User:Charteri

Please click on the tab headings to navigate betweeen tabs.| We generally recommend a single dose response model, and we justify the decision in terms of these criteria. This decision is somewhat subjective, since dose response datasets seldom meet all of these criteria. If all available models are unsatisfactory, we choose a single model to ‘recommend with reservations’. Our recommended model will seldom (if ever) be the best model for all applications. The user should carefully choose the model that is most appropriate for their particular problem.
*Please click on the tab headings to navigate between tabs.

[edit]

• Bacteria
• Viruses
• Protozoa
• Prions
• Criteria for Model Selection
• Back to Dose Response Home Page

Agent	Best fit model*	Optimized parameter(s)	LD50/ID50	Host type	Agent strain	Route	# of doses	Dose units	Response	Reference
Bacillus anthracis: Dose Response Models	exponential	k = 1.65E-05	4.2E+04	guinea pig	Vollum	inhalation	4	spores	death	Druett 1953
Burkholderia pseudomallei: Dose Response Models	beta-Poisson	α = 3.28E-01 , N50 = 5.43E+03	5.43E+03	C57BL/6 mice and diabetic rat	KHW,316c	intranasal,intraperitoneal	10	CFU	death	Liu, Koo et al. 2002 and Brett and Woods 1996
Campylobacter jejuni and Campylobacter coli: Dose Response Models	beta-Poisson	α= 1.44E-01 , N50 = 8.9E+02	8.9E+02	human	strain A3249	oral (in milk)	6	CFU	infection	Black et al 1988
Coxiella burnetii: Dose Response Models	beta-Poisson	α= 3.57E-01 , N50 = 4.93E+08	4.93E+08	C57BL/1OScN mice	phase I Ohio	intraperitoneal	10	PFU	death	Williams et al, 1982
Escherichia coli enterohemorrhagic (EHEC): Dose Response Models	exponential	k=2.18E-04	3.18E+03	pig	EHEC O157:H7, strain 86-24	oral (in food)	3	CFU	shedding in feces	Cornick & Helgerson (2004)
Escherichia coli: Dose Response Models	beta-Poisson	α = 1.55E-01 , N50 = 2.11E+06	2.11E+06	human	EIEC 1624	oral (in milk)	3	CFU	positive stool isolation	DuPont et al. (1971)
Francisella tularensis: Dose Response Models	exponential	k = 4.73E-02	1.46E+01	monkeys	SCHU S-4	inhalation	4	CFU	death	Day and Berendt, 1972
Legionella pneumophila: Dose Response Models	exponential	k = 5.99E-02	1.16E+01	guinea pig	Philadelphia 1	inhalation	4	CFU	infection	Muller et al. (1983)
Listeria monocytogenes (Death as response): Dose Response Models	exponential	k = 1.15E-05	6.05E+04	C57B1/6J mice	F5817	oral	6	CFU	death	Golnazarian, Donnelly et al. 1989
Listeria monocytogenes (Infection): Dose Response Models	beta-Poisson	α = 2.53E-01 , N50 = 2.77E+02	2.77E+02	C57Bl/6J mice	F5817	oral	10	CFU	infection	Golnazarian
Listeria monocytogenes (Stillbirths): Dose Response Models	beta-Poisson	α = 4.22E-02 , N50 = 1.78E+09	1.78E+09	pooled		oral	13	CFU	stillbirths	Smith, Williams2007
Mycobacterium avium: Dose Response Models	exponential	k = 6.93E-04	1E+03	deer	sub sp. Paratuberculosis Bovine	oral	3	CFU	infection	O'Brien et al(1976)
Pseudomonas aeruginosa (Contact lens): Dose Response Models	beta-Poisson	α = 1.9E-01 , N50 = 1.85E+04	1.85E+04	white rabbit		contact lens	10	CFU	corneal ulceration	Lawin-Brussel et al. (1993)
Pseudomonas aeruginosa (bacterimia): Dose Response Models	exponential	k = 1.05E-04	6.61E+03	Swiss webster mice (5day old)	ATCC 19660	injected in eyelids	12	CFU	death	Hazlett, Rosen et al. 1978
Rickettsia rickettsi: Dose Response Models	beta-Poisson	α= 7.77E-01 , N50 = 2.13E+01	2.13E+01	Pooled data	R1 and Sheila Smith	NA	27	CFU	morbidity	Saslaw and Carlisle 1966 and Dupont, Hornick et al. 1973
Salmonella Typhi: Dose Response Models	beta-Poisson	α = 1.75E-01 , N50 = 1.11E+06	1.11E+06	human	Quailes	oral, in milk	8	CFU	disease	Hornick et al. (1966),Hornick et al. (1970)
Salmonella anatum: Dose Response Models	beta-Poisson	α= 3.18E-01 , N50 = 3.71E+04	3.71E+04	human	strain I	oral, with eggnog	16	CFU	positive stool culture	McCullough and Elsele,1951
Salmonella meleagridis: Dose Response Models	beta-Poisson	α= 3.89E-01 , N50 = 1.68E+04	1.68E+04	human	strain I	oral, with eggnog	11	CFU	infection	McCullough and Eisele 1951,2
Salmonella nontyphoid: Dose Response Models	beta-Poisson	α= 2.1E-01 , N50 = 4.98E+01	4.98E+01	mice	strain 216 and 219	intraperitoneal	10	CFU	death	Meynell and Meynell,1958
Salmonella serotype newport: Dose Response Models	exponential	k = 3.97E-06	1.74E+05	human	Salmonella newport	oral	3	CFU	infection	McCullough and Elsele,1951
Shigella: Dose Response Models	beta-Poisson	α= 2.65E-01 , N50 = 1.48E+03	1.48E+03	human	2a (strain 2457T)	oral (in milk)	4	CFU	positive stool isolation	DuPont et al. (1972b)
Staphylococcus aureus: Dose Response Models	exponential	k = 7.64E-08	9.08E+06	human		subcutaneous	6	CFU/cm2	infection	Rose and Haas 1999
TestPage	exponential	k = 1.65E-05	4.2E+04	guinea pig	Vollum	inhalation	4	spores	death	Druett 1953
Vibrio cholerae: Dose Response Models	beta-Poisson	α= 2.50E-01 , N50 = 2.43E+02	2.43E+02	human	Inaba 569B	oral (with NaHCO3)	6	CFU	infection	Hornick et al., (1971)
Yersinia pestis: Dose Response Models	exponential	k = 1.63E-03	4.26E+02	mice	CO92	intranasal	4	CFU	death	Lathem et al. 2005

