Ambulatory Clinician's Guide to Inpatient Service: An Innovative Rapid Onboarding Strategy for the COVID-19 Pandemic

Background and Significance  When hospitals are subject to prolonged surges in patients, such as during the coronavirus disease 2019 (COVID-19) pandemic, additional clinicians may be needed to care for the rapid increase of acutely ill patients. How might we quickly prepare a large number of ambulatory-based clinicians to care for hospitalized patients using the inpatient workflow of the electronic health record (EHR)? Objectives  The aim of the study is to create a successful training intervention which prepares ambulatory-based clinicians as they transition to inpatient services. Methods  We created a training guide with embedded videos that describes the workflow of an inpatient clinician. We delivered this intervention via an e-mail hyperlink, a static hyperlink inside of the EHR, and an on-demand hyperlink within the EHR. Results  In anticipation of the first peak of inpatients with COVID-19 in April 2020, the training manual was accessed 261 times by 167 unique users as clinicians anticipated being called into service. As our institution has not yet needed to deploy ambulatory-based clinicians for inpatient service, usage data of the training document is still pending. Conclusion  We intend that our novel implementation of a multimedia, highly accessible onboarding document with access from points inside and outside of the EHR will improve clinician performance and serve as a helpful example to other organizations during the COVID-19 pandemic and beyond.     

Rapid Implementation of a Complex,Multimodal Technology Response to COVID-19 at an Integrated Community-Based Health Care System

Background  The rapid spread of severe acute respiratory syndrome coronavirus-2 or SARS-CoV-2 necessitated a scaled treatment response to the novel coronavirus disease 2019 (COVID-19). Objective  This study aimed to characterize the design and rapid implementation of a complex, multimodal, technology response to COVID-19 led by the Intermountain Healthcare''s (Intermountain''s) Care Transformation Information Systems (CTIS) organization to build pandemic surge capacity. Methods  Intermountain has active community-spread cases of COVID-19 that are increasing. We used the Centers for Disease Control and Prevention Pandemic Intervals Framework (the Framework) to characterize CTIS leadership''s multimodal technology response to COVID-19 at Intermountain. We provide results on implementation feasibility and sustainability of health information technology (HIT) interventions as of June 30, 2020, characterize lessons learned and identify persistent barriers to sustained deployment. Results  We characterize the CTIS organization''s multimodal technology response to COVID-19 in five relevant areas of the Framework enabling (1) incident management, (2) surveillance, (3) laboratory testing, (4) community mitigation, and (5) medical care and countermeasures. We are seeing increased use of traditionally slow-to-adopt technologies that create additional surge capacity while sustaining patient safety and care quality. CTIS leadership recognized early that a multimodal technology intervention could enable additional surge capacity for health care delivery systems with a broad geographic and service scope. A statewide central tracking system to coordinate capacity planning and management response is needed. Order interoperability between health care systems remains a barrier to an integrated response. Conclusion  The rate of future pandemics is estimated to increase. The pandemic response of health care systems, like Intermountain, offers a blueprint for the leadership role that HIT organizations can play in mainstream care delivery, enabling a nimbler, virtual health care delivery system that is more responsive to current and future needs.     

Trends in adolescent COVID-19 vaccination receipt and parental intent to vaccinate their adolescent children,United States,July to October, 2021

