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Showing 1–13 of 13 results
Advanced filters: Author: Matteo Chinazzi Clear advanced filters

  • Modelling highlights international travel as the main driver of the introduction of SARS-CoV-2 to Europe and the USA, and suggests that introductions and local transmission may have begun in January 2020.

    • Jessica T. Davis
    • Matteo Chinazzi
    • Alessandro Vespignani
    ResearchOpen Access
    Nature
    Volume: 600, P: 127-132

  • This manuscript evaluates forecasts of laboratory-confirmed influenza hospital admissions, a new target for influenza forecasting in the United States. Across two influenza seasons, the FluSight ensemble is robust compared to submitted models.

    • Sarabeth M. Mathis
    • Alexander E. Webber
    • Rebecca K. Borchering
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-13

  • By simulating the implementation of airport-based wastewater surveillance sites at the global level, a modeling study shows how this early warning system would perform in identifying sources of pandemic outbreaks, in time and space, and what the optimal location of monitoring sites would be.

    • Guillaume St-Onge
    • Jessica T. Davis
    • Alessandro Vespignani
    ResearchOpen Access
    Nature Medicine
    Volume: 31, P: 788-796

  • The US COVID-19 Scenario Modeling Hub produced medium to long term projections based on different epidemic scenarios. In this study, the authors evaluate 14 rounds of projections by comparing them to the epidemic trajectories that occurred, and discuss lessons learned for future similar projects.

    • Emily Howerton
    • Lucie Contamin
    • Justin Lessler
    ResearchOpen Access
    Nature Communications
    Volume: 14, P: 1-15

  • The authors construct a model that captures both health and economic aspects of the coronavirus disease 2019 pandemic, and uncover trade-offs between epidemic and economic outcomes both when individuals change their behaviour due to fear of infection and when non-pharmaceutical interventions are imposed.

    • Marco Pangallo
    • Alberto Aleta
    • J. Doyne Farmer
    ResearchOpen Access
    Nature Human Behaviour
    Volume: 8, P: 264-275

  • Global COVID-19 vaccine distribution has been inequitable. In this mathematical modelling study, the authors estimate the proportion of deaths that could have been averted in twenty low- and lower-middle-income countries if vaccines had been more widely available early in the pandemic.

    • Nicolò Gozzi
    • Matteo Chinazzi
    • Alessandro Vespignani
    ResearchOpen Access
    Nature Communications
    Volume: 14, P: 1-10

  • Fine-grained studies of epidemic spread and of the effect of nonpharmaceutical interventions are still needed to underpin demographic and socio-economic effects. Here, the authors study the spatial and temporal spread of SARS-CoV-2 in Santiago de Chile using anonymized mobile phone data.

    • Nicolò Gozzi
    • Michele Tizzoni
    • Nicola Perra
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-9

  • Massive unemployment during the COVID-19 pandemic could result in an eviction crisis in US cities. Here, the authors model the effect of evictions on SARS-CoV-2 epidemics, simulating viral transmission within and among households in a theoretical and applied urban settings.

    • Anjalika Nande
    • Justin Sheen
    • Alison L. Hill
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-13

  • The growing need for realism in addressing complex public health questions calls for accurate models of the human contact patterns that govern disease transmission. Here, the authors generate effective population-level contact matrices by using highly detailed macro (census) and micro (survey) data on key socio-demographic features.

    • Dina Mistry
    • Maria Litvinova
    • Alessandro Vespignani
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-12

  • Klein et al. use mobility data to forecast COVID-19 admissions for five Massachusetts hospitals. Combining aggregated mobile device data about users’ contact patterns, commuting volume, and mobility range with COVID hospitalizations and test-positivity data increases the lead-time of accurate predictions for individual hospitals.

    • Brennan Klein
    • Ana C. Zenteno
    • Hojjat Salmasian
    ResearchOpen Access
    Communications Medicine
    Volume: 3, P: 1-9