*These models are preferred in most circumstances. However, consider all available models to decide which one is most appropriate for your analysis.

Agent	Best fit model*	Optimized parameter(s)	LD50/ID50	Host type	Agent strain	Route	# of doses	Dose units	Response	Reference
Adenovirus
Adenovirus: Dose Response Models
Astrovirus
Coxsackievirus
Echovirus
Echovirus: Dose Response Models
Enterovirus
Enteroviruses
Enteroviruses: Dose Response Models
Hepatitis A
Influenza virus
Influenza: Dose Response Models
Lassa virus
Lassa virus: Dose Response Models
Norovirus
Parainfluenza virus
Poliovirus
Poliovirus: Dose Response Models
Respiratory syncytial virus
Rhinovirus
Rhinovirus: Dose Response Models
Rotavirus
Rotavirus: Dose Response Models
Rubella virus
SARS coronavirus
SARS: Dose Response Models

*These models are preferred in most circumstances. However, consider all available models to decide which one is most appropriate for your analysis.

• "[Recommended DR Model" contains the "[" character as part of a property label and has been classified as invalid.
• The part "]]" of the query was not understood. Results might not be as expected.

Agent	Best fit model*	Optimized parameter(s)	LD50/ID50	Host type	Agent strain	Route	# of doses	Dose units	Response	Reference
Acanthamoeba
Acanthamoeba Keratitis: Dose Response Models
Acanthamoeba spp: Dose Response Models
Aeromonas hydrophila
Cryptosporidium hominis
Cryptosporidium parvum
Cryptosporidium parvum and Cryptosporidium hominis: Dose Response Models
Endamoeba coli
Endamoeba coli: Dose Response Models
Entamoeba coli
Giardia duodenalis
Giardia duodenalis: Dose Response Models
Naegleria fowleri
Naegleria fowleri: Dose Response Models

*These models are preferred in most circumstances. However, consider all available models to decide which one is most appropriate for your analysis.

• "[Recommended DR Model" contains the "[" character as part of a property label and has been classified as invalid.
• The part "]]" of the query was not understood. Results might not be as expected.

Agent	Best fit model*	Optimized parameter(s)	LD50/ID50	Host type	Agent strain	Route	# of doses	Dose units	Response	Reference
PrP prion
PrP prions: Dose Response Models

*These models are preferred in most circumstances. However, consider all available models to decide which one is most appropriate for your analysis.

• "[Recommended DR Model" contains the "[" character as part of a property label and has been classified as invalid.
• The part "]]" of the query was not understood. Results might not be as expected.

We prefer dose response models with the following criteria, in rough order of importance:

1. Statistically acceptable fit (fail to reject goodness of fit, p > 0.05)
2. Human subjects, or animal models that mimic human pathophysiology well
3. Infection as the response, rather than disease, symptoms, or death
4. Exposure route similar/identical to the exposure route of natural infection
5. Pathogen strain is similar to strains causing natural infection
6. Pooled model using data from 2 or more experiments, provided the data sets are statistically similar (fail to reject that datasets are from the same distribution, p > 0.05)
7. Low ID₅₀/LD₅₀ (to obtain a conservative risk estimate)

We generally recommend a single dose response model, and we justify the decision in terms of the above criteria. This decision is somewhat subjective, since dose response datasets seldom meet all of these criteria. If all available models are unsatisfactory, we choose a single model to ‘recommend with reservations’. Our recommended model will seldom (if ever) be the best model for all applications. The user should carefully choose the model that is most appropriate for their particular problem.