Epidemiology of Infectious Diseases: The Epidemiological Triad
top of page

Epidemiology of Infectious Diseases: The Epidemiological Triad


Recognizing and understanding the cause of disease is the holy grail of epidemiology. Epidemiology is the branch of medical science that aims to determine the variables that contribute to disease and poor health outcomes across populations. Epidemiology is a scientific, methodological, and data-based field of research that studies the distribution (frequency, pattern), determinants (causes, risk factors), and occurrence of health-related problems and events in specific populations. Importantly, this research is leveraged to overcome health-related problems. This is mainly achieved through the use of statistics and requires studying the distribution patterns of diseases in the population and identifying their root causes. Unlike other medical disciplines, epidemiology studies groups of people rather than individual patients and is often retrospective or historical in nature (Mullner, 2023). Before the discovery of microorganisms in the 17th century, there were several hypotheses attempting to explain the etiology of infectious diseases. These are diseases caused by pathogenic microorganisms or their toxic by-products and transmitted through contact with an infected person, animal or contaminated object. For instance, the miasma theory developed by the ancient Greeks held that disease was caused by particles from decomposing waste such as sewage or cesspits. People who were in close contact with decomposing material were haunted by such particles. It was believed that this was how diseases like the Black Death, which decimated Europe's population in the Middle Ages, started (Glatter & Finkelman, 2021). The advent of the germ theory in the 19th century paved the way for important advancements in the battle against infectious diseases. Robert Koch formulated a set of postulates (known as Koch's postulates) based on the premise that the cause of a certain disease could be traced back to a specific germ. This theory enabled Koch and his colleagues to pinpoint the microorganisms that cause a number of illnesses, including cholera, anthrax, and tuberculosis. Koch's idea of "One Microbe, One Disease" was the pinnacle of the nineteenth-century paradigm shift away from miasma theory and toward germ theory of disease (The National Academies, 2004).


Later, Louis Pasteur fundamentally changed the concept of disease causation, noting that food spoilage was caused by contamination with microscopic bacteria and that microorganisms underlie both fermentation and disease (Cavaillon & Legout, 2022). Therefore, the focus shifted from non-empirical factors such as bad air and God's wrath to scientifically-based evidence such as the presence of microbes. Humanity's war against infectious diseases seemed all but won. However, the germ hypothesis proved rather insufficient in explaining the causation of most diseases since it presupposes that the causative effect is one-to-one, i.e. a single microorganism is the underlying cause of a specific disease. As an illustration, it is now widely acknowledged that not everyone that is exposed to tuberculosis will contract the disease. The same exposure, however, can cause clinical illness in a malnourished or otherwise susceptible individual. The germ theory was unable to explain this and called for an expanded framework for disease causation that included the fundamental variables of pathogen, host, and environment, rather than just the infectious agent. The inclusion of such disease-causing elements, particularly in infectious diseases, has led to the establishment of the epidemiological triangle, or epidemiological triad.

Figure 1: Pasteurization, microbial fermentation, and the germ theory of disease were all pioneered by Louis Pasteur (Siegfried, 2022).
The Epidemiological Shift: A Theory of Germs

At the end of the 19th century, at the height of germ theory, the causes of diseases were explored under the microscope in a laboratory setting. The germ hypothesis postulated that every ailment was caused by a distinct microorganism. Thus, identifying the microorganism was tantamount to identifying the cause of the disease (The National Academies, 2004). Louis Pasteur and Robert Koch, two famous microbe hunters, devoted countless hours to searching for the exact microorganism responsible for diseases like cholera and tuberculosis. In the 1880s, Koch devised three postulates to help researchers determine whether a particular pathogen is the root cause of a disease: In all cases of sickness, the pathogen must first be identified. Second, it must be isolated from patients and cultivated in a pure culture. Third, the cultured microorganism must be reactivated to cause disease when injected into susceptible animals. However, the entire causality assessment was performed in a laboratory setting (Carter, 1985).


