A municipality-level analysis of excess mortality in Italy in the period January-April 2020.

BACKGROUND: the first confirmed cases of COVID-19 in WHO European Region was reported at the end of January 2020 and, from that moment, the epidemic has been speeding up and rapidly spreading across Europe. The health, social, and economic consequences of the pandemic are difficult to evaluate, since there are many scientific uncertainties and unknowns. OBJECTIVES: the main focus of this paper is on statistical methods for profiling municipalities by excess mortality, directly or indirectly caused by COVID-19. METHODS: the use of excess mortality for all causes has been advocated as a measure of impact less vulnerable to biases. In this paper, observed mortality for all causes at municipality level in Italy in the period January-April 2020 was compared to the mortality observed in the corresponding period in the previous 5 years (2015-2019). Mortality data were made available by the Ministry of Internal Affairs Italian National Resident Population Demographic Archive and the Italian National Institute of Statistics (Istat). For each municipality, the posterior predictive distribution under a hierarchical null model was obtained. From the posterior predictive distribution, we obtained excess death counts, attributable community rates and q-values. Full Bayesian models implemented via MCMC simulations were used. RESULTS: absolute number of excess deaths highlights the burden paid by major cities to the pandemic. The Attributable Community Rate provides a detailed picture of the spread of the pandemic among the municipalities of Lombardy, Piedmont, and Emilia-Romagna Regions. Using Q-values, it is clearly recognizable evidence of an excess of mortality from late February to April 2020 in a very geographically scattered number of municipalities. A trade-off between false discoveries and false non-discoveries shows the different values of public health actions. CONCLUSIONS: despite the variety of approaches to calculate excess mortality, this study provides an original methodological approach to profile municipalities with excess deaths accounting for spatial and temporal uncertainty.

Predictors of social distancing and hand washing among adults in five countries during COVID-19.

The purpose of this cross-sectional study is to examine disparities in hand washing and social distancing among 2,509 adults from the United States, Italy, Spain, the Kingdom of Saudi Arabia, and India. Respondents were recruited via Qualtrics' participant pool and completed an online survey in the most common language spoken in each country. In hierarchical linear regression models, living in a rural area (ß = -0.08, p = .001), older age (ß = 0.07, p < .001), identifying as a woman (ß = 0.07, p = .001), and greater educational attainment (ß = 0.07, p = .017) were significantly associated with hand washing. Similar results were found regarding social distancing, in which living in a rural area (ß = -0.10, p < .001), country of residence (ß = 0.11, p < .001), older age (ß = 0.17, p < .001), identifying as a woman (ß = 0.11, p < .001), and greater educational attainment (ß = 0.06, p = .019) were significant predictors. Results from the multivariable linear regression models demonstrate more nuanced findings with distinct and significant disparities across the five countries found with respect to hand washing and social distancing. Taken together, the results suggest multiple influencing factors that contribute to existing disparities regarding social distancing and hand washing among adults internationally. As such, more tailored public interventions are needed to promote preventive measures to mitigate existing COVID-related disparities.

Differences in Preventive Behaviors of COVID-19 between Urban and Rural Residents: Lessons Learned from A Cross-Sectional Study in China.

Purpose: The purpose of this study is to examine the differences in preventive behaviors of COVID-19 between urban and rural residents, as well as identify the factors that might contribute to such differences. Methods: Our online survey included 1591 participants from 31 provinces of China with 87% urban and 13% rural residents. We performed multiple linear regressions and path analysis to examine the relationship between rural status and behavioral intention, attitude, subjective norms, information appraisal, knowledge, variety of information source use, and preventive behaviors against COVID-19. Findings: Compared with urban residents, rural residents were less likely to perform preventive behaviors, more likely to hold a negative attitude toward the effectiveness of performing preventive behaviors, and more likely to have lower levels of information appraisal skills. We identified information appraisal as a significant factor that might contribute to the rural/urban differences in preventive behaviors against COVID-19 through attitude, subjective norms, and intention. We found no rural/urban differences in behavioral intention, subjective norms, knowledge about preventive behaviors, or the variety of interpersonal/media source use. Conclusions: As the first wave of the pandemic inundated urban areas, the current media coverage about COVID-19 prevention may not fully satisfy the specific needs of rural populations. Thus, rural residents were less likely to engage in a thoughtful process of information appraisal and adopt the appropriate preventive measures. Tailoring health messages to meet rural populations' unique needs can be an effective strategy to promote preventive health behaviors against COVID-19.

