Staffing and Protective Equipment Access Mitigated COVID-19 Penetration and Spread in US Nursing Homes During the Third Surge

ObjectivesDuring the last quarter of 2020—despite improved distribution of personal protective equipment (PPE) and knowledge of COVID-19 management—nursing homes experienced the greatest increases in cases and deaths since the pandemic's beginning. We sought to update COVID-19 estimates of cases, hospitalization, and mortality and to evaluate the association of potentially modifiable facility-level infection control factors on odds and magnitude of COVID-19 cases, hospitalizations, and deaths in nursing homes during the third surge of the pandemic.DesignCross-sectional analysis.Setting and ParticipantsFacility-level data from 13,156 US nursing home facilities.MethodsTwo series of multivariable logistic regression and generalized linear models to examine the association of infection control factors (personal protective equipment and staffing) on incidence and magnitude, respectively, of confirmed COVID-19 cases, hospitalizations, and deaths in nursing home residents reported in the last quarter of 2020.ResultsNursing homes experienced steep increases in COVID-19 cases, hospitalizations, and deaths during the final quarter of 2020. Four-fifths (80.51%; n = 10,592) of facilities reported at least 1 COVID-19 case, 49.44% (n = 6504) reported at least 1 hospitalization, and 49.76% (n = 6546) reported at least 1 death during this third surge. N95 mask shortages were associated with increased odds of at least 1 COVID-19 case [odds ratio (OR) 1.21, 95% confidence interval (CI) 1.05-1.40] and hospitalization (1.26, 95% CI 1.13-1.40), as well as larger numbers of hospitalizations (1.11, 95% CI 1.02-1.20). Nursing aide shortages were associated with lower odds of at least 1 COVID-19 death (1.23, 95% CI 1.12-1.34) and higher hospitalizations (1.09, 95% CI 1.01-1.17). The number of nursing hours per resident per day was largely insignificant across all outcomes. Of note, smaller (<50-bed) and midsized (50- to 150-bed) facilities had lower odds yet higher magnitude of all COVID outcomes. Bed occupancy rates >75% increased odds of experiencing a COVID-19 case (1.48, 95% CI 1.35-1.62) or death (1.25, 95% CI 1.17-1.34).Conclusions and ImplicationsAdequate staffing and PPE—along with reduced occupancy and smaller facilities—mitigate incidence and magnitude of COVID-19 cases and sequelae. Addressing shortcomings in these factors is critical to the prevention of infections and adverse health consequences of a next surge among vulnerable nursing home residents.     

Severity of COVID-19 among Residents in Aged Care Facilities in Victoria,Australia: A Retrospective Cohort Study Comparing the Delta and Omicron Epidemic Periods

ObjectivesDuring the COVID-19 pandemic, no country with widespread community transmission has avoided outbreaks or deaths in residential aged care facilities (RACFs). As RACF residents are at high risk of morbidity and mortality from COVID-19, understanding disease severity risk factors is imperative.DesignThis retrospective cohort study aimed to compare COVID-19 disease severity (hospitalization and deaths) and associated risk factors among RACF residents in Victoria, Australia, across Delta and Omicron epidemic periods.Settings and ParticipantsResident case hospitalization risk (HR) and case fatality risk (CFR) were assessed using Victorian RACFs COVID-19 outbreaks data across 2 epidemic periods; Delta, 994 resident cases linked to 86 outbreaks; and Omicron, 1882 resident cases linked to 209 outbreaks.MethodsAdjusting for outbreak-level clustering, age, sex, up-to-date vaccination status, and time since last vaccination, the odds of hospitalization and death were compared using mixed effects logistic regression.ResultsThe HR and CFR was lower during the Omicron period compared with the Delta period [HR 8.2% vs 24.6%, odds ratio (OR) 0.17, 95% CI 0.11-0.26, and CFR: 11.4% vs 18.7%, OR 0.40, 95% CI 0.28-0.56]. During both periods, males had higher odds of hospitalization and odds of death; being up to date with vaccination reduced odds of hospitalization by 40% (excluding nonemergency patient transfers) and odds of death by 43%; and for each month since last vaccination, odds of hospitalization increased by 9% and odds of death by 16%.Conclusions and ImplicationsThis study provides empirical evidence of lower COVID-19 severity among RACF residents in the Omicron period and highlights the importance of up-to-date and timely vaccination to reduce disease severity in this cohort.     

