Factors associated with spatial clustering of foot-and-mouth disease in Nepal

The purpose of this study was to quantify associations between hypothesized epidemiological factors and the spatial distribution of foot-and-mouth disease (FMD) in Nepal. Spatial clustering of reports of at least one FMD case by Village Development Committee (VDC) in 2004 was examined by use of the spatial scan statistic. A Bayesian Poisson multivariate regression model was used to quantify the association between the number of reports and 25 factors hypothesized to be associated with FMD risk. The spatial scan statistic identified (P < 0.01) two clusters of FMD reports. Large numbers of people, buffalo, and animal technicians in a district were associated with an elevated risk of a VDC reporting ≥1 FMD case. The knowledge of high-risk areas and factors associated with the risk of FMD in Nepal could be applied in future disease control programs.     

Use of the scan statistic on disaggregated province-based data: foot-and-mouth disease in Iran

The spatial scan statistic was applied to density-smoothed data that approximated the spatial distribution within the area and reduced the potential bias produced when location data have been aggregated for large areas. The method is illustrated, using data on the location of foot-and-mouth disease (FMD) outbreaks in Iran. Data examined were 4477 FMD outbreaks reported on a per province basis between June 1996 and September 2003. A kernel density of the outbreak locations was estimated, using a fixed radius and the centroid of each province as the designated location of all cases reported for the province. The radius that produced a density map with the highest correlation with expert opinion was 4° (latitude/longitude). Livestock density was used as a proxy for the underlying population at risk of acquiring FMD. Livestock and outbreak density maps were overlain to obtain the number of outbreaks and livestock in each of 15,599 cells covering the mapped surface of the country. A spatial scan statistic was applied to the density-smoothed data assuming that the outbreaks had a Poisson distribution. Results were compared with those obtained using a spatial scan statistic on provincially aggregated data. Application of the spatial scan statistic on the density-smoothed data allowed identification of clusters (P < 0.01) related more to the actual geographic distribution of cases (expert opinion) and of animals at risk, than to the distribution of the provinces. Significant clusters of FMD were identified that coincided with roads, neighboring countries, and high-density population areas, suggesting that the region may represent a route for cross-continent transmission of FMD.     

Descriptive analysis and spatial epidemiology of porcine reproductive and respiratory syndrome (PRRS) for swine sites participating in area regional control and elimination programs from 3 regions of Ontario

The objectives of this study were to describe demographics, basic biosecurity practices, ownership structure, and prevalence of porcine reproductive and respiratory syndrome (PRRS) in swine sites located in 3 regions in Ontario, and investigate the presence of spatial clustering and clusters of PRRS positive sites in the 3 regions. A total of 370 swine sites were enrolled in Area Regional Control and Elimination projects in Niagara, Watford, and Perth from 2010 to 2013. Demographics, biosecurity, and site ownership data were collected using a standardized questionnaire and site locations were obtained from an industry organization. Status was assigned on the basis of available diagnostic tests and/or assessment by site veterinarians. Spatial dependence was investigated using the D-function, the spatial scan statistic test and the spatial relative risk method. Results showed that the use of strict all-in all-out (AIAO) pig flow and shower before entry are uncommon biosecurity practices in swine sites, but a larger proportion of sites reported having a Danish entry. The prevalence of PRRS in the 3 regions ranged from 17% to 48% and localized high and low risk clusters were detected. Sites enrolled in the PRRS control projects were characterized by membership in multiple and overlapping ownership structures and networks, which complicates the way the results of monitoring and disease management measures are communicated to the target population.     

A Bayesian hierarchical analysis to compare classical and atypical scrapie surveillance data; Wales 2002-2006

We describe the application of Bayesian hierarchical models (BHM) to the analysis of risk of sheep scrapie using data from multiple surveillance sources. More specifically, we analysed data from the test results of three surveillance sources on classical and atypical scrapie in Wales for the period 2002-2006. For each form of scrapie, a BHM was fitted to assess the occurrence of spatial patterns of risk shared by the multiple surveillance sources and the association between covariates and disease. We defined a shared-component model whereby the two types of data sources: exhaustive lists (e.g. reports of clinical cases) and sample-based data sources (e.g. abattoir survey) shared a common spatial pattern of risks at parish level. This shared component was adjusted by a risk-gradient parameter that moderated the individual contribution of the datasets. For both forms of scrapie, the risk-gradient was not significantly different indicating that the sensitivity of the two types of dataset was similar for the two diseases. The spatial patterns of the combinations of data sources appeared similar within disease. However, our results suggest that classical and atypical scrapie differ in their spatial patterns and disease determinants. The joint approach permitted inference from all the available evidence and resulted in robust and less biased estimates of risk, particularly for atypical scrapie where the number of observations was very limited.     

Grazing Impacts in Vegetated Dune Fields: Predictions From Spatial Pattern Analysis

This study deals with the changes induced by grazing on soil erosion processes in vegetated dune fields of Península Valdés, in the Patagonia region of Argentina. We performed a spatial analysis to assess erosion features’ patterns. Blowouts, used as main indicators of aeolian erosion processes, as well as dune crests, which are susceptible to erosion, were mapped on aerial photographs and images from Landsat 7 Enhanced Thematic Mapper Plus, in eight paddocks under two grazing conditions: lightly (0.4 sheep · ha⁻¹) and heavily grazed (0.8 sheep · ha⁻¹). From the mapped locations of water points, crests, and blowouts we calculated a spatial statistic (O-ring statistic), which gives the expected intensity of blowouts within the area covered by crests as function of distance away from water points. Additionally, to explore if the density of crests around water points influences the density of blowouts, we estimated the intensity of dune crests in the neighborhood of water points and compared the densities of blowouts among water points with low, medium, and high densities of crests. For the heavy grazing treatment we found highly significant (P < 0.05) aggregation of blowouts around water points with peak densities threefold higher than expected at random occurring between 90 and 210 m. However, the aggregation was only weakly significant for the light grazing treatment and occurred only at distances of about 30 m away from the water point. We found that the impact of grazing on soil stability contrasted among sites with different sensitivity to accelerated erosion. In sites with a high density of dune crests close to water points, wind erosion becomes more intense and the density of blowouts increases. A more sustainable management of these rangelands depends primarily on the conservation of the soils. Therefore, the location of water points in sites not susceptible to accelerated soil erosion would represent a better management strategy of the dune fields of Península Valdés.     

Emerging viral zoonoses: frameworks for spatial and spatiotemporal risk assessment and resource planning

Spatial epidemiological tools are increasingly being applied to emerging viral zoonoses (EVZ), partly because of improving analytical methods and technologies for data capture and management, and partly because the demand is growing for more objective ways of allocating limited resources in the face of the emerging threat posed by these diseases. This review documents applications of geographical information systems (GIS), remote sensing (RS) and spatially-explicit statistical and mathematical models to epidemiological studies of EVZ.Landscape epidemiology uses statistical associations between environmental variables and diseases to study and predict their spatial distributions. Phylogeography augments epidemiological knowledge by studying the evolution of viral genetics through space and time. Cluster detection and early warning systems assist surveillance and can permit timely interventions. Advanced statistical models can accommodate spatial dependence present in epidemiological datasets and can permit assessment of uncertainties in disease data and predictions. Mathematical models are particularly useful for testing and comparing alternative control strategies, whereas spatial decision-support systems integrate a variety of spatial epidemiological tools to facilitate widespread dissemination and interpretation of disease data. Improved spatial data collection systems and greater practical application of spatial epidemiological tools should be applied in real-world scenarios.     

Conditional dependence between tests affects the diagnosis and surveillance of animal diseases

Dependence between the sensitivities or specificities of pairs of tests affects the sensitivity and specificity of tests when used in combination. Compared with values expected if tests are conditionally independent, a positive dependence in test sensitivity reduces the sensitivity of parallel test interpretation and a positive dependence in test specificity reduces the specificity of serial interpretation. We calculate conditional covariances as a measure of dependence between binary tests and show their relationship to kappa (a chance-corrected measure of test agreement). We use published data for toxoplasmosis and brucellosis in swine, and Johne's disease in cattle to illustrate calculation methods and to indicate the likely magnitude of the dependence between serologic tests used for diagnosis and surveillance of animal diseases.     

