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Objectives: to describe the epidemic trends of COVID-19 over time and by area in the territory covered by Milan's Agency for Health Protection (ATS-MI) from February to May 2020., Design: descriptive study of COVID-19 cases., Setting and Participants: a new information system was developed to record COVID-19 cases with positive nasopharyngeal swab. Patients resident in the area covered by ATS-MI with symptom onset between February and May 2020 were selected. Different epidemic periods were considered based on the timeline of the various regional and national containment measures., Main Outcome Measures: case fatality ratios, incidence rates, and reproduction number by epidemic period and sub-area of ATS-MI., Results: a total of 27,017 swab-positive COVID-19 cases were included. Mean age was 65 years and males were 45%. Incidence in the ATS-MI area was 776 per 100,000 population. The number of deaths was 4,660, the crude case fatality ratio was 17.3%, higher in males (21.2%) than in females (14.0%). The estimated reproduction number registered its peak (3.0) in the early stages of the epidemic and subsequently decreased. Territorial differences were observed in the epidemic spread, with a higher incidence in the Lodi area., Conclusions: estimated incidence and case fatality ratios were higher than national estimates for Italy. Each ATS-MI area had different epidemic spread patterns.

Objectives: to describe the overall mortality increase in the provinces of Milan and Lodi - area covered by the Agency for Health Protection of Milan - during the COVID-19 epidemic in the first four months of 2020, compare it with the same time period in the years 2016-2019, and evaluate to what extent the mortality can be directly attributed to the outbreak., Design: cohort study., Setting and Participants: using a new information system developed during the pandemic, we gathered data on the number of daily deaths in the population residing in the provinces of Milan and Lodi by Local Health Unit (ASST) and age groups. To describe the case fatality of COVID-19, we performed a record linkage with a database specially constructed during the epidemic to identify deaths that occurred in confirmed cases., Main Outcome Measures: mortality and excess mortality were analysed by comparing the number of observed deaths in the first 4 months of 2020 with the average deaths of the years 2016-2019 in the same calendar period and with expected deaths, estimated using a Poisson model. Furthermore, a measure of relative risk was calculated as observed/expected ratio with a 95% confidence interval., Results: the increase in mortality for all causes occurring in the study population in the first 4 months of 2020 was 48.8%, 30.8% for ages between 60 and 69, 43.9% for ages between 70 and 79, and 56.7% for subjects above 80 years of age. Focusing on the epidemic period, from 1 March to 30 April, the excess is quantifiable as more than 2-fold and mainly concerns the population over 60 years of age. The excess mortality was observed in all local health units (ASSTs). The highest increments were in the province of Lodi and the North-East of Milan (ASST Nord). In the ASSTs of Lodi and Melegnano-Martesana the mortality excess was detectable from March 15th, while for the other ASSTs the increase began in the first week of April., Conclusions: evaluation of overall mortality in the provinces of Milan and Lodi during the first wave of the Covid-19 epidemic showed a significant excess compared to the first 4 months of the years 2016-2019, mainly in the population over 60 years of age. However, this excess cannot be completely attributed directly to COVID-19 itself. This phenomenon was more intense in the Lodi ASST, with daily deaths up to 5 times higher than expected.

Background: In February 2021, the spread of a new variant of SARS-CoV-2 in the Lombardy Region, Italy caused concerns about school-aged children as a source of contagion, leading local authorities to adopt an extraordinary school closure measure. This generated a debate about the usefulness of such an intervention in light of the trade-off between its related benefits and costs (e.g. delays in educational attainment, impact on children and families' psycho-physical well-being). This article analyses the epidemiological impact of the school closure intervention in the Milan metropolitan area. Methods: Data from the Agency for Health Protection of the Metropolitan City of Milan allowed analysing the trend of contagion in different age classes before and after the intervention, adopting an interrupted times series design, providing a quasi-experimental counterfactual scenario. Segmented Poisson regression models of daily incident cases were performed separately for the 3–11-year-old, the 12–19-year-old, and the 20+-year-old age groups, examining the change in the contagion curves after the intervention, adjusting for time-varying confounders. Kaplan-Meier survival curves and Cox regression were used to assess the equality of survival curves in the three age groups before and after the intervention. Results: Net of time-varying confounders, the intervention produced a daily reduction of the risk of contagion by 4% in those aged 3–11 and 12–19 (IRR = 0·96) and by 3% in those aged 20 or more (IRR = 0·97). More importantly, there were differences in the temporal order of contagion decrease between the age groups, with the epidemic curve lowering first in the school-aged children directly affected by the intervention, and only subsequently in the adult population, which presumably indirectly benefitted from the reduction of contagion among children. Conclusion: Though it was not possible to completely discern the effect of school closures from concurrent policy measures, a substantial decrease in the contagion curves was clearly detected after the intervention. The extent to which the slowdown of infections counterbalanced the social costs of the policy remains unclear. [ABSTRACT FROM AUTHOR]

Social inequalities in health are known to be influenced by the socioeconomic status of the territory in which people live. In the context of the ongoing coronavirus disease 2019 (COVID-19) pandemic, this study is aimed at assessing the role of 5 area-level indicators in shaping the risk of contagion in the provinces of Milan and Lodi (Lombardy, Italy), namely: educational disadvantage, unemployment, housing crowding, mobility, and population density. The study area includes the municipalities at the origin of the first Italian epidemic outbreak. Data on COVID-19 patients from the Integrated Datawarehouse for COVID Analysis in Milan were used and matched with aggregate-level data from the National Institute of Statistics Italy (Istat). Multilevel logistic regression models were used to estimate the association between the census block-level predictors and COVID-19 infection, independently of age, sex, country of birth, and preexisting health conditions. All the variables were significantly associated with the outcome, with different effects before and after the lockdown and according to the province of residence. This suggests a pattern of socioeconomic inequalities in the outbreak, which should be taken into account in the eventuality of future epidemics to contain their spread and its related disparities. [ABSTRACT FROM AUTHOR]