Risk Factors for Human Salmonellosis Originating from Pigs, Cattle, Broiler Chickens and Egg Laying Hens: A Combined Case-Control and Source Attribution Analysis

<div><p>Several case-control studies have investigated risk factors for human salmonellosis while others have used <i>Salmonella</i> subtyping to attribute human infections to different food and animal reservoirs. This study combined case-control and source attribution data into a single analysis to explore risk factors at the point of exposure for human salmonellosis originating from four putative food-producing animal reservoirs (pigs, cattle, broilers and layers/eggs) in the Netherlands. We confirmed that most human cases (∼90%) were attributable to layers/eggs and pigs. Layers/eggs and broilers were the most likely reservoirs of salmonellosis in adults, in urban areas, and in spring/summer, whereas pigs and cattle were the most likely reservoirs of salmonellosis in children, in rural areas, and in autumn/winter. Several reservoir-specific risk factors were identified. Not using a chopping board for raw meat only and consuming raw/undercooked meat were risk factors for infection with salmonellas originating from pigs, cattle and broilers. Consuming raw/undercooked eggs and by-products were risk factors for layer/egg-associated salmonellosis. Using antibiotics was a risk factor for pig- and cattle-associated salmonellosis and using proton-pump inhibitors for salmonellosis attributable to any reservoir. Pig- and cattle-associated infections were also linked to direct contact with animals and environmental exposure (e.g. playing in sandboxes). Eating fish, meat in pastry, and several non-meat foods (fruit, vegetables and pasteurized dairy products) were protective factors. Consuming pork and occupational exposure to animals and/or raw meats were protective against layer/egg-associated salmonellosis. We concluded that individuals acquiring salmonellosis from different reservoirs have different associated risk factors, suggesting that salmonellas may infect humans through various transmission pathways depending on their original reservoirs. The outcome of classical case-control studies can be enhanced by incorporating source attribution data and vice versa.</p></div

Molecular Detection of Tick-Borne Pathogens in Humans with Tick Bites and Erythema Migrans, in the Netherlands

<div><p>Background</p><p>Tick-borne diseases are the most prevalent vector-borne diseases in Europe. Knowledge on the incidence and clinical presentation of other tick-borne diseases than Lyme borreliosis and tick-borne encephalitis is minimal, despite the high human exposure to these pathogens through tick bites. Using molecular detection techniques, the frequency of tick-borne infections after exposure through tick bites was estimated.</p><p>Methods</p><p>Ticks, blood samples and questionnaires on health status were collected from patients that visited their general practitioner with a tick bite or erythema migrans in 2007 and 2008. The presence of several tick-borne pathogens in 314 ticks and 626 blood samples of this cohort were analyzed using PCR-based methods. Using multivariate logistic regression, associations were explored between pathogens detected in blood and self-reported symptoms at enrolment and during a three-month follow-up period.</p><p>Results</p><p>Half of the ticks removed from humans tested positive for <i>Borrelia burgdorferi</i> sensu lato, <i>Anaplasma phagocytophilum</i>, <i>Candidatus</i> Neoehrlichia mikurensis, <i>Rickettsia helvetica</i>, <i>Rickettsia monacensis</i>, <i>Borrelia miyamotoi</i> and several <i>Babesia</i> species. Among 92 <i>Borrelia burgdorferi</i> s. l. positive ticks, 33% carried another pathogen from a different genus. In blood of sixteen out of 626 persons with tick bites or erythema migrans, DNA was detected from <i>Candidatus</i> Neoehrlichia mikurensis (n = 7), <i>Anaplasma phagocytophilum</i> (n = 5), <i>Babesia divergens</i> (n = 3), <i>Borrelia miyamotoi</i> (n = 1) and <i>Borrelia burgdorferi</i> s. l. (n = 1). None of these sixteen individuals reported any overt symptoms that would indicate a corresponding illness during the three-month follow-up period. No associations were found between the presence of pathogen DNA in blood and; self-reported symptoms, with pathogen DNA in the corresponding ticks (n = 8), reported tick attachment duration, tick engorgement, or antibiotic treatment at enrolment.</p><p>Conclusions</p><p>Based on molecular detection techniques, the probability of infection with a tick-borne pathogen other than Lyme spirochetes after a tick bite is roughly 2.4%, in the Netherlands. Similarly, among patients with erythema migrans, the probability of a co-infection with another tick-borne pathogen is approximately 2.7%. How often these infections cause disease symptoms or to what extend co-infections affect the course of Lyme borreliosis needs further investigations.</p></div

Median percent probabilities for human salmonellosis cases to originate from pigs, cattle, broilers or layers/eggs according to age group, gender, urbanization degree, and season.

