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At the beginning of 2023, the Italian former prime minister, the former health minister and 17 others including the current president of the Lombardy region were placed under investigation on suspicion of aggravated culpable epidemic in connection with the government's response at the start of the COVID-19 pandemic. The charges revolve around the failure by authorities to take adequate measures to prevent the spread of the virus in the Bergamo area, which experienced a significant excess of deaths during the initial outbreak. The aim of this paper is to analyse the pandemic data of Italy and the Lombardy region in the first 10 days of the pandemic, spanning from the 24th of February 2020 to the 4th of March 2020. The objective is to determine whether the use of early warning indicators could have facilitated the identification of a critical increase in infections. This identification, in turn, would have enabled the timely formulation of strategies for pandemic containment, thereby reducing the number of deaths. In conclusion, to translate our findings into practical guidelines, we propose a low-cost early warning method for infectious respiratory diseases with asymptomatic carriers. [ABSTRACT FROM AUTHOR]

The prediction of the evolution of epidemics plays an important role in limiting the transmissibility and the burdensome consequences of infectious diseases, which leads to the employment of mathematical modeling. In this paper, we propose a stochastic particle filtering extended SEIRS model with repeated vaccination and time-dependent parameters, aiming to efficiently describe the demanding dynamics of time-varying epidemics. The validity of our model is examined using daily records of COVID-19 in Italy for a period of 525 days, revealing a notable capacity to uncover the hidden dynamics of the pandemic. The main findings include the estimation of asymptomatic cases, which is a well-known feature of the current pandemic. Unlike other proposed models that employ extra compartments for asymptomatic cases, which force the estimation of this proportion and significantly increase the model's complexity, our approach leads to the evaluation of the hidden dynamics of COVID-19 without additional computational burden. Other findings that confirm the model's appropriateness and robustness are its parameter evolution and the estimation of more ICU-admitted cases compared to the official records during the most prevalent infection wave of January 2022, attributed to the intensified increase in admissions that may have led to full occupancy in ICUs. As the vast majority of datasets contain time series of total recovered and vaccinated cases, we propose a statistical algorithm to estimate the currently recovered and protected through vaccination cases. This necessity arises from the attenuation of antibodies after vaccination/infection and is necessary for long-time interval predictions. Finally, we not only present a novel stochastic epidemiological model and test its efficiency but also investigate its mathematical properties, such as the existence and stability of epidemic equilibria, giving new insights to the literature. The latter provides additional details concerning the system's long-term behavior, while the conclusions drawn from the R0 index provide perspectives on the severity and future of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Highly contagious diseases, such as mumps, are a global concern as new epidemics continue to emerge, even in highly vaccinated populations. The risk of transmission and spread of these viruses is even higher for individuals who are more likely to be exposed, including healthcare workers (HCWs). In healthcare settings, both HCWs and patients are at risk of infection during the care process, potentially leading to nosocomial epidemic outbreaks. Mumps is often underestimated compared with measles and rubella, despite being milder and less likely to spread. In fact, the risk of complications following mumps infection is extremely high, especially if the disease occurs in adulthood. The measles–mumps–rubella (MMR) vaccine has been shown to be an excellent preventive measure. Unfortunately, the mumps component appears to be less effective in inducing immunity than those for measles and rubella (two-dose effectiveness of 85%, 95% and 97%, respectively). The main aim of our study was to investigate the prevalence of detectable mumps antibodies (serum IgG antibodies) in a cohort of Italian and foreign HCWs in relation to personal and occupational factors. We included in the study 468 subjects who underwent health surveillance at the Occupational Medicine Unit of the Tor Vergata Polyclinic in Rome during the period from January 2021 to March 2023. In our study, the proportion of HCWs found to be unprotected against mumps was very high (8.3%), and those found to be immune are below the WHO threshold for herd immunity (95%). From our data, it seems essential that all occupational health services carry out an accurate screening with a dose of anti-mumps antibodies to assess serological protection before starting a job, regardless of an individual's vaccination history. This approach is proving to be beneficial, accurate, as it allows all serologically non-immune individuals to be vaccinated in the workplace, including those who would be protected by their vaccination history but have lost the antibody response. [ABSTRACT FROM AUTHOR]