scholarly journals Spatial distribution ofSalmonella entericain poultry shed environments observed by intensive longitudinal environmental sampling

2019 ◽  
Author(s):  
Helen K Crabb ◽  
Joanne Lee Allen ◽  
Joanne Maree Devlin ◽  
Colin Reginald Wilks ◽  
James Rudkin Gilkerson
Keyword(s):  
Salmonella Enterica ◽  
Spatial Location ◽  
Epidemiological Studies ◽  
Epidemiological Surveillance ◽  
Environmental Sampling ◽  
Sample Collection ◽  
The North ◽  
Serovar Typhimurium ◽  
The Difference ◽  
Spatial Locations

ABSTRACTDuring a series of epidemiological studies to investigate the transmission of salmonellae within poultry environments, intensive longitudinal sampling within caged sheds revealed that both the number and location of sample collection within this environment were important to ensure the best chance of detectingSalmonellaspp. Multiple serovars ofSalmonella entericasubspeciesentericawere detected in each shed; 5% of all samples contained more than one serovar. Samples collected on the north side of the shed (OR = 1.77, 95% CI [1.17, 2.68]), on the sheltered side of the shed (OR = 1.90, 95% CI [1.26, 2.89]) and during winter (OR = 48.41, 95%CI [23.56, 104.19]) were more likely to be positive for salmonellae. The distribution of salmonellae within a shed was not homogenous, as differences were identified in the within-shed distribution ofSalmonella entericasubspeciesentericaserovar Typhimurium (χ2(27, 1,538) = 54.4, P < 0.001), andSalmonella entericasubspeciesentericaserovar Infantis (χ2(27, 1,538) = 79.8, P < 0.0001). The difference in sample prevalence by serovar and spatial location within a shed indicates that there are important shed micro-environmental factors that influence survival and/or distribution of salmonellae. These factors should be taken into consideration when undertaking environmental surveillance for salmonellae in flocks housed in caged sheds.IMPORTANCERoutine epidemiological surveillance for salmonellae in poultry relies initially on environmental sampling. Our study confirmed that the sampling methodology conducted within a poultry environment is a non-trivial part of sampling design. The spatial locations of sample collection within a shed revealed differences in both the sample prevalence and serovar of salmonellae detected.

scholarly journals Spatial Distribution ofSalmonella entericain Poultry Shed Environments Observed by Intensive Longitudinal Environmental Sampling

2019 ◽  
Vol 85 (14) ◽  
Author(s):  
Helen K. Crabb ◽  
Joanne Lee Allen ◽  
Joanne Maree Devlin ◽  
Colin Reginald Wilks ◽  
James Rudkin Gilkerson
Keyword(s):  
Spatial Distribution ◽  
Salmonella Enterica ◽  
Spatial Location ◽  
Epidemiological Surveillance ◽  
Environmental Sampling ◽  
Sample Collection ◽  
Content Type ◽  
The North ◽  
Serovar Typhimurium ◽  
Microenvironmental Factors

ABSTRACTDetection of salmonellae within poultry environments is an important component of many food safety programs, but sampling approaches vary greatly and may not enable the detection of salmonellae when bacteria are present at a low prevalence or concentration. Intensive longitudinal sampling within caged sheds enabled us to undertake a longitudinal analysis of the spatial distribution of salmonellae in caged shed environments. Both the number of samples collected and location of sample collection within a poultry shed were important to ensure the best chance of detectingSalmonellaspp. Differences in the within-shed spatial distribution ofSalmonella entericasubspeciesentericaserovar Typhimurium [χ2(27, 1,538) = 54.4;P < 0.001] andSalmonella entericasubspeciesentericaserovar Infantis [χ2(27, 1,538) = 79.8;P < 0.0001] were identified. More than oneSalmonella entericaserovar was detected in each shed on the same sampling occasion; 5% of all samples contained more than one serovar. Samples collected on the north side of the shed (odds ratio [OR], 1.77; 95% confidence interval [CI], 1.17–2.68), on the sheltered side of the shed (OR, 1.90; 95% CI, 1.26–2.89), and during winter (OR, 48.41; 95% CI, 23.56–104.19) were more likely to be positive for salmonellae. The within-shed differences observed in the both the sample prevalence and spatial location of the serovar detected indicate that there are important shed microenvironmental factors that influence the survival and/or distribution of salmonellae. These factors should be taken into consideration when environmental surveillance is undertaken for salmonellae in flocks housed in cage sheds.IMPORTANCERoutine epidemiological surveillance for salmonellae in poultry relies initially on environmental sampling. Intensive, spatially homogenous sampling, as conducted within this study, confirmed that the sampling methodology conducted within a poultry environment is a nontrivial part of sampling design. The frequency of sampling is especially important when the prevalence ofSalmonellaspp. is low. These factors must be taken into consideration in the design of studies for the detection of salmonellae in poultry sheds.

