Epidemiology

From Wikipedia, the free encyclopedia

Epidemiology is the study and analysis of the distribution (who, when, and where) and determinants of health and disease conditions in defined populations. 

 

It is the cornerstone of public health, and shapes policy decisions and evidence-based practice by identifying risk factors for disease and targets for preventive healthcare. Epidemiologists help with study design, collection, and statistical analysis of data, amend interpretation and dissemination of results (including peer review and occasional systematic review). Epidemiology has helped develop methodology used in clinical research, public health studies, and, to a lesser extent, basic research in the biological sciences.

Major areas of epidemiological study include disease causation, transmission, outbreak investigation, disease surveillance, environmental epidemiology, forensic epidemiology, occupational epidemiology, screening, biomonitoring, and comparisons of treatment effects such as in clinical trials. Epidemiologists rely on other scientific disciplines like biology to better understand disease processes, statistics to make efficient use of the data and draw appropriate conclusions, social sciences to better understand proximate and distal causes, and engineering for exposure assessment.

Etymology

Epidemiology, literally meaning "the study of what is upon the people", is derived from Greek, Modern epi, meaning 'upon, among', demos, meaning 'people, district', and logos, meaning 'study, word, discourse', suggesting that it applies only to human populations. However, the term is widely used in studies of zoological populations (veterinary epidemiology), although the term "epizoology" is available, and it has also been applied to studies of plant populations (botanical or plant disease epidemiology).

The distinction between "epidemic" and "endemic" was first drawn by Hippocrates, to distinguish between diseases that are "visited upon" a population (epidemic) from those that "reside within" a population (endemic). The term "epidemiology" appears to have first been used to describe the study of epidemics in 1802 by the Spanish physician Villalba in Epidemiología Española. Epidemiologists also study the interaction of diseases in a population, a condition known as a syndemic. 

The term epidemiology is now widely applied to cover the description and causation of not only epidemic disease, but of disease in general, and even many non-disease, health-related conditions, such as high blood pressure and obesity. Therefore, this epidemiology is based upon how the pattern of the disease causes change in the function of everyone.

History

The Greek physician Hippocrates, known as the father of medicine, sought a logic to sickness; he is the first person known to have examined the relationships between the occurrence of disease and environmental influences. Hippocrates believed sickness of the human body to be caused by an imbalance of the four humors (air, fire, water and earth "atoms"). The cure to the sickness was to remove or add the humor in question to balance the body. This belief led to the application of bloodletting and dieting in medicine. He coined the terms endemic (for diseases usually found in some places but not in others) and epidemic (for diseases that are seen at some times but not others).

Modern era

In the middle of the 16th century, a doctor from Verona named Girolamo Fracastoro was the first to propose a theory that these very small, unseeable, particles that cause disease were alive. They were considered to be able to spread by air, multiply by themselves and to be destroyable by fire. In this way he refuted Galen's miasma theory (poison gas in sick people). In 1543 he wrote a book De contagione et contagiosis morbis, in which he was the first to promote personal and environmental hygiene to prevent disease. The development of a sufficiently powerful microscope by Antonie van Leeuwenhoek in 1675 provided visual evidence of living particles consistent with a germ theory of disease. 

Wu Youke (1582–1652) developed the concept that some diseases were caused by transmissible agents, which he called liqi (pestilential factors). His book Wenyi Lun (Treatise on Acute Epidemic Febrile Diseases) can be regarded as the main etiological work that brought forward the concept, ultimately attributed to Westerners, of germs as a cause of epidemic diseases (source: http://baike.baidu.com/view/143117.htm). His concepts are still considered in current scientific research in relation to Traditional Chinese Medicine studies (see: http://apps.who.int/medicinedocs/en/d/Js6170e/4.html). 

Another pioneer, Thomas Sydenham (1624–1689), was the first to distinguish the fevers of Londoners in the later 1600s. His theories on cures of fevers met with much resistance from traditional physicians at the time. He was not able to find the initial cause of the smallpox fever he researched and treated.

Original map by John Snow showing the clusters of cholera cases in the London epidemic of 1854.

John Graunt, a haberdasher and amateur statistician, published Natural and Political Observations ... upon the Bills of Mortality in 1662. In it, he analysed the mortality rolls in London before the Great Plague, presented one of the first life tables, and reported time trends for many diseases, new and old. He provided statistical evidence for many theories on disease, and also refuted some widespread ideas on them. 

John Snow is famous for his investigations into the causes of the 19th century cholera epidemics, and is also known as the father of (modern) epidemiology. He began with noticing the significantly higher death rates in two areas supplied by Southwark Company. His identification of the Broad Street pump as the cause of the Soho epidemic is considered the classic example of epidemiology. Snow used chlorine in an attempt to clean the water and removed the handle; this ended the outbreak. This has been perceived as a major event in the history of public health and regarded as the founding event of the science of epidemiology, having helped shape public health policies around the world. However, Snow's research and preventive measures to avoid further outbreaks were not fully accepted or put into practice until after his death. 

Other pioneers include Danish physician Peter Anton Schleisner, who in 1849 related his work on the prevention of the epidemic of neonatal tetanus on the Vestmanna Islands in Iceland. Another important pioneer was Hungarian physician Ignaz Semmelweis, who in 1847 brought down infant mortality at a Vienna hospital by instituting a disinfection procedure. His findings were published in 1850, but his work was ill-received by his colleagues, who discontinued the procedure. Disinfection did not become widely practiced until British surgeon Joseph Lister 'discovered' antiseptics in 1865 in light of the work of Louis Pasteur. 

In the early 20th century, mathematical methods were introduced into epidemiology by Ronald Ross, Janet Lane-Claypon, Anderson Gray McKendrick, and others.

Another breakthrough was the 1954 publication of the results of a British Doctors Study, led by Richard Doll and Austin Bradford Hill, which lent very strong statistical support to the link between tobacco smoking and lung cancer. 

In the late 20th century, with advancement of biomedical sciences, a number of molecular markers in blood, other biospecimens and environment were identified as predictors of development or risk of a certain disease. Epidemiology research to examine the relationship between these biomarkers analyzed at the molecular level, and disease was broadly named "molecular epidemiology". Specifically, "genetic epidemiology" has been used for epidemiology of germline genetic variation and disease. Genetic variation is typically determined using DNA from peripheral blood leukocytes. Since the 2000s, genome-wide association studies (GWAS) have been commonly performed to identify genetic risk factors for many diseases and health conditions. 

