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- Author or Editor: Ariel L. Rivas x
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Abstract
Objective—To evaluate the influence of individual spatial units (ie, counties) on the epidemic spread of foot-and-mouth disease (FMD) virus.
Sample Population—163 counties in Uruguay where there was an outbreak of FMD between April 23 and July 11, 2001.
Procedure—A geographically referenced database was created, and the distance between counties (13,203 county pairs), road density of counties (163 counties), and time when cases were reported in those counties (11 weeks of the epidemic) were considered to assess global spatial and spatial-temporal autocorrelation, determine the contribution of links connecting pairs of counties with infected animals, and allow us to hypothesize the influence for spread during the epidemic for counties with greater than the mean infective link contributions.
Results—Case clusters were indicated by the Moran Iand Mantel tests during the first 6 weeks of the epidemic. Spatial lags between pairs of counties with infected animals revealed case clustering before and after vaccination was implemented. Temporal lags predicted autocorrelation for up to 3 weeks. Link indices identified counties expected to facilitate epidemic spread. If control measures had been implemented in counties with a high index link (identifiable as early as week 1 of the epidemic), they could have prevented (by week 11 of the epidemic) at least 2.5 times as many cases per square kilometer than the same measures implemented in counties with average link indices.
Conclusions and Clinical Relevance—Analysis of spatial autocorrelation and infective link indices may identify network conditions that facilitate (or prevent) disease spread.
Abstract
Objective—To explore whether early analysis of spatial data may result in identification of variables associated with epidemic spread of foot and mouth disease.
Sample Population—37 farms with infected cattle (ie, case farms) reported within the first 6 days of the 2001 Uruguayan foot-and-mouth disease epidemic.
Procedure—A georeferenced database was created and retrospective analysis was performed on case farm location in relation to farm density, cattle density, farm type (ie, beef vs dairy cattle production), road density, case farm distance to the nearest road, farm size, farm ownership, and day of infection. Mean or median results of 1 to 3 day versus 4 to 6 day spatial data were compared. Spatial-temporal associations were investigated by correlation analysis.
Results—Comparison of mean or median values between the first 3 days and days 4 to 6 of the epidemic and results of correlation analysis indicated a significant increase in road density, cattle density, and dairy cattle production and a significant decrease in farm size and case farm distance to the nearest road that developed over time. A route that linked most case farms by the shortest possible distance and also considered significantly associated variables was created. It included 86.1% of all case farms reported by 60 days into the epidemic.
Conclusions and Clinical Relevance—Epidemic direction can be assessed on the basis of road density and other spatial variables as early as 6 days into an epidemic. Epidemic control areas may be more effectively identified if local and regional georeferenced data are considered. (Am J Vet Res 2003;64:1519–1527)
Abstract
Objectives—To assess automated ribotyping for characterization of Pseudomonas aeruginosa isolates and to identify their type prevalence and geographic distribution.
Sample Population—39 human and 56 ruminant P aeruginosa isolates.
Procedures—Isolates were identified by use of bacteriologic techniques and automated PvuII-based ribotyping. Susceptibility to antimicrobials was tested in vitro. Data were analyzed for index of discrimination; prevalence ratio; geographic distribution of ribotypes found only in humans, only in cows, or only in goats (single-host ribotypes); and geographic distribution of ribotypes found in humans and ruminants (multihost ribotypes).
Results—All isolates were typeable (45 ribotypes, 35 single-host ribotypes). Ribotyping index of discrimination was 0.976. More isolates (45.3%) than expected yielded multihost ribotypes (22% of all ribotypes). Although 8.6% of single-host ribotypes were found in 4 or more isolates, 60% of multihost ribotypes were found in 4 or more isolates. Ninety percent of multihost ribotypes were isolated from different geographic areas, whereas 3.0% of singlehost ribotypes were isolated from different geographic areas. All ruminant isolates were susceptible to gentamicin and polymyxin B. In contrast, antibiogram profiles differed for human isolates from different geographic areas. Susceptibility to antimicrobials differentiated 6 isolates not distinguished by ribotyping.
