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.     

Factors Associated With COVID-19 Hospitalizations and Deaths in French Nursing Homes

ObjectivesTo describe the clinical characteristics and management of residents in French nursing homes with suspected or confirmed coronavirus disease 2019 (COVID-19) and to determine the risk factors for COVID-19–related hospitalization and death in this population.DesignA retrospective multicenter cohort study.Setting and ParticipantsFour hundred eighty nursing home residents with suspected or confirmed COVID-19 between March 1 and May 20, 2020, were enrolled and followed until June 2, 2020, in 15 nursing homes in Marseille’s greater metropolitan area.MethodsDemographic, clinical, laboratory, treatment type, and clinical outcome data were collected from patients’ medical records. Multivariable analysis was used to determine factors associated with COVID-19–related hospitalization and death. For the former, the competing risk analysis—based on Fine and Gray’s model—took death into account.ResultsA total of 480 residents were included. Median age was 88 years (IQR 80-93), and 330 residents were women. A total of 371 residents were symptomatic (77.3%), the most common symptoms being asthenia (47.9%), fever or hypothermia (48.1%), and dyspnea (35.6%). One hundred twenty-three patients (25.6%) were hospitalized and 96 (20%) died. Male gender [specific hazard ratio (sHR) 1.63, 95% confidence interval (CI) 1.12-2.35], diabetes (sHR 1.69, 95% CI 1.15-2.50), an altered level of consciousness (sHR 2.36, 95% CI 1.40-3.98), and dyspnea (sHR 1.69, 95% CI 1.09-2.62) were all associated with a greater risk of COVID-19–related hospitalization. Male gender [odds ratio (OR) 6.63, 95% CI 1.04-42.39], thermal dysregulation (OR 2.64, 95% CI 1.60-4.38), falls (2.21 95% CI 1.02-4.75), and being aged >85 years (OR 2.36, 95% CI 1.32-4.24) were all associated with increased COVID-19–related mortality risk, whereas polymedication (OR 0.46, 95% CI 0.27-0.77) and preventive anticoagulation (OR 0.46, 95% CI 0.27-0.79) were protective prognostic factors.Conclusions and ImplicationsMale gender, being aged >85 years old, diabetes, dyspnea, thermal dysregulation, an altered level of consciousness, and falls must all be considered when identifying and protecting nursing home residents who are at greatest risk of COVID-19–related hospitalization and death.     

COVID-19 Incidence and hospitalization during the delta surge were inversely related to vaccination coverage among the most populous U.S. Counties

ObjectiveWe tested whether COVID-19 incidence and hospitalization rates during the Delta surge were inversely related to vaccination coverage among the 112 most populous counties in the United States, comprising 44 percent of the country's total population.MethodsWe measured vaccination coverage as the percent of the county population fully vaccinated as of July 15, 2021. We measured COVID-19 incidence as the number of confirmed cases per 100,000 population during the 14-day period ending August 12, 2021 and hospitalization rates as the number of confirmed COVID-19 admissions per 100,000 population during the same 14-day period.ResultsIn log-linear regression models, a 10-percentage-point increase in vaccination coverage was associated with a 28.3% decrease in COVID-19 incidence (95% confidence interval, 16.8 - 39.7%), a 44.9 percent decrease in the rate of COVID-19 hospitalization (95% CI, 28.8 - 61.0%), and a 16.6% decrease in COVID-19 hospitalizations per 100 cases (95% CI, 8.4 - 24.8%). Inclusion of demographic covariables, as well as county-specific diabetes prevalence, did not weaken the observed inverse relationship with vaccination coverage. A significant inverse relationship between vaccination coverage and COVID-19 deaths per 100,000 during August 20 – September 16 was also observed. The cumulative incidence of COVID-19 through June 30, 2021, a potential indicator of acquired immunity due to past infection, had no significant relation to subsequent case incidence or hospitalization rates in August.ConclusionHigher vaccination coverage was associated not only with significantly lower COVID-19 incidence during the Delta surge, but also significantly less severe cases of the disease.Public Interest SummaryWe tested whether COVID-19 incidence and hospitalization rates during the Delta variant-related surge were inversely related to vaccination coverage among the 112 most populous counties in the United States, together comprising 44 percent of the country's total population. A 10-percentage-point increase in vaccination coverage was associated with a 28.3% decrease in COVID-19 incidence, a 44.9 percent decrease in the rate of COVID-19 hospitalization, and a 16.6% decrease in COVID-19 hospitalizations per 100 cases. Inclusion of demographic covariables, as well as county-specific diabetes prevalence, did not weaken the observed inverse relationship with vaccination coverage. A significant inverse relationship between vaccination coverage and COVID-19 deaths per 100,000 during August 20 – September 16 was also observed. Higher vaccination coverage was associated not only with significantly lower COVID-19 incidence during the Delta surge, but also significantly less severe cases of the disease.     

