Stefan Widgren

Q fever infection in dairy cattle herds: increased risk with high wind speed and low precipitation

SUMMARY Ruminants are considered the main reservoir for transmission of Coxiella burnetii (Cb) to humans. The implementation of effective control measures against Cb in ruminants requires knowledge about potential risk factors. The objectives of this study were (i) to describe the spatial distribution of Q fever-infected dairy cattle herds in Sweden, (ii) to quantify the respective contributions of wind and animal movements on the risk of infection, while accounting for other sources of variation, and (iii) to investigate the possible protective effect of precipitation. A total of 1537 bulk milk samples were collected and tested for presence of Cb antibodies. The prevalence of test-positive herds was higher in the south of Sweden. For herds located in areas with high wind speed, open landscape, high animal densities and high temperature, the risk of being infected reached very high values. Because these factors are difficult to control, vaccination could be an appropriate control measure in these areas. Finally, the cumulated precipitation over 1 year was identified as a protective factor.

EpiContactTrace: an R-package for contact tracing during livestock disease outbreaks and for risk-based surveillance

BackgroundDuring outbreak of livestock diseases, contact tracing can be an important part of disease control. Animal movements can also be of relevance for risk-based surveillance and sampling, i.e. both when assessing consequences of introduction or likelihood of introduction. In many countries, animal movement data are collected with one of the major objectives to enable contact tracing. However, often an analytical step is needed to retrieve appropriate information for contact tracing or surveillance.ResultsIn this study, an open source tool was developed to structure livestock movement data to facilitate contact-tracing in real time during disease outbreaks and for input in risk-based surveillance and sampling. The tool, EpiContactTrace, was written in the R-language and uses the network parameters in-degree, out-degree, ingoing contact chain and outgoing contact chain (also called infection chain), which are relevant for forward and backward tracing respectively. The time-frames for backward and forward tracing can be specified independently and search can be done on one farm at a time or for all farms within the dataset. Different outputs are available; datasets with network measures, contacts visualised in a map and automatically generated reports for each farm either in HTML or PDF-format intended for the end-users, i.e. the veterinary authorities, regional disease control officers and field-veterinarians. EpiContactTrace is available as an R-package at the R-project website (http://cran.r-project.org/web/packages/EpiContactTrace/).ConclusionsWe believe this tool can help in disease control since it rapidly can structure essential contact information from large datasets. The reproducible reports make this tool robust and independent of manual compilation of data. The open source makes it accessible and easily adaptable for different needs.

Infection prevention and control interventions in the first outbreak of methicillin-resistant Staphylococcus aureus infections in an equine hospital in Sweden

BackgroundThe first outbreak of methicillin-resistant Staphylococcus aureus (MRSA) infection in horses in Sweden occurred in 2008 at the University Animal Hospital and highlighted the need for improved infection prevention and control. The present study describes interventions and infection prevention control in an equine hospital setting July 2008 - April 2010.MethodThis descriptive study of interventions is based on examination of policy documents, medical records, notes from meetings and cost estimates. MRSA cases were identified through clinical sampling and telephone enquiries about horses post-surgery. Prospective sampling in the hospital environment with culture for MRSA and genotyping of isolates by spa-typing and pulsed-field gel electrophoresis (PFGE) were performed.ResultsInterventions focused on interruption of indirect contact spread of MRSA between horses via staff and equipment and included: Temporary suspension of elective surgery; and identification and isolation of MRSA-infected horses; collaboration was initiated between authorities in animal and human public health, human medicine infection control and the veterinary hospital; extensive cleaning and disinfection was performed; basic hygiene and cleaning policies, staff training, equipment modification and interior renovation were implemented over seven months.Ten (11%) of 92 surfaces sampled between July 2008 and April 2010 tested positive for MRSA spa-type 011, seven of which were from the first of nine sampling occasions. PFGE typing showed the isolates to be the outbreak strain (9 of 10) or a closely related strain. Two new cases of MRSA infection occurred 14 and 19 months later, but had no proven connections to the outbreak cases.ConclusionsCollaboration between relevant authorities and the veterinary hospital and formation of an infection control committee with an executive working group were required to move the intervention process forward. Support from hospital management and the dedication of staff were essential for the development and implementation of new, improved routines. Demonstration of the outbreak strain in the environment was useful for interventions such as improvement of cleaning routines and interior design, and increased compliance with basic hygienic precautions. The interventions led to a reduction in MRSA-positive samples and the outbreak was considered curbed as no new cases occurred for over a year.

