Syndemic

A syndemic is the aggregation of two or more diseases in a population in which there is some level of positive biological interaction that exacerbates the negative health effects of any or all of the diseases. The term was developed and introduced by Merrill Singer in several articles in the mid-1990s and has since received growing attention and use among epidemiologists and medical anthropologists concerned with community health and the effects of social conditions on health, culminating in a recent textbook.^[1] Syndemics tend to develop under conditions of health disparity, caused by poverty, stress, or structural violence, and contribute to a significant burden of disease in affected populations. The term syndemic is further reserved to label the consequential interactions between concurrent or sequential diseases in a population and in relation to the social conditions that cluster the diseases within the population.

The traditional biomedical approach to disease is characterized by an effort to diagnostically isolate, study, and treat diseases as if they were distinct entities that existed in nature separate from other diseases and independent of the social contexts in which they are found. This singular approach proved useful historically in focusing medical attention on the immediate causes and biological expressions of disease and contributed, as a result, to the emergence of targeted modern biomedical treatments for specific diseases, many of which have been successful. As knowledge about diseases has advanced, it is increasingly realized that diseases are not independent and that synergistic disease interactions are of considerable importance for prognosis. Importantly, few studies in the empirical literature have actually tested the hypothesis of syndergistic disease interaction (see "Statistical modeling in research on syndemics" below), which is a significant gap in the literature. Given that social conditions can contribute to the clustering, form and progression of disease at the individual and population level, there is growing interest in the health sciences on syndemics.

Cooccurrence versus syndemism

Disease cooccurrence, with or without interactions, is known as comorbidity, coinfection, and associated terms. The differences between "comorbid" and "syndemic" are not merely semantic. As Mustanski et al. (2008:40) explain: "comorbidity research tends to focus on the nosological issues of boundaries and overlap of diagnoses, while syndemic research focuses on communities experiencing co-occurring epidemics that additively increase negative health consequences." Consequently, it is possible for two afflictions to be comorbid, but not be syndemic (i.e., the disorders are not epidemic in the studied population or their co-occurrence is not accompanied by worsened health). Thus, two (or more) diseases can be comorbid but no interaction occurs between them, while in other cases interaction occurs but it has beneficial rather than deleterious consequences. Syndemic theory seeks to draw attention to and provide a framework for the analysis of adverse disease interactions, including their causes and consequences for human life and well-being.

Types of disease interaction

Interest in the syndemics perspective has been driven by growing evidence of the regularity of interactions among diseases and recognition that this interaction influences disease course, expression, severity, transmission, and diffusion. Several different kinds of interaction among diseases have been described, including both indirect (changes caused by one disease that facilitate another through an intermediary) and direct interface (diseases act in direct tandem). In some syndemic interactions—such as the one between diabetes and SARS—changes in biochemistry or damage to organ systems caused by one disease (in this case, diabetes), such as weakening of the immune system, promotes the progression of another disease (SARS). This type of relationship also connects HIV infection and a host of "opportunistic" bacterial (e.g. mycobacterial (Mycobacterium tuberculosis, Mycobacterium avium), fungal (e.g. candidiasis), protozoal (e.g. toxoplasmosis), and viral (e.g. Human Papilloma Virus) infections and possibly viral-caused malignancies (Kaposi's Sarcoma). Similarly, there is evidence that periodontitis, which can lead to tooth loss, may arise from a syndemic. Periodontitis is known to be caused by bacteria of several different species (e.g., Porphyromonas gingivalis, Dialister pneumosintes, Prevotella intermedia) that adhere to and reproduce on tooth surfaces, especially under the gum line. Multiplication of these pathogens may be inhibited by bodily defenses unless these are weakened by a herpesvirus infection of the periodontium.

Another type of syndemic relationship involves one disease enhancing the virulence of another. There is evidence, for example, that herpesvirus has this effect on HIV infection, with progression to AIDS being significantly accelerated by co-infection with herpesvirus. Similarly, in gum infection, periodontal bacteria may enhance the virulence of herpesvirus. In addition, HIV-infected individuals are more susceptible to tuberculosis even though the cause is not fully understood.^[2]

Alternately, one disease can assist the physical transmission of another disease. This appears to be the case, for example, with syphilis and HIV coinfection as a result of genital-tract ulceration caused by the former supporting sexual transmission of the latter.

