E.A.J. Fischer

Dynamics of shiga-toxin producing Escherichia coli (STEC) and their virulence factors in cattle

Starting at birth, twenty Holstein calves were housed individually, in groups of five and finally in one large freestall while fecal samples were collected weekly for 25 weeks. From each sample, twenty isolates of Escherichia coli were screened for 6 virulence markers including shiga-toxin 1, 2, intimin, enterohemolysin, the fimbrial antigen efa1 and the adhesin saa. Dynamic models of transmission of E. coli were used to model the transmission of different virulotypes between calves and the loss of the same virulotypes from the calves. It was found that, once E. coli encoding shiga-toxins in combination with enterohemolysin were transmitted and established in a calf, they tended to be eliminated less efficiently compared to E. coli without this combination of virulence markers. It was concluded that the presence of certain combinations of virulence markers coincided with persistence of E. coli in the bovine gastrointestinal tract. In addition, the combinations of stx with either eae or ehxA in E. coli have a greater impact on the loss rates than on the transmission rates.

Mathematical Modelling of Leprosy and Its Control

Leprosy or Hansens disease is an infectious disease caused by the bacterium Mycobacterium leprae. The annual number of new leprosy cases registered worldwide has remained stable over the past years at over 200,000. Early case finding and multidrug therapy have not been able interrupt transmission completely. Elimination requires innovation in control and sustained commitment. Mathematical models can be used to predict the course of leprosy incidence and the effect of intervention strategies. Two compartmental models and one individual-based model have been described in the literature. Both compartmental models investigate the course of leprosy in populations and the long-term impact of control strategies. The individual-based model focusses on transmission within households and the impact of case finding among contacts of new leprosy patients. Major improvement of these models should result from a better understanding of individual differences in exposure to infection and developing leprosy after exposure. Most relevant are contact heterogeneity, heterogeneity in susceptibility and spatial heterogeneity. Furthermore, the existing models have only been applied to a limited number of countries. Parameterization of the models for other areas, in particular those with high incidence, is essential to support current initiatives for the global elimination of leprosy. Many challenges remain in understanding and dealing with leprosy. The support of mathematical models for understanding leprosy epidemiology and supporting policy decision making remains vital.

A spatiotemporal model to assess the introduction risk of African horse sickness by import of animals and vectors in France

BackgroundAfrican horse sickness (AHS) is a major, Culicoides-borne viral disease in equines whose introduction into Europe could have dramatic consequences. The disease is considered to be endemic in sub-Saharan Africa. Recent introductions of other Culicoides-borne viruses (bluetongue and Schmallenberg) into northern Europe have highlighted the risk that AHS may arrive in Europe as well. The aim of our study was to provide a spatiotemporal quantitative risk model of AHS introduction into France. The study focused on two pathways of introduction: the arrival of an infectious host (PW-host) and the arrival of an infectious Culicoides midge via the livestock trade (PW-vector). The risk of introduction was calculated by determining the probability of an infectious animal or vector entering the country and the probability of the virus then becoming established: i.e., the virus’s arrival in France resulting in at least one local equine host being infected by one local vector. This risk was assessed using data from three consecutive years (2010 to 2012) for 22 regions in France.ResultsThe results of the model indicate that the annual risk of AHS being introduced to France is very low but that major spatiotemporal differences exist. For both introduction pathways, risk is higher from July to October and peaks in July. In general, regions with warmer climates are more at risk, as are colder regions with larger equine populations; however, regional variation in animal importation patterns (number and species) also play a major role in determining risk. Despite the low probability that AHSV is present in the EU, intra-EU trade of equines contributes most to the risk of AHSV introduction to France because it involves a large number of horse movements.ConclusionIt is important to address spatiotemporal differences when assessing the risk of ASH introduction and thus also when implementing efficient surveillance efforts. The methods and results of this study may help develop surveillance techniques and other risk reduction measures that will prevent the introduction of AHS or minimize AHS’ potential impact once introduced, both in France and the rest of Europe.

Controlling highly pathogenic avian influenza outbreaks : An epidemiological and economic model analysis