While most molecular epidemiology studies are still using conventional disease diagnosis and classification systems, it is increasingly recognized that disease progression represents inherently heterogeneous processes differing from person to person. Conceptually, each individual has a unique disease process different from any other individual ("the unique disease principle"), considering uniqueness of the exposome (a totality of endogenous and exogenous / environmental exposures) and its unique influence on molecular pathologic process in each individual. Studies to examine the relationship between an exposure and molecular pathologic signature of disease (particularly cancer) became increasingly common throughout the 2000s. However, the use of molecular pathology in epidemiology posed unique challenges including lack of research guidelines and standardized statistical methodologies, and paucity of interdisciplinary experts and training programs. Furthermore, the concept of disease heterogeneity appears to conflict with the long-standing premise in epidemiology that individuals with the same disease name have similar etiologies and disease processes. To resolve these issues and advance population health science in the era of molecular precision medicine, "molecular pathology" and "epidemiology" was integrated to create a new interdisciplinary field of "molecular pathological epidemiology" (MPE), defined as "epidemiology of molecular pathology and heterogeneity of disease". In MPE, investigators analyze the relationships between; (A) environmental, dietary, lifestyle and genetic factors; (B) alterations in cellular or extracellular molecules; and (C) evolution and progression of disease. A better understanding of heterogeneity of disease pathogenesis will further contribute to elucidate etiologies of disease. The MPE approach can be applied to not only neoplastic diseases but also non-neoplastic diseases. The concept and paradigm of MPE have become widespread in the 2010s.

By 2012 it was recognized that many pathogens' evolution is rapid enough to be highly relevant to epidemiology, and that therefore much could be gained from an interdisciplinary approach to infectious disease integrating epidemiology and molecular evolution to "inform control strategies, or even patient treatment."

Types of studies

Epidemiologists employ a range of study designs from the observational to experimental and generally categorized as descriptive, analytic (aiming to further examine known associations or hypothesized relationships), and experimental (a term often equated with clinical or community trials of treatments and other interventions). In observational studies, nature is allowed to "take its course," as epidemiologists observe from the sidelines. Conversely, in experimental studies, the epidemiologist is the one in control of all of the factors entering a certain case study. Epidemiological studies are aimed, where possible, at revealing unbiased relationships between exposures such as alcohol or smoking, biological agents, stress, or chemicals to mortality or morbidity. The identification of causal relationships between these exposures and outcomes is an important aspect of epidemiology. Modern epidemiologists use informatics as a tool.

Observational studies have two components, descriptive and analytical. Descriptive observations pertain to the "who, what, where and when of health-related state occurrence". However, analytical observations deal more with the ‘how’ of a health-related event. Experimental epidemiology contains three case types: randomized controlled trials (often used for new medicine or drug testing), field trials (conducted on those at a high risk of contracting a disease), and community trials (research on social originating diseases).

The term 'epidemiologic triad' is used to describe the intersection of Host, Agent, and Environment in analyzing an outbreak.

Case series

Case-series may refer to the qualitative study of the experience of a single patient, or small group of patients with a similar diagnosis, or to a statistical factor with the potential to produce illness with periods when they are unexposed. 

The former type of study is purely descriptive and cannot be used to make inferences about the general population of patients with that disease. These types of studies, in which an astute clinician identifies an unusual feature of a disease or a patient's history, may lead to a formulation of a new hypothesis. Using the data from the series, analytic studies could be done to investigate possible causal factors. These can include case-control studies or prospective studies. A case-control study would involve matching comparable controls without the disease to the cases in the series. A prospective study would involve following the case series over time to evaluate the disease's natural history.

The latter type, more formally described as self-controlled case-series studies, divide individual patient follow-up time into exposed and unexposed periods and use fixed-effects Poisson regression processes to compare the incidence rate of a given outcome between exposed and unexposed periods. This technique has been extensively used in the study of adverse reactions to vaccination and has been shown in some circumstances to provide statistical power comparable to that available in cohort studies.

Case-control studies

Case-control studies select subjects based on their disease status. It is a retrospective study. A group of individuals that are disease positive (the "case" group) is compared with a group of disease negative individuals (the "control" group). The control group should ideally come from the same population that gave rise to the cases. The case-control study looks back through time at potential exposures that both groups (cases and controls) may have encountered. A 2×2 table is constructed, displaying exposed cases (A), exposed controls (B), unexposed cases (C) and unexposed controls (D). The statistic generated to measure association is the odds ratio (OR), which is the ratio of the odds of exposure in the cases (A/C) to the odds of exposure in the controls (B/D), i.e. OR = (AD/BC). 

	Cases	Controls
Exposed	A	B
Unexposed	C	D

If the OR is significantly greater than 1, then the conclusion is "those with the disease are more likely to have been exposed," whereas if it is close to 1 then the exposure and disease are not likely associated. If the OR is far less than one, then this suggests that the exposure is a protective factor in the causation of the disease. Case-control studies are usually faster and more cost effective than cohort studies, but are sensitive to bias (such as recall bias and selection bias). The main challenge is to identify the appropriate control group; the distribution of exposure among the control group should be representative of the distribution in the population that gave rise to the cases. This can be achieved by drawing a random sample from the original population at risk. This has as a consequence that the control group can contain people with the disease under study when the disease has a high attack rate in a population. 

A major drawback for case control studies is that, in order to be considered to be statistically significant, the minimum number of cases required at the 95% confidence interval is related to the odds ratio by the equation:

${\displaystyle {\text{total cases}}=A+C=1.96^{2}(1+N)\left({\frac {1}{\ln(OR)}}\right)^{2}\left({\frac {OR+2{\sqrt {OR}}+1}{\sqrt {OR}}}\right)\approx 15.5(1+N)\left({\frac {1}{\ln(OR)}}\right)^{2}}$

where N is the ratio of cases to controls. As the odds ratio approached 1, approaches 0; rendering case control studies all but useless for low odds ratios. For instance, for an odds ratio of 1.5 and cases = controls, the table shown above would look like this: 

	Cases	Controls
Exposed	103	84
Unexposed	84	103

For an odds ratio of 1.1: 

	Cases	Controls
Exposed	1732	1652
Unexposed	1652	1732

Cohort studies

Cohort studies select subjects based on their exposure status. The study subjects should be at risk of the outcome under investigation at the beginning of the cohort study; this usually means that they should be disease free when the cohort study starts. The cohort is followed through time to assess their later outcome status. An example of a cohort study would be the investigation of a cohort of smokers and non-smokers over time to estimate the incidence of lung cancer. The same 2×2 table is constructed as with the case control study. However, the point estimate generated is the relative risk (RR), which is the probability of disease for a person in the exposed group, P_e = A / (A + B) over the probability of disease for a person in the unexposed group, P_u = C / (C + D), i.e. RR = P_e / P_u. 

