Epidemiology and Public Health

Lesson Plan

Aims and Objectives:

  • To define epidemiology and public health
  • To list the functions of public health
  • To describe the assessment of evidence of causation
  • To outline the process of population-based health management
  • To describe different public health programs

Epidemiology and Public Health

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Epidemiology is the study of those factors affecting the health of a given population. Public Health is the management of those factors. Together, they act as a concept known as preventive medicine.

The work of communicable and non-communicable disease epidemiologists ranges from outbreak investigation to study design, data collection and analysis, including the development of statistical models to test hypotheses and the documentation of results for submission to peer-reviewed journals. Epidemiologists may draw from other scientific disciplines, such as biology, in understanding disease processes, as well as social science disciplines, including sociology and philosophy, to better understand proximate and distal risk factors.

The goal of public health is to improve lives through the prevention or treatment of disease. The United Nations' World Health Organization defines health as "a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity." In 1920, C.E.A. Winslow defined public health as "the science and art of preventing disease, prolonging life and promoting health through the organized efforts and informed choices of society, organizations, public and private, communities and individuals."

The public-health approach can be applied to a population of just a handful of people or to the whole human population. Public health is typically divided into Epidemiology, Biostatistics and Health services. Environmental, Social, Behavioral, and Occupational health are also important subfields.

Functions

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The functions of public health include:[1]

  • Health surveillance, monitoring and analysis
  • Investigation of disease outbreaks, epidemics and risk to health
  • Establishing, designing and managing health promotion and disease prevention programmes
  • Enabling and empowering communities to promote health and reduce inequalities
  • Creating and sustaining cross-Government and intersectoral partnerships to improve health and reduce inequalities
  • Ensuring compliance with regulations and laws to protect and promote health
  • Developing and maintaining a well-educated and trained, multi-disciplinary public health workforce
  • Ensuring the effective performance of health services to meet goals in improving health, preventing disease and reducing inequalities
  • Research, development, evaluation and innovation
  • Quality assuring the public health function

Assessing evidence of causation

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Although epidemiology is sometimes viewed as a collection of statistical tools used to elucidate the associations of exposures to health outcomes, a deeper understanding of this science is that of discovering causal relationships. It is nearly impossible to say with perfect accuracy how even the most simple physical systems behave beyond the immediate future. Epidemiologists use gathered data and a broad range of biomedical and psychosocial theories in an iterative way to generate or expand theories, to test hypotheses, and to make educated, informed assertions about which relationships are causal, and about exactly how they are causal. Epidemiologists Rothman and Greenland emphasize that the "one cause - one effect" understanding is a simplistic mis-belief. Most outcomes — whether disease or death — are caused by a chain or web consisting of many component causes.

Bradford-Hill criteria

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In 1965 Austin Bradford Hill detailed criteria for assessing evidence of causation.[2] These guidelines are sometimes referred to as the Bradford-Hill criteria, but this makes it seem like it is some sort of checklist. For example, Phillips and Goodman (2004) note that they are often taught or referenced as a checklist for assessing causality, despite this not being Hill's intention [3]. Hill himself said "None of my nine viewpoints can bring indisputable evidence for or against the cause-and-effect hypothesis and none can be required sine qua non"[2].

  1. Strength: A small association does not mean that there is not a causal effect.[2]
  2. Consistency: Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect.[2]
  3. Specificity: Causation is likely if a very specific population at a specific site and disease with no other likely explanation. The more specific an association between a factor and an effect is, the bigger the probability of a causal relationship.[2]
  4. Temporality: The effect has to occur after the cause (and if there is an expected delay between the cause and expected effect, then the effect must occur after that delay).[2]
  5. Biological gradient: Greater exposure should generally lead to greater incidence of the effect. However, in some cases, the mere presence of the factor can trigger the effect. In other cases, an inverse proportion is observed: greater exposure leads to lower incidence.[2]
  6. Plausibility: A plausible mechanism between cause and effect is helpful (but Hill noted that knowledge of the mechanism is limited by current knowledge).[2]
  7. Coherence: Coherence between epidemiological and laboratory findings increases the likelihood of an effect. However, Hill noted that "... lack of such [laboratory] evidence cannot nullify the epidemiological affect on associations" [2].
  8. Experiment: "Occasionally it is possible to appeal to experimental evidence" [2].
  9. Analogy: The effect of similar factors may be considered[2].

Population-based Management

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Epidemiological practice and the results of epidemiological analysis make a significant contribution to emerging population-based health management frameworks.

Population-based health management encompasses the ability to:

  • assess the health states and health needs of a target population;
  • implement and evaluate interventions that are designed to improve the health of that population; and
  • efficiently and effectively provide care for members of that population in a way that is consistent with the community’s cultural, policy and health resource values.

