Case-control studies of sporadic enteric infections: a review and discussion of studies conducted internationally from 1990 to 2009

Genomic perspectives on foodborne illness

Whole-genome sequencing of bacterial pathogens is used by public health agencies to link cases of food poisoning caused by the same source of contamination. The vast majority of these appear to be sporadic cases associated with small contamination episodes and do not trigger investigations. A "contamination episode" refers to one or more contamination events from a single source over a period of time. We examine clusters of sequenced clinical isolates of Salmonella, Escherichia coli, Campylobacter, and Listeria that differ by only a small number of mutations (SNPs) to identify features of the underlying contamination episodes. These analyses provide additional evidence that the youngest age groups have greater susceptibility to infection by Salmonella, E. coli, and Campylobacter than older age groups. This age bias is weaker for the common Salmonella serovar Enteritidis than Salmonella in general. A large fraction of the contamination episodes causing sickness appear to have a long duration. For example, 50% of the Salmonella cases are in clusters that persist for almost 3 y. For all four pathogen species, the majority of the cases were part of genetic clusters with illnesses in multiple states and likely to be caused by contaminated commercially distributed foods. Salmonella infections in infants under 3 mo are predominantly acquired from the same contaminated food, pet food, or environmental sources as older individuals, rather than infant formula contaminated during production.

Genomic perspectives on foodborne illness

Whole-genome sequencing of bacterial pathogens is used by public health agencies to link cases of food poisoning caused by the same source of contamination. The vast majority of these appear to be sporadic cases associated with small contamination episodes and do not trigger investigations. We analyzed clusters of sequenced clinical isolates of Salmonella, Escherichia coli, Campylobacter, and Listeria that differ by only a small number of mutations to provide a new understanding of the underlying contamination episodes. These analyses provide new evidence that the youngest age groups have greater susceptibility to infection from Salmonella, Escherichia coli, and Campylobacter than older age groups. This age bias is weaker for the common Salmonella serovar Enteritidis than Salmonella in general. Analysis of these clusters reveals significant regional variations in relative frequencies of Salmonella serovars across the United States. A large fraction of the contamination episodes causing sickness appear to have long duration. For example, 50% of the Salmonella cases are in clusters that persist for almost three years. For all four pathogen species, the majority of the cases were part of genetic clusters with illnesses in multiple states and likely to be caused by contaminated commercially distributed foods. The vast majority of Salmonella cases among infants < 6 months of age appear to be caused by cross-contamination from foods consumed by older age groups or by environmental bacteria rather than infant formula contaminated at production sites.

Critical Orientation in the Jungle of Currently Available Methods and Types of Data for Source Attribution of Foodborne Diseases

With increased interest in source attribution of foodborne pathogens, there is a need to sort and assess the applicability of currently available methods. Herewith we reviewed the most frequently applied methods for source attribution of foodborne diseases, discussing their main strengths and weaknesses to be considered when choosing the most appropriate methods based on the type, quality, and quantity of data available, the research questions to be addressed, and the (epidemiological and microbiological) characteristics of the pathogens in question. A variety of source attribution approaches have been applied in recent years. These methods can be defined as top–down, bottom–up, or combined. Top–down approaches assign the human cases back to their sources of infection based on epidemiological (e.g., outbreak data analysis, case-control/cohort studies, etc.), microbiological (i.e., microbial subtyping), or combined (e.g., the so-called ‘source-assigned case-control study’ design) methods. Methods based on microbial subtyping are further differentiable according to the modeling framework adopted as frequency-matching (e.g., the Dutch and Danish models) or population genetics (e.g., Asymmetric Island Models and STRUCTURE) models, relying on the modeling of either phenotyping or genotyping data of pathogen strains from human cases and putative sources. Conversely, bottom–up approaches like comparative exposure assessment start from the level of contamination (prevalence and concentration) of a given pathogen in each source, and then go upwards in the transmission chain incorporating factors related to human exposure to these sources and dose-response relationships. Other approaches are intervention studies, including ‘natural experiments,’ and expert elicitations. A number of methodological challenges concerning all these approaches are discussed. In absence of an universally agreed upon ‘gold’ standard, i.e., a single method that satisfies all situations and needs for all pathogens, combining different approaches or applying them in a comparative fashion seems to be a promising way forward.

2017 Infectious Diseases Society of America Clinical Practice Guidelines for the Diagnosis and Management of Infectious Diarrhea

These guidelines are intended for use by healthcare professionals who care for children and adults with suspected or confirmed infectious diarrhea. They are not intended to replace physician judgement regarding specific patients or clinical or public health situations. This document does not provide detailed recommendations on infection prevention and control aspects related to infectious diarrhea.

