Lec 1 TB Flashcards
1
Q
- Public health
- Medicine vs PH
- Best definition for epidemiology
- Disease
A
- Public Health: promote health of the population
- Medicine vs PH
- Medicine: treating illness in individuals
- Public health: prevent illness in the community
- Epi = on or upon
- Demos = the common ppl
- Logy = study
- Epidemiology: the study of that which falls upon the common ppl
- Epidemiology is the study of the distribution** and **determinants** of disease frequency in human populations and the **application of this study to control health problems.
- Disease refers to a broad array of health-related states and events, including diseases, injuries, disabilities, and death.
- Main goals of public health: disease prevention and health promotion
- Focuses on populations and communities rather than on separate indiv
- Epi: a basic science in public health, the study of the distribution and determinants of disease freq in human populations and the application of this study to control health problems
2
Q
5 objectives of epi
A
- The objectives of epidemiology are:
- # 1: study the natural course of disease from onset to resolution
- # 2: determine the extent of disease in a population
- # 3: identify patterns and trends in disease occurrence
- # 4: identify the causes of disease
- # 5: evaluate the effectiveness of measures that prevent and treat disease
3
Q
- 5 key words in eqpi
- Population
- Census
- Disease freq
- 3 steps to quantify disease freq
- Name
- Purpose
- x
- disease distribution
- x
- disease determinants
- indiv determinants
- env, soc determinants
- x
- Disease control
- 2 ways to control
A
- There 5 key words in this definition of epidemiology
- # 1: population
- # 2: disease frequency
- # 3: disease distribution
- # 4: disease determinants
- # 5: disease control
- Population: a group of ppl w/ a common characteristic (eg place of residence, gender, age, use of certain medical services)
- Eg. Ppl who reside in the city of Boston
- Population: a group of ppl w/ a common characteristic (eg place of residence, gender, age, use of certain medical services)
- Census: complete count of the population
- Sources of data - decennial census (feds attempt to count every person in the US for every 10 yrs) to computerized records from medical facilities that provide counts of patients who use the facilities
- Disease frequency
- Refers to quantifying how often a disease arises in a population
- 3 steps:
- # 1: developing a definition of disease
- # 2: instituting a mechanism for counting cases of disease w/in a specified population
- # 3: determine the size of that population
- the definition
- determine accurately who should be counted
- Disease definitions are based on a combination of physical and pathological examinations, diagnostic test results, and signs and symptoms
- Ex. a case definition of breast cancer
- Findings of a palpable lump during physical exam and mammographic and pathological evidence of malignant disease
- Disease distribution
- Refers to the analysis of disease patterns according to the characteristics of person, place, and time
- IOW: who is getting the disease, where it is occurring, and how it is changing over time
- Disease determinants (things that changes a person’s health)
- Factors that bring about change in a person’s health or make a difference in a person’s health
- IOW: consists of both causal and preventative factors
- Determinants include indiv, env, and societal characteristics
- Indiv determinants consists of a person’s genetic makeup, gender, age, immunity level, diet, behaviors, and existing diseases
- Ex. risk of breast cancer is increased among women who have genetic alterations (BRCA1, BRCA2), are elderly, give birth at a late age, have a history of certain benign breast conditions, or history of radiation exposed to the chest
- Env and societal determinants
- Are external to the indiv, includes a wide range of natural, social, and economic events and conditions
- Eg. Presence of infectious agents, reservoirs in which organisms multiply, vectors that transport the agent, poor and crowded housing conditions, political instability
- These cause many communicable diseases around the world
- Disease control
- Epidemiologists accomplish disease control via epidemiological rs and via surveillance
- purpose of surveillance: monitor aspects of disease occurrence that are pertinient to effective control
- Eg. CDC collects info on the occurrence of HIV infections across the USA
- For every case of HIV infection, the surveillance system gathers data on the indiv’s demo characteristics, transmission category (injection drug, male to male sexual contact) and diagnosis date
- The surveillance data are essential to formulate and evaluate programs to reduce the spread of HIV
4
Q
- 3 ways to define subspeciality
- Disease specific subspecialities
- Exposure-specific subspecialities
- Population-specific subspecialties
- x
- 3 ways epi rs expanded
A
Modern epidemiology
- Subspecialities have been established that are defined by
- # 1: disease
- # 2: exposure
- # 3: population being studied
- Disease specific subspecialities: reproductive, cancer, CV, infectious disease, and psychiatric epidemiology
- Exposure-specific subspecialities: environmental, behavioral, nutritional epidemiology, pharmacoepidemiology
- Population-specific subspecialties: pediatric, and geriatric epidemiology
- X
- The scope of epi rs expanded in several directions
- # 1: examine health determinants at the genetic and molecular lv
- Eg: human genome epidemiology uses epi methods to assess the impact of human genetic variation on disease occurrence
- It helps discover genes that causes disease and the use of genetic testing to diagnose, predict, treat, and prevent disease
- Molecular epidemiology:
- Use biological markers to improve the measurement of exposures, disease susceptibility, and health outcomes
