemburi, Sithembile AU - Busza, Joanna AU - Floyd, Sian AU - Birdthistle, Isolde AU - Hargreaves, R. James AU - Cowan, M. Frances PY - 2022/7/27 TI - Strategies to Identify and Reach Young Women Who Sell Sex With HIV Prevention and Care Services: Lessons Learnt From the Implementation of DREAMS Services in Two Cities in Zimbabwe JO - JMIR Public Health Surveill SP - e32286 VL - 8 IS - 7 KW - respondent-driven sampling KW - peer outreach KW - female sex worker KW - young women who sell sex KW - HIV prevention KW - Zimbabwe KW - sub-Saharan Africa N2 - Background: Young women who sell sex (YWSS), are underserved by available HIV prevention and care services. The Determined, Resilient, Empowered, AIDS-free, Mentored and Safe (DREAMS) Partnership aimed to reduce the risk of HIV acquisition among vulnerable populations of adolescent girls and young women, including YWSS, in 10 sub-Saharan African countries. We describe 2 methods, respondent-driven sampling (RDS) and peer outreach, used to refer YWSS for DREAMS services in Zimbabwe, and compare the characteristics and engagement of YWSS referred to these services by each method. We hypothesized that RDS would identify YWSS at higher risk of HIV and those who were less engaged with HIV prevention and care services than peer outreach. Objective: We aimed to compare respondent-driven sampling and peer outreach in recruiting and referring high-risk populations for HIV prevention and care services. Methods: We used RDS, a sampling method designed to reach a representative sample of the network of key populations, and peer outreach, a programmatic approach to identify, reach, and refer YWSS for DREAMS between April and July 2017, and January 2017 and July 2018, respectively, in 2 cities in Zimbabwe. For RDS, we conducted detailed mapping to understand sex work typology and geography, and then purposively selected 10 ?seed? participants in each city to initiate RDS. For peer outreach, we initiated recruitment through 18 trained and age-matched peer educators using youth-tailored community mobilization. We described the characteristics and service engagement of YWSS who accessed DREAMS services by each referral approach and assessed the association of these characteristics with referral approach using the chi-square test. Analysis was performed with and without restricting the period when RDS took place. We estimated the relative incremental costs of recruiting YWSS using each strategy for referral to DREAMS services. Results: Overall, 5386 and 1204 YWSS were referred for DREAMS services through peer outreach and RDS, respectively. YWSS referred through RDS were more likely to access DREAMS services compared to YWSS referred through peer outreach (501/1204, 41.6% vs 930/5386, 17.3%; P<.001). Regardless of referral approach, YWSS who accessed DREAMS had similar education levels, and a similar proportion tested HIV negative and reported not using a condom at the last sex act. A higher proportion of YWSS accessing DREAMS through RDS were aged 18-19 years (167/501, 33.3% vs 243/930, 26.1%; P=.004) and more likely to be aware of their HIV status (395/501, 78.8% vs 396/930, 42.6%; P<.001) compared to those accessing DREAMS services through peer outreach. The incremental cost per young woman who sells sex recruited was US $7.46 for peer outreach and US $52.81 for RDS. Conclusions: Peer outreach and RDS approaches can reach and refer high-risk but different groups of YWSS for HIV services, and using both approaches will likely improve reach. International Registered Report Identifier (IRRID): RR2-10.1186/s12889-018-5085-6 UR - https://publichealth.jmir.org/2022/7/e32286 UR - http://dx.doi.org/10.2196/32286 UR - http://www.ncbi.nlm.nih.gov/pubmed/35896024 ID - info:doi/10.2196/32286 ER - TY - JOUR AU - Liu, Kui AU - Xie, Zhenhua AU - Xie, Bo AU - Chen, Songhua AU - Zhang, Yu AU - Wang, Wei AU - Wu, Qian AU - Cai, Gaofeng AU - Chen, Bin PY - 2022/7/29 TI - Bridging the Gap in End Tuberculosis Targets in the Elderly Population in Eastern China: Observational Study From 2015 to 2020 JO - JMIR Public Health Surveill SP - e39142 VL - 8 IS - 7 KW - pulmonary tuberculosis KW - elderly population KW - prediction N2 - Background: With a progressive increase in the aging process, the challenges posed by pulmonary tuberculosis (PTB) are also increasing for the elderly population. Objective: This study aimed to identify the epidemiological distribution of PTB among the elderly, forecast the achievement of the World Health Organization?s 