Direct interaction of diseases is in the case of genetic recombination among different pathogens, for instance between Avian sarcoma leukosis virus and Marek's disease virus (MDV) in domestic fowl. Both of these cancer-causing viruses are known to infect the same poultry flock, the same chicken, and, even the same anatomic cell. In coinfected cells, the retroviral DNA of the avian leukosis virus can integrate into the MDV genome, producing altered biological properties compared to those of the parental MDV. The frequency of gene reassortment among human pathogens is less clear than is the case among plant or some animal species but of significant potential concern as animal diseases adapt to human hosts—which they have been doing at an increasingly rapid pace—and as new diseases come into contact.

In some cases, coinfection may open up multiple syndemic pathways. In studies of human populations, a lethal synergism has been identified between influenza virus and pneumococcus, a likely cause of excess mortality from secondary bacterial pneumonia during influenza epidemics. There is a significant level of evidence indicating that the influenza virus alters the lungs in ways that increase the adherence, invasion and induction of disease by pneumococcus. But other consequential changes, such as alteration of the immune response which weakens the body’s ability to clear pneumococcus (or, alternately, by amplifying the inflammatory cascade), are also suggested by existing research.

In other cases, syndemic interaction among diseases is apparent but the pathways of linkage are not yet clear. An example is the apparent interaction that occurs between type 2 diabetes mellitus and hepatitis C viral infection. Several factors are known to contribute to the onset of type 2 diabetes, including diet, obesity and aging. The role of infection, however, is only beginning to be understood. Already it is known that risk for serious infections of various kinds increase significantly with poor diabetes control, but appreciation of more complex relationships between infection and type 2 diabetes is now emerging as well.

Counter-syndemics

Discussion of deleterious disease interactions raises a question about the possibility of an opposite kind of disease interaction, namely: are there counter syndemics, disease interactions that lower the burden of disease in a population below the sum effects of the individual diseases involved? The discovery of counter-syndemics is important because such entities may suggest novel strategies for the prevention and treatment of disease. Recent research findings suggest that counter-syndemics do occur and are part of the complex world of co-morbidity. For example, William Moss and fellow researchers at the Johns Hopkins Bloomberg School of Public Health have found that human immunodeficiency virus is transiently suppressed during an acute measles infection. This finding was the product of a study of HIV-infected children living in Zambia. In the study, children who had measles, and reported various typical symptoms, including fever, rash, conjunctivitis, runny nose, and cough, had a significant drop in HIV levels detectable in the blood as compared to HIV-infected children who were not infected with measles. Several potential mechanisms could be responsible for the temporary suppression of HIV replication early in the course of a measles infection. Morbillivirus (measles virus) infection is known to cause lymphopenia, a reduction in the number of CD4+ T lymphocytes circulating in the blood. The low point in lymphocyte levels occurs just prior to the onset of the distinct red circular skin rash (called rubeola) characteristic of a measles infection. Within a month of this nadir, the number of lymphocytes tends to return to normal levels. The drop in HIV may reflect a decrease in target CD4+ T cells needed for replication. Alternately, measles virus infection may stimulate the production of cells that are directly responsible for suppressing HIV replication. Several candidates have been suggested, including the β-chemokines, CD8+ cell antiviral factor, and the cytokines known as IL-10 and IL-16 (biochemicals that inhibit HIV transcription), but none has been confirmed as the source of HIV suppression. Additionally, Moss and co-workers found that median plasma levels of RANTES, a chemokine that attracts immune system components like eosinophils (a kind of white blood cell that destroys parasitic organisms), monocytes (a precursor of macrophages), and lymphocytes, were higher in HIV-infected children with measles than in those without measles. HIV suppression also has been identified in patients suffering tsutsugamushi disease, a mite-borne infection found in Asia and Australia, also known as scrub typhus, although the how this occurs is not clear. Other counter-syndemics are likely to be discovered as a syndemic perspective emphazing paying attention to processes and relationships diffuses among researchers.

Iatrogenic syndemics

The term iatrogenesis means "brought forth by a healer" (iatro is the Greek word for healer) and almost always is used to refer to adverse health conditions caused by medical treatment (such as unwelcome side effects). Can there be iatrogenic syndemics? In principle, this is possible if medical treatment or medical research is involved in creating conditions that increase the likelihood that two or more diseases come together in a population. An example of this scenario would be the use of gene splicing to unite two pathogenic agents and introducing the resulting novel organism into a population. There is a possibility that this precise event occurred, for example, during a randomized, double-blind clinical trial testing the efficacy of the prototype HIV vaccine called V520. On November 6, 2007, the pharmaceutical manufacturer Merck & Co. announced that research on the drug had been stopped because interim findings showed that there appeared to be an increased risk for HIV infection among participants in the vaccine arm of the study compared to those in the placebo group. Specifically, results showed that of the 741 volunteers in the vaccine group, 24 developed HIV infection (3.2%), while among the 762 volunteers in the placebo arm of the trial, 21 developed HIV (2.75%). Notably, investigators in the study reported a higher risk of HIV infection was found among participants who had an existing immunity to the common cold virus (known as adenovirus type 5 or Ad5). The vaccine was created using a mixture of three components, each of which was made in the laboratory with a replication-defective version of Ad5. This was the organism selected to serve as a carrier, or delivery vector, for three synthetically produced HIV genes. Researchers suggested one explanation for the higher rate of HIV infection among individuals in the treatment group was that the vaccine lowered defenses against the human immunodeficiency virus. In other words, novel organisms created through splicing of genes from two naturally occurring pathogens may have increased the rate of disease. While other explanations of the results exist, the study suggests the possibility of the emergence of syndemics with an iatrogenic origin.

Examples of syndemics

Various syndemics (although not always labeled as such) have been described in the literature already, including: the SAVA syndemic (substance abuse, violence and AIDS): the hookworm, malaria and HIV/AIDS syndemic: the Chagas disease, rheumatic heart disease and congestive heart failure syndemic: the possible asthma and infectious disease syndemic: the malnutrition and depression syndemic: the TB, HIV and violence syndemic: the whooping cough, influenza, tuberculosis syndemic; the HIV and STD syndemic; the stress and obesity syndemic, and the mental health and HIV/AIDS syndemic. Additional syndemics are being identified around the world as public health officials, researchers, and service providers begin to focus on the connections among diseases and the social context factors that foster disease concentration and interactions. In January 2006, in a speech at the Enhancing the Healing Environment conference hosted by The Prince's Foundation for the Built Environment and The King's Fund, St James's Palace, London, Prince Charles, The Prince of Wales, noted the importance of paying attention to the built environment, physical inactivity and the obesity/diabetes syndemic.

Syndemics in history

While the rate at which new syndemics develop has accelerated through human history, as populations became larger and ever wider tracts of land were inhabited, as the speed of transportation increased with new technologies, and as human impact on the Earth's climatic and other environmental systems increased, syndemics are not a new phenomenon. Contact between Native Americans and Europeans led to syndemics among the Native American population due to diseases introduced during the Columbian Exchange. This resulted in many deaths due to the Native Americans' lack of built-up immunity to these diseases, which they had not encountered before.

