Evaluation of Waning of SARS-CoV-2 Vaccine-Induced Immunity: A Systematic Review and Meta-analysis.

Importance: Estimates of the rate of waning of vaccine effectiveness (VE) against COVID-19 are key to assess population levels of protection and future needs for booster doses to face the resurgence of epidemic waves. Objective: To quantify the progressive waning of VE associated with the Delta and Omicron variants of SARS-CoV-2 by number of received doses. Data Sources: PubMed and Web of Science were searched from the databases' inception to October 19, 2022, as well as reference lists of eligible articles. Preprints were included. Study Selection: Selected studies for this systematic review and meta-analysis were original articles reporting estimates of VE over time against laboratory-confirmed SARS-CoV-2 infection and symptomatic disease. Data Extraction and Synthesis: Estimates of VE at different time points from vaccination were retrieved from original studies. A secondary data analysis was performed to project VE at any time from last dose administration, improving the comparability across different studies and between the 2 considered variants. Pooled estimates were obtained from random-effects meta-analysis. Main Outcomes and Measures: Outcomes were VE against laboratory-confirmed Omicron or Delta infection and symptomatic disease and half-life and waning rate associated with vaccine-induced protection. Results: A total of 799 original articles and 149 reviews published in peer-reviewed journals and 35 preprints were identified. Of these, 40 studies were included in the analysis. Pooled estimates of VE of a primary vaccination cycle against laboratory-confirmed Omicron infection and symptomatic disease were both lower than 20% at 6 months from last dose administration. Booster doses restored VE to levels comparable to those acquired soon after the administration of the primary cycle. However, 9 months after booster administration, VE against Omicron was lower than 30% against laboratory-confirmed infection and symptomatic disease. The half-life of VE against symptomatic infection was estimated to be 87 days (95% CI, 67-129 days) for Omicron compared with 316 days (95% CI, 240-470 days) for Delta. Similar waning rates of VE were found for different age segments of the population. Conclusions and Relevance: These findings suggest that the effectiveness of COVID-19 vaccines against laboratory-confirmed Omicron or Delta infection and symptomatic disease rapidly wanes over time after the primary vaccination cycle and booster dose. These results can inform the design of appropriate targets and timing for future vaccination programs.

Priority age targets for COVID-19 vaccination in Ethiopia under limited vaccine supply.

The worldwide inequitable access to vaccination claims for a re-assessment of policies that could minimize the COVID-19 burden in low-income countries. Nine months after the launch of the national vaccination program in March 2021, only 3.4% of the Ethiopian population received two doses of COVID-19 vaccine. We used a SARS-CoV-2 transmission model to estimate the level of immunity accrued before the launch of vaccination in the Southwest Shewa Zone (SWSZ) and to evaluate the impact of alternative age priority vaccination targets in a context of limited vaccine supply. The model was informed with available epidemiological evidence and detailed contact data collected across different geographical settings (urban, rural, or remote). We found that, during the first year of the pandemic, the mean proportion of critical cases occurred in SWSZ attributable to infectors under 30 years of age would range between 24.9 and 48.0%, depending on the geographical setting. During the Delta wave, the contribution of this age group in causing critical cases was estimated to increase on average to 66.7-70.6%. Our findings suggest that, when considering the vaccine product available at the time (ChAdOx1 nCoV-19; 65% efficacy against infection after 2 doses), prioritizing the elderly for vaccination remained the best strategy to minimize the disease burden caused by Delta, irrespectively of the number of available doses. Vaccination of all individuals aged ≥ 50 years would have averted 40 (95%PI: 18-60), 90 (95%PI: 61-111), and 62 (95%PI: 21-108) critical cases per 100,000 residents in urban, rural, and remote areas, respectively. Vaccination of all individuals aged ≥ 30 years would have averted an average of 86-152 critical cases per 100,000 individuals, depending on the setting considered. Despite infections among children and young adults likely caused 70% of critical cases during the Delta wave in SWSZ, most vulnerable ages should remain a key priority target for vaccination against COVID-19.

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.

Estimating SARS-CoV-2 transmission in educational settings: A retrospective cohort study.

