epidemiology Flashcards
what are measures of occurrence
Describe the distribution of an outcome in a group of people in regards to Person, Time and Place:
* Prevalence
* Incidence: Cumulative incidence
(risk), incidence rate (rate) * Proportions vs odds
what are measures of association
Describe association between outcome and its determinants (exposures, risk factors, interventions):
* Ratios
* Differences
* Regression coefficient
Point prevalence
measures the proportion of existing people with a disease in a defined population at a single point in time.
no with disease/ total of population at specific time point
Period prevalence
is the number of individuals identified as cases during a specified period of time/ the total number of people in that population.
cumulative incidence (RISK)
number of new cases in specific time period/ number of people at risk at start of time period
(proportion)
incidence rate (RATE)
number of new cases in specific time period/ total person-time at risk during time period
odds (of a disease)
number of new cases/ number who dont have disease at end of period
(part/none part)
if there is an association what could be the cause?
- chance
- bias
- confounding
- true association
- reverse causation
What are ratio/relative measures of association?
Divide the two measures of disease occurrence
CIR, IRR, OR
How much higher is the risk of lung cancer among smokers (exposed) compared to non smokers (unexposed)?
cumulative indicidence ratio
CI in exposed/ CI in unexposed
incidence rate ratio
incidence rate in exposed/ incidence rate in unexposed
what do these relative risk mean.
<1
1
> 1
A relative risk of 1 indicates that the incidence of disease in the exposed and unexposed groups is identical and that there is no association observed between the disease and risk factor/ exposure.
A relative risk > 1 occurs when the risk of disease is greater among those exposed and indicates a positive association, or an increased risk among those exposed to the risk factor compared with those unexposed.
A relative risk < 1 occurs when the risk of disease is lower in those exposed compared to those unexposed and indicates a negative association.
Attributable risk
is it absolute or relative
risk in exposed - risk in unexposed
absolute
what do these mean for the attributable risk
<0
0
> 0
<0 exposure associated with X fewer cases
= 0 no association between exposure and disease
> 0 exposure associated with X more cases compared to unexposed
Attributable Risk Fraction Aetiological Fraction Etiological Fraction
R exposed - R unexposed/ R exposed
population attributable fraction
Risk in total population - risk in unexposed
The population attributable risk (PAR) estimates the excess rate of disease in the total study population that is attributable to the exposure. It provides a measure of the public health impact of the exposure in population,
assumes that the association is causal!!!
Number Needed to Treat (NNT)
1/ absolute risk reduction (ignoring sign)
number of people needed to treat to prevent 1 case
look at absolute risk reduction to see if worthwhile
methods of probability sampling
random (simple)
stratified
systematic
cluster
what is person years definition, What are the advantages and disadvantages.
Definition
Patient years=denominator of the rate, calculated by counting all individuals in a pre-determined time period in this case time spent in the RCT
Advantages
Using person-time rather than just time handles situations where the amount of observation time differs between people,
Can be used to compare between studies as a method of standardisation (e.g. comparing studies of different lengths) and can be used to maximise all data as patients will have been in RCT for variable length of time
Disadvantage
Use of this measure implies that the incidence rate is constant over different periods of time, such that for an incidence rate of 14 per 1000 persons-years, 14 cases would be expected for 1000 persons observed for 1 year or 50 persons observed for 20 years. This may not be the case.
Difficult to interpret and communicate in the real world as requires understanding of the assumptions underlying it
Describe an appropriate method for comparing the two survival curves, what assumptions is this test based on
The log rank test.
null: no difference between survival curves
(used on kaplan meier curves)
Assumptions
1) that the data are continuous or ordinal
2) that risk of an event in one group relative to the other does not change over time (proportional hazards assumption)
- non parametric
what is censoring? give some reasons
Censoring is when an observation is incomplete due to a cause independent of the event of interest
the subject dies from another cause, independently of
the cause of interest;
the study ends while the subject survives; or
the subject is lost to the study, by dropping out, moving
to a different area
Event of interest already occurred at the observation
time, but it is not known exactly when.
Relative Risk Reduction (RRR)
= (ARc – ARt) / ARc; or RRR = 1 – RR
c: control
t: treatment
RR: relative risk - ARt/ ARc
proportional mortality ratio
measures the proportion of deaths occurring from a given
cause for a particular occupation relative to the proportion of deaths from that cause in the
whole population (or a comparison population)
A PMR is based on the underlying cause of death as recorded on the death certificate and provides little information about diseases that cause high morbidity but which are
rarely fatal
Occupational information usually relates to the deceased persons last full-time job, but other jobs undertaken earlier in their career may be of more relevance
The PMR is not a population-based rate, and so it can be used to measure mortality where no denominator is available about the number of people who work in an
occupation
The PMR of an occupational group for a specific cause depends not only on its death rate from the cause in question, but also on its death rate from all causes combined.
