[Long-term exposure to ambient air pollution and the incidence of SARS-CoV-2 infections in Italy: The EpiCovAir study]. / Esposizione a lungo termine a inquinamento dell'aria ambiente e incidenza di infezioni di SARS-CoV-2 in Italia: lo studio EpiCovAir.

BACKGROUND: after the outbreak of the SARS-CoV-2 pandemic in 2020, several waves of pandemic cases have occurred in Italy. The role of air pollution has been hypothesized and investigated in several studies. However, to date, the role of chronic exposure to air pollutants in increasing incidence of SARS-CoV-2 infections is still debated. OBJECTIVES: to investigate the association between long-term exposure to air pollutants and the incidence of SARS-CoV-2 infections in Italy. DESIGN: a satellite-based air pollution exposure model with 1-km2 spatial resolution for entire Italy was applied and 2016-2019 mean population-weighted concentrations of particulate matter < 10 micron (PM10), PM <2.5 micron (PM2.5), and nitrogen dioxide (NO2) was calculated to each municipality as estimates of chronic exposures. A principal component analysis (PCA) approach was applied to 50+ area-level covariates (geography and topography, population density, mobility, population health, socioeconomic status) to account for the major determinants of the spatial distribution of incidence rates of SARS-CoV-2 infection. Detailed information was further used on intra- and inter-municipal mobility during the pandemic period. Finally, a mixed longitudinal ecological design with the study units consisting of individual municipalities in Italy was applied. Generalized negative binomial models controlling for age, gender, province, month, PCA variables, and population density were estimated. SETTING AND PARTICIPANTS: individual records of diagnosed SARS-2-CoV-2 infections in Italy from February 2020 to June 2021 reported to the Italian Integrated Surveillance of COVID-19 were used. MAIN OUTCOME MEASURES: percentage increases in incidence rate (%IR) and corresponding 95% confidence intervals (95% CI) per unit increase in exposure. RESULTS: 3,995,202 COVID-19 cases in 7,800 municipalities were analysed (total population: 59,589,357 inhabitants). It was found that long-term exposure to PM2.5, PM10, and NO2 was significantly associated with the incidence rates of SARS-CoV-2 infection. In particular, incidence of COVID-19 increased by 0.3% (95%CI 0.1%-0.4%), 0.3% (0.2%-0.4%), and 0.9% (0.8%-1.0%) per 1 µg/m3 increment in PM2.5, PM10 and NO2, respectively. Associations were higher among elderly subjects and during the second pandemic wave (September 2020-December 2020). Several sensitivity analyses confirmed the main results. The results for NO2 were especially robust to multiple sensitivity analyses. CONCLUSIONS: evidence of an association between long-term exposure to ambient air pollutants and the incidence of SARS-CoV-2 infections in Italy was found.

Long-Term Exposure to Ambient Air Pollution and Mortality among Four Million COVID-19 Cases in Italy: The EpiCovAir Study.

BACKGROUND: The role of chronic exposure to ambient air pollutants in increasing COVID-19 fatality is still unclear. OBJECTIVES: The study aimed to investigate the association between long-term exposure to air pollutants and mortality among 4 million COVID-19 cases in Italy. METHODS: We obtained individual records of all COVID-19 cases identified in Italy from February 2020 to June 2021. We assigned 2016-2019 mean concentrations of particulate matter (PM) with aerodynamic diameter ≤10µm (PM10), PM with aerodynamic diameter ≤2.5µm (PM2.5), and nitrogen dioxide (NO2) to each municipality (n=7,800) as estimates of chronic exposures. We applied a principal component analysis (PCA) and a generalized propensity score (GPS) approach to an extensive list of area-level covariates to account for major determinants of the spatial distribution of COVID-19 case-fatality rates. Then, we applied generalized negative binomial models matched on GPS, age, sex, province, and month. As additional analyses, we fit separate models by pandemic periods, age, and sex; we quantified the numbers of COVID-19 deaths attributable to exceedances in annual air pollutant concentrations above predefined thresholds; and we explored associations between air pollution and alternative outcomes of COVID-19 severity, namely hospitalizations or accesses to intensive care units. RESULTS: We analyzed 3,995,202 COVID-19 cases, which generated 124,346 deaths. Overall, case-fatality rates increased by 0.7% [95% confidence interval (CI): 0.5%, 0.9%], 0.3% (95% CI: 0.2%, 0.5%), and 0.6% (95% CI: 0.5%, 0.8%) per 1 µg/m3 increment in PM2.5, PM10, and NO2, respectively. Associations were higher among elderly subjects and during the first (February 2020-June 2020) and the third (December 2020-June 2021) pandemic waves. We estimated ∼8% COVID-19 deaths were attributable to pollutant levels above the World Health Organization 2021 air quality guidelines. DISCUSSION: We found suggestive evidence of an association between long-term exposure to ambient air pollutants with mortality among 4 million COVID-19 cases in Italy. https://doi.org/10.1289/EHP11882.

