Medical Design and Outsourcing

  • Home
  • Medical Device Business
    • Mergers & Acquisitions
    • Financial
    • Regulatory
  • Applications
    • Cardiovascular
    • Devices
    • Imaging
    • Implantables
    • Medical Equipment
    • Orthopedic
    • Surgical
  • Technologies
    • Supplies and Components Index
    • Contract Manufacturing
    • Components
    • Electronics
    • Extrusions
    • Materials
    • Motion Control
    • Prototyping
    • Pumps
    • Tubing
  • MedTech Resources
    • Medtech Events in 2025
    • The 2024 Medtech Big 100
    • Medical Device Handbook
    • MedTech 100 Index
    • Subscribe to Print Magazine
    • DeviceTalks
    • Digital Editions
    • eBooks
    • Manufacturer Search
    • Podcasts
    • Print Subscription
    • Webinars / Digital Events
    • Whitepapers
    • Voices
    • Video
  • 2025 Leadership
    • 2024 Winners
    • 2023 Winners
    • 2022 Winners
    • 2021 Winners
  • Women in Medtech
  • Advertise
  • Subscribe

Statistical Test Relates Pathogen Mutation to Infectious Disease Progression

December 29, 2017 By Society for Industrial and Applied Mathematics

Nucleic acid sequencing methods, which determine the order of nucleotides in DNA fragments, are rapidly progressing. These processes yield large quantities of sequence data—some of which is dynamic—that helps researchers understand how and why organisms function like they do. Sequencing also benefits epidemiological studies, such as the identification, diagnosis, and treatment of genetic and/or contagious diseases. Advanced sequencing technologies reveal valuable information about the time evolution of pathogen sequences. Because researchers can estimate how a mutation behaves under the pressure of natural selection, they are thus able to predict the impact of each mutation—in terms of survival and propagation—on the fitness of the pathogen in question. These predictions lend insight to infectious disease epistemology, pathogen evolution, and population dynamics.

In a paper published earlier this month in the SIAM Journal on Applied Mathematics, Ryosuke Omori and Jianhong Wu develop an inductive algorithm to study site-specific nucleotide frequencies using a multi-strain susceptible-infective-removed (SIR) model. A SIR model is a simple compartmental model that places each individual in a population at a given time into one of the three aforementioned categories to compute the theoretical number of people affected by an infectious disease. The authors use their algorithm to calculate Tajima’s D, a popular statistical test that measures natural selection at a specific site by analyzing differences in a sample of sequences from a population. In a non-endemic situation, Tajima’s D can change over time. Investigating the time evolution of Tajima’s D during an outbreak allows researchers to estimate mutations relevant to pathogen fitness. Omori and Wu aim to understand the impact of disease dynamics on Tajima’s D, thus leading to a better understanding of a mutation’s pathogenicity, severity, and host specificity.

The sign of Tajima’s D is determined by both natural selection and population dynamics. “Tajima’s D equals 0 if the evolution is neutral—no natural selection and a constant population size,” Omori said. “A nonzero value of Tajima’s D suggests natural selection and/or change in population size. If no natural selection can be assumed, Tajima’s D is a function of the population size. Hence, it can be used to estimate time-series changes in population size, i.e., how the epidemic proceeds.”

Differential equations, which model the rates of change of the numbers of individuals in each model compartment, can describe population dynamics. In this case, the population dynamics of hosts infected with the strain carrying a given sequence are modeled by a set of differential equations for that sequence, which include terms describing the mutation rate from one sequence to another. When setting up their multi-strain SIR model, Omori and Wu assume that the population dynamics of the pathogen is proportional to the disease dynamics. i.e., the number of pathogens are proportional to the number of infected hosts. This assumption allows the value of Tajima’s D to change.

 

In population genetics, researchers believe that the sign of Tajima’s D is affected by population dynamics. However, the authors show that in the case of a SIR deterministic model, Tajima’s D is independent of the disease dynamics (specifically, independent of the parameters for disease transmission rate and disease recovery rate). They also observe that while Tajima’s D is often negative during an outbreak’s onset, it frequently becomes positive with the passage of time. “The negative sign does not imply an expansion of the infected population in a deterministic model,” Omori said. “We also found the dependence of Tajima’s D on the disease transmission dynamics can be attributed to the stochasticity of the transmission dynamics at the population level. This dependence is different from the aforementioned existing assumption about the relation between population dynamics and the sign of Tajima’s D.”