An example of a syndemic from the 19th century can be found on the reservations on which Native Americans were confined with the closing of the U.S. frontier. It is estimated that in 1860 there were well over 10 million bison living on the American Plains. By the early 1880s, the last of the great herds of bison upon which Plains Indian peoples like the Sioux were dependent as a food source were gone, victims of economic greed as well as a conscious plan to control Plains Indian populations. White hunting parties scoured the region, sometimes shooting hundreds or even thousands of bison a day. At the same time, after the U.S. military's defeat at the Battle of the Little Bighorn in 1876, there was a concerted effort to beat the Sioux into total submission. Thus, in 1872, Secretary of the Interior Columbus Delano stated: "as they become convinced that they can no longer rely upon the supply of game for their support, they will return to the more reliable source of subsistence [i.e., farming]." As a result, they were forced to give up their struggle for an independent existence on their own lands and take up reservation life at the mercy of government authority. Treaties that were signed with the Sioux in 1868 and 1876 stipulated that they would be provided with government annuities and provisions in payment for sections of their land and with the expectation among federal representatives that the Sioux would become farmers on individually held plots of land. The Sioux found themselves confined on a series of small reservations where they were treated as a conquered people. Moreover, as was typical of treaties with Native peoples, the government reneged on its promises. The food that was provided to the Sioux was insufficient and of low quality. Black Elk, a noted Sioux folk healer, told his biographer: "There was hunger among my people before I went across the big water [to Europe in 1886], because the Wasichus [whites] did not give us all the food they promised in the Black Hills treaty... But it was worse when I came back [1889]. My people looked pitiful… We could not eat lies and there was nothing we could do." Under extremely stressful conditions, and with inadequate diets, as well as being the victims of overt racism on the part of the registration agents appointed to oversee Indian reserves, the Sioux confronted exposure to infectious disease transmitted from contact with whites. While knowledge about the epidemiology of the Sioux from this period is limited, James Mooney, an anthropologist and representative of the Bureau of Indian Affairs sent to investigate a possible Sioux rebellion, described the health situation on the reservation in 1896: "In 1888 their cattle had been diminished by disease. In 1889, their crops were a failure ... Thus followed epidemics of measles, grippe [influenza], and whooping cough Pertussis, in rapid succession and with terrible fatal results…" Similarly, the Handbook of American Indians notes, "The least hopeful conditions in this respect prevail among the Dakota [Sioux] and other tribes of the colder northern regions, where pulmonary tuberculosis and scrofula are very common… Other more common diseases, are various forms of, bronchitis… pneumonia, pleurisy, and measles in the young. Whooping cough is also met with." Indian children who were removed to white boarding schools were diagnosed with a wide range of diseases, including tuberculosis, trachoma, measles, smallpox, whooping cough, influenza, and pneumonia.

As these accounts suggest, it is likely that the Sioux were victims of a syndemic that combined a number of interacting infectious diseases (including the 1889–1890 flu pandemic), inadequate diet, and stressful and extremely disheartening life conditions, including, with events like the massacre at Wounded Knee in 1890 and the murder of their leader Sitting Bull, outright brutalization. As a result, while the official mortality rate on the reservation was between one and two percent, the death rate was probably closer to 10 percent, a devastatingly high figure.

The influenza syndemics

There were three influenza pandemics during the 20th century that caused widespread illness, mortality, social disruption, and significant economic losses. These occurred in 1918, 1957, and 1968. In each case, mortality rates were determined primarily by five factors: the number of people who became infected, the virulence of the virus causing the pandemic, the speed of global spread, the underlying features and vulnerabilities of the most affected populations, and the effectiveness and timeliness of the prevention and treatment measures that were implemented. These factors unite a range of bio-social causal forces, including production, communication, and transportation technologies; the medical and public health infrastructures; the specific pathogens involved and the nature of their interactions with human hosts; and the pre-existing health status of patients. All of these, in turn, are shaped, to greater or somewhat lesser degree, by overarching political economic structures globally and locally. Epidemics, in short, including their emergence, course, and impact (and whether they become widespread pandemics that exact a sorrowful toll on life and well-being) are sculpted by the configuration of human social relationships including prevailing patterns of social inequality.

The 1957 pandemic was caused by the Asian influenza virus (known as the H2N2 strain), a novel influenza variety to which humans had not yet developed immunities. The death toll of the 1957 pandemic is estimated to have been around two million globally, with approximately 70,000 deaths in the United States. A little over a decade later, the comparatively mild Hong Kong influenza pandemic erupted due to the spread of a virus strain (H3N2) that genetically was related to the more deadly form seen in 1957. The pandemic was responsible for about one million deaths around the world, almost 34,000 of which were in the United States. In both of these pandemics, death may not have been due only to the primary viral infection, but also to secondary bacterial infections among influenza patients; in short, they were caused by a viral/bacterial syndemic (but see Chatterjee 2007).

The worst of the 20th century influenza pandemics was the 1918 outbreak, which epidemiologists estimate was responsible for the deaths of between 40-100 million people worldwide, making it one of the most deadly events in human history. More people died of the so-called Spanish flu (caused by the H1N1 viral strain) pandemic in the single year of 1918 than during all four-years of the Black Death (Bubonic plague) scourge that lasted from 1347 to 1351 (although a significantly higher percentage of the world’s population died of the plague than of Spanish flu). It is estimated that between 20-40 percent of the world’s population became ill during the 1918 pandemic.

