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Porcine epidemic diarrhea virus (PEDV) emerged in the United States (U.S.) swine population in 2013, initiating an initial significant epidemic followed by a state of endemicity in the U.S. Despite continued monitoring, the epidemiology of PEDV during its endemic phase remains inadequately researched. Our study aimed to characterize the spatial-temporal distribution of postepidemic PEDV cases in the U.S. breeding herd and identify associated risk factors. Data from 1089 breeding farms in 27 states, reported to the Morrison Swine Health Monitoring Project from July 2014 to June 2021, were analyzed. We stratified the data into six U.S. regions and employed SaTScan for spatiotemporal permutation and cluster analysis. Survival analysis was used to assess risk factors. A notable seasonal clustering of PEDV cases was observed in winter (January-March; p=0.001, relative risk = 2.2) with regional variation. Ten high-rate spatial-temporal clusters (p < 0.05) were identified ranging from 2.5 to 833.7 km2 and lasting 1-5 months, occurring in four regions between 2015 and 2021. For the study period, a total of 625 cases of PEDV were recorded on 372 farms. The total number of PEDV cases decreased from 95 breeding farms in 32 counties (2014-2015) to 53 farms in 28 counties (2020-2021), indicating an overall reduction in occurrence and spatial extent. Feed mitigants demonstrated a protective effect, significantly reducing the risk of PEDV occurrence (hazard ratio = 0.3, p=0.003), while air filtration systems exhibited marginal benefits (hazard ratio = 0.3, p=0.06). Other important risk factors included county farm density with farms in high-density regions (>31 farms/100 km2) being 1.3 times more likely to experience outbreaks than in medium-density regions (13-31 farms/1000 km2; p < 0.001). Additionally, farms in region E had higher odds of outbreaks compared to region B. The overall decline in PEDV cases and reduced spatial extent reflect industry efforts in postepidemic control and elimination. The protective effects of feed mitigants warrant further investigation. Our findings underscore the opportunity for coordinated efforts to eliminate PEDV in the U.S. and emphasize the need for comprehensive risk profiling associated with industry practices.
Pubmed ID: 40303073
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NIH genetic sequence database that provides annotated collection of all publicly available DNA sequences for almost 280 000 formally described species (Jan 2014) .These sequences are obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole-genome shotgun (WGS) and environmental sampling projects. Most submissions are made using web-based BankIt or standalone Sequin programs, and GenBank staff assigns accession numbers upon data receipt. It is part of International Nucleotide Sequence Database Collaboration and daily data exchange with European Nucleotide Archive (ENA) and DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. GenBank is accessible through NCBI Entrez retrieval system, which integrates data from major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of GenBank database are available by FTP.
View all literature mentionsSoftware package as multiple alignment program for amino acid or nucleotide sequences. Can align up to 500 sequences or maximum file size of 1 MB. First version of MAFFT used algorithm based on progressive alignment, in which sequences were clustered with help of Fast Fourier Transform. Subsequent versions have added other algorithms and modes of operation, including options for faster alignment of large numbers of sequences, higher accuracy alignments, alignment of non-coding RNA sequences, and addition of new sequences to existing alignments.
View all literature mentionsSoftware application with data analysis tools and spreadsheet templates to track and visualize data. It is used to manage and process data.
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