Protection against severe COVID-19 after second booster dose of adapted bivalent (original/Omicron BA.4-5) mRNA vaccine in persons ≥ 60 years, by time since infection, Italy, 12 September to 11 December 2022.

Effectiveness against severe COVID-19 of a second booster dose of the bivalent (original/BA.4-5) mRNA vaccine 7-90 days post-administration, relative to a first booster dose of an mRNA vaccine received ≥ 120 days earlier, was ca 60% both in persons ≥ 60 years never infected and in those infected > 6 months before. Relative effectiveness in those infected 4-6 months earlier indicated no significant additional protection (10%; 95% CI: -44 to 44). A second booster vaccination 6 months after the latest infection may be warranted.

Characteristics of COVID-19 cases in Italy from a sex/gender perspective.

INTRODUCTION: Coronavirus disease 19 (COVID-19) is an infectious disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). To date, few data on clinical features and risk factors for disease severity and death by gender are available. AIM: The current study aims to describe from a sex/gender perspective the characteristics of the SARS-CoV-2 cases occurred in the Italian population from February 2020 until October 2021. METHOD AND RESULTS: We used routinely collected data retrieved from the Italian National Surveillance System. The highest number of cases occurred among women between 40 and 59 years, followed by men in the same age groups. The proportion of deaths due to COVID-19 was higher in men (56.46%) compared to women (43.54%). Most of the observed deaths occurred in the elderly. Considering the age groups, the clinical outcomes differed between women and men in particular in cases over 80 years of age; with serious or critical conditions more frequent in men than in women. CONCLUSIONS: Our data clearly demonstrate a similar number of cases in women and men, but with more severe disease and outcome in men, thus confirming the importance to analyse the impact of sex and gender in new and emerging diseases.

Assessing COVID-19-Related Excess Mortality Using Multiple Approaches-Italy, 2020-2021.

INTRODUCTION: Excess mortality (EM) is a valid indicator of COVID-19's impact on public health. Several studies regarding the estimation of EM have been conducted in Italy, and some of them have shown conflicting values. We focused on three estimation models and compared their results with respect to the same target population, which allowed us to highlight their strengths and limitations. METHODS: We selected three estimation models: model 1 (Maruotti et al.) is a Negative-Binomial GLMM with seasonal patterns; model 2 (Dorrucci et al.) is a Negative Binomial GLM epidemiological approach; and model 3 (Scortichini et al.) is a quasi-Poisson GLM time-series approach with temperature distributions. We extended the time windows of the original models until December 2021, computing various EM estimates to allow for comparisons. RESULTS: We compared the results with our benchmark, the ISS-ISTAT official estimates. Model 1 was the most consistent, model 2 was almost identical, and model 3 differed from the two. Model 1 was the most stable towards changes in the baseline years, while model 2 had a lower cross-validation RMSE. DISCUSSION: Presently, an unambiguous explanation of EM in Italy is not possible. We provide a range that we consider sound, given the high variability associated with the use of different models. However, all three models accurately represented the spatiotemporal trends of the pandemic waves in Italy.

Estimation of the incubation period and generation time of SARS-CoV-2 Alpha and Delta variants from contact tracing data.

Quantitative information on epidemiological quantities such as the incubation period and generation time of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants is scarce. We analysed a dataset collected during contact tracing activities in the province of Reggio Emilia, Italy, throughout 2021. We determined the distributions of the incubation period for the Alpha and Delta variants using information on negative polymerase chain reaction tests and the date of last exposure from 282 symptomatic cases. We estimated the distributions of the intrinsic generation time using a Bayesian inference approach applied to 9724 SARS-CoV-2 cases clustered in 3545 households where at least one secondary case was recorded. We estimated a mean incubation period of 4.9 days (95% credible intervals, CrI, 4.4-5.4) for Alpha and 4.5 days (95% CrI 4.0-5.0) for Delta. The intrinsic generation time was estimated to have a mean of 7.12 days (95% CrI 6.27-8.44) for Alpha and of 6.52 days (95% CrI 5.54-8.43) for Delta. The household serial interval was 2.43 days (95% CrI 2.29-2.58) for Alpha and 2.74 days (95% CrI 2.62-2.88) for Delta, and the estimated proportion of pre-symptomatic transmission was 48-51% for both variants. These results indicate limited differences in the incubation period and intrinsic generation time of SARS-CoV-2 variants Alpha and Delta compared to ancestral lineages.

Relative effectiveness of a 2nd booster dose of COVID-19 mRNA vaccine up to four months post administration in individuals aged 80 years or more in Italy: A retrospective matched cohort study.

