Publications by authors named "Gianpaolo S Tomba"

New disease challenges, societal demands and better or novel types of data, drive innovations in the structure, formulation and analysis of epidemic models. Innovations in modelling can lead to new insights into epidemic processes and better use of available data, yielding improved disease control and stimulating collection of better data and new data types. Here we identify key challenges for the structure, formulation, analysis and use of mathematical models of pathogen transmission relevant to current and future pandemics.

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Background: For decades, assessments of the impact of universal varicella vaccination on the epidemiology of varicella and herpes zoster (HZ) have been made using mathematical modelling. Decreased virus circulation and the resulting diminished exogenous boosting have been predicted to lead to a surge in HZ incidence. Lately, the exogenous boosting hypothesis has been challenged due to a lack of an extensive surge in HZ incidence in countries with, by now long-standing universal varicella vaccination.

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Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented.

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Background: Online sampling is widely used to recruit hard to reach samples such as drug users at nightlife events. We conducted the first study comparing differences in demographics, drug use and nightlife behaviour between an online sample of young adults engaging with the European nightlife scene, and an offline sample recruited at nightclubs and festivals in Europe.

Methods: Online participants who attended at least six nightlife events in the past 12 months were recruited using social media advertising (May-November 2017).

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Article Synopsis
  • The study aimed to evaluate the health and economic impacts of different sick leave strategies for workers exhibiting influenza symptoms.
  • It assessed various interventions, including increasing sick leave from 65% to 80-90% and reducing the delay to sick leave from 4 days to 0.5 days, across 12 seasonal and 36 pandemic scenarios.
  • Findings indicated that prompt sick leave and a high percentage of workers taking it led to significant health and economic benefits, with the best results coming from interventions that encouraged sick leave within half a day of symptom onset.
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Background: Drug use indicators that are capable of measuring the individual levels of harm following drug use, and in particular, poly-drug use, have previously been proposed, based on individual drug and frequency of use data and expert rankings of harms related to various substances. These indicators allow the estimation of risk profiles for selected groups of individuals and comparisons, both over time and between populations. Recent advances regarding the ranking of drug use harms allow a refinement of these indicators, separating the effects on self and others.

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Background: Knowledge about influenza transmission in the workplace and whether staying home from work when experiencing influenza-like illness can reduce the spread of influenza is crucial for the design of efficient public health initiatives.

Aim: This review synthesizes current literature on sickness presenteeism and influenza transmission in the workplace and provides an overview of sick leave recommendations in Europe for influenza.

Methods: A search was performed on Medline, Embase, PsychINFO, Cinahl, Web of Science, Scopus and SweMed to identify studies related to workplace contacts, -transmission, -interventions and compliance with recommendations to take sick leave.

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Public health-related decision-making on policies aimed at controlling epidemics is increasingly evidence-based, exploiting multiple sources of data. Policy makers rely on complex models that are required to be robust, realistically approximating epidemics and consistent with all relevant data. Meeting these requirements in a statistically rigorous and defendable manner poses a number of challenging problems.

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Several methods for estimating drug use incidence, that have been used in the literature or that could be used, having been used in a different framework, are described and commented. The applicability of the different methods depends on available data and knowledge about relevant parameters. The many similarities between drug use incidence estimation and estimation of disease incidence are highlighted, but also the distinguishing aspects that make drug use incidence estimation a challenge to standard statistical methods.

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A comparative analysis of three different estimation methods of cocaine use in Milan, Italy, is carried out, including an analysis of the size and trends of the underlying reference population. The three cocaine use estimates are derived from wastewater analysis, a "street" survey and one-source capture-recapture analysis of administrative sanctions for drug possession. All three data sources span several years during the decade 2000-2010.

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Background: Anecdotal evidence of the involvement of alternative splicing (AS) in the regulation of protein-protein interactions has been reported by several studies. AS events have been shown to significantly occur in regions where a protein interaction domain or a short linear motif is present. Several AS variants show partial or complete loss of interface residues, suggesting that AS can play a major role in the interaction regulation by selectively targeting the protein binding sites.

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To evaluate the impact of mass vaccination with adjuvanted vaccines (eventually 40% population coverage) and antivirals during the 2009 influenza pandemic in Norway, we fitted an age-structured SEIR model using data on vaccinations and sales of antivirals in 2009/10 in Norway to Norwegian ILI surveillance data from 5 October 2009 to 4 January 2010. We estimate a clinical attack rate of approximately 30% (28.7-29.

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Background: Mathematical modelling of infectious diseases transmitted by the respiratory or close-contact route (e.g., pandemic influenza) is increasingly being used to determine the impact of possible interventions.

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In 2004, we conducted a study in Piemonte (Italy), in order to describe incidence, treatment, hospitalizations and costs of herpes zoster (HZ), in population over 14 years of age. Twenty-four regional general practitioners, with 26,394 patients >14 years in charge (0.71% of the regional population), reported prospectively all diagnosed HZ cases.

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Intrauterine growth retardation (IUGR) has been linked to the development of type 2 diabetes in later life. The mechanisms underlying this phenomenon are unknown. Recent data suggest that some of the molecular defects underlying type 2 diabetes reside in the CNS.

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A mathematical model has been developed in order to assess the effect of extended programs of varicella vaccination on the epidemiology of the disease in Italy. The effect of different vaccination options have been estimated by the change in incidence of the disease and age distribution of cases over a short and long period of time. The developed mathematical model reproduces chickenpox transmission and immunisation; five strategies different for target age of vaccination and/or proportion of vaccinated subjects have been considered.

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