Utilizing direct and indirect information to improve the COVID-19 vaccination booster scheduling

Yotam Dery, Matan Yechezkel, Irad Ben-Gal, Dan Yamin*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Current global COVID-19 booster scheduling strategies mainly focus on vaccinating high-risk populations at predetermined intervals. However, these strategies overlook key data: the direct insights into individual immunity levels from active serological testing and the indirect information available either through sample-based sero-surveillance, or vital demographic, location, and epidemiological factors. Our research, employing an age-, risk-, and region-structured mathematical model of disease transmission—based on COVID-19 incidence and vaccination data from Israel between 15 May 2020 and 25 October 2021—reveals that a more comprehensive strategy integrating these elements can significantly reduce COVID-19 hospitalizations without increasing existing booster coverage. Notably, the effective use of indirect information alone can considerably decrease COVID-19 cases and hospitalizations, without the need for additional vaccine doses. This approach may also be applicable in optimizing vaccination strategies for other infectious diseases, including influenza.

Original languageEnglish
Article number8089
JournalScientific Reports
Issue number1
StatePublished - Dec 2024


FundersFunder number
European Research Council949850


    • COVID-19
    • SEIR model
    • Transmission model
    • Vaccination
    • Value of information


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