Quantifying Disease Occurrence Prepared by: Dr. Ronnie D. Domingo Session objectives: At the end of this topic, the participants should be able to: 1. Explain the differences of ratios, proportions and rates. 2. Describe the different measures of morbidity, mortality and production; 3. Select the right measure for a given population data; 4. Compute the appropriate measures when provided with the necessary data Measures of Disease Page 1
Transcript
Quantifying Disease OccurrencePrepared by:
Dr. Ronnie D. Domingo
Session objectives:
At the end of this topic, the participants should be able to:1. Explain the differences of ratios, proportions and rates.2. Describe the different measures of morbidity, mortality and production;3. Select the right measure for a given population data;4. Compute the appropriate measures when provided with the necessary data
Measures of Disease Page 1
General ConsiderationsImportance of correct counting
• Since epidemiology deals with populations, epidemiologists need to count and summarize the number of cases of disease.
• Health status of a herd is assessed by the collection, compilation, analysis and interpretation of data on illness (morbidity), death (mortality), and production performance.
• If the right measurements are performed, the veterinarian can decide confidently on issues such as disease prioritization, control program and monitoring of disease control impact.
• When comparison is being made between two groups or more, the first thing to verify is that you are comparing apples with apples.
Definitions
Population- The complete collection of elements, groups, or individuals to be studied. Population at risk- The animals that are really susceptible to the disease being studied.
Population at risk in a study of carcinoma of the cervix (WHO)
Source: (Beaglehole, Bonita, & Kjellstrom, 1994)
Counts, rates, proportion and ratio
Count A simple enumeration of the absolute number of cases of disease or number of
animals affected with a condition in a given population. Example
o Simple count: there are 40 sows diagnosed with brucellosis in barangay Rizal last month.
o (Note: no mention about the total number of pigs in Rizal)
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Ratio Ratio is the result of dividing one quantity by another
Ratio= ab
Examples
Sex ratio= Number of femalesNumber of males
• If there are 42 cows and 2 bulls in a farm, you could compare the number of cows to bulls by saying there is a ratio of 42 cows to 2 bulls. You could represent that comparison in three different ways:
42 to 2 42 : 2 42/2
Remember that a ratio must always be in simplest form but have two numbers.• The first operation to perform on a ratio is to reduce it to lowest terms
42:2 =42/22/2 =
211 = 21:1
Additional applications• boar to sow ratio• Feed conversion ratio• Relative risk • Odds ratio
Proportion A proportion is a special type of ratio, in which a is part of the denominator (a + b),
Proportion= aa+b
All proportions are ratios – not all ratios are proportions. A proportion can be expressed as a number between 0 and 1 or as a percentage
between 0 and 100%. • 10ⁿ is a constant that is used to transform the result of the division into a uniform
quantity.• The size of 10ⁿ may equal 1, 10, 100, 1000 and so on depending on the value of n. • Examples:
10² = 10 x 10 = 100 10³ = 10 x 10 x 10 = 1000 10⁵ = 10 x 10 x 10 x 10 x 10 = 100,000Examples:
The proportion of pigs infected with hog cholera in Sta. Cruz is 1.2%. The proportion of pregnancies ending in abortions in a piggery farm is 90/890 or
approximately 10%. The proportion of pigs with lungworm is 24 per 100,000 pigs.
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Rate Rate is another type of ratio. Rates have the added dimension of time. An epidemiologic rate will contain the following: disease frequency (numerator), unit of population size, and the time period during which the event occurred
Rate = number of cases occurringduring a giventime periodpopulationat risk duringthe same time period x 10ⁿ
Example: There were 22 new cases of rectal prolapse per 10,000 sows in
Pangasinan in 2011.
Presentation of percentagesToma, et al., 1999 wrotte the following principles in expressing relative frequencies in the form of percentages.
Principles
1. In epidemiology, the percentage is commonly calculated using the formula.
Percentage= nN
∗100 where n corresponds to the
number of events while N to the population size
2. If N (or the population size) is less than 10, the result should not be expressed in percentage to avoid the false impression of deriving the result from a large population and from a precise calculation. It is better to write “five out of ten animals...” instead of “50% of animals.”
3. If N is less than 100, the percentages should be expressed only as whole numbers.
4. If N is between 100 and 1000, the percentage is given with a single figure after the decimal point.
5. If N is above 1000, the percentage is given with two figures after the decimal point.
6. If the percentage is computed from a sample (n), always include the confidence interval.
Examples
Percentage= 50100
∗100=50%
“five out of ten animals...”