Excess Mortality After COVID-19 in Swedish Long-Term Care Facilities

ObjectiveTo compare 30-day mortality in long-term care facility (LTCF) residents with and without COVID-19 and to investigate the impact of 31 potential risk factors for mortality in COVID-19 cases.DesignRetrospective cohort study.Setting and ParticipantsAll residents of LTCFs registered in Senior Alert, a Swedish national database of health examinations in older adults, during 2019-2020.MethodsWe selected residents with confirmed COVID-19 until September 15, 2020, along with time-dependent propensity score–matched controls without COVID-19. Exposures were COVID-19, age, sex, comorbidities, medications, and other patient characteristics. The outcome was all-cause 30-day mortality.ResultsA total of 3731 residents (median age 87 years, 64.5% female) with COVID-19 were matched to 3731 controls without COVID-19. Thirty-day mortality was 39.9% in COVID-19 cases and 5.7% in controls [relative risk 7.05, 95% confidence interval (CI) 6.10-8.14]. In COVID-19 cases, the odds ratio (OR) for 30-day mortality was 2.44 (95% CI 1.57-3.81) in cases aged 80-84 years, 2.99 (95% CI 1.93-4.65) in cases aged 85-89 years, and 3.28 (95% CI 2.11-5.10) in cases aged ≥90 years, as compared with cases aged <70 years. Other risk factors for mortality among COVID-19 cases included male sex (OR, 2.60, 95% CI 2.22-3.05), neuropsychological conditions (OR, 2.18; 95% CI 1.76-2.71), impaired walking ability (OR, 1.45, 95% CI 1.17-1.78), urinary and bowel incontinence (OR 1.51, 95% CI 1.22-1.85), diabetes (OR 1.36, 95% CI 1.14-1.62), chronic kidney disease (OR 1.37, 95% CI 1.11-1.68) and previous pneumonia (OR 1.57, 95% CI 1.32-1.85). Nutritional factors, cardiovascular diseases, and antihypertensive medications were not significantly associated with mortality.Conclusions and ImplicationsIn Swedish LTCFs, COVID-19 was associated with a large excess in mortality after controlling for an extensive number of risk factors. Beyond older age and male sex, several prevalent clinical risk factors independently contributed to higher mortality. These findings suggest that reducing transmission of COVID-19 in LTCFs will likely prevent a considerable number of deaths.     

Racial/Ethnic Differences in Risk Factors Associated With Severe COVID-19 Among Older Adults With ADRD

ObjectiveTo examine racial/ethnic differences in risk factors, and their associations with COVID-19–related outcomes among older adults with Alzheimer’s disease and related dementias (ADRD).DesignObservational study.Setting and ParticipantsNational Medicare claims data and the Minimum Data Set 3.0 from April 1, 2020, to December 31, 2020, were linked in this study. We included community-dwelling fee-for-service Medicare beneficiaries with ADRD, diagnosed with COVID-19 between April 1, 2020, and December 1, 2020 (N = 138,533).MethodsTwo outcome variables were defined: hospitalization within 14 days and death within 30 days of COVID-19 diagnosis. We obtained information on individual sociodemographic characteristics, chronic conditions, and prior health care utilization based on the Medicare claims and the Minimum Dataset. Machine learning methods, including lasso regression and discriminative pattern mining, were used to identify risk factors in racial/ethnic subgroups (ie, White, Black, and Hispanic individuals). The associations between identified risk factors and outcomes were evaluated using logistic regression and compared across racial/ethnic subgroups using the coefficient comparison approach.ResultsWe found higher risks of COVID-19–related outcomes among Black and Hispanic individuals. The areas under the curve of the models with identified risk factors were 0.65 to 0.68 for mortality and 0.61 to 0.62 for hospitalization across racial/ethnic subgroups. Although some identified risk factors (eg, age, gender) for COVID-19–related outcomes were common among all racial/ethnic subgroups, other risk factors (eg, hypertension, obesity) varied by racial/ethnic subgroups. Furthermore, the associations between some common risk factors and COVID-19–related outcomes also varied by race/ethnicity. Being male was related to 138.2% (95% CI: 1.996–2.841), 64.7% (95% CI: 1.546–1.755), and 37.1% (95% CI: 1.192–1.578) increased odds of death among Hispanic, White, and Black individuals, respectively. In addition, the racial/ethnic disparity in COVID-19–related outcomes could not be completely explained by the identified risk factors.Conclusions and ImplicationsRacial/ethnic differences were detected in the likelihood of having COVID-19–related outcomes, specific risk factors, and relationships between specific risk factors and COVID-19–related outcomes. Future research is needed to elucidate the reasons for these differences.     