2025 goal in this specific group, and predict further advancement of PTB in the eastern area of China. Methods: All notified active PTB cases aged ?65 years from Zhejiang Province were screened and analyzed. The general epidemiological characteristics were depicted and presented using the ArcGIS software. Further prediction of PTB was performed using R and SPSS software programs. Results: Altogether 41,431 cases aged ?65 years were identified by the surveillance system from 2015 to 2020. After excluding extrapulmonary TB cases, we identified 39,832 PTB cases, including laboratory-confirmed (23,664, 59.41%) and clinically diagnosed (16,168, 40.59%) PTB. The notified PTB incidence indicated an evident downward trend with a reduction of 30%; however, the incidence of bacteriologically positive cases was steady at approximately 60/100,000. Based on the geographical distribution, Quzhou and Jinhua Cities had a higher PTB incidence among the elderly. The delay in PTB diagnosis was identified, and a significantly prolonged treatment course was observed in the elderly. Moreover, a 50% reduction of PTB incidence by the middle of 2024 was predicted using a linear regression model. It was found that using the exponential smoothing model would be better to predict the PTB trend in the elderly than a seasonal autoregressive integrated moving average model. Conclusions: More comprehensive and effective interventions such as active PTB screening combined with physical checkup and succinct health education should be implemented and strengthened in the elderly. A more systematic assessment of the PTB epidemic trend in the elderly population should be considered to incorporate more predictive factors. UR - https://publichealth.jmir.org/2022/7/e39142 UR - http://dx.doi.org/10.2196/39142 UR - http://www.ncbi.nlm.nih.gov/pubmed/35904857 ID - info:doi/10.2196/39142 ER - TY - JOUR AU - Abdullah, Md Abu Yousuf AU - Law, Jane AU - Perlman, M. Christopher AU - Butt, A. Zahid PY - 2022/7/28 TI - Age- and Sex-Specific Association Between Vegetation Cover and Mental Health Disorders: Bayesian Spatial Study JO - JMIR Public Health Surveill SP - e34782 VL - 8 IS - 7 KW - mental health disorders KW - vegetation cover KW - age- and sex- specific association KW - Enhanced Vegetation Index KW - Bayesian KW - spatial KW - hierarchical modeling KW - marginalization KW - latent covariates N2 - Background: Despite growing evidence that reduced vegetation cover could be a putative risk factor for mental health disorders, the age- and the sex-specific association between vegetation and mental health disorder cases in urban areas is poorly understood. However, with rapid urbanization across the globe, there is an urgent need to study this association and understand the potential impact of vegetation loss on the mental well-being of urban residents. Objective: This study aims to analyze the spatial association between vegetation cover and the age- and sex-stratified mental health disorder cases in the neighborhoods of Toronto, Canada. Methods: We used remote sensing to detect urban vegetation and Bayesian spatial hierarchical modeling to analyze the relationship between vegetation cover and mental health disorder cases. Specifically, an Enhanced Vegetation Index was used to detect urban vegetation, and Bayesian Poisson lognormal models were implemented to study the association between vegetation and mental health disorder cases of males and females in the 0-19, 20-44, 45-64, and ?65 years age groups, after controlling for marginalization and unmeasured (latent) spatial and nonspatial covariates at the neighborhood level. Results: The results suggest that even after adjusting for marginalization, there were significant age- and sex-specific effects of vegetation on the prevalence of mental health disorders in Toronto. Mental health disorders were negatively associated with the vegetation cover for males aged 0-19 years (?7.009; 95% CI ?13.130 to ?0.980) and for both males (?4.544; 95% CI ?8.224 to ?0.895) and females (?3.513; 95% CI ?6.289 to ?0.681) aged 20-44 years. However, for older adults in the 45-64 and ?65 years age groups, only the marginalization covariates were significantly associated with mental health disorder cases. In addition, a substantial influence of the unmeasured (latent) and spatially structured covariates was detected in each model (relative contributions>0.7), suggesting that the variations in area-specific relative risk were mainly spatial in nature. Conclusions: