Posterior Positivity Distribution Analysis of Subclinical Bluetongue in the Eastern and North-Eastern States of India: A Wakeup Call for Outbreak Preparedness

Siddhartha Narayan Joardar ¹, Aritra Sanyal ², Ahmed Abd El Wahed ³

⁰Department of Veterinary Microbiology, Faculty of Veterinary and Animal Sciences, West Bengal University of Animal and Fishery Sciences, 37 Kshudiram Bose Sarani, P.O. Belgachia, Kolkata 700 037, West Bengal, India.

Viruses +

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January 25, 2025

View abstract on PubMed

Summary

Bluetongue virus (BTV) seroprevalence in India was analyzed using the Markov chain Monte Carlo (MCMC) method. This approach accurately estimated infection rates across regions and species, aiding disease control efforts.

Area Of Science

Veterinary Epidemiology
Infectious Disease Modeling
Computational Biology

Background

Bluetongue (BT) is endemic in southern India, with sporadic cases elsewhere, but historically absent in eastern and northeastern regions.
Recent extensive sero-epidemiological investigations were conducted in these previously unaffected eastern and northeastern Indian states.
Understanding bluetongue virus (BTV) seroprevalence is crucial for disease control and preparedness, especially with emerging strains globally.

Purpose Of The Study

To update and refine estimates of BTV positivity rates in eastern and northeastern India.
To apply the Markov chain Monte Carlo (MCMC) method for accurate seroprevalence estimation.
To enhance understanding of BTV infection dynamics and guide targeted interventions.

Main Methods

Analysis of sero-surveillance data from eastern and northeastern Indian states.
Application of the Markov chain Monte Carlo (MCMC) method for calculating positivity rates.
Utilizing posterior positivity distribution for precise seroprevalence estimation across species and agro-climatic zones.

Main Results

The MCMC method provided accurate seroprevalence estimates of BTV among various species and regions.
The study enhanced the understanding of BTV infection dynamics in previously understudied areas.
Posterior positivity distributions offered refined insights into regional and species-specific infection rates.

Conclusions

The Markov chain Monte Carlo (MCMC) method is a powerful tool for accurate BTV seroprevalence estimation.
This analysis provides crucial epidemiological insights for bluetongue disease control and prevention strategies in India.
The findings support enhanced decision-making for disease preparedness, particularly relevant given global BTV strain emergence.

Keywords:

ELISA bluetongue cattle goat north-eastern states sero-epidemiology sheep