Recent rapid changes in the spatio‐temporal distribution of West Nile Neuro‐invasive Disease in Italy

In Italy, the first human case of West Nile Virus (WNV) infection was reported in 2008 and, since then, the number of cases has been steadily increasing. In this study, we describe the temporal and spatial pattern of WNV infection risk among humans in Italy, focusing on the human cases of West Nile Neuro‐invasive Disease (WNND) observed between 2008 and 2017. Incidence rates are estimated for each year and province under study. The incidence temporal trend is estimated using Poisson regression, and a spatio‐temporal cluster detection analysis is performed to detect high‐risk areas. In total, 231 WNND cases were notified in Italy between 2008 and 2017. The annual incidence rates increased during the study period (annual percentage change: 11.7%; 95%CI: ?0.9%; 26.1%). A geographical spread of the disease was observed during the study period throughout Northern Italy, with an increasing number of affected provinces. Provinces close to the Po River (the main river in the north of Italy) and the Oristano province (in the Sardinia Island) experienced the highest incidence rates during the study period. Our study shows a gradual, but rapid spread of WNND across Northern Italy from east to west and suggests the hypothesis that provinces close to Po River might present ecological and climatic conditions favourable to the virus circulation.     

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.     

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.     

Identification of Visceral Leishmaniasis‐Susceptible Areas using Spatial Modelling in Southern Caucasus

This study explores the application of spatial modelling techniques to generate susceptibility maps for a neglected zoonotic disease, visceral leishmaniasis (VL), in an endemic area in southern Caucasus that includes Iran, Armenia and Azerbaijan. The social and physical environment of southern Caucasus has been mainly characterized by the presence of several factors that are strongly associated with VL, which has caused a significant number of infections during the past decade. Three popular spatial modelling techniques, consisting of the weights of evidence, logistic regression and fuzzy logic methods, were evaluated and trained using a study area in north‐western Iran where an inventory of highly infected areas and high‐quality evidential factors was available. Model performance was assessed using the receiver‐operating characteristic (ROC) approach. According to the results of these assessments, the fuzzy logic method with γ = 0.5 was chosen for the prediction of VL incidence in southern Caucasus. The susceptibility map generated using the fuzzy logic method indicated that VL followed a spatial pattern at the conjunction of the three countries, which suggests that the prevalence of VL in southern Caucasus is socio‐ecologically dependent.     

Identifying the spatiotemporal clusters of plague occurrences in China during the Third Pandemic

Plague, a devastating infectious disease caused by Yersinia pestis, has killed millions of people in the past and is still active in the natural foci of the world today. Understanding the spatiotemporal patterns of plague outbreaks in history is critically important, as it may help to facilitate prevention and control of potential future outbreaks. In this study, we explored spatiotemporal clusters of human plague occurrences in China using a machine‐learning clustering method and reconstructed the potential transmission pattern during the Third Pandemic (1772–1964). We succeeded in identifying 6 clusters in the space domain (2D) and 13 clusters in the spatiotemporal domain (3D). Our results suggest that there were several temporal outbreaks and transmissions of plague in different spatial clusters. Together with the spatiotemporal nearest neighbor approach (ST‐NNA), this method could allow us to have a clearer look at the spatiotemporal patterns of plague.     

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.     

Predicted Distribution of Visceral Leishmaniasis Vectors (Diptera: Psychodidae; Phlebotominae) in Iran: A Niche Model Study

Visceral leishmaniasis (VL) is an important vector‐borne disease in Iran. Till now, Leishmania infantum has been detected from five species of sand flies in the country including Phlebotomus kandelakii, Phlebotomus major s.l., Phlebotomus perfiliewi, Phlebotomus alexandri and Phlebotomus tobbi. Also, Phlebotomus keshishiani was found to be infected with Leishmania parasites. This study aimed at predicting the probable niches and distribution of vectors of visceral leishmaniasis in Iran. Data on spatial distribution studies of sand flies were obtained from Iranian database on sand flies. Sample points were included in data from faunistic studies on sand flies conducted during 1995–2013. MaxEnt software was used to predict the appropriate ecological niches for given species, using climatic and topographical data. Distribution maps were prepared and classified in ArcGIS to find main ecological niches of the vectors and hot spots for VL transmission in Iran. Phlebotomus kandelakii, Ph. major s.l. and Ph. alexandri seem to have played a more important role in VL transmission in Iran, so this study focuses on them. Representations of MaxEnt model for probability of distribution of the studied sand flies showed high contribution of climatological and topographical variables to predict the potential distribution of three vector species. Isothermality was found to be an environmental variable with the highest gain when used in isolation for Ph. kandelakii and Ph. major s.l., while for Ph. alexandri, the most effective variable was precipitation of the coldest quarter. The results of this study present the first prediction on distribution of sand fly vectors of VL in Iran. The predicted distributions were matched with the disease‐endemic areas in the country, while it was found that there were some unaffected areas with the potential transmission. More comprehensive studies are recommended on the ecology and vector competence of VL vectors in the country.     

