Literature DB >> 16460349

Human-mediated foot-and-mouth disease epidemic dispersal: disease and vector clusters.

A L Rivas1, B Kunsberg, G Chowell, S D Smith, J M Hyman, S J Schwager.   

Abstract

Disease clusters were retrospectively explored at national level using a geo-referenced dataset from the 2001 Uruguayan Foot-and-Mouth Disease (FMD) epidemic. Disease location and time (first 11 epidemic weeks) were analysed across 250 counties (of which 160 were infected), without and with control for human mobility related factors (human population and road densities). The null hypothesis of random disease distribution over space and/or time was assessed with: (i) purely temporal; (ii) purely spatial; and (iii) space/time tests. At least within epidemic weeks 2 and 6, a principal disease cluster was observed in 33 contiguous counties (P < 0.01). Two secondary clusters, located at >100 km from each other, were also observed (P < 0.01). The purely spatial test that controlled for human population density identified two non-contiguous clusters (P < 0.01). Space and time analysis also revealed the same 33 counties as members of the principal cluster, of which 31 were also clustered when human population was controlled (P < 0.01). No clusters were reported by the spatial test when road density was assessed. The hypothesis that human mobility related factors autocorrelate with disease was empirically supported by two pieces of information: (i) removal of human population/road densities eliminated >93.9% of the counties included in the principal disease cluster; and (ii) statistically significant correlations (P < 0.05) were observed in the first three epidemic weeks between road density and the number of cases. Clusters where human population density was associated with 47% greater number of cases/sq. km than that of the principal cluster indicated possible roles as disease vectors (vector clusters). Selective control policy in vector clusters is recommended. Periodic (i.e. weekly) cluster and correlation analyses of both disease and other covariates may facilitate disease surveillance and help design space-specific control policy.

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Year:  2006        PMID: 16460349     DOI: 10.1111/j.1439-0450.2006.00904.x

Source DB:  PubMed          Journal:  J Vet Med B Infect Dis Vet Public Health        ISSN: 0931-1793


  3 in total

1.  Disease properties, geography, and mitigation strategies in a simulation spread of rinderpest across the United States.

Authors:  Carrie Manore; Benjamin McMahon; Jeanne Fair; James M Hyman; Mac Brown; Montiago Labute
Journal:  Vet Res       Date:  2011-03-24       Impact factor: 3.683

2.  Forecasting the 2001 Foot-and-Mouth Disease Epidemic in the UK.

Authors:  David W Shanafelt; Glyn Jones; Mauricio Lima; Charles Perrings; Gerardo Chowell
Journal:  Ecohealth       Date:  2017-12-13       Impact factor: 3.184

3.  Proof of concept of a method that assesses the spread of microbial infections with spatially explicit and non-spatially explicit data.

Authors:  Ariel L Rivas; Kevin L Anderson; Roberta Lyman; Stephen D Smith; Steven J Schwager
Journal:  Int J Health Geogr       Date:  2008-11-18       Impact factor: 3.918

  3 in total

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