U.S. Nursing Home Quality Ratings Associated with COVID-19 Cases and Deaths

ObjectivesTo inform future policies and disaster preparedness plans in the vulnerable nursing home setting, we need greater insight into the relationship between nursing homes’ (NHs’) quality and the spread and severity of COVID-19 in NH facilities. We therefore extend current evidence on the relationships between NH quality and resident COVID-19 infection rates and deaths, taking into account NH structural characteristics and community characteristics.DesignCross-sectional study.Setting and Participants15,390 Medicaid- and Medicare-certified NHs.MethodsWe obtained and merged the following data sets: (1) COVID-19 weekly data reported by each nursing home to the Centers for Disease Control and Prevention’s National Healthcare Safety Network, (2) Centers for Medicare & Medicaid Services Five Star Quality Rating System, (3) county-level COVID-19 case counts, (4) county-level population data, and (5) county-level sociodemographic data.ResultsAmong 1-star NHs, there were an average of 13.19 cases and 2.42 deaths per 1000 residents per week between May 25 and December 20, 2020. Among 5-star NHs, there were an average of 9.99 cases and 1.83 deaths per 1000 residents per week. The rate of confirmed cases of COVID-19 was 31% higher among 1-star NHs compared with 5-star NHs [model 1: incidence rate ratio (IRR) 1.31, 95% confidence interval (CI) 1.23-1.39], and the rate of COVID-19 deaths was 30% higher (IRR 1.30, 95% CI 1.20, 1.41). These associations were only partially explained by differences in community spread of COVID-19, case mix, and the for-profit status and size of NHs.Conclusions and ImplicationsWe found that COVID-19 case and death rates were substantially higher among NHs with lower star ratings, suggesting that NHs with quality much below average are more susceptible to the spread of COVID-19. This relationship, particularly with regard to case rates, can be partially attributed to external factors: lower-rated NHs are often located in areas with greater COVID-19 community spread and serve more socioeconomically vulnerable residents than higher-rated NHs.     

Staffing Shortages,Staffing Hours,and Resident Deaths in US Nursing Homes During the COVID-19 Pandemic

