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Epidemiology > 1 > Flashcards

1 Flashcards

1
Q

what is epizootiology

A

science of distribution of disease and factors related to health, as well as application of knowledge in disease prevention

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2
Q

division of study according to data collection

A

interventional (clinical trial) and observational

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3
Q

division of study in relation to time

A

retrospective, prospective and mixed

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4
Q

surveillance data

A

classic observation of population and measurement of certain characteristics

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5
Q

research data

A

comparison of two or more groups

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6
Q

describe cross sectional study

A

prevalence research - random sample in a certain time
odds ratio (exposed v non exposed)
pro = simple and cheap
con = provides only estimation of prevalence

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7
Q

describe case control study

A

analyses relation between certain condition (disease) with specific cause
2 groups - animals selected based on health status - diseased and healthy and compare based on previous exposure RETROSPECTIVE study
pro = cheap and fast, good for rare diseases with low incidence, can study many risk factors retrospectively
con = no data given on incidence, heavily depends on sample quality, difficult to find good controls
calculate odds ratio

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8
Q

describe cohort study

A

compares incidence between groups over certain time period
prospective - condition is not present at start of research -concurrent
retrospective - records on previous exposure to risk factor and traced to present - non-concurrent
observes exposure
pro = monitoring over prolonged period, evaluation of incidence
con = expensive, long studies, rare, difficult follow up and sporadic diseases
can calculate incidence, incidence rate, reactive risk and attributable risk

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9
Q

general considerations for cohort study

A

cohorts must be free from disease under study
both study and control groups should be equally susceptible to disease under study
both groups should be comparable in respect to all possible variables
diagnostic and eligibility criteria of disease must be defined beforehand

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10
Q

features of cohort study

A

relative risk will give you causal relationship between disease and exposure
attributable risk measures the change of incidence due to exposure in question
identification of exposures and risk factors for a disease forms basis for prevention

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11
Q

measures of relation

A

cohort - relative risk, odds ratio
case-control - odds ratio of exposed
cross-section - odds ratio of prevalence

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12
Q

bias

A

selection, misclassification, confounding

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13
Q

experimental study

A

studies the impact of certain drugs/procedures on the course of diseases or its onset

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14
Q

experimental study design

A

similar to cohort
risk factor yes or no = treatment and control
study differences between cohorts
compare treatments and interventions
more comparisons possible 3-4 groups

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15
Q

life cycle of F.magna

A

liver fluke - miracidum - redia - redia and cercaria - cercaria - metacercária

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16
Q

definition of epidemiology

A

the study of diseases in population

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17
Q

descriptive epidemiology answers the questions…

A

what caused the disease, where, when, in which population

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18
Q

analytical epidemiology answers the questions

A

how and why - hypothesis testing

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19
Q

intrinsic host determinants

A

species, breed, age, sex

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20
Q

extrinsic determinants

A

climate, soils, man

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21
Q

what do Kochs postulates describe

A

causality between a causative organism and subsequent disease

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22
Q

an organism is causal if

A

it has to be present in every organism
it has to be isolated and grown in pure culture
it has to cause the same disease in other susceptible animals

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23
Q

why are kochs postulates not fully adequate in all cases?

A

weren’t applicable to non infectious diseases
they ignored interactions between infectious agents, hosts genes and environment in diseases with a multifactorial cause

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24
Q

what came after kochs postulates

A

evans postulates

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25
Q

surveillance

A

the systematic ongoing collection, collation and analysis of information related to animal health and the timely dissemination of information so that action can be taken

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26
Q

passive surveillance

A

collect animal health data and information from disease reporting stakeholders

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27
Q

active surveillance

A

epidemiological information collected through purposeful and planned interventions

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28
Q

syndromic surveillance

A

based on observation of main signs of the disease

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29
Q

clinical surveillance

A

investigate the occurrence of diseases based on observation of clinical signs

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30
Q

targeted surveillance

A

active surveillance based on occurrence of disease in a given area and/or species

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31
Q

risk based surveillance

A

active surveillance that focuses on a certain area or livestock population based on perceived level of threat, risk and/or consequences

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32
Q

participatory disease surveillance

A

active surveillance that uses participatory approaches in search of disease, including input from local livestock producers and others in lifestock value chain

