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  1. Article ; Online: COVID-19 non-pharmaceutical intervention portfolio effectiveness and risk communication predominance.

    Chan, Louis Yat Hin / Yuan, Baoyin / Convertino, Matteo

    Scientific reports

    2021  Volume 11, Issue 1, Page(s) 10605

    Abstract: Non-pharmaceutical interventions (NPIs) including resource allocation, risk communication, social distancing and travel restriction, are mainstream actions to control the spreading of Coronavirus disease 2019 (COVID-19) worldwide. Different countries ... ...

    Abstract Non-pharmaceutical interventions (NPIs) including resource allocation, risk communication, social distancing and travel restriction, are mainstream actions to control the spreading of Coronavirus disease 2019 (COVID-19) worldwide. Different countries implemented their own combinations of NPIs to prevent local epidemics and healthcare system overloaded. Portfolios, as temporal sets of NPIs have various systemic impacts on preventing cases in populations. Here, we developed a probabilistic modeling framework to evaluate the effectiveness of NPI portfolios at the macroscale. We employed a deconvolution method to back-calculate incidence of infections and estimate the effective reproduction number by using the package EpiEstim. We then evaluated the effectiveness of NPIs using ratios of the reproduction numbers and considered them individually and as a portfolio systemically. Based on estimates from Japan, we estimated time delays of symptomatic-to-confirmation and infection-to-confirmation as 7.4 and 11.4 days, respectively. These were used to correct surveillance data of other countries. Considering 50 countries, risk communication and returning to normal life were the most and least effective yielding the aggregated effectiveness of 0.11 and - 0.05 that correspond to a 22.4% and 12.2% reduction and increase in case growth. The latter is quantified by the change in reproduction number before and after intervention implementation. Countries with the optimal NPI portfolio are along an empirical Pareto frontier where mean and variance of effectiveness are maximized and minimized independently of incidence levels. Results indicate that implemented interventions, regardless of NPI portfolios, had distinct incidence reductions and a clear timing effect on infection dynamics measured by sequences of reproduction numbers. Overall, the successful suppression of the epidemic cannot work without the non-linear effect of NPI portfolios whose effectiveness optimality may relate to country-specific socio-environmental factors.
    MeSH term(s) Algorithms ; Basic Reproduction Number ; COVID-19/economics ; COVID-19/epidemiology ; COVID-19/prevention & control ; COVID-19/transmission ; Clinical Laboratory Techniques/methods ; Communicable Disease Control/methods ; Communication ; Computer Simulation ; Disease Transmission, Infectious/prevention & control ; Disease Transmission, Infectious/statistics & numerical data ; Humans ; Japan/epidemiology ; Models, Statistical ; SARS-CoV-2/isolation & purification
    Language English
    Publishing date 2021-05-19
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-021-88309-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Modeling geographic vaccination strategies for COVID-19 in Norway.

    Chan, Louis Yat Hin / Rø, Gunnar / Midtbø, Jørgen Eriksson / Di Ruscio, Francesco / Watle, Sara Sofie Viksmoen / Juvet, Lene Kristine / Littmann, Jasper / Aavitsland, Preben / Nygård, Karin Maria / Berg, Are Stuwitz / Bukholm, Geir / Kristoffersen, Anja Bråthen / Engø-Monsen, Kenth / Engebretsen, Solveig / Swanson, David / Palomares, Alfonso Diz-Lois / Lindstrøm, Jonas Christoffer / Frigessi, Arnoldo / de Blasio, Birgitte Freiesleben

    PLoS computational biology

    2024  Volume 20, Issue 1, Page(s) e1011426

    Abstract: Vaccination was a key intervention in controlling the COVID-19 pandemic globally. In early 2021, Norway faced significant regional variations in COVID-19 incidence and prevalence, with large differences in population density, necessitating efficient ... ...

