Parameterisation of a bluetongue virus mathematical model using a systematic literature review.

Prev Vet Med

The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry CV4 7AL, UK.

Published: November 2024

AI Article Synopsis

  • Bluetongue virus (BT) affects various livestock species worldwide, causing economic losses and health issues, with most existing epidemiological models based on the BTV-8 outbreak from 2006-2009.
  • The study aims to create a flexible model for predicting BT outbreaks globally and to identify key factors influencing outbreak dynamics for better policy planning.
  • A two-host, two-vector model was developed and analyzed using updated parameters from literature, showing that factors like the infectious period of sheep and cows most significantly affect outbreak length and peak infection levels.

Article Abstract

Bluetongue virus (BT) is a vector-borne virus that causes a disease, called bluetongue, which results in significant economic loss and morbidity in sheep, cattle, goats and wild ungulates across all continents of the world except Antarctica. Despite the geographical breadth of its impact, most BT epidemiological models are informed by parameters derived from the 2006-2009 BTV-8 European outbreak. The aim of this study was to develop a highly adaptable model for BT which could be used elsewhere in the world, as well as to identify the parameters which most influence outbreak dynamics, so that policy makers can be properly informed with the most current information to aid in disease planning. To provide a framework for future outbreak modelling and an updated parameterisation that reflects natural variation in infections, a newly developed and parameterised two-host, two-vector species ordinary differential equation model was formulated and analysed. The model was designed to be adaptable to be implemented in any region of the world and able to model both epidemic and endemic scenarios. It was parameterised using a systematic literature review of host-to-vector and vector-to-host transmission rates, host latent periods, host infectious periods, and vaccine protection factors. The model was demonstrated using the updated parameters, with South Africa as a setting based on the Western Cape's known cattle and sheep populations, local environmental parameters, and Culicoides spp. presence data. The sensitivity analysis identified that the duration of the infectious period for sheep and cows had the greatest impact on the outbreak length and number of animals infected at the peak of the outbreak. Transmission rates from cows and sheep to C. imicola midges greatly influenced the day on which the peak of the outbreak occurred, along with the duration of incubation period, and infectious period for cows. Finally, the protection factor of the vaccine had the greatest influence on the total number of animals infected. This knowledge could aid in the development of control measures. Due to gradual climate and anthropological change resulting in alterations in vector habitat suitability, BT outbreaks are likely to continue to increase in range and frequency. Therefore, this research provides an updated BT modelling framework for future outbreaks around the world to explore transmission, outbreak dynamics and control measures.

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http://dx.doi.org/10.1016/j.prevetmed.2024.106328DOI Listing

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