A stochastic model for transmission, extinction and outbreak of Escherichia coli O157:H7 in cattle as affected by ambient temperature and cleaning practices

Dynamics of Extended-spectrum Beta-lactamase-producing, Third-generation Cephalosporin-resistant and Tetracycline-resistant Escherichia coli in Feedlot Cattle With or Without Tylosin Administration

The impact of in-feed use of tylosin in feedlot cattle on Gram-negative foodborne bacteria is unknown. We evaluated the effect of continuous in-feed tylosin use on the concentration and prevalence of tetracycline-resistant (TETr)-, third-generation cephalosporin-resistant (3GCr)-, and extended-spectrum β-lactamase-producing (ESBLs) E. coli in feedlot cattle. A cohort of weaned calves (10 animals/group) were randomized to receive a feed ration with or without tylosin. Fecal samples, regularly collected over the entire feeding period, and pen surface and feed samples, collected at the end of the feeding period, were cultured on selective media. Enumeration and binary outcomes were analyzed by mixed effects linear regression or logistic regression, respectively, using treatment and days on feed as fixed factors, and animal ID as a random variable. Tylosin supplementation did not affect the fecal concentrations of TETrE. coli or fecal prevalence of 3GCrE. coli. However, cattle in the tylosin group were 1.5 times more likely (Odds ratio = 1.5: 95% confidence interval: 1.1-2.0) to harbor ESBLs E. coli than the control cattle. Regardless of tylosin treatment, fecal concentrations of TETrE. coli and the prevalence of 3GCr- and ESBLs-E. coli increased over time. Tylosin-supplemented feed did not affect the prevalence of TETrE. coli; 3GCr and ESBLs-E. coli were not detected from the feed samples. Most of the 3GCr- and ESBLs-E. coli isolates carried the blaCTX-M-15 gene, widely detected among ESBLs-E. coli human isolates. In summary, although in-feed tylosin use in feedlot cattle did not select for TETr- and 3GCr-E. coli, it increased the likelihood of detecting ESBL-producing E. coli. Furthermore, the study indicated that the feedlot production setting gradually increases the levels of E. coli resistant to the critically and/or important antibiotics for public health, indicating an increased risk of their dissemination beyond the feedlot environment.

Impact of the WHO Integrated Stewardship Policy on the Control of Methicillin-Resistant Staphyloccus aureus and Third-Generation Cephalosporin-Resistant Escherichia coli: Using a Mathematical Modeling Approach

Methicillin-resistant Staphylococcus aureus (MRSA) and third-generation cephalosporin-resistant Escherichia coli (3GCREc) are community and hospital-associated pathogens causing serious infections among populations by infiltrating into hospitals and surrounding environment. These main multi-drug resistant or antimicrobial resistance (AMR) bacterial pathogens are threats to human health if not properly tackled and controlled. Tackling antimicrobial resistance (AMR) is one of the issues for the World Health Organization (WHO) to design a comprehensive set of interventions which also helps to achieve the end results of the developing indicators proposed by the same organization. A deterministic mathematical model is developed and studied to investigate the impact of the WHO policy on integrated antimicrobial stewardship activities to use effective protection measures to control the spread of AMR diseases such as MRSA and 3GCREc in hospital settings by incorporating the contribution of the healthcare workers in a hospital and the environment in the transmission dynamics of the diseases. The model also takes into account the parameters describing various intervention measures and is used to quantify their contribution in containing the diseases. The impact of combinations of various possible control measures on the overall dynamics of the disease under study is investigated. The model analysis suggests that the contribution of the interventions: screening and isolating the newly admitted patients, improving the hygiene in hospital settings, decolonizing the pathogen carriers, and increasing the frequency of disinfecting the hospital environment are effective tools to contain the disease from invading the population. The study revealed that without any intervention, the diseases will continue to be a major cause of morbidity and mortality in the affected communities. In addition, the study indicates that a coordinated implementation of the integrated control measures suggested by WHO is more effective in curtailing the spread of the diseases than piecemeal strategies. Numerical experiments are provided to support the theoretical analysis.

Vector-host epidemic model with direct transmission in random environment

This paper studies a stochastic vector-host epidemic model with direct transmission in random environment, governed by a system of stochastic differential equations with regime-switching diffusion. We first examine the existence and uniqueness of a positive global solution. Then, we investigate stability properties of the solution, including almost sure and pth moment exponential stability and stochastic asymptotic stability. Moreover, we study conditions for the existence and uniqueness of a stationary distribution. Numerical simulations are presented to illustrate the theoretical results.

