Exploratory disease mapping: kriging the spatial risk function from regional count data

BACKGROUND: There is considerable interest in the literature on disease mapping to interpolate estimates of disease occurrence or risk of disease from a regional database onto a continuous surface. In addition to many interpolation techniques available the geostatistical method of kriging has been used but also criticised. RESULTS: To circumvent these critics one may use kriging along with already smoothed regional estimates, where smoothing is based on empirical Bayes estimates, also known as shrinkage estimates. The empirical Bayes step has the advantage of shrinking the unstable and often extreme estimates to the global or local mean, and also has a stabilising effect on variance by borrowing strength, as well. Negative interpolates are prevented by choice of the appropriate kriging method. The proposed mapping method is applied to the North Carolina SIDS data example as well as to an example data set from veterinary epidemiology. The SIDS data are modelled without spatial trend. And spatial interpolation is based on ordinary kriging. The second example is included to demonstrate the method when the phenomenon under study exhibits a spatial trend and interpolation is based on universal kriging. CONCLUSION: Interpolation of the regional estimates overcomes the areal bias problem and the resulting isopleth maps are easier to read than choropleth maps. The empirical Bayesian estimate for smoothing is related to internal standardization in epidemiology. Therefore, the proposed concept is easily communicable to map users

Suitability and limitations of portion-specific abattoir data as part of an early warning system for emerging diseases of swine in Ontario

<p>Abstract</p> <p>Background</p> <p>Abattoir data have the potential to provide information for geospatial disease surveillance applications, but the quality of the data and utility for detecting disease outbreaks is not well understood. The objectives of this study were to 1) identify non-disease factors that may bias these data for disease surveillance and 2) determine if major disease events that took place during the study period would be captured using multi-level modelling and scan statistics. We analyzed data collected at all provincially-inspected abattoirs in Ontario, Canada during 2001-2007. During these years there were outbreaks of porcine circovirus-associated disease (PCVAD), porcine reproductive and respiratory syndrome (PRRS) and swine influenza that produced widespread disease within the province. Negative binomial models with random intercepts for abattoir, to account for repeated measurements within abattoirs, were created. The relationships between partial carcass condemnation rates for pneumonia and nephritis with year, season, agricultural region, stock price, and abattoir processing capacity were explored. The utility of the spatial scan statistic for detecting clusters of high partial carcass condemnation rates in space, time, and space-time was investigated.</p> <p>Results</p> <p>Non-disease factors that were found to be associated with lung and kidney condemnation rates included abattoir processing capacity, agricultural region and season. Yearly trends in predicted condemnation rates varied by agricultural region, and temporal patterns were different for both types of condemnations. Some clusters of high condemnation rates of kidneys with nephritis in time and space-time preceded the timeframe during which case clusters were detected using traditional laboratory data. Yearly kidney condemnation rates related to nephritis lesions in eastern Ontario were most consistent with the trends that were expected in relation to the documented disease outbreaks. Yearly lung condemnation rates did not correspond with the timeframes during which major respiratory disease outbreaks took place.</p> <p>Conclusions</p> <p>This study demonstrated that a number of abattoir-related factors require consideration when using abattoir data for quantitative disease surveillance. Data pertaining to lungs condemned for pneumonia did not provide useful information for predicting disease events, while partial carcass condemnations of nephritis were most consistent with expected trends. Techniques that adjust for non-disease factors should be considered when applying cluster detection methods to abattoir data.</p

Spread of porcine circovirus associated disease (PCVAD) in Ontario (Canada) swine herds: Part II. Matched case-control study

