Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Infection01:20

Infection

11.4K
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...
11.4K
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

414
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:
414
Causality in Epidemiology01:21

Causality in Epidemiology

1.4K
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
1.4K
Rous Sarcoma Virus (RSV) and Cancer01:03

Rous Sarcoma Virus (RSV) and Cancer

6.0K
Rous Sarcoma virus or RSV was discovered by F. Peyton Rous in the year 1911 as a filterable transmissible agent that could cause tumors in chickens. He won a Nobel Prize for this discovery in 1966. His experiments clearly demonstrated that some cancers could be caused by infectious agents and led to the discovery of many more cancer-causing viruses in animals as well as humans.
RSV is a retrovirus that contains two copies of a plus-strand  RNA genome. Its genome consists of four main open...
6.0K
Principles of Disease Surveillance01:26

Principles of Disease Surveillance

393
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
393
Viral Recombination00:57

Viral Recombination

24.7K
Cells are sometimes infected by more than one virus at once. When two viruses disassemble to expose their genomes for replication in the same cell, similar regions of their genomes can pair together and exchange sequences in a process called recombination. Alternatively, viruses with segmented genomes can swap segments in a process called reassortment.
24.7K

You might also read

Related Articles

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

Sort by
Same journal

Real particle physics analysis by UK secondary school students using the ATLAS Open Data: an illustration through a collection of original student research.

European physical journal plus·2026
Same journal

Sensitivity analysis of the top-quark sector.

European physical journal plus·2026
Same journal

Probing strong first-order electroweak phase transition scenarios in two-Higgs-doublet model with FCC-ee/CEPC.

European physical journal plus·2026
Same journal

Singlet-like correlations: equal peak work, unequal robustness.

European physical journal plus·2026
Same journal

The Vlasov bivector: a parameter-free approach to Vlasov kinematics.

European physical journal plus·2026
Same journal

From LUXE to future colliders: probing strong-field QED and beyond.

European physical journal plus·2026

Related Experiment Video

Updated: Dec 19, 2025

Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples
09:26

Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples

Published on: June 30, 2023

1.5K

The coronavirus spread: the Italian case.

Aldo Bonasera1,2, G Bonasera1, Suyalatu Zhang3

  • 1Cyclotron Institute, Texas A&M University, College Station, TX 77843 USA.

European Physical Journal Plus
|June 9, 2020
PubMed
Summary

A novel model analyzing population growth and fluid dynamics aids in understanding Coronavirus (COVID-19) spread across Italian regions. It identifies high-risk areas and suggests resource reallocation for better containment strategies.

More Related Videos

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses
03:53

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses

Published on: November 10, 2023

1.7K
Swabbing the Urban Environment - A Pipeline for Sampling and Detection of SARS-CoV-2 From Environmental Reservoirs
07:13

Swabbing the Urban Environment - A Pipeline for Sampling and Detection of SARS-CoV-2 From Environmental Reservoirs

Published on: April 9, 2021

4.5K

Related Experiment Videos

Last Updated: Dec 19, 2025

Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples
09:26

Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples

Published on: June 30, 2023

1.5K
Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses
03:53

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses

Published on: November 10, 2023

1.7K
Swabbing the Urban Environment - A Pipeline for Sampling and Detection of SARS-CoV-2 From Environmental Reservoirs
07:13

Swabbing the Urban Environment - A Pipeline for Sampling and Detection of SARS-CoV-2 From Environmental Reservoirs

Published on: April 9, 2021

4.5K

Area of Science:

  • Epidemiology
  • Mathematical Modeling
  • Public Health

Background:

  • The Coronavirus (COVID-19) pandemic necessitated rapid development of predictive models for effective containment.
  • Understanding regional variations in disease spread is crucial for targeted interventions.

Purpose of the Study:

  • To apply a novel model integrating population dynamics, chaotic maps, and fluid flow principles to predict and analyze COVID-19 spread in Italian regions.
  • To categorize regions by risk, identify geographical patterns, and suggest data-driven strategies for disease control.

Main Methods:

  • Development and application of a mathematical model incorporating population growth, chaotic maps, and turbulent flow concepts.
  • Analysis of COVID-19 spread data stratified by Italian regions.
  • Risk categorization and anomaly detection within regional data.

Main Results:

  • The model identified specific geographical areas (e.g., between the Apennines and Alps) as high-risk zones.
  • The Veneto region demonstrated an effective response, with potential for resource sharing with heavily affected regions like Lombardia.
  • Anomalies in Lazio, Campania, and Sicilia require close monitoring. Predicted fatalities aligned with reported data.

Conclusions:

  • The model provides valuable insights into regional COVID-19 dynamics, aiding in strategic planning.
  • Resource reallocation, particularly increased testing in severely affected regions, is recommended.
  • Investigating regional disparities in fatality rates is essential for refining public health strategies.