IntroductionThere was a five-fold increase in COVID-19 hospitalization case counts among children and adolescents between June and October 2021. However, polls suggest that adolescent COVID-19 vaccination coverage has plateaued in the United States.MethodsUsing the Census Bureau’s Household Pulse Survey, we assessed trends in COVID-19 vaccination among adolescents ages 12–17 years, parents’ intention to vaccinate their adolescent children, and their reasons for not intending to vaccinate their children from July to October 2021 using a large, nationally representative survey of U.S. households (n = 59,424). Trends in COVID-19 adolescent vaccination coverage, nationally and by sociodemographic characteristics, factors associated with adolescent vaccination status and parental intent to vaccinate their adolescent children, as well as changes in reasons for non-vaccination were examined using regression models.ResultsReceipt of ≥1 dose of a COVID-19 vaccine among adolescents ages 12–17 years increased five percentage points, from 56% (July) to 61% (October), with significant increases across most sociodemographic variables. However, there were no significant changes in parental intention to vaccinate their adolescent children during the same time period. Approximately one-quarter of parents were unsure about or reluctant to vaccinate their children, which remained consistent from July to October. Among those who had not vaccinated their children, lack of trust in the government and vaccines, and the belief that the COVID-19 vaccine is not needed or effective, was higher in October compared to July.ConclusionsParental intention to vaccinate their children has remained relatively stable throughout the late summer and early fall of 2021. Encouraging paediatricians to discuss the importance and safety of COVID-19 vaccines, addressing concerns and misinformation, as well as recommending and offering vaccines are important for increasing parental confidence in vaccines as well as vaccination uptake among adolescents.

KEY MESSAGE

• Receipt of ≥1 dose of a COVID-19 vaccine among adolescents ages 12–17 years increased five percentage points, from 56% (July) to 61% (October), with significant increases across most sociodemographic variables.
• Approximately one quarter of parents were unsure about or reluctant to vaccinate their children, which remained consistent from July to October.
• Encouraging paediatricians to discuss the importance and safety of COVID-19 vaccines, addressing concerns and misinformation, as well as recommending and offering vaccines is important for increasing parental confidence in vaccines as well as vaccination uptake among adolescents.

     

Do You Know What Your Scribe Did Last Spring? The Impact of COVID-19 on Medical Scribe Workflow

Objective  To understand the impact of the shift to virtual medicine induced by coronavirus disease 2019 (COVID-19) has had on the workflow of medical scribes. Design  This is a prospective observational survey-based study. Setting  This study was conducted at academic medical center in the United States. Participants  Seventy-four scribes working in ambulatory practices within an academic medical center. Interventions  All medical scribes received a survey assessing their workflow since beginning of COVID-19 restrictions. Primary and Secondary Outcomes  To assess the current workflow of medical scribes since transition to virtual care. Secondary outcomes are to assess the equipment used and location of their new workflow. Results  Fifty-seven scribes completed the survey. Overall 42% of scribes have transitioned to remote scribing with 97% serving as remote scribes for remote visits. This workflow is conducted at home and with personal equipment. Of those not working as scribes, 46% serve in preclinic support, with a wide range of EHR-related activities being reported. The remaining scribes have been either redeployed or furloughed. Conclusion  The rapid transition to virtual care brought about by COVID-19 has resulted in a dramatic shift in scribe workflow with the adoption of a previously unreported workflow of remote scribing for virtual care. Additional work is now needed to ensure these new workflows are safe and effective and that scribes are trained to work in this new paradigm.     

Health Intelligence Atlas: A Core Tool for Public Health Intelligence

Background  The dramatic increase in complexity and volume of health data has challenged traditional health systems to deliver useful information to their users. The novel coronavirus disease 2019 (COVID-19) pandemic has further exacerbated this problem and demonstrated the critical need for the 21st century approach. This approach needs to ingest relevant, diverse data sources, analyze them, and generate appropriate health intelligence products that enable users to take more effective and efficient actions for their specific challenges. Objectives  This article characterizes the Health Intelligence Atlas (HI-Atlas) development and implementation to produce Public Health Intelligence (PHI) that supports identifying and prioritizing high-risk communities by public health authorities. The HI-Atlas moves from post hoc observations to a proactive model-based approach for preplanning COVID-19 vaccine preparedness, distribution, and assessing the effectiveness of those plans. Results  Details are presented on how the HI-Atlas merged traditional surveillance data with social intelligence multidimensional data streams to produce the next level of health intelligence. Two-model use cases in a large county demonstrate how the HI-Atlas produced relevant PHI to inform public health decision makers to (1) support identification and prioritization of vulnerable communities at risk for COVID-19 spread and vaccine hesitancy, and (2) support the implementation of a generic model for planning equitable COVID-19 vaccine preparedness and distribution. Conclusion  The scalable models of data sources, analyses, and smart hybrid data layer visualizations implemented in the HI-Atlas are the Health Intelligence tools designed to support real-time proactive planning and monitoring for COVID-19 vaccine preparedness and distribution in counties and states.     

