Epidemiology MR OGUNDELE Epidemiology The word epidemiology comes

Epidemiology MR OGUNDELE

Epidemiology The word epidemiology comes from the Greek words epi, meaning on or upon, demos, meaning people, and logos, meaning the study of.

Epidemiology In other words, the word epidemiology has its roots in the study of what befalls a population. Many definitions have been proposed, but the following definition captures the underlying principles and public health spirit of epidemiology:

Definition of Epidemiology is the study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to the control of health problems.

Study Epidemiology is a scientific discipline with sound methods of scientific inquiry at its foundation. Basic epidemiologic methods tend to rely on careful observation and use of valid comparison groups to assess whether what was observed, such as the number of cases of disease in a particular area during a particular time period or the frequency of an exposure among persons with disease, differs from what might be expected.

Distribution Epidemiology is concerned with the frequency and pattern of health events in a population: Frequency refers not only to the number of health events, but also to the relationship of that number to the size of the population. Pattern refers to the occurrence of health-related events by time, place, and person.

Determinants Epidemiology is also used to search for determinants, which are the causes and other factors that influence the occurrence of disease and other healthrelated events.

Health-related states or events Epidemiology was originally focused exclusively on epidemics of communicable diseases but was subsequently expanded to address endemic communicable diseases and non-communicable infectious diseases.

Specified populations Epidemiologist is concerned about the collective health of the people in a community or population.

Application Epidemiology is not just “the study of” health in a population; it also involves applying the knowledge gained by the studies to community-based practice.

Historical Evolution of Epidemiology Although epidemiology as a discipline has blossomed since World War II, epidemiologic thinking has been traced from Hippocrates through John Graunt, William Farr, John Snow, and others. The contributions of some of these early and more recent thinkers are described below

Circa 400 B. C. Hippocrates attempted to explain disease occurrence from a rational rather than a supernatural viewpoint. In his essay entitled “On Airs, Waters, and Places, ” Hippocrates suggested that environmental and host factors such as behaviors might influence the development of disease.

John Graunt (1662) Another early contributor to epidemiology was John Graunt, a London councilman who published a landmark analysis of mortality data in 1662. This publication was the first to quantify patterns of birth, death, and disease occurrence, noting disparities between males and females, high infant mortality, urban/rural differences, and seasonal variations.

William Farr (1800) William Farr built upon Graunt’s work by systematically collecting and analyzing Britain’s mortality statistics. Farr, considered the father of modern vital statistics and surveillance. He concentrated his efforts on collecting vital statistics, assembling and evaluating those data, and reporting to responsible health authorities and the general public.

JOHN SNOW In the mid-1800 s, an anesthesiologist named John Snow was conducting a series of investigations in London that warrant his being considered the “father of field epidemiology. ” Twenty years before the development of the microscope, Snow conducted studies of cholera outbreaks both to discover the cause of disease and to prevent its recurrence. John Snow, an English physician, formulated and tested a hypothesis concerning the origin of an epidemic of cholera in London. On the basis of the available data snow postulated that cholera was transmitted by contaminated water through a then unknown mechanism.

JOHN SNOW He observed that death rates from cholera were particularly high in areas of London that were supplied with water by the Lambeth Company or the Southwark and Vauxhall Company, both of which drew their water from the Thames River at a point heavily polluted with sewage. Between 1849 and 1854, the Lambeth Company changed its source to an area of the Thames where the water was "quite free from the sewage of London. " Finally, Snow concluded that the source of cholera outbreak was contaminated water.

19 th and 20 th centuries In the mid- and late-1800 s, epidemiological methods began to be applied in the investigation of disease occurrence. At that time, most investigators focused on acute infectious diseases. In the 1930 s and 1940 s, epidemiologists extended their methods to noninfectious diseases. During the 1960 s and early 1970 s health workers applied epidemiologic methods to eradicate naturally occurring smallpox worldwide. This was an achievement in applied epidemiology of unprecedented proportions

19 th and 20 th centuries The 1980 s, epidemiology was extended to the studies of injuries and violence. In the 1990 s, the related fields of molecular and genetic epidemiology (expansion of epidemiology to look at specific pathways, molecules and genes that influence risk of developing disease) took root. Meanwhile, infectious diseases continued to challenge epidemiologists as new infectious agents emerged (Ebola virus, Human Immunodeficiency virus (HIV)/ Acquired Immunodeficiency Syndrome (AIDS)), were identified, or changed (drug-resistant Mycobacterium tuberculosis, Avian influenza).

Uses of Epidemiology q To make a community diagnosis. Epidemiology helps to identify and describe health problems in a community (for example, the prevalence of anaemia, or the nutrition status of children). q To monitor continuously over a period of time the change of health in a community. (for example, the effect of a vaccination programme, health education, nutritional supplementation). q To practice surveillance for a specific disease in order to be able to act quickly and so cut short any outbreak (example cholera).

