Fw: [BITES-L] bites Oct. 21/10 -- II

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Subject: [BITES-L] bites Oct. 21/10 -- II

bites Oct. 21/10 -- II

Officials release final report of ILLINOIS Subway salmonella outbreak

Nosestretcher alert: CBC (that's in CANADA) sucks at food safety info

Del Monte Fresh Produce N.A., Inc. announces limited voluntary cantaloupe recall in and around Detroit, MICHIGAN

DENMARK: MRSA in pig herds

Climate-health uncertainties untangled

Use of electronic group method in assessing food safety training needs and delivery methods among international college students in the U.S.

A community outbreak of Legionnaires' disease in South Wales, August–September 2010

Urban–rural differences of age- and species-specific campylobacteriosis incidence, Hesse, Germany, July 2005 – June 2006

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Officials release final report of ILLINOIS Subway salmonella outbreak
21.oct.10
barfblog
Doug Powell
http://www.barfblog.com/blog/144713/10/10/21/officials-release-final-report-illinois-subway-salmonella-outbreak
Did the Sponge Bob leafy greens cone of silence descend on Illinois health types as they concluded in a 69-page report published today that lettuce, tomatoes and olives were the possible culprits in a Subway salmonella outbreak that sickened almost 200 earlier this year?
Pantagraph.com reported today that officials with the Illinois Department of Public Health traced a salmonella outbreak at Subway restaurants to one Central Illinois food distributor, but in a final report on the incident issued Thursday, could not identify the exact source of the problem, which led to 109 confirmed cases and another 90-plus probable or suspect cases of the illness between late April and June.
In the 69-page report, investigators said the "most likely source" of the lettuce, tomatoes and olives linked to the illnesses was Lincoln-based Sysco Central Illinois Inc., which delivered produce to the affected restaurants.
Samples collected at the company's distribution facility in June, after many of the victims had already contracted the illness, were tested and found negative for salmonella.
Areas that may have been the source of salmonella may have been washed down and produce that was affected may have been discarded.
The report, which will be forwarded to the federal Centers for Disease Control, shows that 299 Subway restaurants were forced to dispose of their produce during the event.
More than 480 workers at the stores had to be tested. A dozen of them were found to be positive for the strain of salmonella.
http://barfblog.foodsafety.ksu.edu/blog/142465/10/06/04/lost-translation-time-end-don't-ask-don't-tell-food-safety-outbreak-reporting
http://www.pantagraph.com/news/state-and-regional/illinois/article_e0f70332-dd6f-11df-a894-001cc4c002e0.html

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Nosestretcher alert: CBC (that's in CANADA) sucks at food safety info
21.oct.10
barfblog
Doug Powell
http://www.barfblog.com/blog/144712/10/10/21/nosestretcher-alert-cbc-that%E2%80%99s-canada-sucks-food-safety-info
I was on a trip with some Kansas Staters earlier this week, and at a dinner, one of them started talking about a report he'd heard on NPR (National Public Radio) earlier that week.
I said, "State-sponsored jazz."
He looked at me like I was special, because, how hard is it to repeat lines from the Colbert Report.
Satire, like the Intertubes, is lost on some people.
The Vancouver television section of the Canadian Broadcasting Corporation (CBC) ran a bunch of food safety stories in the run-up to Canadian Thanksgiving on Oct. 11, 2010. An astute reader e-mailed me to say, "You may want to check out their 'food-safety facts.'" I have no idea where these alleged facts came from, but the BS highlights include:
2. "Pot luck meals are responsible for a large amount of food poisonings. They are usually caused by poor food temperature controls in egg or meat products."
4. "Harmful bacteria does not stop multiplying unless refrigerated below 5 degrees. However, most refrigerators are not capable of this temperature."
7. "Do not eat foods directly from a jar or can. Saliva can contaminate the contents inside."
8. "Peanut butter needs to be stored in a refrigerator after opening to prevent the fats from going rancid."
None of these facts are substantiated, and there is plenty of available evidence to counter these claims. As the reader points out, nothing is mentioned about cross-contamination or handwashing.
Hate is a strong word, but I hate jazz. Especially state-sponsored jazz. And terrible taxpayer-funded news.
http://barfblog.foodsafety.ksu.edu/blog/140218/09/06/13/pbs-provides-terrible-advice-cooking-hamburgers
www.cbc.ca/bc/features/food-safety/