Several countries started a 2nd booster COVID-19 vaccination campaign targeting the elderly population, but evidence around its effectiveness is still scarce. This study aims to estimate the relative effectiveness of a 2nd booster dose of COVID-19 mRNA vaccine in the population aged ≥ 80 years in Italy, during predominant circulation of the Omicron BA.2 and BA.5 subvariants. We linked routine data from the national vaccination registry and the COVID-19 surveillance system. On each day between 11 April and 6 August 2022, we matched 1:1, according to several demographic and clinical characteristics, individuals who received the 2nd booster vaccine dose with individuals who received the 1st booster vaccine dose at least 120 days earlier. We used the Kaplan-Meier method to compare the risks of SARS-CoV-2 infection and severe COVID-19 (hospitalisation or death) between the two groups, calculating the relative vaccine effectiveness (RVE) as (1 - risk ratio)X100. Based on the analysis of 831,555 matched pairs, we found that a 2nd booster dose of mRNA vaccine, 14-118 days post administration, was moderately effective in preventing SARS-CoV-2 infection compared to a 1st booster dose administered at least 120 days earlier [14.3 %, 95 % confidence interval (CI): 2.2-20.2]. RVE decreased from 28.5 % (95 % CI: 24.7-32.1) in the time-interval 14-28 days to 7.6 % (95 % CI: -14.1 to 18.3) in the time-interval 56-118 days. However, RVE against severe COVID-19 was higher (34.0 %, 95 % CI: 23.4-42.7), decreasing from 43.2 % (95 % CI: 30.6-54.9) to 27.2 % (95 % CI: 8.3-42.9) over the same time span. Although RVE against SARS-CoV-2 infection was much reduced 2-4 months after a 2nd booster dose, RVE against severe COVID-19 was about 30 %, even during prevalent circulation of the Omicron BA.5 subvariant. The cost-benefit of a 3rd booster dose for the elderly people who received the 2nd booster dose at least four months earlier should be carefully evaluated.

Reduction of the risk of severe COVID-19 due to Omicron compared to Delta variant in Italy (November 2021 - February 2022).

OBJECTIVES: During 2022, Omicron became the dominant SARS-CoV-2 variant in Europe. This study aims to assess the impact of such variant on severe disease from SARS-CoV-2 compared with the Delta variant in Italy. METHODS: Using surveillance data, we assessed the risk of developing severe COVID-19 with Omicron infection compared with Delta in individuals aged ≥12 years using a multilevel negative binomial model adjusting for sex, age, vaccination status, occupation, previous infection, weekly incidence, and geographical area. We also analyzed the interaction between the sequenced variant, age, and vaccination status. RESULTS: We included 21,645 cases of SARS-CoV-2 infection where genome sequencing found Delta (10,728) or Omicron (10,917), diagnosed from November 15, 2021 to February 01, 2022. Overall, 3,021 cases developed severe COVID-19. We found that Omicron cases had a reduced risk of severe COVID-19 compared with Delta cases (incidence rate ratio [IRR] = 0.77; 95% confidence interval [CI]: 0.70-0.86). The largest difference was observed in cases aged 40-59 (IRR = 0.66; 95% CI: 0.55-0.79), while no protective effect was found in those aged 12-39 (IRR = 1.03; 95% CI: 0.79-1.33). Vaccination was associated with a lower risk of developing severe COVID-19 in both variants. CONCLUSION: The Omicron variant is associated with a lower risk of severe COVID-19 compared to infection with the Delta variant, but the degree of protection varies with age.

Decline in reported measles cases in Italy in the COVID-19 era, January 2020 - July 2022: The need to prevent a resurgence upon lifting non-pharmaceutical pandemic measures.

From January 2020 to July 2022, 120 measles cases were reported to the Italian national surveillance system, of which 105 had symptom onset in 2020, nine in 2021 and six in the first seven months of 2022. This represents a sharp decline compared to the time period immediately preceding the COVID-19 pandemic, most likely due to the non-pharmaceutical interventions implemented to prevent SARS-CoV2 transmission. Of 105 cases reported in 2020, 103 acquired the infection before a national lockdown was instituted on 9 March 2020. Overall, one quarter of cases reported at least one complication. As non-pharmaceutical pandemic measures are being eased worldwide, and considering measles seasonality, infectiousness, and its potential severity, it is important that countries ensure high vaccination coverage and close immunity gaps, to avoid risk of future outbreaks.

Detecting early signals of COVID-19 outbreaks in 2020 in small areas by monitoring healthcare utilisation databases: first lessons learned from the Italian Alert_CoV project.

