Bioavailability of Organic Solvents in Soils: Input into Biologically-Based Dose- Response Models for Human Risk Assessments

Dose-response models are an important part of quantitative microbiological risk assessments. In this paper, we present a transparent and ready-to-use version of a published dose-response model that estimates the probability of infection and illness after the consumption of a meal that is contaminated with the pathogen Campylobacter jejuni. To this end, model and metadata are implemented in the fskx-standard. The model parameter values are based on data from a set of different studies on the infectivity and pathogenicity of Campylobacter jejuni. Both, challenge studies and outbreaks are considered, users can decide which of these is most suitable for their purpose. We present examples of results for typical ingested doses and demonstrate the utility of our ready-to-use model re-implementation by supplying an executable model embedded in this manuscript.

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Risk Assessment for Fetal Toxicity

Toxicology and Industrial Health ◽

10.1177/074823378500100420 ◽

1985 ◽

Vol 1 (4) ◽

pp. 299-310 ◽

Cited By ~ 1

Author(s):

John Van Ryzin

Keyword(s):

Risk Assessment ◽

Toxic Effect ◽

Dose Response ◽

Risk Assessments ◽

Control Group ◽

Response Model ◽

Statistical Research ◽

Response Models ◽

Fetal Toxicity ◽

Using Data

This paper reviews the problem of performing risk assessments using data on fetal toxic effects. It briefly discusses the usual dose-response models and their inappropriateness for application to such data. The paper then considers tests for determining whether the fetal toxic effect is increased over that of the control group. Assuming an increase has been shown, the use of a fetal toxicity, dose-response model for risk assessment is discussed. The paper then applies these methods to data from an experiment using female mice mated with irradiated males. Finally, the paper discusses the need for further statistical research in this important area.

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Weighted mixed-effects dose–response models for tables of correlated contrasts

The Stata Journal Promoting communications on statistics and Stata ◽

10.1177/1536867x211025798 ◽

2021 ◽

Vol 21 (2) ◽

pp. 320-347

Author(s):

Nicola Orsini

Keyword(s):

Dose Response ◽

Response Pattern ◽

Mixed Effects ◽

Data Generation ◽

Measures Of Association ◽

Response Models ◽

Response Data ◽

Hazard Ratios ◽

Health Related ◽

Generation Mechanisms

Recognizing a dose–response pattern based on heterogeneous tables of contrasts is hard. Specification of a statistical model that can consider the possible dose–response data-generating mechanism, including its variation across studies, is crucial for statistical inference. The aim of this article is to increase the understanding of mixed-effects dose–response models suitable for tables of correlated estimates. One can use the command drmeta with additive (mean difference) and multiplicative (odds ratios, hazard ratios) measures of association. The postestimation command drmeta_graph greatly facilitates the visualization of predicted average and study-specific dose–response relationships. I illustrate applications of the drmeta command with regression splines in experimental and observational data based on nonlinear and random-effects data-generation mechanisms that can be encountered in health-related sciences.

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