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1.
The aim of this paper was to explore the effect of genetic heterogeneity in host resistance to infection on the population-level risks and outcomes of epidemics. This was done using a stochastic epidemiological model in which the model parameters were assumed to be genetically controlled traits of the host. A finite locus model was explored, with a gene controlling the transmission coefficient (i.e., host susceptibility to infection) and a gene controlling the recovery period. Both genes were simulated to have 2 alleles with underlying additive or dominance inheritance and an independent assortment of alleles. The model was parameterized for a viral pig disease (transmissible gastroenteritis), and complete homogeneous mixing among genotypes was assumed. Mean population genotype dramatically affected epidemic outcomes, and subtle effects of heterogeneity on epidemic properties were also observed. Genetic variation in the transmission coefficient led to probabilities of epidemics occurring that were slightly greater than expected, but genetic variation in the recovery rate had no such effect. Epidemics were generally less severe in genetically heterogeneous populations than expected from the constituent subpopulations. Furthermore, the genotype of the initial infected animal had a marked effect on epidemic probabilities, particularly when genetic variation was for recovery rate. The results of this model provide useful information to determine the optimum population structures and to exploit genetic variation in resistance to infection. Applications of the proposed model in genetically heterogeneous populations for identifying practical disease management strategies are also discussed. 相似文献
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ABSTRACT: For the past decade, the Food and Agriculture Organization of the United Nations has been working toward eradicating rinderpest through vaccination and intense surveillance by 2012. Because of the potential severity of a rinderpest epidemic, it is prudent to prepare for an unexpected outbreak in animal populations. There is no immunity to the disease among the livestock or wildlife in the United States (US). If rinderpest were to emerge in the US, the loss in livestock could be devastating. We predict the potential spread of rinderpest using a two-stage model for the spread of a multi-host infectious disease among agricultural animals in the US. The model incorporates large-scale interactions among US counties and the small-scale dynamics of disease spread within a county. The model epidemic was seeded in 16 locations and there was a strong dependence of the overall epidemic size on the starting location. The epidemics were classified according to overall size into small epidemics of 100 to 300 animals (failed epidemics), epidemics infecting 3 000 to 30 000 animals (medium epidemics), and the large epidemics infecting around one million beef cattle. The size of the rinderpest epidemics were directly related to the origin of the disease and whether or not the disease moved into certain key counties in high-livestock-density areas of the US. The epidemic size also depended upon response time and effectiveness of movement controls. 相似文献
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We formulate a stochastic, spatial, discrete-time model of viral "Susceptible, Exposed, Infectious, Recovered" animal epidemics and apply it to an avian influenza epidemic in Pennsylvania in 1983-84. Using weekly data for the number of newly infectious cases collected during the epidemic, we find estimates for the latent period of the virus and the values of two parameters within the transmission kernel of the model. These data are then jackknifed on a progressive weekly basis to show how our estimates can be applied to an ongoing epidemic to generate continually improving values of certain epidemic parameters. 相似文献
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A stochastic model describing disease transmission dynamics for a microparasitic infection in a structured domestic animal population is developed and applied to hypothetical epidemics on a pig farm. Rational decision making regarding appropriate control strategies for infectious diseases in domestic livestock requires an understanding of the disease dynamics and risk profiles for different groups of animals. This is best achieved by means of stochastic epidemic models. Methodologies are presented for 1) estimating the probability of an epidemic, given the presence of an infected animal, whether this epidemic is major (requires intervention) or minor (dies out without intervention), and how the location of the infected animal on the farm influences the epidemic probabilities; 2) estimating the basic reproductive ratio, R0 (i.e., the expected number of secondary cases on the introduction of a single infected animal) and the variability of the estimate of this parameter; and 3) estimating the total proportion of animals infected during an epidemic and the total proportion infected at any point in time. The model can be used for assessing impact of altering farm structure on disease dynamics, as well as disease control strategies, including altering farm structure, vaccination, culling, and genetic selection. 相似文献