The pandemic had devastating effects as disease spread along trade and shipping routes and other corridors of human movement until it had circled the globe. In places like India, the mortality rate reached 50 per 1,000 population. Arriving during the closing phase of the World War I, the pandemic had a significant impact on mobilized national armies. Half of U.S. soldiers who died in the "Great War," for example, were victims of influenza not of enemy bombs and bullets. It is estimated that almost ¾ of a million Americans died during the pandemic. As noted by one alarmed scientific observer at the time, "[if the pandemic continues] civilization could easily disappear from the face of the earth within a matter of a few more weeks". In part, the death toll during the pandemic was caused by viral pneumonia characterized by extensive bleeding in the lungs resulting in suffocation. Many victims died within 48 hours of the appearance of the first symptom. In fact, it was not uncommon for people who appeared to be quite healthy in the morning to have died by sunset. Among those who survived the first several days, however, many died of secondary bacterial pneumonia. Moreover, it has been argued that countless numbers of those who expired quickly from the disease were co-infected with tuberculosis, which would explain the notable plummet in TB cases after 1918 (because so many carriers of the disease perished during the influenza pandemic). Again, as seen with the previous two 20th century global influenza outbreaks, disease interaction appears to have been critical, underlining the importance of syndemics more generally in the production of major public health crises.

Syndemics and the environment

As a result of the floral changes produced by global warming, a significant escalation is occurring in global rates of allergies and asthma. Currently, allergic diseases constitute the sixth leading cause of chronic illness in the United States, impacting the lives of 17 percent of the population. Asthma, characterized by episodic inflammation and narrowing of small airway passages in the lungs, affects about 8 percent of the U.S. population, but the rate of affected individuals has been steadily climbing in recent years, especially in low income, ethnic minority neighborhoods in cities. Thus, in 1980 asthma was found to affect only about three percent of the U.S. population according to the U.S. Centers for Disease Control and Prevention. Asthma among children has been increasing at an even faster pace than among adults, with the percentage of children with asthma going up from 3.6 percent in 1980 to 9 percent in 2005. Among ethnic minority populations, Puerto Ricans the rate of asthma is 125 percent higher than non-Hispanic white people and 80 percent higher than non-Hispanic black people. The asthma prevalence among American Indians, Alaska Natives and black people is 25 percent higher than white people. As is so often the case with health, including health conditions directly affected by global warming, the poor and marginalized suffer the gravest consequences.

Increases in rates of asthma have occurred despite improvements in air quality produced by the passage and enforcement of clean air legislation, such as both the Clean Air Act of 1963 and the Clean Air Act of 1990 in the United States. In other words, existing legislation and regulation have not kept pace with changing climatic conditions and their health consequences. Compounding the problem of air quality is the fact that air-borne pollens have been found to attach themselves to diesel particles from truck or other vehicular exhaust floating in the air, resulting in heightened rates of asthma in areas where busy roads bisect densely populated areas, most notably in poorer inner city areas. Research by the American Cancer Society found that a six percent increase in cardiopulmonary deaths occurs for every elevation of 10 μg/m3 in particulate matter concentration in the air. Exhaust from the burning of diesel fuel is a complex mixture of vapors, gases, and fine particles, including over 40 known pollutants like nitrogen oxide and known or suspected carcinogenic substances such as benzene, arsenic, and formaldehyde. Exposure to diesel exhaust irritates the eyes, nose, throat and lungs, causing coughs, headaches, light headedness and nausea, while causing people with allergies to be more susceptible allergy triggers like dust or pollen. Many particles in disease fuel are so tiny they are able to penetrate deep into the lungs when inhaled. Importantly, diesel fuel particles appear to have even greater immunologic effects in the presence of environmental allergens than they do alone. According to Robert Pandya and co-workers who are studying the role of diesel fuel in asthma, "This immunologic evidence may help explain the epidemiologic studies indicating that children living along major trucking thoroughfares are at increased risk for asthmatic and allergic symptoms and are more likely to have objective evidence of respiratory dysfunction."