- Eg: biomarkers like serum micronutrient lv can determine a person’s fruit and verify intake more accurately than personal interviews
- # 2: study the determinants at the societal lv
- Social epidemiology: study of exposures and disease susceptibility and resistance at diverse lv (eg indiv, household, neighbor, region)
- Eg: social epidemiologists investigate how neighbourhoods, racial discrimination and poverty influence a person’s health
- # 3: analysis of determinants across the life span
- Life course epidemiology: study of lasting effects of exposures during gestation, childhood, adol, and young adulthood on disease risk in later adult life
- # 1: examine health determinants at the genetic and molecular lv
5
Q
Ch 2
- Population
- 2 types of residence
- population in epi
- Catchment pop
- 3 types of hospital catchment areas
*
A
- Population: a group of ppl w/ a common characteristic
- Eg place of residence, religion, gender, age, use of hospital service, life event (eg giving birth)
- 2 definitions of residence
- # 1: Location of residence: country, state, city, neighborhood
- # 2: Residence near natural geographic features (eg rivers, lakes, islands) can be used to define a population
- Eg ppl who live along the Mississippi river, Lake ON, etc
- 2 definitions of residence
- Eg place of residence, religion, gender, age, use of hospital service, life event (eg giving birth)
- Population in epi: Epidemiology focuses on disease occurrence, so pop are defined in relation to a medical facility (eg medical professional’s office, clinic, hospital)
- Catchment population: service population of a medical facility, consists of ppl who use the facility’s services
- This population is difficult to define as an individuals’ decision to use a facility may depend on how far it is from home, their medical condition, type of medical insurance, etc
Summary of 3 types of hospital catchment areas
- # 1: Single county hospital w/ local catchment population: all county residents use this hospital
- # 2: county hospital specialty clinic w/ broad catchment population
- Speciality clinic: residents from local and surrounding counties
- Other services: Residents from local county only
- # 3: public and private hospitals whose catchment populations vary by SES
- Public: poor ppl
- Private: middle class and wealthy ppl
6
Q
Ways to define pop (cont)
- Life event
- Fixed population
- Dynamic/open population
- steady state
- Population subgroup
A
Other way a pop can be defined:
- occurrence of a life event (eg undergo a medical procedures, giving birth to a child, entering/graduating from school, serve military)
- Eg “class of 19” those who graduated in 2019, Iraq War veterans: those who serviced in the US military during the war in Iraq
- Permanent vs transient membership
- Fixed population: a pop whose membership is permanent; it is defined by a life event
- Eg: ppl who were in Hiroshima Japan when the atomic bomb exploded to end WWII
- This population is fixed, will never gain new members b/c only ppl who were at this historical event can be members
- Dynamic/open population: changeable state or condition, it is transient
- The person is a member of a dynamic population only as long as he/she has the defining state/condition
- Eg: the pop of city of Boston is dynamic b/c ppl are members only while they reside w/in the city limits
- Eg: Turnover is always occurring, ppl enter by moving in or by birth; and leave by moving away or death
- Eg: Dynamic populations include gps defined by geographic and hospital catchment areas, religious gps, occupations
- Steady state: a situation in which the # of ppl entering the population = number leaving
- Fixed population: a pop whose membership is permanent; it is defined by a life event
- A population can be divided into subgps based on any characteristic
- Eg men who went through bypass surgery (gender subgroup of fixed population, defined by a life event)
- Eg 6+ yo children who live along the Mississippi River (age subgp of dynamic population, defined by geographic formation)
7
Q
Ch 2
- 3 factors used to determine how common a disease happens
- x
- disease definition
- 3 basis
- How does it change?
A
Measuring disease occurrence
- Epidemiologists need to consider 3 factors when they measure how commonly a disease occurs in a gp of ppl
- # 1: # of ppl who are affected by the disease
- # 2: size of the population from which the cases of disease arise
- # 3: the length of time that the population is followed
- If we don’t consider these components, we get a false impression on the effect of the disease on a population
- Main point: to compare gps, they should have the same population size and time period
- Disease definition is based on physical and pathological exams, diagnostic tests, and signs and symptoms
- Disease definition evolves as we learn more about it
- Eg official case definition of HIV/AIDS expanded when its cause was discovered and improvement in detection were made
8
Q
- 3 types of calculations to describe/compare disease occurrence
- Define ratio
- Define proportion
- Define rate
A
- 3 types of calculations are used to describe and compare measures of disease occurrence: ratios, proportions, and rates
- # 1: Ratio: divide 2 unrelated numbers
- # 2: Proportion: division of 2 RELATED numbers; numerator is a subset of denominator
- Aka fractions
- Eg: prop of US residents who are black = # of black residents/ total # of US residents of all races (i.e. 14.1%)
- # 3: Rate: division of 2 numbers; TIME is always in the denominator
- Eg measures of disease from prev Counties A and B are rates
- 200 cases/100k/yr; 500 cases/100k/yr
- Rate is incorrectly used to describe ratios and proportions (be careful)
- Eg measures of disease from prev Counties A and B are rates
9
Q
- 2 basic measures of disease frequency
- Define incidence
- Define prevalence
- x
- Why is time is included in incidence?