Disease-induced variability of genetic correlations: ascites in broilers as a case study

Breeding against a production disease is complicated by multiple relationships between productivity, disease, and environment. Ascites in broilers is such a disease. The combination of the reasonably well understood etiology (a physiological/pathological cascade due to inadequate oxygen supply) and the practical relevance makes ascites a relevant case for demonstrating and partly revealing these complex relationships. Chickens (n = 2,788) were tested in an ascites-challenging (cold) environment. Genetic analysis of mortality and pathology in combination with performance and physiological traits (especially blood gas traits) revealed ample opportunities for selection against ascites expression. The genetic correlation structure indicated that different mortality traits and pathology traits roughly represent one common characteristic. Direct selection against pathology is more effective than selection on the basis of growth or blood gas traits. The observed negative correlation (-0.26) between productivity and ascites was unexpected. From the etiology of ascites (inadequate supply of oxygen relative to the demand), a positive (unfavorable) correlation was expected. To demonstrate that the actual disease occurrence caused this apparent contradiction, the data from the undiseased subpopulation were reanalyzed. In the undiseased subpopulation, the genetic correlation between productivity and ascites was positive (0.29). This discrepancy was confirmed by comparing regression of ascites expression on actual performance with regression of ascites on independently assessed performance breeding values. The lability of the genetic correlation was explained from complex interactions between productivity, disease susceptibility, and actual occurrence of the disease. The revealed mechanism can be generalized to other production-related diseases and results in systematically lower genetic correlations between disease and productivity. It was inferred that genetic correlations between productivity and such diseases will always be prone to the demonstrated environmental sensitivity, which complicates index selection against production-related diseases.     

Modelling bovine trypanosomosis spatial distribution by GIS in an agro-pastoral zone of Burkina Faso

Modelling of the spatial distribution of bovine trypanosomosis prevalence in Sideradougou district Burkina Faso was performed by using a combination of spatial and statistical analysis. Based on a comprehensive and geographically representative census of herds and farms in the area, more than 2000 cattle were randomly chosen and their blood sampled during field survey. Data on livestock farming practices were recorded for each farm. All data were mapped within a GIS to generate new information on spatial constraints in the area.Surveys results were analysed and serological prevalence data were modelled using logistic regression. The model allowed identification and quantification of risk factors. In a second step the statistical model was used predictively on the entire farm population in the area. This method was successful in predicting the serological prevalence for each individual herd in the sample, from their livestock management patterns and spatial location. Predicted prevalences were represented within the GIS, taking daily movements of animals into account. Spatial distribution of prevalence would illustrate specific locations at risk from an epidemiological viewpoint. It gives evidence that the hydrological network and land occupation patterns in the savanna-type countryside are playing an important part when structuring a so-called "trypanosomosis space".     

The area-wide epidemiology of bovine trypanosomosis and its impact on mixed farming in subhumid West Africa; a case study in Togo.

This paper reports on an area wide study of all major variables determining the expression of trypanosomosis in cattle in the subhumid eco-zone of West Africa, taking Togo as an example. To enable systematic area-wide sampling, the country was divided in 311 grid-squares of 0.125 x 0.125 sides. Cross-sectional surveys were then conducted to generate maps or digital layers on cattle density, herd structure, ownership and breed. These data layers, except for the breed data, were subjected to a cluster analysis in order to define spatial patterns in animal husbandry systems. This analysis revealed two main systems: one is oriented towards integration with crop-agriculture and a second towards investment in cattle. These two systems could be further characterised by incorporating breed data. Zebu cattle and their crossbreeds are more favoured in the second system. The breed distribution map shows the actual situation but also serves to predict the outcome of progressive crossbreeding. An area wide trypanosomosis survey allowed the production of prevalence maps for Trypanosoma congolense, T. vivax and the associated packed cell volume (PCV) values. A simple curvi-linear relationship was established between vector density and disease prevalence. The regression between disease prevalence and PCV for taurine and zebu plus crossbreeds separately, revealed that taurine cattle maintain a comparatively high PCV level particularly in high prevalence scenarios. The relationship between the average herd PCV and cattle density suggests that herd PCV value may provide a mirror for the number of animals not kept because of the prevailing risk. The regression between agricultural intensity and cattle density subsequently in areas with decreasing herd PCV values reveals that the level of integration of cattle in crop production decreases with a decreasing PCV. Thus, despite the presence of taurine animals in Togo, the omnipresence of tsetse in particular Glossina tachinoides, remains a major obstacle to cattle raising and indirectly mixed farming development and intensification. It is argued that only with the present type of wide scale, spatial studies it becomes possible to clarify all the major variables influencing the expression of trypanosomosis. Spatial epidemiological studies at a macro level may form the basis for area wide trypanosomosis control in West Africa.     

