Organizational decision‐making during COVID‐19: A qualitative analysis of the organizational decision‐making system in the United States during COVID‐19

This study sought to understand COVID‐19‐related organizational decisions were made across sectors. To gain this understanding, we conducted semi‐structured interviews with organizational decision‐makers in North Carolina about their experiences responding to COVID‐19. Conventional content analysis was used to analyse the context, inputs, and processes involved in decision‐making. Between October 2020 and February 2021, we interviewed 44 decision‐makers from the following sectors: business (n = 4), community non‐profit (n = 3), county government (n = 4), healthcare (n = 5), local public health (n = 5), public safety (n = 7), religious (n = 6), education (n = 7) and transportation (n = 3). We found that during the pandemic, organizations looked to scientific authorities, the decisions of peer organizations, data about COVID‐19, and their own experience with prior crises. Interpretation of inputs was informed by current political events, societal trends, and organization mission. Decision‐makers had to account for divergent internal opinions and community behaviour. To navigate inputs and contextual factors, organizations decentralized decision‐making authority, formed auxiliary decision‐making bodies, learned to resolve internal conflicts, learned in real time from their crisis response, and routinely communicated decisions with their communities. In conclusion, aligned with systems and contingency theories of decision‐making, decision‐making during COVID‐19 depended on an organization's 'fit' within the specifics of their existing system and their ability to orient the dynamics of that system to their own goals. [ FROM AUTHOR] Copyright of Journal of Contingencies & Crisis Management is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Thoracic surgery in patients on veno-venous extracorporeal membrane oxygenation for COVID-19 associated acute respiratory distress syndrome.

OBJECTIVES: The COVID-19 pandemic has generated a new type of acute respiratory distress syndrome (ARDS) arising as a complication of COVID-19 pneumonia. Extreme cases require the support of extracorporeal membrane oxygenation (ECMO). Here we present the outcomes of patients that underwent surgical tracheostomy or thoracic surgery at a single tertiary centre whilst on ECMO support for COVID-19 related ARDS. METHODS: 18 patients requiring thoracic input whilst on ECMO support during the first wave of COVID-19 (March-June 2020) were included. Thoracic surgery was required both for performing surgical tracheostomies in the operating theatre and for treating emergencies arising under the ECMO treatment such as bleeding complications. RESULTS: Thirteen patients underwent a surgical tracheostomy, whilst five patients had an invasive thoracic procedure. Anticoagulation was withheld for at least 12 h in the perioperative setting regardless of the indication. One patient was re-operated for haemothorax immediately after the end of the primary operation. 94.5% of the patients were successfully decannulated from ECMO support. Overall 30-day mortality in the cohort was 5.5% (1/18). CONCLUSIONS: Thoracic surgeons can play a valuable role in supporting an ECMO unit during the COVID pandemic, by treating ECMO related complications and by safely performing surgical tracheostomies. Withholding anticoagulation in the perioperative window was not associated with increased thromboembolic events and is desirable when interventions or surgery is indicated in this patient cohort to avoid excessive bleeding.

EMS Involvement in COVID-19 Vaccination Efforts - Results of a North Carolina Statewide Survey.

Objective: The COVID-19 pandemic has necessitated the vaccination of large numbers of people across the United States, mobilizing public health resources on a massive scale. The purpose of this study is to determine how emergency medical services (EMS) clinicians and agencies in North Carolina have been utilized in these vaccination efforts.Methods: This retrospective survey was sent to EMS medical directors and EMS system administrators for all 100 county EMS systems in North Carolina. Participation was voluntary, and survey questions asked about the contribution of EMS systems to vaccination efforts, the levels of EMS clinicians being utilized, the activities carried out by those clinicians, and any identifiable barriers to EMS involvement in COVID-19 vaccination efforts.Results: Ninety-eight of the 100 counties in North Carolina responded to the survey, with 88 contributing to vaccination efforts in the communities. Reasons cited by the 10 counties for not being involved in vaccination efforts include: county health departments not needing assistance (two counties), vaccine hesitancy amongst clinicians and the politicization of COVID (three counties), inadequate staffing (one county), and the presence of "robust vaccination clinics" in the community (one county). An additional 12 counties listed staffing shortages as limiting their vaccination efforts. Among the counties supporting vaccine efforts, activities included planning and logistics (54 counties), non-medical roles (38 counties), vaccine preparation (35 counties), medical screening pre-vaccination (41 counties), vaccine administration (74 counties), medical observation post-vaccination (79 counties), and home vaccinations (53 counties). Of the 74 counties that used EMS personnel in vaccine administration, 27 used EMTs (37%), 36 used Advanced EMTs (49%), and 73 used Paramedics (99%).Conclusion: This study demonstrates the large role that EMS clinicians and systems have played and continue to play in COVID-19 vaccination efforts in the state of North Carolina, including planning and logistics, patient screening and observation, vaccine preparation and administration, and home vaccination. Furthermore, it supports the expanded use of EMTs as a potential vaccination workforce. As the public health response to this pandemic continues, EMS clinicians and systems are a valuable resource to their communities and states.