BACKGROUND: School closures and distance learning have been extensively adopted to counter the COVID-19 pandemic. However, the contribution of school transmission to the spread of SARS-CoV-2 remains poorly quantified. METHODS: We analyzed transmission patterns associated with 976 SARS-CoV-2 exposure events, involving 460 positive individuals, as identified in early 2021 through routine surveillance and an extensive screening conducted on students, school personnel, and their household members in a small Italian municipality. In addition to population screenings and contact-tracing operations, reactive closures of class and schools were implemented. RESULTS: From the analysis of 152 clear infection episodes and 584 exposure events identified by epidemiological investigations, we estimated that approximately 50%, 21%, and 29% of SARS-CoV-2 transmission was associated with household, school, and community contacts, respectively. We found substantial transmission heterogeneities, with 20% positive individuals causing 75% to 80% of ascertained infection episodes. A higher proportion of infected individuals causing onward transmission was found among students (46.2% vs. 25%, on average), who also caused a markedly higher number of secondary cases (mean: 1.03 vs. 0.35). By reconstructing likely transmission chains from the entire set of exposures identified during contact-tracing operations, we found that clusters originated from students or school personnel were associated with a larger average cluster size (3.32 vs. 1.15) and a larger average number of generations in the transmission chain (1.56 vs. 1.17). CONCLUSIONS: Uncontrolled SARS-CoV-2 transmission at school could disrupt the regular conduct of teaching activities, likely seeding the transmission into other settings, and increasing the burden on contact-tracing operations.

Evaluation of humoral and cellular response to four vaccines against COVID-19 in different age groups: A longitudinal study.

To date there has been limited head-to-head evaluation of immune responses to different types of COVID-19 vaccines. A real-world population-based longitudinal study was designed with the aim to define the magnitude and duration of immunity induced by each of four different COVID-19 vaccines available in Italy at the time of this study. Overall, 2497 individuals were enrolled at time of their first vaccination (T0). Vaccine-specific antibody responses induced over time by Comirnaty, Spikevax, Vaxzevria, Janssen Ad26.COV2.S and heterologous vaccination were compared up to six months after immunization. On a subset of Comirnaty vaccinees, serology data were correlated with the ability to neutralize a reference SARS-CoV-2 B strain, as well as Delta AY.4 and Omicron BA.1. The frequency of SARS-CoV-2-specific CD4+ T cells, CD8+ T cells, and memory B cells induced by the four different vaccines was assessed six months after the immunization. We found that mRNA vaccines are stronger inducer of anti-Spike IgG and B-memory cell responses. Humoral immune responses are lower in frail elderly subjects. Neutralization of the Delta AY.4 and Omicron BA.1 variants is severely impaired, especially in older individuals. Most vaccinees display a vaccine-specific T-cell memory six months after the vaccination. By describing the immunological response during the first phase of COVID-19 vaccination campaign in different cohorts and considering several aspects of the immunological response, this study allowed to collect key information that could facilitate the implementation of effective prevention and control measures against SARS-CoV-2.

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.

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.

SARS-CoV-2 variants: what have we learnt so far?

Besides the timely detection of different SARS-CoV-2 variants through surveillance systems, functional and modelling studies are essential to better inform public health response and preparedness. Here, an overview on the knowledge available so far on SARS-CoV-2 variants are discussed by different expertises.

SARS-CoV-2 variants: what have we learnt so far? Commentary.

Besides the timely detection of different SARS-CoV-2 variants through surveillance systems, functional and modelling studies are essential to better inform public health response and preparedness. Here, the knowledge available so far on SARS-CoV-2 variants is discussed from different perspectives, in order to highlight the relevance of a multidisciplinary approach in countering the threat posed by this insidious virus.

Investigating the relationship between interventions, contact patterns, and SARS-CoV-2 transmissibility.

