SARS-CoV-2 spread and area economic disadvantage in the italian three-tier restrictions: a multilevel approach.

BACKGROUND: To face the second wave of COVID-19, Italy implemented a tiered restriction system with different limitation levels (yellow = medium; orange = medium-high, red = high) at the beginning of November 2020. The restrictions systematically reduced the transmission of SARS-CoV-2 with increasing strength for increasing tier. However, it is unknown whether the effect of limitations was equal between provinces with different socioeconomic levels. Therefore, we investigated the association between the province's socioeconomic level and SARS-CoV-2 infection daily reproduction number in each restriction level. METHODS: We measured the province's socioeconomic level as the percentage of individuals whose 2019 total yearly income was lower than 10,000€, using the measure as a proxy of economic disadvantage. We estimated the daily reproduction number (Rt) at the province level using the SARS-CoV-2 daily incidence data from November 2020 to May 2021. We then used multilevel linear regression models with random intercepts stratified by restriction level to estimate the association between economic disadvantage and Rt. We also adjusted the analyses for potential confounders of the association between the province's economic disadvantage and the Rt: the percentage of people with 0-5 years, the quartiles of population density, and the geographical repartition. RESULTS: Overall, we found increasing Rt in yellow (+ 0.004 p < 0.01, from Rt = 0.99 to 1.08 in three weeks) and containing effects for the orange (-0.005 p < 0.01, from Rt = 1.03 to 0.93) and the red tier (-0.014 p < 0.01, from Rt = 1.05 to 0.76). More economically disadvantaged provinces had higher Rt levels in every tier, although non-significantly in the yellow level (yellow = 0.001 p = 0.19; orange = 0.002 p = 0.02; red = 0.004 p < 0.01). The results showed that the association between economic disadvantage and Rt differed by level of restriction. The number of days into the restriction and the economic disadvantage had statistically significant interactions in every adjusted model. Compared to better off, more economically disadvantaged provinces had slower increasing trends in yellow and steeper Rt reductions in orange, but they showed slower Rt reductions in the highest tier. CONCLUSION: Lower tiers were more effective in more economically disadvantaged provinces, while the highest restriction level had milder effects. These results underline the importance of accounting for socioeconomic level when implementing public health measures.

Air pollution, SARS-CoV-2 incidence and COVID-19 mortality in Rome – a longitudinal study

Chronic exposure to ambient air pollution has been related to increased mortality in the general population [1]. After the outbreak of SARS-CoV-2 pandemic in 2019, there has been a fast proliferation of epidemiological studies linking ambient air pollution to COVID-19 incidence or adverse prognosis [2]. It has been hypothesised that ambient air pollution might increase human vulnerability to viruses by reducing immune defences, promoting a low-level chronic inflammatory state, or leading to chronic diseases [3]. Most studies applied ecological designs, and failed to account for key individual-level or area-level determinants of COVID-19 spread or severity, such as demographic characteristics of the studied populations, socioeconomic or clinical susceptibility, and area-level proxies of disease spread such as mobility or population density [4].

Indirect impact of the COVID-19 pandemic and its containment measures on social inequalities in hospital utilisation in Italy.

BACKGROUND: The pandemic may undermine the equity of access to and utilisation of health services for conditions other than COVID-19. The objective of the study is to evaluate the indirect impact of COVID-19 and lockdown measures on sociodemographic inequalities in healthcare utilisation in seven Italian areas. METHODS: In this multicentre retrospective study, we evaluated whether COVID-19 modified the association between educational level or deprivation and indicators of hospital utilisation and quality of care. We also assessed variations in gradients by sex and age class. We estimated age-standardised rates and prevalence and their relative per cent changes comparing pandemic (2020) and pre-pandemic (2018-2019) periods, and the Relative Index of Inequalities (RIIs) fitting multivariable Poisson models with an interaction between socioeconomic position and period. RESULTS: Compared with 2018-2019, hospital utilisation and, to a lesser extent, timeliness of procedures indicators fell during the first months of 2020. Larger declines were registered among women, the elderly and the low educated resulting in a shrinkage (or widening if RII <1) of the educational gradients for most of the indicators. Timeliness of procedures indicators did not show any educational gradient neither before nor during the pandemic. Inequalities by deprivation were nuanced and did not substantially change in 2020. CONCLUSIONS: The socially patterned reduction of hospital utilisation may lead to a potential exacerbation of health inequalities among groups who were already vulnerable before the pandemic. The healthcare service can contribute to contrast health disparities worsened by COVID-19 through more efficient communication and locally appropriate interventions.

Educational Inequalities in COVID-19 Vaccination: A Cross-Sectional Study of the Adult Population in the Lazio Region, Italy.

