Assessing COVID-19 vaccination strategies in varied demographics using an individual-based model

Abstract

Background: New variants of SARS-CoV-are constantly discovered. Administration of COVID-vaccines and booster doses, combined with the application of non-pharmaceutical interventions (NPIs), is often used to prevent outbreaks of emerging variants. Such outbreak dynamics are further complicated by the population's behavior and demographic composition. Hence, realistic simulations are needed to estimate the e ciency of proposed vaccination strategies in conjunction with NPIs. Methods:We developed an individual-based model of COVID-dynamics that considers age-dependent parameters such as contact matrices, probabilities of symptomatic and severe disease, and households' age distribution. As a case study, we simulate outbreak dynamics under the demographic compositions of two Israeli cities with di erent household sizes and age distributions. We compare two vaccination strategies: vaccinate individuals in a currently prioritized age group, or dynamically prioritize neighborhoods with a high estimated reproductive number. Total infections and hospitalizations are used to compare the e ciency of the vaccination strategies under the two demographic structures, in conjunction with di erent NPIs. Results:We demonstrate the e ectiveness of vaccination strategies targeting highly infected localities and of NPIs actively detecting asymptomatic infections. We further show that di erent optimal vaccination strategies exist for each sub-population's demographic composition and that their application is superior to a uniformly applied strategy. Conclusion:Our study emphasizes the importance of tailoring vaccination strategies to subpopulations' infection rates and to the unique characteristics of their demographics (e.g., household size and age distributions). The presented simulation framework and findings can help better design future responses against the following emerging variants.

Learning from the COVID-19 pandemic: a systematic review of mathematical vaccine prioritization models

“…In Ben-Zuk et al (2022), an ABM was used to derive and compare optimal vaccine allocation strategies for two Israeli cities of similar size but with different household size and age distributions. The authors compared two strategies: vaccinate those prioritized by public health decision makers, or dynamically prioritize neighborhoods with a high estimated reproductive number.…”

Learning from the COVID-19 pandemic: A systematic review of mathematical vaccine prioritization models

“…The models are further classified by framework, type of vaccine roll-out (as specified in 4.4), as well as considered vaccine functions. ( Althobaity et al., 2022 ; Angelov et al., 2023 ; Anupong et al., 2023 ; Aruffo et al., 2022 ; Ayoub et al., 2021 ; Ben-Zuk et al., 2022 ; Bubar et al., 2021 ; Buckner et al., 2021 ; Bushaj et al., 2023 ; Campos et al., 2021 ; Cartocci et al., 2021 ; Cattaneo et al., 2022 ; Chen et al., 2021 ; Childs et al., 2022 ; Choi et al., 2021 ; Choi and Shim, 2021 ; Conway et al., 2023 ; Ferranna et al., 2021 ; Ferreira et al., 2022 ; Foy et al., 2021 ; Gavish and Katriel, 2022 ; González-Parra et al., 2022 ; Gozzi et al., 2021 ; Gozzi et al., 2022 ; Grundel et al., 2021 ; Han et al., 2021 ; Hogan et al., 2021 ; Hong et al., 2022 ; Hupert et al., 2022 ; Islam et al., 2021 ; Jahn et al., 2021 ; Jentsch et al., 2021 ; Kadelka and McCombs, 2021 ; Kadelka et al., 2022 ; Karabay et al., 2021 ; Kekić et al., 2023 ; Kiem et al., 2021 ; Li et al., 2021 , 2022 ; Liu et al., 2021 , 2022a , 2022b ; Luangasanatip et al., 2023 ; Luebben et al., 2023 ; Luo et al., 2022 ; MacIntyre et al., 2022 ; Makhoul et al., 2020 ; Mandal et al., 2021 ; …”

COVID-19 reinfections in Mexico City: implications for public health

“…However, the interpretation and application of all findings are complicated since virus variants have diverged over time and geographic location, vaccine distribution per vaccine type has been uneven around the globe, local vaccine administration strategies have sometimes been focused on specific population sectors, and vaccine efficiency per type is different. Besides, reports do not always categorize reinfection rate per vaccination status ( 8 – 10 ).…”