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33
Q

epidemiological unit

A

group of animals with a defined relationship sharing common likelihood of exposure to a disease

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34
Q

predisposing factors

A

variety of situations that harbour or promote disease

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35
Q

risk mapping

A

tool used for identification, assessment, communication and mitigation of a disease in a certain geographical area

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36
Q

zero reporting

A

periodic standard reports noting that surveillance in any form for a given disease has been carried out and no disease occurrence has been encountered

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37
Q

what is a sample

A

a smaller but hopefully still representative collection of units from a population used to determine truths about that population

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38
Q

what does sample size depend on

A

prevalence

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39
Q

probability (random) samples

A

systematic random sample
stratified random sample
cluster sample

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40
Q

non probability samples

A

convenience sample
purposive sample
quota

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41
Q

simple random sample

A

population is 10
sample is 5
each animal

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42
Q

systematic random sample

A

population 10
sample is 5
take every second animal (10/5)
if fraction of 1-50 animals, we can pick a number eg 7and pick animals 57, 107, 157 etc

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43
Q

stratified random sampling

A

herd of 20, split in to breeds. take random sample from each breed

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44
Q

benefits of stratified random sampling

A

reduces variance
increases precision

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45
Q

cluster sampling

A

split target population in to clusters - eg a sow with her litter
if we want to estimate prevalence of E.coli in 90 piglets, we need to sample 30 piglets so 30/10 - we need to pick 3 clusters randomly

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46
Q

multistage sampling

A

randomly selected 5 sows
randomly select 6 piglets from 1 cluster

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47
Q

clusters can be

A

natural - herd, litter
artificial - areas, administrative units

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48
Q

to pick sample size we have to consider

A

how many animals should be considered to obtain representative results
desired precision
probability or confidence that our results will be acceptable for population

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49
Q

estimation of sample size

A

n = z2 Pexp (1-Pexp) / d2

n = sample size
Pexp = expected prevalence
d = precision
z = factor that determine confidence levels ( 95% - 1.96)

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50
Q

estimation for small population

A

nadj = (Nxn) / (N+n)

n = sample size for large population
N = sample size of analysed population

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51
Q

qualitative data

A

categorical, can’t be counted, measured or easily expressed as numbers eg breed, sex

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52
Q

quantitative data

A

information that can be expressed in numbers or quantified eg body weight, milk production, body temperature etc

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53
Q

discrete data

A

type of quantitative
can’t be made more precise eg number of pets (can’t have 1.4 animals)

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54
Q

continuous data

A

type of quantitative
can be divided and reduced to finer numbers
eg height can be in m, cm, mm etc

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55
Q

qualitative scales

A

nominal - no quantitative value eg sex, location
ordinal - variable measurement eg satisfaction, degree of pain

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56
Q

continuous scales

A

interval - order of variables and difference between variables known eg body temp
ratio - order of variable and makes a difference between variables

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57
Q

static measures

A

proportion and ratio

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58
Q

proportion is

A

a fraction in which numerator is included in the denominator
dimensionless, from 0-1 and usually a %
relation of 2 groups which are in direct relation

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59
Q

ratio is

A

a fraction in which numerator is not included in the denominator
can have a dimension
to present one group in relation to another

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60
Q

dynamic measures

A

rate - related to certain time frame

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61
Q

prevalence calculation

A

number of sick animals at a particular point in time divided by number of individuals in the population at risk at that point in time

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62
Q

prevalence characteristics

A

dimensionless
static measure
proportion
value from 0-1
probability measure

63
Q

incidence definition

A

number of new cases that occur in a known population over a specified period of time

64
Q

cumulative incidence calculation

A

number of animals that become diseased during a particular period divided by number of healthy animals in the population at the beginning of that period

65
Q

what is cumulative incidence a measure of

A

average risk or probability that certain event will occur during defined time period

66
Q

what are censored animals

A

animals lost from study due to loss and competing causes

67
Q

CI calculation taking in to account censored animals

A

number of new cases of disease divided by number at risk at the start of the period minus half of the censored animals

68
Q

pros and cons of CI

A

pro - simple to calculate
con - new animal cannot be added, only for first occurrence of disease, not for recurring eg mastitis and can be used in dynamic populations but only for a short period of time