Uses of Epidemiology q To investigate an outbreak of a communicable disease, analyze the reasons for it, plan a feasible remedy and carry it out, and monitor the effects of the remedy on the outbreak. q To plan effective health services. Effective services, interventions and remedies all depend on accurate community data.

Measure of disease frequency Setting priorities in public health planning for disease prevention depends on a set of conditions. Public health priorities should be set by the combination of how serious diseases are (a product of their frequency and the impact they have on those affected and society) and our ability to change their frequency or severity

Measure of disease frequency ctnd The risk of getting a disease is usually a function of time and these probabilities are estimated from the observation of populations. By observing the occurrence of diseases in populations over time we may be able to estimate incidence and prevalence of certain diseases.

Incidence The incidence of a disease is the number of new cases/onsets in a population within a specified period of time. It is “The number of new health-related events in a defined population within a specified period of time. May be measured as a frequency count, a rate or a proportion. ” [Porta 2008]

Incidence is Very helpful for etiological/causal inference Difficult to estimate Implies follow-up over time

EXAMPLE: There were 570 new cases of Ebola virus disease during 2014 in a city with a population of 8 million.

EXAMPLE Incidence = 570 cases per year Incidence rate = number of events in time period = 570 number in the population 8 x 106 = 0. 0000713 per year Incidence rate per 100000 persons per year = 0. 0000713 X 100000 = 7. 13 Therefore the estimated annual incidence rate (based on 2014 data) is 7. 13 per 100000 persons.

Cumulative incidence No. of individuals who get the disease during a certain period CI = No. of individuals in the population at the beginning of the period

EXAMPLE The population statistic of Efun District in 2011 revealed that there were 5, 572 women aged 20 -39 years who were sex workers. Record shows that 45 were HIV +ve during 2012 -2015. What is the cumulative incidence of HIV +ve among those women during a period of 4 years? Cumulative incidence = 45 / 5, 572 = 0. 008 or 0. 8%

Prevalence(P): Measures existing cases of a disease at a particular point in time or over a period of time. It is “A measure of disease occurrence: the total number of individuals who have an attribute or disease at a particular time (or period) divided by the population at risk of having the disease at that time or midway through the period. It is a proportion, not a rate. ” [Porta 2008]

PREVALENCE The prevalence of disease is the number of individuals in a population with a disease or other personal attribute. Prevalence rates are calculated in an analogous way to incidence rates and again often expressed per multiple (e. g. 1000, 10000 . . . ) of the population.

PREVALENCE Prevalence is Very helpful for quantifying disease burden (e. g. public health) Relatively easy to estimate Implies a cross-sectional design

Example A questionnaire was distributed to the workforce of a large industrial company on a particular working day. Of the 1534 workers, 178 reported headaches on the survey day. Prevalence=178 cases Prevalence rate (proportion) = 178/1534 = 0. 12 or 12 per 100 workers

INCIDENCE VERSUS PREVALENCE

INCIDENCE VERSUS PREVALENCE Prevalence: can be viewed as describing a pool of disease in a population Incidence describes the input flow of new cases into pool Deaths and cures reflects the output flow from the pool

Measures of Association The key to epidemiologic analysis is comparison. Occasionally you might observe an incidence rate among a population that seems high and wonder whether it is actually higher than what should be expected based on, say, the incidence rates in other communities. A measure of association quantifies the relationship between exposure and disease among the two groups.

Measures of Association Exposure is used loosely to mean not only exposure to foods, mosquitoes, a partner with a sexually transmissible disease, or a toxic waste dump, but also inherent characteristics of persons (for example, age, race, sex), biologic characteristics (immune status), acquired characteristics (marital status), activities (occupation, leisure activities), or conditions under which they live (socioeconomic status or access to medical care).

Measures of Association Examples of measures of association that will be discussed here are Risk ratio (relative risk), Rate ratio, Odds ratio, and

Risk ratio (relative risk) A risk ratio (RR), also called relative risk, compares the risk of a health event (disease, injury, risk factor, or death) among one group with the risk among another group. It does so by dividing the risk (incidence proportion) in group 1 by the risk (incidence proportion) in group 2

Risk ratio The two groups are typically differentiated by such demographic factors as sex (e. g. , males versus females) or by exposure to a suspected risk factor (e. g. , did or did not eat potato salad). Often, the group of primary interest is labelled the exposed group, and the comparison group is labelled the unexposed group.

Risk Ratio RR = Risk of disease (incidence proportion) in group of primary interest Risk of disease (incidence proportion, attack rate) in comparison group

Risk Ratio A risk ratio of 1. 0 indicates identical risk among the two groups. A risk ratio greater than 1. 0 indicates an increased risk for the group in the numerator, usually the exposed group. A risk ratio less than 1. 0 indicates a decreased risk for the exposed group, indicating that perhaps exposure actually protects against disease occurrence.

