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

Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

228
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:
228
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

89
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:
89
Introduction to Epidemiology01:26

Introduction to Epidemiology

538
Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...
538
What is Population Genetics?01:25

What is Population Genetics?

56.8K
A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.
56.8K
Censoring Survival Data01:09

Censoring Survival Data

38
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
38
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

271
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
271

You might also read

Related Articles

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

Sort by
Same author

A scoping review of frameworks that guide race and ethnicity data collection in health settings: Learnings for the Canadian health setting.

Canadian journal of public health = Revue canadienne de sante publique·2026
Same author

Common Determinants of Lung Cancer Screening Uptake in Three High-Risk and Underserved Communities.

Journal of the American College of Radiology : JACR·2025
Same author

Parental Concerns About Child Disordered Eating Among Youth With High Weights Participating in a Motivational Interviewing-Based Behavioral Intervention.

Journal of nutrition education and behavior·2025
Same author

Understanding determinants of lung cancer preventive care in at-risk urban American Indians and Alaska Natives: A mixed-methods study.

Preventive medicine reports·2024
Same author

Impact of Breastfeeding Barriers on Racial/Ethnic Disparities in Breastfeeding Outcomes in North Dakota.

Journal of racial and ethnic health disparities·2024
Same author

Centering Data Sovereignty, Tribal Values, and Practices for Equity in American Indian and Alaska Native Public Health Systems.

Public health reports (Washington, D.C. : 1974)·2023

Related Experiment Video

Updated: May 7, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

2.0K

How Should Epidemiologists Respond to Data Genocide?

Abigail Echo-Hawk1, Sofia Locklear2, Sarah McNally3

  • 1Executive vice president of the Seattle Indian Health Board and director of the Urban Indian Health Institute.

AMA Journal of Ethics
|January 2, 2025
PubMed
Summary

Colonial practices in US federal data systems harm data quality for American Indian/Alaska Native (AI/AN) populations. Improving AI/AN health research requires addressing bias and racist reporting in data collection and analysis.

More Related Videos

MEDUSA for Identifying Death Regulatory Genes in Chemo-genetic Profiling Data
07:17

MEDUSA for Identifying Death Regulatory Genes in Chemo-genetic Profiling Data

Published on: February 7, 2025

244
Microbial Communities in Nature and Laboratory - Interview
29:13

Microbial Communities in Nature and Laboratory - Interview

Published on: May 28, 2007

6.1K

Related Experiment Videos

Last Updated: May 7, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

2.0K
MEDUSA for Identifying Death Regulatory Genes in Chemo-genetic Profiling Data
07:17

MEDUSA for Identifying Death Regulatory Genes in Chemo-genetic Profiling Data

Published on: February 7, 2025

244
Microbial Communities in Nature and Laboratory - Interview
29:13

Microbial Communities in Nature and Laboratory - Interview

Published on: May 28, 2007

6.1K

Area of Science:

  • Public Health
  • Epidemiology
  • Health Equity

Background:

  • US federal data systems contain deeply entrenched colonial practices.
  • These practices undermine data quality for American Indian/Alaska Native (AI/AN) populations.
  • Historical and ongoing biases impact AI/AN health research.

Purpose of the Study:

  • To demonstrate the ethical and clinical need for inclusive, diverse, and accurate data in AI/AN health research.
  • To highlight how colonial practices affect data quality for AI/AN individuals.
  • To advocate for critical evaluation of epidemiological methods concerning AI/AN populations.

Main Methods:

  • Analysis of cases related to maternal mortality among AI/AN people.
  • Examination of COVID-19 data pertaining to AI/AN communities.
  • Review of data collection, analytical, and dissemination practices in epidemiological research.

Main Results:

  • Colonial practices have led to significant data quality issues for AI/AN health trends.
  • Maternal mortality and COVID-19 data illustrate the negative impacts of poor data quality.
  • Existing epidemiological practices perpetuate bias and inaccuracies regarding AI/AN health.

Conclusions:

  • Epidemiologists must actively challenge implicit bias and question established methods.
  • Recognizing and rectifying colonial and racist reporting practices is crucial for accurate AI/AN health research.
  • Inclusive, diverse, and accurate data are essential for understanding and improving AI/AN health outcomes.