Risk of Death in Nursing Home Residents After COVID-19 Vaccination

ObjectivesIn the first months of 2021, the Dutch COVID-19 vaccination campaign was disturbed by reports of death in Norwegian nursing homes (NHs) after vaccination. Reports predominantly concerned persons >65 years of age with 1 or more comorbidities. Also, in the Netherlands adverse events were reported after COVID-19 vaccination in this vulnerable group. Yet, it was unclear whether a causal link between vaccination and death existed. Therefore, we investigated the risk of death after COVID-19 vaccination in Dutch NH residents compared with the risk of death in NH residents prior to the COVID-19 pandemic.DesignPopulation-based longitudinal cohort study with electronic health record data.Setting and ParticipantsWe studied Dutch NH residents from 73 NHs who received 1 or 2 COVID-19 vaccination(s) between January 13 and April 16, 2021 (n = 21,762). As a historical comparison group, we included Dutch NH residents who were registered in the same period in 2019 (n = 27,591).MethodsData on vaccination status, age, gender, type of care, comorbidities, and date of NH entry and (if applicable) discharge or date of death were extracted from electronic health records. Risk of death after 30 days was evaluated and compared between vaccinated residents and historical comparison residents with Kaplan-Meier and Cox regression analyses. Regression analyses were adjusted for age, gender, comorbidities, and length of stay.ResultsRisk of death in NH residents after one COVID-19 vaccination (regardless of whether a second vaccination was given) was decreased compared with historical comparison residents from 2019 (adjusted HR 0.77, 95% CI 0.69-0.86). The risk of death further decreased after 2 vaccinations compared with the historical comparison group (adjusted HR 0.57, 95% CI 0.50-0.64).Conclusions and ImplicationsWe found no indication that risk of death in NH residents is increased after COVID-19 vaccination. These results indicate that COVID-19 vaccination in NH residents is safe and could reduce fear and resistance toward vaccination.     

The Benefits of Nursing Home Air Purification on COVID-19 Outcomes: A Natural Experiment

ObjectivesImproving indoor air quality is one potential strategy to reduce the transmission of SARS-CoV-2 in any setting, including nursing homes, where staff and residents have been disproportionately and negatively affected by the COVID-19 pandemic.DesignSingle group interrupted time series.Setting and ParticipantsA total of 81 nursing homes in a multifacility corporation in Florida, Georgia, North Carolina, and South Carolina that installed ultraviolet air purification in their existing heating, ventilation, and air conditioning systems between July 27, 2020,k and September 10, 2020.MethodsWe linked data on the date ultraviolet air purification systems were installed with the Nursing Home COVID-19 Public Health File (weekly data reported by nursing homes on the number of residents with COVID-19 and COVID-19 deaths), public data on data on nursing home characteristics, county-level COVID-19 cases/deaths, and outside air temperature. We used an interrupted time series design and ordinary least squares regression to compare trends in weekly COVID-19 cases and deaths before and after installation of ultraviolet air purification systems. We controlled for county-level COVID-19 cases, death, and heat index.ResultsCompared with pre-installation, weekly COVID-19 cases per 1000 residents (−1.69; 95% CI, −4.32 to 0.95) and the weekly probability of reporting any COVID-19 case (−0.02; 95% CI, −0.04 to 0.00) declined in the post-installation period. We did not find any difference pre- and post-installation in COVID-19–related mortality (0.00; 95% CI, −0.01 to 0.02).Conclusions and ImplicationsOur findings from this small number of nursing homes in the southern United States demonstrate the potential benefits of air purification in nursing homes on COVID-19 outcomes. Intervening on air quality may have a wide impact without placing significant burden on individuals to modify their behavior. We recommend a stronger, experimental design to estimate the causal effect of installing air purification devices on improving COVID-19 outcomes in nursing homes.     

