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Related Concept Videos

Influenza01:27

Influenza

Influenza is an acute, highly communicable viral disease that affects the respiratory tract and is responsible for seasonal epidemics worldwide. Influenza A is the most prevalent type associated with widespread outbreaks and is subtyped based on two surface glycoproteins: hemagglutinin (H) and neuraminidase (N), as in H1N1. These glycoproteins are essential for viral infectivity, transmission, and immune recognition. Transmission occurs primarily through respiratory droplets and contaminated...
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Infectious 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...
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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:
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Investigation 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...
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Viral replication and dissemination rely on efficient mechanisms for host cell entry, genome replication, assembly, and release. Influenza viruses, such as types A and B, are negative-sense single-stranded RNA viruses with a segmented genome, that depend on two critical surface glycoproteins to carry out these processes: hemagglutinin (HA) and neuraminidase (NA). HA initiates infection by binding to sialic acid residues on the surface of host epithelial cells, facilitating receptor-mediated...

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Updated: Jun 23, 2026

A Luciferase-fluorescent Reporter Influenza Virus for Live Imaging and Quantification of Viral Infection
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A Luciferase-fluorescent Reporter Influenza Virus for Live Imaging and Quantification of Viral Infection

Published on: August 14, 2019

Influenza outbreaks.

Paul S Wikramaratna1, Sunetra Gupta

  • 1Department of Zoology, University of Oxford, UK.

Cellular Microbiology
|April 21, 2009
PubMed
Summary
This summary is machine-generated.

Mathematical models of influenza dynamics often rely on flawed biological assumptions. This review critiques these underlying dogmas, suggesting a need for re-evaluation in understanding seasonal and evolutionary patterns of this impactful virus.

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Use of an Influenza Antigen Microarray to Measure the Breadth of Serum Antibodies Across Virus Subtypes

Published on: July 26, 2019

Area of Science:

  • Virology
  • Epidemiology
  • Mathematical Biology

Background:

  • Influenza virus causes significant annual human morbidity and mortality.
  • Its pandemic potential raises public health concerns, driving extensive research and media attention.
  • Mathematical modeling is frequently employed to study influenza's seasonal and evolutionary dynamics.

Purpose of the Study:

  • To critically examine the biological assumptions underpinning mathematical models of influenza.
  • To identify and challenge the prevailing, often unquestioned, dogmas in influenza modeling.
  • To highlight deficiencies in current theoretical approaches to understanding influenza dynamics.

Main Methods:

  • Review of existing scientific literature on influenza modeling.
  • Analysis of the biological premises used in theoretical frameworks.
  • Critique of established assumptions regarding influenza seasonality and evolution.

Main Results:

  • Identified significant limitations and lack of empirical support for core assumptions in current influenza models.
  • Demonstrated that the "unchallenged dogma" in the field may be hindering a comprehensive understanding.
  • Highlighted a critical need for biologically realistic foundations in mathematical approaches.

Conclusions:

  • Current mathematical models for influenza dynamics are based on potentially flawed biological assumptions.
  • Re-evaluation of these foundational dogmas is crucial for advancing our understanding of influenza's seasonal and evolutionary behavior.
  • Future modeling efforts must incorporate more robust and validated biological principles.