Vaccinating children against COVID-19 is crucial to protect schools and communities.

To evaluate the joint impact of childhood vaccination rates and school masking policies on community transmission and severe outcomes due to COVID-19, we utilized a stochastic, agent-based simulation of North Carolina to test 24 health policy scenarios. In these scenarios, we varied the childhood (ages 5 to 19) vaccination rate relative to the adult's (ages 20 to 64) vaccination rate and the masking relaxation policies in schools. We measured the overall incidence of disease, COVID-19-related hospitalization, and mortality from 2021 July 1 to 2023 July 1. Our simulation estimates that removing all masks in schools in January 2022 could lead to a 31% to 45%, 23% to 35%, and 13% to 19% increase in cumulative infections for ages 5 to 9, 10 to 19, and the total population, respectively, depending on the childhood vaccination rate. Additionally, achieving a childhood vaccine uptake rate of 50% of adults could lead to a 31% to 39% reduction in peak hospitalizations overall masking scenarios compared with not vaccinating this group. Finally, our simulation estimates that increasing vaccination uptake for the entire eligible population can reduce peak hospitalizations in 2022 by an average of 83% and 87% across all masking scenarios compared to the scenarios where no children are vaccinated. Our simulation suggests that high vaccination uptake among both children and adults is necessary to mitigate the increase in infections from mask removal in schools and workplaces.

Can vaccine prioritization reduce disparities in COVID-19 burden for historically marginalized populations?

SARS-CoV-2 vaccination strategies were designed to reduce COVID-19 mortality, morbidity, and health inequities. To assess the impact of vaccination strategies on disparities in COVID-19 burden among historically marginalized populations (HMPs), e.g. Black race and Hispanic ethnicity, we used an agent-based simulation model, populated with census-tract data from North Carolina. We projected COVID-19 deaths, hospitalizations, and cases from 2020 July 1 to 2021 December 31, and estimated racial/ethnic disparities in COVID-19 outcomes. We modeled 2-stage vaccination prioritization scenarios applied to sub-groups including essential workers, older adults (65+), adults with high-risk health conditions, HMPs, or people in low-income tracts. Additionally, we estimated the effects of maximal uptake (100% for HMP vs. 100% for everyone), and distribution to only susceptible people. We found strategies prioritizing essential workers, then older adults led to the largest mortality and case reductions compared to no prioritization. Under baseline uptake scenarios, the age-adjusted mortality for HMPs was higher (e.g. 33.3%-34.1% higher for the Black population and 13.3%-17.0% for the Hispanic population) compared to the White population. The burden on HMPs decreased only when uptake was increased to 100% in HMPs; however, the Black population still had the highest relative mortality rate even when targeted distribution strategies were employed. If prioritization schemes were not paired with increased uptake in HMPs, disparities did not improve. The vaccination strategies publicly outlined were insufficient, exacerbating disparities between racial and ethnic groups. Strategies targeted to increase vaccine uptake among HMPs are needed to ensure equitable distribution and minimize disparities in outcomes.