As significant and negative associations between vegetation and mental health disorder cases were found for young males and females, investments in urban greenery can help reduce the future burden of mental health disorders in Canada. The findings highlight the urgent need to understand the age-sex dynamics of the interaction between surrounding vegetation and urban dwellers and its subsequent impact on mental well-being. UR - https://publichealth.jmir.org/2022/7/e34782 UR - http://dx.doi.org/10.2196/34782 UR - http://www.ncbi.nlm.nih.gov/pubmed/35900816 ID - info:doi/10.2196/34782 ER - TY - JOUR AU - Shinto, Takae AU - Makino, Saneyuki AU - Tahara, Yu AU - Nitta, Lyie AU - Kuwahara, Mai AU - Tada, Ayako AU - Abe, Nanako AU - Michie, Mikiko AU - Shibata, Shigenobu PY - 2022/7/12 TI - Relationship Between Protein Intake in Each Traditional Meal and Physical Activity: Cross-sectional Study JO - JMIR Public Health Surveill SP - e35898 VL - 8 IS - 7 KW - protein KW - dietary pattern KW - physical activity KW - chrononutrition N2 - Background: Protein intake plays an important role in the synthesis and maintenance of skeletal muscles for the prevention of health risks. It is also widely known that physical activity influences muscle function. However, no large-scale studies have examined the relationship between daily dietary habits, especially the timing of protein intake, and daily physical activity. Objective: The purpose of this cross-sectional study was to investigate how protein intake and composition (involving the 3 major nutrients protein, fat, and carbohydrate) in the 3 traditional meals (breakfast, lunch, and dinner) are associated with physical activity. Methods: Using daily dietary data accumulated in the smartphone food log app ?Asken? and a web-based cross-sectional survey involving Asken users (N=8458), we analyzed nutrient intake and composition, as well as daily activity levels. As very few individuals skipped breakfast (1102/19,319 responses, 5.7%), we analyzed data for 3 meals per day. Results: Spearman rank correlation analysis revealed that breakfast and lunch protein intakes had higher positive correlations with daily physical activity among the 3 major macronutrients (P<.001). These findings were confirmed by multivariate logistic regression analysis with confounding factors. Moreover, participants with higher protein intake and composition at breakfast or lunch tended to exhibit significantly greater physical activity than those with higher protein intake at dinner (P<.001). Conclusions: Among the 3 macronutrients, protein intake during breakfast and lunch was closely associated with daily physical activity. UR - https://publichealth.jmir.org/2022/7/e35898 UR - http://dx.doi.org/10.2196/35898 UR - http://www.ncbi.nlm.nih.gov/pubmed/35819831 ID - info:doi/10.2196/35898 ER - TY - JOUR AU - Yao, Yan AU - Chai, Ruiyu AU - Yang, Jianzhou AU - Zhang, Xiangjun AU - Huang, Xiaojie AU - Yu, Maohe AU - Fu, Geng-feng AU - Lan, Guanghua AU - Qiao, Ying AU - Zhou, Qidi AU - Li, Shuyue AU - Xu, Junjie PY - 2022/7/29 TI - Correction: Reasons for COVID-19 Vaccine Hesitancy Among Chinese People Living With HIV/AIDS: Structural Equation Modeling Analysis JO - JMIR Public Health Surveill SP - e40910 VL - 8 IS - 7 UR - https://publichealth.jmir.org/2022/7/e40910 UR - http://dx.doi.org/10.2196/40910 UR - http://www.ncbi.nlm.nih.gov/pubmed/35905496 ID - info:doi/10.2196/40910 ER - TY - JOUR AU - Otridge, Jeremy AU - Ogden, L. Cynthia AU - Bernstein, T. Kyle AU - Knuth, Martha AU - Fishman, Julie AU - Brooks, T. John PY - 2022/7/15 TI - Publication and Impact of Preprints Included in the First 100 Editions of the CDC COVID-19 Science Update: Content Analysis JO - JMIR Public Health Surveill SP - e35276 VL - 8 IS - 7 KW - preprints KW - preprint KW - publishing KW - publish KW - bioRxiv KW - medRxiv KW - Centers for Disease Control and Prevention KW - CDC KW - preprint server KW - public health KW - health information KW - COVID-19 KW - pandemic KW - publication KW - Altmetric attention score KW - Altmetric KW - attention score KW - citation count KW - citation KW - science update KW - decision-making N2 - Background: Preprints are publicly available manuscripts posted to various servers that have not been peer reviewed. Although preprints have existed since 1961, they have gained increased popularity during the COVID-19 pandemic due to the need for immediate, relevant information. Objective: The aim of this study is to evaluate the publication rate and