ObjectivesStaffing shortages at nursing homes during the COVID-19 pandemic may have impacted care providers' staffing hours and affected residents’ care and outcomes. This study examines the association of staffing shortages with staffing hours and resident deaths in nursing homes during the COVID-19 pandemic.DesignThis study measured staffing hours per resident using payroll data and measured weekly resident deaths and staffing shortages using the Centers for Disease Control and Prevention's National Healthcare Safety Network data. Multivariate linear regressions with facility and county-week fixed effects were used to investigate the association of staffing shortages with staffing hours and resident deaths.Setting and Participants15,212 nursing homes.MeasuresThe primary outcomes included staffing hours per resident of registered nurses (RNs), licensed practical nurses (LPNs), and certified nursing assistants (CNAs) and weekly total deaths per 100 residents.ResultsBetween May 31, 2020, and May 15, 2022, 18.4% to 33.3% of nursing homes reported staffing shortages during any week. Staffing shortages were associated with lower staffing hours per resident with a 0.009 decrease in RN hours per resident (95% CI 0.005-0.014), a 0.014 decrease in LPN hours per resident (95% CI 0.010-0.018), and a 0.050 decrease in CNA hours per resident (95% CI 0.043-0.057). These are equivalent to a 1.8%, 1.7%, and 2.4% decline, respectively. There was a positive association between staffing shortages and resident deaths with 0.068 (95% CI 0.048-0.088) total deaths per 100 residents. This was equivalent to an increase of 10.5%.Conclusion and ImplicationsOur results showed that self-reported staffing shortages were associated with a statistically significant decrease in staffing hours and with a statistically significant increase in resident deaths. These results suggest that addressing staffing shortages in nursing homes can save lives.     

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.     

Is There a Link between Nursing Home Reported Quality and COVID-19 Cases? Evidence from California Skilled Nursing Facilities

ObjectivesDuring the Coronavirus disease 2019 (COVID-19) outbreak in the United States, nursing homes became the hotbed for the spread of COVID-19. States developed different policies to mitigate the COVID-19 risks at nursing homes, including limiting nursing home visitation and mandating staff screening. The purpose of this study is to examine whether COVID-19 cases and deaths are related to the nursing home reported quality.DesignWe combined the COVID-19 data reported by the California Department of Public Health, quality ratings provided by Nursing Home Compare, and patient racial information from Long-Term Care Focus to examine the association between nursing home reported quality and COVID-19 cases and deaths.Settings and ParticipantsCross-sectional data from 1223 California skilled nursing facilities with reported quality and longitudinal data of COVID-19 cases were used.MethodsThe dependent variable is COVID-19 residents’ cases and deaths. The main independent variable is nursing home reported quality. Nursing home ownership, size, years of operation, and patient race composition are also included.ResultsNursing home star ratings and greater percentage of residents from different racial and ethnicity groups were significantly (P < .01) related to increased probability of having a COVID-19 residents’ case or death.Conclusions and ImplicationsNursing homes with 5-star ratings were less likely to have COVID-19 cases and deaths after adjusting for nursing home size and patient race proportion.     

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.     

The Metrics Matter: Improving Comparisons of COVID-19 Outbreaks in Nursing Homes

ObjectivesIn the United States, nursing facility residents comprise fewer than 1% of the population but more than 40% of deaths due to Coronavirus Disease 2019 (COVID-19). Mitigating the enormous risk of COVID-19 to nursing home residents requires adequate data. The widely used Centers for Medicare & Medicaid Services (CMS) COVID-19 Nursing Home Dataset contains 2 derived statistics: Total Resident Confirmed COVID-19 Cases per 1000 Residents and Total Resident COVID-19 Deaths per 1000 Residents. These metrics provide a misleading picture, as facilities report cumulative counts of cases and deaths over different time periods but use a point-in-time measure as proxy for number of residents (number of occupied beds in a week), resulting in inflated statistics. We propose an alternative statistic to better illustrate the burden of COVID-19 cases and deaths across nursing facilities.DesignRetrospective cohort study.Setting and ParticipantsUsing the CMS Nursing Home Compare and COVID-19 Nursing Home Datasets, we examined facilities with star ratings and COVID-19 data passing quality assurance checks for each reporting period from May 31 to August 16, 2020 (n = 11,115).MethodsWe derived an alternative measure of the number of COVID-19 cases per 1000 residents using the net change in weekly census. For each measure, we compared predicted number of cases/deaths by overall star rating using negative binomial regression with constant dispersion, controlling for county-level cases per capita and nursing home characteristics.ResultsThe average number of cases per 1000 estimated residents using our method is lower compared with the metric using occupied beds as proxy for number of residents (44.8 compared with 66.6). We find similar results when examining number of COVID-19 deaths per 1000 residents.Conclusions and ImplicationsFuture research should estimate the number of residents served in nursing facilities when comparing COVID-19 cases/deaths in nursing facilities. Identifying appropriate metrics for facility-level comparisons is critical to protecting nursing home residents as the pandemic continues.     