- 2 types of incidence measure
- x
- Cumulative incidence: N, D
- aka
- relationship b/w cumulative incidence and time
- used in fixed or dynamic pop?
- x
- Incidence date: N,D
- Incidence rate = infinity
- Person-time
- When does it stop?
A
Measures of disease freq
- 2 basic measures of disease frequency: incidence and prevalence
- Incidence: measures the occurrence of NEW disease in a population in a specific time period
- Prevalence: measures the existence of current disease (during and new onces)
- x
- Incidence
- Why is time is included in incidence?
- incidence takes into account the specific amount of time the members of the population are followed until they dev the disease
- Since incidence measures a person’s transition from a healthy yo a diseased state, time must pass for this to happen
- incidence takes into account the specific amount of time the members of the population are followed until they dev the disease
2 types of incidence measures: cumulative incidence, incidence rate
-
Cumulative incidence
- N: # of new cases of disease
- D: pop AT RISK (over time)
- Cumulative incidence is dimensionless
- aka avg risk of getting a disease over a certain period of time
- Cumulative incidence is influenced by the length of time
- IOW: cumulative incidence over a long period of time (eg a lifetime) will be higher than that over a few yrs
- Cumulative incidence is mainly used in fixed pop, where there are no or small losses to follow up
- Eg 255k residents of Japan present on the day the bomb dropped
-
Incidence rate:
- # of new cases/ person-time
- Incidence rate of infinity: all members of a population die instantaneously
-
Person-time: the time only while the candidate is being followed
- It stops when the person dies or is lost to follow up (moves away)
- Incidence rate can be calculated for fixed or dynamic population; esp dynamic as it considers pop changes
- Eg in a town (study: 2006-2016)
- Person A: moved in town in 2007, diagnosed in 2011 -> 4 yrs of person-time
- Person B: was observed in 2006, died in 2012 -> 6 yrs of person-time
- Incidence rate in this hypothetical population is 1/10 person-years
- # of new cases/ person-time
10
Q
- 2 ways to convert incidence rate to cumulative incidence
A
- Relationship b/w cumulative incidence and incidence rate
- Situation 1: fixed population w/ constant incidence rate, small cumulative incidence (less than 10%)
- Math relationship: CI = IRi x ti
- CI: cumulative incidence
- IRi: incidence rate
- Ti: specified period of time
- Situation 2: incidence rate is NOT constant, need to take into account the different rates that prevail during each time period
- CI = ∑(IRi x ti)
- Eg mortality rate (a typical incidence rate) among Hiroshima residence was higher shortly after the atomic bomb explosion than subsequent yrs
11
Q
- Prevalence
- 2 types of prevalence
- Pt prev formula
- Period prev formula
- x
- Prevalence and incidence relationship
- Common illness
- Rare illness
- x
- use:
- cumulative incidence/ incidence rate
- prevalence
A
- Prevalence: # of EXISTING disease/ pop
- 2 types of prevalence measures
- Point prevalence
- Period prevalence
- Point prevalence: existing cases/ entire pop at a single point in time
- Eg July 1, 2017
- Period prevalence: existing cases/entire total # pop at a period of time
- Eg year 2017
- X
Relationship b/w prevalence and incidence
- Prevalence depends on the rate at which new cases of disease dev (incidence rate) and the duration that indiv have the disease
- P = Incidence rate x duration
- P/(1 - P) = IR x D
- P = prevalence (proportion of total pop w/ disease)
- (1 – P) = proportion of the total population w/o the disease
- IR = incidence rate
- D = average duration (length of time) the person has the disease
- This eqn assumes the pop is in steady state (inflow = outflow)
- P = Incidence rate x duration
- If the freq of disease is rare (less than 10%)
- We use this equation: P = IR x D
- X
Professional Uses of incidence and prevalence:
- Cumulative incidence: rs on causes, prevention, and treatment of disease
- Incidence rate: rs on causes, prevention, and treatment of disease; effectiveness of treatment programs
- Prevalence: resource planning
12
Q
measures of disease freq
- age-specific mortality rate
- years of potential life lost
- livebirth rate
- N,D
- define livebirth
- birth defect rate
- Attack rate
- mainly applies to what type of disease
- case fatality rate
- survival rate
A
Commonly used measures of disease freq in public health
- Age-specific mortality rate: total # of deaths from all causes among indiv in a specific age category per 100k/year in the age category
- Years of potential life lost: the number of years of potential life not lived when a person dies “prematurely”
- Eg 2015, 957 yrs were lost from heart disease; 1283 yrs lost from cancer, 1172 yrs lost from unintentional injuries b4 age 75 per 100k population younger than 75 yo
- Livebirth rate:
- N: total # of livebirths
- D: only women of childbearing age
- N/D x per 1k population per year
