Introduction to Epidemiology Notes 2024 PDF

Introduction to Epidemiology, Notes 2024 Laura Benjamins, MD, MPH Learning Objectives: Define Epidemiology - Distribution - Determination - Causation Describe Basic Terms & Concepts...

Introduction to Epidemiology, Notes 2024 Laura Benjamins, MD, MPH Learning Objectives: Define Epidemiology - Distribution - Determination - Causation Describe Basic Terms & Concepts - Epidemic, Pandemic, Endemic - Cluster, Rate - Outcomes: Discrete and Continuous Learn How to Calculate Rates - Incidence - Prevalence EPIDEMIOLOGY Study of the distribution and determinants of health-related states among specified populations. The application of that study to the control of health problems. The method used to find the causes of health outcomes and diseases in populations. In epidemiology, the patient is the community and individuals are viewed collectively. By definition, epidemiology is the study (scientific, systematic, and data-driven) of the distribution (frequency, pattern) and determinants (causes, risk factors) of health-related states and events (not just diseases) in specified populations (neighborhood, school, city, state, country, global). Epidemiology Purposes in Public Health Practice: Discover the agent, host, and environmental factors that affect health. Determine the relative importance of causes of illness, disability, and death. Identify those segments of the population that have the greatest risk from specific causes of ill health. Evaluate the effectiveness of health programs and services in improving population health. Epidemiologists Focus On: Distribution The frequency of a particular disease or health outcome, as well as any patterns or trends that may be identified. Determination Introduction to Epidemiology, Notes 2024 Laura Benjamins, MD, MPH Cause and effect: What are the risk factors associated with a disease? What are its underlying causes? Scope of Epidemiology – Six categories: Bradford Hill Criteria of Causation * In 1965 Austin Bradford Hill detailed criteria for assessing evidence of causation: 1. Strength: The larger the association, the more likely that it is causal. 2. Consistency: Consistent findings observed by different persons in different places with different samples. 3. Specificity: The more specific an association between a factor and an effect is, the bigger the probability of a causal relationship. 4. Temporality: The cause must precede the effect or outcome. 5. Biological gradient: Greater exposure should generally lead to greater incidence of the effect. 6. Plausibility: It must make biological sense (however this may be limited by current knowledge). Introduction to Epidemiology, Notes 2024 Laura Benjamins, MD, MPH 7. Coherence: Coherence between epidemiological and laboratory findings increases the likelihood of an effect. 8. Experiment: Similar results are found with experimental designs. 9. Analogy: The effect of similar factors may be considered. Epidemiology Key Terms * Epidemic: Disease occurrence among a population that is in excess of what is expected in a given time and place. Example – Ebola in parts of Africa. Pandemic: A disease or condition that spreads across regions. Example – COVID-19. Endemic: Disease or condition present among a population at all times. Example – Malaria in Africa. Outbreak vs. Epidemic vs. Pandemic o An outbreak is a sudden rise in the number of cases of a disease more than normal expectancy in a community or geographical area. An outbreak can be declared an epidemic when the disease spreads rapidly to many people. o Monkeypox – endemic in Nigeria, there were a cluster of cases in the UK in May, 2022. From then on, cases were reported from an increasing number of countries and regions. July 23, 2022 WHO declared it a public health emergency of international concern (PHEIC). As of Oct. 15th there have been 73,087 confirmed cases in 109 countries. o A pandemic is a global disease outbreak. It differs from an outbreak or epidemic because it:  affects a wider geographical area, often worldwide.  infects a greater number of people than an epidemic.  is often caused by a new virus or a strain of virus that has not circulated among people for a long time. Humans usually have little to no immunity against it. The virus spreads quickly from person-to-person worldwide.  causes much higher numbers of deaths than epidemics.  often creates social disruption, economic loss, and general hardship. Epidemic, Endemic, Pandemic: What are the differences? Differentiating Epidemic from Endemic or Sporadic Infectious Disease Occurrence Cluster: Group of cases in a specific time and place that might be more than expected. Example – measles outbreak at a factory in Fort Worth, Texas. Rate: Number of cases occurring during a specific period; always dependent on the size of the population during that period. Outcomes: o Discrete – disease occurrence or severity. o Continuous – for example blood pressure or glucose levels Introduction to Epidemiology, Notes 2024 Laura Benjamins, MD, MPH Rates Rates help us compare health problems among different populations that include two or more groups who differ by a selected characteristic. To calculate a rate, we first need to determine the frequency of disease, which includes: the number of cases of the illness or condition the size of the population at risk the period during which we are calculating the rate Incidence * The occurrence of NEW cases of disease or injury in a population over a specified period of time. It is used to describe how quickly the disease is occurring in a population. It can be used to identify increasing transmission and influence decision making about what public health interventions are required to slow this down. The incidence can be presented as a proportion or RISK, for example using the population as a denominator, or as a RATE such as person-time, which requires individuals are followed up over time. The incidence risk assumes that the entire population at risk at the beginning of the study period has been followed for the specified time period for the development of the outcome under investigation. However, in a cohort study participants may be lost during follow-up. For example, some participants may: Develop the outcome under investigation Refuse to continue to participate in the study Migrate Die Enter the study some time after it starts To account for these variations during follow up, a more precise measure can be calculated, the incidence rate. Incidence Risk: Incidence risk is the proportion of individuals in a population (initially free of disease) who develop the disease within a specified time. Incidence Rate: Incidence rate is the frequency