Assessing complexity and dynamics in epidemics: geographical barriers and facilitators of foot-and-mouth disease dissemination.

Introduction: Physical and non-physical processes that occur in nature may influence biological processes, such as dissemination of infectious diseases. However, such processes may be hard to detect when they are complex systems. Because complexity is a dynamic and non-linear interaction among numerous elements and structural levels in which specific effects are not necessarily linked to any one specific element, cause-effect connections are rarely or poorly observed. Methods: To test this hypothesis, the complex and dynamic properties of geo-biological data were explored with high-resolution epidemiological data collected in the 2001 Uruguayan foot-and-mouth disease (FMD) epizootic that mainly affected cattle. County-level data on cases, farm density, road density, river density, and the ratio of road (or river) length/county perimeter were analyzed with an open-ended procedure that identified geographical clustering in the first 11 epidemic weeks. Two questions were asked: (i) do geo-referenced epidemiologic data display complex properties? and (ii) can such properties facilitate or prevent disease dissemination? Results: Emergent patterns were detected when complex data structures were analyzed, which were not observed when variables were assessed individually. Complex properties-including data circularity-were demonstrated. The emergent patterns helped identify 11 counties as 'disseminators' or 'facilitators' (F) and 264 counties as 'barriers' (B) of epidemic spread. In the early epidemic phase, F and B counties differed in terms of road density and FMD case density. Focusing on non-biological, geographical data, a second analysis indicated that complex relationships may identify B-like counties even before epidemics occur. Discussion: Geographical barriers and/or promoters of disease dispersal may precede the introduction of emerging pathogens. If corroborated, the analysis of geo-referenced complexity may support anticipatory epidemiological policies.

Development of Disease-specific, Context-specific Surveillance Models: Avian Influenza (H5N1)-Related Risks and Behaviours in African Countries.

Avian influenza virus (H5N1) is a rapidly disseminating infection that affects poultry and, potentially, humans. Because the avian virus has already adapted to several mammalian species, decreasing the rate of avian-mammalian contacts is critical to diminish the chances of a total adaptation of H5N1 to humans. To prevent the pandemic such adaptation could facilitate, a biology-specific disease surveillance model is needed, which should also consider geographical and socio-cultural factors. Here, we conceptualized a surveillance model meant to capture H5N1-related biological and cultural aspects, which included food processing, trade and cooking-related practices, as well as incentives (or disincentives) for desirable behaviours. This proof of concept was tested with data collected from 378 Egyptian and Nigerian sites (local [backyard] producers/live bird markets/village abattoirs/commercial abattoirs and veterinary agencies). Findings revealed numerous opportunities for pathogens to disseminate, as well as lack of incentives to adopt preventive measures, and factors that promoted epidemic dissemination. Supporting such observations, the estimated risk for H5N1-related human mortality was higher than previously reported. The need for multidimensional disease surveillance models, which may detect risks at higher levels than models that only measure one factor or outcome, was supported. To develop efficient surveillance systems, interactions should be captured, which include but exceed biological factors. This low-cost and easily implementable model, if conducted over time, may identify focal instances where tailored policies may diminish both endemicity and the total adaptation of H5N1 to the human species.

Systems Biology and Ratio-Based, Real-Time Disease Surveillance.

Most infectious disease surveillance methods are not well fit for early detection. To address such limitation, here we evaluated a ratio- and Systems Biology-based method that does not require prior knowledge on the identity of an infective agent. Using a reference group of birds experimentally infected with West Nile virus (WNV) and a problem group of unknown health status (except that they were WNV-negative and displayed inflammation), both groups were followed over 22 days and tested with a system that analyses blood leucocyte ratios. To test the ability of the method to discriminate small data sets, both the reference group (n = 5) and the problem group (n = 4) were small. The questions of interest were as follows: (i) whether individuals presenting inflammation (disease-positive or D+) can be distinguished from non-inflamed (disease-negative or D-) birds, (ii) whether two or more D+ stages can be detected and (iii) whether sample size influences detection. Within the problem group, the ratio-based method distinguished the following: (i) three (one D- and two D+) data classes; (ii) two (early and late) inflammatory stages; (iii) fast versus regular or slow responders; and (iv) individuals that recovered from those that remained inflamed. Because ratios differed in larger magnitudes (up to 48 times larger) than percentages, it is suggested that data patterns are likely to be recognized when disease surveillance methods are designed to measure inflammation and utilize ratios.

