Using Location Intelligence to Evaluate the COVID-19 Vaccination Campaign in the United States: Spatiotemporal Big Data Analysis.

BACKGROUND: Highly effective COVID-19 vaccines are available and free of charge in the United States. With adequate coverage, their use may help return life back to normal and reduce COVID-19-related hospitalization and death. Many barriers to widespread inoculation have prevented herd immunity, including vaccine hesitancy, lack of vaccine knowledge, and misinformation. The Ad Council and COVID Collaborative have been conducting one of the largest nationwide targeted campaigns ("It's Up to You") to communicate vaccine information and encourage timely vaccination across the United States. More than 300 major brands, digital and print media companies, and community-based organizations support the campaigns to reach distinct audiences. OBJECTIVE: The goal of this study was to use aggregated mobility data to assess the effectiveness of the campaign on COVID-19 vaccine uptake. METHODS: Campaign exposure data were collected from the Cuebiq advertising impact measurement platform consisting of about 17 million opted-in and deidentified mobile devices across the country. A Bayesian spatiotemporal hierarchical model was developed to assess campaign effectiveness through estimating the association between county-level campaign exposure and vaccination rates reported by the Centers for Disease Control and Prevention. To minimize potential bias in exposure to the campaign, the model included several control variables (eg, age, race or ethnicity, income, and political affiliation). We also incorporated conditional autoregressive residual models to account for apparent spatiotemporal autocorrelation. RESULTS: The data set covers a panel of 3104 counties from 48 states and the District of Columbia during a period of 22 weeks (March 29 to August 29, 2021). Officially launched in February 2021, the campaign reached about 3% of the anonymous devices on the Cuebiq platform by the end of March, which was the start of the study period. That exposure rate gradually declined to slightly above 1% in August 2021, effectively ending the study period. Results from the Bayesian hierarchical model indicate a statistically significant positive association between campaign exposure and vaccine uptake at the county level. A campaign that reaches everyone would boost the vaccination rate by 2.2% (95% uncertainty interval: 2.0%-2.4%) on a weekly basis, compared to the baseline case of no campaign. CONCLUSIONS: The "It's Up to You" campaign is effective in promoting COVID-19 vaccine uptake, suggesting that a nationwide targeted mass media campaign with multisectoral collaborations could be an impactful health communication strategy to improve progress against this and future pandemics. Methodologically, the results also show that location intelligence and mobile phone-based monitoring platforms can be effective in measuring impact of large-scale digital campaigns in near real time.

Impact of Public Health and Social Measures on the COVID-19 Pandemic in the United States and Other Countries: Descriptive Analysis.

BACKGROUND: The United States of America has the highest global number of COVID-19 cases and deaths, which may be due in part to delays and inconsistencies in implementing public health and social measures (PHSMs). OBJECTIVE: In this descriptive analysis, we analyzed the epidemiological evidence for the impact of PHSMs on COVID-19 transmission in the United States and compared these data to those for 10 other countries of varying income levels, population sizes, and geographies. METHODS: We compared PHSM implementation timing and stringency against COVID-19 daily case counts in the United States and against those in Canada, China, Ethiopia, Japan, Kazakhstan, New Zealand, Singapore, South Korea, Vietnam, and Zimbabwe from January 1 to November 25, 2020. We descriptively analyzed the impact of border closures, contact tracing, household confinement, mandated face masks, quarantine and isolation, school closures, limited gatherings, and states of emergency on COVID-19 case counts. We also compared the relationship between global socioeconomic indicators and national pandemic trajectories across the 11 countries. PHSMs and case count data were derived from various surveillance systems, including the Health Intervention Tracking for COVID-19 database, the World Health Organization PHSM database, and the European Centre for Disease Prevention and Control. RESULTS: Implementing a specific package of 4 PHSMs (quarantine and isolation, school closures, household confinement, and the limiting of social gatherings) early and stringently was observed to coincide with lower case counts and transmission durations in Vietnam, Zimbabwe, New Zealand, South Korea, Ethiopia, and Kazakhstan. In contrast, the United States implemented few PHSMs stringently or early and did not use this successful package. Across the 11 countries, national income positively correlated (r=0.624) with cumulative COVID-19 incidence. CONCLUSIONS: Our findings suggest that early implementation, consistent execution, adequate duration, and high adherence to PHSMs represent key factors of reducing the spread of COVID-19. Although national income may be related to COVID-19 progression, a country's wealth appears to be less important in controlling the pandemic and more important in taking rapid, centralized, and consistent public health action.

