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Draft:Epidemiology of complex biological systems

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  • Comment: The sections read more like a report or an essay rather than an encylopeadiac article. I suggest looking at an existing article on Wikipedia with a similar topic and copying the structure, layout, and formatting GMH Melbourne (talk) 22:35, 25 September 2024 (UTC)

Epidemiology of complex biological systems is an interdisciplinary field that focuses on understanding the spread, control, and dynamics of biological processes within populations, particularly when these processes involve multiple, interacting components. This area of study combines principles from epidemiology, population dynamics, and the study of biological systems to explore how organisms, their environments, and external factors influence health outcomes on various scales, from individual organisms to entire ecosystems.

Overview of complex biological systems

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A biological system refers to a group of organs or structures that work together to perform a particular function within an organism, but the concept can be extended to ecological and population levels. Biological systems are inherently complex,[1] often characterized by interactions across various scales (molecular, cellular, organismal, and ecosystem).[2] These systems can be influenced by internal factors, such as genetics, as well as external ones, like environmental changes and species interactions.

Role of population dynamics

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Population dynamics is a key aspect of understanding complex biological systems. It explores how populations of species grow, shrink, and interact with each other and their environments. This field helps epidemiologists understand how diseases spread through populations by modeling factors such as birth rates, death rates, and migration patterns. In complex biological systems, the movement and growth of populations, both human and non-human, play a critical role in the epidemiological spread of diseases and other biological phenomena.[3]

Epidemiological approach

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Epidemiology is traditionally focused on understanding the causes and spread of diseases in human populations,[4] but its principles can be applied to any biological system.[5] The epidemiology of complex biological systems extends this focus to include non-human species and ecosystems, considering how infectious diseases, toxins, or other biological phenomena spread across interconnected systems. These systems may include multiple species, environmental factors, and human influences, making the modeling and prediction of epidemiological trends particularly challenging.

Case study: harmful algal blooms

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A concrete example of the epidemiology of a complex biological system is the study of harmful algal blooms (HABs). HABs are caused by the rapid growth of certain algae species that can produce toxins harmful to both aquatic life and humans. These blooms are influenced by a range of factors, including waterbody depth and volume, geology, water chemistry, temperature, nutrient availability, and human current and historical activities namely pollution and land use changes.

HABs can disrupt entire ecosystems, impact fisheries, human health and cause economic losses. Effective management of HABs involves understanding the population dynamics of algae and the broader ecosystem, as well as the epidemiological risks to human[6][7] and animal health.[8][9][10]

The interaction between biological systems (e.g., algae, fish , and microbial communities), environmental conditions, and human activity creates a complex scenario that requires epidemiological approaches to factor all these elements, create a model to predict and then offer a treatment protocol.

Epidemiological models in this context are used to study the causes and spread of HABs, and to predict outbreaks based on environmental factors and population data.[11] These models help policymakers and environmental managers to mitigate risks by controlling nutrient pollution, monitoring water conditions, issuing early warnings to affected communities and enable improvement of the treatment protocol.

References

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  1. ^ Kaneko, Kunihiko (2006-09-14). Life: An Introduction to Complex Systems Biology. Springer. ISBN 978-3-540-32667-0.
  2. ^ Ross, John; Arkin, Adam P. (2009-04-21). "Complex Systems: From chemistry to systems biology". Proceedings of the National Academy of Sciences. 106 (16): 6433–6434. doi:10.1073/pnas.0903406106. ISSN 0027-8424. PMC 2672531. PMID 19380716.
  3. ^ Aleta, Alberto; Hisi, Andreia N. S.; Meloni, Sandro; Poletto, Chiara; Colizza, Vittoria; Moreno, Yamir (2017). "Human mobility networks and persistence of rapidly mutating pathogens". Royal Society Open Science. 4 (3): 160914. arXiv:1611.02768. Bibcode:2017RSOS....460914A. doi:10.1098/rsos.160914. ISSN 2054-5703. PMC 5383836. PMID 28405379.
  4. ^ Galea, S.; Riddle, M.; Kaplan, G. A (2009-10-09). "Causal thinking and complex system approaches in epidemiology". International Journal of Epidemiology. 39 (1): 97–106. doi:10.1093/ije/dyp296. ISSN 0300-5771. PMC 2912489. PMID 19820105.
  5. ^ Pearce, Neil; Merletti, Franco (2006-01-16). "Complexity, simplicity, and epidemiology". International Journal of Epidemiology. 35 (3): 515–519. doi:10.1093/ije/dyi322. ISSN 1464-3685. PMID 16415326.
  6. ^ CDC (2024-05-15). "Harmful Algal Blooms and Your Health". Harmful Algal Bloom (HAB)-Associated Illness. Retrieved 2024-09-19.
  7. ^ Niedermeyer, Timo; M.-L. Janssen, Elisabeth; Adamovský, Ondřej (May 2021). "Toxic Cyanobacteria in Water – a Guide to Their Public Health Consequences, Monitoring and Management: the totally revised second edition is now available" (PDF). cyanocost.
  8. ^ Duarte, Bernardo; Caçador, Isabel, eds. (2019-08-14). Ecotoxicology of Marine Organisms (1 ed.). Boca Raton : CRC Press, Taylor & Francis Group, [2019] | "A science publishers book.»: CRC Press. doi:10.1201/b22000. ISBN 978-1-315-26749-4.{{cite book}}: CS1 maint: location (link)
  9. ^ Rattner, Barnett A.; Wazniak, Catherine E.; Lankton, Julia S.; McGowan, Peter C.; Drovetski, Serguei V.; Egerton, Todd A. (2022-12-01). "Review of harmful algal bloom effects on birds with implications for avian wildlife in the Chesapeake Bay region". Harmful Algae. 120: 102319. Bibcode:2022HAlga.12002319R. doi:10.1016/j.hal.2022.102319. ISSN 1568-9883. PMID 36470599.
  10. ^ Burkholder, JoAnn M.; Shumway, Sandra E.; Glibert, Patricia M. (2018-07-02), Shumway, Sandra E.; Burkholder, JoAnn M.; Morton, Steve L. (eds.), "Food Web and Ecosystem Impacts of Harmful Algae", Harmful Algal Blooms (1 ed.), Wiley, pp. 243–336, doi:10.1002/9781118994672.ch7, ISBN 978-1-118-99467-2, retrieved 2024-09-19
  11. ^ Janssen, Annette BG; Janse, Jan H; Beusen, Arthur HW; Chang, Manqi; Harrison, John A; Huttunen, Inese; Kong, