Development of Dose-Response Models to Predict the Relationship for HumanToxoplasma gondiiInfection Associated with Meat Consumption

Risk Analysis ◽  
2015 ◽  
Vol 36 (5) ◽  
pp. 926-938 ◽  
Author(s):  
Miao Guo ◽  
Abhinav Mishra ◽  
Robert L. Buchanan ◽  
Jitender P. Dubey ◽  
Dolores E. Hill ◽  
...  
Keyword(s):  
Dose Response ◽  
Meat Consumption ◽  
Response Models ◽  
The Relationship

scholarly journals Dose–response and transmission: the nexus between reservoir hosts, environment and recipient hosts

2019 ◽  
Vol 374 (1782) ◽  
pp. 20190016 ◽  
Author(s):  
Tamika J. Lunn ◽  
Olivier Restif ◽  
Alison J. Peel ◽  
Vincent J. Munster ◽  
Emmie de Wit ◽  
...  
Keyword(s):  
Dose Response ◽  
Nipah Virus ◽  
Underlying Disease ◽  
Host Susceptibility ◽  
Response Models ◽  
Zoonotic Pathogens ◽  
Exposure Experiment ◽  
Reservoir Hosts ◽  
The Relationship ◽  
Dose Dependent

Dose is the nexus between exposure and all upstream processes that determine pathogen pressure, and is thereby an important element underlying disease dynamics. Understanding the relationship between dose and disease is particularly important in the context of spillover, where nonlinearities in the dose–response could determine the likelihood of transmission. There is a need to explore dose–response models for directly transmitted and zoonotic pathogens, and how these interactions integrate within-host factors to consider, for example, heterogeneity in host susceptibility and dose-dependent antagonism. Here, we review the dose–response literature and discuss the unique role dose–response models have to play in understanding and predicting spillover events. We present a re-analysis of dose–response experiments for two important zoonotic pathogens (Middle East respiratory syndrome coronavirus and Nipah virus), to exemplify potential difficulties in differentiating between appropriate models with small exposure experiment datasets. We also discuss the data requirements needed for robust selection between dose–response models. We then suggest how these processes could be modelled to gain more realistic predictions of zoonotic transmission outcomes and highlight the exciting opportunities that could arise with increased collaboration between the virology and epidemiology disciplines. This article is part of the theme issue ‘Dynamic and integrative approaches to understanding pathogen spillover’.

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

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.

Underestimation of Dose - Response Relationship with Particular Reference to the Relationship between the Dietary Intake of Mercury and its Concentration in Blood

1988 ◽  
Vol 7 (2) ◽  
pp. 129-132 ◽  
Author(s):  
J.C. Sherlock ◽  
M.J. Quinn
Keyword(s):  
Linear Regression ◽  
Dietary Intake ◽  
Dose Response ◽  
Mercury Concentration ◽  
Response Relationship ◽  
Dose Response Relationship ◽  
Blood Mercury ◽  
Relationship Of ◽  
The Relationship ◽  
Blood Mercury Concentration

Wide discrepancies have been observed between controlled and uncontrolled intake studies of the relationship of blood mercury concentration to intake of mercury. The probable reason for the apparent discrepancies is that the within-subject variation of mercury intake in the uncontrolled studies was almost certainly considerably larger than the within-subject variation in blood mercury concentration; in these circumstances, the apparent slope obtained from a linear regression of blood mercury on intake will invariably be much smaller than the true slope. Studies of the exposure or intake of any substance should therefore include a consideration of the likely within-subject variation in the exposure or intake relative to that in the effect.

scholarly journals Association of psychiatric comorbidities with the risk of transport accidents in ADHD and MPH

2021 ◽  
Vol 30 ◽  
Author(s):  
Yi-Chun Liu ◽  
Vincent Chin-Hung Chen ◽  
Yao-Hsu Yang ◽  
Yi-Lung Chen ◽  
Michael Gossop
Keyword(s):  
Dose Response ◽  
Case Series ◽  
Autism Spectrum ◽  
Research Database ◽  
Accident Risk ◽  
Response Relationship ◽  
Dose Response Relationship ◽  
Series Analysis ◽  
The Relationship ◽  
Transport Accidents

Abstract Aims Although the relationship between attention-deficit/hyperactivity disorder (ADHD) and transport accidents has been shown, there is limited information on the relationship between medication and dose–response effects and transport accident risk. This study aims to determine whether young people with ADHD, including adolescents, are more prone to transport accidents than those without, and the extent to which methylphenidate (MPH) prescription in these patients reduces the risk. Methods We identified 114 486 patients diagnosed with ADHD from Taiwan's National Health Insurance Research Database from 1997 to 2013. Using a Cox regression model, we compared the risk of transport accidents between ADHD and non-ADHD groups and estimated the effect of MPH on accidents. Furthermore, we applied a self-control case-series analysis to compare the risk of accidents during the medication periods with the same patients' non-medication periods. Results Male ADHD patients had a higher risk of transport accidents than non-ADHD individuals (adjusted hazard ratio [aHR] = 1.24, [95% confidence interval (CI) 1.10–1.39]), especially for those comorbid with epilepsy, oppositional defiant disorder/conduct disorder (ODD/CD), and intellectual disabilities (ID). Female ADHD patients showed no relationship, except for comorbid with autism spectrum disorder (ASD) or ID. We found a reduced risk of transport accidents in patients with ADHD with MPH medication than those without MPH, with a plausible dose–response relationship (aHR of 0.23 to 0.07). A similar pattern was found in self-controlled case-series analysis. Conclusions Male patients with ADHD, especially those comorbid with epilepsy, ODD/CD, or ID, were at high risk of transport accidents. Female patients, when comorbid with ASD or ID, also exhibited a higher risk of accidents. MPH treatment lowered the accident risk with a dose–response relationship.

Statistical characterization of the random errors in the radioimmunoassay dose--response variable.

1976 ◽  
Vol 22 (3) ◽  
pp. 350-358 ◽  
Author(s):  
D Rodbard ◽  
R H Lenox ◽  
H L Wray ◽  
D Ramseth
Keyword(s):  
Least Squares ◽  
Dose Response ◽  
Curve Fitting ◽  
Response Curve ◽  
Dose Response Curve ◽  
Random Errors ◽  
Statistical Characterization ◽  
Response Variable ◽  
Least Squares Curve Fitting ◽  
The Relationship

Abstract We have developed practical methods for evaluating the magnitude of the random errors in radioimmunoassay dose--response variables, and the relationship between this error and position on the dose--response curve. This is important: to obtain appropriate weights for each point on the dose--response curve when utilizing least-squares curve-fitting methods; to evaluate whether the standards and the unknowns are subject to error of the same magnitude; for quality-control purposes; and to study the sources of errors in radioimmunoassay. Both standards and unknowns in radioimmunoassays for cAMP and cGMP were analyzed in triplicate. The same mean (Y), sample standard deviation, sy, and variance (2-y) of the response variable were calculated for each dose level. The relationship between s 2-y and y was calculated utilizing several models. Results for standards and unknowns from several assays were pooled, and a curve smoothing procedure was used to minimize random sampling errors. This pooling increased the reliability of the analysis, and confirmed the presence of the theoretically predicted nonuniformity of variance. Thus, the calculation of results from these radioimmunoassays should utilize a weighted least-squares curve-fitting program. These analyses have been computerized, and can be used as a "pre-processor" for programs for routine analysis of results of radioimmunoassay.

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