Burden of mental distress in the US associated with trust in media for COVID-19 information.

During the COVID-19 pandemic, news and social media outlets have played a major role in dissemination of information. This analysis aimed to study the association between trust in social and traditional media and experiences of mental distress among a representative sample of US adults. Data for this study came from National Pandemic Pulse, a cross-sectional, nationally representative survey that sampled participants on the Dynata platform. Participants included 6435 adults surveyed between 15-23 December 2020. Ordinal logistic regression analyses examined the associations of trust in (i) social media, (ii) print media, (iii) broadcast TV and (iv) cable TV, for COVID-19-related information with self-reported mental distress (4-item Patient Health Questionnaire), controlling for sociodemographics and census region. Compared with those who distrusted social media, those who trusted social media had 2.09 times (95% CI = 1.84-2.37) greater adjusted odds of being in a more severe category of mental distress. In contrast, compared with those who distrusted print media, those who trusted print media had 0.80 times (95% CI = 0.69-0.93) lower adjusted odds of being in a more severe category of mental distress. No significant associations were found between mental distress and trust in broadcast or cable TV for accessing news about COVID-19. Trust in different news outlets may be associated with mental distress during public health emergencies like the COVID-19 pandemic. Future studies should explore mechanisms behind these associations, including adherence to best practices for crisis reporting among different media sources and exposure of individuals to misinformation.

During the COVID-19 pandemic, both, traditional channels like print, TV and cable news, as well as social media, have been major sources to obtain news about the pandemic. In this manuscript, we study the association between trust in social and traditional media and symptoms of mental distress among a nationally representative sample of 6435 US adults surveyed in December 2020. Our findings show that those who reported trusting traditional print media were less likely to report more severe mental distress. Conversely, those who reported trusting social media were more likely to report more severe levels of mental distress. This highlights the urgent need for understanding the diffusion patterns of misinformation and rumors that circulate on social media, and consumers' reactions to them. It is important that during a public health emergency, we follow best practices for crisis communication to reduce panic, address uncertainty, promote protective behaviors and mental health.

The Baltimore Urban Food Distribution (BUD) App: Study Protocol to Assess the Feasibility of a Food Systems Intervention.

Low-income urban communities in the United States commonly lack ready access to healthy foods. This is due in part to a food distribution system that favors the provision of high-fat, high-sugar, high-sodium processed foods to small retail food stores, and impedes their healthier alternatives, such as fresh produce. The Baltimore Urban food Distribution (BUD) study is a multilevel, multicomponent systems intervention that aims to improve healthy food access in low-income neighborhoods of Baltimore, Maryland. The primary intervention is the BUD application (app), which uses the power of collective purchasing and delivery to affordably move foods from local producers and wholesalers to the city's many corner stores. We will implement the BUD app in a sample of 38 corner stores, randomized to intervention and comparison. Extensive evaluation will be conducted at each level of the intervention to assess overall feasibility and effectiveness via mixed methods, including app usage data, and process and impact measures on suppliers, corner stores, and consumers. BUD represents one of the first attempts to implement an intervention that engages multiple levels of a local food system. We anticipate that the app will provide a financially viable alternative for Baltimore corner stores to increase their stocking and sales of healthier foods, subsequently increasing healthy food access and improving diet-related health outcomes for under-resourced consumers. The design of the intervention and the evaluation plan of the BUD project are documented here, including future steps for scale-up. Trial registration #: NCT05010018.

Schooling amidst a pandemic in the United States: Parents' perceptions about reopening schools and anticipated challenges during COVID-19.