The main decision-making competence for willingness-to-pay towards COVID-19 vaccination: a family-based study in Taizhou,China

PurposeThis research aimed to explore individuals’ willingness to pay (WTP) and studied the role of family decision makers in WTP for COVID-19 vaccines.MethodsA self-administered online questionnaire evaluating the willingness of community residents to pay for booster vaccination of COVID-19 vaccine was conducted among families in a community in Taizhou, China. The logistic regression model was performed to identify the factors associated with WTP for the COVID-19 vaccines, and all data were analysed by R software, version 4.1.0.Results44.2% and 43.7% of 824 community residents were willing to pay for the first two doses and the booster dose of the COVID-19 vaccine, respectively. Decision-makers were more willing to pay for both the first two doses and the boost dose of the COVID-19 vaccines, with OR (95%CI) being 1.75 (1.25–2.47) and 1.89 (1.34–2.67), respectively. Besides, participants’ WTP for COVID-19 vaccines were also associated with their occupation and monthly household income.ConclusionThis study found that family decision-makers were more willing to pay for both the first two doses and the booster dose of COVID-19 vaccines in Taizhou, China. To improve the WTP for COVID-19 vaccines, public policy programs need to conduct a comprehensive cost-benefit analysis and focus on the role of family decision makers in vaccination.

Key Messages

• A study evaluating the willingness of community residents to pay for booster vaccination of COVID-19 vaccine was conducted among families in a community in Taizhou, China.
• Family decision-makers were more willing to pay for both the first two doses and the booster dose of COVID-19 vaccines.
• To improve the WTP for COVID-19 vaccines, public policy programs need to conduct a comprehensive cost-benefit analysis and focus on the role of family decision-makers in vaccination.

     

Moving Faster than the COVID-19 Pandemic: The Rapid,Digital Transformation of a Public Health System

Background  Queensland, Australia has been successful in containing the COVID-19 pandemic. Underpinning that response has been a highly effective virus containment strategy which relies on identification, isolation, and contact tracing of cases. The dramatic emergence of the COVID-19 pandemic rendered traditional paper-based systems for managing contact tracing no longer fit for purpose. A rapid digital transformation of the public health contact tracing system occurred to support this effort. Objectives  The objectives of the digital transformation were to shift legacy systems (paper or standalone electronic systems) to a digitally enabled public health system, where data are centered around the consumer rather than isolated databases. The objective of this paper is to outline this case study and detail the lessons learnt to inform and give confidence to others contemplating digitization of public health systems in response to the COVID-19 pandemic. Methods  This case study is set in Queensland, Australia. Universal health care is available. A multidisciplinary team was established consisting of clinical informaticians, developers, data strategists, and health information managers. An agile “pair-programming” approach was undertaken to application development and extensive change efforts were made to maximize adoption of the new digital workflows. Data governance and flows were changed to support rapid management of the pandemic. Results  The digital coronavirus application (DCOVA) is a web-based application that securely captures information about people required to quarantine and creates a multiagency secure database to support a successful containment strategy. Conclusion  Most of the literature surrounding digital transformation allows time for significant consultation, which was simply not possible under crisis conditions. Our observation is that staff was willing to adopt new digital systems because the reason for change (the COVID-19 pandemic) was clearly pressing. This case study highlights just how critical a unified purpose, is to successful, rapid digital transformation.     

Opportunities and Challenges of Telehealth in Disease Management during COVID-19 Pandemic: A Scoping Review

