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Temporal trends and forecasting of COVID-19 hospitalisations and deaths in Scotland using a national real-time patient-level data platform : a statistical modelling study

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  • معلومة اضافية
    • الموضوع:
      2021
    • Collection:
      University of Strathclyde Glasgow: Strathprints
    • نبذة مختصرة :
      Background: As the COVID-19 pandemic continues, national-level surveillance platforms with real-time individual person-level data are required to monitor and predict the epidemiological and clinical profile of COVID-19 and inform public health policy. We aimed to create a national dataset of patient-level data in Scotland to identify temporal trends and COVID-19 risk factors, and to develop a novel statistical prediction model to forecast COVID-19-related deaths and hospitalisations during the second wave. Methods: We established a surveillance platform to monitor COVID-19 temporal trends using person-level primary care data (including age, sex, socioeconomic status, urban or rural residence, care home residence, and clinical risk factors) linked to data on SARS-CoV-2 RT-PCR tests, hospitalisations, and deaths for all individuals resident in Scotland who were registered with a general practice on Feb 23, 2020. A Cox proportional hazards model was used to estimate the association between clinical risk groups and time to hospitalisation and death. A survival prediction model derived from data from March 1 to June 23, 2020, was created to forecast hospital admissions and deaths from October to December, 2020. We fitted a generalised additive spline model to daily SARS-CoV-2 cases over the previous 10 weeks and used this to create a 28-day forecast of the number of daily cases. The age and risk group pattern of cases in the previous 3 weeks was then used to select a stratified sample of individuals from our cohort who had not previously tested positive, with future cases in each group sampled from a multinomial distribution. We then used their patient characteristics (including age, sex, comorbidities, and socioeconomic status) to predict their probability of hospitalisation or death. Findings: Our cohort included 5 384 819 people, representing 98·6% of the entire estimated population residing in Scotland during 2020. Hospitalisation and death among those testing positive for SARS-CoV-2 between March 1 and June 23, ...
    • File Description:
      text
    • Relation:
      https://strathprints.strath.ac.uk/78140/1/Simpson_etal_LDH_2021_Temporal_trends_and_forecasting_of_COVID_19_hospitalisations_and_deaths_in_Scotland.pdf; Simpson, Colin R and Robertson, Chris and Vasileiou, Eleftheria and Moore, Emily and McCowan, Colin and Agrawal, Utkarsh and Stagg, Helen R and Docherty, Annemarie and Mulholland, Rachel and Murray, Josephine L K and Ritchie, Lewis D and McMenamin, Jim and Sheikh, Aziz (2021 ) Temporal trends and forecasting of COVID-19 hospitalisations and deaths in Scotland using a national real-time patient-level data platform : a statistical modelling study. The Lancet Digital Health , 3 (8). e517-e525. ISSN 2589-7500
    • الرقم المعرف:
      10.1016/S2589-7500(21)00105-9
    • Rights:
      cc_by
    • الرقم المعرف:
      edsbas.BD694A44