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The purpose of this work was to study the epidemiology of feline herpes virus (FHV), which causes a respiratory disease within natural populations of domestic cats. A stochastic model was constructed using discrete-events simulation. Two habitats (rural vs. urban) were simulated, featuring different demographic, spatial and social patterns. The evolution of immunity in individuals was reproduced, allowing for the random recrudescence of latent infections (influenced by environment and reproduction). Hypotheses concerning the circulation of FHV were examined regarding the role of host density and the possibility of reinfection of host. Uncertainty analyses were performed on the basis of replicated Monte Carlo sampling. The results were in good agreement with serologic data from a long-term study conducted on five populations in France. The model satisfactorily reproduced the variability of natural immunity, and the epidemic features observed. The simulations have shown that FHV can persist in small populations (because of its capacity of reactivation leading to epidemics). However, the impact on demography was not dramatic. The most important parameters in determining change in epidemiology of FHV were: transmission rate corresponding to ‘friendly’ contacts, and the recrudescence rate of FHV. However, an interaction between these two parameters did not allow estimation of their values. 相似文献
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Fixed parameters for different hypothetical strains of rinderpest virus (RV) and different susceptible populations are described together with details of their derivation. Simulations were then carried out in a computer model to determine the effects that varying these parameters would have on the behaviour of RV in the different populations. The results indicated that virulent strains of RV are more likely to behave in epidemic fashion whereas milder strains tend towards persistence and the establishment of endemicity. High herd immunity levels prevent virus transmission and low herd immunity levels encourage epidemic transmission. Intermediate levels of immunity assist the establishment of endemicity. The virus is able to persist in large populations for longer than in small populations. Different vaccination strategies were also investigated. In areas where vaccination is inefficient annual vaccination of all stock may be the best policy for inducing high levels of herd immunity. In endemic areas and in herds recovering from epidemics the prevalence of clinically affected animals may be very low. In these situations veterinary officers are more likely to find clinical cases by examining cattle for mouth lesions rather than by checking for diarrhoea or high mortalities. 相似文献
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Viet AF Fourichon C Seegers H Jacob C Guihenneuc-Jouyaux C 《Preventive veterinary medicine》2004,63(3-4):211-236
Wet BVDSim (a stochastic simulation model) was developed to study the dynamics of the spread of the bovine viral-diarrhoea virus (BVDV) within a dairy herd. This model took into account herd-management factors (common in several countries), which influence BVDV spread. BVDSim was designed as a discrete-entity and discrete-event simulation model. It relied on two processes defined at the individual-animal level, with interactions. The first process was a semi-Markov process and modelled the herd structure and dynamics (demography, herd management). The second process was a Markov process and modelled horizontal and vertical virus transmission. Because the horizontal transmission occurs by contacts (nose-to-nose) and indirectly, transmission varied with the separation of animals into subgroups. Vertical transmission resulted in birth of persistently infected (PI) calves. Other possible consequences of a BVDV infection during the pregnancy period were considered (pregnancy loss, immunity of calves). The outcomes of infection were modelled according to the stage of pregnancy at time of infection. BVDV pregnancy loss was followed either by culling or by a new artificial insemination depending on the modelled farmer’s decision. Consistency of the herd dynamics in the absence of any BVDV infection was verified. To explore the model behaviour, the virus spread was simulated over 10 years after the introduction of a near-calving PI heifer into a susceptible 38 cow herd. Different dynamics of the virus spread were simulated, from early clearance to persistence of the virus 10 years after its introduction. Sensitivity of the model to the uncertainty on transmission coefficient was analysed. Qualitative validation consisted in comparing the bulk-milk ELISA results over time in a sample of herds detected with a new infection with the ones derived from simulations. 相似文献
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Billiouw M Brandt J Vercruysse J Speybroeck N Marcotty T Mulumba M Berkvens D 《Veterinary parasitology》2005,127(3-4):189-198
Serological surveys using the schizont indirect fluorescence antibody test (IFAt) are routinely carried out to monitor the Theileria parva infection prevalence. The present study evaluates the diagnostic accuracy of the IFAt in eastern Zambia, where the transmission of T. parva is highly seasonal. The data set resulted from a sentinel herd (n = 105 animals) study carried out between 1995 and 2000 and was split into an epidemic period, during which the majority of the cattle became infected, and an endemic period with seasonal disease incidence in calves. In the epidemic period the T. parva seroprevalence followed closely the build up of the herd immunity. In the endemic period the seroprevalence fluctuates considerably although most of the animals had been infected. Overall, the diagnostic sensitivity of the IFA test was 55% at cut-off titre 1:40 and 28% at cut-off 1:160. The specificity of the test was 86 and 95%, respectively. A logistic regression model demonstrates that the sensitivity is significantly lower when the T. parva transmission is low (p < 0.01). The analysis of receiver operator characteristic curves classifies the test as moderately accurate (area under the curve, AUC = 0.79) during the epidemic period and less accurate in the endemic period (AUC = 0.63). Neonatal serology surveys yield a better estimate of the infection prevalence. The sensitivity of the neonatal test was 73% at cut-off titre 1:40 and 24% at cut-off 1:160. 相似文献
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近年,生猪养殖产业不断向着集约化规模化方向发展,养殖密度增加的同时,各种传染性疾病呈现高发趋势。猪传染性疾病发生后,会造成生长发育不良,行动迟缓,生理指标失衡,甚至引发死亡,带来的经济损失不可估量,某些人畜共患病还会威胁人类的身体健康。在疫病防控过程中,需要从传染源、传播途径和易感群体等角度出发,减少养殖环境病原数量,切断病原传播途径,保护易感群体,确保生猪健康生长。该文主要结合一个乡镇的疫病流行特点,分析切断传染源和传播途径对防治猪病发生流行的重要性。 相似文献
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ABSTRACT: Disease modelling is one approach for providing new insights into wildlife disease epidemiology. This paper describes a spatio-temporal, stochastic, susceptible- exposed-infected-recovered process model that simulates the potential spread of classical swine fever through a documented, large and free living wild pig population following a simulated incursion. The study area (300 000 km2) was in northern Australia. Published data on wild pig ecology from Australia, and international Classical Swine Fever data was used to parameterise the model. Sensitivity analyses revealed that herd density (best estimate 1-3 pigs km-2), daily herd movement distances (best estimate approximately 1 km), probability of infection transmission between herds (best estimate 0.75) and disease related herd mortality (best estimate 42%) were highly influential on epidemic size but that extraordinary movements of pigs and the yearly home range size of a pig herd were not. CSF generally established (98% of simulations) following a single point introduction. CSF spread at approximately 9 km2 per day with low incidence rates (< 2 herds per day) in an epidemic wave along contiguous habitat for several years, before dying out (when the epidemic arrived at the end of a contiguous sub-population or at a low density wild pig area). The low incidence rate indicates that surveillance for wildlife disease epidemics caused by short lived infections will be most efficient when surveillance is based on detection and investigation of clinical events, although this may not always be practical. Epidemics could be contained and eradicated with culling (aerial shooting) or vaccination when these were adequately implemented. It was apparent that the spatial structure, ecology and behaviour of wild populations must be accounted for during disease management in wildlife. An important finding was that it may only be necessary to cull or vaccinate relatively small proportions of a population to successfully contain and eradicate some wildlife disease epidemics. 相似文献
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Megersa B Biffa D Abunna F Regassa A Bohlin J Skjerve E 《Tropical animal health and production》2012,44(7):1643-1651
A highly acute and contagious camel disease, an epidemic wave of unknown etiology, referred to here as camel sudden death syndrome, has plagued camel population in countries in the Horn of Africa. To better understand its epidemic patterns and transmission dynamics, we used epidemiologic parameters and differential equation deterministic modeling (SEIR/D-model) to predict the outcome likelihood following an exposure of susceptible camel population. Our results showed 45.7, 17.6, and 38.6 % overall morbidity, mortality, and case fatality rates of the epidemic, respectively. Pregnant camels had the highest mortality and case fatality rates, followed by breeding males, and lactating females, implying serious socioeconomic consequences. Disease dynamics appeared to be linked to livestock trade route and animal movements. The epidemic exhibited a strong basic reproductive number (R (0)) with an average of 16 camels infected by one infectious case during the entire infectious period. The epidemic curve suggested that the critical moment of the disease development is approximately between 30 and 40?days, where both infected/exposed and infectious camels are at their highest numbers. The lag between infected/infectious curves indicates a time-shift of approximately 3-5?days from when a camel is infected and until it becomes infectious. According to this predictive model, of all animals exposed to the infection, 66.8 % (n?=?868) and 33.2 % (n?=?431) had recovered and died, respectively, at the end of epidemic period. Hence, if early measures are not taken, such an epidemic could cause a much more devastative effect, within short period of time than the anticipated proportion. 相似文献
