Anomalous metastability in a temperature-driven transition

Langer theory of metastability provides a description of the lifetime and properties of the metastable phase of the Ising model field-driven transition, describing the magnetic field-driven transition in ferromagnets and the chemical potential-driven transition of fluids. An immediate further step is to apply it to the study of a transition driven by the temperature, as the one underwent by the two-dimensional Potts model. For this model a study based on the analytical continuation of the free energy (Meunier, Morel 2000) predicts the anomalous vanishing of the metastable temperature range in the limit of large system size, an issue that has been controversial since the eighties. With a parallel-GPU algorithm we compare the Monte Carlo dynamics with the theory, obtaining agreement and characterizing the anomalous system size dependence. We discuss the microscopic origin of these metastable phenomena, essentially different with respect to the Ising case.Comment: 5 pages, 3 figure

Rejoinder to Discussion of "A Tale of Two Datasets: Representativeness and Generalisability of Inference for Samples of Networks''

This rejoinder responds to discussions by of Caimo, Niezink, and Schweinberger and Fritz of ''A Tale of Two Datasets: Representativeness and Generalisability of Inference for Samples of Networks'' by Krivitsky, Coletti, and Hens, all published in the Journal of the American Statistical Association in 2023.Comment: 10 pages, 3 figures, 3 table

SOCRATES: an online tool leveraging a social contact data sharing initiative to assess mitigation strategies for COVID-19.

OBJECTIVE: Establishing a social contact data sharing initiative and an interactive tool to assess mitigation strategies for COVID-19. RESULTS: We organized data sharing of published social contact surveys via online repositories and formatting guidelines. We analyzed this social contact data in terms of weighted social contact matrices, next generation matrices, relative incidence and R[Formula: see text]. We incorporated location-specific physical distancing measures (e.g. school closure or at work) and capture their effect on transmission dynamics. All methods have been implemented in an online application based on R Shiny and applied to COVID-19 with age-specific susceptibility and infectiousness. Using our online tool with the available social contact data, we illustrate that physical distancing could have a considerable impact on reducing transmission for COVID-19. The effect itself depends on assumptions made about disease-specific characteristics and the choice of intervention(s)

Inferring age-specific differences in susceptibility to and infectiousness upon SARS-CoV-2 infection based on Belgian social contact data

Several important aspects related to SARS-CoV-2 transmission are not well known due to a lack of appropriate data. However, mathematical and computational tools can be used to extract part of this information from the available data, like some hidden age-related characteristics. In this paper, we present a method to investigate age-specific differences in transmission parameters related to susceptibility to and infectiousness upon contracting SARS-CoV-2 infection. More specifically, we use panel-based social contact data from diary-based surveys conducted in Belgium combined with the next generation principle to infer the relative incidence and we compare this to real-life incidence data. Comparing these two allows for the estimation of age-specific transmission parameters. Our analysis implies the susceptibility in children to be around half of the susceptibility in adults, and even lower for very young children (preschooler). However, the probability of adults and the elderly to contract the infection is decreasing throughout the vaccination campaign, thereby modifying the picture over time.Comment: Revised version, 17 pages, supplementary material 15 page

A comprehensive system for semantic spatiotemporal assessment of risk in urban areas

AbstractRisk assessment of urban areas aims at limiting the impact of harmful events by increasing awareness of their possible consequences. Qualitative risk assessment allows to figure out possible risk situations and to prioritize them, whereas quantitative risk assessment is devoted to measuring risks from data, in order to improve preparedness in case of crisis situations. We propose an automatic approach to comprehensive risk assessment. This leverages on a semantic and spatiotemporal representation of knowledge of the urban area and relies on a software system including: a knowledge base; two components for quantitative and qualitative risk assessments, respectively; and a WebGIS interface. The knowledge base consists of the TERMINUS domain ontology, to represent urban knowledge, and of a geo‐referenced database, including geographical, environmental and urban data as well as temporal data related to the levels of operation of city services. CIPcast DSS is the component devoted to quantitative risk assessment, and WS‐CREAM is the component supporting qualitative risk assessment based on computational creativity techniques. Two case studies concerning the city of Rome (Italy) show how this approach can be used in a real scenario for crisis preparedness. Finally, we discuss issues related to plausibility of risks and objectivity of their assessment