    Abstract Vaccination was a key intervention in controlling the COVID-19 pandemic globally. In early 2021, Norway faced significant regional variations in COVID-19 incidence and prevalence, with large differences in population density, necessitating efficient vaccine allocation to reduce infections and severe outcomes. This study explored alternative vaccination strategies to minimize health outcomes (infections, hospitalizations, ICU admissions, deaths) by varying regions prioritized, extra doses prioritized, and implementation start time. Using two models (individual-based and meta-population), we simulated COVID-19 transmission during the primary vaccination period in Norway, covering the first 7 months of 2021. We investigated alternative strategies to allocate more vaccine doses to regions with a higher force of infection. We also examined the robustness of our results and highlighted potential structural differences between the two models. Our findings suggest that early vaccine prioritization could reduce COVID-19 related health outcomes by 8% to 20% compared to a baseline strategy without geographic prioritization. For minimizing infections, hospitalizations, or ICU admissions, the best strategy was to initially allocate all available vaccine doses to fewer high-risk municipalities, comprising approximately one-fourth of the population. For minimizing deaths, a moderate level of geographic prioritization, with approximately one-third of the population receiving doubled doses, gave the best outcomes by balancing the trade-off between vaccinating younger people in high-risk areas and older people in low-risk areas. The actual strategy implemented in Norway was a two-step moderate level aimed at maintaining the balance and ensuring ethical considerations and public trust. However, it did not offer significant advantages over the baseline strategy without geographic prioritization. Earlier implementation of geographic prioritization could have more effectively addressed the main wave of infections, substantially reducing the national burden of the pandemic.
    MeSH term(s) Humans ; Aged ; Pandemics/prevention & control ; COVID-19/epidemiology ; COVID-19/prevention & control ; Vaccination ; Norway/epidemiology ; Vaccines
    Chemical Substances Vaccines
    Language English
    Publishing date 2024-01-31
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2193340-6
    ISSN 1553-7358 ; 1553-734X
    ISSN (online) 1553-7358
    ISSN 1553-734X
    DOI 10.1371/journal.pcbi.1011426
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Modeling geographic vaccination strategies for COVID-19 in Norway

    Chan, Louis Yat Hin / Rø, Gunnar / Midtbø, Jørgen Eriksson / Di Ruscio, Francesco / Watle, Sara Sofie Viksmoen / Juvet, Lene Kristine / Littmann, Jasper / Aavitsland, Preben / Nygard, Karin Maria / Berg, Are Stuwitz / Bukholm, Geir / Kristoffersen, Anja Brathen / Engø-Monsen, Kenth / Engebretsen, Solveig / Swanson, David / Palomares, Alfonso Diz-Lois / Lindstrøm, Jonas Christoffer / Frigessi, Arnoldo / de Blasio, Birgitte Freiesleben

    medRxiv

    Abstract: Vaccination was a key intervention in controlling the COVID-19 pandemic globally. In early 2021, Norway faced significant regional variations in COVID-19 incidence and prevalence, with large differences in population density, necessitating efficient ... ...

    Abstract Vaccination was a key intervention in controlling the COVID-19 pandemic globally. In early 2021, Norway faced significant regional variations in COVID-19 incidence and prevalence, with large differences in population density, necessitating efficient vaccine allocation to reduce infections and severe outcomes. This study explored alternative vaccination strategies to minimize health outcomes (infections, hospitalizations, ICU admissions, deaths) by varying regions prioritized, extra doses prioritized, and implementation start time. Using two models (individual-based and meta-population), we simulated COVID-19 transmission during the primary vaccination period in Norway, covering the first 7 months of 2021. We investigated alternative strategies to allocate more vaccine doses to regions with a higher force of infection. We also examined the robustness of our results and highlighted potential structural differences between the two models. Our findings suggest that early vaccine prioritization could reduce COVID-19 related health outcomes by 8% to 20% compared to a baseline strategy without geographic prioritization. For minimizing infections, hospitalizations, or ICU admissions, the best strategy was to initially allocate all available vaccine doses to fewer high-risk municipalities, comprising approximately one-fourth of the population. For minimizing deaths, a moderate level of geographic prioritization, with approximately one-third of the population receiving doubled doses, gave the best outcomes by balancing the trade-off between vaccinating younger people in high-risk areas and older people in low-risk areas. The actual strategy implemented in Norway was a two-step moderate level aimed at maintaining the balance and ensuring ethical considerations and public trust. However, it did not offer significant advantages over the baseline strategy without geographic prioritization. Earlier implementation of geographic prioritization could have more effectively addressed the main wave of infections, substantially reducing the national burden of the pandemic.
    Keywords covid19
    Language English
    Publishing date 2023-08-21
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2023.08.16.23294112
    Database COVID19

