Related Experiment Video
Updated: May 6, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Evaluation [corrected] of the "Iceberg Phenomenon" in Johne's disease through mathematical modelling
Gesham Magombedze, Gesgam Magombedze1, Calistus N Ngonghala
1National Institute for Mathematical and Biological Synthesis (NIMBioS), University of Tennessee, Knoxville, Tennessee, United States of America.
Abstract:
Johne's disease (JD) is a chronic, enteric disease in ruminants caused by Mycobacterium avium subsp. paratuberculosis (MAP). Disease progression follows four distinct stages: silent, subclinical, clinical and advanced. Available diagnostic tests have poor sensitivity and cannot detect early stages of the infection; as a result, only animals in the clinical and advanced stages, which represent the tip of the 'iceberg', are identified through testing. The Iceberg Phenomenon is then applied to provide estimates for JD prevalence. For one animal in the advanced stage, it is assumed that there are one to two in the clinical stage, four to eight in the subclinical stage, and ten to fourteen in the silent stage. These ratios, however, are based on little evidence. To evaluate the ratios, we developed a deterministic ordinary differential equation model of JD transmission and disease progression dynamics. When duration periods associated with the natural course of the disease progression are used, the above ratios do not hold. The ratios used to estimate JD prevalence need to be further investigated.
More Related Videos
13:07Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
Published on: January 15, 2022
10:40Visualization and Analysis of Blood Flow and Oxygen Consumption in Hepatic Microcirculation: Application to an Acute Hepatitis Model
Published on: August 4, 2012
Related Concept Videos
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
On...
Pharmacodynamic Models: Direct Effect Model and Indirect Response Model
Pharmacodynamic Models: Overview
Pharmacodynamic Models: Linear Concentration–Effect Model
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...