<p>Abstract</p> <p>Background</p> <p>The emergence of porcine circovirus associated disease (PCVAD) was associated with high mortality in swine populations worldwide. Studies performed in different regions identified spatial, temporal, and spatio-temporal trends as factors contributing to patterns of the disease spread. Patterns consistent with spatial trend and spatio-temporal clustering were already identified in this dataset. On the basis of these results, we have further investigated the nature of local spread in this report. The primary objective of this study was to evaluate risk factors for incidence cases of reported PCVAD.</p> <p>Results</p> <p>A time-matched case-control study was used as a study design approach, and conditional logistic regression as the analytical method. The main exposure of interest was local spread, which was defined as an unidentified mechanism of PCVAD spread between premises located within 3 kilometers of the Euclidean distance. Various modifications of variables indicative of local spread were also evaluated. The dataset contained 278 swine herds from Ontario originally sampled either from diagnostic laboratory submissions or directly from the target population. A PCVAD case was defined on the basis of the producer's recall. Existence of apparent local spread over the entire study period was confirmed (OR = 2.26, 95% CI: 1.06, 4.83), and was further identified to be time-varying in nature - herds experiencing outbreaks in the later part of the epidemic were more likely than control herds to be exposed to neighboring herds experiencing recent PCVAD outbreaks. More importantly, the pattern of local spread was driven by concurrent occurrence of PCVAD on premises under the same ownership (OR_{EXACTwithin ownership}= 25.6, 95% CI: 3.4, +inf; OR_{EXACToutside ownership}= 1.3, 95% CI: 0.45, 3.3). Other significant factors included PRRSv status of a herd (OR_EXACT= 1.9, 95% CI: 1.0, 3.9), after adjusting for geographical location by including the binary effect of the easting coordinate (Easting > 600 km = 1; OR_EXACT= 1.8, 95% CI: 0.5, 5.6).</p> <p>Conclusions</p> <p>These results preclude any conclusion regarding the existence of a mechanism of local spread through airborne transmission or indirectly through contaminated fomites or vectors, as simultaneous emergence of PCVAD could also be a result of concurrent change in contributing factors due to other mechanisms within ownerships.</p

Spread of porcine circovirus associated disease (PCVAD) in Ontario (Canada) swine herds: Part I. Exploratory spatial analysis

<p>Abstract</p> <p>Background</p> <p>The systemic form of porcine circovirus associated disease (PCVAD), also known as postweaning multisystemic wasting syndrome (PMWS) was initially detected in the early 1990s. Starting in 2004, the Canadian swine industry experienced considerable losses due to PCVAD, concurrent with a shift in genotype of porcine circovirus type 2 (PCV2). Objectives of the current study were to explore spatial characteristics of self-reported PCVAD distribution in Ontario between 2004 and 2008, and to investigate the existence and nature of local spread.</p> <p>Results</p> <p>The study included 278 swine herds from a large disease-monitoring project that included porcine reproductive and respiratory syndrome (PRRS) virus-positive herds identified by the diagnostic laboratory, and PRRS virus-negative herds directly from the target population. Herds were included if they had growing pigs present on-site and available geographical coordinates for the sampling site. Furthermore, herds were defined as PCVAD-positive if a producer reported an outbreak of circovirus associated disease, or as PCVAD-negative if no outbreak was noted. Spatial trend was investigated using generalized additive models and time to PCVAD outbreak in a herd using Cox's proportional hazard model; spatial and spatio-temporal clustering was explored using K-functions; and location of most likely spatial and spatio-temporal clusters was investigated using scan statistics. Over the study period, the risk of reporting a PCVAD-positive herd tended to be higher in the eastern part of the province after adjustment for herd PRRS status (<it>P </it>= 0.05). This was partly confirmed for spread (Partial <it>P </it>< 0.01). Local spread also appeared to exist, as suggested by the tentative (<it>P </it>= 0.06) existence of spatio-temporal clustering of PCVAD and detection of a spatio-temporal cluster (<it>P </it>= 0.04).</p> <p>Conclusions</p> <p>In Ontario, PCVAD has shown a general trend, spreading from east-to-west. We interpret the existence of spatio-temporal clustering as evidence of spatio-temporal aggregation of PCVAD-positive cases above expectations and, together with the existence of spatio-temporal and spatial clusters, as suggestive of apparent local spread of PCVAD. Clustering was detected at small spatial and temporal scales. Other patterns of spread could not be detected; however, survival rates in discrete Ontario zones, as well as a lack of a clear spatial pattern in the most likely spatio-temporal clusters, suggest other between-herd transmission mechanisms.</p

Factors associated with whole carcass condemnation rates in provincially-inspected abattoirs in Ontario 2001-2007: implications for food animal syndromic surveillance