.....	Case	Non-case	Total
Exposed	A	B	(A + B)
Unexposed	C	D	(C + D)

As with the OR, a RR greater than 1 shows association, where the conclusion can be read "those with the exposure were more likely to develop disease." 

Prospective studies have many benefits over case control studies. The RR is a more powerful effect measure than the OR, as the OR is just an estimation of the RR, since true incidence cannot be calculated in a case control study where subjects are selected based on disease status. Temporality can be established in a prospective study, and confounders are more easily controlled for. However, they are more costly, and there is a greater chance of losing subjects to follow-up based on the long time period over which the cohort is followed. 

Cohort studies also are limited by the same equation for number of cases as for cohort studies, but, if the base incidence rate in the study population is very low, the number of cases required is reduced by ½.

Causal inference

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. 

"Correlation does not imply causation" is a common theme for much of the epidemiological literature. For epidemiologists, the key is in the term inference. Correlation, or at least association between two variables, is a necessary but not sufficient criteria for inference that one variable causes the other. Epidemiologists use gathered data and a broad range of biomedical and psychosocial theories in an iterative way to generate or expand theory, to test hypotheses, and to make educated, informed assertions about which relationships are causal, and about exactly how they are causal. 

Epidemiologists 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. Causes can be distinguished as necessary, sufficient or probabilistic conditions. If a necessary condition can be identified and controlled (e.g., antibodies to a disease agent, energy in an injury), the harmful outcome can be avoided (Robertson, 2015).

Bradford Hill criteria

In 1965, Austin Bradford Hill proposed a series of considerations to help assess evidence of causation, which have come to be commonly known as the "Bradford Hill criteria". In contrast to the explicit intentions of their author, Hill's considerations are now sometimes taught as a checklist to be implemented for assessing causality. 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."

1. Strength of Association: A small association does not mean that there is not a causal effect, though the larger the association, the more likely that it is causal.
2. Consistency of Data: Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect.
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.
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).
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.
6. Plausibility: A plausible mechanism between cause and effect is helpful (but Hill noted that knowledge of the mechanism is limited by current knowledge).
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 effect on associations".
8. Experiment: "Occasionally it is possible to appeal to experimental evidence".
9. Analogy: The effect of similar factors may be considered.

Legal interpretation

Epidemiological studies can only go to prove that an agent could have caused, but not that it did cause, an effect in any particular case:

Epidemiology is concerned with the incidence of disease in populations and does not address the question of the cause of an individual's disease. This question, sometimes referred to as specific causation, is beyond the domain of the science of epidemiology. Epidemiology has its limits at the point where an inference is made that the relationship between an agent and a disease is causal (general causation) and where the magnitude of excess risk attributed to the agent has been determined; that is, epidemiology addresses whether an agent can cause a disease, not whether an agent did cause a specific plaintiff's disease.

In United States law, epidemiology alone cannot prove that a causal association does not exist in general. Conversely, it can be (and is in some circumstances) taken by US courts, in an individual case, to justify an inference that a causal association does exist, based upon a balance of probability. 

The subdiscipline of forensic epidemiology is directed at the investigation of specific causation of disease or injury in individuals or groups of individuals in instances in which causation is disputed or is unclear, for presentation in legal settings.

Population-based health management

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.

Each of these organizations use a population-based health management framework called Life at Risk that combines epidemiological quantitative analysis with demographics, health agency operational research and economics to perform:

• Population Life Impacts Simulations: Measurement of the future potential impact of disease upon the population with respect to new disease cases, prevalence, premature death as well as potential years of life lost from disability and death;
• Labour Force Life Impacts Simulations: Measurement of the future potential impact of disease upon the labour force with respect to new disease cases, prevalence, premature death and potential years of life lost from disability and death;
• Economic Impacts of Disease Simulations: Measurement of the future potential impact of disease upon private sector disposable income impacts (wages, corporate profits, private health care costs) and public sector disposable income impacts (personal income tax, corporate income tax, consumption taxes, publicly funded health care costs).

Applied field epidemiology

Applied epidemiology is the practice of using epidemiological methods to protect or improve the health of a population. Applied field epidemiology can include investigating communicable and non-communicable disease outbreaks, mortality and morbidity rates, and nutritional status, among other indicators of health, with the purpose of communicating the results to those who can implement appropriate policies or disease control measures.

Humanitarian context

As the surveillance and reporting of diseases and other health factors becomes increasingly difficult in humanitarian crisis situations, the methodologies used to report the data are compromised. One study found that less than half (42.4%) of nutrition surveys sampled from humanitarian contexts correctly calculated the prevalence of malnutrition and only one-third (35.3%) of the surveys met the criteria for quality. Among the mortality surveys, only 3.2% met the criteria for quality. As nutritional status and mortality rates help indicate the severity of a crisis, the tracking and reporting of these health factors is crucial. 

Vital registries are usually the most effective ways to collect data, but in humanitarian contexts these registries can be non-existent, unreliable, or inaccessible. As such, mortality is often inaccurately measured using either prospective demographic surveillance or retrospective mortality surveys. Prospective demographic surveillance requires lots of manpower and is difficult to implement in a spread-out population. Retrospective morality surveys are prone to selection and reporting biases. Other methods are being developed, but are not common practice yet.

Validity: precision and bias

Different fields in epidemiology have different levels of validity. One way to assess the validity of findings is the ratio of false-positives (claimed effects that are not correct) to false-negatives (studies which fail to support a true effect). To take the field of genetic epidemiology, candidate-gene studies produced over 100 false-positive findings for each false-negative. By contrast genome-wide association appear close to the reverse, with only one false positive for every 100 or more false-negatives. This ratio has improved over time in genetic epidemiology as the field has adopted stringent criteria. By contrast other epidemiological fields have not required such rigorous reporting and are much less reliable as a result.

Random error

Random error is the result of fluctuations around a true value because of sampling variability. Random error is just that: random. It can occur during data collection, coding, transfer, or analysis. Examples of random error include: poorly worded questions, a misunderstanding in interpreting an individual answer from a particular respondent, or a typographical error during coding. Random error affects measurement in a transient, inconsistent manner and it is impossible to correct for random error. 

There is random error in all sampling procedures. This is called sampling error. 

Precision in epidemiological variables is a measure of random error. Precision is also inversely related to random error, so that to reduce random error is to increase precision. Confidence intervals are computed to demonstrate the precision of relative risk estimates. The narrower the confidence interval, the more precise the relative risk estimate. 

There are two basic ways to reduce random error in an epidemiological study. The first is to increase the sample size of the study. In other words, add more subjects to your study. The second is to reduce the variability in measurement in the study. This might be accomplished by using a more precise measuring device or by increasing the number of measurements. 

