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  1. Article ; Online: Short-term association between air temperature and mortality in seven cities in Norway: A time series analysis.

    Vázquez Fernández, Liliana / Diz-Lois Palomares, Alfonso / Vicedo Cabrera, Ana M / Freiesleben De Blasio, Birgitte / Di Ruscio, Francesco / Wisløff, Torbjørn / Rao, Shilpa

    Scandinavian journal of public health

    2024  , Page(s) 14034948241233359

    Language English
    Publishing date 2024-03-04
    Publishing country Sweden
    Document type Journal Article
    ZDB-ID 1475054-5
    ISSN 1651-1905 ; 1403-4948
    ISSN (online) 1651-1905
    ISSN 1403-4948
    DOI 10.1177/14034948241233359
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 884: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (1.OG)
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  2. Article ; Online: A real-time regional model for COVID-19: Probabilistic situational awareness and forecasting.

    Engebretsen, Solveig / Diz-Lois Palomares, Alfonso / Rø, Gunnar / Kristoffersen, Anja Bråthen / Lindstrøm, Jonas Christoffer / Engø-Monsen, Kenth / Kamineni, Meghana / Hin Chan, Louis Yat / Dale, Ørjan / Midtbø, Jørgen Eriksson / Stenerud, Kristian Lindalen / Di Ruscio, Francesco / White, Richard / Frigessi, Arnoldo / de Blasio, Birgitte Freiesleben

    PLoS computational biology

    2023  Volume 19, Issue 1, Page(s) e1010860

    Abstract: The COVID-19 pandemic is challenging nations with devastating health and economic consequences. The spread of the disease has revealed major geographical heterogeneity because of regionally varying individual behaviour and mobility patterns, unequal ... ...

    Abstract The COVID-19 pandemic is challenging nations with devastating health and economic consequences. The spread of the disease has revealed major geographical heterogeneity because of regionally varying individual behaviour and mobility patterns, unequal meteorological conditions, diverse viral variants, and locally implemented non-pharmaceutical interventions and vaccination roll-out. To support national and regional authorities in surveilling and controlling the pandemic in real-time as it unfolds, we here develop a new regional mathematical and statistical model. The model, which has been in use in Norway during the first two years of the pandemic, is informed by real-time mobility estimates from mobile phone data and laboratory-confirmed case and hospitalisation incidence. To estimate regional and time-varying transmissibility, case detection probabilities, and missed imported cases, we developed a novel sequential Approximate Bayesian Computation method allowing inference in useful time, despite the high parametric dimension. We test our approach on Norway and find that three-week-ahead predictions are precise and well-calibrated, enabling policy-relevant situational awareness at a local scale. By comparing the reproduction numbers before and after lockdowns, we identify spatially heterogeneous patterns in their effect on the transmissibility, with a stronger effect in the most populated regions compared to the national reduction estimated to be 85% (95% CI 78%-89%). Our approach is the first regional changepoint stochastic metapopulation model capable of real time spatially refined surveillance and forecasting during emergencies.
    MeSH term(s) Humans ; COVID-19/epidemiology ; COVID-19/prevention & control ; Bayes Theorem ; Pandemics ; Awareness ; Communicable Disease Control ; Forecasting
    Language English
    Publishing date 2023-01-23
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2193340-6
    ISSN 1553-7358 ; 1553-734X
    ISSN (online) 1553-7358
    ISSN 1553-734X
    DOI 10.1371/journal.pcbi.1010860
    Database MEDical Literature Analysis and Retrieval System OnLINE

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