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

Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

202
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
202
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

385
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
385
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

135
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:
135
Introduction To Survival Analysis01:18

Introduction To Survival Analysis

252
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
252
Cancer Survival Analysis01:21

Cancer Survival Analysis

359
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
359
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

149
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
149

You might also read

Related Articles

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

Sort by
Same author

Building Career Capital Through Service: A Qualitative Study of Public Health Corps Members' Skill Development and Professional Growth.

Journal of public health management and practice : JPHMP·2026
Same author

Attainment of Public Health Degrees in the Governmental Public Health Workforce in 2024.

American journal of public health·2026
Same author

The long arm of childhood policy: Historical schooling laws and COVID-19 pandemic-era mortality.

Epidemiology (Cambridge, Mass.)·2026
Same author

Taking heterogeneity seriously: black immigrant life expectancy in the United States.

American journal of epidemiology·2026
Same author

Age-specific mortality patterns across influenza pandemics: evidence from all-cause mortality data across multiple populations.

International journal of epidemiology·2026
Same author

Policy Surveillance of Safe Patient Handling and Mobility Laws to Reduce Injury among Healthcare Workers.

New solutions : a journal of environmental and occupational health policy : NS·2026

Related Experiment Video

Updated: Jul 13, 2025

Collection and Extraction of Occupational Air Samples for Analysis of Fungal DNA
12:02

Collection and Extraction of Occupational Air Samples for Analysis of Fungal DNA

Published on: May 2, 2018

12.5K

Examining Excess Mortality Among Critical Workers in Minnesota During 2020-2021: An Occupational Analysis.

Harshada Karnik1, Elizabeth Wrigley-Field1, Zachary Levin1

  • 1Harshada Karnik, Zachary Levin, and Jonathon P. Leider are with the Health Policy and Management Division, University of Minnesota School of Public Health, Minneapolis. Elizabeth Wrigley-Field is with the Department of Sociology and Minnesota Population Center, University of Minnesota. Yea-Hung Chen is with the Department of Epidemiology and Biostatistics, University of California, San Francisco. Erik W. Zabel is with the Center for Occupational Health and Safety, Minnesota Department of Health, St. Paul. Marizen Ramirez was with the Division of Environmental Health Sciences, University of Minnesota School of Public Health, Twin Cities when the study was conducted.

American Journal of Public Health
|October 11, 2023
PubMed
Summary

Civilian critical workers faced higher COVID-19 mortality, with significant variations by occupation and race. Workers of color experienced disproportionately higher excess deaths, highlighting urgent needs for targeted safety protocols.

More Related Videos

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India
09:33

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India

Published on: December 23, 2022

2.3K
Author Spotlight: Deciphering the Long-Term Effects of Low-Level Blast Exposures in Mice
06:00

Author Spotlight: Deciphering the Long-Term Effects of Low-Level Blast Exposures in Mice

Published on: May 24, 2024

952

Related Experiment Videos

Last Updated: Jul 13, 2025

Collection and Extraction of Occupational Air Samples for Analysis of Fungal DNA
12:02

Collection and Extraction of Occupational Air Samples for Analysis of Fungal DNA

Published on: May 2, 2018

12.5K
Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India
09:33

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India

Published on: December 23, 2022

2.3K
Author Spotlight: Deciphering the Long-Term Effects of Low-Level Blast Exposures in Mice
06:00

Author Spotlight: Deciphering the Long-Term Effects of Low-Level Blast Exposures in Mice

Published on: May 24, 2024

952

Area of Science:

  • Public Health
  • Occupational Health
  • Epidemiology

Background:

  • The COVID-19 pandemic presented significant occupational risks for essential workers.
  • Understanding disparities in mortality among critical occupations is crucial for public health interventions.

Purpose of the Study:

  • To assess COVID-19 associated occupational risks among civilian critical workers aged 16-65 in Minnesota.
  • To identify variations in excess mortality by specific critical occupations, race, and vaccine rollout phases.

Main Methods:

  • Utilized death certificate data and occupational employment rates from 2017-2021.
  • Estimated excess mortality for critical versus noncritical occupations during 2020-2021.
  • Analyzed data stratified by race/ethnicity and vaccine eligibility tiers.

Main Results:

  • Workers in critical occupations exhibited higher excess mortality compared to noncritical workers.
  • Transportation, logistics, construction, and food service roles showed higher excess mortality.
  • Workers of color consistently experienced higher excess mortality across most occupations; 2021 saw greater excess mortality than 2020.

Conclusions:

  • Excess mortality varied significantly among critical workers based on occupation and race.
  • Targeted interventions and worker safety protocols are essential to address health inequities.
  • Occupational mortality analysis is key to identifying vulnerable populations and prioritizing protective measures.