Throughout the first half of the 20th century, fresh challenges in disease prevention highlighted the limitations of the germ hypothesis of disease etiology, calling into question this laboratory-driven strategy. The 1918 influenza pandemic and subsequent polio, meningitis, and encephalitis outbreaks had demonstrated that the patterns of the spread of infectious diseases might be far more intricate than previously anticipated (Wegman, 1994). The drawbacks of germ theory were later highlighted by the discovery that nearly all microorganisms caused asymptomatic infections far more frequently than clinical disease (Chadli, 1986). It became clearly evident that the infectious agent, while essential for the development of a disease, was far from sufficient. Wade Hampton Frost, the first American professor of epidemiology and a pioneer in the field, has focused on the larger social and environmental context of disease emergence rather than the infectious agent. Frost's concept of epidemiological thinking was strongly centered on the interplay between agent (pathogen), host, and environment, foreshadowing what post-war epidemiologists later referred to as the epidemiological triad. His trailblazing vision owned him landmark discoveries, including poliomyelitis' transmission mode, the cyclical nature of influenza, and the peculiar pattern of mortality in the 1918 flu pandemic, which sparked the development of several methods in the field (Morabia, 2013). These findings were made possible by Frost's pioneering large national health survey, whereby 113,000 questionnaires detailing the age and gender of each tenant in each home, as well as the time and duration of all cases of pneumonia or flu, whether mild, severe, or fatal, were gathered from house to house to obtain a population-representative sample (Doménech, 2020).

Figure 2: Disease causation is determined by the interplay between agent, host, and environment (Hajek, 1976).

In his metaphor, Frost suggested that the connection between infectious agents and their hosts is like that between "seeds and soil", with a germ (the seed) causing illness when its host (the soil) provides a conducive environment (Krieger, 2011). Although the most fundamental interpretation of this paradigm was that disease was induced by exposure to a new pathogenic agent, it was acknowledged that the effects of such exposure would rely on both the pathogenicity of the agent and the degree of resistance or susceptibility of the host (Engelmann, 2021). In his 1976 lecture, Frost drew an initial outline of an epidemic theory based on the presumption that the agent, the host, and the environment were in a state of equilibrium. This speech laid the ground for the development of the epidemiological triad, today more commonly referred to as the epidemiological triangle (Frost, 1976). However, this pathogen-host-environment link has existed since the 19th century, when John Snow's seminal map showed that cholera was spread through polluted water, namely the water from London's Broad Streep Pump, as documented earlier in this series. Since Frost, an enormously wide range of biomedical research areas, including genetics, molecular biology, immunology, biochemistry and endocrinology, have been largely responsible for elucidating host resistance factors, while epidemiology continues to investigate the causes and effects of a wide range of new and old pathogens in the environment (Cassel, 1976).


Disease Causation: Playing Whack-A-Mole With Variables

Why are some individuals more prone to illness than others? How is it that some individuals who are exposed to a disease show symptoms, some do not, and a small percentage become severely ill? Epidemiology's fundamental tenet is that diseases and other health events do not occur randomly in a society; rather, they are more likely to affect certain people than others owing to risk factors that aren't always distributed randomly across the population (Bovbjerg, n.d.). The interactions between the agent (the pathogen), the host, and the environment are depicted by the epidemiological triangle, a recognized model of infectious disease causation. There are many distinct ways that agent, host, and environmental variables interact, implying that different diseases encompass different balances and interactions among these three elements. Disentangling the features that make certain people more at risk than others is one of the main goals of epidemiology. Notably, epidemiologists deconstruct important elements of disease causation, incidence and transmission using this framework. The creation of suitable, practical, and efficient public health strategies to control or prevent illness depends critically on the assessment of all three elements and how they interact (Aschengrau & Seage, 2013). Notably, none of the components exhibit stochastic behavior: The agent changes during every phase of its existence while interacting with other agents in a dynamic environment. The host is likewise dynamic, whether for infectious agents that travel directly from host to host or indirectly via vectors (such as mosquitoes). Not only does the individual's exposure, susceptibility, and reaction to the pathogen and the environment differ, but also the vector is mobile and engages with a variety of agents (Jia et al., 2020).

