Week 1 - Introduction to Public Health and Epidemiology
Monday, 24 July 2023
2:18 PM
Week 1: An Introduction to Public Health and
Epidemiology
ONLINE LECTURE:
This week we have two lecture slide presentations. The topics are quite related this week.
The first series of lecture slides covers introductory concepts and principles of
epidemiology.
We begin by defining what epidemiology is and how it differs from other health research areas
which are focused on disease at the molecular or individual level. We introduce the notion of
the Natural History of Disease and introduce the notion of prevention at various stages of
disease; we will discuss this in more detail later in the course. At a general level, we then
consider various causes or mechanisms which allow diseases to spread and we consider the
factors related to the host, agent, environment and vector. We briefly discuss the importance
of major public health initiatives, such as immunisation and sanitation on improving population
health and finally consider the importance of epidemiologists in maintaining surveillance to
ensure there are limited negative impacts on our health.
You can download a pdf copy of the slides for Lecture 1.1 here.
A black and white version of the Lecture 1.1 pdf is available here.
You can listen and watch Lecture 1.1 here.
The second series of lecture slides begins to introduce more objective measures by which
we can assess how healthy the public is, including YLL, YLD and DALYs. Don't know what
they are? Then listen to the lecture!
We then consider how addressing communicable diseases in particular has led to increased
life expectancy around the globe and here in Australia. A bulk of the lecture also focuses on
disease burden in Australia. Most good epidemiology textbooks are 'American' or European
focused, so i will supplement the textbook material with Australian examples throughout the
course.
You can download a pdf copy of the slides for Lecture 1.2 here.
A black and white version of the Lecture 1.2 pdf is available here.
You can listen and watch Lecture 1.2 here.
Incidence (and Cumulative Incidence) and Prevalence are related concepts that reflect the
extent of an illness/disability within the community.
Simply:
Prevalence refers to the proportion (or %) of a population with a disease at a current moment
of time.
Incidence refers to the number of new cases (or reflected as a %) in a period of time (day,
week, month, year).
Cumulative Incidence refers to the cumulative number of new cases (or also reflected as a
%), but there is no specific time frame. For example it could be the number who have
contracted a virus since the a pandemic related to the virus was first notified.
So, as an example, let's consider COVID-19. Now, i did admit, in one of the tutorials when i
was asking for an illness/intervention we could do the practice literature search, with i
emphasised that I loathed discussing COVID-19; it is still an ongoing issue, there is still so
much we don't know, and as I mentioned, approximately 75% of pre-print studies never made
it passed peer-review. So not the best topic to bring into an introductory course. BUT, during
the height of the pandemic, we were all paying close attention to the weekly graphs that
summarised these concepts.
So let's look at the COVID numbers in Australia. There are many sites, but all generally are
informed by publicly available data.
One i like is Worldometers: https://www.worldometers.info/coronavirus/country/australia/
Face-To-Face Lecture:
The face-to-face lecture for this week will led by me (Richard) on Monday 24th of July,
4-6pm.
I will first provide an overview of the course. Specifically, we will cover:
1. Who I am and how you can contact/find me
2. Course resources
3. Overview of course topics
4. Overview of the seminar activities
5. Overview of assessment activities and assessment criteria
6. Detailed recommendations on how to succeed on the assessment activities!
7. Critical appraisal skills
8. Referencing and Plagiarism
After we've done all of that, we will be set for a cup of tea, a bex and a lie down...
But first we'll finish with a short video clip of English historian sitting in a pub drinking a beer
talking about John Snow.
Who is John Snow???
You can download a pdf copy of the slides for the Seminar here after the lecture.
And a copy of the lecture recording here.
And for your ease, I've placed a separate link to the short video we will watch on John Snow
here.
In addition I have three short animation videos which provide a short background on who
John Snow was, the development of his thinking/methods, and a little more detail about the
Broad Street Pump here:
Video 1
Video 2
Video 3
Enjoy!
TUTORIALS:
In the tutorials this week we will randomly assign which tutorials you will present your oral
presentations. So it's important to be there!
We then will cover how to do effective oral presentations.
From <https://wattlecourses.anu.edu.au/mod/page/view.php?id=2958509>
1.1 Basic Epidemiologic Concepts and Principles
e.g., genetics
e.g., risk-taking behaviours
This requires an understanding of the above factors, too
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Of particular relevance are the graphs: Total Cases (from which we can derive cumulative
incidence), and Daily cases (which reports daily, 3 and 7 day incidences).
As of 9am this morning:
There were 10,851 active cases in Australia. This reflects a prevalence of .04% of Australia's
population (estimated to be 26,457,567).