Admission of nursing home residents to a hospital internal medicine department

ObjectiveHospitalization of nursing home residents is costly and potentially exposes residents to iatrogenic disease and psychological harm.Design and SettingIn this study, we analyzed the data from the Basic Minimum Data Set of patients hospitalized from the nursing home who were discharged from all the internal medicine departments at the National Health Service hospitals in Spain between 2005 and 2008, according to the data provided by the Ministry of Health and Consumer Affairs.ResultsBetween January 2005 and December 2008, 2,134,363 patients were admitted to internal medicine departments in Spain, of whom 45,757 (2.1%) were nursing home residents. Overall, 7898 (17.3%) patients died during hospitalization, 2442 (30.91%) of them in the first 48 hours. The following variables were the significant predictors of in-hospital mortality in multivariate analysis: age (odds ratio [OR] 1.02, 95% confidence intervals [CI] 1.02–1.03), female gender (OR 1.13, 95% CI 1.13–1.17), dementia (OR 1.09, 95% CI 1.03–1.16), previous feeding tube (OR 1.34, 95% CI 1.09–1.79), malignant disease (OR 2.03, 95% CI 1.86–2.23), acute infectious disease (OR 1.18, 95% CI 1.12–1.25), pressure sores (OR 1.88, 95% CI 1.62–1.95), acute respiratory failure (OR 2.00, 95% CI 1.90–2.10), and nosocomial pneumonia (OR 2.5, 95% CI 2.23–2.72).ConclusionsTwo of every 100 patients admitted to internal medicine departments came from nursing homes. The rate of mortality is very high in these patients, with almost one third of patients dying in the first 48 hours, which suggests that many of these transfers were unnecessary. The cost of these admissions for 1 year was equivalent to the annual budget of a 300- to 400-bed public hospital in Spain. The mechanism of coordination between nursing homes and public hospitals must be reviewed with the aim of containing costs and facilitating the care of patients in the last days of life.     

Risk Factors,Presentation, and Course of Coronavirus Disease 2019 in a Large,Academic Long-Term Care Facility

ObjectiveTo describe clinical characteristics and risk factors associated with coronavirus disease 2019 (COVID-19) in long-stay nursing home residents.Design and ParticipantsRetrospective cohort study (March 16, 2020 to May 8, 2020).SettingAcademic long-term chronic care facility (Boston, MA).ParticipantsLong-term care residents.MethodsPatient characteristics and clinical symptoms were obtained via electronic medical records and Minimum Data Set. Staff residence was inferred by zip codes. COVID-19 infection was confirmed by polymerase chain reaction testing using nasopharyngeal swabs. Residents were followed until discharge from facility, death, or up to 21 days. Risks of COVID-19 infection were modeled by generalized estimating equation to estimate the relative risk (RR) and 95% confidence intervals (CI) of patient characteristics and staff community of residence.ResultsOverall 146 of 389 (37.5%) long-stay residents tested positive for COVID-19. At the time of positive test, 66 of 146 (45.5%) residents were asymptomatic. In the subsequent illness course, the most common symptom was anorexia (70.8%), followed by delirium (57.6%). During follow-up, 44 (30.1%) of residents with COVID-19 died. Mortality increased with frailty (16.7% in pre-frail, 22.2% in moderately frail, and 50.0% in frail; P < .001). The proportion of residents infected with COVID-19 varied across the long-term care units (range: 0%‒90.5%). In adjusted models, male sex (RR 1.80, 95% CI 1.07, 3.05), bowel incontinence (RR 1.97, 95% CI 1.10, 3.52), and staff residence remained significant predictors of COVID-19. For every 10% increase in the proportion of staff living in a high prevalence community, the risk of testing positive increased by 6% (95% CI 1.04, 1.08).Conclusions and ImplicationsAmong long-term care residents diagnosed with COVID-19, nearly one-half were asymptomatic at the time of diagnosis. Predictors of COVID-19 infection included male sex, bowel incontinence, and staff residence in a community with a high burden of COVID-19. Universal testing of patients and staff in communities with high COVID-19 rates is essential to mitigate outbreaks.     