INTRODUCTION: During the COVID-19 pandemic, numerous states in the United States instituted measures to close schools or shift them to virtual platforms. Understanding parents' preferences for sending their children back to school, and their experiences with distance learning is critical for informing school reopening guidelines. This study characterizes parents' plans to return their children to school, and examines the challenges associated with school closures during the 2020-2021 academic year. METHODS: A national-level cross-sectional online survey was conducted in September 2020. Focusing on a subset of 510 respondents, who were parents of school-aged children, we examined variations in parents' plans for their children to return to school by their demographic and family characteristics, and challenges they anticipated during the school-year using multivariable logistic regressions. RESULTS: Fifty percent of respondents (n = 249) said that they would send their children back to school, 18% (n = 92) stated it would depend on what the district plans for school reopening, and 32% (n = 160) would not send their children back to school. No demographic characteristics were significantly associated with parents plans to not return their children to school. Overall, parents reported high-level of access to digital technology to support their child's learning needs (84%). However, those who reported challenges with distance learning due to a lack of childcare were less likely to not return their children to school (aOR = 0.33, 95% CI: 0.17, 0.64). Parents who reported requiring supervision after school had higher odds of having plans to not return their children to school (aOR = 1.97, 95% CI: 1.03, 3.79). Parents viewed COVID-19 vaccines and face-masks important for resuming in-person classes. DISCUSSION: About one-third of parents objected to their children returning to school despite facing challenges with distance learning. Besides access to vaccines and face-masks, our findings highlight the need to better equip parents to support remote learning, and childcare.

Burden of mental distress in the United States is associated with delayed medical visits and missed prescription refills during the COVID-19 pandemic.

The COVID-19 pandemic has contributed to poor health due to a decrease in healthcare utilization and those with mental health problems may be impacted. For this analysis, data came from a cross-sectional, nationally representative December 2020 survey. Logistic regression analyses examined associations between (1) mental distress and delayed medical visits, (2) mental distress and missed prescription refills, controlling for sociodemographics, pre-existing chronic conditions, and access to health insurance. We found that, compared to those that exhibited normal levels of mental distress, those with mild (aOR = 2.83, 95% CI = 2.47-3.24), moderate (aOR = 3.43, 95% CI = 2.95-3.99), and severe (aOR = 4.96, 95% CI = 4.21-5.84) mental distress showed greater odds of delaying medical visits. Similarly, compared to those that exhibited normal levels of mental distress, those with mild (aOR =3.93, 95% CI = 3.04-5.09), moderate (aOR =6.52, 95% CI = 5.07-8.43), and severe (aOR =8.69, 95% CI = 6.71-11.32) mental distress showed greater odds of missing prescription refills. Our study shows that individuals who showed signs of mental distress had increased odds of delayed medical visits and missed prescription refills, compared to those that showed normal levels of mental distress.

Changes in prenatal care and vaccine willingness among pregnant women during the COVID-19 pandemic.

INTRODUCTION: Concerns about SARS-CoV-2 infection risk in health care settings have resulted in changes in prenatal care and birth plans, such as shifts to in-person visits and increased Cesarean delivery. These changes may affect quality of care and limit opportunities for clinicians to counsel pregnant individuals, who are at higher risk of severe COVID-19 disease and adverse pregnancy outcomes, about prevention and vaccination. METHODS: We conducted a cross-sectional online survey of United States adults on changes in prenatal care, COVID-19 vaccine willingness, and reasons for unwillingness to receive a vaccine. We summarized changes in access to care and examined differences in vaccine willingness between pregnant and propensity-score matched non-pregnant controls using chi-squared tests and multivariable conditional logistic regression. RESULTS: Between December 15-23, 2020, 8481 participants completed the survey, of which 233 were pregnant. Three-quarters of pregnant women (n = 186) experienced a change in prenatal care, including format of care (n = 84, 35%) and reduced visits (n = 69, 24%). Two-thirds experienced a change in birth plans, from a hospital birth to home birth (n = 45, 18%) or vaginal birth to a Cesarean delivery (n = 42, 17%). Although 40% of pregnant women (n = 78) were unwilling to receive COVID-19 vaccination, they had higher, though non-significant, odds of reporting willingness to receive vaccination compared to similar non-pregnant women (aOR 1.38, 95% CI: 0.95, 2.00). CONCLUSION: To support pregnant women through the perinatal care continuum, maternity care teams should develop protocols to foster social support, patient-centered education around infection prevention that focuses on improved risk perception, expected changes in care due to COVID-19, and vaccine effectiveness and safety.

