Comparative Risk Analysis of Two Culicoides-Borne Diseases in Horses: Equine Encephalosis More Likely to Enter France than African Horse Sickness.

African horse sickness (AHS) and equine encephalosis (EE) are Culicoides-borne viral diseases that could have the potential to spread across Europe if introduced, thus being potential threats for the European equine industry. Both share similar epidemiology, transmission patterns and geographical distribution. Using stochastic spatiotemporal models of virus entry, we assessed and compared the probabilities of both viruses entering France via two pathways: importation of live-infected animals or importation of infected vectors. Analyses were performed for three consecutive years (2010-2012). Seasonal and regional differences in virus entry probabilities were the same for both diseases. However, the probability of EE entry was much higher than the probability of AHS entry. Interestingly, the most likely entry route differed between AHS and EE: AHS has a higher probability to enter through an infected vector and EE has a higher probability to enter through an infectious host. Consequently, different effective protective measures were identified by 'what-if' scenarios for the two diseases. The implementation of vector protection on all animals (equine and bovine) coming from low-risk regions before their importation was the most effective in reducing the probability of AHS entry. On the other hand, the most significant reduction in the probability of EE entry was obtained by the implementation of quarantine before import for horses coming from both EU and non-EU countries. The developed models can be useful to implement risk-based surveillance.

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, -ß 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.

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

BACKGROUND: African 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. RESULTS: The 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. CONCLUSION: It 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.

Derivation of a Floquet formalism within a natural framework.

Many biological systems experience a periodic environment. Floquet theory is a mathematical tool to deal with such time periodic systems. It is not often applied in biology, because linkage between the mathematics and the biology is not available. To create this linkage, we derive the Floquet theory for natural systems. We construct a framework, where the rotation of the Earth is causing the periodicity. Within this framework the angular momentum operator is introduced to describe the Earth's rotation. The Fourier operators and the Fourier states are defined to link the rotation to the biological system. Using these operators, the biological system can be transformed into a rotating frame in which the environment becomes static. In this rotating frame the Floquet solution can be derived. Two examples demonstrate how to apply this natural framework.

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.

MUSIDH, multiple use of simulated demographic histories, a novel method to reduce computation time in microsimulation models of infectious diseases.

Microsimulation of infectious diseases requires simulation of many life histories of interacting individuals. In particular, relatively rare infections such as leprosy need to be studied in very large populations. Computation time increases disproportionally with the size of the simulated population. We present a novel method, MUSIDH, an acronym for multiple use of simulated demographic histories, to reduce computation time. Demographic history refers to the processes of birth, death and all other demographic events that should be unrelated to the natural course of an infection, thus non-fatal infections. MUSIDH attaches a fixed number of infection histories to each demographic history, and these infection histories interact as if being the infection history of separate individuals. With two examples, mumps and leprosy, we show that the method can give a factor 50 reduction in computation time at the cost of a small loss in precision. The largest reductions are obtained for rare infections with complex demographic histories.

Social distance and spatial distance are not the same, observations on the use of GIS in leprosy epidemiology.

Contacts of leprosy patients have a higher risk of developing clinical leprosy. Being a contact is defined socially, but with the introduction of geographical information systems (GIS) in infectious disease epidemiology, it is necessary to relate spatial distance to social distance. We measured the distances between patients and their socially defined contacts in northwest Bangladesh. Contact categories differ in mean distance to the index patients. Sixty-seven per cent of the high-risk contacts lived within 10 metres (m), while all low-risk contacts lived >10 m from the index patient. Classification based on intervals of spatial distance creates categories that contain contacts of different socially defined categories, illustrated by a category of people living between 10 m and 20 m consisting of 47% of high-risk contacts and 52% low-risk contacts. Classification of contacts based on the spatial distance, as performed with GIS techniques, produces other groups than with social definitions.

Stochastic efficiency analysis of bovine tuberculosis-surveillance programs in the Netherlands.

We constructed a stochastic bio-economic model to determine the optimal cost-efficient surveillance program for bovine tuberculosis. The surveillance programs differed in combinations of one or more detection methods and/or sampling frequency. Stochastic input variables in the epidemiological module described the dynamics of infection and the probability of detection. By means of an efficiency frontier, the trade-off between the expected cost and the epidemiological risk parameter relating to the outbreak size was evaluated. The surveillance scheme based on visual inspection of lesions on carcasses at slaughter was optimal given the current prevalence of the disease in the Netherlands if the objective was to minimise the expected costs. However, the efficient set also included two other schemes: slaughterhouse inspection in combination with GAMMA-interferon testing of blood samples and slaughterhouse inspection in combination with two-stage tuberculin testing. The choice ultimately will depend on the risk attitude of the decision-maker; a more-stringent surveillance scheme will be enforced if the expected outbreak size is to be constrained. In future scenarios, ELISA testing of bulk-tank milk in combination with the current slaughterhouse inspection procedure would outperform the surveillance scheme of solely slaughterhouse inspection if ELISA testing of bulk-tank milk becomes feasible.

