https://mscazmy.github.io/tags/epidemiology/Recent content in Epidemiology on Ahmed AzeezHugoen-usFri, 16 May 2025 00:00:00 +0000https://mscazmy.github.io/2025/05/16/diagnostic-tests/Fri, 16 May 2025 00:00:00 +0000https://mscazmy.github.io/2025/05/16/diagnostic-tests/Before you run a single regression or ANOVA, there is a step that separates rigorous analysis from shaky conclusions: diagnostic testing. Think of it as a pre-flight checklist for your data. Skip it, and you risk landing in entirely the wrong place. Why Diagnostics Matter Most statistical methods rest on assumptions — about how data are distributed, how variables relate to one another, and how errors behave. When those assumptions break down silently, the model keeps running and happily produces numbers that mean very little.https://mscazmy.github.io/2024/02/10/public-health-ethics/Sat, 10 Feb 2024 00:00:00 +0000https://mscazmy.github.io/2024/02/10/public-health-ethics/What is Ethics? What is Public Health Ethics? Principles of Ethical Practice in Public Health Types of Ethics for a Public Health Professional Steps in a Process of Ethical Decision Making Importance of Ethics for Public Health Professionals References and For More Information What is Ethics? Ethics are the set of rules that govern our expectations of our own and others' behavior. The term 'ethics' is derived from the Greek word ethos that can mean custom, tradition, personality or disposition.https://mscazmy.github.io/2024/01/15/epi-outbreak/Mon, 15 Jan 2024 00:00:00 +0000https://mscazmy.github.io/2024/01/15/epi-outbreak/Introduction Data Exploration Feature Engineering Cleaning Data Clustering data Predicting Outbreak Severity Introduction Early detection and classification of infectious disease outbreaks is one of the most consequential challenges in public health. Syndromic surveillance systems collect weekly data on case counts, fatality rates, vaccination coverage, and environmental conditions — yet translating this information into actionable severity classifications remains difficult. In this project, I apply supervised machine learning to a multi-district epidemiological surveillance dataset to predict outbreak severity level: Mild, Moderate, or Severe.