BACKGROUND: After a rapid upsurge of COVID-19 cases in Italy during the fall of 2020, the government introduced a three-tiered restriction system aimed at increasing physical distancing. The Ministry of Health, after periodic epidemiological risk assessments, assigned a tier to each of the 21 Italian regions and autonomous provinces. It is still unclear to what extent these different sets of measures altered the number of daily interactions and the social mixing patterns. METHODS AND FINDINGS: We conducted a survey between July 2020 and March 2021 to monitor changes in social contact patterns among individuals in the metropolitan city of Milan, Italy, which was hardly hit by the second wave of the COVID-19 pandemic. The number of daily contacts during periods characterized by different levels of restrictions was analyzed through negative binomial regression models and age-specific contact matrices were estimated under the different tiers of restrictions. By relying on the empirically estimated mixing patterns, we quantified relative changes in SARS-CoV-2 transmission potential associated with the different tiers. As tighter restrictions were implemented during the fall of 2020, a progressive reduction in the mean number of daily contacts recorded by study participants was observed: from 15.9 % under mild restrictions (yellow tier), to 41.8 % under strong restrictions (red tier). Higher restrictions levels were also found to increase the relative contribution of contacts occurring within the household. The SARS-CoV-2 reproduction number was estimated to decrease by 17.1 % (95 %CI: 1.5-30.1), 25.1 % (95 %CI: 13.0-36.0) and 44.7 % (95 %CI: 33.9-53.0) under the yellow, orange, and red tiers, respectively. CONCLUSIONS: Our results give an important quantification of the expected contribution of different restriction levels in shaping social contacts and decreasing the transmission potential of SARS-CoV-2. These estimates can find an operational use in anticipating the effect that the implementation of these tiered restriction can have on SARS-CoV-2 reproduction number under an evolving epidemiological situation.

Early prediction of SARS-CoV-2 reproductive number from environmental, atmospheric and mobility data: A supervised machine learning approach.

INTRODUCTION: SARS-CoV-2 was declared a pandemic by the WHO on March 11th, 2020. Public protective measures were enforced in every country to limit the diffusion of SARS-CoV-2. Its transmission, mainly by droplets, has been measured by the effective reproduction number (Rt) that counts the number of secondary cases caused in a population by an average infectious individual at time t. Current strategies to calculate Rt reflect the number of secondary cases after several days, due to a delay from symptoms onset to reporting. We propose a complementary Rt estimation using supervised machine learning techniques to predict short term variations with more timely results. MATERIAL AND METHODS: Our primary goal was to predict Rt of the current day in the twelve provinces of Lombardy with the highest possible accuracy, and with no influence of the local testing strategies. We gathered data about mobility, weather, and pollution from different public sources as a proxy of human behavior and public health measures. We built four supervised machine learning algorithms with different strategies: the outcome variable was the daily median Rt values per province obtained from officially adopted algorithms. RESULTS: Data from 243 days for every province were presented to our four models (from February 15th, 2020, to October 14th, 2020). Two models using differential calculation of Rt instead of the raw values showed the highest mean coefficient of determination (0.93 for both) and residuals reported the lowest mean error (-0.03 and 0.01) and standard deviation (0.13 for both) as well. The one with access to the value of Rt of the day before heavily relied on that feature for prediction, while the other one had more distributed weights. DISCUSSION: The model that had not access to the Rt value of the previous day and used Rt differential value as outcome (FDRt) was considered the most robust according to the metrics. Its forecasts were able to predict the trend that Rt values would have developed over different weeks, but it was not particularly accurate in predicting the precise value of Rt. A correlation among mobility, atmospheric, features, pollution and Rt values is plausible, but further testing should be performed.

Risk of Symptomatic Infection During a Second Coronavirus Disease 2019 Wave in Severe Acute Respiratory Syndrome Coronavirus 2-Seropositive Individuals.

We analyzed 221 coronavirus disease 2019 cases identified between June 2020 and January 2021 in 6074 individuals screened for immunoglobulin G antibodies in May 2020, representing 77% of residents of 5 Italian municipalities. The relative risk of developing symptomatic infection in seropositive participants was 0.055 (95% confidence interval, .014-.220).

Co-circulation of SARS-CoV-2 Alpha and Gamma variants in Italy, February and March 2021.