Development of a Multivariable Prediction Model for Risk of Hospitalization With Pressure Injury After Entering Residential Aged Care

ObjectivesAlthough largely preventable, pressure injury is a major concern in individuals in permanent residential aged care (PRAC). Our study aimed to identify predictors and develop a prognostic model for risk of hospitalization with pressure injury (PI) using integrated Australian aged and health care data.DesignNational retrospective cohort study.Setting and ParticipantsIndividuals ≥65 years old (N = 206,540) who entered 1797 PRAC facilities between January 1, 2009, and December 31, 2016.MethodsPI, ascertained from hospitalization records, within 365 days of PRAC entry was the outcome of interest. Individual, medication, facility, system, and health care–related factors were examined as predictors. Prognostic models were developed using elastic nets penalized regression and Fine and Gray models. Area under the receiver operating characteristics curve (AUC) assessed model discrimination out-of-sample.ResultsWithin 365 days of PRAC entry, 4.3% (n = 8802) of individuals had a hospitalization with PI. The strongest predictors for PI risk include history of PIs [sub-distribution hazard ratio (sHR) 2.41; 95% CI 1.77–3.29]; numbers of prior hospitalizations (having ≥5 hospitalizations, sHR 1.95; 95% CI 1.74–2.19); history of traumatic amputation of toe, ankle, foot and leg (sHR 1.72; 95% CI 1.44–2.05); and history of skin disease (sHR 1.54; 95% CI 1.45–1.65). Lower care needs at PRAC entry with respect to mobility, complex health care, and medication assistance were associated with lower risk of PI. The risk prediction model had an AUC of 0.74 (95% CI 0.72–0.75).Conclusions and ImplicationsOur prognostic model for risk of hospitalization with PI performed moderately well and can be used by health and aged care providers to implement risk-based prevention plans at PRAC entry.     

Association of Sources of COVID-19 Information with Vaccine Uptake,Preventive Behaviors,and Perceived Severity of COVID-19

ObjectiveTo investigate the association of using informal sources and reliance on multiple sources of information with actual COVID-19 vaccine uptake, the number of doses of vaccine received, COVID-19 testing, essential preventive measures, and perceived severity of COVID-19.DesignRetrospective cross-sectional study.Setting and ParticipantsOur study sample consisted of 9584 community-dwelling Medicare beneficiaries, representing a weighted 50,029,030 beneficiaries from the Winter 2021 Medicare Current Beneficiary Survey COVID-19 Supplement.MethodsTwo key independent variables were whether a respondent relied on a formal source (ie, traditional news, government guidance, or health care providers) or an informal source (ie, social media, Internet, or friends/family) the most for the COVID-19 information and the total number of information sources a respondent relied on.ResultsCompared with beneficiaries relying on formal sources of information, those relying on informal sources of information were less likely to receive COVID-19 vaccine (odds ratio [OR], 0.65; 95% CI, 0.56–0.75) and COVID-19 testing (OR, 0.85; 95% CI, 0.74–0.98), to engage in preventive behaviors (OR, 0.61; 95% CI, 0.50–0.74), to have high perception of COVID-19 severity, and were more likely to be unvaccinated vs 2 doses of vaccine (relative risk ratio [RRR], 1.64; 95% CI, 1.41–1.91). Relying on more information sources was significantly associated with higher odds of actual vaccine uptake (OR, 1.21; 95% CI, 1.17–1.26), COVID-19 testing (OR, 1.11; 95% CI, 1.07–1.15), engagement of essential preventive behaviors (OR, 1.33; 95% CI, 1.25–1.42), having high perception of COVID-19 severity, and with lower likelihood of being unvaccinated vs 2 doses of vaccine (RRR, 0.82; 0.79–0.85).Conclusions and ImplicationsThe COVID-19 pandemic has made communicating information about coronavirus more important than ever. Our findings suggest that information from formal sources with expertise and more balanced sources of information were key to effective communication to prevent from COVID-19 infection among older adults.     