- Livebirth: pregnancy that results in a child who, after separation, breathes or shows any other evidence of life
- Eg: 2015, crude livebirth rate among US women: 12.4/1k/yr
- Birth defect rate ir congenital anomaly or malformation rate: # of children born w/ defects per 10k births
- Numerator and denominator include both livebirths and stillbirths
- Eg 2016-17, prevalence of brain malformations was 5% among women w/ possible Zika virus infection
- Attack rate: # of new cases of disease that dev (during a defined and short time period) per the # in a healthy population at risk at the start of the period
- a type of cumulative incidence measure
- reserved for infectious disease outbreaks
- Eg 24-hr attack rate for food poisoning was 50% among ppl who are chicken salad at the banquet
- Case fatality rate: # of deaths per # of cases of disease
- a type of cumulative incidence
- Eg 2014 in Congo, the 5-month case fatality rate among indiv w/ Ebola virus = 74.2%
- Survival rate: # of living cases per # of cases of disease
- Rate is the complement of the case fatality rate and is a cumulative incidence measure
- 5-year relative survival rates for cancer compare ppl w/ a particular cancer to similar ppl in the general pop
- Eg 2007-2013, 5-year relative survival rates for prostate cancer were 100% among en diagnosed while the tumor was still confined to the prostate or had spread only to regional lymph nodes
- 30% among men w/ tumors metastasized to distant sites
13
Q
Ch 3
- Descriptive stats
- 7 Person characteristic associated w/ variation in disease occurrence
- 2 aspects increase age increase disease
- 4 aspects explain sex difference in disease
- 4 ways religious affiliation can influence disease rates
- x
- Place can refer 5 aspects
- Explain Malaria
- x
- Time
- LT trends
- ST trends
- 2 types
A
Person characteristic associated w/ variation in disease occurrence
- descriptive stats: person, time, place
- 7 Personal characteristics: age, gender, race/ethnic gp, SES, occupation, religion, marital status
- Age
- The freq of most diseases increases w/ age
- Why: age reflects both the aging process and the person’s experiences
- Experiences include accumulation of harmful exposures, and protective factors
- Eg: the prevalence of habits** (eg OH consumption) increases w/ age (like 12 to 34 yo) as does **prevalence of protective characteristics (immunity)
- The freq of most diseases increases w/ age
- Sex
- Certain diseases are more common among men and others more common among women
- Eg Breast cancer: 1% occur among men; 99% occur among women
- Eg HIV: 19% occur among women
- Reasons for variations in disease rates b/w sexes include differences in
- # 1: hormone lv (eg female hormones may protect women against heart disease)
- # 2: habits like use of tobacco OH, drugs are more common among men
- # 3: sexual practices (eg anal sex, a risk factor for HIV transmission, is most commonly practiced among men having sex w/ men)
- # 4: occupational exposures (eg men are more likely to hold jobs that involve exposure to toxins)
- Race and ethnicity
- Racial health disparities stem from complex histories of racial discrimination and dispossession, differences in SES, health practices, psychosocial stress and resources, env exposures, and access to healthcare
- Since many of these factors are correlated, it is challenging to tease apart their contributions
- SES
- Common measures: educational lv, income, occupation
- Eg sinking of Titanic is an example of health disparities b/w poor and wealthy
- Death rates among passengers of low SES were 2x as high as those among passengers of high SES b/c the small supply of life jackets are mainly given to the wealthy women and children
- Today, large disparities for all measures of health exist b/w ppl from low and high SES
- Eg life expectancy is strongly related to income lv
- At age 40, the gap in life expectancy b/w indiv in the top and bottom 1% of the income distribution (in US) is 15 yrs for men, 10 yrs for women
- Religious affiliation: influences disease rates
- Represents a mixture of factors (eg genetic, env, cultural, and behavioral)
- Eg Tay-Sachs disease, degenerative disease of the brain and NS is associated w/ a genetic mutation that is present mainly among Jews of East Europe decent
- Eg: 3% fewer cases of cancer among male Mormons, and 8% fewer cases among female Mormons is due to their prohibition against smoking and alcohol consumption, and diff sexual and reproductive patterns
- Occupation influences disease patterns
- Reason – potent and sustained exposures to harmful substances can occur in jobs
- Ppl in jobs (eg Aluminum production, boot and shoe manufacturing, coal gasification, furniture making, iron and steel founding, rubber manufacturing, nickel refining) -> higher rates of cancer
- Marital status
- Marital status influence patterns of disease and death
- Eg death rates are higher among ppl who are unmarried than those married and living w/ spouses
- Increased rates of death are greatest among those who never married, esp never-married men
