Epidemiology Flashcards
The study of the distribution, determinants of health problems or disease.
Epidemiology
Uses of Epidemiology
- for surveillance of incidence, frequency and distribution of disease.
- to study the progression of disease
To study the progression of disease:
- stuying risk factors
- for planning, and implementing an intervention to prevent or reduce risk or illness
Some leading cause of death worldwide
- Heart disease
- Neoplasms
- Cerebrovascular Disease
- Chronic Pulmonary Disease
- Accidents/Injuries
- Diabetis Mellitus
- Influenza and pneumonia
- Alzheimer’s Disease
- Nephritis
- Septicemia
The number of people whom something happened (i.e. They got sick, died, etc.)
Numerator
Total observed population or population at risk for the event
Denominator
Disease or condition that affects a greater than expected number of individuals within a population, community, or region at the same time.
Epidemic
Normal occurence of disease in a population
Endemic
- Geographically widespread
- An epidemic that occurs in more than one continent
Pandemic
A graphic demonstration of the relationship between the agent, hosts, environment, and time.
Epidemiologic Triangle
- Infectious (microbes-bacteria, viruses)
- noninfectious (smoking, high bp, exposure to chemical or radiation)
- an epidemiologist determines the primary agent, mode of transmission, geographic patterns.
Agent
-Organisms (humans, animals) that may harbor a disease.
Hosts
Factors that may affect the susceptibility of hosts:
- age
- gender
- race/ethnicity
- occupation
- immune status
- behavior
Favorable conditions external to the host that allow the disease to be transmitted
Environment
Examples of environment in epidemiologic triangle:
- Population density
- geography
- season of the year
- genetic effects/family history
Duration of the illness or sickness till death or recovery occurs
Time
Time between infection and appearance of symptoms occur
Incubation Period
Time between exposure and appearance of symptoms in chronic diseases
Latency Period
Mission of Epidemilogy
Break the triangle to prevent disease completely or control the spread of disease
- understand what causes the disease
- determine the groups that are likely to get the disease
- determine the geographical factors that are conductive to the spread pf disease
- address not just disease but mortality, hospitalization, disability, quality of life and health status
Understanding the disease by studying its pattern from the perspective of person, place and time.
Descriptive Epidemiology
The outcome
Dependent variable
Risk factors/ exposures
Independent variable
The study population and examples
Person
- age, gender, ethnicity, genetic predisposition
- concurrent diease, diet, exercise, smoking
- SES, education, occupation
The geographical location and examples
Place
- school, worksite
- presence or agents or vectors
- climate, geology
- population density and economic development
- nutritional and medical practices
Notion of time and examples
Time
- seosonal patterns, temporal trends over time
- calendar time, time since an event
- physiologic cycles and age (time since birth)
Total no. of cases
Prevalence
Number of new cases
Incidence
Number of deaths
Mortality
Types of Prevalence
- point prevalence
- period prevalence
- prevalence proportion
No. of cases at a single point in time (e.g. November 21)
Point prevalence
Point prevalence formula
No. of cases (point in time)
P= ————————————
Total observed population
x 100,000
No. of existing cases during a period of time (year 2019)
Period prevalence
Period prevalence formula
No. of cases (period of time)
P= ————————————
Total observed population
x 100,000
Prevalence Proportion formula
No. of cases
P= ————————————
Total observed population
x 100,000
Cumulative Incidence fomula
CI =
No. of new cases (period of time)
—————————— x 100,000
No. of population at risk
Incidence Rate or Incidence Density formula
IR =
No. of new cases —————————— x 100,000 Total no. of person-time at risk
Prevalence and incident rate can be expressed as:
- crude
- specific
- adjusted
Rate from the entire population under observation
Crude rate (Raw rate)
CI expressed as crude rate formula
No. of new cases of disease (period of time)
————————————————————
No. of population at risk
The specific subset of the population being observed is the focus
Specific rate
Under specific rate, the numerator and the denominator are both subsets of the population according to:
- age
- gender
- occupation
- race
- cause specific
- age-gender
A rate that is mathematically transformed to provide a summary rate for an observed population after a specified characteristic is removed.