COVID-19 vaccine hesitancy among people living with HIV in a low-resource setting: A multi-center study of prevalence,correlates and reasons

BackgroundHesitancy to COVID-19 vaccine may worsen the burden of COVID-19 among people living with HIV (PLHIV), who are at a higher risk of COVID-19-related hospitalization and death, compared to HIV non-infected individuals. Therefore, we evaluate the predictors and reasons for COVID-19 vaccine hesitancy among unvaccinated PLHIV in six antiretroviral therapy (ART) clinics across northern Nigeria.MethodologyIn this cross-sectional study, conducted between October 2021 and February 2022 in six hospitals across two geopolitical regions of Nigeria, we utilized interviewer-administered questionnaires to assess COVID-19 vaccine hesitancy among a convenience sample of 790 eligible adult PLHIV. Hesitancy was defined as answering ‘no' or ‘maybe’ to a question asking participants their willingness to accept the COVID-19 vaccine. A multivariate logistic regression model was used to estimate the adjusted odds ratio (aOR) and 95% confidence interval (CI) of the factors associated with COVID-19 vaccine hesitancy among PLHIV.ResultsOf the total 660 unvaccinated participants included in the analysis (61.82% female, mean age [SD] of 39.76 [10.75]), 381 (57.72%) were hesitant to COVID-19 vaccine. Being 50 years and older (aOR: 0.43; 95% CI: 0.21–0.89), being unemployed (aOR: 0.57; 95% CI: 0.34–0.95), experiencing the adverse effects of ART (aOR: 0.36; 95% CI: 0.15–0.86), and perception of being at high risk of contracting COVID-19 (aOR: 0.22; 95% CI: 0.13–0.37) were associated with significantly lower odds of hesitancy. Conversely, being female (aOR: 1.64; 95% CI: 1.02–2.61) and attending ART clinics at state administrative capital cities (IIDH Kano [aOR: 2.40; 95% CI: 1.10–5.25], MMSH Kano [aOR: 5.59; 95% CI: 1.97–10.66], YSSH Damaturu [aOR: 9.88; 95% CI: 4.02–24.29] vs. GH Gashua) were associated with significantly higher odds of hesitancy. The most common reasons for hesitancy include fear of potential adverse effects, skepticism about vaccine efficacy, the rapid development of the COVID-19 vaccine, and the perceived lack of effort to develop a cure or vaccine for HIV/AIDS.ConclusionInterventions aimed at combating misperceptions and misinformation regarding the COVID-19 vaccination program may reduce the prevalence of COVID-19 vaccine hesitancy among unvaccinated PLHIV.     

Algorithm for Individual Prediction of COVID-19–Related Hospitalization Based on Symptoms: Development and Implementation Study