- Psychological and economic support associated w/ marriage exerts a protective effect against certain adverse health events, esp for men
- It is also possible that the characteristics that led a person to marry may be responsible for this protection
Place
- It includes
- Geopolitical units (eg countries or states)
- Natural geographic features (eg mountains or rivers)
- Characteristic of place
- Physical env (eg climate, water and air)
- Biological env (eg flora, fauna)
- Social env (eg cultural traditions)
- Eg: malaria happens in areas where
- Physical condition for the development and survival of mosquito: favorable temperature (20 to 30 dC)
- Adequate humidity
- Moderate rainfall
- Presence of standing or gently flowing water
- Biological factors that benefit the mosquito: plants that collect small pools of water
- Social factors: proximity of homes to mosquito breeding sites, housing construction that help mosquito entry, certain occupations that increase a person’s exposure to mosquitoes (eg outdoor work at night)
- Physical condition for the development and survival of mosquito: favorable temperature (20 to 30 dC)
Time
- LT trends
- Eg: age adjusted death rate from Alz disease has increased 25% among women from 2005-2015
- Eg Dramatic decline in deaths from stroke
- ST trends: 2 types
- # 1: infectious disease
- Eg Legionnaires’ disease at a Philadelphia convention occurred over 1-mo
- # 2: non-infectious diseases that follow climatic changes (eg heat waves, hurricanes, pollution episodes)
- Eg 4-day smog disaster is associated w/ an increase in CV and respiratory deaths, esp among elderly
14
Q
- disease cluster
- 3 types of cluster
- x
- disease cluster vs disease outbreak
- How to determine if an outbreak/epidemic is happening?
- disease outbreak
- outbreak vs epidemic
- How to detect disease outbreaks early?
A
Disease clusters and epidemics
Disease clusters in place and time
- Disease cluster: a greater and unexpected aggregation (a bunch) of uncommon events/disease happening in a specific space/time
- Hallmark of a cluster: occurrence of cases of disease close together in space (spatial clustering), time (temporal clustering), or both space and time (spatio-temporal clustering)
- Eg: historical disease cluster of “11 blue men”
- 11 ppl were found ill or unconscious in NYC neighborhood in a single day with blue skin
- Investigating epidemiologist identified the condition as Resulted from ingesting sodium nitrite
- It is rare that 11 cases happened by chance
- Follow-up investigation: local café where all the men eaten mistakenly put sodium nitrite instead of NaCl in salt shakers
- disease cluster vs disease outbreak: cluster (suspected); outbreak (strong association)
Outbreaks and epidemics
- How to determine if an outbreak/epidemic is happening: Analyse disease occurrence by person, place, and time
- Disease outbreak: occurrence of cases of disease in excess of what would normally be expected in a given area or among specific gp of ppl
- Outbreaks are synonymous w/ epidemics
- Outbreaks: describes localized ones
- Epidemics: describe widespread ones
- x
- How to detect disease outbreaks early?
- Internet surveillance helped contribute to the early identification of disease outbreaks (eg searches of global media sources, news wires)
- Eg Health Canada’s Global Public Health Intelligence Network: identified the outbreak of severe acute respiratory syndrome (SARS) in Guangdong China 2 mo b4 the WHO released details
15
Q
- 8 steps in disease outbreak investigation
- x
- 3 characteristics of case definition
- 2-steps in case confirmation
- x
- Step 4: descriptive epi
- epi curve: x anf y axis
- Pt source outbreak
- cont common source outbreak
- Populated outbreak
- x
- Purpose of env or lab investigation
A
-
General approach to conduct an outbreak investigation
- After initial recognition of an outbreak, a thorough investigation includes
- # 1: formulating case definitions
- # 2: conduct case confirmation
- # 3: establish the background rate of disease and finding cases
- # 4: examining the descriptive epidemiology of the outbreak cases
- # 5: generating and testing hypotheses about the causes of the outbreak
- # 6: collecting and testing env samples
- # 7: implementing control measures
- # 8: interacting w/ the press and public to disseminate info
-
#1 & 2: Case definition and confirmation
- Case definition: needs to be
- simple,
- good enough to identify enough cases to investigate, and
- has strict enough exclusion criteria to avoid including cases of unrelated illness as outbreak-related cases
- Eg: WHO uses the following criteria to define a case of measles
- Clinically confirmed case is
- # 1: any person w/ fever and a nonvesicular rash, and either a cough, runny nose, or conjunctivitis or
- # 2: any person in whom the clinician suspects measles b/c of his/her exposure history (eg the person was in close contact of a confirmed measles case)
- Lab confirmed case: a person w/ a +ve blood test for measles specific Ab
- Clinically confirmed case is
- In many outbreaks, case confirmation is needed given certain clinical findings may be from lab error
