ERF of waterborne microbes: Difference between revisions

Revision as of 19:23, 6 August 2019

This page is a knowledge crystal of subtype variable. The page identifier is Op_en7948
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Question

What are the dose-response functions of pathogens in drinking water?

Answer

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library(OpasnetUtils)

objects.latest("Op_en7948", code_name = "variable")

oprint(AnnosVaste)

Rationale

Data

ERF(-)
Obs	Exposure agent	Response	Exposure	Exposure unit	ER function	Scaling	Threshold	ERF	Description
1	campylobacter	campylobacter infection	ingestion	?	beta poisson approximation	None	0.011	0.024
2	rotavirus	rotavirus infection	ingestion	?	exact beta poisson	None	0.191	0.167
3	norovirus	norovirus infection	ingestion	?	exact beta poisson	None	0.055	0.04
4	cryptosporidium	cryptosporidium infection	ingestion	?	exact beta poisson	None	0.176	0.115
5	giardia	giardia infection	ingestion	?	exponential	None	0	0.0199
6	E.coli O157:H7	E.coli O157:H7 infection	ingestion	?	exact beta poisson	None	9.16	0.157	E. coli O157:H7 strain

Probability of illness, given infection(probability)
Obs	Response	Illness	Subgroup	Result
1	giardia infection	gastroenteritis		1
2	cryptosporidium infection	gastroenteritis		0.71
3	cryptosporidium infection	death	Age:age 0-4	0.00000070645
4	cryptosporidium infection	death	Age:age 5-9	0
5	cryptosporidium infection	death	Age:age 10-14	0
6	cryptosporidium infection	death	Age:age 15-64	0.000014839
7	cryptosporidium infection	death	Age:age 65-79	0.0011644
8	cryptosporidium infection	death	Age:age 80+	0.0011644
9	norovirus infection	gastroenteritis		0.7
10	norovirus infection	death	Age:age 0-4	0.000002058
11	norovirus infection	death	Age:age 5-9	0
12	norovirus infection	death	Age:age 10-14	0
13	norovirus infection	death	Age:age 15-64	0
14	norovirus infection	death	Age:age 65-79	0.000168
15	norovirus infection	death	Age:age 80+	0.000168
16	rotavirus infection	gastroenteritis		0.9
17	rotavirus infection	death	Age:age 0-4	0.00001917
18	rotavirus infection	death	Age:age 5-9	0
19	rotavirus infection	death	Age:age 10-14	0
20	rotavirus infection	death	Age:age 15-64	0
21	rotavirus infection	death	Age:age 65-81	0
22	rotavirus infection	death	Age:age 80+	0
23	campylobacter infection	gastroenteritis		0.323
24	campylobacter infection	clinical Guillian-Barré syndrome		0.000066
25	campylobacter infection	residual Guillian Barré syndrome		0.000066
26	campylobacter infection	reactive arthritis		0.0066
27	campylobacter infection	death		0.000131
28	E.coli O157:H7 infection	gastroenteritis		0.4346
29	E.coli O157:H7 infection	hemorrhagic colitis		0.3854
30	E.coli O157:H7 infection	haemolytic uraemic syndrome		0.0082
31	E.coli O157:H7 infection	end stage renal disease		0.0009676
32	E.coli O157:H7 infection	death		0.00062238

⇤--arg6688: . Find out the units of the parameters to understand the functions precisely. --Jouni (talk) 12:54, 11 July 2019 (UTC) (type: truth; paradigms: science: attack)

----arg2087: . The ERF and Threshold numbers in the tables correspond to parameters called alpha and beta respectively in the papers cited below in the cases of campylo, rota, noro and crypto. The equations alpha and beta are used in in the papers don't (seem to) match the equations below. At least for campylo the equations are significantly more complicated. For giardia the value in ERF does seem to be used in the paper it's from in the way the exponential equation shows. In the paper it's marked as r, the probability of infection. The equation in the paper uses "mean number per portion" where Dose is in this equation. E.coli is the biggest mystery: I wasn't able to find the numbers in the table above from the paper sited for it at all. --Heta (talk) 10:32, 12 July 2019 (UTC) (type: truth; paradigms: science: comment)

In these equations, Param1 and Param2 are in Threshold and ERF columns, respectively.