Seroepidemiology of SARS-CoV-2 infections in an urban population-based cohort in León, Nicaragua.

In a Nicaraguan population-based cohort, SARS-CoV-2 seroprevalence reached 28% in the first 6 months of the country's epidemic and reached 35% 6 months later. Immune waning was uncommon. Individuals with a seropositive household member were over three times as likely to be seropositive themselves, suggesting the importance of household transmission.

Disability-adjusted life years (DALYs) due to the direct health impact of COVID-19 in India, 2020.

COVID-19 has affected all countries. Its containment represents a unique challenge for India due to a large population (> 1.38 billion) across a wide range of population densities. Assessment of the COVID-19 disease burden is required to put the disease impact into context and support future pandemic policy development. Here, we present the national-level burden of COVID-19 in India in 2020 that accounts for differences across urban and rural regions and across age groups. Input data were collected from official records or published literature. The proportion of excess COVID-19 deaths was estimated using the Institute for Health Metrics and Evaluation, Washington data. Disability-adjusted life years (DALY) due to COVID-19 were estimated in the Indian population in 2020, comprised of years of life lost (YLL) and years lived with disability (YLD). YLL was estimated by multiplying the number of deaths due to COVID-19 by the residual standard life expectancy at the age of death due to the disease. YLD was calculated as a product of the number of incident cases of COVID-19, disease duration and disability weight. Scenario analyses were conducted to account for excess deaths not recorded in the official data and for reported COVID-19 deaths. The direct impact of COVID-19 in 2020 in India was responsible for 14,100,422 (95% uncertainty interval [UI] 14,030,129-14,213,231) DALYs, consisting of 99.2% (95% UI 98.47-99.64%) YLLs and 0.80% (95% UI 0.36-1.53) YLDs. DALYs were higher in urban (56%; 95% UI 56-57%) than rural areas (44%; 95% UI 43.4-43.6) and in men (64%) than women (36%). In absolute terms, the highest DALYs occurred in the 51-60-year-old age group (28%) but the highest DALYs per 100,000 persons were estimated for the 71-80 years old age group (5481; 95% UI 5464-5500 years). There were 4,815,908 (95% UI 4,760,908-4,924,307) DALYs after considering reported COVID-19 deaths only. The DALY estimations have direct and immediate implications not only for public policy in India, but also internationally given that India represents one sixth of the world's population.

A hierarchical study for urban statistical indicators on the prevalence of COVID-19 in Chinese city clusters based on multiple linear regression (MLR) and polynomial best subset regression (PBSR) analysis.