EXAMPLES: Calculating Risk Ratios Example : In an outbreak of varicella (chickenpox) in Oregon in 2002, varicella was diagnosed in 18 of 152 vaccinated children compared with 3 of 7 unvaccinated children. Calculate the risk ratio. Varicella noncase Total 18 134 152 unvaccinated 3 4 7 Total 138 19 Vaccinated 21

Example ctnd Risk of varicella among vaccinated children = 18 / 152 = 0. 118 = 11. 8% Risk of varicella among unvaccinated children = 3 / 7 = 0. 429 = 42. 9% Risk ratio = 0. 118 / 0. 429 = 0. 28 The risk ratio is less than 1. 0, indicating a decreased risk or protective effect for the exposed (vaccinated) children. The risk ratio of 0. 28 indicates that vaccinated children were only approximately one-fourth as likely (28%, actually) to develop varicella as were unvaccinated children.

Rate ratio A rate ratio compares the incidence rates, person-time rates, or mortality rates of two groups. As with the risk ratio, the two groups are typically differentiated by demographic factors or by exposure to a suspected causative agent. The rate for the group of primary interest is divided by the rate for the comparison group.

Rate ratio Rate Ratio =Rate for group of primary interest Rate for comparison group The interpretation of the value of a rate ratio is similar to that of the risk ratio. That is, a rate ratio of 1. 0 indicates equal rates in the two groups, a rate ratio greater than 1. 0 indicates an increased risk for the group in the numerator, and a rate ratio less than 1. 0 indicates a decreased risk for the group in the numerator

EXAMPLE: Calculating Rate Ratios Public health officials were called to investigate a perceived increase in visits to ships’ sickbay for acute respiratory illness (ARI) by passengers of cruise ships in Alaska in 1998. The officials compared passenger visits to ship sickbay for ARI during May–August 1998 with the same period in 1997. They recorded 11. 6 visits for ARI per 1, 000 tourists per week in 1998, compared with 5. 3 visits per 1, 000 tourists per week in 1997. Calculate the ratio.

Rate Ratio Rate ratio = 11. 6 / 5. 3 = 2. 2 Passengers on cruise ships in Alaska during May– August 1998 were more than twice as likely to visit their ships’ sickbay for ARI than were passengers in 1997.

Odds ratio An odds ratio (OR) is another measure of association that quantifies the relationship between an exposure with two categories and health outcome. The odds ratio is calculated as = {a/b} {c/d} = ad/bc Where a = number of persons exposed and with disease b = number of persons exposed but without disease c = number of persons unexposed but with disease d = number of persons unexposed: and without disease a+c = total number of persons with disease (case-patients) b+d = total number of persons without disease (controls)

Odd ratio Disease Exposure yes No Total Yes a b a+b No c d c+d Total a +c b +c a + b + c +d

Example Amongst 200 patients with Salmonella typhi, 40 had a recent history of urinary tract infection (UTI). By contrast in 120 normal individuals; only 12 had a recent history of UTI. What is the odd ratio? Exposure Yes No Disease yes No 40 12 160 108 Total a+b c+d Total 200 a + b + c +d 120

Solution The odds of exposure (to UTI) were therefore 40/160 or 0. 25 The odds of exposure of normal individuals 12/108 or 0. 11 Odd ratio=0. 25/0. 11=2. 27 The odds ratio of 2. 27 indicates that the odds of those with Salmonella typhi of having a recent UTI was more (twice those without Salmonella typhi).

Ratios, proportions, and rates Ratio A ratio quantifies the magnitude of one occurrence or condition to another. It expresses the relationship between two numbers in the form of x: y or x/y Example: -The ratio of males to females (M: F) in ABUAD -The ratio of male malaria patients to female malaria patients

Proportion A proportion quantifies occurrences in relation to the populations in which these occurrences take place. It is a specific type of ratio in which the numerator is included in the denominator and the result is expressed as a percentage. Example: The proportion of all births that was male Male births x 100 Male + Female births

EXAMPLE In a class of 100 with 60 women and 40 men The proportion of women =60/100 = 0. 60 The proportion of men =40/100 = 0. 40 The ratio of women: men = 3: 2 = 1. 5 The ratio of men: women = 2: 3 = 0. 67

Rate is the most important epidemiological tool used for measuring diseases. Rate is a special form of proportion that includes time. It is the measure that most clearly expresses probability or risk of disease in a defined population over a specified period of time, Rate = Number of events in a specific period x k Population at risk of these events in a specified Period

Example In the United States in 2002, a total of 15, 075 new cases of tuberculosis were reported. During the same year, 802 deaths were attributed to tuberculosis. The tuberculosis death-to-case ratio for 2002 can be calculated as 802 / 15, 075. To get the rate: Divide both numerator and denominator by the numerator 802/802=1 15075/802=18. 8 This yields 1 death per 18. 8 new cases.