impact of preprints included in the Centers for Disease Control and Prevention (CDC) COVID-19 Science Update and assess the performance of the COVID-19 Science Update team in selecting impactful preprints. Methods: All preprints in the first 100 editions (April 1, 2020, to July 30, 2021) of the Science Update were included in the study. Preprints that were not published were categorized as ?unpublished preprints.? Preprints that were subsequently published exist in 2 versions (in a peer-reviewed journal and on the original preprint server), which were analyzed separately and referred to as ?peer-reviewed preprint? and ?original preprint,? respectively. Time to publish was the time interval between the date on which a preprint was first posted and the date on which it was first available as a peer-reviewed article. Impact was quantified by Altmetric Attention Score and citation count for all available manuscripts on August 6, 2021. Preprints were analyzed by publication status, publication rate, preprint server, and time to publication. Results: Of the 275 preprints included in the CDC COVID-19 Science Update during the study period, most came from three servers: medRxiv (n=201, 73.1%), bioRxiv (n=41, 14.9%), and SSRN (n=25, 9.1%), with 8 (2.9%) coming from other sources. Additionally, 152 (55.3%) were eventually published. The median time to publish was 2.3 (IQR 1.4-3.7). When preprints posted in the last 2.3 months were excluded (to account for the time to publish), the publication rate was 67.8%. Moreover, 76 journals published at least one preprint from the CDC COVID-19 Science Update, and 18 journals published at least three. The median Altmetric Attention Score for unpublished preprints (n=123, 44.7%) was 146 (IQR 22-552) with a median citation count of 2 (IQR 0-8); for original preprints (n=152, 55.2%), these values were 212 (IQR 22-1164) and 14 (IQR 2-40), respectively; for peer-review preprints, these values were 265 (IQR 29-1896) and 19 (IQR 3-101), respectively. Conclusions: Prior studies of COVID-19 preprints found publication rates between 5.4% and 21.1%. Preprints included in the CDC COVID-19 Science Update were published at a higher rate than overall COVID-19 preprints, and those that were ultimately published were published within months and received higher attention scores than unpublished preprints. These findings indicate that the Science Update process for selecting preprints had a high fidelity in terms of their likelihood to be published and their impact. The incorporation of high-quality preprints into the CDC COVID-19 Science Update improves this activity?s capacity to inform meaningful public health decision-making. UR - https://publichealth.jmir.org/2022/7/e35276 UR - http://dx.doi.org/10.2196/35276 UR - http://www.ncbi.nlm.nih.gov/pubmed/35544426 ID - info:doi/10.2196/35276 ER - TY - JOUR AU - Stockham, Nathaniel AU - Washington, Peter AU - Chrisman, Brianna AU - Paskov, Kelley AU - Jung, Jae-Yoon AU - Wall, Paul Dennis PY - 2022/7/21 TI - Causal Modeling to Mitigate Selection Bias and Unmeasured Confounding in Internet-Based Epidemiology of COVID-19: Model Development and Validation JO - JMIR Public Health Surveill SP - e31306 VL - 8 IS - 7 KW - selection bias KW - COVID-19 KW - epidemiology KW - causality KW - sensitivity analysis KW - public health KW - surveillance KW - method KW - epidemiologic research design KW - model KW - bias KW - development KW - validation KW - utility KW - implementation KW - sensitivity KW - design KW - research N2 - Background: Selection bias and unmeasured confounding are fundamental problems in epidemiology that threaten study internal and external validity. These phenomena are particularly dangerous in internet-based public health surveillance, where traditional mitigation and adjustment methods are inapplicable, unavailable, or out of date. Recent theoretical advances in causal modeling can mitigate these threats, but these innovations have not been widely deployed in the epidemiological community. Objective: The purpose of our paper is to demonstrate the practical utility of causal modeling to both detect unmeasured confounding and selection bias and guide model selection to minimize bias. We implemented this approach in an applied epidemiological study of the COVID-19 cumulative infection rate in the New York City (NYC) spring 2020 epidemic. Methods: We collected primary data from Qualtrics surveys of Amazon Mechanical Turk (MTurk) crowd workers residing in New Jersey and New York