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Outbreak investigations of foot and mouth disease virus in Nepal between 2010 and 2015 in the context of historical serotype occurrence.

Ganesh AdhikariKrishna Prasad AcharyaMukul UpadhyayRabin RautKrishna KaphleTanka KhanalMiranda R BertramCarolina StenfeldtJonathan Arzt
Published in: Veterinary medicine and science (2018)
Foot and Mouth Disease (FMD) is endemic in Nepal and causes substantial economic losses in the livestock industry. The goal of this study was to perform an epidemiological analysis of FMD outbreaks reported to the Veterinary Epidemiology Center, Tripureshwor, Nepal during 2010-2015, in order to strengthen the National FMD Control Program. These current data were considered in the context of historical data on FMD virus (FMDV) serotypes detected in the country between 1965 and 2015. During 2010-2015, a total of 1333 livestock holdings reported FMD outbreaks in Nepal. On average, 71.2 animals were affected in each outbreak, with a case fatality rate of 3.6%. FMD was reported throughout the country, and the proportion of affected holdings was not significantly among eco-zones, regions, or species. The Hill eco-zone had the highest number of holdings affected (782), followed by Mountain (304), and Terai (247). When analysed by the developmental region, the Western (381) and Central (368) Developmental Regions had the highest numbers of holdings affected. Cattle were the most frequently affected species (39%), followed by buffalo (33%), and goats (19%). FMD occurred throughout the year, with peaks in winter (December/January) and in the pre-monsoon period (April/May). Between 1965 and 2015 FMDV serotype O had the highest prevalence (81%), followed by Asia-1 (11%), A (6%), and C (2%). Serotype C was not detected after 1996, and only serotype O was reported after 2011. These descriptive analyses provide critical landmarks to establish baselines, and document early progress of the ongoing Progressive Control Pathway of FMD (PCP-FMD) which could be useful in Nepal and other South Asian nations.
Keyphrases
  • dengue virus
  • tertiary care
  • klebsiella pneumoniae
  • multiple sclerosis
  • risk factors
  • disease virus
  • electronic health record
  • machine learning
  • big data
  • escherichia coli
  • cross sectional
  • multidrug resistant