John Snow’s Cholera Breakthrough

Describe the situation that led to Snow’s discovery of the cause of cholera

The debate surrounding the source of cholera dominated the public in the eighteen century. The miasma theory was championed by Dr William Farr and seemed to have gained popularity during the 1850s. According to Dr Farr cholera was caused by bad air arising from decayed organic matter or miasmata. In one of the publications, Dr Farr alluded that Cholera was more concentrated in areas of low elevation such as near the banks of River Thames where the concentration of such decayed miasmata was high compared to areas of high elevations.

However, the germ theory seemed to be based on scientific analysis, case studies and graphical presentations. The works of the germ theory were mainly attributed to Dr John Snow, a reputable physician with extensive knowledge in anaesthesia and use of chloroform at that time. The germ tests of the germ theory emerged during the second cholera epidemic which occurred in London in 1848-49 and was proceeding the first documented cholera epidemic in London which occurred in 1831-32. Following the second epidemic, Dr Snow and other cohorts formed the London Epidemiological society with a view of advising the government on the measures of combating the disease.

Dr Snow conducted two classic studies which were conducted during the third epidemic which occurred in London from 1853 to 1855. In the first study, Dr Snow used skilled reasoning, graphs and maps to examine the contaminated water that came from the Broad Street pump outbreak in the Soho Neighbourhood in 1854. This was in a bid to support the fact that cholera was caused by a microbe-like germ that was spread through faecal contact, contaminated water and soiled clothing. The second study involved the “grand experiment, also in 1854 and was focused on comparing the London neighbourhood receiving water from two companies. In this study, one company sourced water from upper river Thames that was located far from contamination while the other company sourced its water in the heart of London with contamination from sewage quite common. In his findings, Dr Snow demonstrated the impact of contaminated water on the people. However, it was until 1883, twenty-five years after the death of Dr Snow, when Robert Koch, a German physician discovered vibrio cholera, an organism causing cholera that Dr Snow’s works gained recognition in the eyes of the public.

References

• Centre for Disease Control and Prevention(CDC) (2004): Laboratory Methods for the Diagnosis of Vibrio Cholerae: Isolation of Vibrio. Centers Dis Control Prev [Internet]; Available from: http://www.cdc.gov/cholera/pdf/laboratory-methods-for-the-diagnosis-of-vibrio-cholerae-chapter-4.pdf
• Hempel S (2007): The strange case of the broad street pump; John snow and the mystery of Cholera. Department of epidemiology, University of California, Los Angeles. http://www.ph.ucla.edu/epi/snow/strangecase.html
• Johnson S (2007): The ghost map; the story of London's most terrifying epidermic- and how it changed science, cities and the modern world, Department of epidemiology, University of California, Los Angeles. http://www.ph.ucla.edu/epi/snow/ghostmap.html

Describe the processes involved in the ‘Scientific Method’

The scientific method of enquiry involves a documented process directing the empirical evaluation and presentation of findings.

Formulation of a Question: scientific examinations are based on a particular topic. This topic is largely guided by a particular question that seeks to be answered through empirical research. In this case, questions can arise from the specific observations or open ended in nature. In most cases, questions arise from the researcher’s experience, or findings from other reports and previous experiments and the works of other scientists. The commonly known as research question is very crucial when applying scientific method and determines the outcome of investigations

Hypothesis: a hypothesis, also referred to as conjecture is identified during the formulation of the question and often explains a given behaviour. The hypothesis is designed to convey a particular form of assertion that is either affirmed of disputed by the scientific study. For instance, in examining the cause of cholera, a sample hypothesis can be “microbe-like germ causes cholera”.

A hypothesis may be very specific such as the one stated above for cholera or may be broad. Furthermore, a statistical hypothesis can also be used and is focused on a given statistical population such as people with particular disease in statistical hypothesis, a null hypothesis is generally used and is the conjecture that the statistical hypothesis is false and researchers usually seek to prove that the hypothesis is false.

Prediction: this step involves identifying the logical consequences of the hypothesis. The prediction seeks to distinguish the hypothesis form likely alternatives. Having identified prediction of the possible outcomes of the study, the next step follows.

Prediction: this step involves identifying the logical consequences of the hypothesis. The prediction seeks to distinguish the hypothesis form likely alternatives. Having identified prediction of the possible outcomes of the study, the next step follows.

Testing: this is the practical experimentation stage and seeks to establish whether the real world behaves as predicted in the hypothesis. This is also known as hypothesis testing and the findings from these experiments shape the hypothesis. For instance, if the experiment findings agree with the hypothesis, the confidence and popularity of the hypothesis increase. However, it is crucial that experiments be designed in a way that possible errors are minimized through use of scientific controls.