Organizational decision‐making during COVID‐19: A qualitative analysis of the organizational decision‐making system in the United States during COVID‐19

This study sought to understand COVID‐19‐related organizational decisions were made across sectors. To gain this understanding, we conducted semi‐structured interviews with organizational decision‐makers in North Carolina about their experiences responding to COVID‐19. Conventional content analysis was used to analyse the context, inputs, and processes involved in decision‐making. Between October 2020 and February 2021, we interviewed 44 decision‐makers from the following sectors: business (n = 4), community non‐profit (n = 3), county government (n = 4), healthcare (n = 5), local public health (n = 5), public safety (n = 7), religious (n = 6), education (n = 7) and transportation (n = 3). We found that during the pandemic, organizations looked to scientific authorities, the decisions of peer organizations, data about COVID‐19, and their own experience with prior crises. Interpretation of inputs was informed by current political events, societal trends, and organization mission. Decision‐makers had to account for divergent internal opinions and community behaviour. To navigate inputs and contextual factors, organizations decentralized decision‐making authority, formed auxiliary decision‐making bodies, learned to resolve internal conflicts, learned in real time from their crisis response, and routinely communicated decisions with their communities. In conclusion, aligned with systems and contingency theories of decision‐making, decision‐making during COVID‐19 depended on an organization's ‘fit’ within the specifics of their existing system and their ability to orient the dynamics of that system to their own goals. [ FROM AUTHOR]

Cross-sector decision landscape in response to COVID-19: A qualitative network mapping analysis of North Carolina decision-makers.

Introduction: The COVID-19 pandemic response has demonstrated the interconnectedness of individuals, organizations, and other entities jointly contributing to the production of community health. This response has involved stakeholders from numerous sectors who have been faced with new decisions, objectives, and constraints. We examined the cross-sector organizational decision landscape that formed in response to the COVID-19 pandemic in North Carolina. Methods: We conducted virtual semi-structured interviews with 44 organizational decision-makers representing nine sectors in North Carolina between October 2020 and January 2021 to understand the decision-making landscape within the first year of the COVID-19 pandemic. In line with a complexity/systems thinking lens, we defined the decision landscape as including decision-maker roles, key decisions, and interrelationships involved in producing community health. We used network mapping and conventional content analysis to analyze transcribed interviews, identifying relationships between stakeholders and synthesizing key themes. Results: Decision-maker roles were characterized by underlying tensions between balancing organizational mission with employee/community health and navigating organizational vs. individual responsibility for reducing transmission. Decision-makers' roles informed their perspectives and goals, which influenced decision outcomes. Key decisions fell into several broad categories, including how to translate public health guidance into practice; when to institute, and subsequently loosen, public health restrictions; and how to address downstream social and economic impacts of public health restrictions. Lastly, given limited and changing information, as well as limited resources and expertise, the COVID-19 response required cross-sector collaboration, which was commonly coordinated by local health departments who had the most connections of all organization types in the resulting network map. Conclusions: By documenting the local, cross-sector decision landscape that formed in response to COVID-19, we illuminate the impacts different organizations may have on information/misinformation, prevention behaviors, and, ultimately, health. Public health researchers and practitioners must understand, and work within, this complex decision landscape when responding to COVID-19 and future community health challenges.

Long-term evaluation of sperm parameters after coronavirus disease 2019 messenger ribonucleic acid vaccination.

Objective: To determine whether the COVID-19 mRNA vaccines can negatively impact the semen parameters of young healthy men in the long-term. Design: We conducted semen analyses on 12 men before, 3 and 9 months after achieving fully vaccinated status. Individuals who admitted a history of infertility or previous azoospermia were excluded from study participation. Subjects: Healthy male volunteers between the ages of 18-50 years old were recruited between September 2021 - March 2022. Main Outcome Measures: Semen analyses were performed and evaluated volume, sperm concentration, total motility, and total motile sperm count (TMSC). The primary outcome was median change in the TMSC at baseline, 3 months, and at least 9 months following vaccination. Results: A total of 12 men volunteered in our study (median age 26 [25 - 30] years). Subjects provided follow-up semen samples at a median of 10 months following the second vaccine dose. There were no significant changes in any semen parameters between baseline, 3 months, and 10 months following vaccination. Baseline samples demonstrated median sperm concentrations and TMSC of 29.5 million/cc [9.3 - 49] and 31 million [4-51.3], respectively. At 9-month follow-up, sperm concentration and TMSC were 43 [20.5 - 63.5] (P=.351) and 37.5 [8.5 - 117.8] (P=.519), respectively. Of note, there were no significant changes in semen volume nor total motility (%) for participants at follow-up. Conclusion: COVID-19 mRNA vaccines and the booster dose does not appear to negatively impact the semen parameters of healthy males up to 10 months following vaccination.

