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Appl Environ Microbiol. 2009 December; 75(24): 7700–7709.
Published online 2009 October 9. doi:  10.1128/AEM.01852-09
PMCID: PMC2794122

Characteristics and Dynamics of Salmonella Contamination along the Coast of Agadir, Morocco[down-pointing small open triangle]


The occurrence of Salmonella enterica in the environment of tropical and desert regions has remained largely uninvestigated in many areas of the world, including Africa. In the present study, we investigated the presence of Salmonella spp. along 122 km of the coastline of Agadir (southern Morocco) in relation to environmental parameters. A total of 801 samples of seawater (243), marine sediment (279), and mussels (279) were collected from six sites between July 2004 and May 2008. The overall prevalence of Salmonella spp. was 7.1%, with the highest occurrence in mussels (10%), followed by sediment (6.8%) and seawater (4.1%). Only three serotypes were identified among the 57 Salmonella sp. strains isolated. S. enterica serotype Blockley represented 43.8% of all Salmonella strains and was identified in mussel and sediment samples. S. enterica serotype Kentucky (29.8%) was found almost exclusively in mussels, whereas S. enterica serotype Senftenberg (26.3%) was detected in sediment and seawater. Statistical analysis using generalized additive models identified seawater temperature, environmental temperature, rainfall, and solar radiation as significant factors associated with the presence of Salmonella. Rainfall was the only variable showing a linear positive effect on the presence of Salmonella in the sea, whereas the remaining variables showed more complex nonlinear effects. Twenty-eight (49.1%) Salmonella isolates displayed resistance to ampicillin (22 isolates), nalidixic acid (9 isolates), sulfonamide compounds (2 isolates), and tetracycline (1 isolate), with six of these isolates displaying multiple resistance to two of these antimicrobial agents. Pulsed-field gel electrophoresis analysis revealed homogenous restriction patterns within each serotype that were uncorrelated with the resistance pattern profiles.

Salmonella enterica bacteria are one of the most frequent causes of food-borne infections transmitted to humans, mainly from animal products (9). In addition to health concerns, the presence of Salmonella contamination in the food chain has serious economic consequences related to the costs of medical care and lost productivity (36). Thus, studies aimed at examining the capacity of Salmonella spp. to survive in different habitats are critical for controlling contamination and understanding the routes of colonization of new hosts (40).

Salmonella bacteria display a high degree of resistance to a large variety of stress factors, which provides them with an enhanced capacity to persist in changing environments (40). However, the persistence of the organism outside of the host is not uniform among the different serogroups (3, 4, 13, 24, 32, 34). About 50 of the more than 2,500 different serotypes of Salmonella included in the current classification scheme (29) are dominantly identified in human and animal sources (34). Information about groups that predominate in a given environment and their relationship to potential human or animal origins remains scarce. In recent years, some studies carried out in aquatic environments have provided new insights into the ecological preferences of different Salmonella serogroups in these environments. These studies have revealed the presence of specific patterns of contamination in different geographical areas in association with environmental and oceanographic variables (13, 24, 32) and have identified major factors and conditions that favor the presence of the contaminating bacteria. Identification of the different Salmonella strains present in the environment at serotype level is an essential preliminary step in discriminating potentially clinically important strains among the Salmonella present in contaminated areas, providing invaluable information about the nature of the contamination and allowing the inference of potential routes of dissemination through microbial source tracking (31). All of this information is critical for an improved assessment of the potential risks to public health associated with Salmonella and for the evaluation of the ecological preferences of the diverse and heterogeneous group of organisms which comprise the genus Salmonella (26).

The lack of information regarding the epidemiology, contamination, and potential routes of transmission of Salmonella is of particular concern in many regions of the world, such as Africa and Central America, where gastrointestinal diseases continue to be a major cause of illness, primarily due to poor sanitary conditions and nutritional deficiencies. In the present study, we investigated the dynamics of Salmonella contamination in the coastal areas of Agadir, a populous region of southern Morocco where shellfish production and maritime tourism are important to the local economy. Information concerning the biological characteristics of the isolates was correlated with environmental data in order to evaluate the climatic conditions that favor contamination of this region by this pathogen and to identify the potential sources of contamination.


Study area.