CD2/CD21 index: a new marker to evaluate udder health in dairy cows.

Lymphocytes play a significant role in the immunological processes of the bovine mammary gland and were found to be the dominant cell population in the milk of healthy udder quarters. The objective of this study was to investigate the quantitative relationship between CD2(+) T and CD21(+) B lymphocytes using flow cytometry. In a first study, quarter foremilk samples from apparently healthy udder quarters [somatic cell counts (SCC) ≤100,000 cells/mL; n=65] were analyzed and compared with diseased quarters (SCC >100,000 cells/mL; n=15). Percentages of CD2(+) T cells were significantly higher in milk samples with SCC ≤100,000 cells/mL than in those with SCC >100,000 cells/mL, whereas percentages of CD21(+) B cells developed in the opposite direction. As a result of this opposing trend, a new variable, the CD2/CD21 index-representing the percentages of CD2(+) cells per CD21(+) cells-was defined. Although diseased quarters with SCC >100,000 cells/mL and the detection of major pathogens revealed generally CD2/CD21 indices <10, values >10 were observed in apparently healthy quarters. Hence, a CD2/CD21 index cutoff value of 10 may be suitable to aid differentiation between unsuspicious and microbiologically suspicious or diseased udder quarters. To test whether CD2/CD21 indices <10 were primarily related to pathogens, quarters with SCC ≤100,000 cells/mL and >100,000 cells/mL with different bacteriological status (culture negative, or minor or major pathogens) were selectively examined in a second biphasic study. In the first trial, 63 udder quarters were analyzed and 55 of these quarters were able to be sampled again in the second trial carried out 14 d later. In both trials, results of the first study were confirmed. Indeed, CD2/CD21 indices <10 were also found in quarters showing SCC ≤100,000 cells/mL and containing minor or major pathogens at the time of the current or previous bacteriological analysis. The results of our examinations indicated a clear relationship between the CD2/CD21 index and the bacteriological status of the mammary gland. In combination with SCC, it offers a new marker for quick differentiation of unsuspicious and microbiologically suspicious or diseased udder quarters.

Epidemic protection zones: centred on cases or based on connectivity?

When an exotic infectious disease invades a susceptible environment, protection zones are enforced. Historically, such zones have been shaped as circles of equal radius (ER), centred on the location of infected premises. Because the ER policy seems to assume that epidemic dissemination is driven by a similar number of secondary cases generated per primary case, it does not consider whether local features, such as connectivity, influence epidemic dispersal. Here we explored the efficacy of ER protection zones. By generating a geographically explicit scenario that mimicked an actual epidemic, we created protection zones of different geometry, comparing the cost-benefit estimates of ER protection zones to a set of alternatives, which considered a pre-existing connecting network (CN) - the road network. The hypothesis of similar number of cases per ER circle was not substantiated: the number of units at risk per circle differed up to four times among ER circles. Findings also showed that even a small area (of <115 km(2) ) revealed network properties. Because the CN policy required 20% less area to be protected than the ER policy, and the CN-based protection zone included a 23.8% greater density of units at risk/km(2) than the ER-based alternative, findings supported the view that protection zones are likely to be less costly and more effective if they consider connecting structures, such as road, railroad and/or river networks. The analysis of local geographical factors (contacts, vectors and connectivity) may optimize the efficacy of control measures against epidemics.

Lessons from Nigeria: the role of roads in the geo-temporal progression of avian influenza (H5N1) virus.

The daily progression of the 2006 (January-June) Nigerian avian influenza (AI H5N1) epidemic was assessed in relation to both spatial variables and the generation interval of the invading virus. Proximity to the highway network appeared to promote epidemic dispersal: from the first AI generation interval onwards > 20% of all cases were located at < 5 km from the nearest major road. Fifty-seven per cent of all cases were located 31 km from three highway intersections. Findings suggest that the spatial features of emerging infections could be key in their control. When the spatial location of a transmission factor is well known, such as that of the highway network, and a substantial percentage of cases (e.g. > 20%) are near that factor, early interventions focusing on transmission factors, such as road blocks that prevent poultry trade, may be more efficacious than interventions applied only to the susceptible population.

Spatial distribution of acaricide profiles (Boophilus microplus strains susceptible or resistant to acaricides) in southeastern Mexico.