Use of Modeling to Inform Decision Making in North Carolina during the COVID-19 Pandemic: A Qualitative Study.

Background. The COVID-19 pandemic has popularized computer-based decision-support models, which are commonly used to inform decision making amidst complexity. Understanding what organizational decision makers prefer from these models is needed to inform model development during this and future crises. Methods. We recruited and interviewed decision makers from North Carolina across 9 sectors to understand organizational decision-making processes during the first year of the COVID-19 pandemic (N = 44). For this study, we identified and analyzed a subset of responses from interviewees (n = 19) who reported using modeling to inform decision making. We used conventional content analysis to analyze themes from this convenience sample with respect to the source of models and their applications, the value of modeling and recommended applications, and hesitancies toward the use of models. Results. Models were used to compare trends in disease spread across localities, estimate the effects of social distancing policies, and allocate scarce resources, with some interviewees depending on multiple models. Decision makers desired more granular models, capable of projecting disease spread within subpopulations and estimating where local outbreaks could occur, and incorporating a broad set of outcomes, such as social well-being. Hesitancies to the use of modeling included doubts that models could reflect nuances of human behavior, concerns about the quality of data used in models, and the limited amount of modeling specific to the local context. Conclusions. Decision makers perceived modeling as valuable for informing organizational decisions yet described varied ability and willingness to use models for this purpose. These data present an opportunity to educate organizational decision makers on the merits of decision-support modeling and to inform modeling teams on how to build more responsive models that address the needs of organizational decision makers. Highlights: Organizations from a diversity of sectors across North Carolina (including public health, education, business, government, religion, and public safety) have used decision-support modeling to inform decision making during COVID-19.Decision makers wish for models to project the spread of disease, especially at the local level (e.g., individual cities and counties), and to help estimate the outcomes of policies.Some organizational decision makers are hesitant to use modeling to inform their decisions, stemming from doubts that models could reflect nuances of human behavior, concerns about the accuracy and precision of data used in models, and the limited amount of modeling available at the local level.

Vaccinating children against COVID-19 is crucial to protect schools and communities

To evaluate the joint impact of childhood vaccination rates and school masking policies on community transmission and severe outcomes due to COVID-19, we utilized a stochastic, agent-based simulation of North Carolina to test 24 health policy scenarios. In these scenarios, we varied the childhood (ages 5 to 19) vaccination rate relative to the adult's (ages 20 to 64) vaccination rate and the masking relaxation policies in schools. We measured the overall incidence of disease, COVID-19-related hospitalization, and mortality from 2021 July 1 to 2023 July 1. Our simulation estimates that removing all masks in schools in January 2022 could lead to a 31% to 45%, 23% to 35%, and 13% to 19% increase in cumulative infections for ages 5 to 9, 10 to 19, and the total population, respectively, depending on the childhood vaccination rate. Additionally, achieving a childhood vaccine uptake rate of 50% of adults could lead to a 31% to 39% reduction in peak hospitalizations overall masking scenarios compared with not vaccinating this group. Finally, our simulation estimates that increasing vaccination uptake for the entire eligible population can reduce peak hospitalizations in 2022 by an average of 83% and 87% across all masking scenarios compared to the scenarios where no children are vaccinated. Our simulation suggests that high vaccination uptake among both children and adults is necessary to mitigate the increase in infections from mask removal in schools and workplaces.

User centered clinical decision support to implement initiation of buprenorphine for opioid use disorder in the emergency department: EMBED pragmatic cluster randomized controlled trial.

