Measuring disease and death frequency Integrated Disease Surveillance Programme (IDSP) district surveillance officers (DSO) course

Outline of the session Ratio, rate, proportion Prevalence Incidence Relation between prevalence and incidence Mortality 2

Count, divide and compare: 1.Question during an outbreak of hepatitis A in Sioux City, IA, USA: Are native Americans at higher risk? Number of new hepatitis A cases Native Americans: 19 (8% of cases) Others: 228 (92% of cases) Can you compare these two groups with this information? How can this information be used? Who can use this information? First we will provide an illustration of the count, divide, compare method. The first step is count. We count cases of hepatitis A in two groups. But, can you compare directly the number of cases of hepatitis A in two groups? Introduction 3

Count, divide and compare: 2. Divide the number of cases by the population New hepatitis A cases # Year Population Native Americans 19 1996 1,697 Others 228 96,576 The case count is useful if you do not leave your own group, but if you want to compare two groups, you need to compare. The population of other groups is larger than the Native American population So before comparing, we divide the number of cases in each group by the population denominator of the group. This gives us a rate. Native Americans: 19/1,697 Others: 228/96,579 Introduction 4

Count, divide and compare: 3. Compare indicators Native Americans: 1,112 per 100,000 Others: 236/100,000/ year Rates among Native Americans are higher Now that we have divided by the denominator, we are allowed to compare. While others had more cases, the frequency of the disease is higher in Native Americans, once the division corrects for the difference in the population size. Introduction 5

A ratio places in relation two quantities that may be unrelated The quotient of two numbers Numerator NOT necessarily INCLUDED in the denominator Allows comparing quantities of different nature: Female to male ratio Now that we have seen the CDC principle, we will see what a ratio is. The ratio is a crude measure: You can divide anything by any other thing. = 5 / 2 = 2.5/1 Introduction 6

Examples of ratio Number of doctor per beds 1 doctor for 85 beds Number of participants per facilitator Sex ratio: Females / Males Ratio of white blood cells to red blood cells 1/600. What does it tell? Number of children with scabies / number of children with malnutrition Does it make sense? Examples. As you can see, a ratio is permissive. You can divide anything by any other thing. Now of course, it needs to make some sense. Introduction 7

A proportion measures a subset of a total quantity The quotient of two numbers Numerator NECESSARILY INCLUDED in the denominator Quantities have to be of the same nature Proportion always ranges between 0 and 1 Percentage = proportion x 100 A proportion is a more elaborate indicator. The quantities have to be of the same nature because the numerator is part of the denominator. 2 / 4 = 0.5=50% Introduction 8

Example of proportions The proportion of children with scabies in a village Tuberculosis cases in a district: 400 males, 200 females Question What is the proportion of males among all cases? What is the proportion of females cases among all cases? Note: All proportions are ratios Is the converse true? Examples and exercises. All proportions are ratios, but not all ratio are proportions. There is a condition to be a proportion that is not required for a ratio. Introduction 9

A rate measures the speed of occurrence of health events The quotient of two numbers Defined duration of observation Numerator Number of EVENTS observed for a given time Denominator (includes time) Population at risk in which the events occur A rate provides an idea of speed. It relates the frequency to a time unit. Observed in 2004 2 ----- = 0.02 / year 100 Introduction 10

Example of rate Mortality rate of tetanus in country X in 1995 Tetanus deaths: 17 Population in 1995: 58 million Mortality rate = 0.03/100,000/year Rate may be expressed in any power of 10 100; 1,000; 10,00; 100,000 Self explanatory examples. Introduction 11

Prevalence – (P) Number of existing cases (old and new) in a defined population at a specified point of time Number pf people with disease at a specified time P = ---------------------------------------------------- x 10n Population at risk at the specified time In some studies the total population is used as an approximation if data on population at risk is not available Now that we have seen ratios, rates and proportions, we will study prevalence. Self explanatory definition. Can you think of examples of prevalence? Like the prevalence of hypertension among participants of the course? By “at risk” we mean that the person can develop the disease. For instance, the prevalence of cancer of the cervix can only be calculated among females: Males are not at risk as they do not have a uterus. Prevalence 12

Source and type of prevalence data Surveys generate prevalence data Prevalence data are expressed as proportions Number affected / Number surveyed The numerator is included in the denominator The affected are only identified among the surveyed Prevalence data are cross sectional in nature. They usually come from cross sectional methods like survey. A prevalence is expressed as a proportion. Prevalence 13

Example of point prevalence 150 children in a school Screening for visual acuity at a given time 15 children require glasses Prevalence of refractory errors 15 / 150 = 10% A simple example of point prevalence. Prevalence 14

Factors influencing prevalence Number of new cases Duration of the illness If the disease is short, the prevalence is reduced The prevalence of sudden infant death = 0 (At a given instant, nobody has sudden infant death because the disease has no duration) If the disease is long, the prevalence is increased Rare lifelong disease can accumulate to build up a large prevalence Prevalence can be affected by a number of factors: The number of new cases and the duration of illness. Prevalence 15

