Impact of mass vaccination on the spatiotemporal dynamics of FMD outbreaks in India, 2008–2016

Umanga Gunasekera, Jitendra Kumar Biswal, Gustavo Machado, Rajeev Ranjan, Saravanan Subramaniam, Manoranjan Rout, Jajati Keshari Mohapatra, Bramhadev Pattnaik, Rabindra Prasad Singh, Jonathan Arzt, Andres M Perez, Kimberly VanderWaal

Research output: Contribution to journalArticlepeer-review

Abstract

Foot-and-mouth disease (FMD) is endemic in India, where circulation of serotypes O, A and Asia1 is frequent. Here, we provide an epidemiological assessment of the ongoing mass vaccination programs in regard to post-vaccination monitoring and outbreak occurrence. The objective of this study was assessing the contribution of mass vaccination campaigns in reducing the risk of FMD in India from 2008 to 2016 by evaluating sero-monitoring data and modelling the spatiotemporal dynamics of reported outbreaks. Through analyzing antibody titre data from >1 million animals sampled as part of pre- and post-vaccination monitoring, we show that the percent of animals with inferred immunological protection (based on ELISA) was highly variable across states but generally increased through time. In addition, the number of outbreaks in a state was negatively correlated with the percent of animals with inferred protection. We then analyzed the distribution of reported FMD outbreaks across states using a Bayesian space–time model. This approach provides better acuity to disentangle the effect of mass vaccination programs on outbreak occurrence, while accounting for other factors that contribute to spatiotemporal variability in outbreak counts, notably proximity to international borders and inherent spatiotemporal correlations in incidence. This model demonstrated a ∼50% reduction in the risk of outbreaks in states that were part of the vaccination program. In addition, after controlling for spatial autocorrelation in the data, states that had international borders experienced heightened risk of FMD outbreaks. These findings help inform risk-based control strategies for India as the country progresses towards reducing reported clinical disease.

Original languageEnglish (US)
JournalTransboundary and Emerging Diseases
DOIs
StateAccepted/In press - 2022

Bibliographical note

Funding Information:
Support for this work was provided by the Indian Council of Agricultural Research, New Delhi. This work was funded by the United States Department of Agriculture (USDA) Agricultural Research Service (ARS) Project 1940‐32000‐061‐00D, the United States Department of State, Biosecurity Engagement Program through the USDA‐ARS Office of International Research Program and a specific collaborative agreement between USDA‐ARS and University of Minnesota. The authors are thankful to DAHD, Government of India for the support and AICRP on FMD Centers for providing the serum samples for analyses.

Publisher Copyright:
© 2022 The Authors. Transboundary and Emerging Diseases published by Wiley-VCH GmbH.

Keywords

  • Bayesian regression
  • endemic setting
  • mass vaccination
  • risk analysis
  • transboundary

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