Figure 3: Efficient public health strategies rely on epidemiologists' assessment of the agent-host-environment interaction (Narain, 2021).

The agent is symbolized by the first vertex of the triangle and refers to the infectious pathogen (virus, bacterium, parasite or other), that must be present for disease to occur. Its sheer existence, however, is not always sufficient to trigger illness. The pathogenicity (ability to cause disease) and the infectious dose (amount of pathogens required to establish an infection) of the agent are two parameters that impact whether or not exposure to that organism causes disease. The term "agent" has changed through time to encompass a wider range of scenarios beyond infectious diseases, such as physical forces, chemical pollutants, and biological and chemical etiologies. However, despite its effectiveness in infectious and many non-infectious diseases, the epidemiological triangle has failed to shed light on complex diseases such as cancer, cardiovascular disease and others, which appear to have multiple contributing components (van Seventer & Hochberg, 2017). The host is any organism affected by the disease (typically human or animal) and is denoted as the second vertex of the triangle. The host plays an important role in the transmission cycle of the infectious agent, acting both as a reservoir (the environment in which the pathogen generally lives, grows and multiplies) as well as a transmission point. The host may be symptomatic and present disease, or it may be asymptomatic but still be a carrier and hence capable of transmitting the pathogen. Host characteristics that determine susceptibility and response to a pathogenic agent include genetic makeup, nutritional and immune status, physiological structure, presence of disease or medical treatment, and psychological status (Rottier & Ince, 2003). Finally, the environment outside the host, other than the agent, that fosters or facilitates disease transmission forms the third corner of the triad. Some pathogens thrive in contaminated water, whilst others thrive in human blood (Lewis, 2023). Others, such as E. coli, thrive in mild temperatures but cannot tolerate extreme heat (van Elsas et al., 2011). The goal of an epidemiologist is to establish the connection between these three crucial components so that one of the axes can be broken.


The Epidemiological Triangle: A Seesaw Model

The host-pathogen-environment interactions that comprise the epidemiological triangle are intricately linked to the transmission of infectious diseases. Interrupting, altering, or eliminating any of the triangle's components can avert an epidemic and halt disease progression along the current transmission route. The environment forms the basis of the epidemiological triangle, with the host on one side and the pathogen on the other. As pathogen, host, and environmental variables achieve balance, epidemiological homeostasis can develop over time (Thrusfield, 1996). When one of the components contributing to the epidemiological balance is disrupted, the triangle tips sideways like a seesaw, representing an increase or decrease in disease incidence. If the epidemiological triangle is regarded as a seesaw, there are three possible outcomes, each reflecting an event with a high probability of a pandemic occurring: i) imbalances towards the pathogen becoming more pathogenic, i.e., with greater ability to induce disease once in the host; ii) host imbalances with a significant increase in the susceptible or endangered population; and iii) environmental imbalances that can either facilitate the spread of the infectious agent or alter the susceptibility of the host population (Engering et al., 2013). The epidemiological balance can shift in favor of the host or the pathogen, depending on how the contributing variables reinforce, weaken, or cancel each other out. Such imbalances often arise as a result of the introduction of a new pathogen into the population, an increase in the ability of an infectious agent to survive in the environment, to infect the host (infectivity), or to cause disease (pathogenicity) or serious illness (virulence). In addition, increases in the number of individuals at risk, as well as environmental changes that promote pathogen growth or transmission or weaken host resistance, contribute to epidemiological imbalances that favor disease spread (Engering et al., 2013; van Seventer & Hochberg, 2017).