Ecological Analysis of the Decline in Incidence Rates of COVID-19 Among Nursing Home Residents Associated with Vaccination,United States,December 2020-January 2021

ObjectiveTo evaluate if facility-level vaccination after an initial vaccination clinic was independently associated with COVID-19 incidence adjusted for other factors in January 2021 among nursing home residents.DesignEcological analysis of data from the CDC's National Healthcare Safety Network (NHSN) and from the CDC's Pharmacy Partnership for Long-Term Care Program.Setting and ParticipantsCMS-certified nursing homes participating in both NHSN and the Pharmacy Partnership for Long-Term Care Program.MethodsA multivariable, random intercepts, negative binomial model was applied to contrast COVID-19 incidence rates among residents living in facilities with an initial vaccination clinic during the week ending January 3, 2021 (n = 2843), vs those living in facilities with no vaccination clinic reported up to and including the week ending January 10, 2021 (n = 3216). Model covariates included bed size, resident SARS-CoV-2 testing, staff with COVID-19, cumulative COVID-19 among residents, residents admitted with COVID-19, community county incidence, and county social vulnerability index (SVI).ResultsIn December 2020 and January 2021, incidence of COVID-19 among nursing home residents declined to the lowest point since reporting began in May, diverged from the pattern in community cases, and began dropping before vaccination occurred. Comparing week 3 following an initial vaccination clinic vs week 2, the adjusted reduction in COVID-19 rate in vaccinated facilities was 27% greater than the reduction in facilities where vaccination clinics had not yet occurred (95% confidence interval: 14%-38%, P < .05).Conclusions and ImplicationsVaccination of residents contributed to the decline in COVID-19 incidence in nursing homes; however, other factors also contributed. The decline in COVID-19 was evident prior to widespread vaccination, highlighting the benefit of a multifaced approach to prevention including continued use of recommended screening, testing, and infection prevention practices as well as vaccination to keep residents in nursing homes safe.     

Stronger Impact of COVID-19 in Nursing Homes of a French Region During the Second Pandemic Wave

ObjectivesQuantify the effects of characteristics of nursing homes and their surroundings on the spread of COVID-19 outbreaks and assess the changes in resident protection between the first 2 waves (March 1 to July 31 and August 1 to December 31, 2020).DesignAn observational study was carried out on data on COVID-19 outbreaks extracted from a database that monitored the spread of the virus in nursing homes.Setting and ParticipantsThe study concerned all 937 nursing homes with >10 beds in Auvergne-Rhône-Alpes region, France.MethodsThe rate of nursing homes with at least 1 outbreak and the cumulative number of deaths were modeled for each wave.ResultsDuring the second (vs the first wave), the proportion of nursing homes that reported at least 1 outbreak was higher (70% vs 56%) and the cumulative number of deaths more than twofold (3348 vs 1590). The outbreak rate was significantly lower in public hospital–associated nursing homes than in private for-profit ones. During the second wave, it was lower in public and private not-for-profit nursing homes than in private for-profit ones. During the first wave, the probability of outbreak and the mean number of deaths increased with the number of beds (P < .001). During the second wave, the probability of outbreak remained stable in >80-bed institutions and, under proportionality assumption, the mean number of deaths was less than expected in >100-bed institutions. The outbreak rate and the cumulative number of deaths increased significantly with the increase in the incidence of hospitalization for COVID-19 in the surrounding populations.Conclusions and ImplicationsThe outbreak in the nursing homes was stronger during the second than the first wave despite better preparedness and higher availabilities of tests and protective equipment. Solutions for insufficient staffing, inadequate rooming, and suboptimal functioning should be found before future epidemics.     