Agadir is located on the southwestern Atlantic coast of Morocco and covers an area of approximately 170 km2 (Fig. (Fig.1).1). The central area has more than 500,000 inhabitants although the population may sometimes grow to 1,000,000 due to the presence of tourists. The Agadir coast is one of the most important areas of shellfish production in Morocco but is subject to frequent contamination from urban and port wastewater discharges. The climate of Agadir is semiarid, with low annual rainfall, and is influenced by the Sahara. Average annual temperatures range from 14°C to 16°C in January and 19°C to 25°C in July although temperatures may rise to over 40°C under the influence of Saharan winds. The rainy season occurs in autumn and the first weeks of winter, and annual rainfall is highly variable, ranging from 100 mm to 443.20 mm. Coastal waters are further influenced by currents from the Canary Islands, which travel from the southwest to the north. The influx of cold waters into the area is especially important in summer months, resulting in upwelling along the coast. Samples were collected from six sites extending over 122 kilometers along the Agadir coast: Tamri and Cap Ghir located in the northern area, Anza and Tifnit in the central region, and Sidi Rabat and Douira in the southern zones (Fig. (Fig.11).

FIG. 1.
Study area in Agadir with locations of the sampling stations and spatial distribution of the presence of Salmonella bacteria at the different sites throughout the study period, as determined using the GIS data.

Sampling program.

The presence of Salmonella spp. was investigated in 801 samples, including seawater (243), marine sediment (279), and mussels (279), between July 2004 and May 2008. Samples were collected every month from each site over the entire study period, with the exception of Cap Ghir, where sample collection started in September 2005 and included only samples of seawater and mussels.

Analysis of Salmonella isolates.

Samples were collected in sterile containers and transported to the laboratory under refrigeration. The presence of Salmonella spp. was determined according to the ISO 6579:1993 standard method (18). For liquid samples, 100 ml of sample was filtered through a 0.45-μm-pore-size sterile filter (Millipore Corporation, Bedford, MA), and the filter was then placed in 225 ml of buffered peptone water (Merck, Darmstadt, Germany). For solid samples, 25 g of the sample was added to 225 ml of buffered peptone water (Merck) and incubated at 37°C for 20 h. Ten milliliters of preenriched cultures was then transferred to 100 ml of selenite cystine broth (Oxoid, Basingstoke, England), and 0.1 ml was transferred to 10 ml of RV10 Rappaport-Vassiliadis broth (Difco, Sparks, MD). The cultures were then incubated at 37°C and 42°C, respectively, for 24 h. Aliquots of enriched broth were streaked onto Hektoen enteric agar (Oxoid), phenol red-brilliant green agar (Oxoid), and bismuth sulfite agar (Oxoid) and incubated at 37°C for 24 h (if only slight growth was observed, the plates were reincubated for an additional 24 h). Typical colonies were selected and streaked onto nutrient agar and subjected to initial biochemical screening in triple-sugar iron agar (Oxoid). Cultures displaying a reaction typical of Salmonella (an alkaline slant and acid butt, with or without production of H2S) were confirmed by biochemical tests using an API-20E strip (bioMérieux, Marcy-l'Etoile, France) and PCR analysis involving the amplification of a 284-bp fragment of the invA gene, according to the protocol described by Malorny et al. (20).

Salmonella serotyping.

All Salmonella isolates were serotyped by seroagglutination with commercial antiserum (Statens Serum Institut, Copenhagen, Denmark). Polyvalent Salmonella O and H antisera were used to obtain a presumptive diagnosis, and the definitive antigenic designation was then assigned by using monovalent antisera.


Pulsed-field gel electrophoresis (PFGE) was performed according to the 1-day (24 to 28 h) standardized laboratory protocol for molecular subtyping of nontyphoidal Salmonella by PFGE (6). Chromosomal DNA was digested with 50 U of XbaI (Promega, Southampton, United Kingdom). PFGE was performed on a CHEF DRIII system (Bio-Rad, Hercules, CA) in 0.5× Tris-Borate-EDTA extended-range buffer (Bio-Rad) with recirculation at 14°C. DNA macrorestriction fragments were resolved on 1% SeaKem Gold agarose (Cambrex) in 0.5× Tris-Borate-EDTA buffer. DNA from S. enterica serotype Braenderup H9812 restricted with XbaI was used as a size marker. Pulse times were ramped from 2.2 to 63.8 s during an 18-h run at 6.0 V/cm. Macrorestriction patterns were compared using BioNumerics software (Applied Maths, Sint-Martens-Latem, Belgium).

Antimicrobial susceptibility testing.