Genetic analysis of river,swamp and hybrid buffaloes of north‐east India throw new light on phylogeography of water buffalo (Bubalus bubalis)

This study analysed buffaloes from north‐east India and compared their nuclear and mitochondrial DNA variations with buffaloes of mainland India, China, Mediterranean and South‐East Asia. Microsatellite genotypes of 338 buffaloes including 210 from six north‐east Indian buffalo populations and three mainland Indian breeds were analysed to evaluate their genetic structure and evolutionary relationships. Phylogenetic analysis and multidimensional scaling plot of pairwise F_ST revealed the clustering of all swamp‐type buffaloes of north‐east India with Lower Assamese (significantly hybrid type) buffaloes in one plane and all the mainland river buffaloes in another plane while the upper Assamese buffaloes being distinct from both these clusters. Analysis of mtDNA D‐loop region of 530‐bp length was performed on 345 sequences belonging to 23 buffalo populations from various geographical regions to establish the phylogeography of Indian water buffalo. The swamp buffaloes of north‐east India clustered with both the lineages of Chinese swamp buffalo. Multidimensional scaling display of pairwise F_ST derived from mitochondrial DNA data showed clustering of upper Assamese, Chilika and Mediterranean buffaloes distinctly from all the other Indian buffalo populations. Median‐joining network analysis further confirmed the distinctness and ancestral nature of these buffaloes. The study revealed north‐east region of India forming part of the wider hybrid zone of water buffalo that may probably extend from north‐east India to South‐East Asia.     

Epidemiology of campylobacteriosis in Denmark 2000–2015

Campylobacter is the most frequently occurring cause of bacterial gastroenteritis in Europe. Unlike other zoonotic diseases, European‐wide incidences of Campylobacter infections have increased during the past decade, resulting in a significant disease burden. In Denmark, campylobacteriosis is notifiable by laboratory and a unique registration system of electronic transfer and storage of notified Campylobacter cases linked to the national person register of age, gender and geographical location allows collection of comprehensive case data. Using national surveillance data, we describe Campylobacter infections in Denmark from 2000 to 2015, focusing on age‐specific incidences, geography, seasonality and outbreaks. During the observed period, a total of 60,725 Campylobacter infections were registered with a mean annual incidence of 69.3 cases/100,000 population. From 2000 to 2014, the incidence of campylobacteriosis decreased by 20%, followed by an apparent increase of 20% from 2014 to 2015. Approximately one‐third of cases were travel‐related. Incidences were highest in males, young adults aged 20–29 years and children under 5 years of age. Generally, children under 10 years of age living in rural areas were at higher risk of infection. Infection patterns were seasonal with an increase from May to October, peaking in August. Outbreaks were identified each year, including four large waterborne outbreaks which all occurred following heavy rainfall events. For the most part, patterns of Campylobacter infection in Denmark during 2000 to 2015 remained remarkably constant and followed what is known about the disease with respect to demographic, temporal and spatial characteristics. To establish better targeted prevention and control measures, the current knowledge gaps regarding both Campylobacter microbiology (degree of clonal diversity and clustering) and the importance of different risk factors (food versus environment/climate) need to be filled.     