- Case confirmation includes
- Detailed medical record review
- Discussion w/ healthcare providers, esp when a new disease appears to be emerging
- Case definition: needs to be
-
#3: Finding all cases and determine background rate:
- Finding all cases in a given population (based on case definition) over a specific time period b4 the outbreak began and using these cases to establish background rate
-
#4: descriptive epidemiology
- Investigators can plot and epidemic curve,
- X-axis: data or time of illness onset among cases
- Y-axis: # of cases
- Helps determine type of outbreak (3 types)
- # 1: Point source outbreak: persons are exposed over a brief time to the same source (eg single meal of an event)
- # of cases rises rapidly to a peak and falls gradually
- Most cases occur w/in 1 incubation period (the time interval b/w infection and clinical onset of the disease)
- # 2: Continuous common source outbreak: persons are exposed to the same source but the exposure it prolonged over a period of days, weeks, or longer
- The epidemic curve rises gradually and may plateau
- It eventually falls out when the exposure ends
- # 3: Propagated outbreak: there is no common source b/c the outbreak spread from person to person
- The epidemic graph will cycle through progressively taller peaks that are often one incubation period apart
- # 1: Point source outbreak: persons are exposed over a brief time to the same source (eg single meal of an event)
- Investigators can plot and epidemic curve,
- #5: Generating and testing hypotheses
-
#6: env or lab investigation:
- env and lab test confirm the source of an outbreak
-
#7: control measures
- implement control and prevention measures to minimize further disease
- Eg: product recall or processing plant shutdown after a foodborne outbreak targets the source of illness
- Eg: COVID 19 vaccines
- need to use epi investigation results to inform control measures; but investigation takes time
- Can’t implement control measures to early (eg damage business; too much quarantine)
- IOW: need to balance timely intervention and deferring action until we have accurate info of the disease
- implement control and prevention measures to minimize further disease
- #8: Dissemination of info
23
Q
- 3 main tasks epidemiologists do
- the epi approach: 5 steps
- x
- define case definition
- 2 reasons to develop case definition
- Why are some case definitions tailored?
- Clinical criteria in case definitions
- 3 aspects needed in Case definitions for outbreaks
- Why do we modify case definitions
- x
- 2 types of variation in case definitions
- Pro and Con
A
The epidemiologic approach
- We count, divide and compare
- Count cases or health events and describe them in terms of time place and person
- Divide the # of cases by an appropriate denominator to calculate rates
- Compare these rates over time or for diff gps of ppl
- X
- # 1: decide what a case it, dev case definition
- # 2: use case definition to find and collect info on case-patients
- # 3: epidemiologist perform descriptive epidemiology by characterizing the cases collectively according to time, place, and person
- Disease rate: # of cases/ size of population
- # 4: determine if this rate is greater than what one will expect; and identify factors contributing to this increase
- Then compare the rate from this population to the rate to a comparison gp using analytic epi
- # 5: report results and rec PH action
- Defining a case
- Case definition: set of standard criteria to classify if a person has a particular disease, syndrome or other health condition
- Case definitions ease case is equivalent and can be compared
- Some case definitions are tailored to the local situation (eg case definition for virus outbreak may need lab confirmation; if there’s not labs, no confirmation)
- x
- Components of a case definition for outbreak investigations
- Case definition has clinical criteria, and may have limitations on time, place and person
- Clinical criteria include confirmatory lab tests, symptoms (subjective complaints), signs (objective physical findings) and other
- Case definitions used in outbreak investigations are likely to specific limits on time, place, and person than those used for surveillance
- x
- Modifying case definitions: Case definitions can change over time as more info is obtained
- Eg SARS
- First case definition: based on clinical symptoms and either contact w/ a case or travel to an area w/ SARS transmission
- Next case definition: novel coronavirus was the causative agent; case definition included lab criteria for evidence of infections w/ SARS associated coronavirus
- x
- Variation in case definitions
- Case definitions may vary based on the purpose for classifying the occurrence of a disease
- 2 types of case definitions
- Sensitive case definition: a broad or loose definition
- Pro: includes most or all of the true cases
- Con: include other illnesses as well
- Specific/strict case definition:
- Pro: certain that any person included in the study really had the disease