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This paper demonstrates the use of stochastic genetic epidemiological models for quantifying the consequences of selecting animals for resistance to a microparasitic infectious disease. The model is relevant for many classes of infectious diseases where sporadic epidemics occur, and it is a powerful tool for investigating the costs, benefits, and risks associated with breeding for resistance to specific diseases. The model is parameterized for transmissible gastroenteritis, a viral disease affecting pigs, and selection for resistance to this disease on a structured pig farm is simulated. Two genetic models are used, both of which involve selection of sires. The first involves selection with the assumption of continuous genetic variation (the continuous selection model). The second involves selection with the assumption of introgression of a major recessive gene that confers resistance (the gene introgression model). In the base population, the basic reproductive ratio, R0 (i.e., the expected number of secondary cases after the introduction of a single infected animal) was 2.24, in agreement with previous studies. The probabilities of no epidemic, a minor epidemic (one that dies out without intervention), and a major epidemic were 0.55, 0.20, and 0.25, respectively. Selection for resistance, under both genetic models, resulted in a nonlinear decline in the probability of a major epidemic and a decrease in the severity of the epidemic, should it occur, until R0 was less than 1.0, at which point the probability of a major epidemic was zero. For minor epidemics, the probability and severity of the epidemic increased until R0 reached 1.0, at which point the probabilities also fell to zero. The epidemic probabilities were critically dependent on the location on the farm where infected animals were situated, and the relative risks of different groups of animals changed with selection. The main difference between the two genetic models was in the time scale; the introgression results simply depended on how quickly the resistance allele could be introgressed into the population. For the introgression model, the probability of a major epidemic declined to zero when 0.6 of the animals were homozygous for the resistance allele. 相似文献
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Billiouw M Vercruysse J Marcotty T Speybroeck N Chaka G Berkvens D 《Veterinary parasitology》2002,107(1-2):51-63
This paper presents the results of the follow-up of three sentinel herds between 1994 and 2000 during an East Coast fever (ECF) epidemic in eastern Zambia. The animals of the sentinel herds were closely monitored clinically and serologically together with detailed Rhipicephalus appendiculatus counts. Peaks of disease incidence occurred in the rainy season (December-February) and the dry months of May-July with nymph-to-adult tick transmission dominating the infection dynamics. A second wave of adult R. appendiculatus at the start of the dry season is essential for the occurrence of a full-blown epidemic while the size of the susceptible cattle population acts as a most important limiting factor. The majority of adult cattle of the sentinel herds became infected less than 2 years after the introduction of the disease. The median age at first contact for calves born towards the end of the study (1999) was about 6 months. The case-fatality ratio (including sub-clinical cases) is estimated at 60%. It is argued that part of the so-called 'natural mortality' is actually due to ECF and that ECF occurrence and mortality are systematically underestimated. The direct financial cost of the epidemic, based on loss of animals and cost of treatment only and calculated over 4 years running, is estimated at about 6 US dollars per year per animal at risk. The value of the traditional seroprevalence survey as a tool for monitoring ECF epidemiology is put in question and the prevalence of maternal antibodies in new-born calves, reflecting the immune status of the dam population, is introduced as an alternative. It is demonstrated that an efficient immunisation campaign should concentrate its efforts in the period of low adult R. appendiculatus abundance (July-October). 相似文献
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Niemi JK Lehtonen H Pietola K Lyytikäinen T Raulo S 《Preventive veterinary medicine》2008,84(3-4):194-212
Rapid structural change and concentration of pig production in regions with most intensive production has raised concerns about whether the risk of large-scale disease losses has increased in Finland. This paper examines the pig industry's losses due to classical swine fever (CSF) epidemics. The work is based on economic and epidemiological models providing insights to the consequences of epidemics to infected and uninfected farms, government and meat processing. The economic analysis was carried out by use of a sector model, which simulated the recovery of pig production, starting from the recognition of the disease in the country and ending at a steady-state market equilibrium about 12 years later. The model explicitly took into account profit-maximising behaviour of producers and the effects of decrease in export demand.