Prevalence and significant geospatial clusters of bovine tuberculosis infection at livestock–wildlife interface ecosystem in Eastern Tanzania

Bovine tuberculosis (BTB) is an important neglected zoonosis that affects livestock, wildlife and human. A study to determine prevalence and geospatial clusters for BTB was conducted from June 2010 to March 2012 at livestock–wildlife interface areas (LWIA). A total of 1,288 cattle located in vicinity of Mikumi-Selous ecosystem Tanzania were tested. Single Intradermal Comparative Tuberculin Test and spatial scan statistic analysis were applied to establish the status of the disease and identify significant spatial BTB clusters. Overall individual prevalence was 3.7 % (n?=?1,288) (95 % CI?=?2.8–4.9) and 7.8 % (95 % CI?=?6.4–9.4) with cut-off of >4 and >2 mm, respectively. Villages with at least one reactor were 55.8 % (n?=?43). Reactivity was significantly higher in Mvomero and Kilosa districts compared with Kilombero and Ulanga districts (χ ²?=?15.9; P?<?0.001). Significant spatial BTB clusters were revealed at 11 villages. BTB clustering was significant in Kilosa and Mvomero districts compared with Kilombero and Ulanga districts. There was overlap and aggregation of BTB clusters covering south and south-east of Kilosa district bordering Mikumi National Park (MNP) and Mvomero. Generally, clustering occurred around major rivers. The current study provides useful information on the dynamics and epidemiological status of BTB around the wildlife–livestock–human interface, it reveals that the wildlife are at risk of BTB from infected livestock. The study revealed hotspots for BTB that can be applied to guide implementation of participatory intervention at LWIA and control strategies in marginalised pastoralist communities. This study calls for similar studies in other Tanzania’s LWIA for efficient intervention of BTB countrywide.     

Techniques for analysis of disease clustering in space and in time in veterinary epidemiology

Techniques to describe and investigate clustering of disease in space — the nearest-neighbour test, autocorrelation, Cuzick-and-Edwards’ test and the spatial scan statistic — and in time — the Ederer–Myers–Mantel test and the temporal scan statistic — are reviewed. The application of these techniques in veterinary epidemiology is demonstrated by the analysis of a data set describing the occurrence of blowfly strike — both body strike and breech strike — between August 1998 and May 1999 in 33 commercial sheep flocks located within two local government areas of southeastern Queensland, Australia. By applying a combination of these methods, the occurrence of blowfly strike in the study area is well-characterised in both space and time. Guidelines for investigating disease clusters in veterinary epidemiology are discussed.     

Spatio‐Temporal Scan Statistics for the Detection of Outbreaks Involving Common Molecular Subtypes: Using Human Cases of Escherichia coli O157:H7 Provincial PFGE Pattern 8 (National Designation ECXAI.0001) in Alberta as an Example

Molecular typing methods have become a common part of the surveillance of foodborne pathogens. In particular, pulsed‐field gel electrophoresis (PFGE) has been used successfully to identify outbreaks of Escherichia coli O157:H7 in humans from a variety of food and environmental sources. However, some PFGE patterns appear commonly in surveillance systems, making it more difficult to distinguish between outbreak and sporadic cases based on molecular data alone. In addition, it is unknown whether these common patterns might have unique epidemiological characteristics reflected in their spatial and temporal distributions. Using E. coli O157:H7 surveillance data from Alberta, collected from 2000 to 2002, we investigated whether E. coli O157:H7 with provincial PFGE pattern 8 (national designation ECXAI.0001) clustered in space, time and space–time relative to other PFGE patterns using the spatial scan statistic. Based on our purely spatial and temporal scans using a Bernoulli model, there did not appear to be strong evidence that isolates of E. coli O157:H7 with provincial PFGE pattern 8 are distributed differently from other PFGE patterns. However, we did identify space–time clusters of isolates with PFGE pattern 8, using a Bernoulli model and a space–time permutation model, which included known outbreaks and potentially unrecognized outbreaks or additional outbreak cases. There were differences between the two models in the space–time clusters identified, which suggests that the use of both models could increase the sensitivity of a quantitative surveillance system for identifying outbreaks involving isolates sharing a common PFGE pattern.     

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.     

Reservoir‐Driven Heterogeneous Distribution of Recorded Human Puumala virus Cases in South‐West Germany

Endemic regions for Puumala virus (PUUV) are located in the most affected federal state Baden‐Wuerttemberg, South‐West Germany, where high numbers of notified human hantavirus disease cases have been occurring for a long time. The distribution of human cases in Baden‐Wuerttemberg is, however, heterogeneous, with a high number of cases recorded during 2012 in four districts (H districts) but a low number or even no cases recorded in four other districts (L districts). Bank vole monitoring during 2012, following a beech (Fagus sylvatica) mast year, resulted in the trapping of 499 bank voles, the host of PUUV. Analyses indicated PUUV prevalences of 7–50% (serological) and 1.8–27.5% (molecular) in seven of eight districts, but an absence of PUUV in one L district. The PUUV prevalence differed significantly between bank voles in H and L districts. In the following year 2013, 161 bank voles were trapped, with reduced bank vole abundance in almost all investigated districts except one. In 2013, no PUUV infections were detected in voles from seven of eight districts. In conclusion, the linear modelling approach indicated that the heterogeneous distribution of human PUUV cases in South‐West Germany was caused by different factors including the abundance of PUUV RNA‐positive bank voles, as well as by the interaction of beech mast and the proportional coverage of beech and oak (Quercus spec.) forest per district. These results can aid developing local public health risk management measures and early warning models.     