OBJECTIVE: To determine the effect of a user centered clinical decision support tool versus usual care on rates of initiation of buprenorphine in the routine emergency care of individuals with opioid use disorder. DESIGN: Pragmatic cluster randomized controlled trial (EMBED). SETTING: 18 emergency department clusters across five healthcare systems in five states representing the north east, south east, and western regions of the US, ranging from community hospitals to tertiary care centers, using either the Epic or Cerner electronic health record platform. PARTICIPANTS: 599 attending emergency physicians caring for 5047 adult patients presenting with opioid use disorder. INTERVENTION: A user centered, physician facing clinical decision support system seamlessly integrated into user workflows in the electronic health record to support initiating buprenorphine in the emergency department by helping clinicians to diagnose opioid use disorder, assess the severity of withdrawal, motivate patients to accept treatment, and complete electronic health record tasks by automating clinical and after visit documentation, order entry, prescribing, and referral. MAIN OUTCOME MEASURES: Rate of initiation of buprenorphine (administration or prescription of buprenorphine) in the emergency department among patients with opioid use disorder. Secondary implementation outcomes were measured with the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework. RESULTS: 1 413 693 visits to the emergency department (775 873 in the intervention arm and 637 820 in the usual care arm) from November 2019 to May 2021 were assessed for eligibility, resulting in 5047 patients with opioid use disorder (2787 intervention arm, 2260 usual care arm) under the care of 599 attending physicians (340 intervention arm, 259 usual care arm) for analysis. Buprenorphine was initiated in 347 (12.5%) patients in the intervention arm and in 271 (12.0%) patients in the usual care arm (adjusted generalized estimating equations odds ratio 1.22, 95% confidence interval 0.61 to 2.43, P=0.58). Buprenorphine was initiated at least once by 151 (44.4%) physicians in the intervention arm and by 88 (34.0%) in the usual care arm (1.83, 1.16 to 2.89, P=0.01). CONCLUSIONS: User centered clinical decision support did not increase patient level rates of initiating buprenorphine in the emergency department. Although streamlining and automating electronic health record workflows can potentially increase adoption of complex, unfamiliar evidence based practices, more interventions are needed to look at other barriers to the treatment of addiction and increase the rate of initiating buprenorphine in the emergency department in patients with opioid use disorder. TRIAL REGISTRATION: ClinicalTrials.gov NCT03658642.

Myocardial involvement in children with post-COVID multisystem inflammatory syndrome: a cardiovascular magnetic resonance based multicenter international study-the CARDOVID registry.

BACKGROUND: Recent evidence shows an association between coronavirus disease 2019 (COVID-19) infection and a severe inflammatory syndrome in children. Cardiovascular magnetic resonance (CMR) data about myocardial injury in children are limited to small cohorts. The aim of this multicenter, international registry is to describe clinical and cardiac characteristics of multisystem inflammatory syndrome in children (MIS-C) associated with COVID-19 using CMR so as to better understand the real extent of myocardial damage in this vulnerable cohort. METHODS AND RESULTS: Hundred-eleven patients meeting the World Health Organization criteria for MIS-C associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), having clinical cardiac involvement and having received CMR imaging scan were included from 17 centers. Median age at disease onset was 10.0 years (IQR 7.0-13.8). The majority of children had COVID-19 serology positive (98%) with 27% of children still having both, positive serology and polymerase chain reaction (PCR). CMR was performed at a median of 28 days (19-47) after onset of symptoms. Twenty out of 111 (18%) patients had CMR criteria for acute myocarditis (as defined by the Lake Louise Criteria) with 18/20 showing subepicardial late gadolinium enhancement (LGE). CMR myocarditis was significantly associated with New York Heart Association class IV (p = 0.005, OR 6.56 (95%-CI 1.87-23.00)) and the need for mechanical support (p = 0.039, OR 4.98 (95%-CI 1.18-21.02)). At discharge, 11/111 (10%) patients still had left ventricular systolic dysfunction. CONCLUSION: No CMR evidence of myocardial damage was found in most of our MIS-C cohort. Nevertheless, acute myocarditis is a possible manifestation of MIS-C associated with SARS-CoV-2 with CMR evidence of myocardial necrosis in 18% of our cohort. CMR may be an important diagnostic tool to identify a subset of patients at risk for cardiac sequelae and more prone to myocardial damage. CLINICAL TRIAL REGISTRATION: The study has been registered on ClinicalTrials.gov, Identifier NCT04455347, registered on 01/07/2020, retrospectively registered.