Importantly, the damaging effects of diesel fuel pollution appears to go significantly beyond playing a synergistic role in the development of asthma. Recent research suggests that exposure to a combination of microscopic diesel fuel particles among people with high blood cholesterol (i.e., low-density lipoprotein, LDL or "bad cholesterol") increases the risk for both heart attack and stroke significantly above levels found among those exposed to only one of these health risks. According to André Nel, Chief of Nanomedicine at the David Geffen School of Medicine at UCLA who led the study of duel exposure, "When you add one plus one, it normally totals two… But we found that adding diesel particles to cholesterol fats equals three. Their combination creates a dangerous synergy that wreaks cardiovascular havoc far beyond what's caused by the diesel or cholesterol alone." The synergy begins when free radical molecules that are attached to diesel exhaust particles enter the body through the lungs and pass into the circulatory system. Another source of free radicals is the fatty acids that comprise LDL cholesterol, which produce free radicals during cell metabolism. Free radical molecules are highly unstable because they have an odd number of electrons in their outer ring. As a result, they react quickly with other compounds in order to "steal" an electron and gain stability. When the "victimized" molecule loses its electron, it, in turn, becomes a free radical and a chain reaction called oxidation is produced that is known to be damaging to living cells and tissues. Of interest to the Los Angeles research team was the consequences of both sources of free radical production coming into contact. Experimentation revealed that the two mechanisms worked in tandem to stimulate genes that promote cell inflammation, a primary risk for hardening and blockage of blood vessels (atherosclerosis) and, as narrowed arteries collect cholesterol deposits and trigger blood clots, for heart attacks and strokes as well. Atherosclerotic cardiovascular disease is the leading cause of death in developed countries.

Mathematical modelling of syndemics

A mathematical model is a simplified representation using mathematical language to describe natural, mechanical or social system dynamics. In the early 20th century, epidemiologists became increasingly interested in the use of mathematical modelling procedures to project possible patterns in the spread of infectious diseases, including potential outcomes of an epidemic. To achieve these goals, epidemiological modelers unite several types of information and analytic capacity, including: 1) mathematical equations and computational algorithms; 2) computer technology; 3) epidemiological knowledge about infectious disease dynamics, including information about specific pathogens and disease vectors; and 4) research data on social conditions and human behavior. Mathematical modelling in epidemiology is now being applied to syndemics. Abu-Raddad, Patnaik, and Kublin (2006), for example, used modelling to quantify the syndemic effects of malaria and HIV in sub-Saharan Africa based on research in Kisumu, Kenya. These researchers point out that infection with HIV facilitates disease progression in individuals exposed to malaria. At the same time, immune reaction to malaria doubles the infectious level of HIV infected individual. In short, in typical syndemic fashion, each of these diseases amplifies the effects of the other. Using mathematical modelling, Abu-Raddad and co-workers found that 5% of HIV infections (or 8,500 cases of HIV since 1980) in Kisumu are the result of the higher HIV infectiousness of malaria-infected HIV patients. Additionally, their model attributed 10% of adult malaria episodes (or almost one million excess malaria infections since 1980) to the greater susceptibility of HIV infected individuals to malaria. Their model also suggests that HIV has contributed to the wider geographic spread of malaria in Africa, a process previously thought to be the consequence primarily of global warming. Other researchers (e.g., Herring and Sattenspiel 2007) also have begun to apply mathematical modelling to syndemics. Modelling offers an enormously useful tool for anticipating future syndemics, including eco-syndemic, based on information about the spread of various diseases across the planet and the consequent co-infections and disease interactions that will result.

In this regard, Jeremy Lauer and colleges (2003) have developed PopMod, a longitudinal population tool that models distinct and possibly interacting diseases. Unlike other life-table population models, PopMod is specifically designed to not assume the statistical independence of the diseases of interest. The PopMod has several intended purposes, including describing the time evolution of population health for standard demographic purposes (such as estimating healthy life expectancy in a population), and providing a standard measure of effectiveness for health interventions and cost-effectiveness analysis. PopMod is used as one of the standard tools of the World Health Organization’s (WHO) CHOICE (Choosing Interventions that are Cost-Effective) program, an initiative designed to provide national health policy makers in the WHO’s 14 epidemiological sub-regions around the world with findings on a range of health intervention costs and effects.

Statistical modeling in research on syndemics

Although Merrill Singer's conceptual work on syndemics specifically identifies the study of disease interaction as a central concept in the theory of syndemics, most empirically based research studies have not actually used appropriate statistical models to do so. This problem with the syndemics literature was recently highlighted in a seminal systematic review published by Tsai and Burns in the journal Social Science and Medicine.^[3] Of the papers identified in the systematic review, the vast majority (78%) used a statistical model that actually provides no information about disease interaction. The methodological and public health consequences of this type of statistical model were further highlighted in a methodological paper by Tsai and Venkataramani published in the journal AIDS and Behavior.^[4] While this criticism of the literature does not undermine the concept of disease concentration, which is another central concept in the theory of syndemics, it nonetheless highlights a serious flaw in the way that syndemics have been investigated.