Figure 4: Imbalances in one of the elements of the epidemiological triangle often culminate in disease outbreaks (Bond, 2020).
COVID-19 Pandemic: Breaking the Triad

The epidemiological triangle is a straightforward yet comprehensive causal conceptual framework that may apply to the Covid-19 epidemic in the same manner that it applied to cholera in the nineteenth century. The astonishing and catastrophic spread of the global Covid-19 pandemic has been driven by specific elements in each corner of the triangle, and their complex interplay. The SARS-CoV-2 virus is the corner of the triangle that garnered the most spotlight in the Covid-19 pandemic. In fact, this virus fulfils many of the characteristics for a successful pandemic agent: it is a tiny virus with no available treatment, that spreads by airborne particles, rendering it exceedingly contagious. Furthermore, it can be transmitted before symptoms arise, as well as from asymptomatic carriers (Hu et al., 2021; Tsui et al., 2020). Without vulnerable hosts, however, this highly transmissible virus would not have become an effective pandemic agent. Older people have been the most vulnerable hosts of Covid-19, a mortality pattern that contrasts with many other infections (such as influenza and salmonella) that disproportionately affect both the very young and the elderly. Pre-existing heart disease, diabetes, and obesity have all been recognized as risk factors for COVID-19 disease. However, because it was an entirely novel virus, immunological naivety was the most prominent host risk factor. This owes to the fact that no human has ever had contact with the virus and therefore did not evolve specific acquired immunity against this virus strain. The immune system can overreact to new invaders and cause severe and permanent organ damage through the immunological response itself (Ganesh, 2022; Zanza et al., 2022). Such naivety is at the root of the most severe symptoms and death rates observed during the pandemic. This becomes clear when one looks back to the H1N1 flu pandemic of 2009, when older people had greater odds of being protected from disease. This is a result of previous exposure to influenza subtypes that were common around the world since the "Spanish flu" of 1918–20. Pandemics have repeatedly shown that novelty equals severity (Morens et al., 2010). The third and perhaps most significant corner of the epidemiological triangle is the environment where susceptible hosts were exposed to the infectious agent as the Covid-19 pandemic unfolded. For a virus with the capacity to travel through the air, physical environmental variables such as distance from the source, indoor and outdoor habitats, ventilation, population density, and crowding ultimately influence whether and how extensively a pandemic spread.


Minimizing the interactions between these components helped restrict the dissemination of the COVID-19 pandemic. Before the advent of the COVID-19 vaccine, epidemiologists sought for numerous “interrupting factors” (IFs) between any two components of the triad to stem the spread of the disease. These can be divided into three categories: agent-host IFs, which aim to reduce host vulnerability or virus virulence; agent-environment IFs, which seek to decrease or eliminate the viral load on surfaces and in airborne droplets; and environment-host IFs, which aim to lessen the likelihood of active viruses to infect new hosts (Tsui et al., 2020). Although a COVID-19 vaccination and/or therapy is the most effective agent-host IF, until the vaccine was made available, strategies for combating the pandemic focused on developing workable solutions that optimize environment-host and agent-environment IFs. Shelter-in-place regulations and social isolation are examples of environment-host IFs. Furthermore, hand washing or decontamination on a regular basis, avoidance of physical contact, and refraining from touching one's face were all important in preventing the spread of COVID-19 (Chirico et al., 2020; Tsui et al., 2020). Additionally, agent-environment IFs covered self-quarantining of sick people, respiratory hygiene, mask use, and prohibiting travel from regions with widespread ongoing transmission. Surface cleansing using disinfectants has also proven to be a crucial agent-environment IF since SARS-CoV-2 may survive on inert surfaces for several days (Cimolai, 2022; Salahshoori et al., 2021).

Figure 5: Vaccination is the most effective agent-host interrupting factor when combating a pandemic (Waters, 2019).

Conclusions

Similar to COVID-19, new outbreaks of infectious diseases occur virtually every year and this trend is expected to persist owing to an aging population, easy access to travel and economic globalization. Governments and institutions design, execute, and enforce policies, procedures, protocols, and initiatives in response to public health emergencies such as a pandemic. The epidemiological triangle serves both as a disease etiology model and as an important tool in the design and implementation of such control efforts. Epidemiology studies disease transmission, the factors that underly disease genesis and etiology, and strategies to combat them. This requires an understanding of how political, social and scientific variables interact to increase disease risk, making epidemiology a critical field in disease prevention, risk reduction and emergency response.