Epidemiological evidence suggests that under the current spatially diversified structure of Finnish pig farming and related industries, the probability of a severe disease epidemic counting dozens of infected farms is small. Even for epidemics considered large in Finland (5–33 infected farms) combined with a major reduction in export demand, the median loss was simulated to be only €19.2 million. The majority of these losses were due to loss of exports corresponding almost 20% of pig meat production in Finland. While the current structure of pig farming in Finland incurs higher production costs than the most intensive structures in Europe, it also seems to decrease the probability of ‘catastrophic’ economic losses. The results suggest that the response of export markets and the number of uninfected farms affected by preventive measures are critical to the magnitude of losses, as they can amplify losses even if only few farms become infected. 相似文献
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The dynamics of foot-and-mouth disease epidemics in France was examined through simulations based on an extended state-transition model. Contagion modelling depended on specific parameters: the so-called dissemination rates. Estimation of these parameters relied on a specific discrete-event simulation model. We were able to address the problem of the hidden spread of the epidemic, before the first outbreak is diagnosed. Furthermore, we took into account the silent development of the disease in affected herds before the diagnosis. The effect of control measures such as the active search for secondary outbreaks could thus be studied. We used the model to compare the development of FMD epidemics in two very different French regions and for different control strategies implemented by the animal-health authorities. These strategies gave similar results in a low herd density area, whereas in a high herd density area, the slaughter of contact herds greatly improved the stamping-out strategy. Finally, key parameters of the model were detected through a sensitivity analysis. 相似文献
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Contagious mastitis pathogens continue to pose an economic threat to the dairy industry. An understanding of their frequency and transmission dynamics is central to evaluating the effectiveness of control programmes. The objectives of this study were twofold: (1) to estimate the annual herd-level incidence rates and apparent prevalences of Streptococcus agalactiae (S. agalactiae) in the population of Danish dairy cattle herds over a 10-year period from 2000 to 2009 inclusive and (2) to estimate the herd-level entry and exit rates (demographic parameters), the transmission parameter, β, and recovery rate for S. agalactiae infection. Data covering the specified period, on bacteriological culture of all bulk tank milk samples collected annually as part of the mandatory Danish S. agalactiae surveillance scheme, were extracted from the Danish Cattle Database and subsequently analysed. There was an increasing trend in both the incidence and prevalence of S. agalactiae over the study period. Per 100 herd-years the value of β was 54.1 (95% confidence interval [CI] 46.0-63.7); entry rate 0.3 (95% CI 0.2-0.4); infection-related exit rate 7.1 (95% CI 5.6-8.9); non-infection related exit rate 9.2 (95% CI 7.4-11.5) and recovery rate 40.0 (95% CI 36.8-43.5). This study demonstrates a need to tighten the current controls against S. agalactiae in order to lower its incidence. 相似文献