With evidence-based measures, COVID-19 can be effectively controlled by advanced data analysis and prediction. However, while valuable insights are available, there is a shortage of robust and rigorous research on what factors shape COVID-19 transmissions at the city cluster level. Therefore, to bridge the research gap, we adopted a data-driven hierarchical modeling approach to identify the most influential factors in shaping COVID-19 transmissions across different Chinese cities and clusters. The data used in this study are from Chinese officials, and hierarchical modeling conclusions drawn from the analysis are systematic, multifaceted, and comprehensive. To further improve research rigor, the study utilizes SPSS, Python and RStudio to conduct multiple linear regression and polynomial best subset regression (PBSR) analysis for the hierarchical modeling. The regression model utilizes the magnitude of various relative factors in nine Chinese city clusters, including 45 cities at a different level of clusters, to examine these aspects from the city cluster scale, exploring the correlation between various factors of the cities. These initial 12 factors are comprised of 'Urban population ratio', 'Retail sales of consumer goods', 'Number of tourists', 'Tourism Income', 'Ratio of the elderly population (> 60 year old) in this city', 'population density', 'Mobility scale (move in/inbound) during the spring festival', 'Ratio of Population and Health facilities', 'Jobless rate (%)', 'The straight-line distance from original epicenter Wuhan to this city', 'urban per capita GDP', and 'the prevalence of the COVID-19'. The study's results provide rigorously-tested and evidence-based insights on most instrumental factors that shape COVID-19 transmissions across cities and regions in China. Overall, the study findings found that per capita GDP and population mobility rates were the most affected factors in the prevalence of COVID-19 in a city, which could inform health experts and government officials to design and develop evidence-based and effective public health policies that could curb the spread of the COVID-19 pandemic.

Nationally representative SARS-CoV-2 antibody prevalence estimates after the first epidemic wave in Mexico.

Seroprevalence surveys provide estimates of the extent of SARS-CoV-2 infections in the population, regardless of disease severity and test availability. In Mexico in 2020, COVID-19 cases reached a maximum in July and December. We aimed to estimate the national and regional seroprevalence of SARS-CoV-2 antibodies across demographic and socioeconomic groups in Mexico after the first wave, from August to November 2020. We used nationally representative survey data including 9,640 blood samples. Seroprevalence was estimated by socioeconomic and demographic characteristics, adjusting by the sensitivity and specificity of the immunoassay test. The national seroprevalence of SARS-CoV-2 antibodies was 24.9% (95%CI 22.2, 26.7), being lower for adults 60 years and older. We found higher seroprevalence among urban and metropolitan areas, low socioeconomic status, low education and workers. Among seropositive people, 67.3% were asymptomatic. Social distancing, lockdown measures and vaccination programs need to consider that vulnerable groups are more exposed to the virus and unable to comply with lockdown measures.

Depression, Anxiety, and Alcohol Use Among LGBTQ+ People During the COVID-19 Pandemic.

Objectives. To describe disparities in depression, anxiety, and problem drinking by sexual orientation, sexual behavior, and gender identity during the COVID-19 pandemic. Methods. Data were collected May 21 to July 15, 2020, from 3245 adults living in 5 major US metropolitan areas (Atlanta, Georgia; Chicago, Illinois; New Orleans, Louisiana; New York, New York; and Los Angeles, California). Participants were characterized as cisgender straight or LGBTQ+ (i.e., lesbian, gay, bisexual, and transgender people, and men who have sex with men, and women who have sex with women not identifying as lesbian, gay, bisexual, or transgender). Results. Cisgender straight participants had the lowest levels of depression, anxiety, and problem drinking compared with all other sexual orientation, sexual behavior, and gender identity groups, and, in general, LGBTQ+ participants were more likely to report that these health problems were "more than usual" during the COVID-19 pandemic. Conclusions. LGBTQ+ communities experienced worse mental health and problem drinking than their cisgender straight counterparts during the COVID-19 pandemic. Future research should assess the impact of the pandemic on health inequities. Policymakers should consider resources to support LGBTQ+ mental health and substance use prevention in COVID-19 recovery efforts.

Anxiety among urban, semi-urban and rural school adolescents in Dhaka, Bangladesh: Investigating prevalence and associated factors.