Healthcare worker resilience during the COVID‐19 pandemic: A qualitative study of primary care providers in India

Since 2020, the world saw a myriad of creative health‐care policy responses to the COVID‐19 pandemic. This article studied the experience of rural primary care providers (PCPs) in India deputized for COVID‐19 care in urban areas. In‐depth interviews were conducted with PCPs (n = 19), who served at COVID‐19 facilities. Lack of epidemic management and intensive tertiary care experience, limited and inadequate training, and fear of infection emerged as the primary sources of distress, in addition to absent systemic mental health support and formalized recognition. Even so, resilience among the respondents emerged as a result of encouragement from their families, peers, and mentors through various means including social media, and from individual recognition from communities and local governments. Rural PCPs expressed an eagerness to serve at the frontlines of COVID‐19 and demonstrated indomitable spirit in the face of an acutely understaffed health system, growing uncertainty, and concerns about personal and family health. It is imperative to reconfigure health‐care education and continuing professional development, and equip all health‐care professionals with mental health support and the ability to deal with public health emergencies and build a more resilient health workforce. Highlights COVID‐19 revealed several gaps in the public health emergency response and the overall health system in India. Building healthcare worker resilience is essential to ensure good quality patient care and a strong system. There is a need for a formal framework to build individual and organisational resilience in the Indian health system.

Diarrhoea and preadmission antibiotic exposure in COVID-19: a retrospective cohort study of 1153 hospitalised patients.

OBJECTIVE: The aims of this study were to describe community antibiotic prescribing patterns in individuals hospitalised with COVID-19, and to determine the association between experiencing diarrhoea, stratified by preadmission exposure to antibiotics, and mortality risk in this cohort. DESIGN/METHODS: Retrospective study of the index presentations of 1153 adult patients with COVID-19, admitted between 1 March 2020 and 29 June 2020 in a South London NHS Trust. Data on patients' medical history (presence of diarrhoea, antibiotic use in the previous 14 days, comorbidities); demographics (age, ethnicity, and body mass index); and blood test results were extracted. Time to event modelling was used to determine the risk of mortality for patients with diarrhoea and/or exposure to antibiotics. RESULTS: 19.2% of the cohort reported diarrhoea on presentation; these patients tended to be younger, and were less likely to have recent exposure to antibiotics (unadjusted OR 0.64, 95% CI 0.42 to 0.97). 19.1% of the cohort had a course of antibiotics in the 2 weeks preceding admission; this was associated with dementia (unadjusted OR 2.92, 95% CI 1.14 to 7.49). After adjusting for confounders, neither diarrhoea nor recent antibiotic exposure was associated with increased mortality risk. However, the absence of diarrhoea in the presence of recent antibiotic exposure was associated with a 30% increased risk of mortality. CONCLUSION: Community antibiotic use in patients with COVID-19, prior to hospitalisation, is relatively common, and absence of diarrhoea in antibiotic-exposed patients may be associated with increased risk of mortality. However, it is unclear whether this represents a causal physiological relationship or residual confounding.

Association of Simulated COVID-19 Vaccination and Nonpharmaceutical Interventions With Infections, Hospitalizations, and Mortality.

Importance: Vaccination against SARS-CoV-2 has the potential to significantly reduce transmission and COVID-19 morbidity and mortality. The relative importance of vaccination strategies and nonpharmaceutical interventions (NPIs) is not well understood. Objective: To assess the association of simulated COVID-19 vaccine efficacy and coverage scenarios with and without NPIs with infections, hospitalizations, and deaths. Design, Setting, and Participants: An established agent-based decision analytical model was used to simulate COVID-19 transmission and progression from March 24, 2020, to September 23, 2021. The model simulated COVID-19 spread in North Carolina, a US state of 10.5 million people. A network of 1 017 720 agents was constructed from US Census data to represent the statewide population. Exposures: Scenarios of vaccine efficacy (50% and 90%), vaccine coverage (25%, 50%, and 75% at the end of a 6-month distribution period), and NPIs (reduced mobility, school closings, and use of face masks) maintained and removed during vaccine distribution. Main Outcomes and Measures: Risks of infection from the start of vaccine distribution and risk differences comparing scenarios. Outcome means and SDs were calculated across replications. Results: In the worst-case vaccination scenario (50% efficacy, 25% coverage), a mean (SD) of 2 231 134 (117 867) new infections occurred after vaccination began with NPIs removed, and a mean (SD) of 799 949 (60 279) new infections occurred with NPIs maintained during 11 months. In contrast, in the best-case scenario (90% efficacy, 75% coverage), a mean (SD) of 527 409 (40 637) new infections occurred with NPIs removed and a mean (SD) of 450 575 (32 716) new infections occurred with NPIs maintained. With NPIs removed, lower efficacy (50%) and higher coverage (75%) reduced infection risk by a greater magnitude than higher efficacy (90%) and lower coverage (25%) compared with the worst-case scenario (mean [SD] absolute risk reduction, 13% [1%] and 8% [1%], respectively). Conclusions and Relevance: Simulation outcomes suggest that removing NPIs while vaccines are distributed may result in substantial increases in infections, hospitalizations, and deaths. Furthermore, as NPIs are removed, higher vaccination coverage with less efficacious vaccines can contribute to a larger reduction in risk of SARS-CoV-2 infection compared with more efficacious vaccines at lower coverage. These findings highlight the need for well-resourced and coordinated efforts to achieve high vaccine coverage and continued adherence to NPIs before many prepandemic activities can be resumed.