Percentage=3395
∗100=35%
(Wrong: 34.74%)
Percentage= 47680
∗100=6.9%
(Wrong: 6.91%)
Percentage= 1253400
∗100=3.68%
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(Toma, 1999)
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Measures of Morbidity
Prevalence Incidence• Period prevalence• Point prevalence
• TRUE RATE: Incidence density (also called true incidence rate , hazard rate, force of morbidity or mortality)
• RISK RATE: Incidence risk or cumulative incidence
• ATTACK RATE (during a disease outbreak)
Incidence • Measures the rapidity with which NEW cases are occurring in a population (how quickly
animals are catching the disease)• Time, (i.e., day, month, year) must be specified
There are three ways of expressing incidence:• Incidence count • Incidence risk (cumulative incidence)• Incidence rate (Incidence density)
Incidence count
• Incidence count is the simple count of the number of cases of disease observed in a population.
• Because it is merely a count, there are limits to the inferences that can be made from count data.
• Incidence counts are rarely used in epidemiologic research
• Example:Hong Kong had 2 cases of bovine spongiform encephalopathy (BSE).
Incidence Risk
Synonym: cumulative incidence (CI)• An incidence risk is the probability that an animal will contract or develop a disease in a
defined time period. • It is the ratio between the number of animals that contracted the disease in a certain
period and the number of healthy animals at risk in the population at the start of that period.
Incidence risk= ¿of new casesduring a specified period
Number of animals freeof the disease∈the population at risk at the beginning of the period x 10 n
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Additional notes about CI:1. The value can be anywhere between O to 1. 2. The time period to which the risk applies must be specified (e.g., “3-year CI”).3. It assumes that the entire population at risk at the beginning was followed-up for the time
period of observation. 4. The term cumulative incidence is applied because it measures the amount of new cases
of disease that accumulated in time. This means that the longer is the period of observation, the higher would be the cumulative incidence.
Sample calculation (Baumann, 2009)• Suppose that 20 out of 100, initially uninfected, pigs develop pseudorabies in a one
week period. • The cumulative incidence in that week then is: 20/100 = 0.2. • When in the subsequent week another 15 pigs get pseudorabies, the cumulative
incidence over the 2-week period amounts to 0.35 (see table):
Week Number of new cases CI1 20 0.202 15 0.353 10 0.454 5 0.505 1 0.51
Interpretation:The cumulative incidence over the entire 5-week period is 0.51.
Incidence Rate
Synonym: Incidence density or ID or incidence density rate (also called true incidence rate, hazard rate, force of morbidity or mortality)
• An incidence rate is the number of new cases of disease in a population per unit of animal-time during a given time period.
• A measure of the average speed (velocity) at which the disease is spreading.
ID = Totalnew casesduring stated period
∑ of thelengthof time at risk for eachanimal∈the population(expressed∈animal time)
• Animal time = total time each animal in the population was at risk of getting the disease
• Interpretation: o ID addresses the question “How rapidly is the disease occurring in the
population, relative to its size?” o “What is the intensity with which the disease is occurring?”
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Sample calculation from (Pfeiffer, Dirk, 2009)
A study was conducted over a period of 12 months to determinate the mortality of cows in a village which has a total 100 cows at the beginning of the study. • 5 cows die after 2 months which means they were 5* 2 = 10 animal months at risk • 2 cows die after 5 months which means they were 2 * 5 = 10 animal months at risk • 3 cows die after 8 months which means they were 3 * 8 = 24 animal months at risk
This means a total of 10 cows die, and these experienced 44 animal months at risk based on the calculation (5* 2 + 2*5 + 3*8) • 90 cows survive past the study period which means they were 90*12 months = 1080 animal months at risk
Therefore, the incidence density of cow mortality in this village is calculated as 10 / 1124 = 0.009 deaths per animal month.
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Hypothetical Study
Modified from (Stevenson, 2008)
Number present at start 10Number of withdrawn animals 2Number present at end of study 8Number of disease events 4
Prevalence in June AD and F or 3/933%
Prevalence in December
ADF and G or 4/8
50%
Cumulative incidence 40% (4 cases in 10 animals)Incidence density (exact) 4 cases per 80 cow-months at risk
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Attack rate
The term “attack rate” is often used instead of incidence during a disease outbreak in a narrowly-defined population over a short period of time.
Attack Rate = Number of newcases amongthe population duringthe period
populationat risk at the beginning of the period X 100
The attack rate is not truly a rate but a proportionThe higher the attack rate, the more important the specific factor is in increasing risk of disease. Usually a percentage: 10ⁿ where n = 2
• Of 75 persons who attended a church picnic, 46 subsequently developed a gastrointestinal illness.
