Integrating epidemiological and economic dynamics to assess Rift Valley fever vaccination strategies: A system dynamics model from Kenya

Sirak Bahta, Francis Wanyoike, Bernard Bett and Karl M Rich

PLOS Complex Systems, 2026, vol. 3, issue 6, 1-25

Abstract: Livestock diseases such as Rift Valley Fever (RVF) present systemic threats to animal health, rural livelihoods, and national economies in endemic regions. However, conventional impact assessments often fail to capture the nonlinear feedbacks, time lags, and cross-sectoral interactions involved. This study develops a dynamic, multi-component system dynamics (SD) model to simulate the Epidemiological and Economic impacts of RVF outbreaks in Ijara County, Kenya, under alternative vaccination strategies. The model integrates biologically detailed Susceptible Exposed Infectious (SEI) dynamics for Aedes and Culex mosquito vectors, Susceptible Exposed Infectious Recovered (SEIR) livestock infection dynamics, herd demography, and end-market processes, incorporating demand-side shocks and behavioral feedback. Using a 10-year simulation with a daily time-step, parameterized with primary and secondary data, including El Niño associated rainfall patterns and producer survey results, the model reproduces key outbreak features consistent with historical RVF events and enables ex-ante comparison of policy responses. Findings indicate that the business-as-usual (BAU) strategy, involving delayed reactionary vaccination, yields only marginal improvements in herd recovery and producer income relative to no intervention. In contrast, annual preventive vaccination with sufficient coverage of susceptible animals prevents simulated outbreaks within the model horizon, while biannual and triennial strategies reduce outbreak severity but do not fully eliminate risk. Shortening the delay between outbreak onset and vaccination initiation substantially reduces livestock losses and improves income recovery trajectories. These results highlight the value of system dynamics modeling for evaluating intervention strategies under uncertainty. The model offers a decision-support tool for livestock health policy, demonstrating that proactive vaccination and rapid response outperform delayed, reactive approaches in both disease control and economic resilience in RVF-prone pastoral systems.Author summary: Rift Valley fever (RVF) is a mosquito-borne disease that causes substantial losses to livestock producers in East Africa and poses risks to human health. While vaccination is an effective control measure, its economic benefits depend critically on timing, coverage, and implementation strategy. In this study, we develop a system dynamics model that integrates RVF transmission, cattle herd demography, livestock markets, and producer income to assess the impacts of alternative vaccination strategies in Ijara County, Kenya, a region with recurrent RVF outbreaks. Using simulated outbreak scenarios, we compare BAU reactive vaccination, regular preventive vaccination programs, and improved response timing. The results show that delayed, reactive vaccination yields limited economic benefits, whereas preventive vaccination and rapid response substantially reduce livestock losses, stabilize incomes, and shorten recovery periods. By explicitly linking disease dynamics and economic outcomes, the model provides a decision-support tool for evaluating RVF control strategies and highlights the importance of proactive vaccination in enhancing livestock-based livelihoods in RVF-prone pastoral systems.

Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/complexsystems/article?id=10.1371/journal.pcsy.0000101 (text/html)
https://journals.plos.org/complexsystems/article/f ... 00101&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pcsy00:0000101

DOI: 10.1371/journal.pcsy.0000101

Access Statistics for this article

More articles in PLOS Complex Systems from Public Library of Science
Bibliographic data for series maintained by complexsystem ().