- Con: requirement that everyone w/ symptoms has to be tested, and underestimates the total # of cases if ppl are not tested
25
Q
- 3 ways to measure risk
- x
- measure of central location freq
- x
- Ratio calculation
- Descriptive method
- Analytic method
- Death-to-case ratio
- aka
- x
- Common types of ratio
A
Measures of risk: summarized by freq measures like ratios, proportions, and rates
- Objectives: Ratio, proportion, incidence proportion (attack rate), incidence rate, prevalence, mortality rate
Frequency measures
- Measure of central location: a value that summarize an entire distribution of data
- Freq: measure that characterize a part of the distribution
- Compares one part of the distribution to another part of the distribution or the entire distribution
-
Ratio
- Definition of ratio: divide 2 unrelated things
- Result is written as “:1”
- Used in descriptive and analytic epi
- Descriptive: M to F ratio in a study, controls to cases
- Analytic tool: ratios are calculated for occurrence of illness, injury or death b/w 2 gps
- Eg: risk ratio (relative risk), rate ratio, odds ratio
- x
- Commonly used epi ratio: death-to-case ratio
- Death-to-case ratio: # of deaths caused by a disease during a time period / # of new cases of the disease in the same time period
- IOW: measures the severity of illness
- Eg: TB: 802 deaths, 15k new cases -> 1 death per 18.8 new cases or 5.3 deaths per 100 new cases
- NOTE: this is a ratio b/c, not propr
- Many in the 802 deaths got TB earler (beyond the time period 2002), and do no belong to the 15k cases in the denominator
- Definition of ratio: divide 2 unrelated things
- x
- Types of ratio
- Common epi measures as ratio, proportion or rate
- Ratio:
- Risk ratio or relative risk
- Rate ratio
- Odds ratio
- Period prevalence
- Death-to-case ratio
- Ratio:
26
Q
- proportion define
- How to convert prop to ratio (scenario)
- numerator = # of women who went to a clinic (179)
- Denominator = all clinic attendees (341)
- Proportion: 179/341 = 52%
- Proportionate mortality
- x
- Type of proportion
A
-
Proportion
- divide 2 related events (N = subset of D)
- Properties and uses of proportions
- used as Descriptive measures
- Eg participation rate
- Eg: prop of children vaccinated for measles
- Eg: sick ppl on ship
- Proportions can be converted into ratios & vv
- Eg
- numerator = # of women who went to a clinic (179)
- Denominator = all clinic attendees (341)
- Proportion: 179/341 = 52%
- Ratio:
- Denominator – numerator = # of patients who are not women = 162
- 179/162 = 1.1 to 1 F-to-M ratio
- used as Descriptive measures
- Specific type of epi proportion: proportionate mortality
- Proportionate mortality: proportion of deaths in a specified population during a time period that are attributed to different causes
- Each cause: x%/total deaths
- Sum of all cause = 100%
- These are NOT rates b/c the denominator is all deaths, NOT the size of the population in which the deaths occurred
- Proportionate mortality of HIV =
- 0.5% among all age gps
- 5.3% for 25-44 yo
- IOW: HIV infection accountd for 0.5% of all deaths, 5.3% of deaths among 25-44 yo
- x
- Types of proportion
- Proportion
- Attack rate (incidence proportion)
- Secondary attack rate
- Pt prevalence
- Attributable proportion
- Proportionate mortality
- Proportion
27
Q
- 2 types of Rate
- Strict version of rate: incidence rate
- Loose version of rate
- x
- Types of rate
A
-
Rate:
- Epi: 2 ways
- Some restrict “rate” to measures expressed per unit of time
- Rate = how fast disease occurs in a population
- Eg: 70 new cases of breast cancer per 1000 women per year
- It shows the speed the disease occurs in a population, and implies this pattern has occurred and will continue in the future
- AKA incidence rate
- Rate = how fast disease occurs in a population
- Some loosely use the term,
- Numerator = proportions w/ case counts
- Denominator = Size of pop
- Attack rate or incidence proportion: proportion of the pop that dev illness during an outbreak
- Eg: 20 of 130 ppl dev diarrhea after a picnic
- Prevalence rate: proportion of pop that has a health condition at a pt of time
- Eg 70 flu case-patients in Mar 2005 reported in County A
- Case fatality rate: prop of ppl w/ the disease who die from it
- Eg: 1 death due to meningitis among County A’s population
- These are all proportions, and not expressed per units of time
- IOW: not TRUE rates
- Some restrict “rate” to measures expressed per unit of time
- Epi: 2 ways
- Types of rate
- Rate:
- Person-time incidence rate
- Crude mortality rate
- Case-fatality rate
- Cause-specific mortality rate
- Age-specific mortality rate
- Maternal-mortality rate
- Infant-mortality rate
- Crude birth rate
- Crude fertility rate
*
- Rate:
29
Q
- 2 types of incidence
- x
- incidence prop
- 4 other names
- Calculation
- Define attack rate
- 3 types of attack rate
- 2ndary attack rate calculation
- total # of contacts definition
- x
- incidence rate calculation
- 3 cases
- x
- Prevalence vs incidence
- Prevalence formula
- Why is prevalence used to measure chronic disease?