State across 2 sampling periods: April 11-14 and May 8-11, 2020. The surveys queried the subjects on household health status and demographic characteristics. We constructed a set of possible causal models of household infection and survey selection mechanisms and ranked them by compatibility with the collected survey data. The most compatible causal model was then used to estimate the cumulative infection rate in each survey period. Results: There were 527 and 513 responses collected for the 2 periods, respectively. Response demographics were highly skewed toward a younger age in both survey periods. Despite the extremely strong relationship between age and COVID-19 symptoms, we recovered minimally biased estimates of the cumulative infection rate using only primary data and the most compatible causal model, with a relative bias of +3.8% and ?1.9% from the reported cumulative infection rate for the first and second survey periods, respectively. Conclusions: We successfully recovered accurate estimates of the cumulative infection rate from an internet-based crowdsourced sample despite considerable selection bias and unmeasured confounding in the primary data. This implementation demonstrates how simple applications of structural causal modeling can be effectively used to determine falsifiable model conditions, detect selection bias and confounding factors, and minimize estimate bias through model selection in a novel epidemiological context. As the disease and social dynamics of COVID-19 continue to evolve, public health surveillance protocols must continue to adapt; the emergence of Omicron variants and shift to at-home testing as recent challenges. Rigorous and transparent methods to develop, deploy, and diagnosis adapted surveillance protocols will be critical to their success. UR - https://publichealth.jmir.org/2022/7/e31306 UR - http://dx.doi.org/10.2196/31306 UR - http://www.ncbi.nlm.nih.gov/pubmed/35605128 ID - info:doi/10.2196/31306 ER - TY - JOUR AU - Hu, Maogui AU - Feng, Yuqing AU - Li, Tao AU - Zhao, Yanlin AU - Wang, Jinfeng AU - Xu, Chengdong AU - Chen, Wei PY - 2022/7/1 TI - Unbalanced Risk of Pulmonary Tuberculosis in China at the Subnational Scale: Spatiotemporal Analysis JO - JMIR Public Health Surveill SP - e36242 VL - 8 IS - 7 KW - pulmonary tuberculosis KW - infectious disease KW - pattern KW - notification rates KW - Bayesian KW - spatiotemporal pattern KW - tuberculosis KW - public health KW - China KW - disease burden KW - spatial data KW - regional inequality KW - risk KW - TB KW - unbalanced KW - notification data KW - trend KW - cases KW - incidence N2 - Background: China has one of the highest tuberculosis (TB) burdens in the world. However, the unbalanced spatial and temporal trends of TB risk at a fine level remain unclear. Objective: We aimed to investigate the unbalanced risks of pulmonary tuberculosis (PTB) at different levels and how they evolved from both temporal and spatial aspects using PTB notification data from 2851 counties over a decade in China. Methods: County-level notified PTB case data were collected from 2009 to 2018 in mainland China. A Bayesian hierarchical model was constructed to analyze the unbalanced spatiotemporal patterns of PTB notification rates during this period at subnational scales. The Gini coefficient was calculated to assess the inequality of the relative risk (RR) of PTB across counties. Results: From 2009 to 2018, the number of notified PTB cases in mainland China decreased from 946,086 to 747,700. The average number of PTB cases in counties was 301 (SD 26) and the overall average notification rate was 60 (SD 6) per 100,000 people. There were obvious regional differences in the RRs for PTB (Gini coefficient 0.32, 95% CI 0.31-0.33). Xinjiang had the highest PTB notification rate, with a multiyear average of 155/100,000 (RR 2.3, 95% CI 1.6-2.8; P<.001), followed by Guizhou (117/100,000; RR 1.8, 95% CI 1.3-1.9; P<.001) and Tibet (108/100,000; RR 1.7, 95% CI 1.3-2.1; P<.001). The RR for PTB showed a steady downward trend. Gansu (local trend [LT] 0.95, 95% CI 0.93-0.96; P<.001) and Shanxi (LT 0.94, 95% CI 0.92-0.96; P<.001) experienced the fastest declines. However, the RRs for PTB in the western region (such as counties in Xinjiang, Guizhou, and Tibet) were significantly higher than those in the eastern and central regions (P<.001), and the decline rate of the RR for PTB was lower than the overall level (P<.001). Conclusions: PTB risk showed significant regional inequality among counties in