The aim of the study is to show whether it is possible to predict infectious disease outbreaks early, by using machine learning. This study was carried out following the guidelines of the Cochrane Collaboration and the meta-analysis of observational studies in epidemiology and the preferred reporting items for systematic reviews and meta-analyses. The suitable bibliography on PubMed/Medline and Scopus was searched by combining text, words, and titles on medical topics. At the end of the search, this systematic review contained 75 records. The studies analyzed in this systematic review demonstrate that it is possible to predict the incidence and trends of some infectious diseases; by combining several techniques and types of machine learning, it is possible to obtain accurate and plausible results.

COVID-19 is a current global threat, and the characterization of antibody response is vitally important to update vaccine development and strategies. In this study we assessed SARS-CoV-2 antibody concentrations in SARS-CoV-2 positive patients (N = 272) and subjects vaccinated with the BNT162b2 m-RNA COVID-19 vaccine (N = 1256). For each participant, socio-demographic data, COVID-19 vaccination records, serological analyses, and SARS-CoV-2 infection status were collected. IgG antibodies against S1/S2 antigens of SARS-CoV-2 were detected. Almost all vaccinated subjects (99.8%) showed a seropositivity to anti-SARS-COV-2 IgG and more than 80% of vaccinated subjects had IgG concentrations > 200 AU/mL. In a Tobit multivariable regression analysis, SARS-CoV-2 vaccination was statistically significantly associated with increased IgG concentrations (β coef = 266.4; p < 0.001). A statistically significant reduction in SARS-CoV-2 IgG concentrations was found with older age (β coef = −1.96 per year increase; p < 0.001), male sex (β coef = −22.3; p < 0.001), and days after immunization (β coef = −1.67 per day increase; p < 0.001). Our findings could support the vaccination campaigns confirming the high immunogenicity of the SARS-CoV-2 vaccine under investigation with respect to the natural infection. Further studies will be required for evaluating the role of age and days after immunization in the persistence of vaccine antibodies and protection from the disease.

In light of the implementation of human papillomavirus (HPV) prevention strategies, epidemiological studies in different geographical areas are required in order to assess the impact of HPV-related diseases. The purpose of the present study was to describe the burden of HPV-related hospitalizations in Sicily. A retrospective observational study estimated 43,531 hospitalizations attributable to HPV from 2007 to 2017. During the observed period, there was a decrease for all HPV-related conditions with a higher reduction, among neoplasms, for cervical cancer (annual percent change (APC) = −9.9%, p < 0.001). The median age for cervical cancer was 45 years old, with an increasing value from 43 to 47 years (p < 0.001). The age classes with greater decreases in hospital admissions for invasive cancers were women aged 35 years or more (APC range from −5.5 to −9.86) and 25–34 years old (APC = −11.87, p < 0.001) for women with cervical carcinoma in situ. After ten years for vaccine introduction and sixteen years for cervical cancer screening availability, a relatively large decrease in hospital admissions for cervical cancer and other HPV-related diseases in Sicily was observed. Some clinical characteristics of hospitalization, such as increasing age, are suggestive clues for the impact of preventive strategies, but further research is needed to confirm this relationship.