arXiv subjects

Piero Manfredi

Publications and source records attributed to Piero Manfredi.

8 recordsLinked to original sources

arXiv2026

A systematic review of COVID-19 epidemic models with endogenous human behaviour. What's next?

Human behaviour and epidemic dynamics are intertwined, yet accounting for this feedback remains one of the key challenges of epidemiological modelling. The COVID-19 pandemic was an opportunity to overcome the traditional limitations of the field, raising expectations that data-informed endogenous approaches to behaviour modelling would advance substantially. To quantify the progresses made, we conducted a systematic review of SARS-CoV-2 transmission models endogenously including human behaviour in response to epidemic dynamics. The COVID-19 pandemic saw great strides in terms of the expanded use of empirical data in epi-behavioural modelling. However, it also showed shortcomings with respect to limited use of behavioural empirical data, lack of innovation in model structure, and limited engagement with other disciplines and decision-makers. Overall, our results suggest that identifying priorities in model design and behavioural data, building an adequate data collection infrastructure, leveraging on AI advancements, and fostering interdisciplinarity are strategies of utmost importance for pandemic preparedness.

physics.soc-ph↗

arXiv2024

Optimal epidemic control by social distancing and vaccination of an infection structured by time since infection: the covid-19 case study

Motivated by the issue of COVID-19 mitigation, in this work we tackle the general problem of optimally controlling an epidemic outbreak of a communicable disease structured by time since exposure, by the aid of two types of control instruments namely, social distancing and vaccination by a vaccine at least partly effective in protecting from infection. Effective vaccines are assumed to be made available only in a subsequent period of the epidemic so that - in the first period - epidemic control only relies on social distancing, as it happened for the COVID-19 pandemic. By our analyses, we could prove the existence of (at least) one optimal control pair, we derived first-order necessary conditions for optimality, and proved some useful properties of such optimal solutions. A worked example provides a number of further insights on the relationships between key control and epidemic parameters.

q-bio.PE↗

arXiv2023

Spatio-temporal chaos and clustering induced by nonlocal information and vaccine hesitancy in the SIR epidemic model

Human behavior, and in particular vaccine hesitancy, is a critical factor for the control of childhood infectious disease. Here we propose a spatio-temporal behavioral epidemiology model where the vaccine propensity depends on information that is non-local in space and in time. The properties of the proposed model are analysed under different hypotheses on the spatio-temporal kernels tuning the vaccination response of individuals. As a main result, we could numerically show that vaccine hesitancy induces the onset of many dynamic patterns of relevance for epidemiology. In particular we observed: behavior-modulated patterns and spatio-temporal chaos. This is the first known example of human behavior-induced spatio-temporal chaos in statistical physics of vaccination. Patterns and spatio-temporal chaos are difficult to deal with, from the Public Health viewpoint, hence showing that vaccine hesitancy can cause them could be of interest. Additionally, we propose a new simple heuristic algorithm to estimate the Maximum Lyapunov Exponent.

physics.soc-ph↗

arXiv2021

Are renewable energies on a sustained path? Analysis of selected case-studies from the pre-pandemic-era

Provided widespread vaccination will bring the COVID-19 pandemic under full control worldwide, the contrast to climate change and the energy transition as one of its main actions will return at the top of national and international policy agendas. This paper employs multivariate diffusion models to investigate and quantitatively assess the competitive power of renewable energy technologies and their perspectives along the invoked energy transition. The study was conducted for the period 1965-2019 on a number of selected case studies, that were considered critically representative of the current transition process in view of their energy and political context. The dynamic relationship between renewable technologies and natural gas has been at the core of the analysis, trying to establish whether gas could be considered as a bridging technology or a lock-in. The main findings show that in all the analyzed countries RETs have exerted a strongly competitive effect towards gas. In most cases, gas is found to have a bridging role, aiding the uptake of renewables.