Future research on syndemics

Medical anthropologist, epidemiologists, and clinical researchers are just beginning to understand the nature of syndemics. There is a critical need for new research in this area. Important arenas of inquiry include the following: First, there is a need for studies that examine the processes by which syndemics emerge, including the specific sets of health and social conditions that foster the occurrence of multiple epidemics in a population and how syndemics function to produce specific kinds of health outcomes in populations. Second, there is a need to better understand processes of interaction between specific diseases with each other and with health-related factors like malnutrition, structural violence, discrimination, stigmatization, and toxic environmental exposure that reflect oppressive social relationships. Specifically, there is a need to identify all of the ways, directly and indirectly, that diseases can interact and have, as a result, enhanced impact on human health. Third there is a need for the development of an eco-syndemic understanding of the ways in which global warming is contributing to the spread of diseases to new areas and to the potential for new disease interactions. Already it is clear that as a result of global warming infectious diseases such as West Nile Virus are spreading to new places. Similarly malaria is now found in new places because it is spread by particular mosquito species that are migrating to new locations as a result of changing climates. As a consequence, diseases that did not often interact in the past---through co-infection of the same individuals within a population---may begin interacting more regularly. Finally, there is a need for a better understanding of how the public health systems and communities can best respond to and limit the health consequences of syndemics. Systems are needed to monitor the emergence of syndemics and to allow early-bird medical and public health responses designed to lessen their impact. Systematic ethno-epidemiological surveillance with populations subject to multiple social stressors must be one component of such a monitoring system. Current efforts by researchers at the CDC to expand the discussion of syndemics in public health discourse is an important step in the development of a funded research agenda that addresses these research needs. Given the nature of syndemics, this research requires a bio-cultural/social approach that attends to both clinical and social processes.

See also

• Coinfection
• Endemic
• Epidemic
• List of epidemics
• List of human diseases associated with infectious pathogens
• Merrill Singer
• Pandemic

References

Further reading

A continually updated bibliography of the rapidly growing syndemics literature is provided below:

=Books on Syndemics

• Marshall, Mac 2013 Drinking Smoke: The Tobacco Syndemic in Oceania. Honolulu, HI: University of Hawai'i Press.
• Mendenhall, Emily 2012 Syndemic Suffering: Social Distress, Depression, and Diabetes among Mexican Immigrant Women. Left Coast Press, Inc.
• Singer, Merrill 2009 Introduction to Syndemics: A Systems Approach to Public and Community Health. San Francisco, CA: Jossey-Bass.