A
- 2 types of incidence: incidence proportion and incidence rate
-
Incidence proportion or risk
- Definition: proportion of an initially disease-free pop that dev disease, injured, or dies during a time period
- Aka attack rate, risk, prob of dev disease, cumulative incidence
- N: # of new cases (disease or injury) in a time period
- D: pop at the start of observation period
- D: ppl who have potential to get the disease
- Eg
- Numerator: new cases of ovarian cancer
- Denom: restricted to women (men do not have ovaries) w/ ovaries
- x
- In an outbreak, attack rate = risk of getting disease in an outbreak
- Types of attack rate
- # 1: Overall attack rate: total # of new cases / total pop
- # 2: Food-specific attack rate” # of ppl who are a specified food and got ill/ total # of ppl who are the food
- # 3: 2ndary attack rate: used to document the difference b/w community transmission [EL1] of illness vs transmission of illness in a household or barrack (building) or closed pop
- N: # of cases among ppl w the primary cases
- D: total # of contacts
- → total population in the households of primary cases – the # of primary cases
- # 3: 2ndary attack rate: used to document the difference b/w community transmission [EL1] of illness vs transmission of illness in a household or barrack (building) or closed pop
- Incidence rate
- N: # of new cases (disease or injury) in a time period
- D: sum of “the time each person was observed”
- Convention: reported in per 1000 PY
- X
- In LT follow up study of morbidity, each participant may be followed or observed for several yrs
- Case 1: person A followed for 5 years w/o developing disease = contributed 5 person-years of follow up
- Case 2: person B followed for 1 year b4 being lost to follow-up at year 2?
- We assume person lost to follow-up were disease free for half of the yr
- This contribute ½ yr to the denominator
- Thus, the person followed for 1 yr b4 lost to follow-up only contributes 1.5 years
- Case 3: The same assumption is made for ppl diagnosed w/ the disease at year 2 examination
- (some dev the illness in month 1, others in months 2 through 12)
- IOW, on avg, they developed illness halfway through the yr
- So, ppl diagnosed w/ the disease contribute ½ yr of follow-up during the year of diagnosis
- Denom of person-time rate = sum of the person-years for each study participant
- If someone is lost to follow-up in Y3, and someone diagnosed w/ the disease in Y3; they each contribute 2.5 yr of disease-free follow-up in the denom
- X
Prevalence
- Prevalence vs incidence
- Prevalence includes all cases (new and preexisting) in the pop in that time period
- Incidence: only NEW cases
- Numerators
- Numerator of incidence: new cases in the time period
- Numerator of prevalence: new and pre-existing present in a time period
- Formula: Prevalence is based on incidence & duration of illness
- High prevalence of disease in a pop = high incidence or prolonged survival w/o cure OR both
- Low prev: low incidence, rapid fatal process, or rapid recovery
- Prevalence (not incidence) is used to measure chronic disease (eg diabetes, osteoarthritis) as they have long duration and dates of onset that are hard to pinpointed
30
Q
- Mortality frea measures Calculation (N, D)
- Crude death rate
- cause-specific death rate
- proportionate mortality
- death-to-case ratio
- neonatal mortality rate
- postnatal mortality rate
- infant mortality rate
- Maternal mortality rate
- Combination or subgp mortality rate
A
Mortality freq measures
- Common Mortality Measures
- Crude death rate
- Num: # of deaths in a time period
- Denom: mid-interval pop
- Expressed in: 10k or 100k
- Cause-specific death rate:
- N: # of deaths due to a specific cause in a time period
- D: mid-interval pop
- Expressed in: 100k
- Proportionate mortality
- N: # of deaths due to a specific cause in a time period
- D: total # of deaths from all causes in the SAME time period
- Expressed in: 100 or 1k
- Death-to-case ratio
- N: # of deaths due to a specific cause in a time period
- D: # of new cases of same disease in the same time period
- In 100
- Neonatal mortality rate:
- N: # of deaths among children less than 28 days in a time period
- D: # of live births in the same time period
- In 1000
- Post neonatal mortality rate:
- N: # of deaths among children 28-364 days of age in a time period
- D: # of live births during the same time period
- In 1000
- Infant mortality rate: (neonatal, postnatal)
- N: # of deaths among children less than 1 yo in a time period
- D: # of live births during the same time period
- In 1000
- Maternal Mortality rate:
- N: # of deaths assigned to pregnancy-related causes in a time period
- D: # of live cirths in the same time period
- In 100k
- Crude death rate
- Combinations of specific mortality rates
- MR can be further stratified by combinations of cause, age, sex, and or race
- Eg: Death rate from heart disease among women ages 45-54: 50.6 per 100k
- Death rate from heart disease among men ages 45-54: 138.4 per 100k
- These rates are a cause-age, and sex-specific rates as they refer to one cause (heart disease), an age gp (45-54) and one sex (M or F)
