Foot-and-mouth disease (FMD) is a severe contagious viral disease of cloven-hoofed animals. In India, a vaccination-based official FMD control programme was started, which got expanded progressively to cover entire country in 2019. The serological tests are used to determine non-structural protein based sero-prevalence rates for properly implementing and assessing the control programme. Since 2008, reporting of the FMD sero-surveillance was limited to the serum sample-based serological test results without going for population-level estimation due to lack of proper statistical methodology. Thus, we present a computational approach for estimating the sero-prevalence rates at the state and national levels. Based on the reported approach, a web-application ( https://nifmd-bbf.icar.gov.in/FMDSeroSurv ) and an R software package ( https://github.com/sam-dfmd/FMDSeroSurv ) have been developed. The presented computational techniques are applied to the FMD sero-surveillance data during 2008–2021 to get the status of virus circulation in India under a strict vaccination policy. Furthermore, through various structural equation models, we attempt to establish a link between India’s estimated sero-prevalence rate and field FMD outbreaks. Our results indicate that the current sero-prevalence rates are significantly associated with previous field outbreaks up to 2 years. Besides, we observe downward trends in sero-prevalence and outbreaks over the years, specifically after 2013, which indicate the effectiveness of various measures implemented under the FMD control programme. The findings of the study may help researchers and policymakers to track virus infection and identification of potential disease-free zones through vaccination.
【저자키워드】 viral infection, Infectious diseases, Computer science, Statistics, Software, Computational science,