BACKGROUND: Anxiety disorder is one of the emerging public health problems in many low- and middle-income countries (LMICs). Likewise, in Bangladesh, a growing number of adolescents are experiencing such symptoms though we have very limited research evidence available. The purpose of this study was to investigate the prevalence of anxiety and the factors associated with this condition among urban, semi-urban, and rural school adolescents in Bangladesh. METHODS: This cross-sectional study used a two-stage cluster sampling procedure. A self-administered questionnaire was conveyed to 2355 adolescents from nine secondary schools of Dhaka, Bangladesh. Of the respondents, 2313 completed the seven-item Generalized Anxiety Disorder (GAD-7). Besides, sociodemographic information, self-reported body image as well as modification of Leisure Time Exercise Questionnaire (LTEQ) and WHO Global PA Questionnaire (GPAQ) were used to determine the sociodemographic and lifestyle factors associated with anxiety among adolescents. RESULTS: A total of 20.1% of adolescents were experiencing moderate to severe anxiety; of them, a significantly higher proportion (49.9%) of female adolescents were suffering more than males (40.1%). Furthermore, age, student's grade, father's educational level, number of family members, and residential setting were found to be significantly associated with anxiety among adolescents. In terms of lifestyle factors, irregular physical activity (AOR: 1.31; 95% CI: 1.05-1.63), high screen time (AOR: 1.51; 95% CI:1.21-1.88), sleep dissatisfaction (AOR: 3.79; 95% CI: 3.02-4.76), and underweight body image (AOR: 2.37; 95% CI:1.70-3.28) were found to be significantly associated with anxiety among school adolescents of urban, semi-urban, and rural residential settings. CONCLUSIONS: Anxiety is prevalent among urban, semi-urban, and rural school adolescents in Dhaka, Bangladesh. To lessen this prevalence of anxiety among Bangladeshi adolescents, evidence-based health programs- healthy school trials-and policies should therefore be taken based on the findings of this study.

The Impact of the COVID-19 Epidemic on Older Adults in Rural and Urban Areas in Mexico.

OBJECTIVES: Mexico is among the countries in Latin America hit hardest by coronavirus disease 2019 (COVID-19). A large proportion of older adults in Mexico have high prevalence of multimorbidity and live in poverty with limited access to health care services. These statistics are even higher among adults living in rural areas, which suggest that older adults in rural communities may be more susceptible to COVID-19. The objectives of the article were to compare clinical and demographic characteristics for people diagnosed with COVID-19 by age group, and to describe cases and mortality in rural and urban communities. METHOD: We linked publicly available data from the Mexican Ministry of Health and the Census. Municipalities were classified based on population as rural (<2,500), semirural (≥2,500 and <15,000), semiurban (≥15,000 and <100,000), and urban (≥100,000). Zero-inflated negative binomial models were performed to calculate the total number of COVID-19 cases, and deaths per 1,000,000 persons using the population of each municipality as a denominator. RESULTS: Older adults were more likely to be hospitalized and reported severe cases, with higher mortality rates. In addition, rural municipalities reported a higher number of COVID-19 cases and mortality related to COVID-19 per million than urban municipalities. The adjusted absolute difference in COVID-19 cases was 912.7 per million (95% confidence interval [CI]: 79.0-1746.4) and mortality related to COVID-19 was 390.6 per million (95% CI: 204.5-576.7). DISCUSSION: Urgent policy efforts are needed to mandate the use of face masks, encourage handwashing, and improve specialty care for Mexicans in rural areas.

COVID-19 vaccine demand, hesitancy, and nationalism: a case of protection motivation behavior in Bangladesh.

INTRODUCTION: Immunization, as a process of fighting against the COVID-19, has gained important research appeal, but very limited endeavor has been paid for vaccine behavioral studies in underdeveloped and developing countries. This study explores the vaccine demand, hesitancy, and nationalism as well as vaccine acceptance and domestic vaccine preference among young adults in Bangladesh. METHODOLOGY: This quantitative study followed the snowball sampling technique and collected responses from 1,018 individuals from various social media platforms. The analysis covered both descriptive and inferential statistics including chi-square, F-statistic, and logistic regression. RESULTS: The findings of the fully-adjusted regression model suggest that the individuals who had more vaccine demand were 3.29 times (95% confidence interval = 2.39-4.54; p < 0.001) higher to accept vaccine compared to those who had no vaccine demand. Conversely, vaccine hesitancy was negatively associated with vaccine acceptance. Here, the odds ratio was found 0.70 (95% confidence interval = 0.62-0.80; p < 0.001), which means that those who had higher vaccine hesitancy were about 30% less likely to accept vaccines than those who had no hesitancy. In addition, the persons who had vaccine nationalism were 1.75 times (95% confidence interval = 1.62-1.88; p < 0.001) more prone to prefer domestic vaccine. CONCLUSIONS: This study suggests that policymakers may take initiatives for making people aware and knowledgeable about the severity and vulnerability to specific health threats. In this concern, perception and efficacy-increasing programs may take part in increasing protection motivation behaviors like vaccine acceptance and (domestic) vaccine preference.