The ability of Boophilus microplus strains to be susceptible (-) or resistant (+) to amidines (Am), synthetic pyrethroids (SP), and/or organo-phosphates (OP) (or acaricide profiles) was investigated in 217 southeastern Mexican cattle ranches (located in the states of Yucatán, Quintana Roo, and Tabasco). Three questions were asked: (1) whether acaricide profiles varied at random and, if not, which one(s) explained more (or less) cases than expected, (2) whether the spatial distribution of acaricide profiles was randomly or non-randomly distributed, and (3) whether acaricide profiles were associated with farm-related covariates (frequency of annual treatments, herd size, and farm size). Three acaricide profiles explained 73.6% of the data, representing at least twice as many cases as expected (P<0.001): (1) Am-SP-, (2) Am+SP+, and (3) (among ranches that dispensed acaricides > or = 6 times/year) Am-OP+SP+. Because ticks collected in Yucatán ranches tended to be susceptible to Am, those of Quintana Roo ranches displayed, predominantly, resistance to OP/SP, and Tabasco ticks tended to be resistant to Am (all with P < or = 0.05), acaricide profiles appeared to be non-randomly disseminated over space. Across states, two farm-related covariates were associated with resistance (P < or = 0.02): (1) high annual frequency of acaricide treatments, and (2) large farm size. Findings supported the hypothesis that spatial acaricide profiles followed neither random nor homogeneous data distributions, being partially explained by agent- and/or farm-specific factors. Some profiles could not be explained by these factors. Further spatially explicit studies (addressing host-related factors) are recommended.

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

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.

The role of spatial mixing in the spread of foot-and-mouth disease.

A model of epidemic dispersal (based on the assumption that susceptible cattle were homogeneously mixed over space, or non-spatial model) was compared to a partially spatially explicit and discrete model (the spatial model), which was composed of differential equations and used geo-coded data (Euclidean distances between county centroids). While the spatial model accounted for intra- and inter-county epidemic spread, the non-spatial model did not assess regional differences. A geo-coded dataset that resembled conditions favouring homogeneous mixing assumptions (based on the 2001 Uruguayan foot-and-mouth disease epidemic), was used for testing. Significant differences between models were observed in the average transmission rate between farms, both before and after a control policy (animal movement ban) was imposed. They also differed in terms of daily number of infected farms: the non-spatial model revealed a single epidemic peak (at, approximately, 25 epidemic days); while the spatial model revealed two epidemic peaks (at, approximately, 12 and 28 days, respectively). While the spatial model fitted well with the observed cumulative number of infected farms, the non-spatial model did not (P<0.01). In addition, the spatial model: (a) indicated an early intra-county reproductive number R of approximately 87 (falling to <1 within 25 days), and an inter-county R<1; (b) predicted that, if animal movement restrictions had begun 3 days before/after the estimated initiation of such policy, cases would have decreased/increased by 23 or 26%, respectively. Spatial factors (such as inter-farm distance and coverage of vaccination campaigns, absent in non-spatial models) may explain why partially explicit spatial models describe epidemic spread more accurately than non-spatial models even at early epidemic phases. Integration of geo-coded data into mathematical models is recommended.

Early and cost-effective identification of high risk/priority control areas in foot-and-mouth disease epidemics.

Geo-referenced data from the 2001 Uruguayan foot-and-mouth disease (FMD) epidemic were explored to assess whether spatial analysis could lead to cost-benefit based policies. Four variables were analysed: (i) location and size of 4022 individual rural land parcels, of which 574 were infected over 60 days, (ii) animal density, (iii) percentage of dairy farms per county, and (iv) road density. Each variable was categorized into two to five classes (e.g. small/medium/large) and the proportion of cases per class reported at days 1-3 of the epidemic was compared with that reported at days 4-6. A higher proportion of cases was found at days 4-6 than at days 1-3 in areas with: small and medium size land parcels, high animal density, > 20% farms specialized in dairy production, and high road density (P < 0.03 for each). Each of these classes showed a greater proportion of cases at days 7-60 than the proportion of the total territory covered by each class's area (early case concentration ratios: 1.14-1.37). Land parcel clusters were indicated by Moran's I-test (P < 0.01). A new region was constructed by intersecting the four spatial classes associated with higher proportions of cases at days 4-6. At days 7-60, this region included 50.4% of all cases and represented 30.6% of the territory under study (final case concentration ratio: 1.65). The final area per case in this region was at least 33% lower and covered at least 45% less territory than any of the four single-variable approaches. Bio-statistical, multivariate spatial analysis of early cases may greatly increase the efficiency of epidemiologic policy.