Different forms of superspreading lead to different outcomes:heterogeneity in infectiousness and contact behavior relevant for the case of SARS-CoV-2

Superspreading events play an important role in the spread of several pathogens, such as SARS-CoV-2. While the basic reproduction number of the original Wuhan SARS-CoV-2 is estimated to be about 3 for Belgium, there is substantial inter-individual variation in the number of secondary cases each infected individual causes—with most infectious individuals generating no or only a few secondary cases, while about 20% of infectious individuals is responsible for 80% of new infections. Multiple factors contribute to the occurrence of superspreading events: heterogeneity in infectiousness, individual variations in susceptibility, differences in contact behavior, and the environment in which transmission takes place. While superspreading has been included in several infectious disease transmission models, research into the effects of different forms of superspreading on the spread of pathogens remains limited. To disentangle the effects of infectiousness-related heterogeneity on the one hand and contact-related heterogeneity on the other, we implemented both forms of superspreading in an individual-based model describing the transmission and spread of SARS-CoV-2 in a synthetic Belgian population. We considered its impact on viral spread as well as on epidemic resurgence after a period of social distancing. We found that the effects of superspreading driven by heterogeneity in infectiousness are different from the effects of superspreading driven by heterogeneity in contact behavior. On the one hand, a higher level of infectiousness-related heterogeneity results in a lower risk of an outbreak persisting following the introduction of one infected individual into the population. Outbreaks that did persist led to fewer total cases and were slower, with a lower peak which occurred at a later point in time, and a lower herd immunity threshold. Finally, the risk of resurgence of an outbreak following a period of lockdown decreased. On the other hand, when contact-related heterogeneity was high, this also led to fewer cases in total during persistent outbreaks, but caused outbreaks to be more explosive in regard to other aspects (such as higher peaks which occurred earlier, and a higher herd immunity threshold). Finally, the risk of resurgence of an outbreak following a period of lockdown increased. We found that these effects were conserved when testing combinations of infectiousness-related and contact-related heterogeneity

Social contact patterns following the COVID-19 pandemic: a snapshot of post-pandemic behaviour from the CoMix study.

The COVID-19 pandemic led to unprecedented changes in behaviour. To estimate if these persisted, a final round of the CoMix social contact survey was conducted in four countries at a time when all societal restrictions had been lifted for several months. We conducted a survey on a nationally representative sample in the UK, Netherlands (NL), Belgium (BE), and Switzerland (CH). Participants were asked about their contacts and behaviours on the previous day. We calculated contact matrices and compared the contact levels to a pre-pandemic baseline to estimate R0. Data collection occurred from 17 November to 7 December 2022. 7477 participants were recruited. Some were asked to undertake the survey on behalf of their children. Only 14.4 % of all participants reported wearing a facemask on the previous day. Self-reported vaccination rates in adults were similar for each country at around 86 %. Trimmed mean recorded contacts were highest in NL with 9.9 (95 % confidence interval [CI] 9.0-10.8) contacts per person per day and lowest in CH at 6.0 (95 % CI 5.4-6.6). Contacts at work were lowest in the UK (1.4 contacts per person per day) and highest in NL at 2.8 contacts per person per day. Other contacts were also lower in the UK at 1.6 per person per day (95 % CI 1.4-1.9) and highest in NL at 3.4 recorded per person per day (95 % CI 43.0-4.0). The next-generation approach suggests that R0 for a close-contact disease would be roughly half pre-pandemic levels in the UK, 80 % in NL and intermediate in the other two countries. The pandemic appears to have resulted in lasting changes in contact patterns expected to have an impact on the epidemiology of many different pathogens. Further post-pandemic surveys are necessary to confirm this finding