The main idea is how incidence versus prevalence relate to illness duration. Incidence is about new infections happening over a period, while prevalence is about how many people are currently ill. If a therapy cures illness faster, it reduces how long people stay diseased, so fewer people are sick at any given time (prevalence goes down). But the rate at which new people become ill (incidence) depends on factors like exposure and transmission, not how long existing cases last. If the therapy doesn’t change how likely people are to get infected, the number of new cases per time remains the same. So the incidence stays the same.

An outbreak that covers many countries or continents and affects a large number of people is a pandemic. The key idea is the geographic spread: an epidemic is a surge of cases in a specific area, while a pandemic crosses borders and becomes global. Endemic means a disease is always present in a particular area at a baseline level, and hyperendemic describes persistently high levels in a population. An example of a pandemic is the Spanish flu that spread worldwide, illustrating how a local outbreak can become global.

A health impact assessment is a structured process to estimate potential health effects of a policy, program, or project. It looks at how decisions influence health through factors like housing, transportation, employment, education, and the environment, and it uses evidence and stakeholder input to identify both positive and negative health outcomes before decisions are finalized. The goal is to inform and shape choices by offering practical recommendations to maximize benefits and minimize harms, often with steps such as screening, scoping, assessment, recommendations, reporting, and monitoring. This approach is distinct from simply measuring economic impact, forecasting weather-related health changes, or implementing interventions without evaluating health consequences.

A logic model functions as a planning and evaluation map that links what you invest and do with the short-, intermediate-, and long-term changes you expect. By laying out inputs (resources), activities, outputs, and outcomes, along with the assumed causal pathways and underlying assumptions, it makes the program theory explicit. This clarity helps ensure that what you implement is aligned with the desired impact and provides a concrete framework for measuring progress. It guides evaluation design by identifying appropriate indicators for each step in the pathway and clarifying what data to collect, when, and how to interpret them. In short, a logic model connects resources and activities to outcomes and impact and shapes how you measure success, rather than focusing solely on disease theory, statistical analysis, or budgeting in isolation.