Isolates were screened for susceptibility to 16 antibiotics on Mueller-Hinton agar (Oxoid, Basingstoke, Hampshire, United Kingdom) by disk diffusion, as described in the Clinical Laboratory Standard Institute (formerly NCCLS) guidelines (7). The following disks (Oxoid) were used: amikacin (30 μg), apramycin (15 μg), amoxicillin-clavulanic acid (30 μg), ampicillin (10 μg), chloramphenicol (10 μg), cefoperazone (30 μg), ceftazidime (30 μg), colistin (25 μg), furazolidone (15 μg), gentamicin (10 μg), nalidixic acid (30 μg), neomycin (10 μg), streptomycin (25 μg), sulfamethoxazole-trimethoprim (25 μg), sulfonamide compound (300 μg), and tetracycline (10 μg).

Environmental parameters.

The environmental parameters considered in the study were air temperature, wind, hours of sunshine per day, rainfall, solar radiation, salinity, and seawater temperature. The minimum, maximum, and average daily air temperatures were recorded each day. Wind direction was measured as the time in hours that the wind blew in each of the four prevailing quadrants (northwest, northeast, southwest, and southeast) or was measured as no wind (calm). Wind speed was expressed as kilometers per day. Rainfall was measured as millimeters of precipitation per day, and solar radiation was measured as watts per square meter (W/m2). All the climatic data were provided by Le Service Climatologique de Sud de la Direction Régional de la Méterologie Nationale from the Agadir-Inezguane station (9°34′58.5"W, 30°25′10.18"N). Salinity and seawater temperature were recorded on each sampling day at each sampling site, with a conductivity meter (WTW, Weilheim, Germany).

Spatial analysis.

The results of the analyses were processed by using the geographical information system (GIS) ArcGIS software (ArcView, version 3.3), produced by the Environmental Systems Research Institute. The data formats were Shapefile (vector data) and were provided by the Agence Nationale de la Conservation Foncière du Cadastre et de la Cartographie, Direction du Cadastre et de la Cartographie.

Statistical analysis.

The associations between environmental factors and the presence of Salmonella spp. were analyzed by generalized additive models (GAMs) (43). Independent models were initially constructed for each environmental variable to select the data set of the variable (data from the same day of sample collection to 4 days prior to sample collection, and the mean values for the 5 days) with the best explanatory values based on the Akaike information criterion (AIC) (1). The selected data sets from each variable were used to construct different models incorporating correlations among binary response data (presence/absence of Salmonella spp.). The final multivariate logistic regression model selected according to both the AIC value and highest proportion of explained deviance was the following:

equation M1

where β0 is an unknown constant, si are unknown partial smooth functions, and logit = log{p[Y = 1/X]/[1 − (Y = 1/X)]}, where X is the vector of the variables considered in the model (i.e., month, solar radiation, etc.), and Y represents the binary outcome of interest (Y = 1 when Salmonella spp. are present and Y = 0 when Salmonella spp. are absent).

To ensure identification of the above logistic GAM, the smooth functions si are all centered on the mean (i.e., zero-mean functions).

Additionally, GAMs for continuous response were used to obtain the predicted values of the environmental variables (seawater temperature, salinity, environmental temperature, rainfall, and solar radiation) over the course of the study.

In all the GAMs considered, thin-plate regression splines (41) were used as smoothers of s, with optimal smoothing parameters (or, equivalently, with optimal effective degrees of freedom [edf]) chosen automatically by use of (i) the unbiased risk estimator (42, 43) criterion for GAMs with a binary response or (ii) the generalized cross-validation (43) criterion for GAMs with a continuous response.

Relationships between the presence of each serotype and the environmental variables were analyzed with the use of the following logistic generalized linear model (25):

equation M2

where, β = (β0, β1, β2, β3, β4, β5, β5) is the vector of the parameters. The strength of the associations between the binary response and each of the explanatory variables was evaluated through the calculation of the corresponding adjusted odds ratio ([OR] eβ) with a 95% confidence interval.

All regression models were fitted with the gam function of the mgcv library (43) in the free R software (30), version 2.9.1.


Salmonella spp. were detected in 57 of 801 (7.1%) samples analyzed over the study period (July 2004 to May 2008) (Table (Table1).1). The highest prevalence of Salmonella bacteria was detected in mussels, with 28 positive samples occurring in the 279 analyzed (10%), followed by sediment, with 19 positive samples (6.8%), and seawater, with 10 positive samples (4.1%) (Table (Table1).1). The prevalence of Salmonella spp. was significantly higher (P < 0.05) in mussel and sediment samples than in seawater samples (Table (Table22).

