Related Experiment Video

Updated: Aug 27, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.7K

Spatial Epidemiological Analysis of Keshan Disease in China

Yuehui Jia1, Shan Han1,2, Jie Hou1

  • 1Institute of Keshan Disease, Chinese Center for Endemic Disease Control, Harbin Medical University, Harbin 150081, China.

Annals of Global Health
|October 3, 2022
PubMed
Abstract

Keywords:
Keshan diseaseprecision prevention and controlspatial autocorrelationspatial epidemiologyspatial regression

More Related Videos

Author Spotlight: Exploring the Role of Inflammation in the Co-occurrence of Primary Sjogren's Syndrome and Lung Adenocarcinoma10:21

Author Spotlight: Exploring the Role of Inflammation in the Co-occurrence of Primary Sjogren's Syndrome and Lung Adenocarcinoma

Published on: September 20, 2024

528
Murine Experimental Model of Original Tumor Development and Peritoneal Metastasis via Orthotopic Inoculation with Ovarian Carcinoma Cells08:17

Murine Experimental Model of Original Tumor Development and Peritoneal Metastasis via Orthotopic Inoculation with Ovarian Carcinoma Cells

Published on: December 9, 2016

10.7K

Related Concept Videos

Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
15.6K
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

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:
171
Introduction to Epidemiology01:26

Introduction to Epidemiology

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,...
924
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

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:
489
Principles of Disease Surveillance01:26

Principles of Disease Surveillance

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...
171