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Comparing COVID-19 vaccine allocation strategies in India: A mathematical modelling study.
Int J Infect Dis. 2021 Feb; 103:431-438.IJ

Abstract

BACKGROUND

The development and widespread use of an effective SARS-CoV-2 vaccine could prevent substantial morbidity and mortality associated with COVID-19 and mitigate the secondary effects associated with non-pharmaceutical interventions.

METHODS

We used an age-structured, expanded SEIR model with social contact matrices to assess age-specific vaccine allocation strategies in India. We used state-specific age structures and disease transmission coefficients estimated from confirmed incident cases of COVID-19 between 1 July and 31 August 2020. Simulations were used to investigate the relative reduction in mortality and morbidity of vaccine allocation strategies based on prioritizing different age groups, and the interactions of these strategies with concurrent non-pharmaceutical interventions. Given the uncertainty associated with COVID-19 vaccine development, we varied vaccine characteristics in the modelling simulations.

RESULTS

Prioritizing COVID-19 vaccine allocation for older populations (i.e., >60 years) led to the greatest relative reduction in deaths, regardless of vaccine efficacy, control measures, rollout speed, or immunity dynamics. Preferential vaccination of this group often produced relatively higher total symptomatic infections and more pronounced estimates of peak incidence than other assessed strategies. Vaccine efficacy, immunity type, target coverage, and rollout speed significantly influenced overall strategy effectiveness, with the time taken to reach target coverage significantly affecting the relative mortality benefit comparative to no vaccination.

CONCLUSIONS

Our findings support global recommendations to prioritize COVID-19 vaccine allocation for older age groups. Relative differences between allocation strategies were reduced as the speed of vaccine rollout was increased. Optimal vaccine allocation strategies will depend on vaccine characteristics, strength of concurrent non-pharmaceutical interventions, and region-specific goals.

Authors+Show Affiliations

Systems Biology Department, Harvard Medical School, USA; Center for Systems Biology and Department of Pathology, Massachusetts General Hospital, USA.Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA; International Vaccine Access Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA; International Vaccine Access Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA; International Vaccine Access Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.Departments of Physics and Biology, Ashoka University, Sonepat, India; Theoretical Physics and Computational Biology, The Institute of Mathematical Sciences, Chennai, India.Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA; Division of Infectious Disease, St. John's Research Institute, Bengaluru, India. Electronic address: carl.britto@childrens.harvard.edu.

Pub Type(s)

Comparative Study
Journal Article

Language

eng

PubMed ID

33388436

Citation

Foy, Brody H., et al. "Comparing COVID-19 Vaccine Allocation Strategies in India: a Mathematical Modelling Study." International Journal of Infectious Diseases : IJID : Official Publication of the International Society for Infectious Diseases, vol. 103, 2021, pp. 431-438.
Foy BH, Wahl B, Mehta K, et al. Comparing COVID-19 vaccine allocation strategies in India: A mathematical modelling study. Int J Infect Dis. 2021;103:431-438.
Foy, B. H., Wahl, B., Mehta, K., Shet, A., Menon, G. I., & Britto, C. (2021). Comparing COVID-19 vaccine allocation strategies in India: A mathematical modelling study. International Journal of Infectious Diseases : IJID : Official Publication of the International Society for Infectious Diseases, 103, 431-438. https://doi.org/10.1016/j.ijid.2020.12.075
Foy BH, et al. Comparing COVID-19 Vaccine Allocation Strategies in India: a Mathematical Modelling Study. Int J Infect Dis. 2021;103:431-438. PubMed PMID: 33388436.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Comparing COVID-19 vaccine allocation strategies in India: A mathematical modelling study. AU - Foy,Brody H, AU - Wahl,Brian, AU - Mehta,Kayur, AU - Shet,Anita, AU - Menon,Gautam I, AU - Britto,Carl, Y1 - 2020/12/31/ PY - 2020/11/22/received PY - 2020/12/22/revised PY - 2020/12/26/accepted PY - 2021/1/4/pubmed PY - 2021/2/17/medline PY - 2021/1/3/entrez KW - COVID-19 KW - Immunization KW - Mathematical modelling KW - SEIR SP - 431 EP - 438 JF - International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases JO - Int J Infect Dis VL - 103 N2 - BACKGROUND: The development and widespread use of an effective SARS-CoV-2 vaccine could prevent substantial morbidity and mortality associated with COVID-19 and mitigate the secondary effects associated with non-pharmaceutical interventions. METHODS: We used an age-structured, expanded SEIR model with social contact matrices to assess age-specific vaccine allocation strategies in India. We used state-specific age structures and disease transmission coefficients estimated from confirmed incident cases of COVID-19 between 1 July and 31 August 2020. Simulations were used to investigate the relative reduction in mortality and morbidity of vaccine allocation strategies based on prioritizing different age groups, and the interactions of these strategies with concurrent non-pharmaceutical interventions. Given the uncertainty associated with COVID-19 vaccine development, we varied vaccine characteristics in the modelling simulations. RESULTS: Prioritizing COVID-19 vaccine allocation for older populations (i.e., >60 years) led to the greatest relative reduction in deaths, regardless of vaccine efficacy, control measures, rollout speed, or immunity dynamics. Preferential vaccination of this group often produced relatively higher total symptomatic infections and more pronounced estimates of peak incidence than other assessed strategies. Vaccine efficacy, immunity type, target coverage, and rollout speed significantly influenced overall strategy effectiveness, with the time taken to reach target coverage significantly affecting the relative mortality benefit comparative to no vaccination. CONCLUSIONS: Our findings support global recommendations to prioritize COVID-19 vaccine allocation for older age groups. Relative differences between allocation strategies were reduced as the speed of vaccine rollout was increased. Optimal vaccine allocation strategies will depend on vaccine characteristics, strength of concurrent non-pharmaceutical interventions, and region-specific goals. SN - 1878-3511 UR - https://www.unboundmedicine.com/medline/citation/33388436/Comparing_COVID_19_vaccine_allocation_strategies_in_India:_A_mathematical_modelling_study_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S1201-9712(20)32599-6 DB - PRIME DP - Unbound Medicine ER -