Note, that if sample size or number of measurements are increased, or a more precise measuring tool is purchased, the costs of the study are usually increased. There is usually an uneasy balance between the need for adequate precision and the practical issue of study cost.

Systematic error

A systematic error or bias occurs when there is a difference between the true value (in the population) and the observed value (in the study) from any cause other than sampling variability. An example of systematic error is if, unknown to you, the pulse oximeter you are using is set incorrectly and adds two points to the true value each time a measurement is taken. The measuring device could be precise but not accurate. Because the error happens in every instance, it is systematic. Conclusions you draw based on that data will still be incorrect. But the error can be reproduced in the future (e.g., by using the same mis-set instrument). 

A mistake in coding that affects all responses for that particular question is another example of a systematic error. 

The validity of a study is dependent on the degree of systematic error. Validity is usually separated into two components:

• Internal validity is dependent on the amount of error in measurements, including exposure, disease, and the associations between these variables. Good internal validity implies a lack of error in measurement and suggests that inferences may be drawn at least as they pertain to the subjects under study.
• External validity pertains to the process of generalizing the findings of the study to the population from which the sample was drawn (or even beyond that population to a more universal statement). This requires an understanding of which conditions are relevant (or irrelevant) to the generalization. Internal validity is clearly a prerequisite for external validity.

Selection bias

Selection bias occurs when study subjects are selected or become part of the study as a result of a third, unmeasured variable which is associated with both the exposure and outcome of interest. For instance, it has repeatedly been noted that cigarette smokers and non smokers tend to differ in their study participation rates. (Sackett D cites the example of Seltzer et al., in which 85% of non smokers and 67% of smokers returned mailed questionnaires.) It is important to note that such a difference in response will not lead to bias if it is not also associated with a systematic difference in outcome between the two response groups.

Information bias

Information bias is bias arising from systematic error in the assessment of a variable. An example of this is recall bias. A typical example is again provided by Sackett in his discussion of a study examining the effect of specific exposures on fetal health: "in questioning mothers whose recent pregnancies had ended in fetal death or malformation (cases) and a matched group of mothers whose pregnancies ended normally (controls) it was found that 28% of the former, but only 20% of the latter, reported exposure to drugs which could not be substantiated either in earlier prospective interviews or in other health records". In this example, recall bias probably occurred as a result of women who had had miscarriages having an apparent tendency to better recall and therefore report previous exposures.

Confounding

Confounding has traditionally been defined as bias arising from the co-occurrence or mixing of effects of extraneous factors, referred to as confounders, with the main effect(s) of interest. A more recent definition of confounding invokes the notion of counterfactual effects. According to this view, when one observes an outcome of interest, say Y=1 (as opposed to Y=0), in a given population A which is entirely exposed (i.e. exposure X = 1 for every unit of the population) the risk of this event will be R_A1. The counterfactual or unobserved risk R_A0 corresponds to the risk which would have been observed if these same individuals had been unexposed (i.e. X = 0 for every unit of the population). The true effect of exposure therefore is: R_A1 − R_A0 (if one is interested in risk differences) or R_A1/R_A0 (if one is interested in relative risk). Since the counterfactual risk R_A0 is unobservable we approximate it using a second population B and we actually measure the following relations: R_A1 − R_B0 or R_A1/R_B0. In this situation, confounding occurs when R_A0 ≠ R_B0. (NB: Example assumes binary outcome and exposure variables.) 

Some epidemiologists prefer to think of confounding separately from common categorizations of bias since, unlike selection and information bias, confounding stems from real causal effects.

The profession

To date, few universities offer epidemiology as a course of study at the undergraduate level. One notable undergraduate program exists at Johns Hopkins University, where students who major in public health can take graduate level courses, including epidemiology, their senior year at the Bloomberg School of Public Health.

Although epidemiologic research is conducted by individuals from diverse disciplines, including clinically trained professionals such as physicians, formal training is available through Masters or Doctoral programs including Master of Public Health (MPH), Master of Science of Epidemiology (MSc.), Doctor of Public Health (DrPH), Doctor of Pharmacy (PharmD), Doctor of Philosophy (PhD), Doctor of Science (ScD). Many other graduate programs, e.g., Doctor of Social Work (DSW), Doctor of Clinical Practice (DClinP), Doctor of Podiatric Medicine (DPM), Doctor of Veterinary Medicine (DVM), Doctor of Nursing Practice (DNP), Doctor of Physical Therapy (DPT), or for clinically trained physicians, Doctor of Medicine (MD) or Bachelor of Medicine and Surgery (MBBS or MBChB) and Doctor of Osteopathic Medicine (DO), include some training in epidemiologic research or related topics, but this training is generally substantially less than offered in training programs focused on epidemiology or public health. Reflecting the strong historical tie between epidemiology and medicine, formal training programs may be set in either schools of public health and medical schools. 

As public health/health protection practitioners, epidemiologists work in a number of different settings. Some epidemiologists work 'in the field'; i.e., in the community, commonly in a public health/health protection service, and are often at the forefront of investigating and combating disease outbreaks. Others work for non-profit organizations, universities, hospitals and larger government entities such as state and local health departments, various Ministries of Health, Doctors without Borders, the Centers for Disease Control and Prevention (CDC), the Health Protection Agency, the World Health Organization (WHO), or the Public Health Agency of Canada. Epidemiologists can also work in for-profit organizations such as pharmaceutical and medical device companies in groups such as market research or clinical development.

Sociology of health and illness

From Wikipedia, the free encyclopedia

The sociology of health and illness, alternatively the sociology of health and wellness (or simply health sociology), examines the interaction between society and health. The objective of this topic is to see how social life affects morbidity and mortality rate, and vice versa. This aspect of sociology differs from medical sociology in that this branch of sociology discusses health and illness in relation to social institutions such as family, employment, and school. The sociology of medicine limits its concern to the patient-practitioner relationship and the role of health professionals in society. The sociology of health and illness covers sociological pathology (causes of disease and illness), reasons for seeking particular types of medical aid, and patient compliance or noncompliance with medical regimes.

 

Health, or lack of health, was once merely attributed to biological or natural conditions. Sociologists have demonstrated that the spread of diseases is heavily influenced by the socioeconomic status of individuals, ethnic traditions or beliefs, and other cultural factors. Where medical research might gather statistics on a disease, a sociological perspective on an illness would provide insight on what external factors caused the demographics who contracted the disease to become ill.