Evaluation of habitat requirements of small rodents and effectiveness of an ecologically‐based management in a hantavirus‐endemic natural protected area in Argentina

Hantavirus pulmonary syndrome is a severe cardio pulmonary disease transmitted to humans by sylvan rodents found in natural and rural environments. Disease transmission is closely linked to the ecology of animal reservoirs and abiotic factors such as habitat characteristics, season or climatic conditions. The main goals of this research were: to determine the biotic and abiotic factors affecting richness and abundance of rodent species at different spatial scales, to evaluate different methodologies for studying population of small rodents, and to describe and analyze an ecologically‐based rodent management experience in a highly touristic area. A 4‐year study of small rodent ecology was conducted between April 2007 and August 2011 in the most relevant habitats of El Palmar National Park, Argentina. Management involved a wide range of control and prevention measures, including poisoning, culling and habitat modification. A total of 172 individuals of 5 species were captured with a trapping effort of 13 860 traps‐nights (1.24 individuals/100 traps‐nights). Five rodent species were captured, including 2 hantavirus‐host species, Oligoryzomys nigripes and Akodon azarae. Oligoryzomys nigripes, host of a hantavirus that is pathogenic in humans, was the most abundant species and the only one found in all the studied habitats. Our results are inconsistent with the dilution effect hypothesis. The present study demonstrates that sylvan rodent species, including the hantavirus‐host species, have distinct local habitat selection and temporal variation patterns in abundance, which may influence the risk of human exposure to hantavirus and may have practical implications for disease transmission as well as for reservoir management.     

近10年来山东区域NPP时空变化分析

净初级生产力(NPP)可以反映植被的固碳能力,估算区域的NPP对研究区域碳循环和气候变化有重要意义。本研究利用光能利用率模型(CASA)估算了山东省2001-2010年NPP的时空变化,在CASA模型中引入陆面水分指数(LSWI)来替换水分估算模块,并分析了该区域NPP与环境因子之间的关系。研究表明,山东省每年植被固碳量约为3.46×1013 g,其中农田的NPP占了山东省总NPP的75%以上;2001-2010年间,山东省NPP以每年0.7×1012 g的速度增加,主要归因于该区域温度和降水的增加。     

A repeated cross‐sectional study of the epidemiology of Campylobacter and antimicrobial resistant Enterobacteriaceae in free‐living Canada geese in Guelph,Ontario, Canada

From May through October 2016, we conducted a repeated cross‐sectional study examining the effects of temporal, spatial, flock and demographic factors (i.e. juvenile vs. adult) on the prevalence of Campylobacter and antimicrobial resistant Enterobacteriaceae among 344 fresh faecal samples collected from Canada geese (Branta canadensis) from four locations where birds nested in Guelph, Ontario, Canada. The overall prevalence of Campylobacter among all fresh faecal samples was 9.3% and was greatest in the fall when these birds became more mobile following the nesting season. Based on 40 gene comparative genomic fingerprinting (CGF40), the increase in prevalence noted in the fall was matched by an increase in the number of unique CGF40 subtypes identified. Resistance to colistin was detected most commonly, in 6% of Escherichia coli isolates, and was highest in the late summer months. All colistin‐resistant isolates were negative for the mcr‐1 to mcr‐5 genes; a chromosomal resistance mechanism (PmrB) was identified in all of these isolates. The prevalence of samples with E. coli exhibiting multi‐class resistance or extended spectrum beta‐lactamase was low (i.e. <2% of samples). The intra‐class correlation coefficients, estimated from the variance components of multilevel logistic regression models, indicated that the shedding of Campylobacter and antimicrobial resistant E. coli among geese within a flock (i.e. birds collected from the same site on the same day) was moderately correlated. Spatial, temporal, and spatiotemporal clusters identified using the spatial scan statistic, largely supported the findings from our multi‐level models. Salmonella was not isolated from any of the fresh faecal samples collected suggesting that its prevalence in this population of birds was very low.     

