Simon E. F. Spencer

Assigning the source of human campylobacteriosis in New Zealand: a comparative genetic and epidemiological approach.

Integrated surveillance of infectious multi-source diseases using a combination of epidemiology, ecology, genetics and evolution can provide a valuable risk-based approach for the control of important human pathogens. This includes a better understanding of transmission routes and the impact of human activities on the emergence of zoonoses. Until recently New Zealand had extraordinarily high and increasing rates of notified human campylobacteriosis, and our limited understanding of the source of these infections was hindering efforts to control this disease. Genetic and epidemiological modeling of a 3-year dataset comprising multilocus sequence typed isolates from human clinical cases, coupled with concurrent data on food and environmental sources, enabled us to estimate the relative importance of different sources of human disease. Our studies provided evidence that poultry was the leading cause of human campylobacteriosis in New Zealand, causing an estimated 58-76% of cases with widely varying contributions by individual poultry suppliers. These findings influenced national policy and, after the implementation of poultry industry-specific interventions, a dramatic decline in human notified cases was observed in 2008. The comparative-modeling and molecular sentinel surveillance approach proposed in this study provides new opportunities for the management of zoonotic diseases.

Source Attribution of Food-Borne Zoonoses in New Zealand: A Modified Hald Model

A Bayesian approach was developed by Hald et al.((1)) to estimate the contribution of different food sources to the burden of human salmonellosis in Denmark. This article describes the development of several modifications that can be used to adapt the model to different countries and pathogens. Our modified Hald model has several advantages over the original approach, which include the introduction of uncertainty in the estimates of source prevalence and an improved strategy for identifiability. We have applied our modified model to the two major food-borne zoonoses in New Zealand, namely, campylobacteriosis and salmonellosis. Major challenges were the data quality for salmonellosis and the inclusion of environmental sources of campylobacteriosis. We conclude that by modifying the Hald model we have improved its identifiability, made it more applicable to countries with less intensive surveillance, and feasible for other pathogens, in particular with respect to the inclusion of nonfood sources. The wider application and better understanding of this approach is of particular importance due to the value of the model for decision making and risk management.

Molecular Epidemiology of Campylobacter jejuni in a Geographically Isolated Country with a Uniquely Structured Poultry Industry

ABSTRACT In New Zealand the number of campylobacteriosis notifications increased markedly between 2000 and 2007. Notably, this countrys poultry supply is different than that of many developed countries as the fresh and frozen poultry available at retail are exclusively of domestic origin. To examine the possible link between human cases and poultry, a sentinel surveillance site was established to study the molecular epidemiology of Campylobacter jejuni over a 3-year period from 2005 to 2008 using multilocus sequence typing. Studies showed that 60.1 to 81.4% of retail poultry carcasses from the major suppliers were contaminated with C. jejuni. Differences were detected in the probability and level of contamination and the relative frequency of genotypes for individual poultry suppliers and humans. Some carcasses were contaminated with isolates belonging to more than one sequence type (ST), and there was evidence of both ubiquitous and supplier-associated strains, an epidemiological pattern not recognized yet in other countries. The common poultry STs were also common in human clinical cases, providing evidence that poultry is a major contributor to human infection. Both internationally rare genotypes, such as ST-3069 and ST-474, and common genotypes, such as ST-45 and ST-48, were identified in this study. The dominant human sequence type in New Zealand, ST-474, was found almost exclusively in isolates from one poultry supplier, which provided evidence that C. jejuni has a distinctive molecular epidemiology in this country. These results may be due in part to New Zealands geographical isolation and its uniquely structured poultry industry.

Molecular and spatial epidemiology of human campylobacteriosis: source association and genotype-related risk factors.

The epidemiology of human campylobacteriosis is complex but in recent years understanding of this disease has advanced considerably. Despite being a major public health concern in many countries, the presence of multiple hosts, genotypes and transmission pathways has made it difficult to identify and quantify the determinants of human infection and disease. This has delayed the development of successful intervention programmes for this disease in many countries including New Zealand, a country with a comparatively high, yet until recently poorly understood, rate of notified disease. This study investigated the epidemiology of Campylobacter jejuni at the genotype-level over a 3-year period between 2005 and 2008 using multilocus sequence typing. By combining epidemiological surveillance and population genetics, a dominant, internationally rare strain of C. jejuni (ST474) was identified, and most human cases (65.7%) were found to be caused by only seven different genotypes. Source association of genotypes was used to identify risk factors at the genotype-level through multivariable logistic regression and a spatial model. Poultry-associated cases were more likely to be found in urban areas compared to rural areas. In particular young children in rural areas had a higher risk of infection with ruminant strains than their urban counterparts. These findings provide important information for the implementation of pathway-specific control strategies.

The spatial and temporal determinants of campylobacteriosis notifications in New Zealand, 2001-2007.

Despite recent improvements, New Zealand still has one of the highest per-capita incidence rates of campylobacteriosis in the world. To reduce the incidence, a thorough understanding of the epidemiology of infection is needed. This retrospective analysis of 36 000 notified human cases during a high-risk period between 2001 and 2007 explored the spatial and temporal determinants of Campylobacter notifications at a fine spatial scale in order to improve understanding of the complex epidemiology. Social deprivation was associated with a decreased risk of notification, whereas urban residence was associated with an increased risk. However, for young children rural residence was a risk factor. High dairy cattle density was associated with an increased risk of notification in two of the three regions investigated. Campylobacter notification patterns exhibit large temporal variations; however, few factors were associated with periods of increased risk, in particular temperature did not appear to drive the seasonality in campylobacteriosis.