BackgroundDuring the COVID-19 pandemic, large-scale diagnostic testing and contact tracing have proven insufficient to promptly monitor the spread of infections.AimTo develop and retrospectively evaluate a system identifying aberrations in the use of selected healthcare services to timely detect COVID-19 outbreaks in small areas.MethodsData were retrieved from the healthcare utilisation (HCU) databases of the Lombardy Region, Italy. We identified eight services suggesting a respiratory infection (syndromic proxies). Count time series reporting the weekly occurrence of each proxy from 2015 to 2020 were generated considering small administrative areas (i.e. census units of Cremona and Mantua provinces). The ability to uncover aberrations during 2020 was tested for two algorithms: the improved Farrington algorithm and the generalised likelihood ratio-based procedure for negative binomial counts. To evaluate these algorithms' performance in detecting outbreaks earlier than the standard surveillance, confirmed outbreaks, defined according to the weekly number of confirmed COVID-19 cases, were used as reference. Performances were assessed separately for the first and second semester of the year. Proxies positively impacting performance were identified.ResultsWe estimated that 70% of outbreaks could be detected early using the proposed approach, with a corresponding false positive rate of ca 20%. Performance did not substantially differ either between algorithms or semesters. The best proxies included emergency calls for respiratory or infectious disease causes and emergency room visits.ConclusionImplementing HCU-based monitoring systems in small areas deserves further investigations as it could facilitate the containment of COVID-19 and other unknown infectious diseases in the future.

Tracking the progressive spread of the SARS-CoV-2 Omicron variant in Italy, December 2021 to January 2022.

BackgroundThe SARS-CoV-2 variant of concern Omicron was first detected in Italy in November 2021.AimTo comprehensively describe Omicron spread in Italy in the 2 subsequent months and its impact on the overall SARS-CoV-2 circulation at population level.MethodsWe analyse data from four genomic surveys conducted across the country between December 2021 and January 2022. Combining genomic sequencing results with epidemiological records collated by the National Integrated Surveillance System, the Omicron reproductive number and exponential growth rate are estimated, as well as SARS-CoV-2 transmissibility.ResultsOmicron became dominant in Italy less than 1 month after its first detection, representing on 3 January 76.9-80.2% of notified SARS-CoV-2 infections, with a doubling time of 2.7-3.3 days. As of 17 January 2022, Delta variant represented < 6% of cases. During the Omicron expansion in December 2021, the estimated mean net reproduction numbers respectively rose from 1.15 to a maximum of 1.83 for symptomatic cases and from 1.14 to 1.36 for hospitalised cases, while remaining relatively stable, between 0.93 and 1.21, for cases needing intensive care. Despite a reduction in relative proportion, Delta infections increased in absolute terms throughout December contributing to an increase in hospitalisations. A significant reproduction numbers' decline was found after mid-January, with average estimates dropping below 1 between 10 and 16 January 2022.ConclusionEstimates suggest a marked growth advantage of Omicron compared with Delta variant, but lower disease severity at population level possibly due to residual immunity against severe outcomes acquired from vaccination and prior infection.

Winning during a pandemic: epidemiology of SARS-CoV-2 during EURO2020 in Italy.

INTRODUCTION: EURO2020 generated a growing media and population interest across the month period, that peaked with large spontaneous celebrations across the country upon winning the tournament. METHODS: We retrospectively analysed data from the national surveillance system (indicator-based) and from event-based surveillance to assess how the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) changed in June-July 2021 and to describe cases and clusters linked with EURO2020. RESULTS: Widespread increases in transmission and case numbers, mainly among younger males, were documented in Italy, none were linked with stadium attendance. Vaccination coverage against SARS-CoV-2 was longer among cases linked to EURO2020 than among the general population. CONCLUSIONS: Transmission increased across the country, mainly due to gatherings outside the stadium, where, conversely, strict infection control measures were enforced. These informal 'side' gatherings were dispersed across the entire country and difficult to control. Targeted communication and control strategies to limit the impact of informal gatherings occurring outside official sites of mass gathering events should be further developed.

An epidemic model for SARS-CoV-2 with self-adaptive containment measures.

During the COVID-19 pandemic, several countries have resorted to self-adaptive mechanisms that tailor non-pharmaceutical interventions to local epidemiological and health care indicators. These mechanisms reinforce the mutual influence between containment measures and the evolution of the epidemic. To account for such interplay, we develop an epidemiological model that embeds an algorithm mimicking the self-adaptive policy mechanism effective in Italy between November 2020 and March 2022. This extension is key to tracking the historical evolution of health outcomes and restrictions in Italy. Focusing on the epidemic wave that started in mid-2021 after the diffusion of Delta, we compare the functioning of alternative mechanisms to show how the policy framework may affect the trade-off between health outcomes and the restrictiveness of mitigation measures. Mechanisms based on the reproduction number are generally highly responsive to early signs of a surging wave but entail severe restrictions. The emerging trade-off varies considerably depending on specific conditions (e.g., vaccination coverage), with less-reactive mechanisms (e.g., those based on occupancy rates) becoming more appealing in favorable contexts.

Effectiveness of BNT162b2 vaccine against SARS-CoV-2 infection and severe COVID-19 in children aged 5-11 years in Italy: a retrospective analysis of January-April, 2022.

