A spatial vaccination strategy to reduce the risk of vaccine-resistant variants

Xiyun Zhang*, Gabriela Lobinska, Michal Feldman, Eddie Dekel, Martin A. Nowak, Yitzhak Pilpel, Yonatan Pauzner, Baruch Barzel, Ady Pauzner*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


The COVID-19 pandemic demonstrated that the process of global vaccination against a novel virus can be a prolonged one. Social distancing measures, that are initially adopted to control the pandemic, are gradually relaxed as vaccination progresses and population immunity increases. The result is a prolonged period of high disease prevalence combined with a fitness advantage for vaccine-resistant variants, which together lead to a considerably increased probability for vaccine escape. A spatial vaccination strategy is proposed that has the potential to dramatically reduce this risk. Rather than dispersing the vaccination effort evenly throughout a country, distinct geographic regions of the country are sequentially vaccinated, quickly bringing each to effective herd immunity. Regions with high vaccination rates will then have low infection rates and vice versa. Since people primarily interact within their own region, spatial vaccination reduces the number of encounters between infected individuals (the source of mutations) and vaccinated individuals (who facilitate the spread of vaccine-resistant strains). Thus, spatial vaccination may help mitigate the global risk of vaccine-resistant variants.

Original languageEnglish
Article numbere1010391
JournalPLoS Computational Biology
Issue number8
StatePublished - Aug 2022


FundersFunder number
National Natural Science Foundation of China12105117
Fundamental Research Funds for the Central Universities21621007
Basic and Applied Basic Research Foundation of Guangdong Province2022A1515010523


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