This topic requires a global approach of analysis because the influence of societal factors varies throughout the world. This will be demonstrated through discussion of the major diseases of each continent. These diseases are sociologically examined and compared based on the traditional medicine, economics, religion, and culture that is specific to each region. HIV/AIDS serves as a common basis of comparison among regions. While it is extremely problematic in certain areas, in others it has affected a relatively small percentage of the population. Sociological factors can help to explain why these discrepancies exist.

There are obvious differences in patterns of health and illness across societies, over time, and within particular society types. There has historically been a long-term decline in mortality within industrialized societies, and on average, life-expectancies are considerably higher in developed, rather than developing or undeveloped, societies. Patterns of global change in health care systems make it more imperative than ever to research and comprehend the sociology of health and illness. Continuous changes in economy, therapy, technology and insurance can affect the way individual communities view and respond to the medical care available. These rapid fluctuations cause the issue of health and illness within social life to be very dynamic in definition. Advancing information is vital because as patterns evolve, the study of the sociology of health and illness constantly needs to be updated.

Historical background

Wall painting found in the tomb of an Egyptian official known as the physicians tomb

Humans have long sought advice from those with knowledge or skill in healing. Paleopathology and other historical records, allow an examination of how ancient societies dealt with illness and outbreak. Rulers in Ancient Egypt sponsored physicians that were specialists in specific diseases. Imhotep was the first medical doctor known by name. An Egyptian who lived around 2650 B.C., he was an adviser to King Zoser at a time when Egyptians were making progress in medicine. Among his contributions to medicine was a textbook on the treatment of wounds, broken bones, and even tumors.

Stopping the spread of infectious disease was of utmost importance for maintaining a healthy society. The outbreak of disease during the Peloponnesian War was recorded by Thucydides who survived the epidemic. From his account it is shown how factors outside the disease itself can affect society. The Athenians were under siege and concentrated within the city. Major city centers were the hardest hit. This made the outbreak even more deadly and with probable food shortages the fate of Athens was inevitable. Approximately 25% of the population died of the disease. Thucydides stated that the epidemic "carried away all alike". The disease attacked people of different ages, sexes and nationalities.

Physician in Ancient Greece treating a patient 480–470 BC

Ancient medical systems stressed the importance of reducing illness through divination and ritual. Other codes of behavior and dietary protocols were widespread in the ancient world. During the Zhou Dynasty in China, doctors suggested exercise, meditation and temperance to preserve one's health. The Chinese closely link health with spiritual well-being. Health regimes in ancient India focused on oral health as the best method for a healthy life. The Talmudic code created rules for health which stressed ritual cleanliness, connected disease with certain animals and created diets. Other examples include the Mosaic Code and Roman baths and aqueducts.

Those that were most concerned with health, sanitation and illness in the ancient world were those in the elite class. Good health was thought to reduce the risk of spiritual defilement and therefore enhanced the social status of the ruling class who saw themselves as the beacon of civilization. During the late Roman Period, sanitation for the lower classes was a concern for the leisured class. Those that had the means would donate to charities that focused on the health of non-elites. After the decline of the Roman Empire, physicians and concern with public health disappeared except in the largest cities. Health and public doctors remained in the Byzantine Empire. Focusing on preventing the spread of diseases such as small pox lead to a smaller mortality rate in much of the western world. Other factors that allowed the modern rise in population include: better nutrition and environmental reforms (such as getting clean water supplies).

The present day sense of health being a public concern for the state began in the Middle Ages. A few state interventions include maintaining clean towns, enforcing quarantines during epidemics and supervising sewer systems. Private corporations also played a role in public health. The funding for research and the institutions for them to work were funded by governments and private firms. Epidemics were the cause of most government interventions. The early goal of public health was reactionary whereas the modern goal is to prevent disease before it becomes a problem. Despite the overall improvement of world health, there still has not been any decrease in the health gap between the affluent and the impoverished. Today, society is more likely to blame health issues on the individual rather than society as a whole. This was the prevailing view in the late 20th century. In the 1980s the Black Report, published in the United Kingdom, went against this view and argued that the true root of the problem was material deprivation. This report proposed a comprehensive anti-poverty strategy to address these issues. Since this did not parallel the views of the Conservative government, it did not go into action immediately. The Conservative government was criticized by the Labour Party for not implementing the suggestions that the Black Report listed. This criticism gave the Black Report the exposure it needed and its arguments were considered a valid explanation for health inequality. There is also a debate over whether poverty causes ill-health or if ill-health causes poverty. Arguments by the National Health Service gave considerable emphasis to poverty and lack of access to health care. It has also been found that heredity has more of a bearing on health than social environment, but research has also proved that there is indeed a positive correlation between socioeconomic inequalities and illness.

Methodology

The Sociology of Health and Illness looks at three areas: the conceptualization, the study of measurement and social distribution, and the justification of patterns in health and illness. By looking at these things researchers can look at different diseases through a sociological lens. The prevalence and response to different diseases varies by culture. By looking at bad health, researchers can see if health affects different social regulations or controls. When measuring the distribution of health and illness, it is useful to look at official statistics and community surveys. Official statistics make it possible to look at people who have been treated. It shows that they are both willing and able to use health services. It also sheds light on the infected person's view of their illness. On the other hand, community surveys look at people's rating of their health. Then looking at the relation of clinically defined illness and self reports and find that there is often a discrepancy. 

A great deal of the time, mortality statistics take the place of the morbidity statistics because in many developed societies where people typically die from degenerative conditions, the age in which they die sheds more light on their life-time health. This produces many limitations when looking at the pattern of sickness, but sociologists try to look at various data to analyze the distribution better. Normally, developing societies have lower life expectancies in comparison to developed countries. They have also found correlations between mortality and sex and age. Very young and old people are more susceptible to sickness and death. On average women typically live longer than men, although women are more likely to have bad health.

>80   77.5–80   75–77.5   72.5–75   70–72.5

67.5–70   65–67.5   60–65   55–60   50–55

Life expectancy by region in 2015

Disparities in health were also found between people in different social classes and ethnicities within the same society, even though in the medical profession they put more importance in “health related behaviors” such as alcohol consumption, smoking, diet, and exercise. There is a great deal of data supporting the conclusion that these behaviors affect health more significantly than other factors. Sociologists think that it is more helpful to look at health and illness through a broad lens. Sociologists agree that alcohol consumption, smoking, diet, and exercise are important issues, but they also see the importance of analyzing the cultural factors that affect these patterns. Sociologists also look at the effects that the productive process has on health and illness. While also looking at things such as industrial pollution, environmental pollution, accidents at work, and stress-related diseases.