BACKGROUND: By April 13, 2022, more than 4 months after the approval of BNT162b2 (Pfizer-BioNTech) for children, less than 40% of 5-11-year-olds in Italy had been vaccinated against COVID-19. Estimating how effective vaccination is in 5-11-year-olds in the current epidemiological context dominated by the omicron variant (B.1.1.529) is important to inform public health bodies in defining vaccination policies and strategies. METHODS: In this retrospective population analysis, we assessed vaccine effectiveness against SARS-CoV-2 infection and severe COVID-19, defined as an infection leading to hospitalisation or death, by linking the national COVID-19 surveillance system and the national vaccination registry. All Italian children aged 5-11 years without a previous diagnosis of infection were eligible for inclusion and were followed up from Jan 17 to April 13, 2022. All children with inconsistent vaccination data, diagnosed with SARS-CoV-2 infection before the start date of the study or without information on the municipality of residence were excluded from the analysis. With unvaccinated children as the reference group, we estimated vaccine effectiveness in those who were partly vaccinated (one dose) and those who were fully vaccinated (two doses). FINDINGS: By April 13, 2022, 1 063 035 (35·8%) of the 2 965 918 children aged 5-11 years included in the study had received two doses of the vaccine, 134 386 (4·5%) children had received one dose only, and 1 768 497 (59·6%) were unvaccinated. During the study period, 766 756 cases of SARS-CoV-2 infection and 644 cases of severe COVID-19 (627 hospitalisations, 15 admissions to intensive care units, and two deaths) were notified. Overall, vaccine effectiveness in the fully vaccinated group was 29·4% (95% CI 28·5-30·2) against SARS-CoV-2 infection and 41·1% (22·2-55·4) against severe COVID-19, whereas vaccine effectiveness in the partly vaccinated group was 27·4% (26·4-28·4) against SARS-CoV-2 infection and 38·1% (20·9-51·5) against severe COVID-19. Vaccine effectiveness against infection peaked at 38·7% (37·7-39·7) at 0-14 days after full vaccination and decreased to 21·2% (19·7-22·7) at 43-84 days after full vaccination. INTERPRETATION: Vaccination against COVID-19 in children aged 5-11 years in Italy showed a lower effectiveness in preventing SARS-CoV-2 infection and severe COVID-19 than in individuals aged 12 years and older. Effectiveness against infection appears to decrease after completion of the current primary vaccination cycle. FUNDING: None. TRANSLATION: For the Italian translation of the summary see Supplementary Materials section.

Intrinsic generation time of the SARS-CoV-2 Omicron variant: An observational study of household transmission.

Background: Starting from the final months of 2021, the SARS-CoV-2 Omicron variant expanded globally, swiftly replacing Delta, the variant that was dominant at the time. Many uncertainties remain about the epidemiology of Omicron; here, we aim to estimate its generation time. Methods: We used a Bayesian approach to analyze 23,122 SARS-CoV-2 infected individuals clustered in 8903 households as determined from contact tracing operations in Reggio Emilia, Italy, throughout January 2022. We estimated the distribution of the intrinsic generation time (the time between the infection dates of an infector and its secondary cases in a fully susceptible population), realized household generation time, realized serial interval (time between symptom onset of an infector and its secondary cases), and contribution of pre-symptomatic transmission. Findings: We estimated a mean intrinsic generation time of 6.84 days (95% credible intervals, CrI, 5.72-8.60), and a mean realized household generation time of 3.59 days (95%CrI: 3.55-3.60). The household serial interval was 2.38 days (95%CrI 2.30-2.47) with about 51% (95%CrI 45-56%) of infections caused by symptomatic individuals being generated before symptom onset. Interpretation: These results indicate that the intrinsic generation time of the SARS-CoV-2 Omicron variant might not have shortened as compared to previous estimates on ancestral lineages, Alpha and Delta, in the same geographic setting. Like for previous lineages, pre-symptomatic transmission appears to play a key role for Omicron transmission. Estimates in this study may be useful to design quarantine, isolation and contact tracing protocols and to support surveillance (e.g., for the accurate computation of reproduction numbers). Funding: The study was partially funded by EU grant 874850 MOOD.

Risk and protective factors for SARS-CoV-2 reinfections, surveillance data, Italy, August 2021 to March 2022.

We explored the risk factors associated with SARS-CoV-2 reinfections in Italy between August 2021 and March 2022. Regardless of the prevalent virus variant, being unvaccinated was the most relevant risk factor for reinfection. The risk of reinfection increased almost 18-fold following emergence of the Omicron variant compared with Delta. A severe first SARS-CoV-2 infection and age over 60 years were significant risk factors for severe reinfection.

Effectiveness of an mRNA vaccine booster dose against SARS-CoV-2 infection and severe COVID-19 in persons aged ≥60 years and other high-risk groups during predominant circulation of the delta variant in Italy, 19 July to 12 December 2021.