Longitudinal observational study over 38 months of verotoxigenic Escherichia coli O157:H7 status in 126 cattle herds

Verotoxigenic Escherichia coli O157:H7 (VTEC O157:H7) is an important zoonotic pathogen capable of causing infections in humans, sometimes with severe symptoms such as hemorrhagic colitis and hemolytic uremic syndrome (HUS). It has been reported that a subgroup of VTEC O157:H7, referred to as clade 8, is overrepresented among HUS cases. Cattle are considered to be the main reservoir of VTEC O157:H7 and infected animals shed the bacteria in feces without showing clinical signs of disease. The aims of the present study were: (1) to better understand how the presence of VTEC O157:H7 in the farm environment changes over an extended period of time, (2) to investigate potential risk factors for the presence of the bacteria, and (3) describe the distribution of MLVA types and specifically the occurrence of the hypervirulent strains (clade 8 strains) of VTEC O157:H7. The farm environment of 126 cattle herds in Sweden were sampled from October 2009 to December 2012 (38 months) using pooled pat and overshoe sampling. Each herd was sampled, on average, on 17 occasions (range=1-20; median=19), at intervals of 64 days (range=7-205; median=58). Verotoxigenic E. coli O157:H7 were detected on one or more occasions in 53% of the herds (n=67). In these herds, the percentage of positive sampling occasions ranged from 6% to 72% (mean=19%; median=17%). Multi-locus variable number tandem repeat analysis (MLVA) typing was performed on isolates from infected herds to identify hypervirulent strains (clade 8). Clustering of MLVA profiles yielded 35 clusters and hypervirulent strains were found in 18 herds; the same cluster was often identified on consecutive samplings and in nearby farms. Using generalized estimating equations, an association was found between the probability of detecting VTEC O157:H7 and status at the preceding sampling, season, herd size, infected neighboring farms and recent introduction of animals. This study showed that the bacteria VTEC O157:H7 were spontaneously cleared from the farm environment in most infected herds over time, and key factors were identified to prevent the spread of VTEC O157:H7 between cattle herds.

Environmental sampling for evaluating verotoxigenic Escherichia coli O157: H7 status in dairy cattle herds.

Verotoxigenic Escherichia coli O157:H7 is a zoonotic bacterial pathogen capable of causing severe disease in human beings. Cattle are considered to be the main reservoir of the bacterium. The objective of the current study was to compare environmental sampling (consisting of dust, overshoe, and pooled pat samples) with pooled, individual fecal sampling for determining the cattle herd status under field conditions in naturally infected dairy herds. Thirty-one dairy cattle farms in Sweden, where verotoxigenic E. coli O157:H7 had been previously detected, were visited. On each farm, dust, overshoe, and pooled pat sampling were performed in each of 3 different age categories: calves, young stock, and adults. In addition, up to 140 individual fecal samples were collected and analyzed as pooled samples. In total, 3,763 individual fecal and 270 environmental samples were collected and analyzed for the presence of verotoxigenic E. coli O157:H7. Overshoe sampling, alone or in combination with dust and pooled pat sampling, correctly classified 20 of the 24 (0.83, 95% CI: 0.63–0.95) herds detected with at least 1 positive pool. On 1 farm, a dust sample was positive although all other samples were negative. In 6 of the 31 farms, the bacteria could not be detected in any of the individual fecal samples or in the environmental samples. The results establish that environmental sampling is a reliable method for identifying cattle herds with animals shedding verotoxigenic E. coli O157:H7.

A novel method to identify herds with an increased probability of disease introduction due to animal trade.

In the design of surveillance, there is often a desire to target high risk herds. Such risk-based approaches result in better allocation of resources and improve the performance of surveillance activities. For many contagious animal diseases, movement of live animals is a main route of transmission, and because of this, herds that purchase many live animals or have a large contact network due to trade can be seen as a high risk stratum of the population. This paper presents a new method to assess herd disease risk in animal movement networks. It is an improvement to current network measures that takes direction, temporal order, and also movement size and probability of disease into account. In the study, the method was used to calculate a probability of disease ratio (PDR) of herds in simulated datasets, and of real herds based on animal movement data from dairy herds included in a bulk milk survey for Coxiella burnetii. Known differences in probability of disease are easily incorporated in the calculations and the PDR was calculated while accounting for regional differences in probability of disease, and also by applying equal probability of disease throughout the population. Each herds increased probability of disease due to purchase of animals was compared to both the average herd and herds within the same risk stratum. The results show that the PDR is able to capture the different circumstances related to disease prevalence and animal trade contact patterns. Comparison of results based on inclusion or exclusion of differences in risk also highlights how ignoring such differences can influence the ability to correctly identify high risk herds. The method shows a potential to be useful for risk-based surveillance, in the classification of herds in control programmes or to represent influential contacts in risk factor studies.

Data-driven network modelling of disease transmission using complete population movement data: spread of VTEC O157 in Swedish cattle.