Beta Poisson approximation: 1-(1+Dose/Param2)^-Param1
Exact beta Poisson: 1-exp(-(Param1/(Param1+Param2))*Dose)
Exponential: 1-exp(-Param1*Dose)

Pathogen	Reference
Campylobacter	^[1]
Rotavirus	^[2]
Norovirus	^[3]
Cryptosporidium	^[4]
Giardia	^[5]
E.coli O157:H7	^[6]

Calculations

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# This is code Op_en7948/P_illness on page [[ERF of waterborne microbes]]

library(OpasnetUtils)

objects.latest("Op_en2031", code_name="subgrouping") # [[ERF]] subgrouping

P_illness <- Ovariable("P_illness", ddata = "Op_en7948", subset="Probability of illness, given infection")
P_illness@data <- subgrouping(P_illness@data)

objects.store(P_illness)
cat("Ovariable P_illness stored.\n")

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# This is code Op_en7948/ERF_micr2 on page [[ERF of waterborne microbes]]
# Note! This version has ERF and threshold in the same ovariable.

library(OpasnetUtils)

ERF_micr <- Ovariable("ERF_micr", ddata = "Op_en7948", subset="ERF")
colnames(ERF_micr@data) <- gsub(" ", "_", colnames(ERF_micr@data))

objects.store(ERF_micr)
cat("Ovariable ERF_micr stored.\n")

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# This is code Op_en7948/ERF_micr on page [[ERF of waterborne microbes]]

library(OpasnetUtils)

d <- opbase.data("Op_en7948")[-1]

colnames(d) <- gsub(" ", "_", colnames(d))
d$Result <- ifelse(d$Result == "", "0", as.character(d$Result))

ERF_micr <- Ovariable("ERF_micr", data = d[d$Observation == "ERF", colnames(d) != "Observation"])

threshold_micr <- Ovariable("threshold_micr", data = d[d$Observation == "Threshold", colnames(d) != "Observation"])

objects.store(ERF_micr, threshold_micr)
cat("Ovariables ERF_micr, threshold_micr stored.\n")

⇤--arg5268: . The code below is old and does not work with the new ERF table. --Jouni (talk) 12:54, 11 July 2019 (UTC) (type: truth; paradigms: science: attack)

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library(OpasnetUtils)

f.exact.beta.poisson <- function(Dose, Param1, Param2, ...) 1 - exp(-(Param1 / (Param1 + Param2)) * Dose)
f.beta.poisson.approx <- function(Dose, Param1, Param2, ...) 1 - (1 + Dose / Param2)^(-Param1)
f.exponential <- function(Dose, Param1, ...) 1 - exp(-Param1 * Dose)
f.alt.exponential <- function(Dose, Param1, Param2, ...) 1 - (1 + (Dose / Param1))^(Param2)

EFR <- Ovariable("ERF", data = tidy(opbase.data("Op_fi2653")))

objects.store(ERF, f.exact.beta.poisson, f.beta.poisson.approx, f.exponential, f.alt.exponential)

cat("Ovariable ERF and functions f.exact.beta.poisson, f.beta.poisson.approx, f.exponential and f.alt.exponential saved.\n")

oprint(ERF)