stat.AP↗

arXiv2019

Evidence of disorientation towards immunization on online social media after contrasting political communication on vaccines. Results from an analysis of Twitter data in Italy

Background. In Italy, in recent years, vaccination coverage for key immunizations as MMR has been declining to worryingly low levels. In 2017, the Italian Gov't expanded the number of mandatory immunizations introducing penalties to unvaccinated children's families. During the 2018 general elections campaign, immunization policy entered the political debate with the Gov't in charge blaming oppositions for fuelling vaccine scepticism. A new Gov't established in 2018 temporarily relaxed penalties. Objectives and Methods. Using a sentiment analysis on tweets posted in Italian during 2018, we aimed to: (i) characterize the temporal flow of vaccines communication on Twitter (ii) evaluate the polarity of vaccination opinions and usefulness of Twitter data to estimate vaccination parameters, and (iii) investigate whether the contrasting announcements at the highest political level might have originated disorientation amongst the Italian public. Results. Vaccine-relevant tweeters interactions peaked in response to main political events. Out of retained tweets, 70.0% resulted favourable to vaccination, 16.5% unfavourable, and 13.6% undecided, respectively. The smoothed time series of polarity proportions exhibit frequent large changes in the favourable proportion, enhanced by an up and down trend synchronized with the switch between gov't suggesting evidence of disorientation among the public. Conclusion. The reported evidence of disorientation documents that critical immunization topics, should never be used for political consensus. This is especially true given the increasing role of online social media as information source, which might yield to social pressures eventually harmful for vaccine uptake, and is worsened by the lack of institutional presence on Twitter, calling for efforts to contrast misinformation and the ensuing spread of hesitancy.

cs.SI↗

arXiv2018

Lyapunov stability of an SIRS epidemic model with varying population

In this paper we consider an SIRS epidemic model under a general assumption of density-dependent mortality. We prove the global stability of the disease-free equilibrium and propose a Lyapunov function that allows to demonstrate the global stability of the (unique) endemic state under broad conditions.

math.DS↗

arXiv2016

Statistical physics of vaccination

Historically, infectious diseases caused considerable damage to human societies, and they continue to do so today. To help reduce their impact, mathematical models of disease transmission have been studied to help understand disease dynamics and inform prevention strategies. Vaccination - one of the most important preventive measures of modern times - is of great interest both theoretically and empirically. And in contrast to traditional approaches, recent research increasingly explores the pivotal implications of individual behavior and heterogeneous contact patterns in populations. Our report reviews the developmental arc of theoretical epidemiology with emphasis on vaccination, as it led from classical models assuming homogeneously mixing (mean-field) populations and ignoring human behavior, to recent models that account for behavioral feedback and/or population spatial/social structure. Many of the methods used originated in statistical physics, such as lattice and network models, and their associated analytical frameworks. Similarly, the feedback loop between vaccinating behavior and disease propagation forms a coupled nonlinear system with analogs in physics. We also review the new paradigm of digital epidemiology, wherein sources of digital data such as online social media are mined for high-resolution information on epidemiologically relevant individual behavior. Armed with the tools and concepts of statistical physics, and further assisted by new sources of digital data, models that capture nonlinear interactions between behavior and disease dynamics offer a novel way of modeling real-world phenomena, and can help improve health outcomes. We conclude the review by discussing open problems in the field and promising directions for future research.

physics.soc-ph↗

arXiv2013

Information-related changes in contact patterns may trigger oscillations in the endemic prevalence of infectious diseases

It is well known that behavioral changes in contact patterns may significantly affect the spread of an epidemic outbreak. Here we focus on simple endemic models for recurrent epidemics, by modelling the social contact rate as a function of the available information on the present and past disease prevalence. We show that social behaviour change alone may trigger sustained oscillations. This indicates that human behavior might be a critical explaining factor of oscillations in time-series of endemic diseases. Finally, we briefly show how the inclusion of seasonal variations in contacts may imply chaos.

q-bio.PE↗