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

Pareto Chart00:52

Pareto Chart

7.3K
A Pareto chart is a bar graph or a combination of both line and bar graphs. The bar lengths represent the individual values or the frequency, while the lines represent the cumulative total values. In this chart, the longest bars are arranged on the left and the shortest bars on the right, which makes it easier to read and interpret the data. It can also be called a Pareto diagram or Pareto analysis.
The Pareto chart is named after the Italian economist Vilfredo Pareto, who described the Pareto...
7.3K
Correlation01:09

Correlation

13.1K
In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
13.1K
Factors Affecting Illness01:18

Factors Affecting Illness

4.7K
When a person's physical, emotional, intellectual, social development or spiritual functioning is compromised, this deviation from a healthy normal state is called illness. Illness creates stress that in turn harms individuals. Irritation, anger, denial, hopelessness, and fear are behavioral and emotional changes an individual experiences in the phases of illness. A variety of factors influence a person's health and well-being.
For instance, risk factors are connected to illness,...
4.7K
Types of Skewness01:09

Types of Skewness

14.5K
If the frequency distribution of a data set is more inclined towards smaller or larger values, the distribution is said to be skewed. If data values are skewed to the right, then the distribution is called positively skewed. Conversely, if the plot is skewed to the left, the distribution is called negatively skewed.
For instance, in the middle of a pandemic, the geographical distribution of vaccine coverage may be positively skewed towards populations in the global north countries. However,...
14.5K
Factors Affecting the Risk of Infection01:26

Factors Affecting the Risk of Infection

12.8K
The hosts' susceptibility to infection depends on several factors. The integrity of the skin and mucous membranes helps protect the body against microbial attacks. When the skin is altered, the chance of infection, limb loss, and even death increases.
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin...
12.8K
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

851
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
851

You might also read

Related Articles

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

Sort by
Same author

Education, health-based selection, and the widening mortality gap between Americans with and without a 4-year college degree.

American journal of epidemiology·2024
Same author

The Great Divide: Education, Despair, and Death.

Annual review of economics·2022
Same author

GDP, wellbeing, and health: thoughts on the 2017 round of the International Comparison Program.

The Review of income and wealth·2022
Same author

Life expectancy in adulthood is falling for those without a BA degree, but as educational gaps have widened, racial gaps have narrowed.

Proceedings of the National Academy of Sciences of the United States of America·2021
Same author

Decoding the mystery of American pain reveals a warning for the future.

Proceedings of the National Academy of Sciences of the United States of America·2020
Same author

What do self-reports of wellbeing say about life-cycle theory and policy?

Journal of public economics·2018
See all related articles

Related Experiment Video

Updated: Oct 26, 2025

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

1.5K

COVID-19 and Global Income Inequality.

Angus Deaton1,2

  • 1School of Public and International Affairs, Princeton University National Bureau of Economic Research.

LSE Public Policy Review
|July 26, 2021
PubMed
Summary
This summary is machine-generated.

The COVID-19 pandemic decreased international income inequality when measured country-by-country, contrary to popular belief. However, when weighted by population, global income inequality increased due to significant GDP declines in India.

More Related Videos

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

1.3K
Comparing Objective Conjunctival Hyperemia Grading and the Ocular Surface Disease Index Score in Dry Eye Syndrome During COVID-19
06:29

Comparing Objective Conjunctival Hyperemia Grading and the Ocular Surface Disease Index Score in Dry Eye Syndrome During COVID-19

Published on: May 25, 2022

2.5K

Related Experiment Videos

Last Updated: Oct 26, 2025

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

1.5K
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

1.3K
Comparing Objective Conjunctival Hyperemia Grading and the Ocular Surface Disease Index Score in Dry Eye Syndrome During COVID-19
06:29

Comparing Objective Conjunctival Hyperemia Grading and the Ocular Surface Disease Index Score in Dry Eye Syndrome During COVID-19

Published on: May 25, 2022

2.5K

Area of Science:

  • Economics
  • Global Health
  • Public Policy

Background:

  • A common assumption is that the COVID-19 pandemic exacerbated global income inequality.
  • This belief suggests poorer nations experienced greater per capita income reductions than wealthier ones.

Purpose of the Study:

  • To investigate the pandemic's actual impact on global income inequality.
  • To analyze the relationship between country-level COVID-19 mortality and GDP per capita changes.

Main Methods:

  • Comparative analysis of GDP per capita data across countries before and after the pandemic's onset.
  • Examination of COVID-19 death rates and their correlation with economic performance.
  • Utilizing International Monetary Fund (IMF) forecasts from October 2019 and October 2020 for comparison.

Main Results:

  • Contrary to expectations, international income inequality decreased when analyzed on a per-country basis.
  • Higher-income countries experienced greater declines in GDP per capita, linked to higher COVID-19 death rates.
  • When weighted by population, global income inequality rose, primarily due to India's GDP fall and China's continued growth.

Conclusions:

  • The pandemic's effect on global income inequality is complex and depends on the measurement method (country-by-country vs. population-weighted).
  • Higher COVID-19 mortality correlated with greater economic contraction in richer nations.
  • Findings focus on GDP per capita and do not fully capture living standards or suffering distribution.