COVID-19 cases,hospitalizations and deaths after vaccination: a cohort event monitoring study,Islamic Republic of Iran

ObjectiveTo investigate the incidence of coronavirus disease 2019 (COVID-19) cases, hospitalizations and deaths in Iranians vaccinated with either AZD1222 Vaxzevria, CovIran® vaccine, SARS-CoV-2 Vaccine (Vero Cell), Inactivated (lnCoV) or Sputnik V.MethodsWe enrolled individuals 18 years or older receiving their first COVID-19 vaccine dose between April 2021 and January 2022 in seven Iranian cities. Participants completed weekly follow-up surveys for 17 weeks (25 weeks for AZD1222) to report their COVID-19 status and hospitalization. We used Cox regression models to assess risk factors for contracting COVID-19, hospitalization and death.FindingsOf 89 783 participants enrolled, incidence rates per 1 000 000 person-days were: 528.2 (95% confidence interval, CI: 514.0–542.7) for contracting COVID-19; 55.8 (95% CI: 51.4–60.5) for hospitalization; and 4.1 (95% CI: 3.0–5.5) for death. Compared with SARS-CoV-2 Vaccine (Vero Cell), hazard ratios (HR) for contracting COVID-19 were: 0.70 (95% CI: 0.61−0.80) with AZD1222; 0.73 (95% CI: 0.62–0.86) with Sputnik V; and 0.73 (95% CI: 0.63–0.86) with CovIran®. For hospitalization and death, all vaccines provided similar protection 14 days after the second dose. History of COVID-19 protected against contracting COVID-19 again (HR: 0.76; 95% CI: 0.69–0.84). Diabetes and respiratory, cardiac and renal disease were associated with higher risks of contracting COVID-19 after vaccination.ConclusionThe rates of contracting COVID-19 after vaccination were relatively high. SARS-CoV-2 Vaccine (Vero Cell) provided lower protection against COVID-19 than other vaccines. People with comorbidities had higher risks of contracting COVID-19 and hospitalization and should be prioritized for preventive interventions.     

The Adverse Effects of the COVID-19 Pandemic on Nursing Home Resident Well-Being

ObjectiveQuantify the effects of the COVID-19 pandemic on nursing home resident well-being.DesignQuantitative analysis of resident-level assessment data.Setting and participantsLong-stay residents living in Connecticut nursing homes.MethodsWe used Minimum Data Set assessments to measure nursing home resident outcomes observed in each week between March and July 2020 for long-stay residents (eg, those in the nursing home for at least 100 days) who lived in a nursing home at the beginning of the pandemic. We compared outcomes to those observed at the beginning of the pandemic, controlling for both resident characteristics and patterns for outcomes observed in 2017-2019.ResultsWe found that nursing home resident outcomes worsened on a broad array of measures. The prevalence of depressive symptoms increased by 6 percentage points relative to before the pandemic in the beginning of March—representing a 15% increase. The share of residents with unplanned substantial weight loss also increased by 6 percentage points relative to the beginning of March—representing a 150% increase. We also found significant increases in episodes of incontinence (4 percentage points) and significant reductions in cognitive functioning. Our findings suggest that loneliness and isolation play an important role. Though unplanned substantial weight loss was greatest for those who contracted COVID-19 (about 10% of residents observed in each week), residents who did not contract COVID-19 also physically deteriorated (about 7.5% of residents in each week).Conclusions and ImplicationsThese analyses show that the pandemic had substantial impacts on nursing home residents beyond what can be quantified by cases and deaths, adversely affecting the physical and emotional well-being of residents. Future policy changes to limit the spread of COVID-19 or other infectious disease outbreaks should consider any additional costs beyond the direct effects of morbidity and mortality due to COVID-19.     

