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Med J Aust ; 215(9): 427-432, 2021 11 01.
Article in English | MEDLINE | ID: covidwho-1389702

ABSTRACT

OBJECTIVES: To analyse the outcomes of COVID-19 vaccination by vaccine type, age group eligibility, vaccination strategy, and population coverage. DESIGN: Epidemiologic modelling to assess the final size of a COVID-19 epidemic in Australia, with vaccination program (Pfizer, AstraZeneca, mixed), vaccination strategy (vulnerable first, transmitters first, untargeted), age group eligibility threshold (5 or 15 years), population coverage, and pre-vaccination effective reproduction number ( R eff v ¯ ) for the SARS-CoV-2 Delta variant as factors. MAIN OUTCOME MEASURES: Numbers of SARS-CoV-2 infections; cumulative hospitalisations, deaths, and years of life lost. RESULTS: Assuming R eff v ¯ = 5, the current mixed vaccination program (vaccinating people aged 60 or more with the AstraZeneca vaccine and people under 60 with the Pfizer vaccine) will not achieve herd protection unless population vaccination coverage reaches 85% by lowering the vaccination eligibility age to 5 years. At R eff v ¯ = 3, the mixed program could achieve herd protection at 60-70% population coverage and without vaccinating 5-15-year-old children. At R eff v ¯ = 7, herd protection is unlikely to be achieved with currently available vaccines, but they would still reduce the number of COVID-19-related deaths by 85%. CONCLUSION: Vaccinating vulnerable people first is the optimal policy when population vaccination coverage is low, but vaccinating more socially active people becomes more important as the R eff v ¯ declines and vaccination coverage increases. Assuming the most plausible R eff v ¯ of 5, vaccinating more than 85% of the population, including children, would be needed to achieve herd protection. Even without herd protection, vaccines are highly effective in reducing the number of deaths.


Subject(s)
COVID-19 Vaccines/immunology , COVID-19/prevention & control , Immunity, Herd , Mass Vaccination/organization & administration , SARS-CoV-2/pathogenicity , Adolescent , Adult , Age Factors , Australia/epidemiology , COVID-19/epidemiology , COVID-19/immunology , COVID-19/virology , COVID-19 Vaccines/administration & dosage , Child , Child, Preschool , Computer Simulation , Humans , Immunogenicity, Vaccine , Mass Vaccination/statistics & numerical data , Middle Aged , Models, Immunological , SARS-CoV-2/genetics , SARS-CoV-2/immunology , Vaccination Coverage/organization & administration , Vaccination Coverage/statistics & numerical data , Young Adult
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