BackgroundThe COVID-19 pandemic has placed a huge strain on the health care system globally. The metropolitan area of Milan, Italy, was one of the regions most impacted by the COVID-19 pandemic worldwide. Risk prediction models developed by combining administrative databases and basic clinical data are needed to stratify individual patient risk for public health purposes.ObjectiveThis study aims to develop a stratification tool aimed at improving COVID-19 patient management and health care organization.MethodsA predictive algorithm was developed and applied to 36,834 patients with COVID-19 in Italy between March 8 and the October 9, 2020, in order to foresee their risk of hospitalization. Exposures considered were age, sex, comorbidities, and symptoms associated with COVID-19 (eg, vomiting, cough, fever, diarrhea, myalgia, asthenia, headache, anosmia, ageusia, and dyspnea). The outcome was hospitalizations and emergency department admissions for COVID-19. Discrimination and calibration of the model were also assessed.ResultsThe predictive model showed a good fit for predicting COVID-19 hospitalization (C-index 0.79) and a good overall prediction accuracy (Brier score 0.14). The model was well calibrated (intercept –0.0028, slope 0.9970). Based on these results, 118,804 patients diagnosed with COVID-19 from October 25 to December 11, 2020, were stratified into low, medium, and high risk for COVID-19 severity. Among the overall study population, 67,030 (56.42%) were classified as low-risk patients; 43,886 (36.94%), as medium-risk patients; and 7888 (6.64%), as high-risk patients. In all, 89.37% (106,179/118,804) of the overall study population was being assisted at home, 9% (10,695/118,804) was hospitalized, and 1.62% (1930/118,804) died. Among those assisted at home, most people (63,983/106,179, 60.26%) were classified as low risk, whereas only 3.63% (3858/106,179) were classified at high risk. According to ordinal logistic regression, the odds ratio (OR) of being hospitalized or dead was 5.0 (95% CI 4.6-5.4) among high-risk patients and 2.7 (95% CI 2.6-2.9) among medium-risk patients, as compared to low-risk patients.ConclusionsA simple monitoring system, based on primary care data sets linked to COVID-19 testing results, hospital admissions data, and death records may assist in the proper planning and allocation of patients and resources during the ongoing COVID-19 pandemic.     

The Association Between Chronic Disease and Serious COVID-19 Outcomes and Its Influence on Risk Perception: Survey Study and Database Analysis

BackgroundCOVID-19, a viral respiratory disease first reported in December 2019, quickly became a threat to global public health. Further understanding of the epidemiology of the SARS-CoV-2 virus and the risk perception of the community may better inform targeted interventions to reduce the impact and spread of COVID-19.ObjectiveIn this study, we aimed to examine the association between chronic diseases and serious outcomes following COVID-19 infection, and to explore its influence on people’s self-perception of risk for worse COVID-19 outcomes.MethodsThis study draws data from two databases: (1) the nationwide database of all confirmed COVID-19 cases in Portugal, extracted on April 28, 2020 (n=20,293); and (2) the community-based COVID-19 Barometer survey, which contains data on health status, perceptions, and behaviors during the first wave of COVID-19 (n=171,087). We assessed the association between relevant chronic diseases (ie, respiratory, cardiovascular, and renal diseases; diabetes; and cancer) and death and intensive care unit (ICU) admission following COVID-19 infection. We identified determinants of self-perception of risk for severe COVID-19 outcomes using logistic regression models.ResultsRespiratory, cardiovascular, and renal diseases were associated with mortality and ICU admission among patients hospitalized due to COVID-19 infection (odds ratio [OR] 1.48, 95% CI 1.11-1.98; OR 3.39, 95% CI 1.80-6.40; and OR 2.25, 95% CI 1.66-3.06, respectively). Diabetes and cancer were associated with serious outcomes only when considering the full sample of COVID-19–infected cases in the country (OR 1.30, 95% CI 1.03-1.64; and OR 1.40, 95% CI 1.03-1.89, respectively). Older age and male sex were both associated with mortality and ICU admission. The perception of risk for severe COVID-19 disease in the study population was 23.9% (n=40,890). This was markedly higher for older adults (n=5235, 46.4%), those with at least one chronic disease (n=17,647, 51.6%), or those in both of these categories (n=3212, 67.7%). All included diseases were associated with self-perceptions of high risk in this population.ConclusionsOur results demonstrate the association between some prevalent chronic diseases and increased risk of worse COVID-19 outcomes. It also brings forth a greater understanding of the community’s risk perceptions of serious COVID-19 disease. Hence, this study may aid health authorities to better adapt measures to the real needs of the population and to identify vulnerable individuals requiring further education and awareness of preventive measures.     

