Predictive population dose-response assessment for Cryptosporidium parvum: Infection endpoint

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Data validation of safe doses of pathogens in drinking water consistent with public health goals is not possible due to the number of subjects that would be needed at each dose. Because of this problem, together with the difficulty in extrapolating pathogenic response between species, and the ability of microbes to adapt rapidly, confidence-level-dependent assessments of Cryptosporidium parvum dose-response have been developed. However, these results, even on a relative basis, are dependent on confidence level, and the lack of scientific basis for this choice hampers efforts to set water quality standards. Therefore, a predictive Bayesian dose-response assessment method was proposed previously. In this article, a hierarchical predictive population dose-response Bayesian assessment for C. parvum is presented for the infection endpoint. Available data on the infectivity of three isolates of C. parvum, genotype C, were adjusted for sensitive and antibody-positive subpopulations not proportionately represented in the data, by bootstrap analysis. The diverse mean infectivities of the isolates were used to obtain a predictive distribution for population infectivity, used in turn to obtain the predictive population dose-response function. The predictive result is a distribution of unconditional probability of infection, based on available dose-response information. Information includes theoretical and empirical evidence for the conditional beta-Poisson parametric dose-response function. Results indicate that a dose of 6 × 10-6 oocysts per exposure corresponds to 10-4 infections per capita year. An allowable dose corresponding to goals of the SWTR should be increased over this value to reflect the illness endpoint, while potentially being reduced to account for secondary transmission among hosts if important for gastroenteritis in developed countries.

Original languageEnglish
Pages (from-to)651-666
Number of pages16
JournalJournal of Toxicology and Environmental Health - Part A
Volume67
Issue number8-10
DOIs
StatePublished - Apr 23 2004

Fingerprint

Cryptosporidium parvum
Public health
Pathogens
Infection
Antibodies
Potable water
Drinking Water
Population
Water quality
Oocysts
Water Quality
Gastroenteritis
infectivity
Developed Countries
Public Health
Genotype
Demography
dose
infection
gastroenteritis

ASJC Scopus subject areas

  • Environmental Science(all)
  • Environmental Chemistry
  • Public Health, Environmental and Occupational Health
  • Pollution
  • Toxicology
  • Health, Toxicology and Mutagenesis

Cite this

Predictive population dose-response assessment for Cryptosporidium parvum : Infection endpoint. / Englehardt, James Douglas; Swartout, Jeff.

In: Journal of Toxicology and Environmental Health - Part A, Vol. 67, No. 8-10, 23.04.2004, p. 651-666.

Research output: Contribution to journalArticle

@article{03087d9726684619830b995006ebc1c5,
title = "Predictive population dose-response assessment for Cryptosporidium parvum: Infection endpoint",
abstract = "Data validation of safe doses of pathogens in drinking water consistent with public health goals is not possible due to the number of subjects that would be needed at each dose. Because of this problem, together with the difficulty in extrapolating pathogenic response between species, and the ability of microbes to adapt rapidly, confidence-level-dependent assessments of Cryptosporidium parvum dose-response have been developed. However, these results, even on a relative basis, are dependent on confidence level, and the lack of scientific basis for this choice hampers efforts to set water quality standards. Therefore, a predictive Bayesian dose-response assessment method was proposed previously. In this article, a hierarchical predictive population dose-response Bayesian assessment for C. parvum is presented for the infection endpoint. Available data on the infectivity of three isolates of C. parvum, genotype C, were adjusted for sensitive and antibody-positive subpopulations not proportionately represented in the data, by bootstrap analysis. The diverse mean infectivities of the isolates were used to obtain a predictive distribution for population infectivity, used in turn to obtain the predictive population dose-response function. The predictive result is a distribution of unconditional probability of infection, based on available dose-response information. Information includes theoretical and empirical evidence for the conditional beta-Poisson parametric dose-response function. Results indicate that a dose of 6 × 10-6 oocysts per exposure corresponds to 10-4 infections per capita year. An allowable dose corresponding to goals of the SWTR should be increased over this value to reflect the illness endpoint, while potentially being reduced to account for secondary transmission among hosts if important for gastroenteritis in developed countries.",
author = "Englehardt, {James Douglas} and Jeff Swartout",
year = "2004",
month = "4",
day = "23",
doi = "10.1080/15287390490428080",
language = "English",
volume = "67",
pages = "651--666",
journal = "Journal of Toxicology and Environmental Health - Part A: Current Issues",
issn = "1528-7394",
publisher = "Taylor and Francis Ltd.",
number = "8-10",