This may be of relevance where an occupational group has particularly high or low mortality from the most common causes of death. As it is a proportional measure, the
PMR can be raised in situations where the frequency of other causes of death is low
Relative Risk (RR)
= ARt / ARc (AR exposed/ ER unexposed)
what type of graph is this and give four things that it shows
Epidemic curve
- duration of outbreak
- magnitude of outbreak
- time trend of outbreak
- propagation of outbreak (person to person spread)
- outlier investigation
basic reproduction number and what is it affected by
average number of secondary infections produced by a typical case of an infection in a population where everyone is susceptible
affected by:
The rate of contacts in the host population (eg behaviours)
The probability of infection being transmitted during contact
The duration of infectiousness.
how infection spread (direct contact, airborne)
effective reproductive number
average number of secondary cases caused by a disease in a particular population, at a particular time.
OR
average number of secondary cases per infectious case in a population made up of both susceptible and non-susceptible hosts.
herd immunity threshold
the proportion of a population that need to be immune in order for an infectious disease to become stable in that community. If this is reached, for example through immunisation, then each case leads to a single new case (R=1) and the infection will become stable within the population.
(R0-1) /Ro
If the threshold for herd immunity is surpassed, then R<1 and the number of cases of infection decreases. This is an important measure used in infectious disease control and immunisation and eradication programmes.
Attack rate
total number of new cases/ population at risk in a defined time period
how to calculate excess deaths
- define baseline risk (lowest exposure)
- ensure each group has a death rate
- death rate A - baseline death rate = excess death rate
- excess death rate x population n A = excess deaths
Life table (how to calculate)
- calculate deaths, survivors
- work out life years lived for each age band = survivors + (deaths/2)
- sum all life years
- life expectancy = sum life years/ alive at start
for life year (Lx)
times by age band
cohort vs period life expectancy
Cohort:
the average lifespan of a group (cohort) based on their actual mortaity rates
-A combination of OBSERVED AND PROJECTED mortality rates
good: more accurate, can project
issues: how projections calculated, complicated to produce
Period:
life expectnacy if they experiecned the age specific rates of a given year(s)
For example, period life expectancy at age 65 years in 2020 would use the mortality rates for 2020 for ages 65, 66 and 67 years, and so on.
use mortality rates from a single year (or group of years) and assume that those rates apply throughout the remainder of a person’s life. This means that any future changes to mortality rates would not be taken into account
good: baseline for cohort LE
issues: normally more conservative LE
Ecological study
data on an aggregate level
pros:
- quick
- cheap
- hypothesis testing
cons:
- ecological fallacy
- no information on individual
- cant control for unknown confounding
- only average exposure (?J curve)
-spatial autocorrelation (assumes areas of independent)
- leakage via migration
case report/series
report descriptive on case
pros:
- quick
- easy
- start of outbreak
- describe features of a new disease
cons:
- no causation (may be coincidence)
- no disease burden
- may not be generalisable
- no comparison group
case/control
have a disease of interest, look for exposure that increase odds of disease in cases comapred to control
pros:
- quick
- easy to carry out
- good if disease rare to look for possible RF
cons:
- hard to control for counfounders
- ?how to select controls
- may be exposure no measured
- no temporal relationships
cohort
this is when a group of individuals with a particular exposure are followed up (either prospectively or retrospectively) til outcome
pros:
Able to follow temporal relationships.
Well suited to rare exposures.
Multiple effects of a single exposure.
Minimises selection bias (prospective cohort studies).
Useful for diseases with long latency periods (retrospective cohort studies).
cons:
Time-consuming.
Expensive.
Risk of loss to follow-up (➔ poor validity [power and bias], especially if loss to follow-up >30% or if loss to follow-up is disproportionate between two groups).
Inefficient for rare diseases.
Records may be inadequate for ascertainment (retrospective cohort studies).
Healthy worker effect
RCT
experimental, randomisation to see effect
pros:
- see effect of a treatment
- minimise bias ( blinding, randomisation)
- high quality evidence
cons:
- expensive
- time consuming
- issues with generalisability
- ethical issues
cross sectional
when exposure and outcome data collected at same time
pros:
- quick
- multiple exposure and outcomes
- cheap
- rare disease
- assess disease burden
cons:
- no temporal relationship
- data collection varies
- bias (recall)