Attribution of human infections with Shiga toxin-producing Escherichia coli (STEC) to livestock sources and identification of source-specific risk factors, The Netherlands (2010-2014)

Shiga toxin-producing Escherichia coli (STEC) is a zoonotic pathogen of public health concern whose sources and transmission routes are difficult to trace. Using a combined source attribution and case-control analysis, we determined the relative contributions of four putative livestock sources (cattle, small ruminants, pigs, poultry) to human STEC infections and their associated dietary, animal contact, temporal and socio-econo-demographic risk factors in the Netherlands in 2010/2011-2014. Dutch source data were supplemented with those from other European countries with similar STEC epidemiology. Human STEC infections were attributed to sources using both the modified Dutch model (mDM) and the modified Hald model (mHM) supplied with the same O-serotyping data. Cattle accounted for 48.6% (mDM) and 53.1% (mHM) of the 1,183 human cases attributed, followed by small ruminants (mDM: 23.5%; mHM: 25.4%), pigs (mDM: 12.5%; mHM: 5.7%) and poultry (mDM: 2.7%; mHM: 3.1%), whereas the sources of the remaining 12.8% of cases could not be attributed. Of the top five O-serotypes infecting humans, O157, O26, O91 and O103 were mainly attributed to cattle (61%-75%) and O146 to small ruminants (71%-77%). Significant risk factors for human STEC infection as a whole were the consumption of beef, raw/undercooked meat or cured meat/cold cuts. For cattle-attributed STEC infections, specific risk factors were consuming raw meat spreads and beef. Consuming raw/undercooked or minced meat were risk factors for STEC infections attributed to small ruminants. For STEC infections attributed to pigs, only consuming raw/undercooked meat was significant. Consuming minced meat, raw/undercooked meat or cured meat/cold cuts were associated with poultry-attributed STEC infections. Consuming raw vegetables was protective for all STEC infections. We concluded that domestic ruminants account for approximately three-quarters of reported human STEC infections, whereas pigs and poultry play a minor role and that risk factors for human STEC infection vary according to the attributed source.

The case-control design in veterinary sciences: A survey

The case-control study design is deceptively simple. However, many design considerations influence the estimated effect measure. An investigation of case-control studies in the human health literature suggested that some of these considerations are not described in reports of case-control studies. Our hypothesis was that the majority of veterinary studies labeled as case-controls would be incident density designs, and many would not interpret the effect measure obtained from those studies as the rate ratio rather than the odds ratio. Reference databases were searched for author-designated case-control studies. A survey of 100 randomly selected studies was conducted to examine the different design options described and estimated effect measures. Of the 100 author-identified case-control studies, 83 assessed an exposure-outcome association and, of those, only 54 (65.1%) sampled the study population based on an outcome and would thus be considered case-control designs. Twelve studies were incidence density designs but none used this terminology. Of the studies that reported an odds ratio as the effect measure, none reported on additional considerations that would have enabled a more interpretable result. This survey indicated many case-control-labeled studies were not case-control designs and among case-control studies, key design aspects were not often described. The absence of information about study design elements and underlying assumptions in case-control studies limits the ability to establish the effect measured by the study and the evidentiary value of the study might be underestimated.

Modelling study to estimate the health burden of foodborne diseases: cases, general practice consultations and hospitalisations in the UK, 2009

OBJECTIVE

To generate estimates of the burden of UK-acquired foodborne disease accounting for uncertainty.

DESIGN

A modelling study combining data from national public health surveillance systems for laboratory-confirmed infectious intestinal disease (IID) and outbreaks of foodborne disease and 2 prospective, population-based studies of IID in the community. The underlying data sets covered the time period 1993-2008. We used Monte Carlo simulation and a Bayesian approach, using a systematic review to generate Bayesian priors. We calculated point estimates with 95% credible intervals (CrI).

SETTING

UK, 2009.

OUTCOME MEASURES

Pathogen-specific estimates of the number of cases, general practice (GP) consultations and hospitalisations for foodborne disease in the UK in 2009.

RESULTS

Bayesian approaches gave slightly more conservative estimates of overall health burden (∼511 000 cases vs 566 000 cases). Campylobacter is the most common foodborne pathogen, causing 280 400 (95% CrI 182 503-435 693) food-related cases and 38 860 (95% CrI 27 160-55 610) GP consultations annually. Despite this, there are only around 562 (95% CrI 189-1330) food-related hospital admissions due to Campylobacter, reflecting relatively low disease severity. Salmonella causes the largest number of hospitalisations, an estimated 2490 admissions (95% CrI 607-9631), closely followed by Escherichia coli O157 with 2233 admissions (95% CrI 170-32 159). Other common causes of foodborne disease include Clostridium perfringens, with an estimated 79 570 cases annually (95% CrI 30 700-211 298) and norovirus with 74 100 cases (95% CrI 61 150-89 660). Other viruses and protozoa ranked much lower as causes of foodborne disease.

CONCLUSIONS

The 3 models yielded similar estimates of the burden of foodborne illness in the UK and show that continued reductions in Campylobacter, Salmonella, E. coli O157, C. perfringens and norovirus are needed to mitigate the impact of foodborne disease.

Risk factors for sporadic listeriosis in the Netherlands, 2008 to 2013

Although the disease burden of listeriosis on population level is low, on individual level the impact is high, largely due to severe illness and a high case fatality. Identification of risk factors supports and specifies public health actions needed for prevention. We performed a case–control study to determine host- and food-related risk factors for non-perinatal listeriosis in the Netherlands. Patients with non-perinatal listeriosis reported between July 2008 and December 2013 were compared with controls from a periodic control survey who completed a questionnaire in the same period. Higher age, male sex, underlying disease, especially cancer and kidney disease, and use of immunosuppressive medicine were strong risk factors for acquiring non-perinatal listeriosis. Analysis of the food consumption in the group of cases and controls with underlying diseases did not reveal any high-risk food products. Information and advice should continue to be given to persons at risk of severe listeriosis. Univariate analyses indicate that patients using gastric acid inhibitors are at risk. It is worth adding these patients to the group of susceptible persons.