Health literacy, preventive COVID 19 behaviour and adherence to chronic disease treatment during lockdown among patients registered at primary health facility in urban Jodhpur, Rajasthan.

BACKGROUND AND AIMS: Potential role of health literacy in determining adherence to COVID-19 preventive behavior, pharmacological, and lifestyle management among diagnosed patients of chronic diseases during nationwide lockdown is inadequately investigated. METHODS: A cross-sectional study was conducted from May-August 2020 among diagnosed patients of chronic diseases residing in a COVID-19 hotspot of urban Jodhpur, Rajasthan, and availing health services from primary care facility. Telephonic interviews of participants were conducted to determine their health literacy using HLS-EU-Q47 questionnaire, adherence to COVID-19 preventive behaviour as per World Health Organization recommendations, and compliance to prescribed pharmacological and physical activity recommendations for chronic disease. RESULTS: All the 605 diagnosed patients of chronic diseases availing services from primary care facility were contacted for the study, yielding response rate of 68% with 412 agreeing to participate. Insufficient health literacy was observed for 65.8% participants. Only about half of participants had scored above median for COVID-19 awareness (55.1%) and preventive behavior (45.1%). Health literacy was observed to be significant predictor of COVID-19 awareness [aOR: 3.53 (95% CI: 1.81-6.88)]; COVID-19 preventive behavior [aOR: 2.06, 95%CI; 1.14-3.69] and compliance to pharmacological management [aOR: 3.05; 95% CI: 1.47-6.35] but not for physical activity. CONCLUSION: COVID-19 awareness, preventive behavior, and compliance to pharmacological management is associated with health literacy among patients of chronic disease availing services from primary health facility. Focusing on health literacy could thus be an essential strategic intervention yielding long term benefits.

Review and Analysis of Massively Registered Clinical Trials of COVID-19 using the Text Mining Approach.

OBJECTIVE: Immediately after the outbreak of nCoV, many clinical trials are registered for COVID-19. The numbers of registrations are now raising inordinately. It is challenging to understand which research areas are explored in this massive pool of clinical studies. If such information can be compiled, then it is easy to explore new research studies for possible contributions in COVID-19 research. METHODS: In the present work, a text-mining technique of artificial intelligence is utilized to map the research domains explored through the clinical trials of COVID-19. With the help of the open-- source and graphical user interface-based tool, 3007 clinical trials are analyzed here. The dataset is acquired from the international clinical trial registry platform of WHO. With the help of hierarchical cluster analysis, the clinical trials were grouped according to their common research studies. These clusters are analyzed manually using their word clouds for understanding the scientific area of a particular cluster. The scientific fields of clinical studies are comprehensively reviewed and discussed based on this analysis. RESULTS: More than three-thousand clinical trials are grouped in 212 clusters by hierarchical cluster analysis. Manual intervention of these clusters using their individual word-cloud helped to identify various scientific areas which are explored in COVID19 related clinical studies. CONCLUSION: The text-mining is an easy and fastest way to explore many registered clinical trials. In our study, thirteen major clusters or research areas were identified in which the majority of clinical trials were registered. Many other uncategorized clinical studies were also identified as "miscellaneous studies". The clinical trials within the individual cluster were studied, and their research purposes are compiled comprehensively in the present work.