Conclusions and Clinical Relevance—Automated ribotyping with PvuII discriminated more isolates than in vitro antimicrobial susceptibility. In combination, both tests provided more information than either test alone. Given the greater prevalence and geographic distribution of multihost ribotypes, immunocompromised humans and lactating ruminants may have a greater risk for disease if exposed to multihost P aeruginosa ribotypes, compared with single-host ribotypes. (Am J Vet Res 2001;62:864–870)
Abstract
Objectives—To differentiate early (1 to 8 days) from late (9 to 14 days) inflammatory phases and assess relationships between leukocyte phenotype and bacterial recovery in cows with Staphylococcus aureus-induced mastitis.
Animals—10 first-lactation Holstein cows.
Procedure—Blood and milk samples were collected from 4 or 6 cows before and after intramammary infusion of sterile broth or S aureus, respectively. Flow cytometric expression of CD3 and CD11b antigens on blood and milk leukocytes, leukocyte differential counts, bacterial counts in milk, and somatic cell counts were determined longitudinally.
Results—Density of CD3 molecules decreased on blood lymphocytes and increased on milk lymphocytes after infusion of bacteria. Density of CD11b molecules on lymphocytes and phagocytes and percentage of CD11b+ lymphocytes in milk increased significantly after infusion; maximum values were achieved during the early inflammatory phase. Density of CD3 and CD11b molecules on milk lymphocytes and macrophages, respectively, 1 day after inoculation were negatively correlated with bacterial recovery on day 1 and days 9 to 14, respectively. Density of CD11b molecules on milk macrophages and the ratios of phagocyte to lymphocyte percentages and polymorphonuclear cell to macrophage percentages in milk differentiated the early from the late inflammatory phase.
Conclusions and Clinical Relevance—Activation of bovine mammary gland macrophages and T cells in response to intramammary infusion of S aureus was associated with an inability to culture this bacterium from milk. Identification of specific inflammatory phases of S aureus-induced mastitis in cows may allow for the design of more efficacious treatment and control programs. (Am J Vet Res 2001;62:1840–1851)
Abstract
Objectives
To develop a reference database for characterization of bovine Staphylococcus aureus and Streptococcus agalactiae strains by automated ribotyping and to use it to assess the discriminatory power of this typing procedure and the geographic distribution of Sta aureus and Str agalactiae strains in New York state dairy herds.
Sample Population
22 commercial dairy herds.
Procedure
Isolates of Sta aureus and Str agalactiae from bovine milk were identified by standard bacteriologic procedures, then typed by automated ribotyping. Antimicrobial susceptibility of isolates was tested in vitro. Two indicators made from the data were percentage of farms with multiple ribotypes and percentage of single ribotypes found in several geographic regions. Standard bacteriologic diagnosis, automated ribotyping, and determination of antibiograms (Kirby-Bauer method) also were done.
Results
Of 50 Sta aureus and 44 Str agalactiae isolates from composite milk samples of 12 and 10 herds, respectively, 18 and 14 ribotypes, respectively, were identified. The discriminatory power of automated ribotyping was approximately 0.96 (Hunter-Gaston's formula). A higher percentage of herds with Sta aureus had multiple ribotypes. The most common Sta aureus ribotypes tended to have broader geographic distribution. Some Sta aureus ribotypes were significantly associated with antibiotic resistance profiles.
Conclusions
Automated ribotyping appears to characterize bovine strains of bacteria associated with intramammary infections with a high discriminatory index. Potential applications include identification of strains that appear to have broad geographic distribution suggesting interfarm transfer, discrimination between recurrent versus new intramammary infections (ie, for control of Str agalactiae and Sta aureus), and evaluation of antibiotic therapy. (Am J Vet Res 1997;58:482–487)