of new cases of disease in a population. Introduction to Epidemiology, Notes 2024 Laura Benjamins, MD, MPH Incidence Risk Examples Two-Hundred (200) Wayne State Medical Students are followed from October, 2022 to March, 2023 to determine how many develop the Flu. No students had the Flu at the beginning of the study. During that time period, 50 students are diagnosed with Flu. The incidence risk of developing Flu during those six months = 50/200 = 0.25, or 25% Same study, but 50 students tested positive for Flu at the beginning of the study (meaning they had it before the study period). The incidence risk of developing Flu during those six months = 50/(200-50) = 50/150 = 0.33, or 33% Incidence Rate The denominator in an incidence rate is the sum of each individual's time at risk and is commonly expressed in person years at risk. The incidence rate is the rate of contracting the disease among those still at risk. When a study subject develops the disease, dies or leaves the study they are no longer at risk and will no longer contribute person-time units at risk. Introduction to Epidemiology, Notes 2024 Laura Benjamins, MD, MPH Incidence Rate Examples Person-time (years) at risk for 5 individuals in a hypothetical cohort study between 2000-2004. --- = time at risk, X = disease, L = person lost to follow up This Figure illustrates the calculation of person-time units (years) at risk of a hypothetical population of 5 individuals in a 5 year cohort study. In the above example the incidence rate for disease (X) is calculated as: 3/18 = 0.167 per person year or 16.7 per 100 person years. Note that for most rare diseases, risks and rates are numerically similar because the number at risk will approximately equal the total population at all times. Prevalence * The amount of disease at one particular point in time, or over a specified period of time. The proportion of people who have the disease. Prevalence % = Number of People with Disease x 100 % Number of People in the Population Point prevalence is the proportion of people with a particular disease at a particular timepoint and can be calculated as follows: Number of cases in the population at one time Total population at the same point in time Introduction to Epidemiology, Notes 2024 Laura Benjamins, MD, MPH Period prevalence is the proportion of people with a particular disease during a given time period. Prevalence is a useful measure of the burden of disease. Knowing about the prevalence of a specific disease can help us to understand the demands on health services to manage this disease. Prevalence changes when people with the condition are cured or die. Increased prevalence doesn’t necessarily mean a bigger problem. Higher prevalence could mean a prolonged survival without cure or an increase of new cases, or both. A lower prevalence could mean that more people are dying rather than being cured, a rapid recovery, and/or a low number of new cases. Prevalence vs. Incidence Prevalence differs from incidence proportion as prevalence includes all cases (new and pre- existing cases) in the population at the specified time whereas incidence is limited to new cases only. Prevalence and Incidence Examples Fifty people are followed for one month to see how many have or develop COVID. The prevalence of this disease is 8 per 50, or 0.16, or 16%. Introduction to Epidemiology, Notes 2024 Laura Benjamins, MD, MPH The incidence from July 1st to August 1st is 5 per 47, or 0.106, or 10.6%. Incidence & Prevalence Video Another Example (from: https://s4be.cochrane.org/blog/2020/11/06/prevalence-vs-incidence-what-is-the-difference/) A general practice surgery with a patient population of 40,000 people wanted to evaluate the epidemiology of COPD in its patients. The information they collected from their records is shown in the following table: Year Number of Patients with COPD Total number of patients at the practice 2018 1780 39,640 2019 1826 40,000 * For simplicity, we assume that there were no deaths or recovery of patients with COPD during 2018 and 2019, and all the patients remained in the practice. From this table we can say that: In 2018, the number of patients at the practice (total population) was 39,640. The number of people at that time with COPD was 1780. Therefore, the prevalence equals 1780/39640= 0.0449. This can be expressed as 4.5% of the patient population had COPD at that time. In 2019, the number of patients at the practice had increased to 40,000. The number of cases of COPD in 2019 had risen to 1826. The prevalence in 2019 therefore was 1826/40000= 0.0456 giving us 4.6% of the population. We can see the prevalence of COPD in this population only changed by approximately 0.1%. The number of new cases in 2019 compared to 2018 is 1826-1780, making the difference 46. Therefore, the number of new cases at the practice is 46 per year, which makes the incidence 46/40,000 =0.00115 (1.15 per 1000 population). (For simplicity this is assuming those 46 were all new patients with onset of COPD in 2019). It is useful to use these numbers in combination. As we can see from this example, the incidence of COPD tells us 46 patients at the practice are being newly diagnosed. If the number of patients at the surgery had stayed the same, you might be worried that they had all suddenly developed risk factors such as began smoking heavily causing so many to have the condition. However, the prevalence considers the fact that the number of people in the total population had increased as well, and the proportion of the population with COPD in 2018 vs 2019 only changed by 0.1%. As a GP you could be reassured by this that as the number of new cases was proportional to the number of new patients you were taking on. Introduction to Epidemiology, Notes 2024 Laura Benjamins, MD, MPH Factors that Effect Incidence & Prevalence Prevalence-Incidence Bias (https://first10em.com/ebm/prevalence-incidence-bias/) Prevalence-incidence bias is a type of selection bias. It is also known as “Neyman bias”. Prevalence-incidence bias occurs when individuals with severe or mild disease are excluded, resulting in an error in the estimated association between an exposure and an outcome. Ex: When studying cardiac arrest, if one only collects data on arrival to the emergency department, you would miss all the patients who were declared dead on scene, who may be systematically different from those who make it to hospital. Ex: If you were studying risk factors for myocardial infarction among patients admitted to a cardiac ward, you could get a skewed result if you failed to include healthier patients (perhaps those who has “silent MIs”) or sicker patients, such as those who have already died from a cardiac arrest.