Several studies reported socioeconomic inequalities during the COVID-19 pandemic. We aimed at investigating educational inequalities in COVID-19 vaccination on 22 December 2021. We used the cohort of all residents in the Lazio Region, Central Italy, established at the beginning of the pandemic to investigate the effects of COVID-19. The Lazio Region has 5.5 million residents, mostly distributed in the Metropolitan Area of Rome (4.3 million inhabitants). We selected those aged 35 years or more who were alive and still residents on 22 December 2021. The cohort included data on sociodemographic, health characteristics, COVID-19 vaccination (none, partial, or complete), and SARS-CoV-2 infection. We used adjusted logistic regression models to analyze the association between level of education and no vaccination. We investigated 3,186,728 subjects (54% women). By the end of 2021, 88.1% of the population was fully vaccinated, and 10.3% were not vaccinated. There were strong socioeconomic inequalities in not getting vaccinated: compared with those with a university degree, residents with a high school degree had an odds ratio (OR) of 1.29 (95% confidence interval, CI, 1.27-1.30), and subjects with a junior high or primary school attainment had an OR = 1.41 (95% CI: 1.40-1.43). Since a comprehensive vaccination against COVID-19 could help reduce socioeconomic inequalities raised with the pandemic, further efforts in reaching the low socioeconomic strata of the population are crucial.

Incidence of SARS-CoV-2 Infection and Related Mortality by Education Level during Three Phases of the 2020 Pandemic: A Population-Based Cohort Study in Rome.

Evidence on social determinants of health on the risk of SARS-CoV-2 infection and adverse outcomes is still limited. Therefore, this work investigates educational disparities in the incidence of infection and mortality within 30 days of the onset of infection during 2020 in Rome, with particular attention to changes in socioeconomic inequalities over time. A cohort of 1,538,231 residents in Rome on 1 January 2020, aged 35+, followed from 1 March to 31 December 2020, were considered. Cumulative incidence and mortality rates by education were estimated. Multivariable log-binomial and Cox regression models were used to investigate educational disparities in the incidence of SARS-CoV-2 infection and mortality during the entire study period and in three phases of the pandemic. During 2020, there were 47,736 incident cases and 2281 deaths. The association between education and the incidence of infection changed over time. Till May 2020, low- and medium-educated individuals had a lower risk of infection than that of the highly educated. However, there was no evidence of an association between education and the incidence of SARS-CoV-2 infection during the summer. Lastly, low-educated adults had a 25% higher risk of infection from September to December than that of the highly educated. Similarly, there was substantial evidence of educational inequalities in mortality within 30 days of the onset of infection in the last term of 2020. In Rome, social inequalities in COVID-19 appeared in the last term of 2020, and they strengthen the need for monitoring inequalities emerging from this pandemic.

Delirium in Patients with SARS-CoV-2 Infection: A Multicenter Study.

OBJECTIVES: The aims of this study are to report the prevalence of delirium on admission to the unit in patients hospitalized with SARS-CoV-2 infection, to identify the factors associated with delirium, and to evaluate the association between delirium and in-hospital mortality. DESIGN: Multicenter observational cohort study. SETTINGS: Acute medical units in four Italian hospitals. PARTICIPANTS: A total of 516 patients (median age 78 years) admitted to the participating centers with SARS-CoV-2 infection from February 22 to May 17, 2020. MEASUREMENTS: Comprehensive medical assessment with detailed history, physical examinations, functional status, laboratory and imaging procedures. On admission, delirium was determined by the Diagnostic and Statistical Manual of Mental Disorders (5th edition) criteria, 4AT, m-Richmond Agitation Sedation Scale, or clinical impression depending on the site. The primary outcomes were delirium rates and in-hospital mortality. RESULTS: Overall, 73 (14.1%, 95% confidence interval (CI) = 11.0-17.3%) patients presented delirium on admission. Factors significantly associated with delirium were dementia (odds ratio, OR = 4.66, 95% CI = 2.03-10.69), the number of chronic diseases (OR = 1.20, 95% CI = 1.03; 1.40), and chest X-ray or CT opacity (OR = 3.29, 95% CI = 1.12-9.64 and 3.35, 95% CI = 1.07-10.47, for multiple or bilateral opacities and single opacity vs no opacity, respectively). There were 148 (33.4%) in-hospital deaths in the no-delirium group and 43 (58.9%) in the delirium group (P-value assessed using the Gray test <.001). As assessed by a multivariable Cox model, patients with delirium on admission showed an almost twofold increased hazard ratio for in-hospital mortality with respect to patients without delirium (hazard ratio = 1.88, 95% CI = 1.25-2.83). CONCLUSION: Delirium is prevalent and associated with in-hospital mortality among older patients hospitalized with SARS-CoV-2 infection.

