❤️‍🩹Intro to Public Health Unit 3 – Epidemiology: Core Principles & Methods

What's Epidemiology Anyway?

• Epidemiology involves the study of the distribution and determinants of health-related states or events in specified populations
• Applies this study to the control of health problems by identifying risk factors and targets for preventive healthcare
• Focuses on population-level health rather than individual-level health outcomes
• Encompasses research methodologies to investigate the causes of health outcomes and diseases in populations
• Provides data for policy decisions and evidence-based practice by identifying risk factors for disease and targets for preventive healthcare
• Helps in understanding the transmission patterns during epidemics and measures to contain the spread of diseases
• Plays a key role in disease prevention by identifying modifiable risk factors that inform public health policies and interventions

Key Concepts You Need to Know

• Incidence refers to the occurrence of new cases of disease or injury in a population over a specified period of time
• Prevalence describes the proportion of a population found to have a condition at a specific point in time
• Morbidity represents the state of being symptomatic or unhealthy for a disease or condition
• Mortality indicates the state of being deceased as a result of a disease or condition
  • Case fatality rate measures the proportion of deaths within a designated population of people with a particular condition over a certain period of time
• Risk factors encompass any attribute, characteristic, or exposure that increases the likelihood of developing a disease or injury
• Health determinants include the range of behavioral, biological, socioeconomic, and environmental factors that influence health status
• Epidemiological triad consists of an external agent, a susceptible host, and an environment that brings the host and agent together

How We Track Diseases

• Surveillance systems involve the continuous, systematic collection, analysis, and interpretation of health-related data for planning, implementation, and evaluation of public health practice
  • Active surveillance requires health officials to contact healthcare providers or the population to seek information about health conditions
  • Passive surveillance relies on the cooperation of health-care providers to report the occurrence of a specific disease or condition to the health department
• Notifiable diseases are those that healthcare providers must report to public health authorities due to their severity or communicability (tuberculosis, measles)
• Disease registries collect and maintain data on specific conditions or diseases (cancer registries)
• Outbreak investigations aim to identify the source of ongoing outbreaks and implement control measures to prevent additional illness
• Contact tracing involves identifying and monitoring individuals who may have had contact with an infectious person to prevent further transmission
• Screening programs test for diseases in at-risk populations to enable early detection and treatment (mammography for breast cancer)
• Sentinel surveillance uses a prearranged sample of reporting sources to monitor disease trends and identify outbreaks (influenza-like illness in selected healthcare facilities)

Crunching the Numbers: Basic Epi Methods

• Measures of frequency quantify the occurrence of health events in a population
  • Incidence rate calculates the number of new cases of a disease or condition that occur during a specified time period divided by the size of the population at risk
  • Prevalence proportion estimates the proportion of a population that has a particular disease or condition at a specific point in time
• Measures of association assess the relationship between an exposure and a health outcome
  • Relative risk compares the risk of a health event among an exposed group to the risk among an unexposed group: $RR = \frac{Incidence \: in \: exposed}{Incidence \: in \: unexposed}$
  • Odds ratio represents the odds that an outcome will occur given a particular exposure, compared to the odds of the outcome occurring in the absence of that exposure
• Measures of impact gauge the potential effects of a risk factor on disease occurrence in a population
  • Attributable risk estimates the proportion of disease incidence that can be attributed to a specific exposure
  • Population attributable risk determines the proportion of disease cases over a specified time period that would be prevented following elimination of the exposures
• Stratification involves separating data into subgroups based on specific characteristics (age, sex) to examine stratum-specific estimates and control for confounding variables
• Adjustment techniques account for the effects of differences in the distribution of potential confounding factors between comparison groups

Study Types: From Observational to Experimental

• Observational studies examine the association between exposures and outcomes without any intervention from the investigator
  • Cohort studies follow a group of people over time who are alike in many ways but differ by a certain characteristic (smokers vs. non-smokers) to determine how exposure affects incidence of a disease
  • Case-control studies identify people with a disease (cases) and a similar group without the disease (controls), then compare previous exposures between the two groups
  • Cross-sectional studies measure the prevalence of disease and exposures simultaneously in a representative subset of the population
  • Ecological studies assess the overall frequency of disease in relation to a set of risk factors measured at the population level rather than individual level
• Experimental studies involve an intervention by the investigator to assess the effect of an exposure on an outcome
  • Randomized controlled trials randomly allocate subjects into an experimental group or a control group to test a specific drug, treatment, or intervention while controlling other factors
  • Field trials are conducted in a natural setting with healthy people to investigate whether an agent or intervention reduces the risk of developing a specific disease
  • Community trials apply the intervention to an entire community or geographical area rather than to individuals

Causation vs. Correlation: The Big Debate

• Correlation indicates the relationship between two variables, where a change in one variable is associated with a change in the other variable
  • Positive correlation exists when an increase in one variable corresponds to an increase in the other variable
  • Negative correlation occurs when an increase in one variable corresponds to a decrease in the other variable
• Causation implies that one event is the direct result of the occurrence of the other event; a cause-and-effect relationship
• Hill's criteria for causation provide a framework to assess the evidence of a causal relationship between an exposure and a health outcome
  • Strength of association evaluates the magnitude of the association between exposure and outcome
  • Consistency assesses whether the association has been repeatedly observed in different populations and circumstances
  • Specificity examines if a single putative cause produces a specific effect
  • Temporality ensures that the cause precedes the effect in time
  • Biological gradient, or dose-response relationship, observes whether the magnitude of the effect varies with the level of exposure
  • Plausibility considers if the association agrees with currently accepted understanding of pathobiological processes
  • Coherence determines if the association is compatible with existing theory and knowledge
  • Experiment evaluates whether the frequency of the outcome changes when the exposure is altered
  • Analogy assesses if there are similar associations in other populations or under different circumstances

Real-World Applications

• Outbreak investigations during public health emergencies (Ebola, Zika) to identify the source and mode of transmission and implement control measures
• Surveillance of infectious diseases (influenza, COVID-19) to monitor trends, detect outbreaks, and guide public health interventions
• Identification of risk factors for chronic diseases (obesity, cardiovascular disease) to inform prevention strategies and health promotion efforts
• Evaluation of the effectiveness and safety of vaccines and other public health interventions through post-licensure studies
• Investigation of environmental health hazards (air pollution, water contamination) and their impact on population health outcomes
• Assessment of health disparities and social determinants of health to guide policies and programs aimed at reducing inequities
• Monitoring and evaluation of global health programs (HIV/AIDS, malaria) to track progress and optimize resource allocation
• Informing evidence-based clinical practice guidelines and decision-making in healthcare settings

Challenges and Ethical Considerations

• Balancing individual privacy and confidentiality with the need for data collection and sharing for public health purposes
• Addressing potential biases in study design, data collection, and analysis that may lead to erroneous conclusions or perpetuate health inequities
• Ensuring equitable access to public health interventions and resources, particularly for vulnerable or marginalized populations
• Navigating the complexities of informed consent and community engagement in epidemiological research, especially in emergency settings
• Considering the social, economic, and political implications of epidemiological findings and their impact on public health policy and practice
• Maintaining scientific integrity and independence in the face of competing interests or pressures from stakeholders
• Promoting transparency, accountability, and effective communication of epidemiological information to diverse audiences
• Addressing the limitations of observational studies in establishing causal relationships and the need for rigorous experimental designs when feasible and ethically appropriate