Model-Based Analysis of Gumboro Disease Transmission and the Impact of Prevention Strategies

Tariku Merga Tolasa, Aychew Wondyfraw Tesfaye, Tesfaye Sama Satana and Yehualashet Bayu

Abstract and Applied Analysis, 2026, vol. 2026, 1-18

Abstract: Infectious bursal disease virus (IBDV) is a cause of Gumboro disease and transmitted through environmental contamination, mainly via the fecal-oral route. The Gumboro disease is associated with significant economic challenges. Thus, predicting its transmission dynamics is of paramount importance to understand its spread and design effective control measures to avoid economic losses in poultry industries. This study presents a comprehensive approach to modeling the spread of Gumboro disease among chickens. A clear model using ordinary differential equations (ODEs) divides the chicken population into susceptible (S(t)), vaccinated (V(t)), protected (P(t)), infected (I(t)), temporarily recovered (R(t)), and environmental virus load (G(t)) categories, allowing a detailed analysis of disease dynamics. This structure helps identify the impact of each group on the overall spread of the virus. The model’s qualitative analysis was checked, and it was verified that the developed model is positively bounded in the invariant region. Using the next-generation matrix method, we calculated the average number of secondary (basic reproductive number, R0) Gumboro infections caused by a single infected chicken. Our finding reveals that a single infected chicken can transmit the virus to an average of 2.57 other chickens that is greatly influenced by environmental factors. This highlights the high contagiousness of Gumboro disease in chicken populations. The disease-free equilibrium is stable when the secondary infections are less than one, while the endemic equilibrium is stable when it exceeds one. This provides valuable insight into the conditions under which the disease could be controlled or could persist. Numerical simulations were conducted to visualize the impact of different control measures and are illustrated graphically using MATLAB. Based on the findings, increasing vaccination coverage is predicted to reduce IBDV transmission under modeled vaccination scenarios, though outcomes may differ in field conditions due to vaccine efficacy, viral strain diversity, and maternally derived antibodies (MDAs). In addition, improvements of environmental sanitation is significant. Future work could extend the model by explicitly incorporating MDA dynamics and accounting for partial vaccine effectiveness against diverse IBDV strains, thereby enabling evaluation of optimal coverage levels and cost-effectiveness of control strategies.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlaaa:8086895

DOI: 10.1155/aaa/8086895

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