Individual-level factors associated with COVID-19 vaccine acceptance among U.S. patients with cancer

IntroductionVaccine hesitancy in the wake of the COVID-19 pandemic is a major public health concern in the US. Cancer patients are especially vulnerable to adverse COVID-19 outcomes and require targeted prevention efforts against COVID-19.MethodsWe used longitudinal survey data from patients seen at Moffitt Cancer Center to identify attitudes, beliefs, and sociodemographic factors associated with COVID-19 vaccination acceptance among cancer patients. Patients with confirmed invasive cancer diagnosis through Cancer Registry data were asked about vaccine acceptance through the question “Now that a COVID-19 vaccine is available, are you likely to get it?” and dichotomized into high accepters (already received it, would get it when available) and low accepters (waiting for a doctor to recommend it, waiting until more people received it, not likely to get it).ResultsMost patients (86.8% of 5,814) were high accepters of the COVID-19 vaccine. High accepters had more confidence in the effectiveness and safety of the vaccine than low accepters. Multivariable logistic regression showed older individuals (70–89 vs.18–49: OR:2.57, 95% CI:1.33–4.86), those with greater perceived severity of COVID-19 infection (very serious vs. not at all serious: OR:2.55, 95% CI:1.76–3.70), practicing more risk mitigation behaviors (per one standard deviation OR:1.75, 95% CI:1.57–1.95), and history of receiving the flu shot versus not (OR:6.56, 95% CI:5.25–8.20) had higher odds of vaccine acceptance. Individuals living with more than one other person (vs. alone: OR: 0.53, 95% CI: 0.35, 0.79) and those who were more socioeconomically disadvantaged (per 10 percentile points: OR: 0.89, 95 %CI: 0.85, 0.93) had lower odds of reporting vaccine acceptance.ConclusionMost patients with cancer have or would receive the COVID-19 vaccine. Those who are less likely to accept the vaccine have more concerns regarding effectiveness and side effects, are younger, more socioeconomically disadvantaged, and have lower perceptions of COVID-19 severity.     

Does BCG provide long-term protection against SARS-CoV-2 infection? A case–control study in Quebec,Canada

BackgroundEarly in the coronavirus disease 2019 (COVID-19) pandemic, before severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines became available, it was hypothesized that BCG (Bacillus Calmette–Guérin), which stimulates innate immunity, could provide protection against SARS-CoV-2. Numerous ecological studies, plagued by methodological deficiencies, revealed a country-level association between BCG use and lower COVID-19 incidence and mortality. We aimed to determine whether BCG administered in early life decreased the risk of SARS-CoV-2 infection in adulthood and the severity of COVID-19.MethodsThis case-control study was conducted in Quebec, Canada. Cases were patients with a positive SARS-CoV-2 nucleic acid amplification test performed at two hospitals between March–October 2020. Controls were identified among patients with non-COVID-19 samples processed by the same microbiology laboratories during the same period. Enrolment was limited to individuals born in Quebec between 1956 and 1976, whose vaccine status was accessible in a computerized registry of 4.2 million BCG vaccinations.ResultsWe recruited 920 cases and 2123 controls. Fifty-four percent of cases (n = 424) and 53% of controls (n = 1127) had received BCG during childhood (OR: 1.03; 95% CI: 0.89–1.21), while 12% of cases (n = 114) and 11% of controls (n = 235) had received two or more BCG doses (OR: 1.14; 95% CI: 0.88–1.46). After adjusting for age, sex, material deprivation, recruiting hospital and occupation there was no evidence of protection conferred by BCG against SARS-CoV-2 (AOR: 1.01; 95% CI: 0.84–1.21). Among cases, 77 (8.4%) needed hospitalization and 18 (2.0%) died. The vaccinated were as likely as the unvaccinated to require hospitalization (AOR: 1.01, 95% CI: 0.62–1.67) or to die (AOR: 0.85, 95% CI: 0.32–2.39).ConclusionsBCG does not provide long-term protection against symptomatic COVID-19 or severe forms of the disease.