BACKGROUND: Consolidated information on the effectiveness of COVID-19 booster vaccination in Europe are scarce. RESEARCH DESIGN AND METHODS: We assessed the effectiveness of a booster dose of an mRNA vaccine against any SARS-CoV-2 infection (symptomatic or asymptomatic) and severe COVID-19 (hospitalization or death) after over two months from administration among priority target groups (n = 18,524,568) during predominant circulation of the Delta variant in Italy (July-December 2021). RESULTS: Vaccine effectiveness (VE) against SARS-CoV-2 infection and, to a lesser extent, against severe COVID-19, among people ≥60 years and other high-risk groups (i.e. healthcare workers, residents in long-term-care facilities, and persons with comorbidities or immunocompromised), peaked in the time-interval 3-13 weeks (VE against infection = 67.2%, 95% confidence interval (CI): 62.5-71.3; VE against severe disease = 89.5%, 95% CI: 86.1-92.0) and then declined, waning 26 weeks after full primary vaccination (VE against infection = 12.2%, 95% CI: -4.7-26.4; VE against severe disease = 65.3%, 95% CI: 50.3-75.8). After 3-10 weeks from the administration of a booster dose, VE against infection and severe disease increased to 76.1% (95% CI: 70.4-80.7) and 93.0% (95% CI: 90.2-95.0), respectively. CONCLUSIONS: These results support the ongoing vaccination campaign in Italy, where the administration of a booster dose four months after completion of primary vaccination is recommended.

A population-based cohort approach to assess excess mortality due to the spread of COVID-19 in Italy, January-May 2020.

AIMS: To assess the impact of the COVID-19 pandemic on all-cause mortality in Italy during the first wave of the epidemic, taking into consideration the geographical heterogeneity of the spread of COVID-19. METHODS: This study is a retrospective, population-based cohort study using national statistics throughout Italy. Survival analysis was applied to data aggregated by day of death, age groups, sex, and Italian administrative units (107 provinces). We applied Cox models to estimate the relative hazards (RH) of excess mortality, comparing all-cause deaths in 2020 with the expected deaths from all causes in the same time period. The RH of excess deaths was estimated in areas with a high, moderate, and low spread of COVID-19. We reported the estimate also restricting the analysis to the period of March-April 2020 (first peak of the epidemic). RESULTS: The study population consisted of 57,204,501 individuals living in Italy as of January 1, 2020. The number of excess deaths was 36,445, which accounts for 13.4% of excess mortalities from all causes during January-May 2020 (i.e., RH = 1.134; 95% confidence interval (CI): 1.129-1.140). In the macro-area with a relatively higher spread of COVID-19 (i.e., incidence rate, IR): 450-1,610 cases per 100,000 residents), the RH of excess deaths was 1.375 (95% CI: 1.364-1.386). In the area with a relatively moderate spread of COVID-19 (i.e., IR: 150-449 cases) it was 1.049 (95% CI: 1.038-1.060). In the area with a relatively lower spread of COVID-19 (i.e., IR: 30-149 cases), it was 0.967 (95% CI: 0.959-0.976). Between March and April (peak months of the first wave of the epidemic in Italy), we estimated an excess mortality from all causes of 43.5%. The RH of all-cause mortality for increments of 500 cases per 100,000 residents was 1.352 (95% CI: 1.346-1.359), corresponding to an increase of about 35%. CONCLUSIONS: Our analysis, making use of a population-based cohort model, estimated all-cause excess mortality in Italy taking account of both time period and of COVID-19 geographical spread. The study highlights the importance of a temporal/geographic framework in analyzing the risk of COVID-19-epidemy related mortality.

Effectiveness of mRNA vaccines and waning of protection against SARS-CoV-2 infection and severe covid-19 during predominant circulation of the delta variant in Italy: retrospective cohort study.