Articles, Chapters, and Dissertations on Syndemics

• Abu-Raddad Laith, Patnaik P., Kublin J (2006). "Dual Infection with HIV and Malaria Fuels the Spread of Both Diseases in sub-Saharan Africa". Science 314: 1603–1606. doi:10.1126/science.1132338. PMID 17158329. 
• Acevedo, Gabriel 2008 Causal Determinism, Elective Affinities, and Syndemic Networks: An Application of Epidemiological Theory to the Study of non-Medical Phenomenon. All Academic Research. Available online at: http://www.allacademic.com//meta/p_mla_apa_research_citation/1/8/4/6/3/pages184630/p184630-1.php.
• Agnieszka Kalwa, Szymanska Bogna, Cholewinska Grazyna, Anna Siwy-Hudowska (2012). "HIV/HCV Co-Infection—A Dual Neurocognitive Problem". World Journal of AIDS 2 (1): 33–41. doi:10.4236/wja.2012.21005. 
• Akksilp, Somsak, Karnkawinpong, Opart, Wattanaamornkiat, Wanpen, Viriyakitja, Daranee, Monkongdee, Patama, Sitti, Walya, Rienthong, Dhanida, Siraprapasiri,Taweesap, Wells, Charles D., Tappero, Jordan W. and Varmaet, Jay K. 2007 Antiretroviral Therapy during Tuberculosis Treatment and Marked Reduction in Death Rate of HIV-infected Patients, Thailand. Emerging Infectious Diseases 13(7). Available online at: http://www.cdc.gov/EID/content/13/7/1001.htm.
• Alisjahbana B., van Crevel R., Sahiratmadja E., den Heijer M., Maya A. (2006). "Diabetes mellitus is strongly associated with tuberculosis in Indonesia". International Journal Tuberculosis and Lung Disease 10: 696–700. 
• Andreani Guadalupe, Lodge Robert, Richard Dave, Tremblay Michel (2012). "Mechanisms of Interaction between Protozoanarasites and HIV". Current Opinion in HIV and AIDS 7: 276–282. doi:10.1097/coh.0b013e32835211e9. 
• Baer, Hans and Singer, Merrill 2008 Global Warming and the Political Ecology of Health: Emerging Crises and Systemic Solutions. Left Coast Press.
• Baer, Hans, Singer, Merrill, and Susser, Ida 2004 Medical Anthropology and the World System. Begin & Garvey: Westport, CT.
• Bayliss Elizabeth, Steiner John, Fernald Douglas, Crane Lori, Main Deborah (2003). "Descriptions of Barriers to Self-Care by Persons with Comorbid Chronic Diseases". Annal of Family Medicine 1 (1): 15–21. doi:10.1370/afm.4. 
• Bastos Barcellos, Inacio Francisco, Christovam Lowndes, Catherine , Friedman Samuel (1999). "Co-infection with malaria and HIV in injecting drug users in Brazil: a new challenge to public health?". Addiction 94 (8): 1165–1174. doi:10.1046/j.1360-0443.1999.94811656.x. 
• Bennett, Elaine 2009 Understanding childhood malnutrition in a Maya village in Guatemala: A syndemic perspective. Doctoral Dissertation. Department of Anthropology, University of Connecticut.
• Bini Edmund, Perumalswami Ponni (2010). "Hepatitis B Virus Infection Among American Patients with Chronic Hepatitis C Virus Infection: Prevalence, Racial/Ethnic Differences, and Viral Interactions". Hepatology 51: 759–766. doi:10.1002/hep.23461. 
• Brennan Julia, Kuhns Lisa, Johnson Amy, Belzer Marvin, Wilson Erin, Garofalo Robert (2012). "Syndemic Theory and HIV-Related Risk Among Young Transgender Women: The Role of Multiple Co-Occurring Health Problems and Social Marginalization". American Journal of Public Health 102 (9): 1751–1757. doi:10.2105/ajph.2011.300433. 
• Bruce Douglas, Harper Gary, Interventions AIDS (2011). "Operating Without a Safety Net: Gay Male Adolescents and Emerging Adults' Experiences of Marginalization and Migration, and Implications for Theory of Syndemic Production of Health Disparities". Health Education and Behavior 38 (4): 367–378. doi:10.1177/1090198110375911. 
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External links

• http://syndemic.chip.uconn.edu
• "Introduction to Syndemics: A Critical Systems Approach to Public and Community Health: Merill Singer: 9780470472033". Amazon.com. 
• http://www.cdc.gov/syndemics/[]
• Merrill Singer (October 2008). "The Perfect Epidemiological Storm: food insecurity, HiV/aids and Poverty in southern africa" (PDF). In Focus. 
• "Syndemics Research". May 5, 2007. 
• "Syndemic Simulation". Forio's Forum. August 9, 2013. 
• "Defenition of Syndemic". MedicineNet. June 14, 2012. 
• "cultural anthropology". 2013. 
• http://www.cdc.gov/syndemics/pdfs/Encyclopedia.pdf
• http://www.princeofwales.gov.uk/speechesandarticles/a_speech_by_hrh_the_prince_of_wales_at_the_enhancing_the_hea_66.html
• Helmut Albrecht (April 2, 2007). "New Data on HIV and Viral Hepatitis Coinfection". Massachusetts Medical Society. 
• http://www.healthdecisions.org/Dental/News/default.aspx?doc_id=109688
• "NASTAD HIV Prevention" (PDF). 
• Jack Homer; Bobby Milstein (April 2003). "A Dynamic Simulation Model of Syndemics: Casual Structure, Assumptions, and Results" (PDF). Centers for Disease Control and Prevention. 
• "The SAGE Dictionary of Health and Society". Amazon.com. 
• "ECOSALUD Y ECOSINDEMIAS". 
• "Syndemic". Medanth.