Related Experiment Video
Updated: Aug 11, 2026
10:11
Modeling The Lifecycle Of Ebola Virus Under Biosafety Level 2 Conditions With Virus-like Particles Containing Tetracistronic Minigenomes
Published on: September 27, 2014
Modelling infectious disease - time to think outside the box?
Siouxsie Wiles1, William P Hanage, Gad Frankel
1Division of Cell and Molecular Biology, Imperial College London, South Kensington Campus, London SW7 2AZ, UK. siouxsie.wiles@imperial.ac.uk
Nature Reviews. Microbiology
|March 7, 2006
Summary
Animal models are crucial for studying infectious diseases ethically. However, significant differences exist between these models and natural infections, particularly in mouse models of bacterial pathogens, necessitating improvements.
Area of Science:
- Infectious disease research
- Animal modeling
- Bacteriology
Background:
- Ethical constraints limit human exposure to infectious agents.
- Animal models offer a controlled environment to study disease.
- Existing animal models may not fully replicate natural infection dynamics.
Purpose of the Study:
- To highlight discrepancies between animal models and natural infections.
- To focus on mouse models of bacterial pathogens.
- To propose future improvements for animal model systems.
Main Methods:
- Review of experimental advances in infectious disease modeling.
- Comparative analysis of natural infections versus animal models.
- Focus on bacterial pathogens using mouse models.
Main Results:
- Significant differences identified between natural infections and animal models.
- Mouse models of bacterial pathogens exhibit notable discrepancies.
- Experimental data reveals limitations in current model systems.
Conclusions:
- Animal models are valuable but imperfect representations of natural disease.
- Improvements are needed to enhance the accuracy of mouse models for bacterial pathogens.
- Future research should aim to refine model systems for better translational relevance.
Related Concept Videos
01:18Steps in Outbreak Investigation
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
01:28Infectious Diseases and Their Occurrence
Infectious diseases appear in populations through various transmission patterns, influenced by pathogen characteristics, population immunity, environmental conditions, and social behavior. Understanding these patterns is essential for effective public health surveillance and intervention. These categories—sporadic, outbreak, epidemic, pandemic, and endemic—help frame the nature and scope of disease events.Sporadic diseases occur irregularly and infrequently, without a predictable temporal or...
01:23Investigation of Disease Outbreaks
Multistate foodborne outbreaks pose significant public health risks and require meticulous investigation to identify sources and implement control measures. The Centers for Disease Control and Prevention (CDC) utilizes a dynamic seven-step process for these investigations, integrating data from laboratories, interviews, and environmental assessments to protect public health.Outbreak Detection: The detection of multistate outbreaks typically begins with PulseNet, the CDC's national laboratory...
01:26Exponential Equations for Modeling Growth
Exponential models are essential for describing rapid, multiplicative changes in natural systems, such as population growth. When a population doubles at regular intervals, the process can be modeled using a suitable base. For instance, a bacterial culture that doubles every three hours follows the model n(t)=n0⋅2t/3, where n(t) is the population at the time t.A more general model uses the natural base e, especially for continuous growth. This takes the form n(t)=n0⋅ert, where r is the relative...
01:25Modeling with Differential Equations
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
01:20Infection
When a pathogen enters the body and reproduces, it can cause an infection, damage body cells, and cause illness symptoms that eventually lead to disease. Therefore, its prevention requires breaking the chain of infection.
The chain begins with pathogens: bacteria, viruses, fungi, prions, or parasites such as protozoa helminths. These can be present on the skin as transient or resident flora, or they can be acquired from the environment. Identifying and treating the type of infection and...
The chain begins with pathogens: bacteria, viruses, fungi, prions, or parasites such as protozoa helminths. These can be present on the skin as transient or resident flora, or they can be acquired from the environment. Identifying and treating the type of infection and...