OBJECTIVES: To estimate the effectiveness of mRNA vaccines against SARS-CoV-2 infection and severe covid-19 at different time after vaccination. DESIGN: Retrospective cohort study. SETTING: Italy, 27 December 2020 to 7 November 2021. PARTICIPANTS: 33 250 344 people aged ≥16 years who received a first dose of BNT162b2 (Pfizer-BioNTech) or mRNA-1273 (Moderna) vaccine and did not have a previous diagnosis of SARS-CoV-2 infection. MAIN OUTCOME MEASURES: SARS-CoV-2 infection and severe covid-19 (admission to hospital or death). Data were divided by weekly time intervals after vaccination. Incidence rate ratios at different time intervals were estimated by multilevel negative binomial models with robust variance estimator. Sex, age group, brand of vaccine, priority risk category, and regional weekly incidence in the general population were included as covariates. Geographic region was included as a random effect. Adjusted vaccine effectiveness was calculated as (1-IRR)×100, where IRR=incidence rate ratio, with the time interval 0-14 days after the first dose of vaccine as the reference. RESULTS: During the epidemic phase when the delta variant was the predominant strain of the SARS-CoV-2 virus, vaccine effectiveness against SARS-CoV-2 infection significantly decreased (P<0.001) from 82% (95% confidence interval 80% to 84%) at 3-4 weeks after the second dose of vaccine to 33% (27% to 39%) at 27-30 weeks after the second dose. In the same time intervals, vaccine effectiveness against severe covid-19 also decreased (P<0.001), although to a lesser extent, from 96% (95% to 97%) to 80% (76% to 83%). High risk people (vaccine effectiveness -6%, -28% to 12%), those aged ≥80 years (11%, -15% to 31%), and those aged 60-79 years (2%, -11% to 14%) did not seem to be protected against infection at 27-30 weeks after the second dose of vaccine. CONCLUSIONS: The results support the vaccination campaigns targeting high risk people, those aged ≥60 years, and healthcare workers to receive a booster dose of vaccine six months after the primary vaccination cycle. The results also suggest that timing the booster dose earlier than six months after the primary vaccination cycle and extending the offer of the booster dose to the wider eligible population might be warranted.