Objective  The novel coronavirus disease 2019 (COVID-19) pandemic is an unexpected universal problem that has changed health care access across the world. Telehealth is an effective solution for health care delivery during disasters and public health emergencies. This study was conducted to summarize the opportunities and challenges of using telehealth in health care delivery during the COVID-19 pandemic. Methods  A structured search was performed in the Web of Science, PubMed, Science Direct, and Scopus databases, as well as the Google Scholar search engine, for studies published until November 4, 2020. The reviewers analyzed 112 studies and identified opportunities and challenges. This review followed the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) protocols. Quality appraisal was done according to the Mixed Methods Appraisal Tool (MMAT) version 2018. Thematic analysis was applied for data analysis. Results  A total of 112 unique opportunities of telehealth application during the pandemic were categorized into 4 key themes, such as (1) clinical, (2) organizational, (3) technical, and (4) social, which were further divided into 11 initial themes and 26 unique concepts. Furthermore, 106 unique challenges were categorized into 6 key themes, such as (1) legal, (2) clinical, (3) organizational, (40 technical, (5) socioeconomic, and (6) data quality, which were divided into 16 initial themes and 37 unique concepts altogether. The clinical opportunities and legal challenges were the most frequent opportunities and challenges, respectively. Conclusion  The COVID-19 pandemic significantly accelerated the use of telehealth. This study could offer useful information to policymakers about the opportunities and challenges of implementing telehealth for providing accessible, safe, and efficient health care delivery to the patient population during and after COVID-19. Furthermore, it can assist policymakers to make informed decisions on implementing telehealth in response to the COVID-19 pandemic by addressing the obstacles ahead.     

U.S. COVID-19 State Government Public Dashboards: An Expert Review

Background  In the United States, all 50 state governments deployed publicly viewable dashboards regarding the novel coronavirus disease 2019 (COVID-19) to track and respond to the pandemic. States dashboards, however, reflect idiosyncratic design practices based on their content, function, and visual design and platform. There has been little guidance for what state dashboards should look like or contain, leading to significant variation. Objectives  The primary objective of our study was to catalog how information, system function, and user interface were deployed across the COVID-19 state dashboards. Our secondary objective was to group and characterize the dashboards based on the information we collected using clustering analysis. Methods  For preliminary data collection, we developed a framework to first analyze two dashboards as a group and reach agreement on coding. We subsequently doubled coded the remaining 48 dashboards using the framework and reviewed the coding to reach total consensus. Results  All state dashboards included maps and graphs, most frequently line charts, bar charts, and histograms. The most represented metrics were total deaths, total cases, new cases, laboratory tests, and hospitalization. Decisions on how metrics were aggregated and stratified greatly varied across dashboards. Overall, the dashboards were very interactive with 96% having at least some functionality including tooltips, zooming, or exporting capabilities. For visual design and platform, we noted that the software was dominated by a few major organizations. Our cluster analysis yielded a six-cluster solution, and each cluster provided additional insights about how groups of states engaged in specific practices in dashboard design. Conclusion  Our study indicates that states engaged in dashboard practices that generally aligned with many of the goals set forth by the Centers for Disease Control and Prevention, Essential Public Health Services. We highlight areas where states fall short of these expectations and provide specific design recommendations to address these gaps.     

A Framework for Systematic Assessment of Clinical Trial Population Representativeness Using Electronic Health Records Data

Background  Clinical trials are the gold standard for generating robust medical evidence, but clinical trial results often raise generalizability concerns, which can be attributed to the lack of population representativeness. The electronic health records (EHRs) data are useful for estimating the population representativeness of clinical trial study population. Objectives  This research aims to estimate the population representativeness of clinical trials systematically using EHR data during the early design stage. Methods  We present an end-to-end analytical framework for transforming free-text clinical trial eligibility criteria into executable database queries conformant with the Observational Medical Outcomes Partnership Common Data Model and for systematically quantifying the population representativeness for each clinical trial. Results  We calculated the population representativeness of 782 novel coronavirus disease 2019 (COVID-19) trials and 3,827 type 2 diabetes mellitus (T2DM) trials in the United States respectively using this framework. With the use of overly restrictive eligibility criteria, 85.7% of the COVID-19 trials and 30.1% of T2DM trials had poor population representativeness. Conclusion  This research demonstrates the potential of using the EHR data to assess the clinical trials population representativeness, providing data-driven metrics to inform the selection and optimization of eligibility criteria.     