White‐Tailed Deer (Odocoileus virginianus) as a Potential Sentinel for Human Lyme Disease in Indiana

We assessed the potential of white‐tailed deer (WTD) (Odocoileus virginianus) to be a sentinel for human cases of Lyme disease (LD) in Indiana using location data from a 3‐year survey of approximately 3400 hunted deer with associated tick Ixodes scapularis and Borrelia burgdorferi (Bb) data. Data on human LD cases at the county level were obtained from the Indiana Department of Health. All data were assigned to county centroids to match the resolution of the LD data before creating optimized trend surfaces for LD incidence, hunted deer count, Ixodes scapularis and Bb prevalence. To determine whether LD was spatially associated with the areas of high densities of deer, deer with Ixodes scapularis and deer with ticks infected with Bb, we used spatial analysis with distance indices (SADIE). The SADIE analysis found significant spatial association between LD and the distribution of three organismal predictor variables, that is, WTD, Ixodes ticks and Bb. Lyme disease incident rate varied between 0.08 cases per 10 000 habitants (Johnson county) and 5.9 cases per 10 000 habitants (Warren county). In conclusion, WTD can be used as an accurate and cost‐effective sentinel for human LD. This method will permit public health workers to identify potentially endemic areas independently of human case reports.     

Multiple‐Aetiology Enteric Infections Involving Non‐O157 Shiga Toxin‐Producing Escherichia coli – FoodNet, 2001–2010

We describe multiple‐aetiology infections involving non‐O157 Shiga toxin‐producing Escherichia coli (STEC) identified through laboratory‐based surveillance in nine FoodNet sites from 2001 to 2010. A multiple‐aetiology infection (MEI) was defined as isolation of non‐O157 STEC and laboratory evidence of any of the other nine pathogens under surveillance or isolation of >1 non‐O157 STEC serogroup from the same person within a 7‐day period. We compared exposures of patients with MEI during 2001–2010 with those of patients with single‐aetiology non‐O157 STEC infections (SEI) during 2008–2009 and with those of the FoodNet population from a survey conducted during 2006–2007. In total, 1870 non‐O157 STEC infections were reported; 68 (3.6%) were MEI; 60 included pathogens other than non‐O157 STEC; and eight involved >1 serogroup of non‐O157 STEC. Of the 68 MEI, 21 (31%) were part of six outbreaks. STEC O111 was isolated in 44% of all MEI. Of patients with MEI, 50% had contact with farm animals compared with 29% (P < 0.01) of persons with SEI; this difference was driven by infections involving STEC O111. More patients with non‐outbreak‐associated MEI reported drinking well water (62%) than respondents in a population survey (19%) (P < 0.01). Drinking well water and having contact with animals may be important exposures for MEI, especially those involving STEC O111.     

Phage and MLVA Typing of Salmonella Enteritidis Isolated from Layers and Humans in Belgium from 2000–2010, A Period in which Vaccination of Laying Hens was Introduced

The aim of the study was to characterize isolates of Salmonella enterica serovar Enteritidis (S. Enteritidis) obtained from humans and layer farms in Belgium collected during 2000–2010. Three periods were compared, namely (i) before implementation of vaccination (2000–2004), (ii) during voluntary vaccination (2005–2006) and (iii) during implementation of the national control program (NCP) for Salmonella including mandatory vaccination against S. Enteritidis (2007–2010). The characteristics compared across time periods were distributions of phage type and multiple‐locus variable number tandem‐repeat assay (MLVA). While PT4 and PT21 were predominantly isolated in Belgium in layers and humans before 2007, a significant reduction of those PTs was observed in both populations in the period 2007–2010. The relative proportion of PT4b, PT21c and PT6c was found to have increased considerably in the layer population since 2007. In the human population, PT8, PT1 and the group of ‘other’ PTs were more frequently isolated compared to the previous periods. When comparing the proportion of the predominant MLVA types Q2 and U2, no significant difference was found between the layer and human population in the three periods and between periods within each category (layer and human). A significant difference in isolate distribution among MLVA clusters I and II was found between human and layer isolates recovered during Period 3 and in the human population between Period 1 and 3. Results suggest that the association between S. Enteritidis in layers and the occurrence of the pathogen in humans changed since implementation of the NCP in 2007.