China, and western China presented a high plateau of disease burden. Improvements in economic and medical service levels are required to boost PTB case detection and eventually reduce PTB risk in the whole country. UR - https://publichealth.jmir.org/2022/7/e36242 UR - http://dx.doi.org/10.2196/36242 UR - http://www.ncbi.nlm.nih.gov/pubmed/35776442 ID - info:doi/10.2196/36242 ER - TY - JOUR AU - Bao, Yuhan AU - Wang, Chunxiang AU - Xu, Haiping AU - Lai, Yongjie AU - Yan, Yupei AU - Ma, Yuanyuan AU - Yu, Ting AU - Wu, Yibo PY - 2022/7/14 TI - Effects of an mHealth Intervention for Pulmonary Tuberculosis Self-management Based on the Integrated Theory of Health Behavior Change: Randomized Controlled Trial JO - JMIR Public Health Surveill SP - e34277 VL - 8 IS - 7 KW - ITHBC KW - mHealth KW - RCT KW - pulmonary tuberculosis N2 - Background: Improving the health self-management level of patients with tuberculosis (TB) is significant for reducing drug resistance, improving the cure rate, and controlling the prevalence of TB. Mobile health (mHealth) interventions based on behavioral science theories may be promising to achieve this goal. Objective: This study aims to explore and conduct an mHealth intervention based on the Integrated Theory of Health Behavior Change (ITHBC) in patients with pulmonary TB to increase their ability of self-care management. Methods: A prospective randomized controlled study was conducted from May to November 2020. A total of 114 patients who were admitted consecutively to the TB clinic of Harbin Chest Hospital, China from May 2020 to August 2020 were recruited by convenience sampling. Patients were divided into the control group and intervention group, and all received a 3-month intervention. Patients in the intervention group and the control group received routine medical and nursing care in the TB clinic, including the supervision of their medications. In addition, pharmacist-assisted mHealth (WeChat) intervention based on the ITHBC theory about TB management was provided to the intervention group. The primary outcome was self-management behavior, while the secondary outcomes were TB awareness, self-efficacy, social support, and degree of satisfaction with health education. The outcomes were measured using web-based self-designed and standard questionnaires administered at baseline and at the end point of the study. Intergroup data were assessed using the Mann-Whitney U test, whereas intragroup data were assessed with the Wilcoxon test (for paired samples). Results: A total of 112 patients (59 in intervention group and 53 in control group) completed the study. After the intervention, a statistically significant increase was noted in the scores of each item of self-care management behaviors compared with the scores at the baseline (P<.001) in the intervention group. The scores of all self-care management behaviors of the control group were lower than those of all self-care management behaviors in the intervention group (all P<.05), except for the item ?cover your mouth and nose when coughing or sneezing? (P=.23) and item ?wash hands properly? (P=.60), which had no statistically significant difference from those in the intervention group. Compared with those at baseline, TB knowledge awareness, self-efficacy, social support, and degree of satisfaction with health education in the intervention group increased significantly (P<.001), and the intervention group had significantly higher scores than the control group (P<.001). Conclusions: mHealth intervention for TB self-management based on ITHBC could deepen the understanding of patients with TB about their disease and improve their objective initiative and self-care management behaviors, which were beneficial for promoting compliance behavior and quality of prevention and control for pulmonary TB. Trial Registration: Chinese Clinical Trial Registry ChiCTR2200055557; https://tinyurl.com/4ray3xnw UR - https://publichealth.jmir.org/2022/7/e34277 UR - http://dx.doi.org/10.2196/34277 UR - http://www.ncbi.nlm.nih.gov/pubmed/35834302 ID - info:doi/10.2196/34277 ER - TY - JOUR AU - Garrett, M. Paul AU - White, P. Joshua AU - Dennis, Simon AU - Lewandowsky, Stephan AU - Yang, Cheng-Ta AU - Okan, Yasmina AU - Perfors, Andrew AU - Little, R. Daniel AU - Kozyreva, Anastasia AU - Lorenz-Spreen, Philipp AU - Kusumi, Takashi AU - Kashima, Yoshihisa PY - 2022/7/15 TI - Papers Please - Predictive Factors of National and International Attitudes Toward Immunity and Vaccination Passports: Online