Safety Climate Associated With Adverse Events in Nursing Homes: A National VA Study

ObjectivesAdverse events in nursing homes are leading causes of morbidity and mortality, prompting facilities to investigate their antecedents. This study examined the contribution of safety climate—how frontline staff typically think about safety and act on safety issues—to adverse events in Veterans Affairs (VA) nursing homes or Community Living Centers (CLCs).DesignCross-sectional study.Setting and ParticipantsA total of 56 CLCs nationwide, 1397 and 1645 CLC staff (including nurses, nursing assistants, and clinicians/specialists), respectively, responded to the CLC Employee Survey of Attitudes about Resident Safety (CESARS) in 2017 and 2018.MethodsAdverse events (pressure ulcers, falls, major injuries from falls, and catheter use) were measured using the FY2017-FY2018 Minimum Data Set (MDS). Safety climate was defined as 7 CESARS domains (safety priorities, supervisor commitment to safety, senior management commitment to safety, personal attitudes toward safety, environmental safety, coworker interactions around safety, and global rating of CLC). The associations between safety climate domains and each adverse event were determined separately for each frontline group, using beta-logistic regression with random effects.ResultsBetter ratings of supervisor commitment to safety were associated with lower rates of major injuries from falls [odds ratio (OR) 0.33, 95% confidence interval (CI) 0.11-0.97, clinicians] and catheter use (OR 0.42, 95% CI 0.21-0.85, nurses), and better ratings of environmental safety were associated with lower rates of pressure ulcers (OR 0.23, 95% CI 0.09-0.61, clinicians), major injuries from falls (OR 0.48, 95% CI 0.24-0.93, nurses), and catheter use (OR 0.55, 95% CI 0.32-0.93, nursing assistants). Better global CLC ratings were associated with higher rates of catheter use. No other safety climate domains had significant associations.Conclusions and ImplicationsNursing homes may reduce adverse events by fostering supportive supervision of frontline staff and a safer physical environment.     

Excess Mortality During the COVID-19 Pandemic in Jordan: Secondary Data Analysis

BackgroundAll-cause mortality and estimates of excess deaths are commonly used in different countries to estimate the burden of COVID-19 and assess its direct and indirect effects.ObjectiveThis study aimed to analyze the excess mortality during the COVID-19 pandemic in Jordan in April-December 2020.MethodsOfficial data on deaths in Jordan for 2020 and previous years (2016-2019) were obtained from the Department of Civil Status. We contrasted mortality rates in 2020 with those in each year and the pooled period 2016-2020 using a standardized mortality ratio (SMR) measure. Expected deaths for 2020 were estimated by fitting the overdispersed Poisson generalized linear models to the monthly death counts for the period of 2016-2019.ResultsOverall, a 21% increase in standardized mortality (SMR 1.21, 95% CI 1.19-1.22) occurred in April-December 2020 compared with the April-December months in the pooled period 2016-2019. The SMR was more pronounced for men than for women (SMR 1.26, 95% CI 1.24-1.29 vs SMR 1.12, 95% CI 1.10-1.14), and it was statistically significant for both genders (P<.05). Using overdispersed Poisson generalized linear models, the number of expected deaths in April-December 2020 was 12,845 (7957 for women and 4888 for men). The total number of excess deaths during this period was estimated at 4583 (95% CI 4451-4716), with higher excess deaths in men (3112, 95% CI 3003-3221) than in women (1503, 95% CI 1427-1579). Almost 83.66% of excess deaths were attributed to COVID-19 in the Ministry of Health database. The vast majority of excess deaths occurred in people aged 60 years or older.ConclusionsThe reported COVID-19 death counts underestimated mortality attributable to COVID-19. Excess deaths could reflect the increased deaths secondary to the pandemic and its containment measures. The majority of excess deaths occurred among old age groups. It is, therefore, important to maintain essential services for the elderly during pandemics.     

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.