Causes of increase of prevalence Long duration Low cure rate Low case fatality Increase in new cases Immigration of patients Improved detection Emigration of healthy people Once we have understood this principle, we can identify a number of factors that will increase the prevalence. Can you say how? Prevalence 16

Causes of decrease of prevalence Shorter duration High cure rate High case fatality Decrease in new cases Emigration of patients Improved cure rate Immigration of healthy people Once we have understood this principle, we can identify a number of factors that will decrease the prevalence. Can you say how? So you see, prevalence is an indirect reflection and it requires the understanding of numerous factors to be interpreted. Conclusion: Changes in prevalence may have many causes and may be difficult to interpret Prevalence 17

Uses of prevalence data Assessing health care needs Planning health services services Measure occurrence of conditions with gradual onset Study chronic diseases Prevalence data are useful when we want to estimate burden and plan resources accordingly. They are adapted to diseases of long duration. Prevalence 18

Incidence – (I) Number of new cases in a given period in a specified population Time, (i.e., day, month, year) must be specified Measures the rapidity with which new cases are occurring in a population Not influenced by the duration of the disease Now that we have seen prevalence, we can study incidence. Incidence is about new cases. Incidence 19

Cumulated incidence - (CI) Number of new cases CI = -------------------------------------------------- x 10n Population at risk at the beginning Also known as: Attack rate Assumes that the entire population at risk at the beginning was followed-up for the time period of observation This is the formula of prevalence. Again, incidence, like prevalence, should be calculated among those “at risk”. Those who had measles (and who are immune) before should be theoretically excluded from the denominator when we calculate the incidence of measles. Incidence 20

Source and type of incidence data Surveillance generate incidence data Incidence data are expressed as rates Number affected / Population / time Dynamic measure (speed) We saw that prevalence data come from surveys. Incidence data rarely comes from survey (unless you ask the survey participants about their recent past). Incidence data usually comes from cohort study or from surveillance data. Incidence is expressed as a rate to provide a dynamic figure of speed. Prevalence 21

Uses of incidence data Describe trends in diseases Evaluate impact of prevention programmes These are the use of incidence data. Incidence 22

The dynamic of incidence and prevalence New cases Incidence Prevalence Death Cure This graphs shows the relation between incidence and prevalence. Think of a bucket that gets water from a tap (new cases) and leaks (death or cure) at the same time. Incidence is the speed at which the tap is filling the bucket. Prevalence is the level of water in the bucket. Prevalence will go up if the tap flows faster of if the leaks is slower. Incidence and prevalence 23

The relation between prevalence and incidence Prevalence depends on Incidence (I) Duration of the disease (D) P = I x D Change in prevalence from one time period to another may be the result of changes in incidence rates, changes in the duration of disease, or both This intuitive understanding can be made into a mathematical formula. Incidence and prevalence 24

Patterns of incidence and prevalence High prevalence and low incidence e.g., Diabetes Mellitus Low prevalence and high incidence e.g., Common cold Here are example of disease with low incidence and high prevalence and with high incidence but low prevalence. Can you think of others? Can you find examples of diseases of high prevalence and incidence? Of disease of low prevalence and incidence? Incidence and prevalence 25

Incidence and prevalence Evolution of HIV prevalence in a country scaling up public health efforts Increase in HIV prevention Reduction in incidence (Difficult to measure) Increase in HIV AIDS care and support (treatment) Increase in disease duration (reduced mortality) Increase in prevalence (Easier to measure) Incidence measures the impact of prevention efforts Prevalence may be used to plan care and support The immediate consequence of the plan may be an increased prevalence This example illustrates how prevalence is complex. In a country scaling up HIV public health efforts, the first measurable outcome could be an increase of prevalence because of lower mortality. Incidence and prevalence 26

Crude mortality rate - (CMR) Number of deaths in a specified period CMR = ------------------------------------------------ x 10n Average total population Does not take into account factors such as age, sex, race, socio economic status, etc. Provides information on trends in a population’s health status Self explanatory. Mortality is in fact the incidence of death. Deaths 27

Disease specific mortality rate - (SMR) Number of deaths from a disease in a specified period SMR = ---------------------------------------------------------------- x 10n Average total population Reflect the impact of a disease on a population in terms of death Should not be confused with case fatality Likewise specific mortality is the incidence of death because of specific causes. Deaths 28

Case fatality ratio of a given disease Divide Number of deaths from the disease Number of cases of the disease Example: Measles outbreak 3 deaths 145 cases Case fatality ratio: 2.1% Don’t mix up with disease-specific mortality! Case fatality divides the deaths FROM A DISEASE by the number of cases of that disease. It reflects the severity of illness. Don’t mix it up with disease-specific mortality! 29

Take home messages Tell apart ratio, proportion and rates Prevalence is a static measure taken at a point in time Incidence is a dynamic measure taken over a certain time Mortality is calculated using population denominators to reflect burden while case fatality is calculated using cases as denominators to reflect severity These are the take home messages of the session. 30