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Optimising the impact of COVID-19 vaccination on mortality and hospitalisations using an individual additive risk measuring approach based on a risk adjustment scheme

Author

Listed:
  • Danny Wende

    (Bifg Institute of BARMER
    TU Dresden c/o Chair of Econometrics)

  • Dagmar Hertle

    (Bifg Institute of BARMER)

  • Claudia Schulte

    (Bifg Institute of BARMER)

  • Pedro Ballesteros

    (Bifg Institute of BARMER)

  • Uwe Repschläger

    (Bifg Institute of BARMER)

Abstract

In this population-based cohort study, billing data from German statutory health insurance (BARMER, 10% of population) are used to develop a prioritisation model for COVID-19 vaccinations based on cumulative underlying conditions. Using a morbidity-based classification system, prevalence and risks for COVID-19-related hospitalisations, ventilations and deaths are estimated. Trisomies, behavioural and developmental disorders (relative risk: 2.09), dementia and organic psychoorganic syndromes (POS) (2.23) and (metastasised) malignant neoplasms (1.99) were identified as the most important conditions for escalations of COVID-19 infection. Moreover, optimal vaccination priority schedules for participants are established on the basis of individual cumulative escalation risk and are compared to the prioritisation scheme chosen by the German Government. We estimate how many people would have already received a vaccination prior to escalation. Vaccination schedules based on individual cumulative risk are shown to be 85% faster than random schedules in preventing deaths, and as much as 57% faster than the German approach, which was based primarily on age and specific diseases. In terms of hospitalisation avoidance, the individual cumulative risk approach was 51% and 28% faster. On this basis, it is concluded that using individual cumulative risk-based vaccination schedules, healthcare systems can be relieved and escalations more optimally avoided.

Suggested Citation

  • Danny Wende & Dagmar Hertle & Claudia Schulte & Pedro Ballesteros & Uwe Repschläger, 2022. "Optimising the impact of COVID-19 vaccination on mortality and hospitalisations using an individual additive risk measuring approach based on a risk adjustment scheme," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(6), pages 969-978, August.
    • Handle: RePEc:spr:eujhec:v:23:y:2022:i:6:d:10.1007_s10198-021-01408-8
    DOI: 10.1007/s10198-021-01408-8
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    References listed on IDEAS

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    1. Bruce Mellado & Jianhong Wu & Jude Dzevela Kong & Nicola Luigi Bragazzi & Ali Asgary & Mary Kawonga & Nalamotse Choma & Kentaro Hayasi & Benjamin Lieberman & Thuso Mathaha & Mduduzi Mbada & Xifeng Rua, 2021. "Leveraging Artificial Intelligence and Big Data to Optimize COVID-19 Clinical Public Health and Vaccination Roll-Out Strategies in Africa," IJERPH, MDPI, vol. 18(15), pages 1-7, July.
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    More about this item

    Keywords

    COVID-19; Vaccination prioritisation; Immunization strategy; Severe outcomes; Risk adjustment scheme; Additive risk measuring;
    All these keywords.

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • H84 - Public Economics - - Miscellaneous Issues - - - Disaster Aid
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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