SARS-CoV-2 Breakthrough Infections According to the Immune Response Elicited after mRNA Third Dose Vaccination in COVID-19-Naïve Hospital Personnel.

BACKGROUND: Vaccine-induced SARS-CoV-2-anti-spike antibody (anti-S/RBD) titers are often used as a marker of immune protection and to anticipate the risk of breakthrough infections, although no clear cut-off is available. We describe the incidence of SARS-CoV-2 vaccine breakthrough infections in COVID-19-free personnel of our hospital, according to B- and T-cell immune response elicited one month after mRNA third dose vaccination. METHODS: The study included 487 individuals for whom data on anti-S/RBD were available. Neutralizing antibody titers (nAbsT) against the ancestral Whuan SARS-CoV-2, and the BA.1 Omicron variant, and SARS-CoV-2 T-cell specific response were measured in subsets of 197 (40.5%), 159 (32.6%), and 127 (26.1%) individuals, respectively. RESULTS: On a total of 92,063 days of observation, 204 participants (42%) had SARS-CoV-2 infection. No significant differences in the probability of SARS-CoV-2 infection for different levels of anti-S/RBD, nAbsT, Omicron nAbsT, or SARS-CoV-2 T cell specific response, and no protective thresholds for infection were found. CONCLUSIONS: Routine testing for vaccine-induced humoral immune response to SARS-CoV-2 is not recommended if measured as parameters of 'protective immunity' from SARS-CoV-2 after vaccination. Whether these findings apply to new Omicron-specific bivalent vaccines is going to be evaluated.

High temperature, COVID-19, and mortality excess in the 2022 summer: a cohort study on data from Italian surveillances.

We aimed to assess whether the effect of high temperature on mortality differed in COVID-19 survivors and naive. We used data from the summer mortality and COVID-19 surveillances. We found 3.8 % excess risk in 2022 summer, compared to 2015-2019, while 20 % in the last fortnight of July, the period with the highest temperature. The increase in mortality rates during the second fortnight of July was higher among naïve compared to COVID-19 survivors. The time series analysis confirmed the association between temperatures and mortality in naïve people, showing an 8 % excess (95%CI 2 to 13) for a one-degree increase of Thom Discomfort Index while in COVID-19 survivors the effect was almost null with -1 % (95%CI -9 to 9). Our results suggest that the high fatality rate of COVID-19 in fragile people has decreased the proportion of susceptible people who can be affected by the extremely high temperature.

[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.

Geographic heterogeneity of the epidemiological impact of the COVID-19 pandemic in Italy using a socioeconomic proxy-based classification of the national territory.

Objectives: This study aimed to evaluate the differences in incidence, non-intensive care unit (non-ICU) and intensive care unit (ICU) hospital admissions, and COVID-19-related mortality between the "inner areas" of Italy and its metropolitan areas. Study design: Retrospective population-based study conducted from the beginning of the pandemic in Italy (20 February 2020) to 31 March 2022. Methods: The municipalities of Italy were classified into metropolitan areas, peri-urban/intermediate areas and "inner areas" (peripheral/ultra-peripheral). The exposure variable was residence in an "inner area" of Italy. Incidence of diagnosis of SARS-CoV-2 infection, non-ICU and ICU hospital admissions and death within 30 days from diagnosis were the outcomes of the study. COVID-19 vaccination access was also evaluated. Crude and age-standardized rates were calculated for all the study outcomes. The association between the type of area of residence and each outcome under study was evaluated by calculating the ratios between the standardized rates. All the analyses were stratified by period of observation (original Wuhan strain, Alpha variant, Delta variant, Omicron variant). Results: Incidence and non-ICUs admissions rates were lower in "inner areas." ICU admission and mortality rates were much lower in "inner areas" in the early phases of the pandemic, but this protection progressively diminished, with a slight excess risk observed in the "inner areas" during the Omicron period. The greater vaccination coverage in metropolitan areas may explain this trend. Conclusion: Prioritizing healthcare planning through the strengthening of the primary prevention policies in the peripheral areas of Italy is fundamental to guarantee health equity policies.