Social factors play a significant role in developing health and illness. Studies of epidemiology show that autonomy and control in the workplace are vital factors in the etiology of heart disease. One cause is an effort-reward imbalance. Decreasing career advancement opportunities and major imbalances in control over work have been coupled with various negative health costs. Various studies have shown that pension rights may shed light on mortality differences between retired men and women of different socioeconomic statuses. These studies show that there are outside factors that influence health and illness.

International perspective

Africa

Estimation of the number of adults in Africa who are infected with HIV or AIDS. Note that levels of infection are much higher in sub-Saharan Africa.

HIV/AIDS is the leading epidemic that affects the social welfare of Africa. Human Immunodeficiency virus (HIV) can cause AIDS which is an acronym for Acquired Immunodeficiency Syndrome (AIDS), a condition in humans in which the immune system begins to fail, leading to life-threatening infections. Two-thirds of the worlds HIV population is located in Sub-Saharan Africa. Since the epidemic started more than 15 million Africans have died by complications with HIV/AIDS.

People apart of religious sub-groups of Sub-Saharan Africa and those who actively and frequently participate in religious activities are more likely to be at a lower risk of contracting HIV/AIDS. On the opposite end, there are many beliefs that an infected male can be cured of the infection by having sex with a virgin. These beliefs increase the number of people with the virus and also increase the number of rapes against women.

Herbal treatment is one of the primary medicines used to treat HIV in Africa. It is used more than standard treatment because it is more affordable. Herbal treatment is more affordable but is not researched and is poorly regulated . This lack of research on whether the herbal medicines work and what the medicines consist of is a major flaw in the healing cycle of HIV in Africa.

Economically, HIV has a significant negative effect. The labor force in Africa is slowly diminishing, due to HIV-related deaths and illness. In response, government income declines and so does tax revenue. The government has to spend more money than it is making, in order to care for those affected with HIV/AIDS.

AIDS orphans in Malawi

A major social problem in Africa in regards to HIV is the orphan epidemic. The orphan epidemic in Africa is a regional problem. In most cases, both of the parents are affected with HIV. Due to this, the children are usually raised by their grandmothers and in extreme cases they are raised by themselves. In order to care for the sick parents, the children have to take on more responsibility by working to produce an income. Not only do the children lose their parents but they also lose their childhood as well. Having to provide care for their parents, the children also miss out on an education which increases the risk of teen pregnancy and people affected with HIV. The most efficient way to diminish the orphan epidemic is prevention: preventing children from acquiring HIV from their mothers at birth, as well as educating them on the disease as they grow older. Also, educating adults about HIV and caring for the infected people adequately will lower the orphan population.

The HIV/AIDS epidemic is reducing the average life expectancy of people in Africa by twenty years. The age range with the highest death rates, due to HIV, are those between the ages of 20 and 49 years. The fact that this age range is when adults acquire most of their income they cannot afford to send their children to school, due to the high medication costs. It also removes the people who could help aid in responding to the epidemic.

Asia

Asian countries have wide variations of population, wealth, technology and health care, causing attitudes towards health and illness to differ. Japan, for example, has the third highest life expectancy (82 years old), while Afghanistan has the 11th worst (44 years old). Key issues in Asian health include childbirth and maternal health, HIV and AIDS, mental health, and aging and the elderly. These problems are influenced by the sociological factors of religion or belief systems, attempts to reconcile traditional medicinal practices with modern professionalism, and the economic status of the inhabitants of Asia. 

People living with HIV/AIDS

Like the rest of the world, Asia is threatened by a possible pandemic of HIV and AIDS. Vietnam is a good example of how society is shaping Asian HIV/AIDS awareness and attitudes towards this disease. Vietnam is a country with feudal, traditional roots, which, due to invasion, wars, technology and travel is becoming increasingly globalized. Globalization has altered traditional viewpoints and values. It is also responsible for the spread of HIV and AIDS in Vietnam. Even early globalization has added to this problem – Chinese influence made Vietnam a Confucian society, in which women are of less importance than men. Men in their superiority have no need to be sexually responsible, and women, generally not well educated, are often unaware of the risk, perpetuating the spread of HIV and AIDS as well as other STIs.

Confucianism has had a strong influence on the belief system in Asia for centuries, particularly in China, Japan, and Korea, and its influence can be seen in the way people chose to seek, or not seek, medical care. An important issue in Asia is societal effect on the ability of disabled individuals to adjust to a disability. Cultural beliefs shape attitudes towards physical and mental disabilities. China exemplifies this problem. According to Chinese Confucian tradition (which is also applicable in other countries where Confucianism has been spread), people should always pursue good health in their lives, with an emphasis on health promotion and disease prevention. To the Chinese, having a disability signifies that one has not led a proper lifestyle and therefore there is a lack of opportunities for disabled individuals to explore better ways to accept or adapt to their disability.

Indigenous healing practices are extremely diverse throughout Asia but often follow certain patterns and are still prevalent today. Many traditional healing practices include shamanism and herbal medicines, and may have been passed down orally in small groups or even institutionalized and professionalized. In many developing countries the only health care available until a few decades ago were those based on traditional medicine and spiritual healing. Now governments must be careful to create health policies that strike a balance between modernity and tradition. Organizations, like the World Health Organization, try to create policies that respect tradition without trying to replace it with modern science, instead regulating it to ensure safety but keeping it accessible. India in particular tries to make traditional medicines safe but still available to as many people as possible, adapting tradition to match modernization while still considering the economic positions and culture of its citizens.

Flag of World Health Organization

Mental health issues are gaining an increasing amount of attention in the Asian countries. Many of these countries have a preoccupation with modernizing and developing their economies, resulting in cultural changes. In order to reconcile modern techniques with traditional practices, social psychologists in India are in the process of “indigenizing psychology”. Indigenous psychology is that which is derived from the laws, theories, principals, and ideas of a culture and unique to each society.

In many Asian countries, childbirth is still treated by traditional means and is thought of with regional attitudes. For example, in Pakistan, decisions concerning pregnancy and antenatal care (ANC) are usually made by older women, often the pregnant woman's mother-in-law, while the mother and father to be are distanced from the process. They may or may not receive professional ANC depending on their education, class, and financial situation. Generally in Asia, childbirth is still a woman's area and male obstetricians are rare. Female midwives and healers are still the norm in most places. Western methods are overtaking the traditional in an attempt to improve maternal health and increase the number of live births.

Asian countries, which are mostly developing nations, are aging rapidly even as they are attempting to build their economies. Even wealthy Asian nations, such as Japan, Singapore, and Taiwan, also have very elderly populations and thus have to try to sustain their economies and society with small younger generations while caring for their elderly citizens. The elderly have been traditionally well respected and well cared for in most Asian cultures; experts predict that younger generations in the future are less likely to be concerned and involved in the health care of their older relatives due to various factors such as women joining the workforce more, the separation of families because of urbanization or migration, and the proliferation of Western ideals such as individualism.