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  4. Article ; Online: Modeling geographic vaccination strategies for COVID-19 in Norway

    Chan, Louis Yat Hin / Rø, Gunnar / Midtbø, Jørgen Eriksson / Di Ruscio, Francesco / Watle, Sara Sofie Viksmoen / Juvet, Lene Kristine / Littmann, Jasper / Aavitsland, Preben / Nygård, Karin Maria / Berg, Are Stuwitz / Bukholm, Geir / Kristoffersen, Anja Bråthen / Engø-Monsen, Kenth / Engebretsen, Solveig / Swanson, David / Palomares, Alfonso Diz-Lois / Lindstrøm, Jonas Christoffer / Frigessi, Arnoldo / de Blasio, Birgitte Freiesleben

    medRxiv

    Abstract: Vaccination was a key intervention in controlling the COVID-19 pandemic globally. In early 2021, Norway faced significant regional variations in COVID-19 incidence and prevalence, with large differences in population density, necessitating efficient ... ...

    Abstract Vaccination was a key intervention in controlling the COVID-19 pandemic globally. In early 2021, Norway faced significant regional variations in COVID-19 incidence and prevalence, with large differences in population density, necessitating efficient vaccine allocation to reduce infections and severe outcomes. This study explored alternative vaccination strategies to minimize health outcomes (infections, hospitalizations, ICU admissions, deaths) by varying regions prioritized, extra doses prioritized, and implementation start time. Using two models (individual-based and meta-population), we simulated COVID-19 transmission during the primary vaccination period in Norway, covering the first 7 months of 2021. We investigated alternative strategies to allocate more vaccine doses to regions with a higher force of infection. We also examined the robustness of our results and highlighted potential structural differences between the two models. Our findings suggest that early vaccine prioritization could reduce COVID-19 related health outcomes by 8% to 20% compared to a baseline strategy without geographic prioritization. For minimizing infections, hospitalizations, or ICU admissions, the best strategy was to initially allocate all available vaccine doses to fewer high-risk municipalities, comprising approximately one-fourth of the population. For minimizing deaths, a moderate level of geographic prioritization, with approximately one-third of the population receiving doubled doses, gave the best outcomes by balancing the trade-off between vaccinating younger people in high-risk areas and older people in low-risk areas. The actual strategy implemented in Norway was a two-step moderate level aimed at maintaining the balance and ensuring ethical considerations and public trust. However, it did not offer significant advantages over the baseline strategy without geographic prioritization. Earlier implementation of geographic prioritization could have more effectively addressed the main wave of infections, substantially reducing the national burden of the pandemic.
    Keywords covid19
    Language English
    Publishing date 2023-08-21
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2023.08.16.23294112
    Database COVID19

    Kategorien

  5. Article ; Online: Regional probabilistic situational awareness and forecasting of COVID-19

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

    medRxiv

    Abstract: Mathematical models and statistical inference are fundamental for surveillance and control of the COVID-19 pandemic. Several aspects cause regional heterogeneity in disease spread. Individual behaviour, mobility, viral variants and transmission vary ... ...

    Abstract Mathematical models and statistical inference are fundamental for surveillance and control of the COVID-19 pandemic. Several aspects cause regional heterogeneity in disease spread. Individual behaviour, mobility, viral variants and transmission vary locally, temporally and with the season, and interventions and vaccination are often implemented regionally. Therefore, we developed a new regional changepoint stochastic SEIR metapopulation model. The model is informed by real-time mobility estimates from mobile phone data, laboratory-confirmed cases, and hospitalisation incidence. To estimate locally and time-varying transmissibility, case detection probabilities, and missed imported cases, we present a new 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, suitable for real-time surveillance. By comparing the reproduction number before and after lockdown, we find a national transmissibility reduction of 85% (95% CI 78%-89%). The estimated effect varied regionally and was larger for the most populated regions than in the national average.
    Keywords covid19
    Language English
    Publishing date 2021-10-27
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2021.10.25.21265166
    Database COVID19

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