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

Actuarial Approach01:20

Actuarial Approach

112
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
112
Causality in Epidemiology01:21

Causality in Epidemiology

673
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...
673
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

513
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:  
513
Truncation in Survival Analysis01:09

Truncation in Survival Analysis

273
Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
273
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

229
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
229
Factors Affecting Illness01:18

Factors Affecting Illness

4.3K
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,...
4.3K

You might also read

Related Articles

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

Sort by
Same author

Lingering Effects Of The COVID-19 Pandemic On Non-COVID-19 Death Rates In The US, 2020-24.

Health affairs (Project Hope)·2026
Same author

Mental health and mortality trends in the United States.

Journal of health economics·2025
Same author

US State Restrictions and Excess COVID-19 Pandemic Deaths.

JAMA health forum·2024
Same author

Estimating Drug Involvement in Fatal Overdoses With Incomplete Information.

American journal of preventive medicine·2023
Same author

The Evolution of Excess Deaths in the United States During the First 2 Years of the COVID-19 Pandemic.

American journal of epidemiology·2023
Same author

Marijuana legalization and opioid deaths.

Journal of health economics·2023

Related Experiment Video

Updated: Aug 22, 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

1.3K

Pandemic And Recession Effects On Mortality In The US During The First Year Of COVID-19.

Christopher J Ruhm1

  • 1Christopher J. Ruhm (ruhm@virginia.edu), University of Virginia, Charlottesville, Virginia.

Health Affairs (Project Hope)
|November 7, 2022
PubMed
Summary

The COVID-19 pandemic and economic recession had complex effects on US mortality. While the pandemic increased deaths, the recession effect lowered them, preventing thousands of additional fatalities.

More Related Videos

A New Method for Inducing a Depression-Like Behavior in Rats
07:57

A New Method for Inducing a Depression-Like Behavior in Rats

Published on: February 22, 2018

21.1K
Live Imaging and Quantification of Viral Infection in K18 hACE2 Transgenic Mice Using Reporter-Expressing Recombinant SARS-CoV-2
08:41

Live Imaging and Quantification of Viral Infection in K18 hACE2 Transgenic Mice Using Reporter-Expressing Recombinant SARS-CoV-2

Published on: November 5, 2021

2.9K

Related Experiment Videos

Last Updated: Aug 22, 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

1.3K
A New Method for Inducing a Depression-Like Behavior in Rats
07:57

A New Method for Inducing a Depression-Like Behavior in Rats

Published on: February 22, 2018

21.1K
Live Imaging and Quantification of Viral Infection in K18 hACE2 Transgenic Mice Using Reporter-Expressing Recombinant SARS-CoV-2
08:41

Live Imaging and Quantification of Viral Infection in K18 hACE2 Transgenic Mice Using Reporter-Expressing Recombinant SARS-CoV-2

Published on: November 5, 2021

2.9K

Area of Science:

  • Public Health
  • Epidemiology
  • Health Economics

Background:

  • The period of March 2020–February 2021 saw nearly 700,000 excess deaths in the US.
  • Mortality changes resulted from both the pandemic effect (COVID-19 related) and the recession effect (unemployment related).

Purpose of the Study:

  • To decompose excess mortality into pandemic and recession effects.
  • To analyze these effects across demographics and causes of death.

Main Methods:

  • Utilized data from the Centers for Disease Control and Prevention (CDC).
  • Decomposed total mortality into pandemic and recession components.
  • Estimated effects by sex, race, ethnicity, age, and 14 specific causes of death.

Main Results:

  • The pandemic effect increased many mortality types, while the recession effect decreased most.
  • Without the recession effect, approximately 40,000 more deaths would have occurred.
  • Disparate impacts were observed, with vehicular, alcohol-related, and drug fatalities rising, and suicides decreasing due to offsetting effects.

Conclusions:

  • The recession effect partially counterbalanced pandemic-related mortality.
  • Understanding these distinct impacts is crucial for future pandemic preparedness and mitigation policies.
  • Policy efforts should consider socioeconomic factors alongside direct health interventions.