COVID-19 response: effectiveness of weekly rapid risk assessments, Italy

Problem After Italy's first national restriction measures in 2020, a robust approach was needed to monitor the emerging epidemic of coronavirus disease 2019 (COVID-19) at subnational level and provide data to inform the strengthening or easing of epidemic control measures. Approach We adapted the European Centre for Disease Prevention and Control rapid risk assessment tool by including quantitative and qualitative indicators from existing national surveillance systems. We defined COVID-19 risk as a combination of the probability of uncontrolled transmission of severe acute respiratory syndrome coronavirus 2 and of an unsustainable impact of COVID-19 cases on hospital services, adjusted in relation to the health system's resilience. The monitoring system was implemented with no additional cost in May 2020. Local setting The infectious diseases surveillance system in Italy uses consistent data collection methods across the country's decentralized regions and autonomous provinces. Relevant changes Weekly risk assessments using this approach were sustainable in monitoring the epidemic at regional level from 4 May 2020 to 24 September 2021. The tool provided reliable assessments of when and where a rapid increase in demand for health-care services would occur if control or mitigation measures were not increased in the following 3 weeks. Lessons learnt Although the system worked well, framing the risk assessment tool in a legal decree hampered its flexibility, as indicators could not be changed without changing the law. The relative complexity of the tool, the impossibility of real-time validation and its use for the definition of restrictions posed communication challenges. Situación Tras las primeras medidas nacionales de restricción en Italia en 2020, se necesitaba un enfoque sólido para supervisar la epidemia emergente de la coronavirosis de 2019 (COVID-19) a nivel subnacional y proporcionar datos que informaran sobre el refuerzo o la flexibilización de las medidas de contención de la epidemia. Enfoque Se adaptó la herramienta de valoración rápida de riesgos del Centro Europeo para la Prevención y el Control de las Enfermedades, al incluir indicadores cuantitativos y cualitativos de los sistemas nacionales de vigilancia existentes. Se definió el riesgo de la COVID-19 como una combinación de la probabilidad de transmisión descontrolada del coronavirus del síndrome respiratorio agudo grave de tipo 2 y de un efecto no sostenible de los casos de la COVID-19 en los servicios hospitalarios, y se ajustó en relación con la capacidad de recuperación del sistema sanitario. El sistema de supervisión se aplicó sin costes adicionales en mayo de 2020. Marco regional El sistema de vigilancia de las enfermedades infecciosas en Italia aplica métodos de recopilación de datos coherentes en todas las regiones y provincias autónomas descentralizadas del país. Cambios importantes Las valoraciones semanales de los riesgos mediante este enfoque fueron sostenibles en la supervisión de la epidemia a nivel regional entre el 4 de mayo de 2020 y el 24 de septiembre de 2021. La herramienta proporcionó valoraciones fiables de cuándo y dónde se produciría un rápido aumento de la demanda de servicios sanitarios si no se incrementaban las medidas de contención o mitigación en las tres semanas siguientes. Lecciones aprendidas Aunque el sistema funcionó bien, el hecho de enmarcar la herramienta de valoración de los riesgos en un decreto legal dificultó su flexibilidad, ya que los indicadores no se podían modificar sin cambiar la ley. La relativa complejidad de la herramienta, la imposibilidad de validación en tiempo real y su uso para la definición de las restricciones plantearon problemas de comunicación. Problème Après avoir pris ses premières mesures de restriction nationales en 2020, l'Italie avait besoin d'une approche solide pour surveiller l'épidémie naissante de maladie à coronavirus 2019 (COVID-19) au niveau régional, et fournir les données permettant de renforcer ou d'alléger les mesures destinées à l'endiguer. Approche Nous avons adapté l'outil d'évaluation rapide des risques du Centre européen de prévention et de contrôle des maladies en y intégrant des indicateurs quantitatifs et qualitatifs issus des systèmes de surveillance nationaux existants. Pour définir le risque lié à la COVID-19, nous avons associé la probabilité d'une transmission incontrôlée du coronavirus 2 du syndrome respiratoire aigu sévère, à l'impact immédiat des cas de COVID-19 sur les services hospitaliers, en procédant à des ajustements selon la résilience du système de soins de santé. Le dispositif de surveillance a été mis en oeuvre en mai 2020 sans entraîner de coûts supplémentaires. Environnement local En Italie, le système de surveillance des maladies infectieuses repose sur des méthodes uniformes de collecte de données dans les provinces autonomes et régions décentralisées à travers le pays. Changements significatifs Les évaluations des risques réalisées toutes les semaines avec cette approche ont permis de surveiller l'épidémie à l'échelle régionale du 4 mai 2020 au 24 septembre 2021. L'outil a identifié les dates et lieux susceptibles de connaître une augmentation rapide de la demande en services de soins de santé si aucune mesure supplémentaire de contrôle et de lutte n'était prise dans les trois semaines. Leçons tirées Bien que le système ait fonctionné, inscrire l'outil d'évaluation des risques dans un décret législatif a réduit sa flexibilité, car les indicateurs ne pouvaient être modifiés sans réformer la loi. La relative complexité de l'outil, l'impossibilité de procéder à une validation en temps réel et son usage pour imposer des restrictions ont posé des problèmes de communication. Проблема После первых национальных ограничительных мер в Италии в 2020 году потребовался активный подход для мониторинга зарождающейся эпидемии коронавирусной инфекции 2019 года (COVID-19) на субнациональном уровне и для предоставления данных для обоснования усиления или ослабления мер по борьбе с эпидемией. Подход Авторы адаптировали инструмент для оперативных оценок рисков Европейского центра по контролю и профилактике заболеваний, включив в него количественные и качественные показатели из существующих национальных систем эпиднадзора. Авторы определили риск COVID-19 как комбинацию вероятности неконтролируемой передачи тяжелого острого респираторного синдрома, вызванного коронавирусом-2, и разрушительного воздействия случаев COVID-19 на больничное обслуживание, которая скорректирована с учетом устойчивости системы здравоохранения. Система мониторинга была внедрена без каких-либо дополнительных затрат в мае 2020 года. Местные условия В системе эпиднадзора за инфекционными заболеваниями в Италии используются последовательные методы сбора данных по децентрализованным регионам и автономным провинциям страны. Осуществленные перемены Еженедельные оценки рисков с использованием данного подхода регулярно применялись при мониторинге эпидемии на региональном уровне с 4 мая 2020 года по 24 сентября 2021 года. Инструмент обеспечил надежную оценку того, когда и где может произойти быстрое увеличение спроса на медицинские услуги, если меры по борьбе или смягчению последствий не будут усилены в течение следующих 3 недель. Выводы Несмотря на то что система работала эффективно, включение инструмента для оценок рисков в юридические постановления ограничивало его гибкость, поскольку показатели не могли быть изменены без изменения закона. Относительная сложность инструмента, невозможность проверки в реальном времени и его использование для определения ограничений создают проблемы коммуникации. 问题 2020 年意大利首次实施全国性限制措施后，需要 采取可靠方法以监测新型冠状病毒肺炎 (新冠肺炎) 疫情在地方层面的蔓延情况，并提供数据以表明是否 需要加强或放松疫情控制措施。 方法 通过纳入现有国家监测系统的定量和定性指 标，我们调整了欧洲疾病预防和控制中心的快速风险 评估工具。我们将新型冠状病毒肺炎风险综合定义为 严重急性呼吸系统综合症冠状病毒 2 不受控制传播 的可能性以及新型冠状病毒肺炎病例对医院服务的非持续性影响，并根据卫生系统的顺应力进行了调整。 2020 年 5 月，在没有产生额外成本的前提下实施了监 测系统。 当地状况 意大利传染病监测系统在全国各个分散 的地区和自治省统一使用相同的数据收集方法。 相关变化 在 2020 年 5 月 4 日至 2021 年 9 月 24 日 期间，使用这种方法开展的每周风险评估在监测区域 层面疫情情况方面具有可持续性。该工具能够可靠地 评估，如果在接下来的 3 周内没有加强控制或缓解措 施，何时何地医疗保健服务需求会迅速增加。 经验教训 尽管该系统运作良好，但将风险评估工 具纳入法令范畴限制了其灵活性，因为若不更改法律， 则无法变更指标。该工具的相对复杂性、实时验证的 不可能性及其在法规限定方面的用途导致产生了沟通 挑战。