[Homicides in Rio de Janeiro, Brazil: an analysis of lethal violence]

Francisca Letícia Miranda Gadelha Cardoso1, Fátima Regina Cecchetto2, Juliana Silva Corrêa1

  • 1Escola Nacional de Saúde Pública, Fiocruz, Rio de Janeiro, RJ, Brasil, gadelhacardoso.leticia@gmail.com.

Related Concept Videos

Bystander Effect02:09

Bystander Effect

The discussion of bullying highlights the problem of witnesses not intervening to help a victim. This is a common occurrence, as the following well-publicized event demonstrates. In 1964, in Queens, New York, a 19-year-old woman named Kitty Genovese was attacked by a person with a knife near the back entrance to her apartment building and again in the hallway inside her apartment building. When the attack occurred, she screamed for help numerous times and eventually died from her stab wounds.
10.4K
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:  
1.5K
Aggression01:47

Aggression

Humans engage in aggression when they seek to cause harm or pain to another person. Aggression takes two forms depending on one’s motives: hostile or instrumental. Hostile aggression is motivated by feelings of anger with intent to cause pain; a fight in a bar with a stranger is an example of hostile aggression. In contrast, instrumental aggression is motivated by achieving a goal and does not necessarily involve intent to cause pain (Berkowitz, 1993); a contract killer who murders for...
30.6K
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:
1.2K
Lethal Alleles02:41

Lethal Alleles

Agouti: A Lethal Allele
Lucien Cuénot discovered lethal alleles in 1905 while studying the inheritance of coat color in mice. The agouti gene is responsible for the color of the coat in mice. This gene codes for an agouti-signaling protein, which is responsible for melanin distribution in mammals. The wild-type allele gives rise to gray-brown coat color in mice, while the mutant allele gives rise to yellow coat color. In addition to coat color, the agouti gene is associated with the yellow...
19.2K
Investigation of Disease Outbreaks01:23

Investigation of Disease Outbreaks

Multistate foodborne outbreaks pose significant public health risks and require meticulous investigation to identify sources and implement control measures. The Centers for Disease Control and Prevention (CDC) utilizes a dynamic seven-step process for these investigations, integrating data from laboratories, interviews, and environmental assessments to protect public health.Outbreak Detection: The detection of multistate outbreaks typically begins with PulseNet, the CDC's national laboratory...
29