Related Experiment Video

Updated: Apr 25, 2026

Preventing the Spread of Malaria and Dengue Fever Using Genetically Modified Mosquitoes
17:50

Preventing the Spread of Malaria and Dengue Fever Using Genetically Modified Mosquitoes

Published on: July 4, 2007

11.9K

[The contribution of epidemiology to disease control: malaria]

Lyda E Osorio1

  • 1Facultad de Salud, Universidad del Valle, Cali, Colombia, lyda1oso@gmail.com.

Revista De Salud Publica (Bogota, Colombia)
|August 16, 2014
PubMed

More Related Videos

Building a Better Mosquito: Identifying the Genes Enabling Malaria and Dengue Fever Resistance in A. gambiae and A. aegypti Mosquitoes15:03

Building a Better Mosquito: Identifying the Genes Enabling Malaria and Dengue Fever Resistance in A. gambiae and A. aegypti Mosquitoes

Published on: July 4, 2007

14.9K
Standard Membrane Feeding Assay for the Detection of Plasmodium falciparum Infection in Anopheles Mosquito Vectors05:28

Standard Membrane Feeding Assay for the Detection of Plasmodium falciparum Infection in Anopheles Mosquito Vectors

Published on: May 12, 2022

3.2K

Related Concept Videos

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,...
2.3K
Causality in Epidemiology01:21

Causality in Epidemiology

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...
2.1K
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:  
1.6K
Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
1.1K
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...
845
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:
1.3K