Bibliographical References

Aschengrau, A., & Seage, G. R. (2013). Essentials of Epidemiology in Public Health (3rd Edition). Jones & Bartlett Learning.


Bovbjerg, M. (n.d.). Foundations of Epidemiology. Oregon State University. https://open.oregonstate.education/epidemiology/chapter/what-is-epidemiology/


Carter, K. C. (1985). Koch’s postulates in relation to the work of Jacob Henle and Edwin Klebs. Medical History, 29(4), 353–374. https://doi.org/10.1017/S0025727300044689


Casanova, J.-L., & Abel, L. (2013). The Genetic Theory of Infectious Diseases: A Brief History and Selected Illustrations. Annual Review of Genomics and Human Genetics, 14(1), 215–243. https://doi.org/10.1146/annurev-genom-091212-153448


Cassel, J. (1976). The contribution of the social environment to host resistance. American Journal of Epidemiology, 104(2). https://doi.org/10.1093/oxfordjournals.aje.a112281


Cavaillon, J.-M., & Legout, S. (2022). Louis Pasteur: Between Myth and Reality. Biomolecules, 12(4), 596. https://doi.org/10.3390/biom12040596


Chadli, A. (1986). Charles Nicolle and the accomplishments of his scientific thought. Archives de l’Institut Pasteur de Tunis, 63(1), 3–14. http://www.ncbi.nlm.nih.gov/pubmed/3535708


Chirico, F., Nucera, G., & Magnavita, N. (2020). COVID-19: Protecting Healthcare Workers is a priority. Infection Control & Hospital Epidemiology, 41(9), 1117–1117. https://doi.org/10.1017/ice.2020.148


Cimolai, N. (2022). Disinfection and decontamination in the context of SARS‐CoV‐2‐specific data. Journal of Medical Virology, 94(10), 4654–4668. https://doi.org/10.1002/jmv.27959


Doménech, F. (2020). Wade Hampton Frost and the (almost) Impossible Challenge of Counting the Dead from a Pandemic. BBVA OpenMind. https://www.bbvaopenmind.com/en/science/research/wade-hampton-frost-and-the-almost-impossible-challenge-of-counting-the-dead-from-a-pandemic/


Engelmann, L. (2021). A box, a trough and marbles: How the Reed-Frost epidemic theory shaped epidemiological reasoning in the 20th century. History and Philosophy of the Life Sciences, 43(3), 105. https://doi.org/10.1007/s40656-021-00445-z


Engering, A., Hogerwerf, L., & Slingenbergh, J. (2013). Pathogen–host–environment interplay and disease emergence. Emerging Microbes & Infections, 2(1), 1–7. https://doi.org/10.1038/emi.2013.5


Frost, W. H. (1976). Some Conceptions of Epidemics in General. American Journal of Epidemiology, 103(2). https://academic.oup.com/aje/article-abstract/103/2/141/105557


Ganesh, A. (2022). Epidemiology of Covid–19: An epidemic into a pandemic. Journal Of Dental Research And Dental Prospects, 1(1). https://www.acquaintpublications.com/article/epidemiology_of_covid19_an_epidemic_into_a_pandemic80


Glatter, K. A., & Finkelman, P. (2021). History of the Plague: An Ancient Pandemic for the Age of COVID-19. The American Journal of Medicine, 134(2), 176–181. https://doi.org/10.1016/j.amjmed.2020.08.019


Hu, B., Guo, H., Zhou, P., & Shi, Z.-L. (2021). Characteristics of SARS-CoV-2 and COVID-19. Nature Reviews. Microbiology, 19(3), 141–154. https://doi.org/10.1038/s41579-020-00459-7


Jia, P., Dong, W., Yang, S., Zhan, Z., Tu, L., & Lai, S. (2020). Spatial Lifecourse Epidemiology and Infectious Disease Research. Trends in Parasitology, 36(3), 235–238. https://doi.org/10.1016/j.pt.2019.12.012


Krieger, N. (2011). Epidemiology and the People’s Health. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195383874.001.0001