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Del Monte Fresh Produce N.A., Inc. announces limited voluntary cantaloupe recall in and around Detroit, MICHIGAN
21.oct.10
FDA
http://www.fda.gov/Safety/Recalls/ucm230528.htm
Del Monte Fresh Produce N.A., Inc ("Del Monte Fresh") announced today the voluntary recall of certain cantaloupes grown in and shipped from Arizona. The affected product was distributed to limited customers in and around Detroit, Michigan and is being recalled because these cantaloupes have the potential to be contaminated with Salmonella.
Persons infected with Salmonella may experience a variety of symptoms and illnesses. Healthy persons infected with Salmonella often experience fever, diarrhea (which may be bloody), nausea, vomiting and abdominal pain. In rare circumstances, infection with Salmonella can result in more severe illnesses and potentially can be fatal if untreated.
Approximately eighty one (81) cartons of cantaloupes, each containing fifteen (15) cantaloupes per carton, were distributed to wholesalers in Detroit who in turn sell to other wholesalers and or to retail and foodservice outlets beginning on October 11, 2010. The cantaloupes have a light brown color skin on the exterior; with orange flesh. Each cantaloupe has a Del Monte® sticker with the words "Cantaloupe USA". The cantaloupes were distributed for sale in bulk in cardboard cartons. The recalled cartons of cantaloupes are dark brown cardboard with the "Del Monte" logo in red lettering and "cantaloupes" in yellow lettering on a green background. The cantaloupes have the lot codes W-11-147-43-size 15 or W-11-14-19 size 15.
The cantaloupe recall is being implemented as a result of a random test directed by the USDA and carried out by the Michigan Department of Agriculture. Although no illnesses have been reported, Del Monte Fresh voluntarily decided to recall the potentially affected lot.
Consumers who believe that they are in possession of uneaten cantaloupe affected by this recall may contact Del Monte Fresh at any time by calling 1-800-659-6500 or email Del Monte Fresh at Contact-US-Executive-Office@freshdelmonte.com.

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DENMARK: MRSA in pig herds
21.oct.10
Fodevarestyrelsen
http://translate.google.com/translate?sl=auto&tl=en&u=http://www.foedevarestyrelsen.dk/Nyheder/Nyheder/2010/MRSA_i_svinebesaetninger.htm
MRSA is an abbreviation for methicillin-resistant Staphylococcus aureus. It is a staphylococcal type that is resistant to certain antibiotics.
People who are in close contact with swine farms (farmers, vets and their families) have a greater risk to be carriers of MRSA than the general population, since the bacterium can be transmitted by close contact with animals. applies primarily pigs but also other animals can carry MRSA.
MRSA was found in meat in several countries, including Denmark. But by judicious kitchen hygiene is no transmission of infection through food. Current research also suggests that meat and food does not play a significant role in disease transmission to consumers.
The authorities have focused on MRSA
There has been focus on this specific type of MRSA for several years by the authorities. This applies both in Denmark and EU level.
In 2006 was appointed a 'coordinating group on zoonotic aspects of MRSA' with participants from the Health Protection Agency (Presidency), the National Food Authority, National Working Environment Authority, National Food Institute (DTU) and Statens Serum Institut.. The purpose of the Coordination Group is to advise relevant authorities on the prevention of human disease caused by zoonotic MRSA strains.
Evolution of MRSA in pig herds, among other preventable by a reduction in antibiotic consumption. Use of antibiotics in humans and animals involves the risk of developing resistance - therefore, the use of antibiotics is limited.
There is political consensus to reduce the consumption of antibiotics in swine herds by 10 percent in 2013 compared to 2009 level. This ia done by introducing a 'yellow card scheme' for the pig herds with the highest consumption of antibiotics.
How to find MRSA?
Detection of MRSA in animals and humans is usually achieved by grafting from the nose and throat, followed by cultivation on suitable growth medium. For the detection of staphylococcal conducting further study to clarify whether the identified staphylococci belonging MRSA group.
In people's eradication of MRSA by infection prevention and antibiotic treatment of the person with confirmed MRSA and his family for 5 days.
Research is currently faster and safer methods to identify infected herds, as well as routes of infection for MRSA. The research focuses in particular to identify factors that contribute to the bacterium can colonize the mucous membranes in pigs and humans and thus may explain why the bacterium appears to spread easily from animal to animal and humans.
MRSA strains mainly from pigs?
MRSA-type CC398 seen primarily in the pig, but it is outside Denmark also found in chickens and cattle. The incidence appears to be related to the use of penicillin production.
Under the auspices of the European Food Safety Authority (EFSA) has conducted studies of the prevalence of MRSA in pigs in different countries. The studies show that Denmark is among the EU countries that have low incidence of MRSA in pig herds.