Spatial and temporal patterns of bovine anaplasmosis as reported by Illinois veterinarians

Spatial analysis was used in combination with more traditional epidemiologic methods to study patterns of anaplasmosis in a transitional area between anaplasmosis endemic and non-endemic regions. Data were collected using a mail survey from 179 veterinarians with practice areas including 100/102 Illinois counties. The pattern of anaplasmosis reported by practitioners did not follow the general distribution of cattle and was clustered, with two major endemic foci. Endemic counties (22/100 counties) were bordered by areas of intermediate endemicity (36/100 counties) with only sporadic cases occurring in the remainder of the state (42/100 counties). Clinical disease occurred mainly in late summer and early fall with a small number of new herds diagnosed during the winter. Illinois practitioners most commonly identified horseflies and other biting flies as the vectors of anaplasmosis but also believed mosquitos, ticks and iatrogenic means could account for transmission in their practice areas. Ries were most often reported in summer while iatrogenic transmission was more commonly reported with winter outbreaks. Vaccination and low level antibiotics were used in endemic areas but only by a small proportion of respondents (12%). Veterinarians in endemic and marginal areas also used antibiotics to clear infection from herds more often than did those experiencing sporadic cases in non-endemic areas. Many practitioners expressed uncertainty about the actual extent of the problem in their areas. Wooded land area was used as a proxy to test for co-distribution of general vector habitat with anaplasmosis. Significantly more anaplasmosis was found in the more wooded parts of the state (based on the Kappa statistic). Respondents from western Illinois reported carrier cattle to be the source of infection for most new outbreaks while white-tailed deer were considered to be as important a reservoir as cattle in southern Illinois. Spatial analysis did not support an important role for white-tailed deer.     

Exploratory spatial relative risk mapping

The many faces of disease mapping include maps of disease case locations, regional counts of cases, and disease risk. Another approach is that of mapping the relative risk. Previous methods to map the relative risk were based on regression models of relative risk, given information about geographical locations and established risk factors. However, spatial epidemiological investigations are often exploratory with limited knowledge about the putative risk factors. Indeed, often the primary motivation for the analysis is to identify unknown geographically varying risk factors.

An exploratory approach to mapping the spatial relative risk is to scale the risk map using the background risk in the unexposed (or less-exposed) population. Exposure to unknown spatial risk factors is defined via specific cluster analysis. Identification of spatial disease clusters separates the population into those inside and those outside high risk areas (the exposed and unexposed populations). This exploratory approach to relative risk mapping gives the investigator an impression about the importance and geographical distribution of the unknown spatial risk factors.

Two examples illustrate the exploratory relative risk mapping approach using a spatial point data set on pseudorabies in pig-herds and a regional count data set on small fox tapeworm infections in red foxes.     

Spatial distribution of bluetongue surveillance and cases in Switzerland

Swiss Bluetongue surveillance from mid 2007 to mid 2008 was a combination of monthly bulk milk testing of 200 cattle herds in zones of higher risk for vector presence and intensification of passive clinical surveillance. The spatial scan statistic and Moran's I statistic were used to determine clustering of surveillance data. The results show a high level of surveillance intensity for BT in Switzerland in 2007. In the region encompassing the Cantons of Aargau, Basel-Landschaft, Basel-Stadt and Solothurn, where cases were detected in 2007, the surveillance was significantly higher than in the rest of Switzerland. Six cases of Bluetongue were detected within the surveillance system. The prevalence estimates 9.62% (95% CI = 3.25%-18.85% versus 0.98% (95% CI = 0.2%-2.22%) were also significantly higher in the area with higher surveillance intensity. Spatial variation in surveillance data should to be considered if a disease event is analysed on a national scale. The spatial variation of prevalence estimates should be considered in future Bluetongue surveillance in Switzerland.     

Risk signals of an influenza pandemic caused by highly pathogenic avian influenza subtype H5N1: spatio-temporal perspectives

Highly pathogenic avian influenza (HPAI) subtype H5N1 is a trans-boundary animal disease that has crossed the animal-human species barrier and over the past decade has had a considerable impact on the poultry industry, wild bird populations and on human health. Understanding the spatio-temporal patterns of H5N1 outbreaks can provide visual clues to the dynamics of disease spread and of areas at risk, and thus improve the cost-effectiveness of disease control and prevention. This study describes the characteristics and investigates the temporal, spatial and space-time dynamics of H5N1 outbreaks in domestic poultry between December 2003 and December 2009 using a global database. The study found that the start date of the epidemic wave was postponed, the duration of the epidemic was prolonged and its magnitude reduced over time, but the disease transmission cycle was not efficiently interrupted. Two 'hot-spot' regions of H5N1 outbreaks were identified: well-documented locations in East and Southeast Asia, as well as a novel location at the boundaries of Europe and Africa, where enhanced surveillance should be conducted. The risk of a pandemic due to H5N1 remains high.     