69
Q

incidence rate

A

measures the rapidity with which new cases of disease develop over time

70
Q

IR calculation

A

number of new cases of disease that occur in a population during a particular period of time divided by the sum, over all animals, of the length of time at risk of developing a disease
IR = I/(number at risk at beginning + at end/2)

71
Q

pros an cons of IR

A

pro - can be calculated in case of multiple disease occurrence
con - can’t be interpreted on the individual level and is complicated

72
Q

morbidity

A

total number of diseased animals in a certain population over a given period of time divided by total number of animals in population

73
Q

proportional morbidity

A

number of cases in a given population over certain time period divided with total number of diseased animals in a population

74
Q

mortality

A

number of deaths during certain period of time divided by number of animals at the beginning of study

75
Q

proportional mortality

A

total number of deaths of certain specific disease in certain population with respect to all recorded deaths in that population during that specific period of time

76
Q

case fatality

A

number of deaths divided by number of diseased animals

77
Q

survival rate

A

number of cases minus number of deaths divided by number of cases

78
Q

crude measure

A

applied for whole population

79
Q

specific method

A

applied for certain specific part of population or subpopulation

80
Q

what is a diagnostic test

A

more or less an objective method for the reduction of diagnostic insecurity and to increase the speed of testing

81
Q

potential problems of diagnostic test

A

cross reactivity, analytical specificity, non-specific inhibitors, improper timing etc

82
Q

accuracy

A

how close are the test results to a real clinical condition (truth - gold standard)

83
Q

validity

A

power to detect diseased and non-diseased animals

84
Q

precision

A

results of repeated tests

85
Q

gold standard

A

best existing test

86
Q

true positive

A

sick animals correctly identified as positive

87
Q

false positive

A

healthy animals incorrectly identified as positive

88
Q

true negative

A

healthy animals correctly identified as negative

89
Q

false negative

A

sick animals incorrectly identified as negative

90
Q

sensitivity

A

proportion of diseased animals recognised by test as positive ones
100% sensitivity means no false negatives
RULE OUT disease

91
Q

sensitivity calculation

A

number of true positives divided by number of true positives plus number of false negatives

92
Q

false positive rate

A

proportion of negative animals incorrectly classified as positive

93
Q

false negative rate

A

proportion of positive animals incorrectly classified as negative

94
Q

specificity

A

proportion of healthy animals recognised by the test as negative
100% specificity = no false positives
RULE IN disease

95
Q

when sensitivity increases….

A

specificity decreases and vice versa

96
Q

predictive values

A

reflect diagnostic power of test

97
Q

what do predictive values depend on

A

sensitivity, specificity and prevalence

98
Q

positive predictive value

A

proportion of positive animals that really have the disease

99
Q

negative predictive value

A

proportion of negative animals that really dont have the disease

100
Q

increase in prevalence causes….

A

increased PPV

101
Q

decrease in prevalence will cause…

A

increased NPV

102
Q

if test is more sensitive then

A

higher NPV

103
Q

if test is more specific then

A

higher PPV

104
Q

likelihood ratio

A

assess the value of performing the diagnostic test
higher LR, the better the test to rule IN the disease

105
Q

smaller LR means

A

the better the test to rule OUT the disease

106
Q

parallel testing

A

application of several tests on the same animal and if one is positive the animal is considered positive
FP more likely to occur but increase NPV and Sn

107
Q

serial testing

A

only animals recognised as positive will undergo the second tets

108
Q

what is a mathematical model

A

mathematical description of the real world
focuses on specific quantitative features of the scenario and ignores others (simplifies)

109
Q

epidemic

A

higher incidence of disease than usual
actively spreading
often localised to a region

110
Q

epidemic curve shape determined by

A

incubation period
infectivity
proportion of susceptible animals
potential contact (distance between animals)

111
Q

endemic

A

disease/condition present among a population at all times
signs may be present or latent disease
after epidemics

112
Q

pandemic

A

epidemics that spread over multiple countries/ continents
eg avian influenza, ASF

113
Q

reproduction number definition

A

term that indicates how contagious an infectious disease is
average number of animals that will contract a contagious disease from one sick animal

114
Q

reproduction number calculation

A

infection rate divided by removal rate
epidemic can only occur if Ro >1

115
Q

factors determining reproduction number

A

infectiousness of pathogen, population density, course of infectiousness (incubation period, latent periods), mode of transmission, mixed population, seasonal variations, genetic variations in population at risk