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Climate-health uncertainties untangled
21.oct.10
Emerging Health Threats
http://www.eht-forum.org/news.html?fileId=news101021015121
By the turn of the century, climate change could raise the risk of diarrhoea by about a third in countries where the condition is already common, according to research published online this month in Environmental Health Perspectives. Even conservative estimates suggest a substantial impact, according to the authors, Erik Kolstad and Kjell Johansson.
But like previous estimates, the forecast comes with uncertainty. The authors trace the sources of this uncertainty and show that a dearth of data from direct observation has a big impact on how accurately scientists can make predictions.
"Our research calls attention to how today's scarcity of empirical studies of climate change impacts [on] health as well as the disagreement between climate models act together to limit the precision of future projections," write Kolstad and Johansson, from research institutions in Bergen, Norway.
Worldwide, diarrhoea is responsible for nearly a fifth of all deaths among children under five years of age. Its statistical relationship with climatic changes, particularly temperature, is well researched, according to the authors. This makes it a good case-study for how uncertainties can be made more explicit in climate-health models.
A study by the World Health Organization (WHO), the only quantitative assessment of the link, estimated that the risk of diarrhoea could increase by 5% for every 1 0C rise in temperature. But it also indicated that the estimate could be off by as much as 10% — undermining confidence in the assumption that climate change would have an effect.
The authors say this variation is down to uncertainties in climate change models, as well as incomplete understanding of how temperature fluctuations affect health risks, and how climate-related changes in disease will be influenced by social and economic measures taken to adapt to the threat.
To capture some of this uncertainty, they came up with a range of predictions using a matrix produced by taking temperature projections from 19 climate models, and combining them with five estimates of temperature-related rise in the risk of diarrhoea, which were derived from empirical studies.
The earlier WHO estimate was based on just one climate model, with two empirical studies used as inputs for predicting the percent rise in risk for each degree change in temperature.
In developing countries currently affected by high rates of diarrhoea, the WHO study had predicted an 8–9% increase in risk by 2030. Kolstad and Johansson estimate a similar increase — by 8–11%, averaged across years 2010–2039.
"Later in this century, for the periods 2040–2069 and 2070–2099, the mean of our projection matrices gives risk increases of 15–20% and 22–29%, respectively," they write, adding that increases of this scale would be "disastrous".
Alert to the uncertainty surrounding these estimates, the authors looked at how widely the projections varied across the matrix and spotted a pattern: differences between climate change models contributed to the variation in their estimates, but did so to a lesser extent compared with differences in the empirical data used to quantify the effect of temperature on diarrhoea incidence.
This suggests that models based on just one value for each variable may be misleading, they caution. "But perhaps the most important insight to be gained... is that the part of the variance that originates from inter-model discrepancies is relatively small."
Although the WHO considers climate change a real and urgent threat, debates over model predictions and the role of human activity in climate change were fuelled in recent months by allegations that scientific evidence has been mishandled, and by an error in a report authored by the Intergovernmental Panel on Climate Change. The controversies spurred calls for scientists to be more transparent about the uncertainties associated with climate change projections.
Warnings about the effect of climate change on human health have relied mainly on expected changes in risk for diseases sensitive to temperature fluctuations, which are prone to the uncertainties highlighted by Kolstad and Johansson.
The authors also note that their findings cast doubt on a common assumption made in models of the relationship between climate change and the risk of diarrhoea — that the increase in risk associated with each degree change is constant for all temperatures. "An obvious and important item for future work is therefore to develop non-linear regression models for temperature impacts on diarrhoea."
Reference and links
1.
Kolstad EW, Johansson KA. Uncertainties associated with quantifying climate change impacts on human health: a case study for diarrhea. Environ Health Perspect 2010. doi: 10.1289/ehp.1002060

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Use of electronic group method in assessing food safety training needs and delivery methods among international college students in the U.S.
20.oct.10
Appetite
Julie Garden-Robinson, Myron A. Eighmy, and Agnes Ngale Lyonga
http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6WB2-518TY3B-1&_user=508790&_coverDate=10%2F20%2F2010&_rdoc=1&_fmt=high&_orig=search&_origin=search&_sort=d&_docanchor=&view=c&_acct=C000025157&_version=1&_urlVersion=0&_userid=508790&md5=c277fc1b305bd71d6a81e2aeab0d7601&searchtype=a
Abstract
The purpose of this study was to determine the types of unfamiliar foods international students in the U.S. encounter and to assess food safety information that international students would like to receive for mitigating risks associated with handling and preparing unfamiliar foods. The study identified preferred instructional delivery methods and media for receiving food safety training or information. An electronic group method was used for this study. The electronic group method was chosen to maximize group efficiency by allowing participants to share ideas simultaneously and anonymously with minimal use of time and resources.
Types of different (unfamiliar) foods were grouped into major categories. Fast and ready-to-eat foods, and processed and frozen foods constituted a major change for some international students, who were accustomed to homemade and fresh foods in their countries. Participants were interested in receiving information about how to safely handle and prepare unfamiliar foods in their new environment. Preferred methods for receiving food safety information included written materials, online publications, presentations, and materials provided during student orientation. Food packages, websites, and television programs were other preferred methods of receiving food safety information.

