Multi-scale modeling and analysis of vaccine prevention and control strategies for Chikungunya disease

Abstract In response to the wait-and-see attitude arising from environmental uncertainty and the costs associated with prevention and control during the promotion of Chikungunya vaccine, this study evaluates the effectiveness of vaccine strategies using multi-scale dynamic models. First, a Chikungunya periodic model driven by temperature factors is established to quantify the synergistic effects of incomplete vaccination coverage and the seasonal activity of mosquitoes. It is found that neglecting the temperature factor will lead to an underestimation of the required vaccination rate. And a comprehensive measure combining vaccination and physical protection is proved to be more cost-effective than combined insecticide-based vaccination. Second, an autonomous model corresponding to the periodic model under average annual temperature is constructed. This model is analyzed to determine the threshold for vaccine coverage and the extinction conditions for Chikungunya disease, providing a rapid tool for resource assessment. Furthermore, time-varying control variables are introduced into the autonomous model, and the optimal strategy is obtained through theoretical analysis. The numerical results in the three different control scenarios indicate that when the proportion of high-risk groups is low, vaccination targeting only high-risk groups may fail, while dynamic vaccination adjustments can partially compensate for seasonal risks when using the annual average parameter.

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Publication Details

Journal
Advances in Continuous and Discrete Models
Published
2025-12-03
DOI
https://doi.org/10.1186/s13662-025-04034-3
Primary Topic
Mosquito-borne diseases and control
Type
article
Field-Weighted Citation Impact
0.00
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article

Multi-scale modeling and analysis of vaccine prevention and control strategies for Chikungunya disease

Yan Qian, Yan Wang, Lili Liu
Advances in Continuous and Discrete Models
Mosquito-borne diseases and control
article

Multi-scale modeling and analysis of vaccine prevention and control strategies for Chikungunya disease

Yan Qian, Yan Wang, Lili Liu
article en

Abstract

Abstract In response to the wait-and-see attitude arising from environmental uncertainty and the costs associated with prevention and control during the promotion of Chikungunya vaccine, this study evaluates the effectiveness of vaccine strategies using multi-scale dynamic models. First, a Chikungunya periodic model driven by temperature factors is established to quantify the synergistic effects of incomplete vaccination coverage and the seasonal activity of mosquitoes. It is found that neglecting the temperature factor will lead to an underestimation of the required vaccination rate. And a comprehensive measure combining vaccination and physical protection is proved to be more cost-effective than combined insecticide-based vaccination. Second, an autonomous model corresponding to the periodic model under average annual temperature is constructed. This model is analyzed to determine the threshold for vaccine coverage and the extinction conditions for Chikungunya disease, providing a rapid tool for resource assessment. Furthermore, time-varying control variables are introduced into the autonomous model, and the optimal strategy is obtained through theoretical analysis. The numerical results in the three different control scenarios indicate that when the proportion of high-risk groups is low, vaccination targeting only high-risk groups may fail, while dynamic vaccination adjustments can partially compensate for seasonal risks when using the annual average parameter.

Advances in Continuous and Discrete ModelsVol. 2026(1)
Chongqing Normal University (CN), Minzu University of China (CN), Shanxi University (CN), Minda Hospital (CN), Hubei University (CN)
Openalex Percentile: Top 51%
Mosquito-borne diseases and control
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Multi-scale modeling and analysis of vaccine prevention and control strategies for Chikungunya disease — Yan Qian, Yan Wang, et al. · Advances in Continuous and Discrete Models (2025) | TGRS Research Map | TGRS