Extracting Medical Information from Paper COVID-19 Assessment Forms

Objective  This study examines the validity of optical mark recognition, a novel user interface, and crowdsourced data validation to rapidly digitize and extract data from paper COVID-19 assessment forms at a large medical center. Methods  An optical mark recognition/optical character recognition (OMR/OCR) system was developed to identify fields that were selected on 2,814 paper assessment forms, each with 141 fields which were used to assess potential COVID-19 infections. A novel user interface (UI) displayed mirrored forms showing the scanned assessment forms with OMR results superimposed on the left and an editable web form on the right to improve ease of data validation. Crowdsourced participants validated the results of the OMR system. Overall error rate and time taken to validate were calculated. A subset of forms was validated by multiple participants to calculate agreement between participants. Results  The OMR/OCR tools correctly extracted data from scanned forms fields with an average accuracy of 70% and median accuracy of 78% when the OMR/OCR results were compared with the results from crowd validation. Scanned forms were crowd-validated at a mean rate of 157 seconds per document and a volume of approximately 108 documents per day. A randomly selected subset of documents was reviewed by multiple participants, producing an interobserver agreement of 97% for documents when narrative-text fields were included and 98% when only Boolean and multiple-choice fields were considered. Conclusion  Due to the COVID-19 pandemic, it may be challenging for health care workers wearing personal protective equipment to interact with electronic health records. The combination of OMR/OCR technology, a novel UI, and crowdsourcing data-validation processes allowed for the efficient extraction of a large volume of paper medical documents produced during the COVID-19 pandemic.     

Evidence-Based Strategies for Clinical Organizations to Address COVID-19 Vaccine Hesitancy

The success of vaccination programs is contingent upon irrefutable scientific safety data combined with high rates of public acceptance and population coverage. Vaccine hesitancy, characterized by lack of confidence in vaccination and/or complacency about vaccination that may lead to delay or refusal of vaccination despite the availability of services, threatens to undermine the success of coronavirus disease 2019 (COVID-19) vaccination programs. The rapid pace of vaccine development, misinformation in popular and social media, the polarized sociopolitical environment, and the inherent complexities of large-scale vaccination efforts may undermine vaccination confidence and increase complacency about COVID-19 vaccination. Although the experience of recent lethal surges of COVID-19 infections has underscored the value of COVID-19 vaccines, ensuring population uptake of COVID-19 vaccination will require application of multilevel, evidence-based strategies to influence behavior change and address vaccine hesitancy. Recent survey research evaluating public attitudes in the United States toward the COVID-19 vaccine reveals substantial vaccine hesitancy. Building upon efforts at the policy and community level to ensure population access to COVID-19 vaccination, a strong health care system response is critical to address vaccine hesitancy. Drawing on the evidence base in social, behavioral, communication, and implementation science, we review, summarize, and encourage use of interpersonal, individual-level, and organizational interventions within clinical organizations to address this critical gap and improve population adoption of COVID-19 vaccination.     

Impact of Changes in EHR Use during COVID-19 on Physician Trainee Mental Health

Objectives  This article investigates the association between changes in electronic health record (EHR) use during the coronavirus disease 2019 (COVID-19) pandemic on the rate of burnout, stress, posttraumatic stress disorder (PTSD), depression, and anxiety among physician trainees (residents and fellows). Methods  A total of 222 (of 1,375, 16.2%) physician trainees from an academic medical center responded to a Web-based survey. We compared the physician trainees who reported that their EHR use increased versus those whose EHR use stayed the same or decreased on outcomes related to depression, anxiety, stress, PTSD, and burnout using univariable and multivariable models. We examined whether self-reported exposure to COVID-19 patients moderated these relationships. Results  Physician trainees who reported increased use of EHR had higher burnout (adjusted mean, 1.48 [95% confidence interval [CI] 1.24, 1.71] vs. 1.05 [95% CI 0.93, 1.17]; p  = 0.001) and were more likely to exhibit symptoms of PTSD (adjusted mean = 15.09 [95% CI 9.12, 21.05] vs. 9.36 [95% CI 7.38, 11.28]; p  = 0.035). Physician trainees reporting increased EHR use outside of work were more likely to experience depression (adjusted mean, 8.37 [95% CI 5.68, 11.05] vs. 5.50 [95% CI 4.28, 6.72]; p  = 0.035). Among physician trainees with increased EHR use, those exposed to COVID-19 patients had significantly higher burnout (2.04, p  < 0.001) and depression scores (14.13, p  = 0.003). Conclusion  Increased EHR use was associated with higher burnout, depression, and PTSD outcomes among physician trainees. Although preliminary, these findings have implications for creating systemic changes to manage the wellness and well-being of trainees.     