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A community outbreak of Legionnaires' disease in South Wales, August–September 2010
21.oct.10
Eurosurveillance
M Keramarou, M R Evans
http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=19691
During August and September 2010, an outbreak comprising 22 cases of Legionnaires' disease was identified by the public health service in Wales. The cases are distributed over a wide geographical area in South East Wales. There are two space-time clusters centred on the upper Rhymney Valley and the lower Cynon Valley respectively. Epidemiological investigations are compatible with cooling towers in each location as the potential source, but environmental inspections were satisfactory and microbiological investigations are inconclusive.
Outbreak description
In mid and late August 2010, six cases of Legionnaires' disease, with no history of recent travel abroad, were reported to the public health service. All the patients tested positive for urinary antigen for Legionella pneumophila serogroup 1 (mAb2 positive), which is the most common cause of Legionnaires' disease in the United Kingdom (UK). There were 24 cases of Legionnaires' disease in Wales in 2009 and an average of 13 cases per year over the past 10 years. A multidisciplinary Outbreak Control Team was convened on 3 September 2010 and an outbreak of Legionnaires' disease was declared.
Epidemiological investigation
Active case finding was undertaken by alerting clinicians throughout Wales and by alerting public health professionals throughout the UK. All cases of Legionnaires' disease reported in Wales from 1 July 2010 to 30 September 2010 were reviewed. A probable outbreak-associated case was defined as a person with a positive urine antigen test for L. pneumophila and onset of symptoms after 1 July 2010, who lived in, or had visited, the outbreak area during the 14 days before onset of symptoms. The outbreak case definition was based on the European Union case definitions for Legionnaires' disease [1]. The outbreak area was defined as the 12 km corridor on either side of the Heads of the Valleys Road (A465). This is a major road that links South West Wales with South East Wales and the English Midlands. Over the next two weeks a further 16 cases of Legionnaires' disease were identified.
Environmental health officers from 10 county or city councils interviewed all cases as soon as possible after notification. Information on demographic factors and recent movements within and outside the outbreak area was collected for the 14–day period before the onset of symptoms. Patients' residence and movements, as well as the locations of cooling towers in the area, were mapped using a geographical information system in order to help generate hypotheses about potential sources of exposure.
Environmental and microbiological investigations
By law, all cooling towers and evaporative condensers in the UK are required to be registered with the local council [2]. Owners should also follow the Approved Code of Practice (ACOP) on their operation and maintenance [3]. The Health and Safety Executive (HSE) inspected registered premises in the Merthyr Tydfil, Blaenau Gwent, Rhondda Cynon Taff and Caerphilly county council areas to identify any operating deficiencies. A search was also undertaken for unregistered premises. In addition, other potential sources within the outbreak area that might generate aerosols such as car wash and jet wash facilities were visited and inspected by local authority environmental health officers. Water samples were taken from a wide variety of sources at all sites that were found to have operating deficiencies or that were epidemiologically linked to the outbreak and analysed for legionella by PCR and culture.
Environmental samples were sent to the Severn Trent Water Company laboratory for testing and to the Respiratory and Systemic Infection Laboratory (RSIL) of the Health Protection Agency for further typing. Patient samples were also collected and sent to RSIL for testing and typing, in order to identify a match with the potential environmental source.
Results
Thirty-one patients with Legionnaires' disease with onset since 1 July 2010 were identified, 22 of whom met the outbreak case definition [1]. Dates of onset of symptoms ranged from 4 August to 10 September 2010 (Figure 1) and none had travelled abroad in the two weeks beforehand.
Figure 1. Patients with Legionnaire's disease by date of symptom onset, South Wales, July-September 2010 (n=31)
Cases had a median age of 65 years (range 38-86) and most had underlying medical risk factors that are known to be associated with Legionnaires' disease. There were 15 males and seven females. All 22 cases were admitted to hospital and two died (case fatality rate 7%). There were two distinct spatio-temporal clusters (Figure 2): a cluster of seven people in the upper Rhymney Valley (cluster A) and a cluster of six people in the lower Cynon Valley (cluster B) including one case linked to both. The clusters are located around 15km apart but both are within a 5 km radius of a cooling tower. Of the remaining 10 cases, two were epidemiologically linked to a retail premises outside the outbreak area and one was microbiologically linked to another premises outside the outbreak area. The source for the remaining cases is unknown.
Figure 2. Location of clusters of Legionnaires' disease cases South Wales, August–September 2010
Laboratory results
All cases tested positive for urinary antigen for L. pneumophila serogroup 1 (mAb2 positive). Respiratory samples were available for typing from 11 patients. L. pneumophila has so far been cultured/typed from four patients and typed directly from sputum in a further three. Six strains are different subtypes and/or genotypes and neither cluster A nor B can be clearly characterised (Table). 
 
Table. Microbiological results from clinical samples, Legionnaires' disease outbreak, South Wales, August–September 2010