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.

The influence of meteorological factors on COVID-19 spread in Italy during the first and second wave.

The relation between meteorological factors and COVID-19 spread remains uncertain, particularly with regard to the role of temperature, relative humidity and solar ultraviolet (UV) radiation. To assess this relation, we investigated disease spread within Italy during 2020. The pandemic had a large and early impact in Italy, and during 2020 the effects of vaccination and viral variants had not yet complicated the dynamics. We used non-linear, spline-based Poisson regression of modeled temperature, UV and relative humidity, adjusting for mobility patterns and additional confounders, to estimate daily rates of COVID-19 new cases, hospital and intensive care unit admissions, and deaths during the two waves of the pandemic in Italy during 2020. We found little association between relative humidity and COVID-19 endpoints in both waves, whereas UV radiation above 40 kJ/m2 showed a weak inverse association with hospital and ICU admissions in the first wave, and a stronger relation with all COVID-19 endpoints in the second wave. Temperature above 283 K (10 °C/50 °F) showed a strong non-linear negative relation with COVID-19 endpoints, with inconsistent relations below this cutpoint in the two waves. Given the biological plausibility of a relation between temperature and COVID-19, these data add support to the proposition that temperature above 283 K, and possibly high levels of solar UV radiation, reduced COVID-19 spread.

Risk of SARS-CoV-2 reinfection by vaccination status, predominant variant and time from prior infection: a cohort study, Reggio Emilia province, Italy, February 2020 to February 2022.

BackgroundUnderstanding the epidemiology of reinfections is crucial for SARS-CoV-2 control over a long period.AimTo evaluate the risk of SARS-CoV-2 reinfection by vaccination status, predominant variant and time after first infection.MethodsWe conducted a cohort study including all residents in the Reggio Emilia province on 31 December 2019, followed up until 28 February 2022 for SARS-CoV-2 first infection and reinfection after 90 days. Cox models were used to compare risk of first infection vs reinfection, adjusting for age, sex, vaccine doses and comorbidities.ResultsThe cohort included 538,516 residents, 121,154 with first SARS-CoV-2 infections and 3,739 reinfections, most in the Omicron BA.1 period. In the pre-Omicron period, three doses of vaccine reduced risk of reinfection by 89% (95% CI: 87-90), prior infection reduced risk by 90% (95% CI: 88-91), while two doses and infection reduced risk by 98% (95% CI: 96-99). In the Omicron BA.1 period, protection estimates were 53% (95% CI: 52-55), 9% (95% CI: 4-14) and 76% (95% CI: 74-77). Before Omicron, protection from reinfection remained above 80% for up to 15 months; with Omicron BA.1, protection decreased from 71% (95% CI: 65-76) at 5 months to 21% (95% CI: 10-30) at 22 months from the first infection. Omicron BA.1 reinfections showed 48% (95% CI: 10-57) lower risk of severe disease than first infections.ConclusionsNatural immunity acquired with previous variants showed low protection against Omicron BA.1. Combined vaccination and natural immunity seems to be more protective against reinfection than either alone. Vaccination of people with prior infection reduced the risk of severe disease.

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.

[Integrated Surveillance in Italy: outputs and related activities]. / La sorveglianza integrata COVID-19 in Italia: output e attività correlate.

OBJECTIVES: to describe the integrated surveillance system of COVID-19 in Italy, to illustrate the outputs used to return epidemiological information on the spread of the epidemic to the competent public health bodies and to the Italian population, and to describe how the surveillance data contributes to the ongoing weekly regional monitoring and risk assessment system. METHODS: the COVID-19 integrated surveillance system is the result of a close and continuous collaboration between the Italian National Institute of Health (ISS), the Italian Ministry of Health, and the regional and local health authorities. Through a web platform, it collects individual data of laboratory confirmed cases of SARS-CoV-2 infection and gathers information on their residence, laboratory diagnosis, hospitalisation, clinical status, risk factors, and outcome. Results, for different levels of aggregation and risk categories, are published daily and weekly on the ISS website, and made available to national and regional public health authorities; these results contribute one of the information sources of the regional monitoring and risk assessment system. RESULTS: the COVID-19 integrated surveillance system monitors the space-time distribution of cases and their characteristics. Indicators used in the weekly regional monitoring and risk assessment system include process indicators on completeness and results indicators on weekly trends of newly diagnosed cases per Region. CONCLUSIONS: the outputs of the integrated surveillance system for COVID-19 provide timely information to health authorities and to the general population on the evolution of the epidemic in Italy. They also contribute to the continuous re-assessment of risk related to transmission and impact of the epidemic thus contributing to the management of COVID-19 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.