Building a Learning Health System: Creating an Analytical Workflow for Evidence Generation to Inform Institutional Clinical Care Guidelines

Background  One key aspect of a learning health system (LHS) is utilizing data generated during care delivery to inform clinical care. However, institutional guidelines that utilize observational data are rare and require months to create, making current processes impractical for more urgent scenarios such as those posed by the COVID-19 pandemic. There exists a need to rapidly analyze institutional data to drive guideline creation where evidence from randomized control trials are unavailable. Objectives  This article provides a background on the current state of observational data generation in institutional guideline creation and details our institution''s experience in creating a novel workflow to (1) demonstrate the value of such a workflow, (2) demonstrate a real-world example, and (3) discuss difficulties encountered and future directions. Methods  Utilizing a multidisciplinary team of database specialists, clinicians, and informaticists, we created a workflow for identifying and translating a clinical need into a queryable format in our clinical data warehouse, creating data summaries and feeding this information back into clinical guideline creation. Results  Clinical questions posed by the hospital medicine division were answered in a rapid time frame and informed creation of institutional guidelines for the care of patients with COVID-19. The cost of setting up a workflow, answering the questions, and producing data summaries required around 300 hours of effort and $300,000 USD. Conclusion  A key component of an LHS is the ability to learn from data generated during care delivery. There are rare examples in the literature and we demonstrate one such example along with proposed thoughts of ideal multidisciplinary team formation and deployment.     

Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial

Background  We previously developed and validated a predictive model to help clinicians identify hospitalized adults with coronavirus disease 2019 (COVID-19) who may be ready for discharge given their low risk of adverse events. Whether this algorithm can prompt more timely discharge for stable patients in practice is unknown. Objectives  The aim of the study is to estimate the effect of displaying risk scores on length of stay (LOS). Methods  We integrated model output into the electronic health record (EHR) at four hospitals in one health system by displaying a green/orange/red score indicating low/moderate/high-risk in a patient list column and a larger COVID-19 summary report visible for each patient. Display of the score was pseudo-randomized 1:1 into intervention and control arms using a patient identifier passed to the model execution code. Intervention effect was assessed by comparing LOS between intervention and control groups. Adverse safety outcomes of death, hospice, and re-presentation were tested separately and as a composite indicator. We tracked adoption and sustained use through daily counts of score displays. Results  Enrolling 1,010 patients from May 15, 2020 to December 7, 2020, the trial found no detectable difference in LOS. The intervention had no impact on safety indicators of death, hospice or re-presentation after discharge. The scores were displayed consistently throughout the study period but the study lacks a causally linked process measure of provider actions based on the score. Secondary analysis revealed complex dynamics in LOS temporally, by primary symptom, and hospital location. Conclusion  An AI-based COVID-19 risk score displayed passively to clinicians during routine care of hospitalized adults with COVID-19 was safe but had no detectable impact on LOS. Health technology challenges such as insufficient adoption, nonuniform use, and provider trust compounded with temporal factors of the COVID-19 pandemic may have contributed to the null result. Trial registration  ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT04570488","term_id":"NCT04570488"}}NCT04570488.     