Quantifying the Role of Stochasticity in the Development of Autoimmune Disease

In this paper, we propose and analyse a mathematical model for the onset and development of autoimmune disease, with particular attention to stochastic effects in the dynamics. Stability analysis yields parameter regions associated with normal cell homeostasis, or sustained periodic oscillations. Variance of these oscillations and the effects of stochastic amplification are also explored. Theoretical results are complemented by experiments, in which experimental autoimmune uveoretinitis (EAU) was induced in B10.RIII and C57BL/6 mice. For both cases, we discuss peculiarities of disease development, the levels of variation in T cell populations in a population of genetically identical organisms, as well as a comparison with model outputs.

Estimation of anthracnose dynamics by nonlinear filtering

In this work, we apply the nonlinear filtering theory to the estimation of the partially observed dynamics of anthracnose which is a phytopathology. The signal here is the inhibition rate and the observations are the fruit volume and the rotted volume. We propose stochastic models based on deterministic models studied previously in the literature, in order to represent the noise introduced by uncontrolled variations on parameters and errors on the measurements. Under the assumption of Brownian noises, we prove the well-posedness of the models in either they take into account the space variable or not. The filtering problem is solved for the nonspatial model giving Zakai and Kushner–Stratonovich equations satisfied respectively by the unnormalized and the normalized conditional distribution of the signal with respect to the observations. A prevision problem and a discrete filtering problem are also studied for the realistic cases of discrete and possibly incomplete observations. We illustrate the filter behavior through figures displaying the average estimation relative error and a 95% confidence region obtained after a hundred of numerical simulations with initial conditions taken randomly with respect to uniform law.

Current Interventions for Controlling Pathogenic Escherichia coli

This review examined scientific reports and articles published from 2007 to 2016 regarding the major environmental sources of pathogenic Escherichia coli and the routes by which they enter the human gastrointestinal tract. The literature describes novel techniques used to combat pathogenic E. coli transmitted to humans from livestock and agricultural products, food-contact surfaces in processing environments, and food products themselves. Although prevention before contamination is always the best "intervention," many studies aim to identify novel chemical, physical, and biological techniques that inactivate or eliminate pathogenic E. coli cells from breeding livestock, growing crops, and manufactured food products. Such intervention strategies target each stage of the food chain from the perspective of "Farm to Table food safety" and aim to manage major reservoirs of pathogenic E. coli throughout the entire process. Issues related to, and recent trends in, food production must address not only the safety of the food itself but also the safety of those who consume it. Thus, research aims to discover new "natural" antimicrobial agents and to develop "multiple hurdle technology" or other novel technologies that preserve food quality. In addition, this review examines the practical application of recent technologies from the perspective of product quality and safety. It provides comprehensive insight into intervention measures used to ensure food safety, specifically those aimed at pathogenic E. coli.

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.

Stochastic SIS metapopulation models for the spread of disease among species in a fragmented landscape

Two stochastic models are derived for a susceptible–infectious–susceptible epidemic spreading through a metapopulation: a continuous time Markov chain (CTMC) model and an Itô stochastic differential equation (SDE) model. The stochastic models are numerically compared. Close agreement suggests that computationally intense CTMC simulations can be approximated by simpler SDE simulations. Differential equations for the moments of the SDE probability distribution are also derived, the steady states are solved numerically using a moment closure technique, and these results are compared to simulations. The moment closure technique only coarsely approximates simulation results. The effect of model parameters on stability of the disease-free equilibrium is also numerically investigated.

Saltelli Global Sensitivity Analysis and Simulation Modelling to Identify Intervention Strategies to Reduce the Prevalence of Escherichia coli O157 Contaminated Beef Carcasses

Introduction

Strains of Shiga-toxin producing Escherichia coli O157 (STEC O157) are important foodborne pathogens in humans, and outbreaks of illness have been associated with consumption of undercooked beef. Here, we determine the most effective intervention strategies to reduce the prevalence of STEC O157 contaminated beef carcasses using a modelling approach.

Method

A computational model simulated events and processes in the beef harvest chain. Information from empirical studies was used to parameterise the model. Variance-based global sensitivity analysis (GSA) using the Saltelli method identified variables with the greatest influence on the prevalence of STEC O157 contaminated carcasses. Following a baseline scenario (no interventions), a series of simulations systematically introduced and tested interventions based on influential variables identified by repeated Saltelli GSA, to determine the most effective intervention strategy.

Results

Transfer of STEC O157 from hide or gastro-intestinal tract to carcass (improved abattoir hygiene) had the greatest influence on the prevalence of contaminated carcases. Due to interactions between inputs (identified by Saltelli GSA), combinations of interventions based on improved abattoir hygiene achieved a greater reduction in maximum prevalence than would be expected from an additive effect of single interventions. The most effective combination was improved abattoir hygiene with vaccination, which achieved a greater than ten-fold decrease in maximum prevalence compared to the baseline scenario.

