In 1853 William
Farr introduced standard nomenclature for causes of death. In 1946 WHO introduced an International Classification of Diseases,
Trauma, and Cause of Death (ICD). Disease classification is useful for explanation & description, prediction of disease
course, prognosis, planning treatment, and disease prevention. Manifestational, causal, abstract, operational/pragmatic criteria
are used in disease classification. In classification is based on etiologic agent, disease process, organ system, transmission,
and portal of entry.
answers the what, why, when, how, where, and who of a disease. Time can be described
as calendar time (on the interval scale) or cohort time (on the ratio scale). Time trends are biorhythmic, periodic (monthly,
annual, seasonal), linear, and curvilinear. Diseases are acute (<3 months), sub-acute, and chronic >3 months). Natural
history is progression from susceptibility; sub-clinical disease; clinical disease; and recovery, disability, or death. Time
intervals are induction (causal action to disease initiation), incubation, and latent periods (disease initiation to disease
detection). Disease is described by place (as rural, urban, sub-urban, and slums/shacks (septic fringe), boundaries (political
and natural), institution (hospital, home, school, factory, farm, and outer space). Individual variation is by heredity, age,
sex, SES, marital status, and ethnicity/race.
interactions can be described as clustering, disease outbreaks, epidemics, endemics, and pandemics. Clustering is excessive
concentration of events at a point in time or a place. A disease outbreak is excessive disease occurrence of a lesser degree
than an epidemic. An endemic disease has high prevalence in an area. An epidemic is excessive incidence over a brief period
of time. A pandemic is an epidemic affecting several countries. A point source epidemic originates from one person or place.
A common source epidemic has more than one origin. In epidemic progression new infections occur after the initial ones. An
epidemic is visible when cases are few but the disease is rare, case number is large, disease is distinctive, swift shift
from non-epidemic to epidemic status is swift, and disease duration is short. The occurrence of an epidemic can be ascertained
by changes in trend over time, comparing incidence in epidemic and non-epidemic places, and comparing disease incidence among
population sub-groups of the same country. Investigating an epidemic consists of establishing the diagnosis, case definition,
determination is made whether an epidemic exists, characterizing the epidemic by place, time, and person, drawing a spot map
showing cases, computing incidence rates by location, identifying clusters, developing hypotheses about the source and route
of infection, testing the hypotheses laboratory and case control studies. Control measures are then instituted and may include
sanitation, prophylaxis, diagnosis and treatment, and vector control. Surveillance is continued in the post epidemic period.
An epizootic is an epidemic disease in animal populations. Epizootics can become
epidemics in human populations. An enzootic is an endemic disease among animals. An epizoodemic is an epidemic involving both
human and animal populations.
rate (IR) = incident number/ total person-time. Cumulative incidence = incident number / susceptible population at the start.
Prevalence proportion = # cases of illness at a particular time (old and new) / # of individuals in the population at the
same time. Prevalence can be point, period, and lifetime prevalence. Prevalence proportion = incidence rate x average duration
of disease. Prevalence is useful for administrative purposes. It is not used for etiological studies because the time sequence
is not obvious. Prevalence changes due to changes in incidence and duration. Excess disease risk is measured as an absolute
effect (Rate Difference or Risk Difference) or a relative effect (Relative Risk, Rate Ratio, Risk Ratio, Prevalence Ratio,
Cumulative Incidence Ratio, Incidence density Ratio, Odds Ratio, and Standard Mortality Ratio). The following interpretations
of the odds ratio and risk ratio are used – up to 0.3 strong benefit, 0.4
– 0.5 moderate benefit, 0.6 – 0.8 weak benefit, 0.9 – 1.1 no effect, 1.2 –1.6 weak hazard, 1.7 –2.5
moderate hazard, and >=2.6 strong hazard. OR values range from 0 to infinity.
OR is a good estimator of risk ratio if the disease is rare and the cases and controls are randomly selected from the population.
The proportion of disease due to a particular exposure is measured by various parameters of attributable rate (AR)
that take into consideration the population at risk. Proportional mortality studies are used to compare the proportion of
deaths among the exposed to the proportion of deaths among the non-exposed. A common measure of disease impact is the years
of potential life lost (YPLL). The Kaplan-Meier formula helps compute the survival proportion over several consecutive time
identification is by symptoms, signs (clinical, laboratory, radiological), observation (direct & indirect, passive &
induced), indirect marker of abnormality, and response to a therapeutic. Case definition uses clinical criteria, underlying
pathology, epidemiologic, and logical criteria. Definition of the abnormal is based on four considerations: statistical, clinical,
prognostic, and operational. There is observation error in symptoms and measurement error in signs. Signs can be pathognomonic,
non-specific, qualitative, or quantitative. A syndrome is a complex of symptoms
and signs. Tests are an extension of clinical examination for signs. Validity is when a test measures what it is supposed
to measure. Sensitivity, specificity, and predictive value are measures of validity (accuracy). Sensitivity is a measure of
the strength of association. Specificity measures the uniqueness of association. We can talk of tests as True positives; True
negatives; False negative; and False positives. There is a trade-off between specificity and sensitivity. High sensitivity
is associated with low specificity & vice versa. High specificity is associated with low sensitivity & vice versa.
True/correct diagnosis is based on high specificity (with low or high sensitivity). Ability of a test to predict true diagnosis
is measured as the positive predictive value (detection of disease) and the negative predictive value (correct indication
of absence of disease). High prevalence of disease increases PV+ve. Reproducibility consists of repeatability, consistency,
reliability, and stability.
Follow-up studies are used to
study prognostic factors using case fatality rates, survival (5-year survival rates, the survival curve, median survival time,
relative survival, and comparison of actual with expected survival), and life table analysis. The matching of discharge information
with death certificates can also be used to study prognostic factors.