Representative Surveys JO - JMIR Public Health Surveill SP - e32969 VL - 8 IS - 7 KW - COVID-19 KW - immunity passport KW - vaccination passport KW - cross-cultural KW - health policy KW - digital certificates KW - SARS-CoV-2 KW - vaccine KW - policy KW - international N2 - Background: In response to the COVID-19 pandemic, countries are introducing digital passports that allow citizens to return to normal activities if they were previously infected with (immunity passport) or vaccinated against (vaccination passport) SARS-CoV-2. To be effective, policy decision-makers must know whether these passports will be widely accepted by the public and under what conditions. This study focuses attention on immunity passports, as these may prove useful in countries both with and without an existing COVID-19 vaccination program; however, our general findings also extend to vaccination passports. Objective: We aimed to assess attitudes toward the introduction of immunity passports in six countries, and determine what social, personal, and contextual factors predicted their support. Methods: We collected 13,678 participants through online representative sampling across six countries?Australia, Japan, Taiwan, Germany, Spain, and the United Kingdom?during April to May of the 2020 COVID-19 pandemic, and assessed attitudes and support for the introduction of immunity passports. Results: Immunity passport support was moderate to low, being the highest in Germany (775/1507 participants, 51.43%) and the United Kingdom (759/1484, 51.15%); followed by Taiwan (2841/5989, 47.44%), Australia (963/2086, 46.16%), and Spain (693/1491, 46.48%); and was the lowest in Japan (241/1081, 22.94%). Bayesian generalized linear mixed effects modeling was used to assess predictive factors for immunity passport support across countries. International results showed neoliberal worldviews (odds ratio [OR] 1.17, 95% CI 1.13-1.22), personal concern (OR 1.07, 95% CI 1.00-1.16), perceived virus severity (OR 1.07, 95% CI 1.01-1.14), the fairness of immunity passports (OR 2.51, 95% CI 2.36-2.66), liking immunity passports (OR 2.77, 95% CI 2.61-2.94), and a willingness to become infected to gain an immunity passport (OR 1.6, 95% CI 1.51-1.68) were all predictive factors of immunity passport support. By contrast, gender (woman; OR 0.9, 95% CI 0.82-0.98), immunity passport concern (OR 0.61, 95% CI 0.57-0.65), and risk of harm to society (OR 0.71, 95% CI 0.67-0.76) predicted a decrease in support for immunity passports. Minor differences in predictive factors were found between countries and results were modeled separately to provide national accounts of these data. Conclusions: Our research suggests that support for immunity passports is predicted by the personal benefits and societal risks they confer. These findings generalized across six countries and may also prove informative for the introduction of vaccination passports, helping policymakers to introduce effective COVID-19 passport policies in these six countries and around the world. UR - https://publichealth.jmir.org/2022/7/e32969 UR - http://dx.doi.org/10.2196/32969 UR - http://www.ncbi.nlm.nih.gov/pubmed/35377317 ID - info:doi/10.2196/32969 ER - TY - JOUR AU - Megahed, M. Fadel AU - Jones-Farmer, Allison L. AU - Ma, Yinjiao AU - Rigdon, E. Steven PY - 2022/7/19 TI - Explaining the Varying Patterns of COVID-19 Deaths Across the United States: 2-Stage Time Series Clustering Framework JO - JMIR Public Health Surveill SP - e32164 VL - 8 IS - 7 KW - explanatory modeling KW - multinomial regression KW - SARS-CoV-2 KW - COVID-19 KW - socioeconomic analyses KW - time series analysis N2 - Background: Socially vulnerable communities are at increased risk for adverse health outcomes during a pandemic. Although this association has been established for H1N1, Middle East respiratory syndrome (MERS), and COVID-19 outbreaks, understanding the factors influencing the outbreak pattern for different communities remains limited. Objective: Our 3 objectives are to determine how many distinct clusters of time series there are for COVID-19 deaths in 3108 contiguous counties in the United States, how the clusters are geographically distributed, and what factors influence the probability of cluster membership. Methods: We proposed a 2-stage data analytic framework that can account for different levels of temporal aggregation for the pandemic outcomes and community-level predictors. Specifically, we used time-series clustering to identify clusters with similar outcome