scholarly journals A Mathematical Model of Campylobacter Dynamics Within a Broiler Flock

2019 ◽  
Vol 10 ◽  
Author(s):  
Thomas Rawson ◽  
Marian Stamp Dawkins ◽  
Michael B. Bonsall
2005 ◽  
Vol 71 (10) ◽  
pp. 5765-5770 ◽  
Author(s):  
T. J. W. M. Van Gerwe ◽  
A. Bouma ◽  
W. F. Jacobs-Reitsma ◽  
J. van den Broek ◽  
D. Klinkenberg ◽  
...  

ABSTRACT Campylobacter species are frequently identified as a cause of human gastroenteritis, often from eating or mishandling contaminated poultry products. Quantitative knowledge of transmission of Campylobacter in broiler flocks is necessary, as this may help to determine the moment of introduction of Campylobacter in broiler flocks more precisely. The aim of this study was to determine the transmission rate parameter in broiler flocks. Four experiments were performed, each with four Campylobacter-inoculated chicks housed with 396 contact chicks per group. Colonization was monitored by regularly testing fecal samples for Campylobacter. A mathematical model was used to quantify the transmission rate, which was determined to be 1.04 new cases per colonized chick per day. This would imply that, for example, in a flock of 20,000 broilers, the prevalence of Campylobacter would increase from 5% to 95% within 6 days after Campylobacter introduction. The model and the estimated transmission rate parameter can be used to develop a suitable sampling scheme to determine transmission in commercial broiler flocks, to estimate whether control measures can reduce the transmission rate, or to estimate when Campylobacter was introduced into a colonized broiler flock on the basis of the time course of transmission in the flock.


2008 ◽  
Author(s):  
Ishii Akira ◽  
Yoshida Narihiko ◽  
Hayashi Takafumi ◽  
Umemura Sanae ◽  
Nakagawa Takeshi
Keyword(s):  

1974 ◽  
Vol 13 (03) ◽  
pp. 151-158 ◽  
Author(s):  
D. A. B. Lindbebo ◽  
Fr. R. Watson

Recent studies suggest the determinations of clinical laboratories must be made more precise than at present. This paper presents a means of examining benefits of improvement in precision. To do this we use a mathematical model of the effect upon the diagnostic process of imprecision in measurements and the influence upon these two of Importance of Diagnosis and Prevalence of Disease. The interaction of these effects is grossly non-linear. There is therefore no proper intuitive answer to questions involving these matters. The effects can always, however, be calculated.Including a great many assumptions the modeling suggests that improvements in precision of any determination ought probably to be made in hospital rather than screening laboratories, unless Importance of Diagnosis is extremely high.


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