Number of samples collected and prevalence of Salmonella bacteria in the different sample types
Estimated coefficients of the categorical predictors for the logistic GAM with SE, z-statistic, and P values

The presence of Salmonella at the six sampling sites (Table (Table22 and Fig. Fig.1)1) was significantly higher (P < 0.05) in Tifnit and Anza (southern and central areas), where 20 (13.8%) and 15 (11%) positive samples, respectively, were detected (Table (Table3).3). The site with the lowest occurrence of Salmonella spp. was Douira, with 5 positive samples occurring in the 144 studied (3.5%). Finally, no positive samples were detected in Cap Ghir (northern area).

Incidence of Salmonella spp. at each sampling site over the course of the study period

Salmonella bacteria were detected throughout the period of study. The presence of Salmonella spp. was higher in 2006, with 22 positive samples occurring in a total of 201 samples (10.9%), and lower in 2008, when the bacteria were found in only 1.7% of the 116 samples analyzed. The highest incidence coincided with autumn (13%) and the winter months (12%) and reached a maximum in November 2006, when 47.1% positive samples were detected (Fig. (Fig.2).2). In contrast, Salmonella spp. were rarely detected in spring and summer during the 4 years of the study, with two (1%) and three (1.5%) positive samples, respectively.

FIG. 2.
Overall incidence of Salmonella bacteria along the Agadir coast throughout the study period (A) and variations in rainfall and temperature during the same period (B).

The seasonal trends in the environmental variables (salinity, seawater temperature, environmental temperature, rainfall, and solar radiation) over the period of study were initially evaluated separately using independent GAMs with continuous responses for each variable (Fig. (Fig.3).3). The predicted salinity (data not shown), seawater temperature, and environmental temperature values formed a clear seasonal pattern, with values peaking during the summer months. In contrast, the highest predicted rainfall occurred during the last months of 2004, with a second, less significant, peak toward the end of 2005 and at the beginning of 2006, with no rainfall detected thereafter. Predicted solar radiation showed a variable pattern over the course of the study, with the highest value observed in June 2005, followed by a drastic reduction in November 2005, with high variability being observed throughout the remainder of the study period.

FIG. 3.
Predicted values for the principal environmental variables estimated through the smooth effect (s) obtained from the GAM. Predicted values for seawater temperature (A), environmental temperature (B), rainfall (C), and solar radiation (D) over the course ...

Associations between the environmental and oceanographic parameters considered in the study (salinity, seawater temperature, environmental temperature, rainfall, and solar radiation) and the presence of Salmonella were analyzed by logistic GAM for binary responses. Independent models were constructed for each variable using data from the same day of sample collection to 4 days prior to sample collection and from the mean values for the 5 days. The best explanatory models for each variable, selected on the basis of the AIC, were those constructed using the mean values of the variables, with the exception of rainfall, which showed the lowest AIC value in the data from the 4 days prior to sample collection. Selected data from each variable were used to construct different regression models. The best explanatory model, with AIC and unbiased risk estimator values of 283.07 and −0.601, respectively, accounted for 50% of the deviance explained. The selected model included the environmental variables seawater temperature, environmental temperature, rainfall, and solar radiation, as well as sampling site and sample source, as the variables significantly (P < 0.01) associated with the response (Table (Table44 and Fig. Fig.4).4). Rainfall was the only explanatory environmental variable showing a linear relationship with the presence of Salmonella (Fig. (Fig.4)4) and positively influenced the probability of Salmonella detection. The presence of Salmonella was also positively influenced by solar radiation although this effect was restricted to low values since no effect was observed for values exceeding 5 W/m2. The remaining variables showed more complex nonlinear relationships with the presence of Salmonella. The overall probability of Salmonella detection over the course of our study, as obtained from the final GAM, which integrated the four significant environmental variables (seawater temperature, environmental temperature, rainfall, and solar radiation) in addition to variables of sampling site and the sample source, showed a pattern that was distinctive for each period (Fig. (Fig.4).4). The probability of the presence of Salmonella showed a similar pattern for the years 2005 and 2006, with the presence of Salmonella peaking in May of both years. However, a different pattern was observed in 2007 and 2008, with the highest predicted presence of Salmonella occurring from September of 2007 to January of 2008, followed by a drastic decline after this point.