Conclusion

Study results suggest that effective interventions to reduce the prevalence of STEC O157 contaminated carcasses should initially be based on improved abattoir hygiene. However, the effect of improved abattoir hygiene on the distribution of STEC O157 concentration on carcasses is an important information gap—further empirical research is required to determine whether reduced prevalence of contaminated carcasses is likely to result in reduced incidence of STEC O157 associated illness in humans. This is the first use of variance-based GSA to assess the drivers of STEC O157 contamination of beef carcasses.

From the bench to modeling--R0 at the interface between empirical and theoretical approaches in epidemiology of environmentally transmitted infectious diseases

For environmentally transmitted infectious diseases (ETIDs), which spread through the contaminated environment (such as foods, surfaces and fomites), there is a lack of consensus about the mathematical approach to derive R0, leading to inconsistent predictions about the spread and control of these infections in their host populations. The objective of this study was to explain three current, though conflicting, approaches to derive a theoretical expression for R0 for ETIDs and assess their validity through comparison with available empirical data. Salmonella Typhimurium in laboratory mice was used as a theoretical and empirical model system. The three conflicting theoretical expressions for R0 were derived using the next generation matrix approach according to three unverified hypotheses about the role of the environmental phase in the transmission of ETIDs. The hypotheses assume that the environment contaminated with a pathogen is: (H1) an extension of the host's infectious period, (H2) a reservoir for the infectious agent, or (H3) has both of these characteristics. For the parameter values describing the empirical model system, the theoretical values of R0 corresponding to the hypotheses H2 and H3 were very similar (1.38 and 1.62, respectively) and their values were approximately half of the value of R0 for hypothesis H1 (2.94). The theoretical R0 values were compared with an empirical R0 (1.58, 95% confidence interval: 1.14, 2.02) estimated using a Martingale method from published experimental data on Salmonella Typhimurium transmission in mice. The results of the comparison suggested that hypothesis H1 is unlikely to hold true but it could not be rejected with confidence because of uncertainty in the value of the pathogen growth rate in the environment. The hypotheses H2 and H3 were both equally strongly supported with the empirical data suggesting that either of them could be valid. A sensitivity analysis identified critical information gaps about the indirect transmission rate of infection and the pathogen growth rate in the environment. Moreover, we identified experimental conditions for which the theoretical R0 predictions based on the hypotheses H2 and H3 differ greatly, which would assist their discrimination and conclusive validation against future empirical studies. Once a valid theoretical R0 is identified for Salmonella Typhimurium in mice, its generalizability to other host-pathogen-environment systems should be tested. The present study may serve as a template for integrated empirical and theoretical research of R0 in the epidemiology of ETIDs.

Estimating the probability of an extinction or major outbreak for an environmentally transmitted infectious disease

Indirect transmission through the environment, pathogen shedding by infectious hosts, replication of free-living pathogens within the environment, and environmental decontamination are suspected to play important roles in the spread and control of environmentally transmitted infectious diseases. To account for these factors, the classic Susceptible-Infectious-Recovered-Susceptible epidemic model is modified to include a compartment representing the amount of free-living pathogen within the environment. The model accounts for host demography, direct and indirect transmission, replication of free-living pathogens in the environment, and removal of free-living pathogens by natural death or environmental decontamination. Based on the assumptions of the deterministic model, a continuous-time Markov chain model is developed. An estimate for the probability of disease extinction or a major outbreak is obtained by approximating the Markov chain with a multitype branching process. Numerical simulations illustrate important differences between the deterministic and stochastic counterparts, relevant for outbreak prevention, that depend on indirect transmission, pathogen shedding by infectious hosts, replication of free-living pathogens, and environmental decontamination. The probability of a major outbreak is computed for salmonellosis in a herd of dairy cattle as well as cholera in a human population. An explicit expression for the probability of disease extinction or a major outbreak in terms of the model parameters is obtained for systems with no direct transmission or replication of free-living pathogens.

Transmission of Escherichia coli O157:H7 in cattle is influenced by the level of environmental contamination

A pen infection-transmission experiment was conducted to elucidate the role of pathogen strain and environmental contamination in transmission of Escherichia coli O157:H7 (ECO157) in cattle. Five steers were inoculated with a three-strain mixture of ECO157 and joined with five susceptible steers in each of two experimental replicates. Faecal and environmental samples were monitored for ECO157 presence over 30 days. One ECO157 strain did not spread. Transmission rates for the other two strains were estimated using a generalized linear model developed based on a modified ‘Susceptible–Infectious–Susceptible’ mathematical model. Transmission rates estimated for the two strains (0·11 and 0·14) were similar. However, the rates significantly (P = 0·0006) increased 1·5 times for every 1-unit increase in the level of environmental contamination measured as log₁₀ c.f.u. Depending on the level of environmental contamination, the estimated basic reproduction numbers varied from <1 to 8. The findings indicate the importance of on-farm measures to reduce environmental contamination for ECO157 control in cattle that should be validated under field conditions.