Ultimately, Omori and Wu prove that Tajima’s D in a deterministic SIR model is completely determined by mutation rate and sample size, and that the time evolution of an infectious disease pathogen’s genetic diversity is fully determined by the mutation rate. “This work revealed some dependence of Tajima’s D on the (disease transmission dynamics) basic reproduction number (R0) and mutation rate,” Omori said. “With the assumption of neutral evolution, we can then estimate mutation rate or R0 from sequence data.”

Given the demand for tools that analyze evolutionary and disease dynamics, the observation that Tajima’s D depends on the stochasticity of the dynamics is useful when estimating epidemiological parameters. For example, if sequences of pathogens are sampled from a small outbreak in a limited host population, then Tajima’s D depends on both the mutation rate and R0; therefore, a joint estimate of these parameters from Tajima’s D is possible. “We are applying this theoretic result to analyze real-world epidemiological data,” Omori said. “We should also see if our approach can be used to investigate non-equilibrium disease dynamics with natural selection.”

 

Related Articles Read More >

Axoft Fleuron brain-computer interface BCI probe
Axoft makes Fleuron BCI material available for purchase, inks license deal with Stanford
An illustration showing the Edwards Lifesciences Sapien M3 transcatheter mitral valve replacement (TMVR) system's valve being placed in the heart. [Image courtesy of Edwards Lifesciences]
The top nitinol cardiac medtech news of 2025 (so far)
An illustration showing the Edwards Lifesciences Sapien M3 transcatheter mitral valve replacement (TMVR) system's valve being placed in the heart. [Image courtesy of Edwards Lifesciences]
Q&A with Darshin Patel, who led the Edwards Lifesciences Sapien M3 TMVR system’s development
A photo of nitinol, a nickel-titanium alloy used for medical devices such as stents, heart valves, catheters and orthopedics.
What is nitinol and where is it used?
“mdo
EXPAND YOUR KNOWLEDGE AND STAY CONNECTED
Get the latest medical device business news, application and technology trends.

DeviceTalks Weekly

See More >

MDO Digital Edition

Digital Edition

Subscribe to Medical Design & Outsourcing. Bookmark, share and interact with the leading medical design engineering magazine today.

MEDTECH 100 INDEX

Medtech 100 logo
Market Summary > Current Price
The MedTech 100 is a financial index calculated using the BIG100 companies covered in Medical Design and Outsourcing.
DeviceTalks

DeviceTalks is a conversation among medical technology leaders. It's events, podcasts, webinars and one-on-one exchanges of ideas & insights.

DeviceTalks

New MedTech Resource

Medical Tubing

MassDevice

Mass Device

The Medical Device Business Journal. MassDevice is the leading medical device news business journal telling the stories of the devices that save lives.

Visit Website
MDO ad
Medical Design and Outsourcing
  • MassDevice
  • DeviceTalks
  • MedTech100 Index
  • Medical Tubing + Extrusion
  • Medical Design Sourcing
  • Drug Delivery Business News
  • Drug Discovery & Development
  • Pharmaceutical Processing World
  • R&D World
  • About Us/Contact
  • Advertise With Us
  • Subscribe to Print Magazine
  • Subscribe to our E-Newsletter
  • Listen to our Weekly Podcasts
  • Join our DeviceTalks Tuesdays Discussion

Copyright © 2025 WTWH Media, LLC. All Rights Reserved. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of WTWH Media LLC. Site Map | Privacy Policy | RSS

Search Medical Design & Outsourcing

  • Home
  • Medical Device Business
    • Mergers & Acquisitions
    • Financial
    • Regulatory
  • Applications
    • Cardiovascular
    • Devices
    • Imaging
    • Implantables
    • Medical Equipment
    • Orthopedic
    • Surgical
  • Technologies
    • Supplies and Components Index
    • Contract Manufacturing
    • Components
    • Electronics
    • Extrusions
    • Materials
    • Motion Control
    • Prototyping
    • Pumps
    • Tubing
  • MedTech Resources
    • Medtech Events in 2025
    • The 2024 Medtech Big 100
    • Medical Device Handbook
    • MedTech 100 Index
    • Subscribe to Print Magazine
    • DeviceTalks
    • Digital Editions
    • eBooks
    • Manufacturer Search
    • Podcasts
    • Print Subscription
    • Webinars / Digital Events
    • Whitepapers
    • Voices
    • Video
  • 2025 Leadership
    • 2024 Winners
    • 2023 Winners
    • 2022 Winners
    • 2021 Winners
  • Women in Medtech
  • Advertise
  • Subscribe