Evaluation of surveillance strategies for bovine tuberculosis (Mycobacterium bovis) using an individual based epidemiological model.

The Netherlands holds the bovine tuberculosis-free (BTB-free) status according to European Union standards, but in recent years small outbreaks of the infection have occurred. After the last outbreak in 1999 with 10 infected herds the question raised if the current surveillance system, visual inspection of carcasses at the slaughterhouse, is efficient enough to detect infected cattle in time and to maintain the official BTB-free status. Through epidemiological modelling, the risk of a major outbreak is quantified, using one of six surveillance strategies. These are the currently used visual inspection of carcasses at the slaughterhouse (SL), the ELISA test on blood samples of carcasses at the slaughterhouse (ELISA-B), the gamma-interferon test on blood samples of carcasses at the slaughterhouse (GAMMA-B), comparative tuberculination of the herd (CT), the combined method of single and comparative tuberculination of the herd (ST+CT) and the ELISA test on samples of bulk milk (ELISA-M). Test frequency of the last three methods was varied as well. A stochastic individual based model (IBM) was developed to simulate a chain of infected herds, where each individual animal is followed in time. The model mimics the nation-wide situation after the introduction of one infected animal into one herd. BTB-transmission is simulated with an S-E(1)-E(2)-I state transition model. Output is time until detection of the infection, prevalence in the detected herd and the number of infected herds at the time of detection. For the assessment 500 simulations were used, representing 500 BTB-introductions. Model robustness to parameter values was analysed with Monte Carlo elasticity analysis, for which 1000 simulations were used. Results of median time until detection and median number of infected farms at detection for SL (302 weeks and seven farms) were in agreement with estimates from an outbreak in the Netherlands in 1999. ELISA-B and GAMMA-B performed better than SL with a much lower median time until detection (189 and 97 weeks, respectively). The results for the tuberculination methods (ST+CT and CT) and ELISA-M depended heavily on the frequency in which the tests were performed. The tuberculination methods ST+CT and CT yield comparable results and detect the infection sooner than SL, also at the lowest tested frequency of once in 5 years. ELISA-M is comparable with SL at frequencies of once in 4 or 5 years, and this test works well at frequencies of once a year or higher. Our study results are used for an economical optimisation analysis of the six surveillance strategies.

Bayesian networks of BI-RADStrade mark descriptors for breast lesion classification.

We investigated Bayesian network structure learning and probability estimation from mammographic feature data in order to classify breast lesions into different pathological categories. We compared the learned networks to naive Bayes classifiers, which are similar to the expert systems previously investigated for breast lesion classification. The learned network structures reflect the difference in the classification of biopsy outcome and the invasiveness of malignant lesions for breast masses and microcalcifications. The difference between masses and microcalcifications should be taken into consideration when interpreting systems for automatic pathological classification of breast lesions. The difference may also affect use of these systems for tasks such as estimating the sampling error of biopsy.

Integrated health care: passing fad or lasting legacy?

The breakup of several integrated delivery systems (IDSs), and a continuing focus on the failures of many of these organizations to live up to expectations, suggests that integration may be a passing trend. Nonetheless, some systems, particularly those driven by multispecialty clinics, are achieving considerable marketplace success. Integrated systems that base their strategies on delivering value-added services to patients and healthcare purchasers still appear viable. Strategies typically used by IDSs include developing primary care networks, gainsharing with or owning health plans, reducing clinical variation, demonstrating high quality, cutting costs, and developing a seamless system of care. Primary care strategies are especially controversial given the fact that most hospital-affiliated primary care practices are losing money. However, research indicates that primary network development is one of the strategies that adds the most value for consumers and, thus, may be assumed to be of particular benefit to IDSs. Strategies aimed at reducing clinical variation can be expected to reap huge long-term benefits.

Physician leaders in integrated delivery.

It's common to hear the analogy comparing organizing physicians to "herding cats." Actual practice proves the adage false. Physicians are taking leadership roles in the formation of integrated systems across the country. Their input is proving invaluable. Based on case studies of integrated systems, the authors answer commonly asked questions about physician leaders, including: Should physician leaders be specilists? Should they continue to practice? and What will expensive physicians do to our administrative overhead?