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.

Surveillance, contact tracing and characteristics of SARS-CoV-2 transmission in educational settings in Northern Italy, September 2020 to April 2021.

BACKGROUND: The role of school contacts in the spread of the virus and the effectiveness of school closures in controlling the epidemic is still debated. We aimed to quantify the risk of transmission of SARS-CoV-2 in the school setting by type of school, characteristics of the index case and calendar period in the Province of Reggio Emilia (RE), Italy. The secondary aim was to estimate the speed of implementation of contact tracing. METHODS: A population-based analysis of surveillance data on all COVID-19 cases occurring in RE, Italy, from 1 September 2020, to 4 April 2021, for which a school contact and/or exposure was suspected. An indicator of the delay in contact tracing was calculated as the time elapsed since the index case was determined to be positive and the date on which the swab test for classmates was scheduled (or most were scheduled). RESULTS: Overall, 30,184 and 13,608 contacts among classmates and teachers/staff, respectively, were identified and were recommended for testing, and 43,214 (98.7%) underwent the test. Secondary transmission occurred in about 40% of the investigated classes, and the overall secondary case attack rate was 4%. This rate was slightly higher when the index case was a teacher but with almost no differences by type of school, and was stable during the study period. Speed of implementation of contact tracing increased during the study period, with the time from index case identification to testing of contacts being reduced from seven to three days. The ability to identify the possible source of infection in the index case also increased. CONCLUSIONS: Despite the spread of the Alpha variant during the study period in RE, the secondary case attack rate remained stable from school reopening in September 2020 until the beginning of April 2021.

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.

Substantial impact of mobility restrictions on reducing COVID-19 incidence in Italy in 2020.

BACKGROUND: Italy was the first country after China to be severely affected by the COVID-19 pandemic, in early 2020. The country responded swiftly to the outbreak with a nationwide two-step lockdown, the first one light and the second one tight. By analyzing 2020 national mobile phone movements, we assessed how lockdown compliance influenced its efficacy. METHODS: We measured individual mobility during the first epidemic wave with mobile phone movements tracked through carrier networks, and related this mobility to daily new SARS-CoV-2 infections, hospital admissions, intensive care admissions and deaths attributed to COVID-19, taking into account reason for travel (work-related or not) and the means of transport. RESULTS: The tight lockdown resulted in an 82% reduction in mobility for the entire country and was effective in swiftly curbing the outbreak as indicated by a shorter time-to-peak of all health outcomes, particularly for provinces with the highest mobility reductions and the most intense COVID-19 spread. Reduction of work-related mobility was accompanied by a nearly linear benefit in outbreak containment; work-unrelated movements had a similar effect only for restrictions exceeding 50%. Reduction in mobility by car and by airplane was nearly linearly associated with a decrease in most COVID-19 health outcomes, while for train travel reductions exceeding 55% had no additional beneficial effects. The absence of viral variants and vaccine availability during the study period eliminated confounding from these two sources. CONCLUSIONS: Adherence to the COVID-19 tight lockdown during the first wave in Italy was high and effective in curtailing the outbreak. Any work-related mobility reduction was effective, but only high reductions in work-unrelated mobility restrictions were effective. For train travel, there was a threshold above which no further benefit occurred. These findings could be particular to the spread of SARS-CoV-2, but might also apply to other communicable infections with comparable transmission dynamics.

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.