<p>Abstract</p> <p>Background</p> <p>Ontario provincial abattoirs have the potential to be important sources of syndromic surveillance data for emerging diseases of concern to animal health, public health and food safety. The objectives of this study were to: (1) describe provincially inspected abattoirs processing cattle in Ontario in terms of the number of abattoirs, the number of weeks abattoirs process cattle, geographical distribution, types of whole carcass condemnations reported, and the distance animals are shipped for slaughter; and (2) identify various seasonal, secular, disease and non-disease factors that might bias the results of quantitative methods, such as cluster detection methods, used for food animal syndromic surveillance.</p> <p>Results</p> <p>Data were collected from the Ontario Ministry of Agriculture, Food and Rural Affairs and the Ontario Cattlemen's Association regarding whole carcass condemnation rates for cattle animal classes, abattoir compliance ratings, and the monthly sales-yard price for various cattle classes from 2001-2007. To analyze the association between condemnation rates and potential explanatory variables including abattoir characteristics, season, year and commodity price, as well as animal class, negative binomial regression models were fit using generalized estimating equations (GEE) to account for autocorrelation among observations from the same abattoir. Results of the fitted model found animal class, year, season, price, and audit rating are associated with condemnation rates in Ontario abattoirs. In addition, a subset of data was used to estimate the average distance cattle are shipped to Ontario provincial abattoirs. The median distance from the farm to the abattoir was approximately 82 km, and 75% of cattle were shipped less than 100 km.</p> <p>Conclusions</p> <p>The results suggest that secular and seasonal trends, as well as some non-disease factors will need to be corrected for when applying quantitative methods for syndromic surveillance involving these data. This study also demonstrated that animals shipped to Ontario provincial abattoirs come from relatively local farms, which is important when considering the use of spatial surveillance methods for these data.</p

A Description of Laying Hen Husbandry and Management Practices in Canada

Canadian laying hen farms are transitioning from conventional cage housing to furnished cage and non-cage housing systems to improve laying hen welfare. However, little is known about the current housing and management systems in Canada. This study addresses this knowledge gap by describing different housing and management practices used on farms where laying hens were housed in furnished cages or non-cage housing systems. A questionnaire covering farm and housing conditions, litter management, nutrition and feeding, environmental control, flock characteristics, rearing and placement, health, egg production and performance were distributed through provincial egg boards to 122 producers across Canada. Data were collected from 65 laying hen flocks (52.5% response rate) in 26 furnished cage, 17 single-tier and 22 multi-tier systems. Flocks were on average 45.1 &plusmn; 14.59 weeks old (range: 19&ndash;69 weeks). Frequencies of different management practices were calculated according to housing system. Most flocks were reared in the same housing system as they were housed in during lay, with the exception of furnished cage layers which were reared in conventional cage systems. Results indicated that a large proportion of non-cage systems were either fully slatted or had manure as a litter substrate, which could have implications for consumer perspectives on these systems. Further research is needed to develop clear recommendations on proper litter management for farmers. In general, flock health was managed through daily inspections and vaccination schemes, whereas veterinarian involvement on-farm was less common. Vaccination, hygiene, and effective biosecurity should be maintained to ensure good health in laying hens in furnished cage and non-cage systems during the transition to these systems

House-level risk factors associated with the colonization of broiler flocks with Campylobacter spp. in Iceland, 2001 – 2004

<p>Abstract</p> <p>Background</p> <p>The concurrent rise in consumption of fresh chicken meat and human campylobacteriosis in the late 1990's in Iceland led to a longitudinal study of the poultry industry to identify the means to decrease the frequency of broiler flock colonization with <it>Campylobacter</it>. Because horizontal transmission from the environment is thought to be the most likely source of <it>Campylobacter </it>to broilers, we aimed to identify broiler house characteristics and management practices associated with flock colonization. Between May 2001 and September 2004, pooled caecal samples were obtained from 1,425 flocks at slaughter and cultured for <it>Campylobacter</it>. Due to the strong seasonal variation in flock prevalence, analyses were restricted to a subset of 792 flocks raised during the four summer seasons. Logistic regression models with a farm random effect were used to analyse the association between flock <it>Campylobacter </it>status and house-level risk factors. A two-stage process was carried out. Variables were initially screened within major subsets: ventilation; roof and floor drainage; building quality, materials and repair; house structure; pest proofing; biosecurity; sanitation; and house size. Variables with p ≤ 0.15 were then offered to a comprehensive model. Multivariable analyses were used in both the screening stage (i.e. within each subset) and in the comprehensive model.</p> <p>Results</p> <p>217 out of 792 flocks (27.4%) tested positive. Four significant risk factors were identified. <it>Campylobacter </it>colonization was predicted to increase when the flock was raised in a house with vertical (OR = 2.7), or vertical and horizontal (OR = 3.2) ventilation shafts, when the producer's boots were cleaned and disinfected prior to entering the broiler house (OR = 2.2), and when the house was cleaned with geothermal water (OR = 3.3).</p> <p>Conclusion</p> <p>The increased risk associated with vertical ventilation shafts might be related to the height of the vents and the potential for vectors such as flies to gain access to the house, or, increased difficulty in accessing the vents for proper cleaning and disinfection. For newly constructed houses, horizontal ventilation systems could be considered. Boot dipping procedures should be examined on farms experiencing a high prevalence of <it>Campylobacter</it>. Although it remains unclear how geothermal water increases risk, further research is warranted to determine if it is a surrogate for environmental pressures or the microclimate of the farm and surrounding region.</p