References

↑ Teunis, P., van den Brandhof, W., Nauta, M., Wagenaar, J., van den Kerkhof, H. and van Pelt, W. 2005. A reconsideration of the Campylobacter dose–response relation. Epidemiol. Infec. 133, 583-592. DOI: https://doi.org/10.1017/S0950268805003912
↑ Teunis, P. F. M. and Havelaar, A. 2000. "The beta Poisson dose‐response model is not a single hit model."Risk Analysis 20(4): 513-520. https://doi.org/10.1111/0272-4332.204048
↑ Teunis P.F.M., Moe, C.L., Liu, P., Miller, S.E., Lindesmith, L., Baric, R.S., Le Pendu, J., Calderon, R.L. 2008. Norwalk Virus: How Infectious is It? Journal of Medical Virology 80:1468-1476. https://doi.org/10.1002/jmv.21237
↑ Teunis, P.F.M., Chappell, C.L., Okhuysen, P.C. 2002. Cryptosporidium Dose Response Studies: Variation Between Isolates. Risk Analysis 22(1) 175-183 https://doi.org/10.1111/0272-4332.00014
↑ Teunis, P.F.M., van der Heijden, O.G., van der Giessen, J.W.B., Havelaar, A.H. 1996. The dose-response relation in human volunteers for gastro-intestinal pathogens. RIVM report No. 284550002. http://hdl.handle.net/10029/9966
↑ Teunis, P., Takumi, K. and Shinagawa, K. 2004. "Dose response for infection by Escherichia coli O157:H7 from outbreak data." Risk Analysis 24(2): 401‐407. https://doi.org/10.1111/j.0272-4332.2004.00441.x

[1] Teunis, P., van den Brandhof, W., Nauta, M., Wagenaar, J., van den Kerkhof, H. and van Pelt, W. 2005. A reconsideration of the Campylobacter dose–response relation. Epidemiol. Infec. 133, 583-592. DOI: https://doi.org/10.1017/S0950268805003912

[2] Teunis, P. F. M. and Havelaar, A. 2000. "The beta Poisson dose‐response model is not a single hit model."Risk Analysis 20(4): 513-520. https://doi.org/10.1111/0272-4332.204048

[3] Teunis P.F.M., Moe, C.L., Liu, P., Miller, S.E., Lindesmith, L., Baric, R.S., Le Pendu, J., Calderon, R.L. 2008. Norwalk Virus: How Infectious is It? Journal of Medical Virology 80:1468-1476. https://doi.org/10.1002/jmv.21237

[4] Teunis, P.F.M., Chappell, C.L., Okhuysen, P.C. 2002. Cryptosporidium Dose Response Studies: Variation Between Isolates. Risk Analysis 22(1) 175-183 https://doi.org/10.1111/0272-4332.00014

[5] Teunis, P.F.M., van der Heijden, O.G., van der Giessen, J.W.B., Havelaar, A.H. 1996. The dose-response relation in human volunteers for gastro-intestinal pathogens. RIVM report No. 284550002. http://hdl.handle.net/10029/9966

[6] Teunis, P., Takumi, K. and Shinagawa, K. 2004. "Dose response for infection by Escherichia coli O157:H7 from outbreak data." Risk Analysis 24(2): 401‐407. https://doi.org/10.1111/j.0272-4332.2004.00441.x

[1]

[2]

[3]

[4]

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[6]

@@ Line 29: / Line 29: @@
 cryptosporidium|cryptosporidium infection|ingestion|?|exact beta poisson|None|0.176|0.115|
 giardia|giardia infection|ingestion|?|exponential|None|0|0.0199|
-E.coli O157:H7|E. coli infection|ingestion|?|exact beta poisson|None|9.16|0.157|E. coli O157:H7 strain
+E.coli O157:H7|E.coli O157:H7 infection|ingestion|?|exact beta poisson|None|9.16|0.157|E. coli O157:H7 strain
 </t2b>
@@ Line 61: / Line 61: @@
 campylobacter infection|reactive arthritis||0.0066
 campylobacter infection|death||0.000131
-E. coli infection|gastroenteritis||0.4346
+E.coli O157:H7 infection|gastroenteritis||0.4346
-E. coli infection|hemorrhagic colitis||0.3854
+E.coli O157:H7 infection|hemorrhagic colitis||0.3854
-E. coli infection|haemolytic uraemic syndrome||0.0082
+E.coli O157:H7 infection|haemolytic uraemic syndrome||0.0082
-E. coli infection|end stage renal disease||0.0009676
+E.coli O157:H7 infection|end stage renal disease||0.0009676
-E. coli infection|death||0.00062238
+E.coli O157:H7 infection|death||0.00062238
 </t2b>

ERF of waterborne microbes: Difference between revisions

Revision as of 19:23, 6 August 2019

Contents

Question

Answer

Rationale

Data

Calculations

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References

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