}

TY - JOUR

T1 - Predictive population dose-response assessment for Cryptosporidium parvum

T2 - Infection endpoint

AU - Englehardt, James Douglas

AU - Swartout, Jeff

PY - 2004/4/23

Y1 - 2004/4/23

N2 - Data validation of safe doses of pathogens in drinking water consistent with public health goals is not possible due to the number of subjects that would be needed at each dose. Because of this problem, together with the difficulty in extrapolating pathogenic response between species, and the ability of microbes to adapt rapidly, confidence-level-dependent assessments of Cryptosporidium parvum dose-response have been developed. However, these results, even on a relative basis, are dependent on confidence level, and the lack of scientific basis for this choice hampers efforts to set water quality standards. Therefore, a predictive Bayesian dose-response assessment method was proposed previously. In this article, a hierarchical predictive population dose-response Bayesian assessment for C. parvum is presented for the infection endpoint. Available data on the infectivity of three isolates of C. parvum, genotype C, were adjusted for sensitive and antibody-positive subpopulations not proportionately represented in the data, by bootstrap analysis. The diverse mean infectivities of the isolates were used to obtain a predictive distribution for population infectivity, used in turn to obtain the predictive population dose-response function. The predictive result is a distribution of unconditional probability of infection, based on available dose-response information. Information includes theoretical and empirical evidence for the conditional beta-Poisson parametric dose-response function. Results indicate that a dose of 6 × 10-6 oocysts per exposure corresponds to 10-4 infections per capita year. An allowable dose corresponding to goals of the SWTR should be increased over this value to reflect the illness endpoint, while potentially being reduced to account for secondary transmission among hosts if important for gastroenteritis in developed countries.

AB - Data validation of safe doses of pathogens in drinking water consistent with public health goals is not possible due to the number of subjects that would be needed at each dose. Because of this problem, together with the difficulty in extrapolating pathogenic response between species, and the ability of microbes to adapt rapidly, confidence-level-dependent assessments of Cryptosporidium parvum dose-response have been developed. However, these results, even on a relative basis, are dependent on confidence level, and the lack of scientific basis for this choice hampers efforts to set water quality standards. Therefore, a predictive Bayesian dose-response assessment method was proposed previously. In this article, a hierarchical predictive population dose-response Bayesian assessment for C. parvum is presented for the infection endpoint. Available data on the infectivity of three isolates of C. parvum, genotype C, were adjusted for sensitive and antibody-positive subpopulations not proportionately represented in the data, by bootstrap analysis. The diverse mean infectivities of the isolates were used to obtain a predictive distribution for population infectivity, used in turn to obtain the predictive population dose-response function. The predictive result is a distribution of unconditional probability of infection, based on available dose-response information. Information includes theoretical and empirical evidence for the conditional beta-Poisson parametric dose-response function. Results indicate that a dose of 6 × 10-6 oocysts per exposure corresponds to 10-4 infections per capita year. An allowable dose corresponding to goals of the SWTR should be increased over this value to reflect the illness endpoint, while potentially being reduced to account for secondary transmission among hosts if important for gastroenteritis in developed countries.

UR - http://www.scopus.com/inward/record.url?scp=1942532007&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=1942532007&partnerID=8YFLogxK

U2 - 10.1080/15287390490428080

DO - 10.1080/15287390490428080

M3 - Article

C2 - 15192860

AN - SCOPUS:1942532007

VL - 67

SP - 651

EP - 666

JO - Journal of Toxicology and Environmental Health - Part A: Current Issues

JF - Journal of Toxicology and Environmental Health - Part A: Current Issues

SN - 1528-7394

IS - 8-10

ER -