BackgroundSeveral SARS-CoV-2 variants of concern (VOC) have emerged through 2020 and 2021. There is need for tools to estimate the relative transmissibility of emerging variants of SARS-CoV-2 with respect to circulating strains.AimWe aimed to assess the prevalence of co-circulating VOC in Italy and estimate their relative transmissibility.MethodsWe conducted two genomic surveillance surveys on 18 February and 18 March 2021 across the whole Italian territory covering 3,243 clinical samples and developed a mathematical model that describes the dynamics of co-circulating strains.ResultsThe Alpha variant was already dominant on 18 February in a majority of regions/autonomous provinces (national prevalence: 54%) and almost completely replaced historical lineages by 18 March (dominant across Italy, national prevalence: 86%). We found a substantial proportion of the Gamma variant on 18 February, almost exclusively in central Italy (prevalence: 19%), which remained similar on 18 March. Nationally, the mean relative transmissibility of Alpha ranged at 1.55-1.57 times the level of historical lineages (95% CrI: 1.45-1.66). The relative transmissibility of Gamma varied according to the assumed degree of cross-protection from infection with other lineages and ranged from 1.12 (95% CrI: 1.03-1.23) with complete immune evasion to 1.39 (95% CrI: 1.26-1.56) for complete cross-protection.ConclusionWe assessed the relative advantage of competing viral strains, using a mathematical model assuming different degrees of cross-protection. We found substantial co-circulation of Alpha and Gamma in Italy. Gamma was not able to outcompete Alpha, probably because of its lower transmissibility.

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。

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.

Model-based evaluation of alternative reactive class closure strategies against COVID-19.

There are contrasting results concerning the effect of reactive school closure on SARS-CoV-2 transmission. To shed light on this controversy, we developed a data-driven computational model of SARS-CoV-2 transmission. We found that by reactively closing classes based on syndromic surveillance, SARS-CoV-2 infections are reduced by no more than 17.3% (95%CI: 8.0-26.8%), due to the low probability of timely identification of infections in the young population. We thus investigated an alternative triggering mechanism based on repeated screening of students using antigen tests. Depending on the contribution of schools to transmission, this strategy can greatly reduce COVID-19 burden even when school contribution to transmission and immunity in the population is low. Moving forward, the adoption of antigen-based screenings in schools could be instrumental to limit COVID-19 burden while vaccines continue to be rolled out.

Pressure on the Health-Care System and Intensive Care Utilization During the COVID-19 Outbreak in the Lombardy Region of Italy: A Retrospective Observational Study in 43,538 Hospitalized Patients.

During the spring of 2020, the coronavirus disease 2019 (COVID-19) epidemic caused an unprecedented demand for intensive-care resources in the Lombardy region of Italy. Using data on 43,538 hospitalized patients admitted between February 21 and July 12, 2020, we evaluated variations in intensive care unit (ICU) admissions and mortality over the course of 3 periods: the early phase of the pandemic (February 21-March 13), the period of highest pressure on the health-care system (March 14-April 25, when numbers of COVID-19 patients exceeded prepandemic ICU bed capacity), and the declining phase (April 26-July 12). Compared with the early phase, patients aged 70 years or more were less often admitted to an ICU during the period of highest pressure on the health-care system (odds ratio (OR) = 0.47, 95% confidence interval (CI): 0.41, 0.54), with longer ICU delays (incidence rate ratio = 1.82, 95% CI: 1.52, 2.18) and lower chances of dying in the ICU (OR = 0.47, 95% CI: 0.34, 0.64). Patients under 56 years of age had more limited changes in the probability of (OR = 0.65, 95% CI: 0.56, 0.76) and delay to (incidence rate ratio = 1.16, 95% CI: 0.95, 1.42) ICU admission and increased mortality (OR = 1.43, 95% CI: 1.00, 2.07). In the declining phase, all quantities decreased for all age groups. These patterns may suggest that limited health-care resources during the peak phase of the epidemic in Lombardy forced a shift in ICU admission criteria to prioritize patients with higher chances of survival.

The effect of COVID-19 vaccination in Italy and perspectives for living with the virus.

COVID-19 vaccination is allowing a progressive release of restrictions worldwide. Using a mathematical model, we assess the impact of vaccination in Italy since December 27, 2020 and evaluate prospects for societal reopening after emergence of the Delta variant. We estimate that by June 30, 2021, COVID-19 vaccination allowed the resumption of about half of pre-pandemic social contacts. In absence of vaccination, the same number of cases is obtained by resuming only about one third of pre-pandemic contacts, with about 12,100 (95% CI: 6,600-21,000) extra deaths (+27%; 95% CI: 15-47%). Vaccination offset the effect of the Delta variant in summer 2021. The future epidemic trend is surrounded by substantial uncertainty. Should a pediatric vaccine (for ages 5 and older) be licensed and a coverage >90% be achieved in all age classes, a return to pre-pandemic society could be envisioned. Increasing vaccination coverage will allow further reopening even in absence of a pediatric vaccine.