HIV Infection and HIV-Associated Behaviors Among Persons Who Inject Drugs - 23 Metropolitan Statistical Areas, United States, 2018.

In the United States, 10% of HIV infections diagnosed in 2018 were attributed to unsafe injection drug use or male-to-male sexual contact among persons who inject drugs (PWID) (1). In 2017, among PWID or men who have sex with men and who inject drugs (MSM-ID), 76% of those who received a diagnosis of HIV infection lived in urban areas* (2). To monitor the prevalence of HIV infection and associated behaviors among persons who reported injecting drugs in the past 12 months, including MSM-ID, CDC's National HIV Behavioral Surveillance (NHBS) conducts interviews and HIV testing among populations of persons at high risk for HIV infection (MSM, PWID, and heterosexually active adults at increased risk for HIV infection) in selected metropolitan statistical areas (MSAs) (3). The estimated HIV infection prevalence among PWID in 23 MSAs surveyed in 2018 was 7%. Among HIV-negative PWID, an estimated 26% receptively shared syringes and 68% had condomless vaginal sex during the preceding 12 months. During the same period, 57% had been tested for HIV infection, and 55% received syringes from a syringe services program (SSP). While overall SSP use did not significantly change since 2015, a substantial decrease in SSP use occurred among Black PWID, and HIV prevalence among Black PWID was higher than that among Hispanic and White PWID. These findings underscore the importance of continuing and expanding HIV prevention programs and community-based strategies for PWID, such as those provided by SSPs, especially following service disruptions created by the COVID-19 pandemic (4). Efforts are needed to ensure that PWID have low-barrier access to comprehensive and integrated needs-based SSPs (where legally permissible) that include provision of sterile syringes and safe syringe disposal, HIV and hepatitis C virus (HCV) testing and referrals to HIV and HCV treatment, HIV preexposure prophylaxis, and treatment for substance use and mental health disorders.

Validation of a Crisis Standards of Care Model for Prioritization of Limited Resources During the Coronavirus Disease 2019 Crisis in an Urban, Safety-Net, Academic Medical Center.

OBJECTIVES: The coronavirus disease 2019 pandemic has overwhelmed healthcare resources even in wealthy nations, necessitating rationing of limited resources without previously established crisis standards of care protocols. In Massachusetts, triage guidelines were designed based on acute illness and chronic life-limiting conditions. In this study, we sought to retrospectively validate this protocol to cohorts of critically ill patients from our hospital. DESIGN: We applied our hospital-adopted guidelines, which defined severe and major chronic conditions as those associated with a greater than 50% likelihood of 1- and 5-year mortality, respectively, to a critically ill patient population. We investigated mortality for the same intervals. SETTING: An urban safety-net hospital ICU. PATIENTS: All adults hospitalized during April of 2015 and April 2019 identified through a clinical database search. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 365 admitted patients, 15.89% had one or more defined chronic life-limiting conditions. These patients had higher 1-year (46.55% vs 13.68%; p < 0.01) and 5-year (50.00% vs 17.22%; p < 0.01) mortality rates than those without underlying conditions. Irrespective of classification of disease severity, patients with metastatic cancer, congestive heart failure, end-stage renal disease, and neurodegenerative disease had greater than 50% 1-year mortality, whereas patients with chronic lung disease and cirrhosis had less than 50% 1-year mortality. Observed 1- and 5-year mortality for cirrhosis, heart failure, and metastatic cancer were more variable when subdivided into severe and major categories. CONCLUSIONS: Patients with major and severe chronic medical conditions overall had 46.55% and 50.00% mortality at 1 and 5 years, respectively. However, mortality varied between conditions. Our findings appear to support a crisis standards protocol which focuses on acute illness severity and only considers underlying conditions carrying a greater than 50% predicted likelihood of 1-year mortality. Modifications to the chronic lung disease, congestive heart failure, and cirrhosis criteria should be refined if they are to be included in future models.