-the resulting rate is the estimated value.
Adjusted rate (standardized rate)
Distinguishing characteristics of incidence and prevalence
- Measure
- Type of number
- Units
- Range
- Numerator
- Denominator
- Major use
Characteristics of Cumulative Incidence
- type of no.: proportion
- units: none
- range: 0 to 1
- numerator: new cases
- denominator: population at risk
- major use: research on causes prevention and treatment of disease
Characteristics of Incidence rate
- type of no.: true rate
- units: 1/time/t^-1
- range: 0 to infinity
- numerator: new cases
- denominator: person-time at risk
- major use: research on causes prevention and treatment of disease
Characteristics of prevalence
- type of no.: proportion
- units: none
- range: 0 to 1
- numerator: existing cases
- denominator: total population
- major use: resource planning
- Anything that brings about an effect or result.
- An event, condition or characteristic which plays an important role in producing the diease.
Cause
- An association between exposure and outcome.
- An alteration in the exposure in terms of frequency and quality if follwed by a change in the outcome.
Causal Association
A factor that causes the problem without any intermediate step
Direct cause
A factor that may cause the problem but with an intermediate factor or step
Indirect cause
Attributes of a cause:
- association
- time order
- direction
A casual factor (x) must occur together witn the outcome (y);
There is a statisticsl dependece.
Association
The cause must precede the outcome.
Time order
There should be a liner relationship between the cause and effect
Direction
Casuality of infectious diseases
Koch’s Postulates
4 causal relationships under koch’s postulates
- An organism can be isolated from a host with the disease.
- The organism can be cultured in the laboratory.
- The organism causes the same disease when introduced to another host
- The organism can be re-isolated from that host.
Bradford Hill Criteria of Assesing Causality
- Strength of Association
- Consistency of Association
- Specificity of Association
- Temporality
- Biological Gradient
- Plausibility
- Coherence
- Experimental Evidence
- Analogy
More likely to be causal than weak associations
Strength of Association
The repeatability of observation of an association in different population
Consistency of association
The causal factor leads to a single effect and not multiple effect
Speicificity of Association
The cause precedes the effect in time.
Temporality
Increasing amount of exposure increases at risk
Biological Gradient
The findings agree with currently accepted understanding of pathological processes
Plausibility
A cause and effect interpretation do not conflict with the natural history and biology of the disease.
Coherence
The condition can be altered by an appropriate experimental regimen
Experimental evidence
Provides a source of more elaborate hypothesis about the associations under the study
Analogy
A type of study that has strong ability to prove causation
Randomized controlled trials
2 types of studies that has moderate ability to prove causation
- Cohort studies
- Case-control studies
3 types of studies that has weak ability to prove causation
- cross-sectional studies
- ecologic studies
- case series and reports
How do epidemilogists identify “cause” of disease?
- Generating and testing hypothesis.
2. Casual inference
Under casual inference, how do we determine of the observed value is valid or true?
By eliminating:
- bias
- confounders
- random error
Types of Bias
- Selection bias
- Information bias
Error that arises in the process of identifying and choosing rhe study populations.
Selection Bias
Misclassifications bias due to recall bias and interviewer bias.
Information Bias
Refers to the mixing of effects of the exposure with that of a third factor
Confounding
- A cause that must be present for the disease to occur.
- The disease never develops without the factor.
- All caded of the disease are exposed to the factor.
Necessary Cause
- A set of factors or causes that inevitably results in the disease.
- the disease always develops in the presence of a factor.
- complete casual mechanism that inecitably produces diseases.
Sufficient Cause
- When present, it can increase the likelihood of developing the disease compared to when it is absent.
- not necessarily a causal factor
- if modifiable by intervention may reducy the probability of occurence of disease
Risk Factor
