Planning and adjusting the COVID-19 booster vaccination campaign to reduce disease burden

As public health policies shifted in 2023 from emergency response to long-term COVID-19 disease management, immunization programs started to face the challenge of formulating routine booster campaigns in a still highly uncertain seasonal behavior of the COVID-19 epidemic. Mathematical models assessing past booster campaigns and integrating knowledge on waning of immunity can help better inform current and future vaccination programs. Focusing on the first booster campaign in the 2021/2022 winter in France, we used a multi-strain age-stratified transmission model to assess the effectiveness of the observed booster vaccination in controlling the succession of Delta, Omicron BA.1 and BA.2 waves. We explored counterfactual scenarios altering the eligibility criteria and inter-dose delay. Our study showed that the success of the immunization program in curtailing the Omicron BA.1 and BA.2 waves was largely dependent on the inclusion of adults among the eligible groups, and was highly sensitive to the inter-dose delay, which was changed over time. Shortening or prolonging this delay, even by only one month, would have required substantial social distancing interventions to curtail the hospitalization peak. Also, the time window for adjusting the delay was very short. Our findings highlight the importance of readiness and adaptation in the formulation of routine booster campaign in the current level of epidemiological uncertainty.

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Publication Details

Journal
Infectious Disease Modelling
Published
2024-09-12
DOI
https://doi.org/10.1016/j.idm.2024.09.002
Citations
2
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.79

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article

Planning and adjusting the COVID-19 booster vaccination campaign to reduce disease burden

Yair Goldberg, Vittoria Colizza, Laura Di Domenico
2 citations
Infectious Disease Modelling
COVID-19 epidemiological studies
0.79
article

Planning and adjusting the COVID-19 booster vaccination campaign to reduce disease burden

Yair Goldberg, Vittoria Colizza, Laura Di Domenico
article en
2 citations

Abstract

As public health policies shifted in 2023 from emergency response to long-term COVID-19 disease management, immunization programs started to face the challenge of formulating routine booster campaigns in a still highly uncertain seasonal behavior of the COVID-19 epidemic. Mathematical models assessing past booster campaigns and integrating knowledge on waning of immunity can help better inform current and future vaccination programs. Focusing on the first booster campaign in the 2021/2022 winter in France, we used a multi-strain age-stratified transmission model to assess the effectiveness of the observed booster vaccination in controlling the succession of Delta, Omicron BA.1 and BA.2 waves. We explored counterfactual scenarios altering the eligibility criteria and inter-dose delay. Our study showed that the success of the immunization program in curtailing the Omicron BA.1 and BA.2 waves was largely dependent on the inclusion of adults among the eligible groups, and was highly sensitive to the inter-dose delay, which was changed over time. Shortening or prolonging this delay, even by only one month, would have required substantial social distancing interventions to curtail the hospitalization peak. Also, the time window for adjusting the delay was very short. Our findings highlight the importance of readiness and adaptation in the formulation of routine booster campaign in the current level of epidemiological uncertainty.

Infectious Disease ModellingVol. 10(1)
University of Bern (CH), Inserm (FR), Technion – Israel Institute of Technology (IL), Georgetown University (US), Sorbonne Université (FR), Institut Pierre Louis d‘Épidémiologie et de Santé Publique (FR), Institute of Social and Preventive Medicine (CH)
European Commission, Agence Nationale de la Recherche, Agence Nationale de Recherches sur le Sida et les Hépatites Virales, Horizon 2020 Framework Programme, HORIZON EUROPE Framework Programme, Horizon 2020
Openalex Percentile: Top 30%
COVID-19 epidemiological studies
0.79
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