Critical response time (time available to implement effective measures for epidemic control): model building and evaluation.

The time available to implement successful control measures against epidemics was estimated. Critical response time (CRT), defined as the time interval within which the number of epidemic cases remains stationary (so that interventions implemented within CRT may be the most effective or least costly), was assessed during the early epidemic phase, when the number of cases grows linearly over time. The CRT was calculated from data of the 2001 foot-and-mouth disease (FMD) epidemic that occurred in Uruguay. Significant regional CRT differences (ranging from 1.4 to 2.7 days) were observed. The CRT may facilitate selection of control measures. For instance, a CRT equal to 3 days would support the selection of measures, such as stamping-out, implementable within 3 days, but rule out measures, such as post-outbreak vaccination, because intervention and immunity building require more than 3 days. Its use in rapidly disseminating diseases, such as FMD, may result in regionalized decision-making.

Identification of subpopulations of bovine mammary-gland phagocytes and evaluation of sensitivity and specificity of morphologic and functional indicators of bovine mastitis.

The number and function of bovine mammary-gland phagocytes were assessed in 8 lactating cows, each tested at least twice within an 8-mo period (total number of observations, 20). Macrophages and polymorphonuclear (PMN) cells were evaluated by conventional cytology, flow cytometry, fluorescent microscopy, and somatic-cell count (SCC). Phagocytosis was evaluated from the uptake of fluorescent beads and expressed as median fluorescence intensity (MFI). Two major subpopulations of phagocytes, of low or high MFI (LFI or HFI), were observed, and there were up to 4 sub-subpopulations within the HFI subpopulation of both macrophages and PMN cells. Fluorescent microscopy identified phagocytes containing up to 4 beads per cell. Cows showing < or = 72.3% phagocytes by cytology were regarded as non-mastitic (11 observations), and those showing > or = 80.7% phagocytes were considered to be mastitic (8 observations). Phagocyte MFI was negatively associated with mastitis; that is, the higher the MFI, the lower the SCC. The percentage of HFI PMN cells was the only indicator of mastitis with 100% sensitivity and specificity. Thus, bovine mammary-gland phagocytes consist of several subpopulations of different phagocytic ability, whose assessment more adequately predicts bovine mastitis than do morphologic indicators.

Blood and milk cellular immune responses of mastitic non-periparturient cows inoculated with Staphylococcus aureus.

Lymphocyte function and phenotype of peripheral blood and mammary gland cells were evaluated in non-periparturient cows before and at 1, 4 to 8 and 9 to 14 d after inoculation with Staphylococcus aureus, as expressed by percentage of CD3+, CD2+, and CD45R+ cells, antigen density of these markers per lymphocyte, and mitogen-induced blastogenesis. Milk bacterial counts and somatic cell counts (SCC) were also assessed. Mitogen-induced blastogenic responses were strong in blood and weak in mammary gland cells in all observations and positively correlated with the percent of CD45R+ cells. Significantly greater percentages of milk CD3+ lymphocytes and increased CD3, CD2, and CD45R antigen density per cell were observed after challenge. The blood CD3 and CD2 antigen density per lymphocyte and the milk CD2+ lymphocyte percent were negatively correlated with SCC (P < or = 0.01). No mastitis (SCC < or = 500 000 cells/mL) was observed in cows showing blood lymphocyte CD2 and CD3 antigen density indices < or = 2.5 and 6, respectively. Forty-one percent of SCC values were predicted by the combined blood CD2 and milk CD3 antigen density (P < or = 0.01). These findings support the hypotheses that mitogen-induced lymphocyte blastogenesis is not a valid test to assess mammary gland immunocompetence and that CD2 expression may facilitate immune responses by decreasing the number of T cell receptors required to achieve full activation.

Longitudinal evaluation of bovine mammary gland health status by somatic cell counting, flow cytometry, and cytology.

