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PUB 540 Role of Individuals in Shaping Contemporary Epidemiology

As health care providers try optimizing health care delivery, they need to use data-driven
knowledge. In this case, they must understand a disease’s particulars in detail to be in a position
to intervene appropriately. Epidemiology, which evolves progressively, deals with studying the
distribution and determinants of health-related matters. It mostly deals with events and issues
while targeting specified populations. Over time, key individuals and historical events have been
instrumental in shaping the field of epidemiology diversely. The contributions of James Lind,
Ignaz Semmelweis, and John Snow are immense in epidemiology, and their epidemiological
methods are still relevant.

James Lind

When examining the emergence of experimentation in epidemiology, James Lind’s role
was immense. As an 18th century physician, James Lind's epidemiology contributions were
triggered by the emergence of scurvy as a major problem among sailors (Lamb, 2018). At this
time, the cause and risk factors of scurvy were not known, and only guesses were made
regarding the causes. As Lee (2019) further mentioned, scurvy causes were linked with
indigestible food, congenital laziness, and bad air. From Lind’s perspective, the sailors’ diet was
the issue due to poor quality, but more details were necessary.
To advance epidemiological methods, Lind experimented with patients suffering from
scurvy. As Lamb (2018) explained, Lind took part in experimental epidemiology where
populations were divided into groups and subjected to different treatments. Each group was
allocated a specific exposure, and the outcome observed. As a major characteristic of many
experimental studies today, James Lind has a control group of patients who were not subjected to

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the treatment. By comparing outcomes between groups, the qualitative study demonstrated the
need for placebos in health-related experiments. In this case, it would be impractical for a
researcher to use one group to assess and deduce a study's outcomes.
Ignaz Semmelweis
Ignaz Semmelweis’ concentrated on examining the cause and treatment of illnesses. As
Leigh (2018) mentioned, Ignaz Semmelweis was instrumental in discovering hand washing as a
way of preventing illness transmission. His research was on childbed fever, which claimed the
lives of many women in the 19th century. According to Gakuu (2016), Semmelweis was
concerned about women’s mortality rate from childbed fever. He observed that women under the
care of physicians when delivering had a higher mortality rate than those under midwives (Davis,
2015). Given this, he hypothesized that handling corpses before attending to pregnant women led
to the fever, and hand washing could prevent transmission.
To advance epidemiology, Semmelweis took part in an experiment where he initiated a
mandatory hand-washing policy and sanitization programs. Doctors and midwives were the
primary subjects to assess whether childbed fever could be prevented by improved hygiene
(washing). According to Leigh (2018), the results did not disappoint, given that the mortality rate
fell from 18% to 2% among doctors and reached as low as 1% in midwives after they started
washing medical instruments. By design, Semmelweis engaged in an empirical study where
results are not based on an assumption.

John Snow

John Snow’s contribution to epidemiology was immense as well. When cholera was
claiming many lives, John Snow conducted several investigations of cholera outbreaks to

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understand the cause and possible prevention. As Friis and Sellers (2020) posited, Snow’s
investigations demonstrate the development of hypothesis testing from descriptive epidemiology.
His main experiment was after a cholera outbreak in Golden Square of London in 1854.
According to Yan and Chowell (2019), Snow believed in spot mapping to identify the cause of
the cholera outbreak. After identifying the source, interventions follow while responding to
specific elements of the illness.
A study starts with a basic assumption, and this study was not different. Snow assumed
that water was the source of cholera’s infection, and samples from different pumps in the Golden
Square area could reveal where the problem started. As Friis (2017) explained, Snow gathered
data from people with cholera while asking them where they obtained their water. After
summarizing his findings, Snow identified the pump where most infected people obtained their
water. Its closure ended the outbreak. Largely, Snow’s study typifies an empirical study where
the researcher collects data from the field to prove or disprove the hypothesis.
Informing the Definition of Epidemiology

The definition of epidemiology is broad, and several elements from these studies helped
to inform the definition. These individuals depict illness identification as a scientific and data-
driven process that is concerned with health-related events. Moreover, they targeted some
populations, resembling the present day’s view of epidemiology to study health issues in specific
populations. As experimental studies, it is right deducing that these individuals used qualitative
and quantitative data collection methods. On testing the hypothesis, they used the standard
approach. After identifying the hypothesis, a sample is analyzed, leading to rejection of the null
hypothesis's validation based on the outcome of the analysis. A perfect example is Semmelweis’s

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study proving that hand-washing could reduce infections from childbed fever, and it turned out
to be so (validating the hypothesis).