Promised and Lottery Airtime Incentives to Improve Interactive Voice Response Survey Participation Among Adults in Bangladesh and Uganda: Randomized Controlled Trial

Background: Increased mobile phone penetration allows the interviewing of respondents using interactive voice response surveys in low- and middle-income countries. However, there has been little investigation of the best type of incentive to obtain data from a representative sample in these countries. Objective: We assessed the effect of different airtime incentives options on cooperation and response rates of an interactive voice response survey in Bangladesh and Uganda. Methods: The open-label randomized controlled trial had three arms: (1) no incentive (control), (2) promised airtime incentive of 50 Bangladeshi Taka (US $0.60;1 BDT is approximately equivalent to US $0.012) or 5000 Ugandan Shilling (US $1.35;1 UGX is approximately equivalent to US $0.00028), and (3) lottery incentive (500 BDT and 100,000 UGX), in which the odds of winning were 1:20. Fully automated random-digit dialing was used to sample eligible participants aged ≥18 years. The risk ratios (RRs) with 95% confidence intervals for primary outcomes of response and cooperation rates were obtained using log-binomial regression. Results: Between June 14 and July 14, 2017, a total of 546,746 phone calls were made in Bangladesh, with 1165 complete interviews being conducted. Between March 26 and April 22, 2017, a total of 178,572 phone calls were made in Uganda, with 1248 complete interviews being conducted. Cooperation rates were significantly higher for the promised incentive (Bangladesh: 39.3%;RR 1.38, 95% CI 1.24-1.55, P<.001;Uganda: 59.9%;RR 1.47, 95% CI 1.33-1.62, P<.001) and the lottery incentive arms (Bangladesh: 36.6%;RR 1.28, 95% CI 1.15-1.45, P<.001;Uganda: 54.6%;RR 1.34, 95% CI 1.21-1.48, P<.001) than those for the control arm (Bangladesh: 28.4%;Uganda: 40.9%). Similarly, response rates were significantly higher for the promised incentive (Bangladesh: 26.5%%;RR 1.26, 95% CI 1.14-1.39, P<.001;Uganda: 41.2%;RR 1.27, 95% CI 1.16-1.39, P<.001) and lottery incentive arms (Bangladesh: 24.5%%;RR 1.17, 95% CI 1.06-1.29, P=.002;Uganda: 37.9%%;RR 1.17, 95% CI 1.06-1.29, P=.001) than those for the control arm (Bangladesh: 21.0%;Uganda: 32.4%). Conclusions: Promised or lottery airtime incentives improved survey participation and facilitated a large sample within a short period in 2 countries. Trial Registration: ClinicalTrials.gov NCT03773146;http://clinicaltrials.gov/ct2/show/NCT03773146

Food Insecurity and Delayed or Forgone Medical Care During the COVID-19 Pandemic.

Objectives. To describe food insecurity in the United States in December 2020 and examine associations with underuse of medical care during the COVID-19 pandemic. Methods. We fielded a nationally representative Web-based survey in December 2020 (n = 8318). Multivariable logistic regression models and predicted probabilities were used to evaluate factors associated with food insecurity and compare the likelihood of delaying or forgoing medical care because of cost concerns by food security status. Results. In December 2020, 18.8% of US adults surveyed reported experiencing food insecurity. Elevated odds of food insecurity were observed among non-Hispanic Black, Hispanic, and low-income respondents. Experiencing food insecurity was significantly associated with a greater likelihood of forgoing any type of medical care as a result of cost concerns. Conclusions. Food insecurity during the COVID-19 pandemic disproportionately affected non-White and low-income individuals. Experiencing food insecurity was a significant risk factor for delaying or forgoing medical care, an association that could have cumulative short- and long-term health effects. Public Health Implications. Comprehensive policies that target the most at-risk groups are needed to address the high rates of food insecurity in the United States and mitigate its adverse health effects. (Am J Public Health. 2022;112(5):776-785. https://doi.org/10.2105/AJPH.2022.306724).

COVID-19 risk perceptions of social interaction and essential activities and inequity in the USA: results from a nationally representative survey.