• Cases of GI illness occurring within the incubation period for GI illness among persons who attended the picnic = 46
• Number of persons at the picnic = 75
• Then, the attack rate for GI illness is 4675 x 100 = 61%
• Interpretation: Among persons who attended the picnic, the probability of developing GI illness was 61%, or the risk of developing GI illness was 61%.
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Prevalence1. It describes the proportion of the population that is in the disease state at a specific time.2. A snapshot of the situation at a single point in time. 3. Prevalence can be expressed per 100 people (per cent, %) or per 1,000 (10 3 ), 10,000 (10
4) or 100,000 (10 5 )4. The term ‘prevalence rate’ is not a true rate because a rate should include units of time.
Point Prevalence
It is the probability that a randomly selected animal suffers from that disease at a certain moment.
Point Prevalence = Number of animalswith diseaseat agiven point∈time
Totalnumber of animals∈the population at a given point∈time x 100
Example A population of 10,500 pigs held at a quarantined farm was investigated on April 04,
2015. A total of 140 cases of FMD were identified. The point prevalence of FMD at that farm on April 04 was:
Point Prevalence= 14010500x 100 = .013 x100 = 1.3 % or 13 cases per 1000 pigs
Period Prevalence
Period prevalence refers to the proportion of the population that had the disease during a specified PERIOD of time.
It combines the point prevalence at the beginning of the period and the incidence (number of new cases that occur during the period).
Period prevalence can be calculated for a week, month, year, decade, or any other specified length of time.
Period Prevalence = Number of animals with diseaseat agiven period of time
Totalnumber of animals∈the population at a given period of time x
100
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Prevalence Illustrated
* Point prevalence- 01/01/2009: case No. 2, 4, 5. Point prevalence in 01/01/2009 is 3/10 or 0.3 or 30 %- 31/12/2009: case No. 6, 7, 10. Point prevalence in 31/12/2009 is also 3/10 or 30%* Period prevalence between 01/01-31/12/2009:Case No. 2, 3, 4, 5, 6, 7, 9, 10
Period prevalence between 01/01-31/12/2009= 8/10 or 0.8 or 80%
Relationship between prevalence, incidence and duration of disease state
1. Prevalence differs from incidence in that prevalence includes all cases, both new and preexisting, in the population at the specified time, whereas incidence is limited to new cases only.
2. Prevalence refers to proportion of animals which have a condition at or during a particular time period, whereas incidence refers to the proportion or rate of animals which develop a condition during a particular time period.
3. A disease with a long duration has a higher chance of being counted during a cross-sectional survey than a disease with short duration. Given the assumption that population is stable and incidence and duration are unchanging, the relation between incidence and prevalence can be expressed as
P ≈ IR × DWhere:
≈ means approximately equal to.P = prevalence IR= incidence rateD = average duration of disease
4. High prevalence of a disease within a population might reflect high incidence or prolonged survival without cure or both. Conversely, low prevalence might indicate low incidence, a rapidly fatal process, or rapid recovery.
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Wash basin Analogy. Incidence is depicted by water flowing from a faucet into a basin, and prevalence is
represented by the volume water in the basin. When the inflow is copious, the basin readily fills.
The process, however, is influenced by another factor, which is represented by the basin drain.
This factor is disease resolution or duration. If the disease resolves fast by recovery or death, this will have the effect of decreasing the prevalence unless the inflow is heavy enough to sustain the water level in the basin.
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A comparison of the main features of prevalence, incidence risk, and incidence rate
Point prevalence Period prevalence
Incidence risk Incidence rate
Numerator All cases counted on a single occasion
Cases present at period start + new cases during follow-up period
New cases during follow-up period
New cases during follow-up period
Denominator All individuals examined
All individuals examined
All susceptible individuals present at the start of the study
Sum of time period at risk for susceptible individuals present at the start of the study
Time Single point or period
Defined follow-up period
Defined follow-up period
Measured for each individual from beginning of study until disease event, exit from thepopulation, or end of the follow-up period
Study type Cross-sectional Cohort Cohort Cohort
Interpretation Probability of having disease at a given point in time
Probability of having disease over a defined follow-up period
Probability of developing disease over a defined follow-up period
How quickly new cases develop over a defined follow-up period
Source: (Stevenson, 2005)
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Measures of MortalityCrude death rate (Death rate or Crude mortality rate)
The crude mortality rate is the mortality rate from all causes of death for a population. • The denominator is the population at the mid-point of the time period.
Crude mortality rate = Number of deathsreported withinagiven period
Population¿ themiddleof that period
• Example
The crude mortality rate for Quezon City in 2009 was 896 deaths per 100,000 people.
Case-fatality rate
Case fatality risk (or rate) refers to the incidence of death (proportion) among individuals who develop a specific disease (within a specified time period).
Its denominator is limited to those who possess the disease.