The 7-day incidence as of 29 July 2023 was 749 - that is the incidence rate over the last 7
days was 749 out of 26,457,567 million Australians (or .003% of the population)
The cumulative incidence is the total number of the population who have have reported
COVID-19, this is the summation of past infection and current infection which as of 29 July
2023 was 11,731,399 out of 26,457,567 Australians (or 44.3%).
ONE CAVEAT: the cumulative incidence is usually reflecting the number of NEW incidences
and my understanding that the reporting of the cumulative graphs of COVID-19 is that they
reflect the cumulative number/incidence of NEW cases. So if you've had COVID-19 twice or
thrice, or 10 times, you will only be reflected in this cumulative graph once.
Hoping this helps, and as i say the graphs really go someway to visually explaining these
differences.
If that hasn't helped, another website provides another discussion/example:
https://sphweb.bumc.bu.edu/otlt/MPH-Modules/EP/EP713_DiseaseFrequency/EP713
_DiseaseFrequency4.html
From <https://wattlecourses.anu.edu.au/mod/forum/discuss.php?d=887314#p2351990>
(pollution)
Natural history of disease:
1. Stage of susceptibility
2. Exposure leads to pathological changes
3. Stage of subclinical disease (asymptomatic; diagnosis may be possible with
advanced testing)
4. Onset of symptoms in the stage of clinical disease (diagnosis can occur)
5. Stage of recovery/disability/death
If you understand the aetiology, you can prevent it
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--> But may be apparent in testing
e.g., through exercise and diet
Can be managed by changing diet and exercise, possibly taking medications
Thus requiring medical (e.g., surgical and pharmaceutical)
intervention to prevent disease progression
Social factors (purdah) lead to change in biology (no sunlight --> no vitamin D), which
can lead to disease (osteomalacia)
4 factors that underly the development of disease:
1. Host factors
○ Susceptibility
2. Agents of disease
○ Biological/chemical/physical
3. Environmental factors
○ Humidity/weather/herd-immunity/hygiene of water/overpopulation
4. Vectors of disease
○ Usually some insect/animal
○ Not always needed
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Rates per 100,000, which is important before the actual population numbers are
different. Hence, these rates are more comparable
Note the high rates in the southeast
Note the high rates in the southeast
Growing it and smoking it
Low tobacco tax, although only the southeastern ones have the high rates of lung
cancer
High taxes
and low lung
cancer
Hence, it may seem that there are multiple causes (both social and environmental) for
the lung cancer distribution
- Whilst this may be true, we should also consider the time lag between smoking
and the development of lung cancer
○ For example, in Florida, it is possible that taxes were raised in response to
the high prevalence of lung cancer, but the incidence hasn’t dropped yet
because it takes a while
Florida have high taxes but high lung cancer rates
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--> increased population and disease spread
~12.5%
Unintended consequences!
Once epidemiologists identify the
cause of disease, they can suggest
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Once epidemiologists identify the
cause of disease, they can suggest
policies and programs to prevent
them
Are the advertisements too confronting? May be effective in stopping the spread of
certain diseases, but could this have been achieved without causing as much distress?
The true epidemiology of a disease is only
apparent with extensive surveillance, due to
asymptomatic cases and unreported cases
-----------------------------
1.2 Introduction to Public Health
An early and famous definition of public health:
"Public health is the science and the art of preventing disease, prolonging life, and
promoting physical health and efficiency through organized community efforts for
the sanitation of the environment, the control of community infections, the education
of the individual in principles of personal hygiene, the organization of medical and
nursing service for the early diagnosis and preventive treatment of disease, and the
development of the social machinery which will ensure to every individual in the
community a standard of living adequate for the maintenance of health. (...) I look to
see our health departments in the coming years organizing diverse forms of sanitary and
medical and nursing and social service in such fashion as to enable every citizen to realize his
birthright of health and longevity.
~ Charles-Edward Amory Winslow
• Promote health
• Prevent disease
• Socially-governing policy
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This statistic (increasing life expectancy) is often used as an
indicator of good public health policy and to demonstrate the
efficacy of population health interventions such as vaccinations,
access to universal health care, access to highly nutritious food
and attempts to address environmental pollution.
More people make it to 65 because infant mortality dropped
In addition to improved infant mortality rates, general death rates have ALSO improved
More than halved!
Side note… LE figures may be inaccurate. They represent our current knowledge.
However, the future rates depend on many factors that we cannot accurately account
for in our calculations. Especially relevant is the increase in rates of diabetes and
sedentary lifestyles, which may be impairing LE more significantly than the current LE
figures reflect.