INTRODUCTION: SARS-CoV-2 has disproportionately affected disadvantaged communities across the USA. Risk perceptions for social interactions and essential activities during the COVID-19 pandemic may vary by sociodemographic factors. METHODS: We conducted a nationally representative online survey of 1592 adults in the USA to understand risk perceptions related to transmission of COVID-19 for social (eg, visiting friends) and essential activities (eg, medical visits or returning to work). We assessed relationships for activities using bivariate comparisons and multivariable logistic regression modelling, between responses of safe and unsafe, and participant characteristics. Data were collected and analysed in 2020. RESULTS: Among 1592 participants, risk perceptions of unsafe for 13 activities ranged from 29.2% to 73.5%. Large gatherings, indoor dining and visits with elderly relatives had the highest proportion of unsafe responses (>58%), while activities outdoor, accessing healthcare and going to the grocery store had the lowest (<36%). Older respondents were more likely to view social gatherings and indoor activities as unsafe but less likely for other activities, such as going to the grocery store and accessing healthcare. Compared with white/Caucasian respondents, black/African-American and Hispanic/Latino respondents were more likely to view activities such as dining and visiting friends outdoor as unsafe. Generally, men versus women, Republicans versus Democrats and independents, and individuals with higher versus lower income were more likely to view activities as safe. CONCLUSION: Evidence-based interventions should be tailored to sociodemographic differences in risk perception, access to information and health behaviours when implementing efforts to control the COVID-19 pandemic.

Rapid Real-time Tracking of Nonpharmaceutical Interventions and Their Association With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Positivity: The Coronavirus Disease 2019 (COVID-19) Pandemic Pulse Study.

BACKGROUND: Current mitigation strategies for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rely on the population-wide adoption of nonpharmaceutical interventions (NPIs). Monitoring the adoption of NPIs and their associations with SARS-CoV-2 infection history can provide key information for public health. METHODS: We sampled 1030 individuals in Maryland from 17-28 June 2020 to capture sociodemographically and geographically resolved information about NPI adoption and access to SARS-CoV-2 testing, and examine associations with self-reported SARS-CoV-2 positivity. RESULTS: Overall, 92% reported traveling for essential services and 66% visited friends/family. Use of public transport was reported by 18%. In total, 68% reported strict social distancing indoors and 53% reported strict masking indoors; indoor social distancing was significantly associated with age, and race/ethnicity and income were associated with masking. Overall, 55 participants (5.3%) self-reported ever testing positive for SARS-CoV-2, with strong dose-response relationships between several forms of movement frequency and SARS-CoV-2 positivity. In a multivariable analysis, a history of SARS-CoV-2 infection was negatively associated with strict social distancing (adjusted odds ratio [aOR] for outdoor social distancing, 0.10; 95% confidence interval, .03-.33). Only public transport use (aOR for >7 times vs never, 4.3) and visiting a place of worship (aOR for ≥3 times vs never, 16.0) remained significantly associated with SARS-CoV-2 infection after adjusting for strict social distancing and demographics. CONCLUSIONS: These results support public health messaging that strict social distancing during most activities can reduce SARS-CoV-2 transmission. Additional considerations are needed for indoor activities with large numbers of persons (places of worship and public transportation), where even NPIs may not be possible or sufficient.

Food insecurity is adversely associated with psychological distress, anxiety and depression during the COVID-19 pandemic.

Early COVID-19 pandemic data showed a spike in both food insecurity and poor mental health. The purpose of this study was to examine the relationship between food insecurity and mental health outcomes nine months after the start of the COVID-19 pandemic. A national survey of adults 18 years and older was administered in December 2020 (N = 8,355). Multivariable logistic models and post-estimation margins commands were used to show the predicted probability of mental health outcomes (psychological distress, anxiety, and depression) by food security status. The majority of participants (68.5%) reported high/marginal food security, 15.5% had low food security, and 16.0% had very low food security. There was a strong dose response relationship between food insecurity and higher psychological distress, anxiety and depression. Fewer than one in five adults with high/marginal food security screened positive for all three mental health outcomes, while more than two in five adults with low food security screened positive for psychological distress (39.9%), depression (41.7%) and anxiety (41.3%). Among adults with very low food security, nearly half screened positive for psychological distress (47.7%), depression (48.1%) and anxiety (49.4%). Younger adults had higher prevalence of psychological distress compared to older adults regardless of food security status. Food insecure adults, particularly young adults, have higher rates of psychological distress, anxiety, and depression than their food secure counterparts. Facilitating opportunities to connect at risk populations with food assistance and affordable mental healthcare should be prioritized as the pandemic continues and beyond.