Case fatality rate = Total number of animals dying¿ the diseaseduring(specified period) ¿
Total number of animals who had the disease during(specified period)
Example: The case-fatality rate of PED last April 2015 in Masagana Swine Farm was 6,000 deaths due to PED/10,000 piglets diagnosed with PED disease or 60%.
Cause-specific mortality rate
The cause-specific mortality rate is the mortality rate concerning a specified cause for a population during a specified time period.
The numerator is the number of fatalities attributed to a specific cause while the denominator consists of the population at the midpoint of the time period.
Example: In the United States in 2003, a total of 108,256 deaths were attributed to accidents (unintentional injuries), yielding a cause-specific mortality rate of 37.2 per 100,000 population.= 8.18 / 100,000
Proportional mortality/morbidity
Calculated by dividing the number of cases (or deaths) due to a specific disease by the number of cases (or deaths) from all disease s diagnosed.
Proportional mortality = Number of deaths ¿ the disease ¿Number of deaths ¿
all causes¿
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Summary of common measures of mortality
Crude death rate = CD
Where D represents the total number of animals in the study population, both sick and healthy.
Cause specific mortality rate = BmD
Case fatality rate = BmAm (note that Am includes Bm in the drawing above)
Proportional mortality rate = BmC
Source: (Dicker, 2006)
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Adjusted Measures of Disease
Crude measures give a snap shot of the disease situation in a given population. For a homogenous population, crude measures may be sufficient.However, for a heterogeneous population, crude measures must be adjusted in order to determine the true distribution of the disease problem.
Source: (Baumann, 2009)
ExamplePoint prevalence (crude) of porcine circovirus type 2 in Bulacan Piggery FarmCrude Stratified
ReferencesBaumann, M. P. O. (2009). Quantification of animal health and disease.Beaglehole, Bonita, & Kjellstrom, R. &. (1994). Basic Epidemiology. Orient BlackSwan.Dicker, R., Coronado, F., Koo, D., & Parrish, R. G. (2006). Principles of Epidemiology in Public
Health Practice, 3rd Edition (3rd edition). CDC.Pfeiffer, Dirk. (2009). Veterinary Epidemiology: An Introduction.Stevenson, M. (2008). An Introduction to Veterinary Epidemiology. Massey University,
Palmerston North, New Zealand. Retrieved from http://www.sciencedirect.com/science/article/pii/0197245686900462
Toma, B. (1999). Applied Veterinary Epidemiology and the Control of Disease in Populations. AEEMA.
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WORKSHOP 3: Measuring morbidities and mortalities
Bacolod Sheep ImportationThe City of Bacolod imported 5000 sheep from New Zealand in 2010. After five months, 2800 animals showed signs of anemia and diarrhea due to blood-sucking roundworms identified by fecalysis as Haemonchus sp. Overall, 1100 animals died. However, during necropsy, the roundworm was recovered only in 730 sheep.
Calculate the following:
Crude death rate =
Case fatality rate =
Cause specific mortality rate =
Proportional mortality rate =
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Fasciolosis in Kabacan, North Cotabato
Fecal samples were collected rectally from carabaos and cattle from five selected barangays, namely Colambog and Takepan in Pikit, Malanduage, Pisan, and Bannawag in Kabacan. The age, sex, and condition of female animals (whether pregnant or lactating) were noted. Groupings according to age were as follows: 0-2.9 years; 3-5.9 years; 6-8.9 years; and, 9 years and above. The feces were examined for the presence of fasciola eggs using the sedimentation technique adapted from Suhardono (1998). The results are shown below (note that for this exercise, the values from the original document were modified).
Table M1 summarizes the results of examination of fecal samples from cattle while Table M2 summarizes the results from carabao samples. For each table, write an appropriate table title and supply the missing figures.
Age Group Fecalysis (+) Fecalysis (-) Total Prevalence (%)
0-2.9 48 783-5.9 58 416-8.9 45 30
9 and above 24 17
TOTAL 175 166
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Cattle Anaplasmosis
Hypothetical study. A total of 80 beef cattle imported from Australia were delivered in Busuanga Animal Quarantine Station in 2011. The field epidemiologist monitored the health condition of the animals for six months. Several animals became infected with a protozoan tick-borne disease, Anaplasmosis. Some animals recovered while others died. A timeline was shown to you to visualize what happened to the 12 animals:
Note: S= onset of illness; R= date of recovery; D= date of death
Calculate the following:
1. Point prevalence of Anaplasmosis on July 01, 2011.
Answer:
2. Point prevalence of Anaplasmosis on September 03, 2011.
Answer:
3. Period prevalence of Anaplasmosis from June 1 to August 01, 2011
