Related Experiment Video
Updated: Jul 31, 2026
23:56
Comprehensive & Cost Effective Laboratory Monitoring of HIV/AIDS: an African Role Model
Published on: November 1, 2010
The risks of transfusion-transmitted infection: direct estimation and mathematical modelling
1University of British Columbia, Vancouver, BC, Canada.
Bailliere'S Best Practice & Research. Clinical Haematology
|December 5, 2000
Summary
Estimating transfusion-transmitted infection (TTI) risk requires mathematical modeling due to low current levels. This approach, alongside direct measurement, is vital for assessing emerging infectious agents in blood transfusions.
Area of Science:
- Infectious Diseases
- Public Health
- Hematology
Background:
- Direct measurement of transfusion-transmitted infection (TTI) risk is feasible only when risk levels are high.
- Historical sample repositories aided in assessing risks of human immunodeficiency virus (HIV), hepatitis B virus (HBV), and hepatitis C virus (HCV).
- Current TTI risks are very low, necessitating advanced estimation methods.
Purpose of the Study:
- To highlight the necessity of mathematical modeling for estimating current TTI risks.
- To explain the role of modeling in predicting risk reduction from new screening tests.
- To emphasize the combined importance of direct estimation and modeling for future TTI surveillance.
Main Methods:
- Utilizing historical data from recipient and donor sample repositories for risk assessment.
- Employing mathematical modeling, specifically the incidence/window period model, to estimate TTI risk.
- Analyzing the contribution of the 'window period' to residual TTI risk for screened agents.
Main Results:
- The incidence/window period model estimates TTI risks to be in the range of 1:100,000 to 1:1,000,000 for screened agents.
- Mathematical modeling is crucial for estimating the magnitude of low-level TTI risks.
- Modeling aids in predicting the effectiveness of new screening technologies in reducing TTI risk.
Conclusions:
- Mathematical modeling is essential for accurately estimating current, low-level TTI risks.
- Both direct measurement and mathematical modeling are critical for evaluating existing and emerging TTI agents.
- The incidence/window period model provides valuable insights into residual risks and potential mitigation strategies.
Related Concept Videos
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
01:15Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions
PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure (CHF).