LB-10. Rapid Assessments of Non-Pharmaceutical Intervention Uptake and Population Mobility Patterns Elucidate SARS-Cov-2 Transmission Dynamics

Background. Current mitigation strategies for SARS-CoV-2 rely on population- wide adoption of non-pharmaceutical interventions (NPIs). Monitoring NPI adoption, mobility patterns and their association with SARS-CoV-2 infection can provide key information for public health agencies and be used to calibrate transmission models. Methods. We used an online panel to accrue representative samples from Florida, Illinois, and Maryland (n=3,009, approximately 1,000 per state) from July 15-31, 2020 and capture socio-demographically and geographically resolved information about NPI adoption and mobility in the prior 2 weeks. Logistic regression was used to identify correlates of self-reported SARS-CoV-2 infection in the prior 2 weeks. Results. Overall, 96% reported traveling outside their home in the prior 2 weeks, the most common reason being to visit a grocery store/pharmacy (92%), followed by visiting friends/family (61%), and visiting a place of worship (23%);22% reporting public transportation use. In total, 44% of respondents reported always practicing social distancing and 40% reported always using a mask indoors and outdoors. Overall, 74 (2.5%) reported testing positive for SARS-CoV-2 in the prior 2 weeks, with strong dose-response relationships between several forms of movement frequency and SARS-CoV-2 positivity. Variables capturing mobility were all highly correlated with one another, suggesting there are clusters of individuals who engage in multiple activities (Figure);41% of positive cases engaged in all forms of mobility captured compared to 1% of those who did not test positive within the prior 2 weeks. Patterns of mobility and NPI uptake did not significantly differ by state;however, there were significant relationships with age, race/ethnicity, and gender. In multivariable models including adjustment for NPIs, significant relationships remained with public transportation, visiting a place of worship, and participating in outdoor group fitness activities. Conclusion. NPI adoption and mobility did not vary across these three states with variable policies and SARS-CoV-2 positivity rates. Rather, associations with recent positivity appear to be driven largely by mobility patterns and engagement in activities where NPI use may be challenging or inconsistent. (Figure Presented).

Factors Associated With Intention to Adopt mHealth Apps Among Dementia Caregivers With a Chronic Condition: Cross-sectional, Correlational Study.

BACKGROUND: In the United States, nearly 80% of family caregivers of people with dementia have at least one chronic condition. Dementia caregivers experience high stress and burden that adversely affect their health and self-management. mHealth apps can improve health and self-management among dementia caregivers with a chronic condition. However, mHealth app adoption by dementia caregivers is low, and reasons for this are not well understood. OBJECTIVE: The purpose of this study is to explore factors associated with dementia caregivers' intention to adopt mHealth apps for chronic disease self-management. METHODS: We conducted a cross-sectional, correlational study and recruited a convenience sample of dementia caregivers. We created a survey using validated instruments and collected data through computer-assisted telephone interviews and web-based surveys. Before the COVID-19 pandemic, we recruited dementia caregivers through community-based strategies, such as attending community events. After nationwide closures due to the pandemic, the team focused on web-based recruitment. Multiple logistic regression analyses were used to test the relationships between the independent and dependent variables. RESULTS: Our sample of 117 caregivers had an average age of 53 (SD 17.4) years, 16 (SD 3.3) years of education, and 4 (SD 2.5) chronic conditions. The caregivers were predominantly women (92/117, 78.6%) and minorities (63/117, 53.8%), experienced some to extreme income difficulties (64/117, 54.7%), and were the child or child-in-law (53/117, 45.3%) of the person with dementia. In logistic regression models adjusting for the control variables, caregiver burden (odds ratio [OR] 1.3, 95% CI 0.57-2.8; P=.57), time spent caregiving per week (OR 1.7, 95% CI 0.77-3.9; P=.18), and burden of chronic disease and treatment (OR 2.3, 95% CI 0.91-5.7; P=.08) were not significantly associated with the intention to adopt mHealth apps. In the final multiple logistic regression model, only perceived usefulness (OR 23, 95% CI 5.6-97; P<.001) and the interaction term for caregivers' education and burden of chronic disease and treatment (OR 31, 95% CI 2.2-430; P=.01) were significantly associated with their intention to adopt mHealth apps. Perceived ease of use (OR 2.4, 95% CI 0.67-8.7; P=.18) and social influence (OR 1.8, 95% CI 0.58-5.7; P=.31) were not significantly associated with the intention to adopt mHealth apps. CONCLUSIONS: When designing mHealth app interventions for dementia caregivers with a chronic condition, it is important to consider caregivers' perceptions about how well mHealth apps can help their self-management and which app features would be most useful for self-management. Caregiving factors may not be relevant to caregivers' intention to adopt mHealth apps. This is promising because mHealth strategies may overcome barriers to caregivers' self-management. Future research should investigate reasons why caregivers with a low education level and low burden of chronic disease and treatment have significantly lower intention to adopt mHealth apps for self-management.