Improving COVID-19 Research of University Hospitals in Germany: Formative Usability Evaluation of the CODEX Feasibility Portal

Background  Within the German “Network University Medicine,” a portal is to be developed to enable researchers to query on novel coronavirus disease 2019 (COVID-19) data from university hospitals for assessing the feasibility of a clinical study. Objectives  The usability of a prototype for federated feasibility queries was evaluated to identify design strengths and weaknesses and derive improvement recommendations for further development. Methods  In the course of a remote usability test with the thinking-aloud method and posttask interviews, 15 clinical researchers evaluated the usability of a prototype of the Feasibility Portal. The identified usability problems were rated according to severity, and improvement recommendations were derived. Results  The design of the prototype was rated as simple, intuitive, and as usable with little effort. The usability test reported a total of 26 problems, 8 of these were rated as “critical.” Usability problems and revision recommendations focus primarily on improving the visual distinguishability of selected inclusion and exclusion criteria, enabling a flexible approach to criteria linking, and enhancing the free-text search. Conclusion  Improvement proposals were developed for these user problems which will guide further development and the adaptation of the portal to user needs. This is an important prerequisite for correct and efficient use in everyday clinical work in the future. Results can provide developers of similar systems with a good starting point for interface conceptualizations. The methodological approach/the developed test guideline can serve as a template for similar evaluations.     

Acceptance of a COVID-19 Vaccine and Its Related Determinants among the General Adult Population in Kuwait

ObjectiveThe objective of this study was to determine the acceptance of a coronavirus disease 2019 (COVID-19) vaccine among the general adult population in Kuwait and assess its determinants.Subjects and MethodsA web-based cross-sectional study was conducted by enrolling adults living in Kuwait (n = 2,368; aged ≥21 years). Acceptance of a COVID-19 vaccine was inferred if participants indicated that they “definitely or probably will accept vaccination against COVID-19 once a vaccine is available.” Associations were explored by applying a modified Poisson regression to estimate and infer adjusted prevalence ratios (aPR) and their 95% confidence intervals (CI).ResultsIn total, 53.1% (1,257/2,368) of the participants were willing to accept a COVID-19 vaccine once available. Male subjects were more willing to accept a COVID-19 vaccine than females (58.3 vs. 50.9%, p < 0.001). Subjects who viewed vaccines in general to have health-related risks were less willing to accept vaccination (aPR = 0.39, 95% CI: 0.35–0.44). Moreover, participants who previously received an influenza vaccine were more likely to accept a COVID-19 vaccine (aPR = 1.44, 95% CI: 1.31–1.58). Willingness to get vaccinated against COVID-19 increased as the self-perceived chances of contracting the infection increased (p < 0.001).ConclusionOverall, 53.1% of the study participants demonstrated willingness to get vaccinated against COVID-19. We found several factors influencing the level of acceptance. Since vaccination appears to be an essential preventive measure that can halt the COVID-19 pandemic, factors relating to low vaccine acceptance need to be urgently addressed by public health strategies.     

An epidemiological evaluation of COVID-19 in La paz,Bolivia

IntroductionThe Plurinational State of Bolivia (Bolivia) has experienced four major waves of coronavirus disease 2019 (COVID-19) so far. Although the ministry of health has been tracking morbidity and mortality through each wave, epidemiology of COVID-19 in Bolivia is not well defined, despite a need for more accurate measurement of the number of cases and deaths to allow for forecasting of the pandemic. This study examined prevalence of COVID-19 at community level, determinants of its occurrence and vaccine effectiveness.MethodsWe conducted a cross-sectional study in La Paz city on 2,775 individuals between March 2020 and February 2022. A structured questionnaire was used to collect data on COVID-19 morbidity, mortality and vaccination status.ResultsOf the 2,775 participants, 1,586 (57.1%) were infected with COVID-19, and 187 (6.7%) were suspected cases. The mortality rate was 2.9%. Sinopharm, Johnson & Johnson, Gamaleya, Pfizer-BioNtech, Moderna and AstraZeneka vaccines are in use, and all vaccines have demonstrated effectiveness in reducing the risk of onset. Risk for mortality was significantly lower in the vaccinated group with an odds ratio of 0.037 (95％ confidential interval: 0.01–0.10, p-value: <0.001).ConclusionsActual prevalence of COVID-19 in La Paz (the prevalence rate: 63.8%, including suspected case) was higher than that reported by the Ministry of Health and Sports in Bolivia (7.5%). In addition, vaccination has contributed significantly to the control of the COVID-19 epidemic in Bolivia. We believe that our report will be useful for COVID-19 prevention strategies in Bolivia for the future.