Environmental samples
In total, 28 registered premises were visited by the HSE. Another three unregistered premises were identified and visited. A total of 26 environmental samples were collected and tested and all but one (linked to a single case not associated with either cluster) were negative on culture.
Control measures
In the vicinity of cluster A, there is a cooling tower and an air scrubber. Both were voluntarily closed down after inspection and the cooling tower was cleaned and disinfected. Both have resumed normal operation following microbiological clearance. A cooling tower in the vicinity of cluster B was also closed, disinfected and re-opened following microbiological clearance. None of the sites has been definitively identified as the source of the outbreak.
In addition, a Prohibition Notice was served by the HSE at a site in Merthyr Tydfil. The notice was served as the cooling towers were not being operated in accordance with the Approved Code of Practice. Improvement Notices were also served on six further companies that were found to have minor deficiencies in their training, risk management policies, or maintenance procedures requiring them to improve the operation of their systems. None of these companies were located in the vicinity of Cluster A or B.
Discussion and conclusion
The outbreak investigation has so far identified two time-space clusters compatible with cooling towers in each location as the potential source. The outbreak has proved a particular challenge to investigate by virtue of the wide geographical distribution of cases, the identification of two distinct spatio-temporal clusters, the existence of different strains of L. pneumophila in cases, and the absence of L. pneumophila in environmental samples.
Previous outbreak investigations have identified geographical spread of Legionella up to 10 km from an industrial source [4,5]. However, even this would not explain the wide geographical distribution in this outbreak. Although the two clusters are only 15 km apart in a straight line, the topography comprises a series of hills and valleys and the road distance is considerably greater.
When microbiological results do not confirm a single source, or are contradictory, it can be difficult to decide if an outbreak is actually taking place [6]. The number of cases in this outbreak is clearly in excess of what would normally be observed in South Wales at this time of year. Some of this may be the consequence of heightened awareness and active case finding after declaration of the outbreak, but this does not explain the clustering of cases.
Investigations are continuing and some typing results are still awaited. So far, there has been only one successful match between an environmental and human sample. This highlights the importance of isolating and typing Legionella from as many clinical and environmental samples as possible to help identify the source [7,8]. The fact that no further cases have been detected since mid September 2010 indicates that the control measures taken appear to have been successful.
 
Acknowledgements 
We would like to thank all the members of the South Wales Legionnaires' Disease Outbreak Control Team: the Public Health Wales health protection teams, communications team, and microbiology services; environmental health departments of Blaenau Gwent, Caerphilly, Merthyr Tydfil, Monmouthshire, Neath Port Talbot, Rhondda Cynon Taff, Torfaen and Vale of Glamorgan County Borough Councils and of Swansea and Cardiff City Councils; the Health and Safety Executive; Environment Agency; microbiology departments of Aneurin Bevan and Cwm Taf Health Boards; the Scottish Legionella Reference Laboratory and the Health Protection Agency's Centre for Emergency Preparedness and Response, Porton Down and Centre for Infections, Colindale who participated in the outbreak investigation. We also thank Clare Elliott for assistance in producing the map.
References
European Centre for Disease Prevention and Control (ECDC). European Legionnaires' Disease Surveillance Network (ELDSNet). EU case definition for Legionnaires' disease. Stockholm :ECDC. [Accessed 14 Oct 2010]. Available from: http://www.ecdc.europa.eu/en/activities/surveillance/ELDSNet/Pages/EU%20case%20definition.aspx
Ricketts KD, Joseph C, Lee J, Wewalka G, European Working Group for Legionella Infections. Survey on legislation regarding wet cooling systems in European countries. Euro Surveill. 2008;13(38):pii=18982. Available from: http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=18982
Health and Safety Executive (HSE). Legionnaires' disease. The control of Legionella bacteria in water systems. Approved Code of Practice and guidance. London: HSE. 2000. Available from: http://www.hse.gov.uk/pubns/books/l8.htm
Nygard K, Werner-Johansen O, Ronsen S, Caugant DA, Simonsen O, Kanestrom A, et al. An outbreak of legionnaires' disease spread from an industrial air scrubber in Sarpsborg, Norway. Clin Infect Dis. 2008;46(1):61-9.
Nguyen TM, Ilef D, Jarraud S, Rouil L, Campese C, Che D, et al. A community-wide outbreak of legionnaires' disease linked to industrial cooling towers – how far can contaminated aerosols spread? J Infect Dis. 2006;193(1):102-11.
Pereira AJ, Broadbent J, Mahgoub H, Morgan O, Bracebridge S, Reacher M, et al. Legionnaires' disease: when an 'outbreak' is not an outbreak. Euro Surveill. 2006;11(48):pii=3089. Available from: http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=3089
Rota MC, Pontrelli G, Scaturro M, Bella A, Bellomo AR, Trinito MO, et al. Legionnaires' disease outbreak in Rome, Italy. Epidemiol Infect. 2005;133(5):853-9.
Kirrage D, Reynolds G, Smith GE, Olowokure B, Hereford Legionnaires Outbreak Control Team. Investigation of an outbreak of legionnaires' disease: Hereford, UK 2003. Resp Med. 2007;101(8):1639-44.