Modern population-based health management is complex, requiring a multiple set of skills (medical, political, technological, mathematical etc.) of which epidemiological practice and analysis is a core component, that is unified with management science to provide efficient and effective health care and health guidance to a population. This task requires the forward looking ability of modern risk management approaches that transform health risk factors, incidence, prevalence and mortality statistics (derived from epidemiological analysis) into management metrics that not only guide how a health system responds to current population health issues, but also how a health system can be managed to better respond to future potential population health issues.

Examples of organizations that use population-based health management that leverage the work and results of epidemiological practice include Canadian Strategy for Cancer Control, Health Canada Tobacco Control Programs, Rick Hansen Foundation, Canadian Tobacco Control Research Initiative.[4][5][6]

Public Health at work

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One of the most important public health issues facing the world currently is HIV/AIDS. Tuberculosis is also reemerging as a major concern due to the rise of HIV/AIDS-related infections and the development of tuberculin strains that are resistant to standard antibiotics. Another major public health concern is diabetes. In 2006, according to the World Health Organization, at least 171 million people worldwide suffered from diabetes. Its incidence is increasing rapidly, and it is estimated that by the year 2030, this number will double.

A controversial aspect of public health is the control of smoking. Many nations have implemented major initiatives to cut smoking, such as increased taxation and bans on smoking in some or all public places. Proponents argue by presenting evidence that smoking is one of the major killers in all developed countries, and that therefore governments have a duty to reduce the death rate, both through limiting passive (second-hand) smoking and by providing fewer opportunities for smokers to smoke. Opponents say that this undermines individual freedom and personal responsibility (often using the phrase nanny state in the UK), and worry that the state may be emboldened to remove more and more choice in the name of better population health overall. However, proponents counter that inflicting disease on other people via passive smoking is not a human right, and in fact smokers are still free to smoke in their own homes.

Screening

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Screening, in medicine, is a strategy used in a population to detect a disease in individuals without signs or symptoms of that disease. Unlike most medicine, in screening, tests are performed on those without any clinical indication of disease.

The intention of screening is to identify disease in a community early, thus enabling earlier intervention and management in the hope to reduce mortality and suffering from a disease. Although screening may lead to an earlier diagnosis, not all screening tests have been shown to benefit the person being screened; overdiagnosis, misdiagnosis, and creating a false sense of security are some potential adverse effects of screening. For these reasons, a test used in a screening program, especially for a disease with low incidence, must have good specificity in addition to acceptable sensitivity.

Like any medical test, the tests used in screening are not perfect. The test may appear positive for those without disease (false positive), or may miss people who have the disease (false negative). Even with a correct result, other factors may mean that a screening test is not beneficial to a population.

  • Adverse effects of screening procedure (e.g. Stress, anxiety, radiation exposure, chemical exposure).
  • Stress and anxiety caused by a false positive screening result.
  • Unnecessary investigation and treatment of false positive results.
  • Prolonging knowledge of an illness if nothing can be done about it.
  • A false sense of security caused by false negatives, which may even delay final diagnosis.
  • Overuse/waste of medical resources.
  • Unnecessary and uncomfortable procedures looking for a disease that is unlikely.

World Health Organization guidelines were published in 1968, but they are still applicable today.

1. The condition should be an important health problem. 2. There should be a treatment for the condition. 3. Facilities for diagnosis and treatment should be available. 4. There should be a latent stage of the disease. 5. There should be a test or examination for the condition. 6. The test should be acceptable to the population. 7. The natural history of the disease should be adequately understood. 8. There should be an agreed policy on who to treat. 9. The total cost of finding a case should be economically balanced in relation to medical expenditure as a whole. 10. Case-finding should be a continuous process, not just a "once and for all" project.

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References

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  1. Gabriel Scally. The use or uselessness of annual public health reports: Time to rise to the challenge of a new role for public health. BMJ No 7117 Volume 315
  2. 2.00 2.01 2.02 2.03 2.04 2.05 2.06 2.07 2.08 2.09 2.10 Hill, A.B. (1965). "The environment and disease: association or causation?". Proceedings of the Royal Society of Medicine 58: 295–300. http://www.edwardtufte.com/tufte/hill. 
  3. Phillips, Carl V.; Karen J. Goodman (October 2004). "The missed lessons of Sir Austin Bradford Hill". Epidemiologic Perspectives and Innovations 1 (3): 3. doi:10.1186/1742-5573-1-3. http://www.epi-perspectives.com/content/1/1/3. 
  4. Smetanin, P.; P. Kobak (October 2005). "Interdisciplinary Cancer Risk Management: Canadian Life and Economic Impacts" in 1st International Cancer Control Congress
  5. Smetanin, P.; P. Kobak (July 2006). "A Population-Based Risk Management Framework for Cancer Control" (PDF) in The International Union Against Cancer Conference
  6. Smetanin, P.; P. Kobak (July 2005). "Selected Canadian Life and Economic Forecast Impacts of Lung Cancer" (PDF) in 11th World Conference on Lung Cancer