Bluetongue (BT) is considered endemic in the southern states of India, with sporadic incidences reported from the northern, western and central parts of India. However, the eastern and north-eastern states of India have not experienced active disease so far. In the recent past, an extensive sero-epidemiological investigation was carried out in the eastern and north-eastern Indian states. With the aim of getting updated and refined estimates of positivity rates, the sero-surveillance data were analyzed using the Markov chain Monte Carlo (MCMC) method to calculate the positivity rates of various species across different states and agro-climatic zones. The posterior positivity distribution helped in accurately estimating the seroprevalence of bluetongue virus (BTV) among different species and regions. The MCMC method was applied for the first time in a BTV seroprevalence analysis that enhanced our understanding of infection dynamics, guided targeted interventions and supported better decision-making in bluetongue disease control, prevention and disease preparedness. This exercise is quite pertinent in the context of the recent upsurge of newer BTV strains, e.g., BTV-3 and BTV-8, in the western world. In short, as a powerful computational tool, MCMC could be used for accurate seroprevalence estimation, species-specific insights, regional analysis, enhanced decision-making and epidemiological insights for bluetongue.

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http://dx.doi.org/10.3390/v17010018DOI Listing

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