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Urban–rural differences of age- and species-specific campylobacteriosis incidence, Hesse, Germany, July 2005 – June 2006
21.oct.10
Eurosurveillance
J Fitzenberger, H Uphoff, S Gawrich, A M Hauri
http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=19693
Campylobacter infection is the most common cause of bacterial gastroenteritis worldwide. This study examines the association between campylobacteriosis incidence and degree of urbanicity in Hesse, Germany, by age and Campylobacter species. During a one-year period (July 2005–June 2006), Hessian local health authorities provided information on municipality of residence for 3,315 campylobacteriosis cases. We calculated age- and Campylobacter species-specific incidences for six levels of urbanicity, as defined by population density and accessibility of centres. For children under five years old, living in inner rural areas (incidence rate ratio (IRR): 2.9; 95% confidence interval (CI): 1.9 to 4.4) and for children aged 5–14 years living in inner rural (IRR: 2.1; 95% CI: 1.3 to 3.1) or intermediate areas (inner intermediate area IRR: 1.8; 95% CI: 1.2 to 2.7; outer intermediate area IRR: 2.1; 95% CI: 1.3 to 3.3) was associated with a statistically significantly higher campylobacteriosis risk (reference category: inner urban area). Calculations by Campylobacter species showed a higher risk of gastroenteritis due to C. coli for inhabitants (all ages) of non-urban areas. This study suggests that differences in risk factors by age, Campylobacter species and degree of urbanicity do exist. For children contact with animals or the environment may be responsible for a substantial proportion of sporadic Campylobacter infections.
Introduction
Campylobacter infections resulting in gastroenteritis are recognised as an emerging problem worldwide. With 47 cases per 100,000 population campylobacteriosis is the most commonly reported gastrointestinal disease in the European Union (data from 2007) [1]. Notification rates differ markedly, ranging from zero per 100,000 population in Romania to 95 per 100,000 population in the United Kingdom in 2007 [1]. In Germany, the annual number of reported cases rose from 47,937 in 2003 (58 per 100,000 population) to 62,807 in 2009 (79 per 100,000 population) [2]. A number of case–control studies identified travelling abroad, eating poultry, pork and sausages, drinking untreated water or unpasteurised milk, barbecuing and having contact with domestic animals as risk factors for infection [3-5], but most infections are believed to result from the ingestion of contaminated food [6]. The primary source of food contamination is believed to be animal faeces. This is consistent with high Campylobacter carriage rates in poultry, pigs and cattle and the fact that similar Campylobacter genotypes have been identified in farm animals and humans [7-9]. Contamination of the environment by faeces of domestic and wild animals presents an alternative exposure pathway for human infection, for example, via contamination of drinking and recreational water sources [10]. Humans may also be exposed to animal faeces in the environment through other outdoor activities such as playing, camping, walking and picnicking.
Since 2001, when the country's disease reporting system was reorganised, specific notification data on human campylobacteriosis have been available in Germany. Using national case definitions [11], local health authorities verify locally identified notifiable diseases and send case reports electronically via state health departments to the national surveillance unit at the Robert Koch Institute in Berlin [12]. For campylobacteriosis, data collected in this system include demographic characteristics, dates of illness, county and – for internationally imported cases – country of infection, diagnostic procedure used (bacterial culture or enzyme-linked immunosorbent assay (ELISA)), and if performed, results of species differentiation, but not the techniques used) and association with outbreaks.
Hesse is one of the 16 German Laender, with a population of 6.1 million in 2007. In Hesse, the annual number of notified cases of campylobacteriosis rose from 3,000 in 2001 to 4,029 cases in 2009, corresponding to an incidence of 49 per 100,000 population and 66 per 100,000 population, respectively. County-specific incidence of Campylobacter infection in Hesse ranged from 19 per 100,000 inhabitants in 2001, 2002 and 2004 to 113 per 100,000 inhabitants in 2007. While the annual campylobacteriosis incidence varied widely between Hessian counties, intracounty incidence changed little from 2001 to 2007. We investigated the association between campylobacteriosis incidence and living in Hessian urban, intermediate and rural environments by cases' age, sex and Campylobacter species.
Methods
Data on age, sex and Campylobacter species of all campylobacteriosis cases with disease onset (or if missing, date of diagnosis) from July 2005 to June 2006 were extracted from the state surveillance database. In addition, Hessian local health authorities provided information on the municipality of the cases' residence (postal code and/or name of municipality) for all cases included in the study. Population data were provided by the Hesse Statistical Office. The 426 Hessian municipalities were grouped into six categories according to their degree of urbanicity, as defined by the Federal Office of Building and Regional Planning based on population density (urban, intermediate and rural) and accessibility of centres (inner and outer) [13]. The spatial distribution of categories of urbanisation in Hesse is shown in Figure 1. In Hesse, the total inner urban area (IUA) has a population density of 1,441 inhabitants per km2. Some 35% of the Hessian population live in municipalities of the IUA (Table 1). 

Figure 1. Geographical distribution of Campylobacter infections, by municipality, showing (A) degree of urbanicity, (B) incidence in children aged 0–14 years and (C) incidence in people aged 15 years and above, Hesse, Germany, July 2005 – June 2006


Table 1. Population density and percentage population, by degree of urbanicity, Hesse, Germany, July 2005 – June 2006

