CPH Focus: Evidence-Based Approaches to Public Health: Epidemiology – Measures of Disease Frequency: Mortality and Morbidity Rates In this tutorial, we’ll cover another essential topic in public health: measures of
Category: Tutorial
Epi Explained: Understanding Morbidity and Mortality Morbidity and mortality are two critical concepts in public health and epidemiology. These terms help researchers and healthcare professionals assess the impact of diseases
Epi Explained: Understanding Statistical Significance, P-Values, and Z-Scores Statistical significance, p-values, and z-scores are fundamental concepts in statistics and research. They are crucial in fields such as medicine, psychology, and
Epi Explained: Understanding Prevalence Rate Measuring disease burden in a population is crucial to public health decision-making. One of the most fundamental metrics used is the prevalence rate. Understanding this
In the realm of epidemiology, the terms epidemic, pandemic, and endemic are fundamental in describing the prevalence and geographic spread of diseases. These terms, often used in public health discussions,
Introduction For this ThuRsday Tutorial, we’re going to cover something a bit different. Instead of showing how to do fairly simple epidemiological calculations, this edition will cover the first of
Clinical trials, particularly randomized controlled trials (RCTs), are critical to evidence-based interventions, pharmaceutical testing, and public heatlh. They provide the most reliable data on the effectiveness of treatments, interventions, and
Case-control studies are a cornerstone of population research, offering insights into the factors that may contribute to the occurrence of diseases or conditions. These studies are particularly invaluable in understanding
Nonrandomized (Community) Trials, also known as observational studies or quasi-experimental studies, are a crucial research design in epidemiology and public health. These studies provide valuable insights into the effects of
The Susceptible-Exposed-Infected-Recovered (SEIR) model is a natural extension of the SIR Model, accounting for a fourth category of disease state, Exposure. For this PyFriday Tutorial, we’ll cover how to not