The changing mortality figures do not only reflect public health initiatives and medical
advancements, but also the age of the population. We see that, today, birth rates in
developed countries are lower but people are living longer, leading to an aging
population. This is reflected by the kinds of diseases that affect the population the most
which tend to be age-related. That being said, the trends over the years indicate areas
where improvements have been made; whether in public health or medical
advancements. CVD mortality rates have declined, whereas cancer mortality rates
have remained somewhat stable. Hence, despite high MORBIDITY rates for each of
these age-related diseases, the MORTALITY rates have changed in different ways;
suggesting that the burden of disease of cancer has remained similar but burden from
CVD has declined. This may reflect the public health and medical advancements in
those fields; perhaps suggesting that CVD treatments have improved more
substantially.
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What's the life expectancy limit (LE)?
- Notice that life-expectancy at birth increased more than LE at age 65, suggesting
improvement in infant mortality, but not as significant improvement at the "top of
the range"
- Why? Is there a set biological limit or is there an issue with our approach to
medicine? An issue with our public health approach? Some combination?
Something else - like new diseases, comorbidities, etc.?
Limitations of LE:
- Living longer doesn’t equate to living a better life. May be living longer but have
many disabilities that make the quality of life abysmal
○ Quality of life is measured separately, and can be used to adjust LE to
disability-adjusted life years
- YLD are higher in younger ages and peak around 60-64 years of age, at
which point they begin to decline
○ Disability burden (YLD) is low in childhood because not many children
have disabilities, as disabilities are more likely to appear as people
age due to lifestyle diseases and mental health disorders that are
diagnosed later than childhood
○ Higher in younger because, if you develop a disability early on (which
does not lead to mortality right away), then there will be many years
during which you live with a disability (i.e., high YLD)
○ Also, as you continue living, the chance of experiencing disability
increases, so you will live more years with disability (increasing YLD)
○ Eventually, YLD decreases because disabilities that develop later in
life may either be more likely to kill you (i.e., don’t live with the
disability for a while; lo YLD) or the person simply nears their life
expectancy, hence they will not continue living with the disability for
many years (lower YLD)
- YLL increase gradually and peak around 80-84 years of age, at which point
they begin to decline
○ The decline is attributed to the lower number of people who make it
to that age and the fact that there are fewer number of years to be
lived (thus less years to be lost) as your age nears the age of death
• Congenital abnormalities no longer in top 10 when in age groups35 -44 and above.
Why? Not because all of them die by 35, but because living to age 35 despite a
congenital abnormality means that your chance of dying from it is lower (lower
compared to other causes of death)
• Unintentional injuries are a leading cause in younger age because the age -related
causes of death are not as prevalent, and may potentially reflect risk -taking
behaviours that are more prevalent in younger individuals
• Death by suicide declines with age (see next slide)
Proportion of deaths vs rate per 100k produce different patterns
Whilst rates of suicide are higher in the older
population, they comprise a smaller
proportion of the deaths because the older
population have higher mortality rates from
other factors, whereas it is closer to (if not
the) leading cause of death for the younger
individuals.
It is important that these rates are
standardised to be per 100,000, such that
we can make meaningful comparisons
between different demographics
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i.e., despite the suicide rates being
higher in 85yo males than 25yo
males, the death rates due to suicide
is higher amongst the 25yo males is
higher. This is because the 85yo
males have many other causes of
death, meaning that these other
causes of death contribute to the
majority of death. On the other hand,
amongst the 25yo, there are less
other causes of death, so the suicide
contributes to a greater portion of
death (right)
Black male LE increased at a higher rate, but still lower than the other groups
--> and determine their efficacy in order to inform changes
--> data collection can be used in electronic healthcare records
--> to inform travel restrictions and vaccination advice and antibiotic usage
--> to direct interventions, investments, and policies
Cause of death recorded can be erroneous!
+ hospitalisations (rates and reasons)
--> mainly related to access (e.g., to medical services and green spaces)
Risk-taking behaviour may be contributing to this - like driving. Policy implementation
related to drink-driving and seatbelts have helped lower mortality rates
These are actions that prevent injuries. Addressing driver attitude and knowledge.
Behaviours include alcohol intake - policies may address alcohol laws and social
factors that lead to: access to alcohol, alcohol usage, access to transport instead of
drinking and driving. We can control behaviour on the road using traffic measures.
These are actions that limit the severity of the injuries. We can control safety of the
vehicle with safety checks and requirements in manufacturing. We can implement laws
for seatbelt-wearing, and for their availability in cars. Traffic measures can also be
used (whereas stop signs prevent injuries, guard rails can prevent serious injury).
There are actions to maximise the recovery of the injured individuals. For example,
making it compulsory for every learner driver to be proficient in first aid. Also includes
access to fast and effective trauma response.
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