FIG. 4.
Estimated centered smooth effect (s) of the presence of Salmonella obtained from the GAM. Temporal variation in the probability of detection of Salmonella throughout the period of study (A) and association between the presence of Salmonella and the environmental ...
Estimated nonparametric components of the logistic GAM, with corresponding edf, chi-square statistic, and P values

Serotyping of Salmonella sp. strains revealed three different serotypes among the 57 isolates (Table (Table5).5). The dominant was S. enterica serotype Blockley, which occurred in 25 strains (43.8%), 12 of which were detected in mussels (48%), 12 in sediment samples (48%), and only 1 strain in seawater (4%). PFGE analysis revealed a homogenous pattern of restriction fragments among the strains of this serotype (Fig. (Fig.5).5). Nearly 85% of the strains exhibited indistinguishable pulsotypes, and only four isolates presented slight differences in restriction profiles. S. enterica serotype Kentucky was identified in 17 isolates (29.8%) occurring almost exclusively in mussels (94.1%) and in 1 isolate from sediment (5.9%). All serotype Kentucky isolates showed indistinguishable restriction patterns and grouped into a single cluster. Finally, S. enterica serotype Senftenberg was identified in 15 strains (26.3%), primarily occurring in seawater (60%) but also in sediment, with six isolates (40%). Serotype Senftenberg was entirely absent from mussels. PFGE analysis of serotype Senftenberg isolates showed four different related pulsotypes included in a single cluster with 77.5% similarity. The three serotypes were detected throughout the study area. No significant association between the different serotypes and the environmental variables was obtained by applying the generalized linear models.

FIG. 5.
Dendrogram generated by Bionumerics software showing the relationship between the different PFGE fingerprints and antibiotic resistance patterns of the strains. Antimicrobial resistance, indicated by a black box, was present for amikacin (AK), apramycin ...
Distribution of distinct serotypes among S. enterica isolates obtained throughout the study period per sample type

Almost 50% of the Salmonella isolates obtained in this study showed resistance to at least one antibiotic (Fig. (Fig.5).5). Among the three serotypes identified, serotype Senftenberg displayed the highest degree of resistance, with 60% of the isolates being resistant, followed by serotypes Kentucky and Blockley, with resistances of 47.1% and 44%, respectively. Overall, 22 isolates were resistant to ampicillin (38.6%), 9 to nalixidic acid (15.8%), 2 to sulfonamide compound (3.5%), and 1 to tetracycline (1.7%). Among the 28 resistant isolates, 22 displayed resistance to one antimicrobial agent, and the remaining 6 isolates displayed resistance to two antimicrobial agents. A total of six different resistance patterns were observed among the Salmonella isolates; these were predominantly ampicillin (17 isolates), nalidixic acid (4 isolates), and ampicillin-nalidixic acid (4 isolates) No associations between the resistance patterns and the different genetic profiles identified by PFGE analysis were found (Fig. (Fig.55).


Data on the presence of Salmonella in human and nonhuman sources in Africa are extremely limited. This is true for most developing countries worldwide. Almost 90% of all reported Salmonella isolates submitted to the WHO Global Salm-Surv country databank ( are submitted from North America and Europe (11) even though these regions account for only 16% of the world population (U.S. Census Bureau, International Data Base, Population Division []). The limited information available for other countries seriously restricts the understanding and interpretation of the data obtained in studies carried out in these areas, which cannot be compared with reports from similar areas or with general trends. According to the information included in the WHO Global Salm-Surv country databank provided by the National Institute of Hygiene, Morocco, the dominant serotype isolated from human sources in Morocco between 2000 and 2003 was S. enterica serotype Enteritidis, which accounted for 76.3% of the reported strains in 2003. Animal-related data provided by the same institution showed a well-differentiated pattern of serotype dominance, with S. enterica serotype Gallinarum representing 52.5% of total Salmonella isolates for 2003 and serotype Enteritis representing 12% of strains. Although this information is based on only a small number of strains and is not likely representative of the overall situation in this large country with diverse habitats, the dominance of serotype Enteritidis appears to be a constant feature of most reported human infections. The serotype Enteritidis was prevalent in two studies carried out in Rabat (17, 19), and S. enterica serotypes Wien and Infantis were the second-most frequently isolated serotypes.