European Union legislation requires member states to keep national databases of all bovine animals. This allows for disease spread models that includes the time-varying contact network and population demographic. However, performing data-driven simulations with a high degree of detail are computationally challenging. We have developed an efficient and flexible discrete-event simulator SimInf for stochastic disease spread modelling that divides work among multiple processors to accelerate the computations. The model integrates disease dynamics as continuous-time Markov chains and livestock data as events. In this study, all Swedish livestock data (births, movements and slaughter) from July 1st 2005 to December 31st 2013 were included in the simulations. Verotoxigenic Escherichia coli O157:H7 (VTEC O157) are capable of causing serious illness in humans. Cattle are considered to be the main reservoir of the bacteria. A better understanding of the epidemiology in the cattle population is necessary to be able to design and deploy targeted measures to reduce the VTEC O157 prevalence and, subsequently, human exposure. To explore the spread of VTEC O157 in the entire Swedish cattle population during the period under study, a within- and between-herd disease spread model was used. Real livestock data was incorporated to model demographics of the population. Cattle were moved between herds according to real movement data. The results showed that the spatial pattern in prevalence may be due to regional differences in livestock movements. However, the movements, births and slaughter of cattle could not explain the temporal pattern of VTEC O157 prevalence in cattle, despite their inherently distinct seasonality.

Vetsyn: An R package for veterinary syndromic surveillance.

A recent inventory showed that several countries are exploring varied types of animal health sources for the development of veterinary syndromic surveillance (VSS), however, few systems have documented success after the phase of development or exploratory analysis of data. We suggest there are three main challenges in the current development of animal syndromic surveillance: (i) the lack of standards in disease recording and classification; (ii) the development of statistical methods appropriate to deal with animal data; and (iii) the creation of ready-to-use tools that employ these statistical methods. We address the latter two challenges and present an R package - vetsyn - which covers the steps of VSS implementation from classified data to interface. Detailed tutorials are included with the package. The goal is to provide ready-to-use codes to automatize the process of converting pre-classified animal health data into epidemiological information. The package functions are illustrated using real data and simulated outbreaks. Functions to monitor data daily and weekly are available. The main innovation offered by the package is ability to manage data streams, analyses, alarms and user interface in a continuous flow. We expect that this will facilitate the implementation of syndromic surveillance systems by veterinary epidemiologists and surveillance practitioners.

Spatio-temporal modelling of verotoxigenic Escherichia coli O157 in cattle in Sweden: exploring options for control

A spatial data-driven stochastic model was developed to explore the spread of verotoxigenic Escherichia coli O157 (VTEC O157) by livestock movements and local transmission among neighbouring holdings in the complete Swedish cattle population. Livestock data were incorporated to model the time-varying contact network between holdings and population demographics. Furthermore, meteorological data with the average temperature at the geographical location of each holding was used to incorporate season. The model was fitted against observed data and extensive numerical experiments were conducted to investigate the model’s response to control strategies aimed at reducing shedding and susceptibility, as well as interventions informed by network measures. The results showed that including local spread and season improved agreement with prevalence studies. Also, control strategies aimed at reducing the average shedding rate were more efficient in reducing the VTEC O157 prevalence than strategies based on network measures. The methodology presented in this study could provide a basis for developing disease surveillance on regional and national scales, where observed data are combined with readily available high-resolution data in simulations to get an overview of potential disease spread in unobserved regions.

Mechanistic modelling of interventions against spread of livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) within a Danish farrow-to-finish pig herd

Knowledge on successful interventions against livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) within pig herds is sparse. In situations like this, a mechanistic simulation model can be a valuable tool for assessing the effect of potential intervention strategies, and prioritising which should be tested in the field. We have simulated on-farm interventions in a farrow-to-finish pig herd, with a previously published LA-MRSA spread model, within four different areas: 1) Reduced antimicrobial consumption, 2) Reduced number of pigs within each section, 3) Reduced mixing of pigs, and 4) Improved internal biosecurity. To model a decrease in the selective pressure, the transmission rates were reduced after LA-MRSA had become fully established within a herd, which resulted in a marked decrease in the prevalence within all stable units. However, LA-MRSA rarely disappeared completely from the herd; this was only observed in scenarios where the transmission rates were reduced to ≤ 30% of the original level. While changes in antimicrobial consumption patterns might be a very important step towards reducing the spread of LA-MRSA, the simulation results indicate that it may need to be paired with other preventive or intervention measures. Reducing the number of pigs within each section, reducing mixing of pigs, or improving internal biosecurity after LA-MRSA had become established within the herd only resulted in marginal changes in the median prevalence within the herd. However, these factors might be important in relation to being able to achieve or maintain a low level of antimicrobial consumption, and thus still indirectly influence the LA-MRSA prevalence within the herd. The results of a sensitivity analysis indicated the assumptions regarding the existence of pigs persistently shedding MRSA have a noticeable influence on the model results. The assumptions regarding transmission from sow to offspring at the day of birth also had a considerable influence on the MRSA prevalence within the farrowing unit but did not cause any marked changes in the simulated effect of interventions. Effects might differ between different farm types contaminated in different levels and this simulation study highlights a strong need for more knowledge from on-farm trials.