<p>The Netherlands, 2002–2003.</p

Detected DNA sequences in 314 ticks obtained from 293 participants.

<p>The results on <i>B</i>. <i>burgdorferi</i> s. l. have been published by Hofhuis et al. 2013 [<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0005042#pntd.0005042.ref029" target="_blank">29</a>].</p

Characteristics of participants with DNA of tick-borne pathogens detected in blood.

<p>Characteristics of participants with DNA of tick-borne pathogens detected in blood.</p

Prevalence of DNA detection of tick-borne pathogens in blood of persons with tick bites or erythema migrans (EM), as determined by PCRs.

<p>Prevalence of DNA detection of tick-borne pathogens in blood of persons with tick bites or erythema migrans (EM), as determined by PCRs.</p

Adjusted odds ratios and 95% confidence intervals of the significant risk factors for human salmonellosis attributable to specific animal reservoirs and overall.

<p>Odds ratios presented are also adjusted for age, sex, degree of urbanization, season, and level of education. Risk factors are in bold, protective factors in normal font. Estimates are based on 414 cases (168 and 197 of which caused by <i>S.</i> Enteritidis and <i>S.</i> Typhimurium, respectively) and 3165 controls.</p

Phylogenetic tree of the sequences obtained from human blood samples.

<p>PCR and sequencing was performed on the real-time PCR-positive blood samples. Sequences were clustered with (reference) sequences from Genbank. The evolutionary distance values were determined by Kimura method, and the tree was constructed according to the neighbor-joining method. A.) <i>Anaplasma phagocytophilum</i>: Phylogenetic tree of partial heat shock protein gene <i>groEL</i> of <i>Anaplasma phagocytophilum</i> of the four, one sequences is slightly different by couple of mismatches. All four are part of zoonotic variant of <i>Anaplasma phagocytophilum</i>. B.) <i>Babesia</i> genospecies: Three of the tested blood samples for <i>Babesia</i> genospecies yielded a sequence for the ribosomal <i>18S rRNA</i> gene, and showed to be identical to <i>B</i>. <i>divergens</i> sequences. C.) <i>Candidatus</i> Neoehrlichia mikurensis: Five out of seven <i>Candidatus</i> Neoehrlichia mikurensis yielded a partial sequence of the citrate synthase gene <i>gltA</i>. D.) <i>Candidatus</i> Neoehrlichia mikurensis: All seven <i>Candidatus</i> Neoehrlichia mikurensis yielded a partial sequence of the heat shock protein gene <i>groEL</i>.</p

Plot of the first and second canonical dimension of the multivariate relationships between <i>Salmonella</i> subtype reservoir specificity (<i>Pr</i>s) and the significant risk factors.

<p>Blue squares: <i>S</i>. Typhimurium subtypes. Red dots: <i>S</i>. Enteritidis subtypes. Green triangles: other <i>Salmonella</i> subtypes. Yellow stars: reservoir centroids. Total variance explained by the first and second canonical dimensions is 82% and 15%, respectively.</p

Unit costs in the Netherlands, 2013 (all costs are in Euros).

<p>*We regarded all consultations as though children had visited the doctor.</p><p>**The costs of antibiotics, antiviral and other medications prescribed by a GP were assumed equal and included pharmaceutical fees.</p><p>***Costs for analyzing blood, urine, respiratory and fecal material in the laboratory were assumed equal.</p><p>****We assumed that transport to a doctor would cost €0.21 per km regardless whether care or public transport was used. We set the average distance from a household to a doctor at 1.1 km.</p><p>*****Productivity losses were estimated per working days lost (1 day = 8 hours' work) using standard tariffs according to gender and age-class.</p