Outbreaks of highly pathogenic avian influenza (HPAI) can cause large losses for the poultry sector and for animal disease controlling authorities, as well as risks for animal and human welfare. In the current simulation approach epidemiological and economic models are combined to compare different strategies to control highly pathogenic avian influenza in Dutch poultry flocks. Evaluated control strategies are the minimum EU strategy (i.e., culling of infected flocks, transport regulations, tracing and screening of contact flocks, establishment of protection and surveillance zones), and additional control strategies comprising pre-emptive culling of all susceptible poultry flocks in an area around infected flocks (1 km, 3 km and 10 km) and emergency vaccination of all flocks except broilers around infected flocks (3 km). Simulation results indicate that the EU strategy is not sufficient to eradicate an epidemic in high density poultry areas. From an epidemiological point of view, this strategy is the least effective, while pre-emptive culling in 10 km radius is the most effective of the studied strategies. But these two strategies incur the highest costs due to long duration (EU strategy) and large-scale culling (pre-emptive culling in 10 km radius). Other analysed pre-emptive culling strategies (i.e., in 1 km and 3 km radius) are more effective than the analysed emergency vaccination strategy (in 3 km radius) in terms of duration and size of the epidemics, despite the assumed optimistic vaccination capacity of 20 farms per day. However, the total costs of these strategies differ only marginally. Extending the capacity for culling substantially reduces the duration, size and costs of the epidemic. This study demonstrates the strength of combining epidemiological and economic model analysis to gain insight in a range of consequences and thus to serve as a decision support tool in the control of HPAI epidemics.

Dynamics of CMY-2 producing E. coli in a broiler parent flock

Extended-spectrum β-lactamase and plasmid mediated AmpC β-lactamase (ESBL/pAmpC) producing bacteria are resistant to Extended Spectrum Cephalosporins (ESC), and are present in all levels of the broiler production chain. We determined the prevalence, concentration, and persistence of ESBL/pAmpC-Escherichia coli in a broiler parent flock during the rearing and laying period. One-day old chickens were housed in four separate pens. Until week 33 no antibiotics or coccidiostatics were used. During rearing 57 chickens in each pen (n=228), and in the laying period two groups of 33 chickens were individually sampled (n=66). Environmental samples were taken from week 16 onwards. ESBL/pAmpC-E. coli presence was determined by selective culturing. In the samples of week 16-19 the concentration of ESBL/pAmpC-E. coli was determined. All ESC-resistant isolates found were positive for pAmpC gene blaCMY-2 located on IncA/C plasmids, in several E. coli MLST types. CMY-2-E. coli prevalence decreased from 91% (95%CI 86-94%) at day 7 (week 1) to 0% (95%CI 0-5%) in week 21. However, CMY-2-E. coli remained present in the environmental samples during the whole study. CMY-2-E. coli concentration varied between detection limit (<10^3) and 2·10^4 cfu/g faeces. The sharp reduction of CMY-2-E. coli in this broiler parent flock in absence of antibiotics suggests a selective disadvantage of blaCMY-2 on IncA/C plasmids on animal level. The underlying mechanism should be studied further as this may provide new insights on how to reduce ESBL/pAmpC prevalence and transmission in the broiler production chain.

Host and Environmental Factors Affecting the Intestinal Microbiota in Chickens

The initial development of intestinal microbiota in poultry plays an important role in production performance, overall health and resistance against microbial infections. Multiplexed sequencing of 16S ribosomal RNA gene amplicons is often used in studies, such as feed intervention or antimicrobial drug trials, to determine corresponding effects on the composition of intestinal microbiota. However, considerable variation of intestinal microbiota composition has been observed both within and across studies. Such variation may in part be attributed to technical factors, such as sampling procedures, sample storage, DNA extraction, the choice of PCR primers and corresponding region to be sequenced, and the sequencing platforms used. Furthermore, part of this variation in microbiota composition may also be explained by different host characteristics and environmental factors. To facilitate the improvement of design, reproducibility and interpretation of poultry microbiota studies, we have reviewed the literature on confounding factors influencing the observed intestinal microbiota in chickens. First, it has been identified that host-related factors, such as age, sex, and breed, have a large effect on intestinal microbiota. The diversity of chicken intestinal microbiota tends to increase most during the first weeks of life, and corresponding colonization patterns seem to differ between layer- and meat-type chickens. Second, it has been found that environmental factors, such as biosecurity level, housing, litter, feed access and climate also have an effect on the composition of the intestinal microbiota. As microbiota studies have to deal with many of these unknown or hidden host and environmental variables, the choice of study designs can have a great impact on study outcomes and interpretation of the data. Providing details on a broad range of host and environmental factors in articles and sequence data repositories is highly recommended. This creates opportunities to combine data from different studies for meta-analysis, which will facilitate scientific breakthroughs toward nutritional and husbandry associated strategies to improve animal health and performance.