The serotype dominance observed in the coastal areas of Agadir throughout the present study exhibited a pattern clearly different from the serotypes reported in human isolates in Morocco. Only three serotypes—Blockley, Kentucky, and Senftenberg—were identified among the 57 Salmonella strains isolated along 122 km of coastline. Serotypes Kentucky, Blockey, and Senftenberg, however, are not included in the top 10 most frequently reported serotypes from human infection and animal sources in Morocco, according to the WHO Global Salm-Surv country databank. The restricted number of serotypes occurring in the coastal regions of Morocco notably contrasts with the high degree of diversity of serotypes previously reported for aquatic and marine environments in many other parts of the world. Typically, environmental studies of rivers and coastal areas have identified between 10 and 20 different serotypes (4, 5, 13, 24, 32, 35, 39). The variety of serotypes has been associated with the presence of highly diverse sources of Salmonella contamination along the shores of rivers and maritime zones (3, 13, 23, 24). Although most contamination is expected to be of animal or human origin, serotypes that prevail in the environment often do not coincide with the most common zoonotic or human serotypes identified in these areas (5, 16, 21, 24, 28, 35, 39). The discrepancy between the dominant serotypes in human and animal hosts and in the environment may be ascribed to the diverse rates of survival of the different Salmonella serotypes in the presence of adverse or stressful conditions (24) although differences in the pathogenic potential and host range of the different serotypes and clones could also influence in the rates of detection (34). S. enterica serotype Typhimurium is the most frequently reported serotype of clinical importance and predominates over other serotypes in most environmental studies (3, 5, 24, 28, 32, 39), a finding that has been attributed to its high survival rate outside the host (3, 10, 24). Serotype Senftenberg is the most resistant to extreme environments (22) and is the most widespread serotype in tropical and temperate marine regions of the world (3, 5, 15, 16, 22, 24, 33). The identification of only three serotypes along the Agadir coast throughout the entire period of the study and among all the sample sites investigated may be directly related to two factors: the particular pattern of Salmonella contamination in this region linked to sources of contamination and the ability of the prevailing serotypes to survive in the environment outside the host. Most of the Salmonella isolates in this study were detected in the central sampling sites, surrounding the mouth of the Souss River, which is the principal river in the region and passes through the populated areas surrounding Agadir.

The present study identified a high rate of antimicrobial resistance which was similarly distributed among the three serotypes identified; almost 50% of the strains displayed resistance to at least one of the antibiotics tested. The antibiotic resistance observed was restricted to four antibiotics which have been reported to be commonly used in veterinary practices in the region (2). Although antimicrobial-resistant bacteria has been identified in areas without any evidence of selective pressure, the presence of resistant and multidrug-resistant strains linked to an enteric bacteria like Salmonella occurring in the marine environment may be considered a very preliminary evidence suggesting the extensive use of antibiotics in veterinary and medical practices for the control of bacterial diseases in the region, as has been reported for other regions (8, 14, 27, 37, 38).

The presence of Salmonella contamination in coastal waters of Agadir was detected throughout the entire period of study, with most of the contamination events coinciding with the periods of rainfall. The statistical analysis identified the presence of rain as a direct factor favoring the occurrence of Salmonella in coastal areas, especially when rainfall occurred in the days immediately prior to sample collection. As found in the present study, the influence of rainfall as the primary factor in determining Salmonella contamination events in rivers and coastal areas has been reported in various other studies carried out in diverse geographical areas worldwide (3, 12, 13, 24, 32). Rainfall has been identified as the universal environmental driver for the presence of Salmonella in the environment (32), with storm waters participating in the transport of Salmonella from its source points to marine environments by aquifers (13, 24, 32). Recognition of the decisive role that rainfall plays in the process of environmental contamination by Salmonella provides a practical tool for the development of simple surveillance programs to prevent contamination events in natural habitats and food-producing areas and, consequently, to further advance the methods of controlling diseases caused by this organism.


Ibtissame Setti received a travel grant to carry out research at the University of Santiago de Compostela, funded by project number A/012228/07 from the Agencia Española de Cooperación Internacional para el Desarrollo. The work of M.P.P. and C.C.-S. was supported by grants MTM2008-001603 from the Ministerio de Ciencia e Innovación and INCITE08PXIB208113PR from the Xunta de Galicia.

We are grateful to Isabel Mayán Barreiro and Silvia Carlés Gonzalez (University of Santiago de Compostela) and A. Hanoune (Institut National de Recheche Halieutique) for technical assistance and to Morjani Zine for help with the GIS analysis. We also thank A. Berraho, A. Chafik, A. Bernoussi, and A. Lahnin for their support in the development of the present study.


[down-pointing small open triangle]Published ahead of print on 9 October 2009.


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