Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Clearance Models: Physiological Models

Clearance Models: Physiological Models

Drug clearance is a critical pharmacokinetic process involving the irreversible removal of drugs from the body through various organs over a specified time period. Physiological models are indispensable in determining organ-specific clearance, defined by the proportion of the drug eliminated per unit of time from the organ's blood volume.
The organ's clearance rate depends on the blood flow to the organ and the extraction ratio (E). The extraction ratio describes the organ's proficiency in drug...

Modeling and Similitude

Modeling and Similitude

Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

The starting dates of COVID-19 multiple waves.

Chaos (Woodbury, N.Y.)·2022

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 11, 2026

Modelling Zika Virus Infection of the Developing Human Brain In Vitro Using Stem Cell Derived Cerebral Organoids

Modelling Zika Virus Infection of the Developing Human Brain In Vitro Using Stem Cell Derived Cerebral Organoids

Published on: September 19, 2017

Embedded model discrepancy: A case study of Zika modeling.

Rebecca E Morrison¹, Americo Cunha²

¹Department of Computer Science, University of Colorado Boulder, Boulder, Colorado 80309, USA.

Chaos (Woodbury, N.Y.)

|June 4, 2020

Summary

This summary is machine-generated.

Mathematical models for disease outbreaks often oversimplify complex systems, leading to inaccurate predictions. This study introduces an embedded discrepancy operator to enhance model accuracy using real-world data, improving epidemiological predictions.

More Related Videos

Establishing Mouse Models for Zika Virus-induced Neurological Disorders Using Intracerebral Injection Strategies: Embryonic, Neonatal, and Adult

Establishing Mouse Models for Zika Virus-induced Neurological Disorders Using Intracerebral Injection Strategies: Embryonic, Neonatal, and Adult

Published on: April 26, 2018

Vector Competence Analyses on Aedes aegypti Mosquitoes using Zika Virus

Vector Competence Analyses on Aedes aegypti Mosquitoes using Zika Virus

Published on: May 31, 2020

Related Experiment Videos

Last Updated: Jul 11, 2026

Modelling Zika Virus Infection of the Developing Human Brain In Vitro Using Stem Cell Derived Cerebral Organoids

Modelling Zika Virus Infection of the Developing Human Brain In Vitro Using Stem Cell Derived Cerebral Organoids

Published on: September 19, 2017

Establishing Mouse Models for Zika Virus-induced Neurological Disorders Using Intracerebral Injection Strategies: Embryonic, Neonatal, and Adult

Establishing Mouse Models for Zika Virus-induced Neurological Disorders Using Intracerebral Injection Strategies: Embryonic, Neonatal, and Adult

Published on: April 26, 2018

Vector Competence Analyses on Aedes aegypti Mosquitoes using Zika Virus

Vector Competence Analyses on Aedes aegypti Mosquitoes using Zika Virus

Published on: May 31, 2020

Area of Science:

Epidemiology
Mathematical Biology
Computational Science

Background:

Mathematical models are crucial for understanding disease outbreaks but often lack accuracy due to oversimplification.
Model predictions can conflict with real-world data, necessitating model improvement for reliable public health decisions.

Purpose of the Study:

To address the inconsistency between simplified epidemiological models and real-world data.
To propose a novel method for enhancing the accuracy of mathematical models in epidemiology.
To demonstrate the method's effectiveness using the 2016 Zika outbreak in Brazil.

Main Methods:

Development of an embedded discrepancy operator, a modification to existing model equations.
Calibration of the modified model using all available relevant data.
Case study application to the 2016 Zika outbreak in Brazil.

Main Results:

The enriched model demonstrated significantly improved consistency with real-world data compared to standard models.
The embedded discrepancy operator effectively reconciles model output with observed epidemiological trends.
The proposed method proved generalizable to other mathematical models in epidemiology.

Conclusions:

The embedded discrepancy operator offers a practical approach to enhance the accuracy of epidemiological models.
This method improves the reliability of predictions for disease outbreaks, aiding public health strategies.
The approach is adaptable and broadly applicable across various epidemiological modeling scenarios.