Application of Similar Epidemiological Methods

The researchers’ approach to a disease’s cause and control has been used in many health-
related scenarios for a long time. Experimentation morphed into randomized trials where
placebos usually serve as the control. Today, experimentation is used to assess the cause and
possible control of the cardiovascular disease. There is an assumption that people’s changing
lifestyles and shifts in dietary habits could be the primary cause. This assumption acts as the
hypothesis to be tested while comparing different groups, imitating the methods that Snow,
Semmelweis, and Lind used.

Research Studies used to Understand Risk Factors

Heart problems have troubled people for a long time, and research studies to understand
its risk factors have been done in the past. A suitable example is the cardiovascular disease and
the Framingham Heart Study by Drawber and colleagues in 1950. According to Hajar (2016),
this study found that cigarette smoking, high cholesterol, and increased blood pressure are
leading risk factors for heart disease. Another key research study is the risk stratification for
sudden cardiac death. As Detai et al. (2018) explained, this study found that relieving the
obstruction in hypertrophic cardiomyopathy (HCM) can reduce sudden death. Such experimental
studies like those that John Snow, Lind, and Semmelweis carried out help understand risk factors
of illnesses and possible control.
Undeniably, the best way to deal with an illness is to understand its causes and risk
factors. If the cause is known, control is known since interventions focus on specific aspects of

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the illness. Experiments by John Snow, James Lind, and Ignaz Semmelweis show how
quantitative and qualitative methods guide in illness control. These individuals advanced
epidemiology by making it a systematic and scientific study that focuses on health matters
affecting specific populations.

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References

Davis, R. (2015, Jan 12). The doctor who championed hand-washing and briefly saved lives. npr.
https://www.npr.org/sections/health-shots/2015/01/12/375663920/the-doctor-who-
championed-hand-washing-and-saved-women-s-lives
Desai, M. Y., Smedira, N. G., Dhillon, A., Masri, A., Wazni, O., Kanj, M., … & Lever, H. M.
(2018). Prediction of sudden death risk in obstructive hypertrophic cardiomyopathy:
potential for refinement of current criteria. The Journal of thoracic and cardiovascular
surgery, 156(2), 750-759. https://doi.org/10.1016/j.jtcvs.2018.03.150
Friis, R. H. (2017). Epidemiology 101. Jones & Bartlett Learning.
Friis, R. H., & Sellers, T. (2020). Epidemiology for public health practice. Jones & Bartlett
Learning.
Gakuu, L. N. (2016). Ignas Semmelweis: the doctor who championed hand-washing. East
African Orthopaedic Journal, 10(2), 43-44.
https://www.ajol.info/index.php/eaoj/article/view/149036/138538
Hajar R. (2016). Framingham Contribution to Cardiovascular Disease. Heart views : the official
journal of the Gulf Heart Association, 17(2), 78–81. https://doi.org/10.4103/1995-
705X.185130
Lamb, J. (2018). Scurvy: The disease of discovery. Princeton University Press.
Lee, W. J. (2019). Vitamin C in Human Health and Disease: Effects, Mechanisms of Action, and
New Guidance on Intake. Springer.
Leigh, A. (2018). Randomistas: how radical researchers are changing our world. Yale
University Press.

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Yan, P., & Chowell, G. (2019). Quantitative methods for investigating infectious disease
outbreaks (Vol. 70). Cham, Switzerland: Springer.

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