Age-specific campylobacteriosis incidences for the six categories of urbanisation and five age groups (under 5 years, 5–14 years, 15–44 years, 45–64 years, more than 64 years) were calculated. In our study, C. coli and C. jejuni together represent over 96% of campylobacteriosis reports with species information. Due to the small numbers of C. coli cases, species-specific campylobacteriosis incidences for C. jejuni and C. coli were calculated only for three categories of urbanisation (urban, intermediate and rural areas). We also calculated 95% confidence intervals (CI) for incidence rates and incidence rate ratios (IRRs) and the attributable fraction among the exposed and the population attributable fraction for living in non-urban areas according to Boice and Monson, using the incidence in urban areas as reference for calculation [14].
As species information was not available for all cases and in order to take into account variation in the frequency of species differentiation according to degree of urbanicity, the number of species-specific cases was estimated using the formula: corrected number of species-specific cases = (number culture confirmed/number differentiated to species level) x (reported number of species-specific cases). Corrected incidence rates and IRRs were then calculated. For corrected incidences, 95% CI were not calculated, due to the additional uncertainty resulting from incompleteness of species differentiation. Data were analysed with Stata version 10.0.
Results
From July 2005 to June 2006, 3,331 campylobacteriosis cases were reported in Hesse. Of these, 2,710 cases (81.4%) were reported to have acquired their infection in Hesse. Of the remaining 621 campylobacteriosis cases, 377 (60.7%) were infected outside Germany, 74 (11.9%) were infected in German Laender other than Hesse, and for 170 (27.4%) details of the place of infection were not available. Only the 2,710 cases reported to have acquired their infection in Hesse were included in this study. Of these, 2,673 (98.6%) were laboratory confirmed, for 1,581 (58.3%) species information was available, and 43 (1.6%) cases were part of nine small clusters, each of three to six cases.
Campylobacteriosis incidence for Hesse and all age groups was 44 per 100,000 population, (2,710 of 6,095,055) and did not differ by degree of urbanicity (urban area: 43.0, 95% CI: 41.0–45.2; intermediate area: 48.5, 95% CI: 44.9–52.3; rural area: 44.1, 95% CI: 40.0–48.7). Of the 2,710 infections acquired in Hesse, 53.3 % (1,445) were male and 46.5% (1,259) were female. For six cases details of their sex were not available. For males and females campylobacteriosis incidence did not vary by degree of urbanicity (data not shown).
Campylobacteriosis incidence was highest in children under five years of age (annual incidence: 61 per 100,000 population) and in people aged 15–44 years (annual incidence: 56 per 100,000 population), and lowest in people older than 65 years (annual incidence: 29 per 100,000 population). In the age groups under five years and 5–14 years, campylobacteriosis incidence varied largely by degree of urbanicity (Table 2). When compared with living in IUAs, living in IRAs was significantly associated with a higher campylobacteriosis incidence in children aged under five years of age (IRR: 2.9, 95% CI: 1.9–4.4). For children aged 5–14 years, living in IRAs (IRR: 2.1, 95% CI: 1.3–3.1) and in intermediate areas (IIA IRR: 1.8, 95% CI: 1.2–2.7; OIA IRR: 2.1, 95% CI: 1.3–3.3) was significantly associated with a higher campylobacteriosis incidence. For children aged under five years and those aged 5–14 years, the association between living in the ORAs and higher campylobacteriosis incidence was not statistically significant (children under five years IRR: 1.8, 95% CI: 0.8–3.6; children aged 5–14 years IRR: 1.6, 95% CI: 0.8–3.0) (Figures 1 and 2). 

Table 2. Association between campylobacteriosis cases and degree of urbanicity, by age group, Hesse, Germany, July 2005 – June 2006 (n=2,710)

Figure 2. Age-specific incidence rate ratios and 95% confidence intervals, by degree of urbanicity, Hesse, Germany, July 2005 – June 2006



We then calculated the attributable risk of living in non-urban areas for children aged 0–14 years In the exposed children, the risk was 46%; the population attributable risk was 25%.
While urban–rural differences were most pronounced in children 14 years of age and younger, they were also seen in the three older age groups. In these age groups there was a tendency towards lower campylobacteriosis incidences for persons living in more rural areas (Figure 2). However, only for those aged 65 years and above living in ORAs did this difference reach statistical significance (IRR: 0.5, 95% CI: 0.2–1.0).
Of 1,581 cases with species information, 15% (n=243 were infected with C. coli, 81% (n=1,282) with C. jejuni, 3% (n=49) with C. lari, and less than 1% (n=7) with other Campylobacter species. The proportion of culture-confirmed cases did not differ by degree of urbanicity: 88.7%, 87.4% and 89.4% of cases were culture confirmed in urban, intermediate and rural areas, respectively. However, a higher proportion of isolates from patients in non-urban areas were differentiated to species level: 53.7%, 79.4% and 71.3% of culture-confirmed cases were differentiated to species level in urban, intermediate and rural areas, respectively (Pearson's chi-square test p<0.001). When compared with urban areas, species-specific incidences for C. coli and C. jejuni were higher in rural and intermediate areas. However, when the number of C. coli and C. jejuni cases was corrected for incomplete differentiation to species level, only incidence of C. coli infections differed by degree of urbanicity (Table 3). In addition, a relatively higher proportion of C. coli cases lived in non-urban areas: the ratio of the C. coli to C. jejuni cases (corrected) was 0.13 in urban areas, 0.26 in intermediate areas and 0.28 in rural areas.
Table 3. Association between campylobacteriosis cases and degree of urbanicity, by Campylobacter species, Hesse, Germany, July 2005 – June 2006