The evolution trend of availability of China's community-based care services and its impact on the cognitive function of elderly people: 2008-2018.

BACKGROUND: To address the challenge of the aging population, community-based care services (CBCS) have been developed rapidly in China as a new way of satisfying the needs of elderly people. Few studies have described the evolution trend of availability of CBCS in rural and urban areas and evaluated their effectiveness. This study aims to show the availability of China's CBCS and further analyze the effect of the CBCS on the cognitive function of elderly people. METHODS: Longitudinal analysis was performed using data from the 2008 to 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS). A total of 23937 observations from 8421 elderly people were included in the study. The Chinese version of the Mini-Mental State Examination (MMSE) was used to assess cognitive function. We aggregated similar CBCS to generate three binary variable categories (daily life support, emotional comfort and entertainment services, medical support and health services) indicating the availability of CBCS (1 = yes, 0 = no). Multilevel growth models were employed to estimate the association between CBCS and cognitive function while adjusting for many demographic and socioeconomic characteristics. RESULTS: The availability of CBCS increased a lot from 2008 to 2018 in China. Although the availability of CBCS in urban areas was higher than that in rural areas in 2008, by 2018 the gap narrowed significantly. Emotional comfort and entertainment services (B = 0.331, 95% CI = 0.090 to 0.572) and medical support and health services (B = 1.041, 95% CI = 0.854 to 1.228) were significantly and positively associated with cognitive function after adjusting for the covariates. CONCLUSION: There was a significant increase in the availability of CBCS from 2008 to 2018 in China. This study sheds light on the positive correlation between CBCS and cognitive function among Chinese elderly individuals. The results suggest that policymakers should pay more attention to the development of CBCS and the equity of the supply of CBCS in urban and rural areas.

Modelling COVID-19 severity in the Republic of Ireland using patient co-morbidities, socioeconomic profile and geographic location, February to November 2020.

Understanding patient progression from symptomatic COVID-19 infection to a severe outcome represents an important tool for improved diagnoses, surveillance, and triage. A series of models have been developed and validated to elucidate hospitalization, admission to an intensive care unit (ICU) and mortality in patients from the Republic of Ireland. This retrospective cohort study of patients with laboratory-confirmed symptomatic COVID-19 infection included data extracted from national COVID-19 surveillance forms (i.e., age, gender, underlying health conditions, occupation) and geographically-referenced potential predictors (i.e., urban/rural classification, socio-economic profile). Generalised linear models and recursive partitioning and regression trees were used to elucidate COVID-19 progression. The incidence of symptomatic infection over the study-period was 0.96% (n = 47,265), of whom 3781 (8%) required hospitalisation, 615 (1.3%) were admitted to ICU and 1326 (2.8%) died. Models demonstrated an increasingly efficacious fit for predicting hospitalization [AUC 0.816 (95% CI 0.809, 0.822)], admission to ICU [AUC 0.885 (95% CI 0.88 0.89)] and death [AUC of 0.955 (95% CI 0.951 0.959)]. Severe obesity (BMI ≥ 40) was identified as a risk factor across all prognostic models; severely obese patients were substantially more likely to receive ICU treatment [OR 19.630] or die [OR 10.802]. Rural living was associated with an increased risk of hospitalization (OR 1.200 (95% CI 1.143-1.261)]. Urban living was associated with ICU admission [OR 1.533 (95% CI 1.606-1.682)]. Models provide approaches for predicting COVID-19 prognoses, allowing for evidence-based decision-making pertaining to targeted non-pharmaceutical interventions, risk-based vaccination priorities and improved patient triage.