Epidemiology of canine heartworm (Dirofilaria immitis) infection in domestic dogs in Ontario, Canada: Geographic distribution, risk factors and effects of climate

Dirofilaria immitis is the causal agent of heartworm, a mosquito-borne parasite that primarily infects domestic and wild canids. The infection is endemic in parts of Canada, and Ontario has been identified as the province where the majority of heartworm infections occur. Test results for blood samples submitted by veterinary clinics for the years 2007-2016 were used to conduct a spatial risk analysis of heartworm among domestic dogs in Ontario. The geographic extent of the apparent heartworm prevalence was examined through smoothed choropleth maps for all 49 census division regions. Furthermore, the regions were assessed for local clusters in apparent prevalence using the flexible spatial scan statistic. Three clusters were found and located in western, southern and eastern Ontario, respectively. A spatial Poisson regression model for heartworm prevalence among pet dog populations in southern Ontario census divisions was fit to determine the association between human population size, heartworm development units (HDUs), climate moisture index (CMI), precipitation and directions, east or north, with heartworm infection. The model identified the spatial distribution of HDUs and CMI as positively associated with heartworm infection and therefore important predictors of the infection. In contrast, human population size, increasing northern latitude and drier areas were negatively associated with heartworm infection. The east direction and precipitation were not significant

Spatial Analysis of Sleeping Sickness, Southeastern Uganda, 1970–2003

Disease will likely spread into central Uganda

Detection of Clostridium difficile infection clusters, using the temporal scan statistic, in a community hospital in southern Ontario, Canada, 2006–2011

BACKGROUND: In hospitals, Clostridium difficile infection (CDI) surveillance relies on unvalidated guidelines or threshold criteria to identify outbreaks. This can result in false-positive and -negative cluster alarms. The application of statistical methods to identify and understand CDI clusters may be a useful alternative or complement to standard surveillance techniques. The objectives of this study were to investigate the utility of the temporal scan statistic for detecting CDI clusters and determine if there are significant differences in the rate of CDI cases by month, season, and year in a community hospital. METHODS: Bacteriology reports of patients identified with a CDI from August 2006 to February 2011 were collected. For patients detected with CDI from March 2010 to February 2011, stool specimens were obtained. Clostridium difficile isolates were characterized by ribotyping and investigated for the presence of toxin genes by PCR. CDI clusters were investigated using a retrospective temporal scan test statistic. Statistically significant clusters were compared to known CDI outbreaks within the hospital. A negative binomial regression model was used to identify associations between year, season, month and the rate of CDI cases. RESULTS: Overall, 86 CDI cases were identified. Eighteen specimens were analyzed and nine ribotypes were classified with ribotype 027 (n = 6) the most prevalent. The temporal scan statistic identified significant CDI clusters at the hospital (n = 5), service (n = 6), and ward (n = 4) levels (P ≤ 0.05). Three clusters were concordant with the one C. difficile outbreak identified by hospital personnel. Two clusters were identified as potential outbreaks. The negative binomial model indicated years 2007–2010 (P ≤ 0.05) had decreased CDI rates compared to 2006 and spring had an increased CDI rate compared to the fall (P = 0.023). CONCLUSIONS: Application of the temporal scan statistic identified several clusters, including potential outbreaks not detected by hospital personnel. The identification of time periods with decreased or increased CDI rates may have been a result of specific hospital events. Understanding the clustering of CDIs can aid in the interpretation of surveillance data and lead to the development of better early detection systems