Australia

The health patterns found on the continent of Australia which includes the Pacific Islands, have been very much influenced by European colonization. While indigenous medicinal beliefs are not significantly prevalent in Australia, traditional ideas are still influential in the health care problems in many of the islands of the Pacific. The rapid urbanization of Australia led to epidemics of typhoid fever and the Bubonic plague. Because of this, public health was professionalized beginning in the late 1870s in an effort to control these and other diseases. Since then Australia's health system has evolved similarly to Western countries and the main cultural influence affecting health care are the political ideologies of the parties in control of the government.

Old heroin bottle

Australia has had treatment facilities for 'problem drinkers' since the 1870s. In the 1960s and 1970s it was recognized that Australia had several hundred thousand alcoholics and prevention became a priority over cures, as there was a societal consensus that treatments are generally ineffective. The government began passing laws attempting to curb alcohol consumption but consistently met opposition from the wine-making regions of southern Australia. The government has also waged a war on illegal drugs, particularly heroin, which in the 1950s became widely used as a pain reliever.

Experts believe that many of the health problems in the Pacific Islands can be traced back to European colonization and the subsequent globalization and modernization of island communities. European colonization and late independence meant modernization but also slow economic growth, which had an enormous effect on health care, particularly on nutrition in the Pacific Islands. The end of colonization meant a loss of medical resources, and the fledgling independent governments could not afford to continue the health policies put in place by the colonial governments. Nutrition was changed radically, contributing to various other health problems. While more prosperous, urban areas could afford food, they chose poor diets, causing 'overnourishment', and leading to extremely high levels of obesity, type 2 diabetes, and cardiovascular diseases. Poorer rural communities, on the other hand, continue to suffer from malnutrition and malaria.

Traditional diets in the Pacific are very low in fat, but since World War II there has been a significant increase in fat and protein in Pacific diets. Native attitudes towards weight contribute to the obesity problem. Tongan natives see obesity as a positive thing, especially in men. They also believe that women should do as little physical work as possible while the men provide for them, meaning they get very little exercise.

Europe

The largest endeavors to improve health across Europe is the World Health Organization European Region. The goal is to improve the health of poor and disadvantaged populations by promoting healthy lifestyles including environmental, economic, social and providing health care. Overall health in Europe is very high compared to the rest of the world. The average life expectancy is around 78 in EU countries but there is a wide gap between Western and Eastern Europe. It is as low as 67 in Russia and 73 in the Balkan states. Europe is seeing an increase in the spread of HIV/AIDS in Eastern Europe because of a worsening socioeconomic situation. Cardiovascular disease, cancer and diabetes mellitus are more prevalent is Eastern Europe. The WHO claims that poverty is the most important factor bringing on ill health across Europe. Those at low socioeconomic status levels and many young people are also at risk because of their increased tobacco, alcohol and drug abuse. Health and illness prevention in Europe is largely funded by the governmental services including: regulating health care, insurance and social programs. The role of religion and traditional medicine, however, is often left unexamined in such reports. 

The study of hypertension within the United Kingdom has turned to examining the role that beliefs play in its diagnosis and treatment. Hypertension is an essential topic for study since it is linked to increased risk of stroke and coronary heart disease. The most common treatment for hypertension is medication but compliance for this treatment plan is low. A study conducted in the UK examined the differences between 'white' patients and first generation immigrants from the West Indies. There were differing reasons for non-compliance that involve the patients' perception and beliefs about the diagnosis. Patients commonly believe that high levels of anxiety when first diagnosed are the major cause and think that when stress levels decline so too will their hypertension. Other respondents in this UK based study had varying beliefs concerning the necessity of medication while others still argued that it was the side effects of medication that made them end their prescribed regimen. West Indian respondents whose lay culture teaches them to reject long-term drug therapy opted instead for folk remedies in higher numbers than the 'white' respondents. What can be seen here is that some people will choose to ignore a doctor's expert advice and will employ 'lay consultation' instead.

Regions of the WHO

Before people seek medical help they try to interpret the symptoms themselves and often consult people in their lives or use 'self-help' measures. A study of 'everyday illness' in Finland including: influenza, infections and musculo-skeletal problems focused on reasons for consulting medical experts and explanations of illness. These common illness were examined not because of their seriousness but because of their frequency. The researchers explain five possible triggers that people seek medical aid: 1- the occurrence of an interpersonal crisis 2- perceived interference with social and personal relations 3- perceived interference with vocational & physical activity 4- sanctioning by other people 5- sufferers ideas about how long certain complaints should last. These kind of explanatory models are part of the process that people use to construct medical culture. They give meaning to illness and health, answer questions about personal responsibility about health and most importantly are part of the dialogue between patients' and professionals' illness explanations. It can help explore why some patients will follow a doctors instructions to the letter and others ignore them completely. A patient's explanation or understanding of their illness can be much broader than a physician's and this dynamic has become a major criticism of modern medical practice since it normally excludes the "social, psychological and experiential dimensions of illness."

The Finnish study examined 127 patients and the results have been different from findings in other countries where there is more 'lay consultation'. Half of the respondents did not have any lay consultation before coming to the doctors office. One-third did not try any self-treatment and three-quarters of the sample consulted the doctor within three days of symptoms developing. Possible explanations are that in Finland there is an aspect "over-protectiveness" within their health care system. Many might conclude that the Finnish people are dependent and helpless but the researchers of this study found that people chose to consult professionals because they trusted them over some lay explanation. These results echo similar studies in Ireland that explain this phenomenon as being based in a strong work ethic. Illness in these countries will affect their work and Finnish people will quickly get treatment so they can return to work. This research out of Finland also describes that this relationship between patient and doctor is based on:

• National and municipal administrative bureaucracies that demand more output and more satisfied patients;
• The public demanding better care;
• Nurses criticizing physicians for not taking a holistic view of patients;
• Hospital specialists wanting better/earlier screening for serious illnesses (e.g. cancer).

The conflict between medical and lay worlds is prominent. On one hand many patients believe they are the expert of their own body and view the Doctor-patient relationship as authoritarian. These people will often use knowledge outside the medical field to deal with health and illness. Others see the doctor as the expert and are shy about describing their symptoms and therefore rely on the doctor for diagnosis and treatment.

North America

Compares figures in the population of OECD countries and the percentage of total population (aged 15 and above) with a body mass index greater than 30. Data was collected between 1996 and 2003.