Brazilian spotted fever: A spatial analysis of human cases and vectors in the state of São Paulo,Brazil

Brazilian spotted fever (BSF) is a highly lethal disease caused by Rickettsia spp. and is transmitted by ticks of the genus Amblyomma. Understanding the epidemiology of BSF in each region can help direct health surveillance actions. The objective of this study was to determine the spatial distribution of vectors and the incidence of BSF in the state of São Paulo. Spatial analysis included confirmed BSF cases between 2009 and 2019; occurrences were registered by municipalities of the state. There were 752 confirmed BSF cases, with incidences ranging between 0.01 and 10.37/10,000 inhabitants. Moran's Global Index for BSF was 0.20 (p = .001), which was indicative of spatial dependence. Moran's map located a cluster of 20 high priority municipalities for BSF and showed that Amblyomma sculptum is the vector involved in Rickettsia rickettsii transmission in these locations. Spatial analysis identified clusters formed by 47, 20 and seven significant municipalities for the presence of A. sculptum, Amblyomma aureolatum and Amblyomma ovale vectors, respectively. Surveillance and prevention actions are necessary in areas that are at high risk for BSF and in areas where the presence of vectors was significant.     

Spatial analysis of Mycobacterium bovis infection in white-tailed deer (Odocoileus virginianus) in Michigan, USA

The wild white-tailed deer (Odocoileus virginianus) population in Michigan, USA, has endemic Mycobacterium bovis. We determined whether there were spatial clusters of retrospective TB cases in white-tailed deer in northeastern Michigan and identified specific factors associated with the spatial clusters. Data from hunter-harvested deer (age, gender, TB status, and geographic section) were collected by the Michigan Department of Natural Resources (MDNR) during TB surveillance from 1995 to 2002. Land cover (vegetation, land-use) and land type (soil types and drainage characteristics, landforms) described potential deer habitats. Specific locations of large-scale supplemental feeding sites were collected from the MDNR aerial surveillance program from 1997 to 2002. Analyses were conducted using principal components derived from environmental data (and other risk factors) on spatial clusters of disease (identified by the spatial scan statistic). Spatial effects were incorporated into the multivariable analyses by using a neighborhood approach. A total of 420 deer with M. bovis infection were identified from 1995 to 2002, out of 39,451 harvested deer from 3216 TRS units, and spatial clusters of cases were identified. A total of seven principal components of environmental data were generated. Clusters were associated with the presence of large expanses of deciduous forests on moraine ridges separated by low areas of forested wetlands, and the presence of many small lakes. Factors that promoted congregation of deer for extended periods of time (natural cover, access to water, and less human contact) appeared to be associated with increased odds of TB positivity. This suggests that there are specific areas where interventions can be implemented to reduce congregation of animals and disrupt the cycle of infection transmission.     

The epidemiology of subfertility in non-seasonal calving dairy herds in the Camden region of New South Wales: preliminary investigation of risk factors

OBJECTIVE: To investigate relationships between biographic, reproductive, production and disease traits and subfertility among 965 Holstein cows from 10 non-seasonal calving dairy herds in the Camden region of New South Wales. DESIGN: A retrospective case-control study METHODS: Biographical, disease and reproductive data were collated from computerised records for cows with lactations that commenced between 1 July 1995 and 30 June 1996 and univariable and bivariable associations with subfertility were determined. RESULTS: Records from 965 cows that conceived were considered for risk factor analyses. Associations between subfertility and a number of risk factors (P < 0.3) were detected. Significant (P < 0.05) risk factors for subfertility in multiparous cows included herd of origin and, after controlling for the effect of herd, subfertility in the previous lactation, greater than 62 days dry, parity greater than five, interval between calving and first recorded heat, metritis and cystic ovarian disease. Herd of origin and, after controlling for herd effects, dystocia, metritis and percentage of milk fat plus protein at the time of first service were significant (P < 0.05) risk factors for subfertility in primiparous cows. The direction and magnitude of these associations are presented. CONCLUSION: Subfertility has a similar rate of occurrence in the herds examined to that reported overseas. Although herd of origin has a substantial effect on individual risk of subfertility, cow-level risk factors for subfertility are likely to exist. Exposures differ between primiparous and multiparous cows.