Related Experiment Video

Updated: Dec 18, 2025

DNA Fingerprinting of Mycobacterium leprae Strains Using Variable Number Tandem Repeat VNTR - Fragment Length Analysis FLA
09:39

DNA Fingerprinting of Mycobacterium leprae Strains Using Variable Number Tandem Repeat VNTR - Fragment Length Analysis FLA

Published on: July 15, 2011

27.7K

Epidemiological monitoring of leprosy indicators in Sergipe (2001-2015): segmented regression analysis

Carlos Dornels Freire de Souza1, Thiago Cavalcanti Leal1, João Paulo Silva de Paiva1

  • 1Department of Medicine, Center for the Study of Social and Preventative Medicine, Universidade Federal de Alagoas, Arapiraca, AL, Brazil.

Anais Brasileiros De Dermatologia
|June 12, 2020
PubMed

Keywords:
EpidemiologyLeprosyTime series studies

More Related Videos

Optimized Protocols for Mycobacterium leprae Strain Management: Frozen Stock Preservation and Maintenance in Athymic Nude Mice10:32

Optimized Protocols for Mycobacterium leprae Strain Management: Frozen Stock Preservation and Maintenance in Athymic Nude Mice

Published on: March 23, 2014

15.5K
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.9K

Related Concept Videos

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:
414
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:
799
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...
393
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,...
1.5K
Prevalence and Incidence01:08

Prevalence and Incidence

In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
1.4K
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

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:  
1.1K