116
Q

highest reproduction number in which mode of transmission

A

airborne and

117
Q

herd immunity

A

resistance of a group for attack of disease because of immunity of a large proportion of the members and so less likely of an affected individual to come in to contact with a susceptible individual
prevalence or immunity in a population above which it becomes difficult for the organism to circulate and reach new susceptible animal

118
Q

herd immunity can be

A

innate
acquired - had a disease or vaccinated

119
Q

density models

A

in case of diseases usually performed for cases where number of infectious agents can be numbered eg parasitic infections

120
Q

prevalence models

A

presence or absence of disease in various host cohorts eg age groups, immunity status et c

121
Q

deterministic models

A

describing situation with no random variation of input parameters
more suitable for large populations

122
Q

stochastic methods

A

enable probability distribution and CI to be associated with outputs
possibility of chances, suitable for small populations

123
Q

potential application of modelling

A

to model processes in organism - metabolism, drug kinetics etc
estimation of population dynamics
simulation of spreading diseases
education
animal production - simulation of profitability through reduction of negative factors

124
Q

SIR model is

A

susceptible - infectious - recovered

125
Q

enhancing SIR model

A

consider additional populations of disease vectors - fleas etc
consider an exposed but not yet infected class - SEIR model
SIR, SIS and double (gendered model) for STDs
consider biased mixing, age differences, multiple types of transmission, geographic spread etc
enhancements often need more compartments

126
Q

SIR calculation

A

S+I+R= 1

127
Q

reed frost model

A

also considers time and probability that an animal can’t infect another animal

128
Q

probability defintion

A

proportion of times an event would occur if an observation was repeated many times

129
Q

risk definition

A

probability of an event among those experiencing the event divided by the number who are at risk

130
Q

odds definiton

A

probability of an event divided by the probability of the event not happening

131
Q

association

A

is present if probability of occurrence of a variable depends upon one or more variable

132
Q

risk factor

A

any factor that is related to increased chance of disease/death etc

133
Q

exposure

A

means that an animal was exposed (in contact) with specific risk factor

134
Q

absolute risk

A

only those who have a condition due to exposure
a/a+b

135
Q

relative risk

A

if an association exists, then how strong is it?
what is the ratio of the risk of disease in exposed individuals to the risk of disease in unexposed individuals?

136
Q

relative risk calculation

A

risk in exposed divided by risk in unexposed
incidence in exposed divided by incidence among unexposed

137
Q

interpreting relative risk of a disease

A

RR >1 = positive association (probably causal)
RR <1 = negative association (possibly protective)

138
Q

if odds ratio is 1

A

no association

139
Q

cohort studies and odds ratio

A

probability of disease occurrence

140
Q

case control studies and odds ratio

A

ratio of exposure to risk factor in group case, compared to group control
what are the odds that a case was exposed?

141
Q

cross sectional studies and odds ratio

A

estimate prevalence odds ratio

142
Q

odds calculation

A

probability of an event occurring divided by probability of the event not occurring

143
Q

relationship between OR and RR

A

OR is a valid measure of association in its own right and is often used as an approximation of the relative risk
OR always further from 1 than RR
the higher the incidence the higher the discrepancy

144
Q

attributable risk

A

the amount of proportion of disease incidence (or disease risk) that can be attributed to a specific exposure

145
Q

what does AR include

A

baseline incidence and indicates what was the effect of the risk factor in the population

146
Q

higher AR means

A

higher effect of the risk factor

147
Q

attributable fraction

A

answers the question - which proportion of disease in exposed animals is due to exposure

148
Q

when is AF difficult to calculate

A

in case-control studies

149
Q

preventative fraction asks

A

how much disease among the non exposed group could be prevented by adding the exposure to the non exposed

150
Q

population attributable risk

A

help assess the effect of primary prevention interventions on an entire population
amount of risk that would be eliminated from th population if the exposure were eliminated

151
Q

types of error

A

type 1 - alpha - accepting the hypothesis despite the fact Ho is correct
type 2 - beta - acceptign the false Ho

152
Q

why do we test if there is a difference

A

to determine what is a probability that differences are accidental or actual - significance

153
Q

why do we test if there are no differences

A

how probable is that differences do exist but our test have failed to determine them

Epidemiology (1 decks)

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