Analysis: this step is largely concerned with determining the results of the experiments and deciding the next actions to be taken. For instance, the researcher may recommend other scientists to conduct further similar experiments to support their findings or fill the gaps of the current study. Statistical analyses are sometimes used in the analysis of findings. One the hypothesis is strongly supported or refuted by the findings from the analysis, the research conducted through scientific methods is then published for public study and scrutiny.

References

• Franklin, James (2009), What Science Knows: And How It Knows It, New York: Encounter Books, ISBN 978-1-59403-207-3.
• Scientific method [Online] Available at:< https://www.britannica.com/science/scientific-method> [Accessed on 24th November, 2019]

Describe the possible impact of sampling error and the placebo effect

In research conducted with sampling of participants, there is a high probability of sampling error. A sampling error can be understood as the difference between the average values obtained through a study and the true average values of the target population. For instance, a research may find that 20% of the participants like coffee, basing on the results from their research sample but in reality, the target population’s real values may project that 30% of the people like coffee. Thus, the research will have 10% margin from the real values. Thus, sampling error may question the credibility, and reliability of the research conducted since the fact that the study research missed the mark, it points to the availability of flaws in the research study. This further affects the confidence level of the research in the eyes of the public scrutiny since numerous questions will be asked as to whether the researcher followed appropriate research approach, and measures to minimize flaws in the research.

In a more related aspect, especially in medicine research involving testing different treatment mechanisms such as drugs, the placebo effect is so real. A placebo is anything that appears to be real medical treatment and they do not contain an active substance meant to affect health. When conducting studies to test the effect of new medicine on the people’s health, researchers administer the new medicine to one group and placebo to another group and using these two analyses establishes the effect of the new medicine. However, the placebo effect is where certain patients react to placebo and exhibit what appear to be side effects from the treatment. The placebo effect can be manifested among people with conditions such as depression, pain, sleep disorders, irritable bowel syndrome and menopause. In fact, the relationship of the mind and the body is responsible for the placebo effect. For instance, is a person expects the pill to do something their body’s own chemistry may cause effects similar to those that would have been caused by the medication. Thus, the placebo effect may affect the research findings on the side effects of the new medicine and if wrong conclusions are drawn, this might result into sampling error.

References

• Arnstein P, Broglio K, Wuhrman E, Kean MB (2011). "Use of placebos in pain management" (PDF). Pain Manag Nurs(Position Statement of the American Society for Pain Management Nursing). 12 (4): 225–9. doi:10.1016/j.pmn.2010.10.033. PMID 22117754.
• Yeung V, Sharpe L, Glozier N, Hackett ML, Colagiuri B (April 2018). "A systematic review and meta-analysis of placebo versus no treatment for insomnia symptoms". Sleep Medicine Reviews. 38: 17–27. doi:10.1016/j.smrv.2017.03.006. PMID 28554719.

How did Tversky & Kahneman’s 1974 paper describe the process of decision making?

Decision making in an event of uncertainty relies heavily on the judgement of the decision maker. In such a circumstance, it is generally expected that the decision will be made with precision bearing in mind that experts may be involved in such circumstances. Heuristics as described by Tversky and Kahneman (1974) paper are unconscious quick rules formed in the mind when an individual is faced with a situation of uncertainty and shape their judgement and ultimately decision making. In most of the time, the authors argue, heuristics lead to making of sensible decisions.

Tversky and Kahneman (1974) paper establishes three main heuristics relied upon in making judgements and decisions during uncertainty. The first heuristic is representativeness and the authors of the paper argue that faced with two almost related scenarios, a person will likely base their judgement on how representative scenario A is to Scenario B and vice versa. However, regardless of this judgement, the authors identify that it may be highly probable that these two scenarios are not representative of each other and much as they may be related, the two scenarios may lead to completely different outcomes. However, despite this reality, representativeness is largely applied in making judgments in such a scenario. The authors identify that judgements made on the premise of representativeness are often insensitive of the prior probability of outcomes and sample size. Additionally, representativeness is also pegged on the misconceptions of change, insensitivity to predictability and illusion of validity that create biases in decisions made based on the representativeness heuristic.

The second element of judgement is availability and the authors explain that under this element, people tend to make decision on events or occurrences based on their experience of recent occurrences that readily available in their memory and tend to link the two. Common biases of this element are biases due to irretrievability of certain instances and due to effectiveness of a search set and may lead to wrong decisions under uncertainty. Biases under availability heuristic may also stem from imagination and illusion where the subject may be misled in their imagination into making judgements that are biased. Dig deeper into Importance Of Internal Factors In Shaping Human Behaviour And Performance with our selection of articles.

The final element discussed by authors is adjustment and anchoring and they argue that in many instances, people base their decision on an initial value that's adjusted to the final answer and is thus insufficient since different starting points yield different results. Biases arise in the evaluation of conjunctive and disjunctive events as well as in the assessment of subjective probability distributions.

References

• Tversky A and Kahneman D. 1974. Judgement under uncertainty: heuristics and biases. Science. New series 185(4157)