patterns for the 3108 contiguous US counties. Multinomial logistic regression was used to explain the relationship between community-level predictors and cluster assignment. We analyzed county-level confirmed COVID-19 deaths from Sunday, March 1, 2020, to Saturday, February 27, 2021. Results: Four distinct patterns of deaths were observed across the contiguous US counties. The multinomial regression model correctly classified 1904 (61.25%) of the counties? outbreak patterns/clusters. Conclusions: Our results provide evidence that county-level patterns of COVID-19 deaths are different and can be explained in part by social and political predictors. UR - https://publichealth.jmir.org/2022/7/e32164 UR - http://dx.doi.org/10.2196/32164 UR - http://www.ncbi.nlm.nih.gov/pubmed/35476722 ID - info:doi/10.2196/32164 ER - TY - JOUR AU - Fang, Guixia AU - Yang, Diling AU - Wang, Li AU - Wang, Zhihao AU - Liang, Yuanyuan AU - Yang, Jinxia PY - 2022/7/22 TI - Experiences and Challenges of Implementing Universal Health Coverage With China?s National Basic Public Health Service Program: Literature Review, Regression Analysis, and Insider Interviews JO - JMIR Public Health Surveill SP - e31289 VL - 8 IS - 7 KW - universal health coverage KW - basic public health service KW - China KW - experience KW - challenge N2 - Background: Public health service is an important component and pathway to achieve universal health coverage (UHC), a major direction goal of many countries. China?s National Basic Public Health Service Program (the Program) is highly consistent with this direction. Objective: The aim of this study was to analyze the key experience and challenges of the Program so as to present China?s approach to UHC, help other countries understand and learn from China?s experience, and promote UHC across the world. Methods: A literature review was performed across five main electronic databases and other sources. Some data were obtained from the Department of Primary Health, National Health Commission, China. Data obtained included the financing share of the national/provincial/prefectural government among the total investment of the program in 32 provinces in 2016, their respective per capita funding levels, and some indicators related to program implementation from 2009 to 2016. The Joinpoint regression model was adopted to test the time trend of changes in program implementation indicators. Face-to-face individual interviews and group discussions were conducted with 48 key insiders. Results: The program provided full life cycle service to the whole population with an equitable and affordable financing system, enhanced the capability and quality of the health workforce, and facilitated integration of the public health service delivery system. Meanwhile, there were also some shortcomings, including lack of selection and an exit mechanism of service items, inadequate system integration, shortage of qualified professionals, limited role played by actors outside the health sector, and a large gap between the subsidy standard and the actual service cost. The Joinpoint regression analysis demonstrated that 13 indicators related to program implementation showed a significant upward trend (P<.05) from 2009 to 2016, with average annual percent change values above 10% for 6 indicators and below 6% for 7 indicators. Three indicators (coverage of health records, electronic health records, and health management among the elderly) rose rapidly with annual percent change values above 30% between 2009 and 2011, but rose slowly or remained stable between 2011 and 2016. In 2016, the subsidy standard per capita in the eastern, central, and western regions was equivalent to US $7.43, $7.15, and $6.57, respectively, of which the national-level subsidy accounted for 25.50%, 60.57%, and 79.52%, respectively. Conclusions: The Program has made a significant contribution to China?s efforts in achieving UHC. The Program focuses on a key population and provides full life cycle services for the whole population. The financing system completely supported by the government makes the services more equitable and affordable. However, there are a few challenges to implementing the Program in China, especially to increase the public investment, optimize service items, enhance quality of the services, and evaluate the health outcomes. UR - https://publichealth.jmir.org/2022/7/e31289 UR - http://dx.doi.org/10.2196/31289 UR - http://www.ncbi.nlm.nih.gov/pubmed/35867386 ID - info:doi/10.2196/31289 ER -