Predicting Mortality Risk in Older Hospitalized Persons With COVID-19: A Comparison of the COVID-19 Mortality Risk Score with Frailty and Disability.

OBJECTIVES: To assess the association of pre-morbid functional status [Barthel Index (BI)] and frailty [modified Frailty Index (mFI)] with in-hospital mortality and a risk scoring system developed for COVID-19 in patients ≥75 years diagnosed with COVID-19. DESIGN: Retrospective bicentric observational study. SETTING AND PARTICIPANTS: Data on consecutive patients aged ≥75 years admitted with COVID-19 at 2 Italian tertiary care centers were collected from February 22 to May 30, 2020. METHODS: Overall, 221 consecutive patients with COVID-19 aged ≥75 years were admitted to 2 hospitals in the study period and were included in the analysis. Clinical, functional (BI), frailty (mFI), laboratory, and imaging data were collected. Mortality risk on admission was assessed with the COVID-19 Mortality Risk Score (COVID-19 MRS), a dedicated score developed for hospital triage. RESULTS: Ninety-seven (43.9%) patients died. BI, frailty, age, dementia, respiratory rate, Pao2/Fio2 ratio, creatinine, and platelet count were associated with mortality. Analysis of the area under the receiver operating characteristic (AUC) indicated that the predictivity of age was modest and the combination of BI, mFI, and COVID-19 MRS yielded the highest prediction accuracy (AUCCOVID-19MRS+BI+mFI vs AUCAge: 0.87 vs 0.59; difference: +0.28, lower bound-upper bound: 0.17-0.34, P < .001). CONCLUSIONS AND IMPLICATIONS: Premorbid BI and mFI are associated with mortality and improved the accuracy of the COVID-19 MRS. Functional status may prove useful to guide clinical management of older individuals.

Delirium: Clinical Presentation and Outcomes in Older COVID-19 Patients.

The aim of the study is to describe the clinical characteristics and outcomes of a series of older patients consecutively admitted into a non-ICU ward due to SARS-CoV-2 infection (14, males 11), developing delirium. Hypokinetic delirium with lethargy and confusion was observed in 43% of cases (6/14 patients). A total of eight patients exhibited hyperkinetic delirium and 50% of these patients (4/8) died. The overall mortality rate was 71% (10/14 patients). Among the four survivors we observed two different clinical patterns: two patients exhibited dementia and no ARDS (acute respiratory distress syndrome), while the remaining two patients exhibited ARDS and no dementia. The observed different clinical patterns of delirium (hypokinetic delirium; hyperkinetic delirium with or without dementia; hyperkinetic delirium with or without ARDS) identified patients with different prognosis: we believe these observations may have an impact on the management of older subjects with delirium due to COVID-19.

Clinical risk score to predict in-hospital mortality in COVID-19 patients: a retrospective cohort study.

OBJECTIVES: Several physiological abnormalities that develop during COVID-19 are associated with increased mortality. In the present study, we aimed to develop a clinical risk score to predict the in-hospital mortality in COVID-19 patients, based on a set of variables available soon after the hospitalisation triage. SETTING: Retrospective cohort study of 516 patients consecutively admitted for COVID-19 to two Italian tertiary hospitals located in Northern and Central Italy were collected from 22 February 2020 (date of first admission) to 10 April 2020. PARTICIPANTS: Consecutive patients≥18 years admitted for COVID-19. MAIN OUTCOME MEASURES: Simple clinical and laboratory findings readily available after triage were compared by patients' survival status ('dead' vs 'alive'), with the objective of identifying baseline variables associated with mortality. These were used to build a COVID-19 in-hospital mortality risk score (COVID-19MRS). RESULTS: Mean age was 67±13 years (mean±SD), and 66.9% were male. Using Cox regression analysis, tertiles of increasing age (≥75, upper vs <62 years, lower: HR 7.92; p<0.001) and number of chronic diseases (≥4 vs 0-1: HR 2.09; p=0.007), respiratory rate (HR 1.04 per unit increase; p=0.001), PaO2/FiO2 (HR 0.995 per unit increase; p<0.001), serum creatinine (HR 1.34 per unit increase; p<0.001) and platelet count (HR 0.995 per unit increase; p=0.001) were predictors of mortality. All six predictors were used to build the COVID-19MRS (Area Under the Curve 0.90, 95% CI 0.87 to 0.93), which proved to be highly accurate in stratifying patients at low, intermediate and high risk of in-hospital death (p<0.001). CONCLUSIONS: The COVID-19MRS is a rapid, operator-independent and inexpensive clinical tool that objectively predicts mortality in patients with COVID-19. The score could be helpful from triage to guide earlier assignment of COVID-19 patients to the most appropriate level of care.