Lewis, L. (2023). Cholera, Dengue Fever, and Malaria: The Unquestionable Link to Water. The Water Project. https://thewaterproject.org/water-scarcity/cholera-dengue-fever-malaria-water


Morabia, A. (2013). Snippets from the past: the evolution of Wade Hampton Frost’s epidemiology as viewed from the American Journal of Hygiene/Epidemiology. American Journal of Epidemiology, 178(7), 1013–1019. https://doi.org/10.1093/aje/kwt199


Morens, D. M., Taubenberger, J. K., Harvey, H. A., & Memoli, M. J. (2010). The 1918 influenza pandemic: Lessons for 2009 and the future. Critical Care Medicine, 38, e10–e20. https://doi.org/10.1097/CCM.0b013e3181ceb25b


Mullner, R. M. (2023). epidemiology. In Encyclopedia Britannica. https://www.britannica.com/science/epidemiology


Rottier, E., & Ince, M. (2003). Disease and disease transmission. Controlling and Preventing Disease. http://ec.europa.eu/echo/files/evaluation/watsan2005/annex_files/WEDC/diseases/diseases.htm


Salahshoori, I., Mobaraki-Asl, N., Seyfaee, A., Mirzaei Nasirabad, N., Dehghan, Z., Faraji, M., Ganjkhani, M., Babapoor, A., Shadmehr, S. Z., & Hamrang, A. (2021). Overview of COVID-19 Disease: Virology, Epidemiology, Prevention Diagnosis, Treatment, and Vaccines. Biologics, 1(1), 2–40. https://doi.org/10.3390/biologics1010002


Satyarup, D., Kumar, M., Dalai, R. P., Mohanty, S., & Rathor, K. R. (2020). Theories of Disease Causation: An Overview. Indian Journal of Forensic Medicine & Toxicology. https://doi.org/10.37506/ijfmt.v14i4.12923


The National Academies. (2004). A Theory of Germs. In Science, Medicine, and Animals. National Academies Press (US). https://www.ncbi.nlm.nih.gov/books/NBK24649/


Thrusfield, M. (1996). Foundations of epidemiology. In Preventive Veterinary Medicine (Vol. 26, Issue 1). https://doi.org/10.1016/s0167-5877(96)90005-7


Tsui, B. C. H., Deng, A., & Pan, S. (2020). COVID-19: Epidemiological Factors During Aerosol-Generating Medical Procedures. Anesthesia & Analgesia, 131(3), e175–e178. https://doi.org/10.1213/ANE.0000000000005063


van Elsas, J. D., Semenov, A. V, Costa, R., & Trevors, J. T. (2011). Survival of Escherichia coli in the environment: fundamental and public health aspects. The ISME Journal, 5(2), 173–183. https://doi.org/10.1038/ismej.2010.80


van Seventer, J. M., & Hochberg, N. S. (2017). Principles of Infectious Diseases: Transmission, Diagnosis, Prevention, and Control. In International Encyclopedia of Public Health (pp. 22–39). Elsevier. https://doi.org/10.1016/B978-0-12-803678-5.00516-6


Wegman, M. E. (1994). Causation and Disease: A Chronological Journey. JAMA: The Journal of the American Medical Association, 271(8), 632. https://doi.org/10.1001/jama.1994.03510320074036


Zanza, C., Romenskaya, T., Manetti, A. C., Franceschi, F., La Russa, R., Bertozzi, G., Maiese, A., Savioli, G., Volonnino, G., & Longhitano, Y. (2022). Cytokine Storm in COVID-19: Immunopathogenesis and Therapy. Medicina (Kaunas, Lithuania), 58(2). https://doi.org/10.3390/medicina58020144


Visual Sources

Author Photo

Maria Inês Marreiros

Arcadia _ Logo.png

Arcadia

Arcadia, has many categories starting from Literature to Science. If you liked this article and would like to read more, you can subscribe from below or click the bar and discover unique more experiences in our articles in many categories

Let the posts
come to you.

Thanks for submitting!

  • Instagram
  • Twitter
  • LinkedIn
bottom of page