Lecture 8 – Epidemiology
I. What is epidemiology?
Epidemiology – study of disease determinants, distribution and dynamics. From the Greek ‘epi’
meaning ‘upon’ and ‘demos’ meaning ‘people’.
Epidemic – temporally distinct disease; one that is ‘visited upon the people’.
Endemic – spatially distinct persistent disease; one that ‘resides within the people’
Pandemic – widespread disease; one that ‘resides in all people’.
The above terms are used when referring to humans. When referring to other animals, the
terms epizoology, epizootic, enzootic and panzootic are appropriate.
II. Disease determinants – methods for determining the causative agent of disease
A. Koch’s postulates – first attempt at a method to establish the microbial cause of diseases.
However, it does not work for pathogens other than cultivable bacteria. Additionally, many
pathogenic bacteria are found in healthy asymptomatic hosts (e.g. polio or cholera)
1. Microorganisms must be found in abundance in all organisms suffering from disease,
but not found in healthy organisms
2. The microorganism must be isolated from the diseased organism and grown in culture
3. The cultured microorganism should cause disease when introduced into healthy
4. Microorganisms must be isolated and cultured anew from newly diseased organism
B. Modernized postulates – Hill attempts to create postulates without the weaknesses of Koch’s
C. Koch’s molecular postulates – Koch’s postulates envisioned for the age of molecular biology.
III. Disease distribution – mapping methods to determine source / spread of causative agent
A. Spatial mapping of disease prevalence is a cornerstone of modern epidemiology.
1. Cholera
a. Caused by bacterium Vibrio cholera and transmitted by water. Induces
diarrhea and vomiting. High mortality if untreated.
b. London epidemic – John Snow mapped distribution of cholera infections in
London. Determined that disease source of a single water pump, suggesting that
the disease was transmitted by water and not air as previously thought.
c. broad street water pump had the handle removed to stop further
2. Bird flu
a. phylogeny (a form of temporal mapping) allowed the determination of human
disease source – chickens in Hong Kong
b. Phylogeny also allowed the identification of how the disease was transmitted
to wild fowl, identifying a large migratory bird lake in Guangdong province in
Lecture 8 – Epidemiology
c. By linking modern phylogenetic technique with spatial mapping, bird flu
spread to the rest of the world was minimized.
IV. Dynamics
A. Modern epidemiology seeks to understand how epidemics unfold and how diseases are
maintained endemically within populations.
B. Early attempts at understanding how epidemics unfold
1. Small pox epidemic – small pox cuased by Variola major and Variola minor viruses
and is transmitted via the air. Mortality rate of V. major is 35%. Immunity can be
induced via variolation, which involves inhaling dried scabs from infected patients.
Latter, vaccine developed from a related disease, cow pox. This was the first vaccine
ever developed and small pox is the first disease ever to be eradicated via vaccination.
2. Daniel Bernoulli was a Swiss mathematician and physicist who performed one of the
first epidemiological analyses of disease dynamics. Using the small pox epidemic of
London, he created three groups of individuals; those that were susceptible to the
disease, those that were infected and those that had recovered and were immune. He
found that by simply vaccinating a small proportion of the population would provide a
large benefit to the susceptible population.
C. Modern attempts to understand epidemics involves epidemiologic modelling
1. SIR models – compartmental models that allow the progression of epidemics in large
populations to be modelled. The most common of which is the SIR (Susceptible Infected
Recovered). See PowerPoint for equations.
a. General SIR models assume density dependence in disease transmission and
infection via mass action. Mass action states that all individuals meet within a
population meet at random and in proportion to their numbers.
b. SIR models predict that diseases can be maintained endemically with high
birth rates (or immigration rates). Otherwise, diseases are prone to fadeout (i.e.
extinction of parasite post epidemic).
c. SIR models predict that short lasting immunity of recovered population can
help sustain an epidemic.
d. SIR models predict high virulence can lead to fadeout.
2. Conditions by which parasites can persist in a population can be predicted by I(hat).
a. increased background host mortality allows the parasite to persist in high
Lecture 8 – Epidemiology
3. Minimum population size of susceptibles need for parasite to establish is provided by
4. Minimum number of vaccinated susceptibles needed to eradicate a parasite is given
by Pcrit.
D. Parasite persistence – ways in which a parasite can persist if it runs out of susceptible hosts.
1. Carrier state – continued presence of organism in host that causes no symptoms.
Example – Typhoid Mary.
2. Parasite latency – parasite lays dormant in host for extended period of time, resulting
in cyclic outbreaks or epidemics.
3. Biological reservoirs – parasite is endemic in one species, but causes periodic
epidemics in another species. Examples are rabies in jackals and Ebola in humans.
4. Extensive incubation periods – beneficial when host mortality rates are low or when
alternative biological reservoirs are absent. Example – Transmissible spongiform
5. Environmental reservoir – some pathogens can exist outside of a host for extended
periods of time. Examples – endospores.
6. Metapopulation structure – subdivided host population can allow parasites to cycle
between populations. Subdivisions may arise socially, spatially or temporally.
E. Extensions of SIR models – SIR models are often unrealistic. However, they can be modified to
accommodate a variety of circumstances.
1. Type of parasite (e.g. macroparasite versus microparasite).
2. Population structure
3. Latency period
4. Immunizations
5. Transmission mode
6. Network connectivity
7. Spatial heterogeneity
8. host heterogeneity
9. within host dynamics.

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