Discussion
In this analysis, degree of urbanisation was found to be associated with campylobacteriosis in children under 15 years of age. Calculation of the attributable risk indicated that 25% of all reported cases of campylobacteriosis aged under 15 years were associated with living in non-urban areas. These attributable risk calculations reflect the degree to which the true, unknown sources of infection are more abundant in non-urban areas than in urban areas.
Recent studies investigated urban–rural differences in campylobacteriosis incidence in Canada [15], the Netherlands [16], Scotland [17], Denmark [18] and Sweden [19]. Four of these studies found higher incidences in rural environments [15, 17-19] and one in urban and urbanised environments [16]. The authors of the last study suggested the higher incidence of campylobacteriosis in urban and urbanised areas could be related to higher consumption of ready-to-eat foods. Of the two studies that presented age-specific data, one reported the greatest urban–rural differences for children 0–4 years-old [15] and one that urban–rural differences were limited to children 0–14 years of age [18]. Authors of both studies suggested that contact with farm animals and the environment were the source of a substantial proportion of sporadic Campylobacter infections.
When interpreting age-specific differences in urban–rural gradients of campylobacteriosis incidence, two main factors need to be considered: age-specific risk factors for infection and immunity acquired during childhood towards local, i.e. rural sources of Campylobacter infection. Few studies reported on age-specific risk factors for campylobacteriosis [20-25]. However, in case–control studies on risk factors for the disease in infants and young children food exposures explained less than 40% of the infections [20,22,23]. Campylobacter infections in these age groups have been associated with contacts with diarrhoeic pets [20,23,24] and live chickens [24,25], drinking water from a well, lake or river [20,23], riding in a shopping trolley next to meat or poultry [23], visiting or living on a farm [23], ownership of farm animals or visiting farm animals outside the household [22] as well as different food exposures. Among these food exposures were the consumption of fruits and vegetables prepared at home [23], mayonnaise [24], butter [25], porridge [25], undercooked meat [22], products containing raw eggs [22] and grilled meat [20,22]. In contrast to many other published case–control studies [4-5], these studies did not find an association between eating chicken and Campylobacter infection. In the light of these findings we believe that environmental exposure accounts for a considerable part of Campylobacter infections in children and that children living in non-urban areas have more opportunities for direct or indirect contact with animals or their excrement. In addition, children living in urban and rural environments may differ in their eating and drinking habits. C. jejuni outbreaks, for example, have been repeatedly related to the consumption of raw milk [26]; children living in non-urban areas may drink raw milk more frequently.
The absence of urban–rural differences in campylobacteriosis incidence in persons aged 15 years and above may be related to differences in behaviour and/or a higher level of immunity from previous exposures [27]. In developing countries, clinical disease due to C. jejuni is common among children younger than two years, but rare among individuals later in life [28]. This relative absence of disease is thought to be related to acquired immunity [29]. If a higher proportion of inhabitants of Hessian rural areas aged 15 years and above are immune to Campylobacter infection, then the association between living in rural areas and campylobacteriosis may be decreased or even reversed. These questions should be addressed in Campylobacter seroprevalence studies or the inclusion of only non-immune controls in future case–control studies for the identification of risk factors.
In our study, 15% of all campylobacteriosis cases with species information were due to C. coli. Germany is one of the European Union Member States with the highest proportion of cases due to C. coli [30]. Within Germany, the proportion of cases due to C. coli differs widely between States and is higher in the former East German or new Laender (in 2006, 14% of all cases (n=7,494) with species information) than in the former West German or old Laender (in 2006, 6% (n=26,205). For whole of Germany, the proportion in 2006 was 8% (n=33,699) [2]. The new Länder are more rural, i.e. the population density is lower [31], a greater proportion of the total area is agricultural [32] and a smaller proportion of the total area is inhabited [33].
When analysing species–specific differences in campylobacteriosis incidence in urban, intermediate and rural areas and correcting for differences in frequency of species differentiation, we found a higher incidence for C. coli in non-urban areas. Microbiological data show that the prevalence of different Campylobacter species varies between different potential sources of infection, including animal species, food and water [10,34,35]. Poultry has been recognised as the primary reservoir of C. jejuni, while pigs are mostly implicated as reservoirs of C. coli [36-38]. Differences in food-borne exposures between C. coli and C. jejuni have been shown to exist [22,39] and differences in consumption habits between persons living in urban and rural areas may contribute to the observed difference in species distribution. However, it has been suggested that C. coli may survive in the environment better than C. jejuni [10] and people living in non-urban areas may be exposed more frequently to environmental sources of C. coli.
This study is limited by constraints inherent to all ecological analyses: a sample size limiting detailed subgroup analysis and a limited availability of further data on municipality level (for example, information on water supply, animal density or consultation of health services and diagnostic practices). However, our analysis suggests that differences in risk factors by Campylobacter species, cases' age and degree of urbanicity do exist. 

Acknowledgements
We thank the Hessian Public Health Offices for providing, in addition to case reports, data on municipality of campylobacteriosis cases. We are also grateful to Thomas Pütz, Federal Office of Building and Regional Planning, Bonn, Germany, for providing data on degree of urbanicity for the Hessian municipalities.
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