Comparing COVID-19 vaccine allocation strategies in India: A mathematical modelling study
| Autor: | Carl Britto, Brody H. Foy, Brian Wahl, Kayur Mehta, Gautam I. Menon, Anita Shet |
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| Rok vydání: | 2021 |
| Předmět: |
Adult
0301 basic medicine Microbiology (medical) COVID-19 Vaccines Coronavirus disease 2019 (COVID-19) COVID-19 Immunization Mathematical modelling SEIR Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Population 030106 microbiology Psychological intervention India Article lcsh:Infectious and parasitic diseases Young Adult 03 medical and health sciences 0302 clinical medicine Immunity Environmental health Humans Medicine lcsh:RC109-216 030212 general & internal medicine Young adult education Aged education.field_of_study SARS-CoV-2 business.industry Mortality rate Social distance Incidence (epidemiology) Vaccination General Medicine Middle Aged Models Theoretical Vaccine efficacy Infectious Diseases Female business |
| Zdroj: | International journal of infectious diseases, 103:431-438 International Journal of Infectious Diseases International Journal of Infectious Diseases, Vol 103, Iss, Pp 431-438 (2021) |
| ISSN: | 1201-9712 |
| DOI: | 10.1016/j.ijid.2020.12.075 |
| Popis: | BackgroundThe development and widespread use of an effective SARS-CoV-2 vaccine could help prevent substantial morbidity and mortality associated with COVID-19 infection and mitigate many of the secondary effects associated with non-pharmaceutical interventions. The limited availability of an effective and licensed vaccine will task policymakers around the world, including in India, with decisions regarding optimal vaccine allocation strategies. Using mathematical modelling we aimed to assess the impact of different age-specific COVID-19 vaccine allocation strategies within India on SARS CoV-2-related mortality and infection.MethodsWe used an age-structured, expanded SEIR model with social contact matrices to assess different age-specific vaccine allocation strategies in India. We used state-specific age structures and disease transmission coefficients estimated from confirmed Indian incident cases of COVID-19 between 28 January and 31 August 2020. Simulations were used to investigate the relative reduction in mortality and morbidity of vaccinate allocation strategies based on prioritizing different age groups, and the interactions of these strategies with several concurrent non-pharmacologic interventions (i.e., social distancing, mandated masks, lockdowns). Given the uncertainty associated with current COVID-19 vaccine development, we also varied several vaccine characteristics (i.e., efficacy, type of immunity conferred, and rollout speed) in the modelling simulations.ResultsIn nearly all scenarios, prioritizing COVID-19 vaccine allocation for older populations (i.e., >60yrs old) led to the greatest relative reduction in deaths, regardless of vaccine efficacy, control measures, rollout speed, or immunity dynamics. However, preferential vaccination of this target group often produced higher total symptomatic infection counts and more pronounced estimates of peak incidence than strategies which targeted younger adults (i.e., 20-40yrs or 40-60yrs) or the general population irrespective of age. Vaccine efficacy, immunity type, target coverage and rollout speed all significantly influenced overall strategy effectiveness, with the time taken to reach target coverage significantly affecting the relative mortality benefit comparative to no vaccination.ConclusionsOur findings support global recommendations to prioritize COVID-19 vaccine allocation for older age groups. Including younger adults in the prioritisation group can reduce overall infection rates, although this benefit was countered by the larger mortality rates in older populations. Ultimately an optimal vaccine allocation strategy will depend on vaccine characteristics, strength of concurrent non-pharmaceutical interventions, and region-specific goals such as reducing mortality, morbidity, or peak incidence. |
| Databáze: | OpenAIRE |
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