Are We Reaching Everyone? A Cross-Sectional Study of Telehealth Inequity in the COVID-19 Pandemic in an Urban Academic Pediatric Primary Care Clinic.

The COVID-19 (coronavirus disease 2019) pandemic brought rapid expansion of pediatric telehealth to maintain patient access to care while decreasing COVID-19 community spread. We designed a retrospective, serial, cross-sectional study to investigate if telehealth implementation at an academic pediatric practice led to disparities in health care access. Significant differences were found in pre-COVID-19 versus during COVID-19 patient demographics. Patients seen during COVID-19 were more likely to be younger, White/Caucasian or Asian, English speaking, and have private insurance. They were less likely to be Black/African American or Latinx and request interpreters. Age was the only significant difference in patient demographics between in-person and telehealth visits during COVID-19. A multivariate regression showed older age as a significant positive predictor of having a video visit and public insurance as a significant negative predictor. Our study demonstrates telehealth disparities based on insurance existed at our clinic as did inequities in who was seen before versus during COVID-19.

Exploring the behavioral determinants of COVID-19 vaccine acceptance among an urban population in Bangladesh: Implications for behavior change interventions.

BACKGROUND: While vaccines ensure individual protection against COVID-19 infection, delay in receipt or refusal of vaccines will have both individual and community impacts. The behavioral factors of vaccine hesitancy or refusal are a crucial dimension that need to be understood in order to design appropriate interventions. The aim of this study was to explore the behavioral determinants of COVID-19 vaccine acceptance and to provide recommendations to increase the acceptance and uptake of COVID-19 vaccines in Bangladesh. METHODS: We employed a Barrier Analysis (BA) approach to examine twelve potential behavioral determinants (drawn from the Health Belief Model [HBM] and Theory of Reasoned Action [TRA]) of intended vaccine acceptance. We conducted 45 interviews with those who intended to take the vaccine (Acceptors) and another 45 interviews with those who did not have that intention (Non-acceptors). We performed data analysis to find statistically significant differences and to identify which beliefs were most highly associated with acceptance and non-acceptance with COVID-19 vaccines. RESULTS: The behavioral determinants associated with COVID-19 vaccine acceptance in Dhaka included perceived social norms, perceived safety of COVID-19 vaccines and trust in them, perceived risk/susceptibility, perceived self-efficacy, perceived positive and negative consequences, perceived action efficacy, perceived severity of COVID-19, access, and perceived divine will. In line with the HBM, beliefs about the disease itself were highly predictive of vaccine acceptance, and some of the strongest statistically-significant (p<0.001) predictors of vaccine acceptance in this population are beliefs around both injunctive and descriptive social norms. Specifically, Acceptors were 3.2 times more likely to say they would be very likely to get a COVID-19 vaccine if a doctor or nurse recommended it, twice as likely to say that most people they know will get a vaccine, and 1.3 times more likely to say that most close family and friends will get a vaccine. The perceived safety of vaccines was found to be important since Non-acceptors were 1.8 times more likely to say that COVID-19 vaccines are "not safe at all". Beliefs about one's risk of getting COVID-19 disease and the severity of it were predictive of being a vaccine acceptor: Acceptors were 1.4 times more likely to say that it was very likely that someone in their household would get COVID-19, 1.3 times more likely to say that they were very concerned about getting COVID-19, and 1.3 times more likely to say that it would be very serious if someone in their household contracted COVID-19. Other responses of Acceptors on what makes immunization easier may be helpful in programming to boost acceptance, such as providing vaccination through government health facilities, schools, and kiosks, and having vaccinators maintain proper COVID-19 health and safety protocols. CONCLUSION: An effective behavior change strategy for COVID-19 vaccines uptake will need to address multiple beliefs and behavioral determinants, reducing barriers and leveraging enablers identified in this study. National plans for promoting COVID-19 vaccination should address the barriers, enablers, and behavioral determinants found in this study in order to maximize the impact on COVID-19 vaccination acceptance.