Machine learning approach to dynamic risk modeling of mortality in COVID-19: a UK Biobank study.

The COVID-19 pandemic has created an urgent need for robust, scalable monitoring tools supporting stratification of high-risk patients. This research aims to develop and validate prediction models, using the UK Biobank, to estimate COVID-19 mortality risk in confirmed cases. From the 11,245 participants testing positive for COVID-19, we develop a data-driven random forest classification model with excellent performance (AUC: 0.91), using baseline characteristics, pre-existing conditions, symptoms, and vital signs, such that the score could dynamically assess mortality risk with disease deterioration. We also identify several significant novel predictors of COVID-19 mortality with equivalent or greater predictive value than established high-risk comorbidities, such as detailed anthropometrics and prior acute kidney failure, urinary tract infection, and pneumonias. The model design and feature selection enables utility in outpatient settings. Possible applications include supporting individual-level risk profiling and monitoring disease progression across patients with COVID-19 at-scale, especially in hospital-at-home settings.

Population risk factors for severe disease and mortality in COVID-19: A global systematic review and meta-analysis.

AIM: COVID-19 clinical presentation is heterogeneous, ranging from asymptomatic to severe cases. While there are a number of early publications relating to risk factors for COVID-19 infection, low sample size and heterogeneity in study design impacted consolidation of early findings. There is a pressing need to identify the factors which predispose patients to severe cases of COVID-19. For rapid and widespread risk stratification, these factors should be easily obtainable, inexpensive, and avoid invasive clinical procedures. The aim of our study is to fill this knowledge gap by systematically mapping all the available evidence on the association of various clinical, demographic, and lifestyle variables with the risk of specific adverse outcomes in patients with COVID-19. METHODS: The systematic review was conducted using standardized methodology, searching two electronic databases (PubMed and SCOPUS) for relevant literature published between 1st January 2020 and 9th July 2020. Included studies reported characteristics of patients with COVID-19 while reporting outcomes relating to disease severity. In the case of sufficient comparable data, meta-analyses were conducted to estimate risk of each variable. RESULTS: Seventy-six studies were identified, with a total of 17,860,001 patients across 14 countries. The studies were highly heterogeneous in terms of the sample under study, outcomes, and risk measures reported. A large number of risk factors were presented for COVID-19. Commonly reported variables for adverse outcome from COVID-19 comprised patient characteristics, including age >75 (OR: 2.65, 95% CI: 1.81-3.90), male sex (OR: 2.05, 95% CI: 1.39-3.04) and severe obesity (OR: 2.57, 95% CI: 1.31-5.05). Active cancer (OR: 1.46, 95% CI: 1.04-2.04) was associated with increased risk of severe outcome. A number of common symptoms and vital measures (respiratory rate and SpO2) also suggested elevated risk profiles. CONCLUSIONS: Based on the findings of this study, a range of easily assessed parameters are valuable to predict elevated risk of severe illness and mortality as a result of COVID-19, including patient characteristics and detailed comorbidities, alongside the novel inclusion of real-time symptoms and vital measurements.

The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology.

The ongoing coronavirus disease 2019 (COVID-19) pandemic has heightened discussion of the use of mobile phone data in outbreak response. Mobile phone data have been proposed to monitor effectiveness of non-pharmaceutical interventions, to assess potential drivers of spatiotemporal spread, and to support contact tracing efforts. While these data may be an important part of COVID-19 response, their use must be considered alongside a careful understanding of the behaviors and populations they capture. Here, we review the different applications for mobile phone data in guiding and evaluating COVID-19 response, the relevance of these applications for infectious disease transmission and control, and potential sources and implications of selection bias in mobile phone data. We also discuss best practices and potential pitfalls for directly integrating the collection, analysis, and interpretation of these data into public health decision making.