North America is a fairly recent settled continent, made up of the United States, Canada, Mexico, Central America, and the Caribbean. It was built by an amalgamation of wealth, ideas, culture, and practices. North America is highly advanced intellectually, technologically, and traditionally. This advantageous character of North American nations has caused a high average life expectancy of 75 years for males and 80 years for females. This leads to the conclusion that North America has cultivated a comparatively healthy society. As North America contains several core nations, the growing economies in those nations are able to maintain and develop medical institutions. This subsequently provides more access to health care for American citizens but health care is not universal. North America is known for being a leading nation in regards to industrialization and modernization, but the United States lacks federal laws regarding health care as a basic human right. This lag of health care security causes subsequent issues with pharmaceutical competition, lack of care for the elderly, and little attention to alternative medicine. Health care and education are plentiful at a price and illness still persists for many reasons. A main reason is that a lower- and middle-class population still exists in plentiful numbers, maintaining a group that is highly vulnerable to physical ailment. 

World map showing alcohol consumption around the world

 

North America's primary risk factors for illness are currently alcohol abuse, malnutrition, obesity, tobacco use, and water sanitation. Obesity is a recent epidemic in North America. The 1990s brought a rise in the average Body Mass Index, or BMI. From the beginning and to the end of the decade, the median percent of adults who were obese rose from 12% to 20%. Alcoholism is the addiction of over-consumption of alcohol and is highly prevalent in the US. There are high incidence rates in many other world regions. Roughly 61% of American adults drank in 2007, and 21% of current drinkers consumed five or more drinks at one point in the last year. There have also been 22,073 alcohol induced deaths in the United States in the past year, about 13,000 of which were related to liver disease. Alcoholism has many risk factors ingrained in North American culture, such as heredity, stress from competition or availability. 

The Swine Flu (also known as (H1N1) epidemic is a recent disease emerging in the early 21st century. In April 2009, during the early days of the outbreak, a molecular biologist named Dr. Henry Miller wrote in the Wall Street Journal about New York City high-school students. These students apparently brought the virus back from Mexico and infected their classmates. All six cases so far reported in Canada were connected directly or indirectly with travel to Mexico as well. Flu viruses can be directly transmitted (via droplets from sneezing or coughing) from pigs to people, and vice versa. These cross-species infections occur most commonly when people are close to large numbers of pigs, such as in barns, livestock exhibits at fairs, and slaughterhouses. The flu is transmissible from human to human, either directly or via contaminated surfaces."

South America

There are many diseases that affect South America, but two major conditions are malaria and Hepatitis D. Malaria affects every country in South America except Uruguay, Chile, and The Falkland Islands. Elevation is a major factor in the areas where malaria is found. The disease is spread from person to person via mosquito bites. People are typically bitten by mosquitoes at dusk and dawn. Symptoms of this disorder are: high fever, chills, sweating, headaches, body aches, weakness, vomiting and diarrhea. If left untreated, new symptoms can occur; people that are infected may experience seizures, delirium and coma. Severe cases may end in death. Malaria can be cured, but the symptoms may not become noticeable until months later. There are three forms of medication that can cure Malaria. An infected person's accessibility to these drugs is dependent upon their access to medical care and their financial situation. Literature about Malaria treatment typically is focused toward people who are tourists. Most sources are not written with the native in mind.

Malaria

The first sign of Hepatitis D was detected in 1978 when a strange and unrecognizable internuclear antigen was discovered during a liver biopsy of several Italians who suffered HBV infection. Scientists initially thought that it was an antigenic specificity of HBV, but they soon found that it was a protein from another disease altogether. They called it "Hepatitis Delta Virus" (HDV). This new virus was found to be defective. HDV needed HBV to act as a helper function in order for it to be detected. Normally Hepatitis B is transmitted through blood or any type of blood product. In South America Hepatitis D was found to be fatal. Scientists are still unsure in what way this disease was being transmitted throughout certain South American countries. Sexual contact and drug use are the most common means of transmission. HDV is still considered an unusual form of hepatitis. Agents of this virus resemble that of plant viroids. It is still hard to tell how many stereotypes exist because HDV is under the umbrella of HBV. HDV causes very high titers in the blood of people who are infected. Incubation of Hepatitis D typically lasts for thirty five days. Most often Hepatitis D is a co-infection with Hepatitis B or a super-infection with chronic hepatitis. In terms of super infections there are high mortality rates, ranging seventy to eighty percent; in contrast with co-infections which have a one to three percent mortality rate. There is little information with the ecology of Hepatitis D. Epidemics have been found in Venezuela, Peru, Columbia, and Brazil. People who are treated for Hepatitis B have been able to control Hepatitis D. People who have chronic HDB will continue to get HDV.

Another disease that affects South America is HIV and AIDS. In 2008 roughly two million people had HIV and AIDS. By the end of 2008 one hundred and seventy thousand people were infected with AIDS and HIV. Seventy seven thousand people died from this disease by the end of that year. Brazil has the most people that are affected with AIDS and HIV in South America. Forty-three percent of people in Brazil have HIV. In Brazil sixty percent of the inhabitants use drugs, are HIV positive, and are HIV positive because of their drug use. Usually this disease is transmitted by either drug use involving needles or unprotected sex. Sharing needles and being infected with HIV and AIDS is most common in Paraguay and Uruguay. South America is trying to get treatment to the thousands of people infected by this disease. Brazil is offering generic AIDS prescriptions that are much less expensive than the name brand drugs. One hundred and eighty-one thousand inhabitants in Brazil who were infected are being treated. That accounts for eighty percent of those who needed immediate help. This aid from the government has had positive results. Statistics show that there was a fifty percent decrease in mortality rates, approximately sixty to eighty percent decrease in morbidity rates and a seventy percent decrease in hospitalization of infected people.

In very remote areas of South America, traditional healers are the only forms of health care people have. In north Aymara and south Mapuche, where the indigenous groups have the strongest voices, they still heavily use traditional medicine. The government in Chile has implemented an Indigenous Health System to help strengthen the health care system. Even with Chile's indigenous groups, Chile still has the best public health services in South America. They also have the lowest mortality rates in the area. Their health care policies are centered around family and community well-being by focusing on the strategies for prevention health strategies. Reports have shown an increase in mental health issues, diabetes, and cardiovascular diseases.

South America's economy is developing rapidly and has a great deal of industries. The major industry in South America are agriculture. Other industries are fishing, handicrafts, and natural resources. Its trade and import-export market is continually thriving. In the past South American countries moved slowly in regards to economic development. South America began to build its economy ever since World War II. South America's largest economies are Brazil, Chile, Argentina, and Columbia. Venezuela, Peru, and Argentina's economy are growing very rapidly.