scholarly journals An unusual way to validate regional chemistry-transport models

2016 ◽  
Author(s):  
Lauren Menut ◽  
Sylvain Mailler ◽  
Bertrand Bessagnet ◽  
Guillaume Siour ◽  
Augustin Colette ◽  
...  
Keyword(s):  
Model Evaluation ◽  
Temporal Correlation ◽  
Spatial Location ◽  
Reference Period ◽  
Evaluation Technique ◽  
Transport Models ◽  
Time Periods ◽  
The Difference ◽  
Spatial Locations

Abstract. A simple and exhaustive model evaluation technique for regional chemistry-transport is discussed. It is based on the concept that we can learn more on models performances by comparing the results to in situ measurements available for other time periods than the period originally targeted in the simulation. First, the usual scores (spatial and temporal correlation) are computed for a reference period, using the actual temporal synchronization and spatial location of measurements . Second, the same scores are calculated for several other years by conserving only the actual spatial locations and days of the year. The difference between the two score provides complementary insights to the following questions: (i) is the model performing well only because the situation is persistent? (ii) is the model representative enough of the measurements for all variables? (iii) if the pollutants concentrations are not well modelled, is it due to meteorology or chemistry? In order to synthetize the large amount of results, a new score is proposed: the "multi-year variability", designed to compare the several indicators between all the years of validation and to quantify if the studied period was well modelled and, if yes, for the good reasons.

Note. Genetic Diversity of Food Isolates of Salmonella enterica serovar Typhimurium in India

2008 ◽  
Vol 14 (2) ◽  
pp. 151-156 ◽  
Author(s):  
S.D. Saroj ◽  
R. Shashidhar ◽  
J.R. Bandekar
Keyword(s):  
Genetic Diversity ◽  
Salmonella Enterica ◽  
Salmonella Enterica Serovar Typhimurium ◽  
Genotypic Diversity ◽  
Epidemiological Studies ◽  
Plasmid Profile ◽  
Specific Pattern ◽  
Pulsed Field ◽  
Fish Samples ◽  
Serovar Typhimurium

The study aimed to determine the genetic diversity of Salmonella enterica serovar Typhimurium isolates from sprouts and fish samples from India. Twenty-eight S. Typhimurium isolates were genotyped by pulsed-field gel electrophoresis and tested for antibiotic susceptibility, plasmid profile, and presence of virulence genes ( invA and spvC). Three distinct XbaI-pulsed-field profiles (PFPs) were observed. Out of 22 isolates from sprouts, 20 showed PFP-A and remaining two showed PFP-B. All six fish isolates showed PFP-C. All the strains were sensitive to the examined antibiotics except two strains of PFP-A. Two different plasmid profiles P1 and P2 were observed. P2 was observed only in the antibiotic resistant strains. All strains were positive for the invA, whereas spvC was detected only in sprout isolates. There was no specific pattern in occurrence of the genotypes with respect to seasons. However, PFP-A was dominant and was isolated throughout the year. This is the first report to assess the genotypic diversity of S. Typhimurium obtained in foods from India. As S. Typhimurium is the predominant serotype in India, the data generated in this study would be useful in epidemiological studies during outbreaks of Salmonellosis in India.

Dynamic Visual Noise Affects Visual Short-Term Memory for Surface Color, but not Spatial Location

2010 ◽  
Vol 57 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Kevin Dent
Keyword(s):  
Short Term Memory ◽  
Spatial Location ◽  
Visual Noise ◽  
Dynamic Visual Noise ◽  
Short Term ◽  
Surface Color ◽  
Term Memory ◽  
Visual Short Term Memory ◽  
Experimental Tool ◽  
Spatial Locations

In two experiments participants retained a single color or a set of four spatial locations in memory. During a 5 s retention interval participants viewed either flickering dynamic visual noise or a static matrix pattern. In Experiment 1 memory was assessed using a recognition procedure, in which participants indicated if a particular test stimulus matched the memorized stimulus or not. In Experiment 2 participants attempted to either reproduce the locations or they picked the color from a whole range of possibilities. Both experiments revealed effects of dynamic visual noise (DVN) on memory for colors but not for locations. The implications of the results for theories of working memory and the methodological prospects for DVN as an experimental tool are discussed.

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