The integration of molecular tools into veterinary and spatial epidemiology

At the interface of molecular biology and epidemiology, the emerging discipline of molecular epidemiology offers unique opportunities to advance the study of diseases through the investigation of infectious agents at the molecular level. Molecular tools can increase our understanding of the factors that shape the spatial and temporal distribution of pathogens and disease. Both spatial and molecular aspects have always been important to the field of infectious disease epidemiology, but recently news tools have been developed which increase our ability to consider both elements within a common framework. This enables the epidemiologist to make inferences about disease patterns in space and time. This paper introduces some basic concepts of molecular epidemiology in a veterinary context and illustrates the application of molecular tools at a range of spatio-temporal scales. Case studies - a multi-state outbreak of Serratia mastitis, a national control program for campylobacteriosis, and evolution of foot-and-mouth-disease viruses - are used to demonstrate the importance of considering molecular aspects in modern epidemiological studies. The discipline of molecular epidemiology is in its infancy and our contribution aims to promote awareness, understanding and uptake of molecular epidemiology in veterinary science.

Utilizing a combination of molecular and spatial tools to assess the effect of a public health intervention

Until recently New Zealand had one of the highest rates of human campylobacteriosis reported by industrialized countries. Since the introduction of a range of control measures in the poultry production chain a reduction in human cases of around 50% has been observed nationwide. To inform risk managers a combination of spatial, temporal and molecular tools - including minimum spanning trees, risk surfaces, rarefaction analysis and dynamic source attribution modelling - was used in this study to formally evaluate the reduction in disease risk that occurred after the implementation of control measures in the poultry industry. Utilizing data from a sentinel surveillance site in the Manawatu region of New Zealand, our analyses demonstrated a reduction in disease risk attributable to a reduction in the number of poultry-associated campylobacteriosis cases. Before the implementation of interventions poultry-associated cases were more prevalent in urban than rural areas, whereas for ruminant-associated cases the reverse was evident. In addition to the overall reduction in prevalence, this study also showed a stronger intervention effect in urban areas where poultry sources were more dominant. Overall a combination of molecular and spatial tools has provided evidence that the interventions aimed at reducing Campylobacter contamination of poultry were successful in reducing poultry-associated disease and this will inform the development of future control strategies.

‘Super' or just ‘above average'? Supershedders and the transmission of Escherichia coli O157:H7 among feedlot cattle

Supershedders have been suggested to be major drivers of transmission of Escherichia coli O157:H7 (E. coli O157:H7) among cattle in feedlot environments, despite our relatively limited knowledge of the processes that govern periods of high shedding within an individual animal. In this study, we attempt a data-driven approach, estimating the key characteristics of high shedding behaviour, including effects on transmission to other animals, directly from a study of natural E. coli O157:H7 infection of cattle in a research feedlot, in order to develop an evidence-based definition of supershedding. In contrast to the hypothesized role of supershedders, we found that high shedding individuals only modestly increased the risk of transmission: individuals shedding over 103 cfu g−1 faeces were estimated to pose a risk of transmission only 2.45 times greater than those shedding below that level. The data suggested that shedding above 103 cfu g−1 faeces was the most appropriate definition of supershedding behaviour and under this definition supershedding was surprisingly common, with an estimated prevalence of 31.3% in colonized individuals. We found no evidence that environmental contamination by faeces of shedding cattle contributed to transmission over timescales longer than 3 days and preliminary evidence that higher stocking density increased the risk of transmission.

Bayesian zero-inflated predictive modelling of herd-level Salmonella prevalence for risk-based surveillance.

The national control programme for Salmonella in Danish swine herds introduced in 1993 has led to a large decrease in pork‐associated human cases of salmonellosis. The pork industry is increasingly focused on the cost‐effectiveness of surveillance while maintaining consumer confidence in the pork food supply. Using national control programme data from 2003 and 2004, we developed a zero‐inflated binomial model to predict which farms were most at risk of Salmonella. We preferentially sampled these high‐risk farms using two sampling schemes based on model predictions resulting from a farm’s covariate pattern and its random effect. Zero‐inflated binomial modelling allows assessment of similarities and differences between factors that affect herd infection status (introduction), and those that affect the seroprevalence in infected herds (persistence and spread). Both large (producing greater than 5000 pigs per annum), and small herds (producing less than 2000 pigs per annum) were at significantly higher risk for infection and subsequent seroprevalence, when compared with medium sized herds (producing between 2000 and 5000 pigs per annum). When compared with herds being located elsewhere, being located in the south of Jutland significantly decreased the risk of herd infection, but increased the risk of a pig from an infected herd being seropositive. The model suggested that many of the herds where Salmonella was not detected were infected, but at a low prevalence. Using cost and sensitivity, we compared the results of our model based sampling schemes with those under the standard sampling scheme, based on herd size, and the recently introduced risk‐based approach. Model‐based results were less sensitive but show significant cost savings. Further model refinements, sampling schemes and the methods to evaluate their performance are important areas for future work, and these should continue to occur in direct consultation with Danish authorities.

Context-specificity in causal signaling networks revealed by phosphoprotein profiling

Summary Signaling networks downstream of receptor tyrosine kinases are among the most extensively studied biological networks, but new approaches are needed to elucidate causal relationships between network components and understand how such relationships are influenced by biological context and disease. Here, we investigate the context specificity of signaling networks within a causal conceptual framework using reverse-phase protein array time-course assays and network analysis approaches. We focus on a well-defined set of signaling proteins profiled under inhibition with five kinase inhibitors in 32 contexts: four breast cancer cell lines (MCF7, UACC812, BT20, and BT549) under eight stimulus conditions. The data, spanning multiple pathways and comprising ∼70,000 phosphoprotein and ∼260,000 protein measurements, provide a wealth of testable, context-specific hypotheses, several of which we experimentally validate. Furthermore, the data provide a unique resource for computational methods development, permitting empirical assessment of causal network learning in a complex, mammalian setting.