Measuring Public Concern About COVID-19 in Japanese Internet Users Through Search Queries: Infodemiological Study.

BACKGROUND: COVID-19 has disrupted lives and livelihoods and caused widespread panic worldwide. Emerging reports suggest that people living in rural areas in some countries are more susceptible to COVID-19. However, there is a lack of quantitative evidence that can shed light on whether residents of rural areas are more concerned about COVID-19 than residents of urban areas. OBJECTIVE: This infodemiology study investigated attitudes toward COVID-19 in different Japanese prefectures by aggregating and analyzing Yahoo! JAPAN search queries. METHODS: We measured COVID-19 concerns in each Japanese prefecture by aggregating search counts of COVID-19-related queries of Yahoo! JAPAN users and data related to COVID-19 cases. We then defined two indices-the localized concern index (LCI) and localized concern index by patient percentage (LCIPP)-to quantitatively represent the degree of concern. To investigate the impact of emergency declarations on people's concerns, we divided our study period into three phases according to the timing of the state of emergency in Japan: before, during, and after. In addition, we evaluated the relationship between the LCI and LCIPP in different prefectures by correlating them with prefecture-level indicators of urbanization. RESULTS: Our results demonstrated that the concerns about COVID-19 in the prefectures changed in accordance with the declaration of the state of emergency. The correlation analyses also indicated that the differentiated types of public concern measured by the LCI and LCIPP reflect the prefectures' level of urbanization to a certain extent (ie, the LCI appears to be more suitable for quantifying COVID-19 concern in urban areas, while the LCIPP seems to be more appropriate for rural areas). CONCLUSIONS: We quantitatively defined Japanese Yahoo users' concerns about COVID-19 by using the search counts of COVID-19-related search queries. Our results also showed that the LCI and LCIPP have external validity.

Patient Satisfaction with Telephone Versus Video-Televisits: A Cross-Sectional Survey of an Urban, Multiethnic Population.

OBJECTIVE: To examine differences between telephone and video-televisits and identify whether visit modality is associated with satisfaction in an urban, academic general urology practice. METHODS: A cross sectional analysis of patients who completed a televisit at our urology practice (summer 2020) was performed. A Likert-based satisfaction telephone survey was offered to patients within 7 days of their televisit. Patient demographics, televisit modality (telephone vs video), and outcomes of the visit (eg follow-up visit scheduled, orders placed) were retrospectively abstracted from each chart and compared between the telephone and video cohorts. Multivariate regression analysis was used to evaluate variables associated with satisfaction while controlling for potential confounders. RESULTS: A total of 269 patients were analyzed. 73% (196/269) completed a telephone televisit. Compared to the video cohort, the telephone cohort was slightly older (mean 58.8 years vs. 54.2 years, P = .03). There were no significant differences in the frequency of orders placed for medication changes, labs, imaging, or for in-person follow-up visits within 30 days between cohorts. Survey results showed overall 84.7% patients were satisfied, and there was no significant difference between the telephone and video cohorts. Visit type was not associated with satisfaction on multivariable analyses, while use of an interpreter [OR:8.13 (1.00-65.94); P = .05], labs ordered [OR:2.74 (1.12-6.70); P = .03] and female patient gender [OR:2.28 (1.03-5.03); P = .04] were significantly associated with satisfaction. CONCLUSION: Overall, most patients were satisfied with their televisit. Additionally, telephone- and video-televisits were similar regarding patient opinions, patient characteristics, and visit outcome. Efforts to increase access and coverage of telehealth, particularly telephone-televisits, should continue past the COVID-19 pandemic.