Bovine mastitis phases induced by Staphylococcus aureus were assessed in 6 lactating cows before challenge and at 1, 4-8, and 9-14 days postinoculation (dpi). Milk lymphocytes, macrophages, and polymorphonuclear cells (PMN) were counted by conventional (manual) cytology, identified by CD3+ and CD11b+ immunofluorescence and counted by flow cytometry (based on leukocyte forward and side light scatter values). Somatic cell counts (SCC) and recovery of bacteria were recorded at the same times. Preinoculation samples showed a lymphocyte-dominated composition. At 1 dpi, the percentage of PMN increased and that of lymphocytes decreased. At 4-8 dpi, PMN were predominant, but the percentage of mononuclear cells increased above that at 1 dpi and further increased by 9-14 dpi (when lymphocytes approached prechallenge values). Based on leukocyte percentages, 3 indices were created from the data: 1) the PMN/lymphocyte percentage ratio (PMN/L), 2) the PMN/macrophage percentage ratio (PMN/M), and 3) the phagocyte (PMN and macrophage)/lymphocyte percentage ratio (Phago/L). Significant correlations were found between cytologic and flow cytometric data in all of these indicators (all with P < or = 0.01). These indices identified nonmastitic, early inflammatory (1-8 dpi), and late inflammatory (9-14 dpi) animals. In contrast, SCC and bacteriology did not. Although sensitivity of the SCC was similar to that of Phago/L, the specificity of SCC was almost half that of the Phago/L index. Based on flow cytometry indicators, an algorithm for presumptive diagnosis of bovine mastitis was developed. Flow cytometry provides results as valid as those obtained by conventional (manual) cytology, shows greater ability to identify mastitic cases than does SCC, and may identify 3 mammary gland health-related conditions.

Molecular epidemiologic features and antimicrobial susceptibility profiles of various ribotypes of Pseudomonas aeruginosa isolated from humans and ruminants.

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 Pvull-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 single-host 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 Pvull 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.

Expression of CD3 and CD11b antigens on blood and mammary gland leukocytes and bacterial survival in milk of cows with experimentally induced Staphylococcus aureus mastitis.

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.

Longitudinal evaluation of CD4+ and CD8+ peripheral blood and mammary gland lymphocytes in cows experimentally inoculated with Staphylococcus aureus.

Staphylococcus aureus is a major pathogen associated with mastitis, a disease affecting both women and dairy cows. The longitudinal profiles of bovine peripheral blood and mammary gland lymphocyte phenotypes in response to S. aureus-induced mastitis were investigated in dairy cows. Increased percentage of CD4 lymphocytes in the mammary gland between 1 and 8 days post-inoculation, increased milk CD4 protein density per cell between 1-8 days post-inoculation, and a statistically significant negative correlation between post-inoculation bacterial counts in milk and blood lymphocyte CD4 protein density were found. Together with blood and milk leukocyte counts, the milk lymphocyte CD4/CD8 ratio and the milk lymphocyte CD4 protein density were more informative indicators than milk somatic cell counts and bacteriology for identification of early vs. late inflammatory phases. These findings suggest that CD4+ lymphocytes play a protective role in the early stages of S. aureus-induced mastitis.

Diversity of Streptococcus agalactiae and Staphylococcus aureus ribotypes recovered from New York dairy herds.

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.

Characterization of monoclonal antibodies directed to canine T lymphocyte markers expressed during development.

Two monoclonal antibodies (mAb) which recognize cell surface antigens of canine T lymphocytes are described. mAb RQ1 (of IgG1 subclass) binds a 34 kDa peptide under non-reducing conditions which is expressed, on average, by 27 +/- 9% (n = 11 dogs) of thymocytes, with preferential binding for medullary, but not cortical thymocytes. RQ1 adheres to splenic periarteriolar lymphoid sheath cells. In adult dogs (n = 7) RQ1 binds on average 86 +/- 7% of unstimulated canine peripheral blood mononuclear cells (CPBMC), 69 +/- 13% (n = 11) of lymph node cells, and < or = 19% (n = 2) of bone marrow cells. RQ1 does not bind canine granulocytes, erythrocytes, fibroblasts or kidney epithelial cells. The relative density of RQ1-binding antigen (expressed as fluorescence intensity per cell) was up to 83% greater in lymph node cells than in thymocytes. Thus RQ1 appears to preferentially bind mature T cells. In contrast, mAb LQ1 (of IgG3 subclass, which binds a 32 kDa sialic acid containing glycoprotein) recognizes both cortical and medullary canine thymocytes as well as 75 +/- 6% CPBMC. This profile is characteristic of a pan-T cell marker. The simultaneous utilization of these two markers allows for the characterization of canine T lymphocyte development: early lymphocyte (e.g. LQ1+, RQ1- thymocytes), common lymphocyte (e.g. LQ1+, RQ1+ [dim fluorescence] thymocytes), and mature lymphocyte (e.g. LQ1+, RQ1 + [bright fluorescence]).