Competitive exclusion reduces transmission and excretion of extended-spectrum β-lactamase producing Escherichia coli in broilers

ABSTRACT Extended-spectrum β-lactamases (ESBLs) and plasmid-mediated AmpC β-lactamases (pAmpC) are enzymes able to hydrolyze a large variety of β-lactam antibiotics, including third-generation cephalosporins and monobactams. Broilers and broiler meat products can be highly contaminated with ESBL- and pAmpC-producing Escherichia coli strains, also known as extended-spectrum cephalosporin (ESC)-resistant E. coli strains, and can be a source for human infections. As few data on interventions to reduce the presence of ESC-resistant E. coli in broilers are available, we used transmission experiments to examine the role of competitive exclusion (CE) on reducing transmission and excretion in broilers. A broiler model to study the transmission of ESC-resistant E. coli was set up. Day-old chickens were challenged with an ESBL-producing E. coli strain isolated from healthy broilers in the Netherlands. Challenged and not challenged chicks were housed together in pairs or in groups, and ESBL-producing E. coli transmission was monitored via selective culturing of cloacal swab specimens. We observed a statistically significant reduction in both the transmission and excretion of ESBL-producing E. coli in chicks treated with the probiotic flora before E. coli challenge compared to the transmission and excretion in untreated controls. In conclusion, our results support the use of competitive exclusion as an intervention strategy to control ESC-resistant E. coli in the field. IMPORTANCE Extended-spectrum β-lactamases (ESBLs) and plasmid-mediated AmpC β-lactamases are a primary cause of resistance to β-lactam antibiotics among members of the family Enterobacteriaceae in humans, animals, and the environment. Food-producing animals are not exempt from this, with a high prevalence being seen in broilers, and there is evidence pointing to a possible foodborne source for human contamination. We investigated the effect of administration of a commercial probiotic product as an intervention to reduce the amount of ESBL-producing Escherichia coli in broilers. Our results showed a substantial reduction in the level of colonization of broiler intestines by ESBL-producing E. coli after administration of commercial probiotic product. The protective effect provided by these probiotics could be implemented on a larger scale in poultry production. Reductions in the levels of ESBL-producing Enterobacteriaceae in the food chain would considerably benefit public health.

Quantitative analysis of the probability of introducing equine encephalosis virus (EEV) into The Netherlands

Equine encephalosis is a midge-borne viral disease of equines caused by equine encephalosis virus (EEV, Orbivirus, Reoviridae), and closely related to African horse sickness virus (AHSV). EEV and AHSV share common vectors and show similar transmission patterns. Until now EEV has caused outbreaks in Africa and Israel. This study aimed to provide insight in the probability of an EEV outbreak in The Netherlands caused by infected vectors or hosts, the contribution of potential source areas (risk regions) to this probability, and the effectiveness of preventive measures (sanitary regimes). A stochastic risk model constructed for risk assessment of AHSV introduction was adapted to EEV. Source areas were categorized in risk regions (high, low, and very low risk) based on EEV history and the presence of competent vectors. Two possible EEV introduction pathways were considered: importation of infected equines and importation of infected vectors along with their vertebrate hosts. The probability of EEV introduction (PEEV) was calculated by combining the probability of EEV release by either pathway and the probability of EEV establishment. The median current annual probability of EEV introduction by an infected equine was estimated at 0.012 (90% uncertainty interval 0.002-0.020), and by an infected vector at 4.0 10(-5) (90% uncertainty interval 5.3 10(-6)-2.0 10(-4)). Equines from high risk regions contributed most to the probability of EEV introduction with 74% on the EEV introduction by equines, whereas low and very low risk regions contributed 18% and 8%, respectively. International movements of horses participating in equestrian events contributed most to the probability of EEV introduction by equines from high risk regions (86%), but also contributed substantially for low and very low risk regions with 47% and 56%. The probability of introducing EEV into The Netherlands is much higher than the probability of introducing AHSV with equines from high risk countries contributing most. The introduction by an infected equine is the most likely pathway. Control measures before exportation of equines showed to have a strong mitigating effect on the probability of EEV introduction. The risk of EEV outbreaks should be taken into account when altering these import regulations.

Modelling the Innate Immune Response against Avian Influenza Virus in Chicken.

At present there is limited understanding of the host immune response to (low pathogenic) avian influenza virus infections in poultry. Here we develop a mathematical model for the innate immune response to avian influenza virus in chicken lung, describing the dynamics of viral load, interferon-α, -β and -γ, lung (i.e. pulmonary) cells and Natural Killer cells. We use recent results from experimentally infected chickens to validate some of the model predictions. The model includes an initial exponential increase of the viral load, which we show to be consistent with experimental data. Using this exponential growth model we show that the duration until a given viral load is reached in experiments with different inoculation doses is consistent with a model assuming a linear relationship between initial viral load and inoculation dose. Subsequent to the exponential-growth phase, the model results show a decline in viral load caused by both target-cell limitation as well as the innate immune response. The model results suggest that the temporal viral load pattern in the lungs displayed in experimental data cannot be explained by target-cell limitation alone. For biologically plausible parameter values the model is able to qualitatively match to data on viral load in chicken lungs up until approximately 4 days post infection. Comparison of model predictions with data on CD107-mediated degranulation of Natural Killer cells yields some discrepancy also for earlier days post infection.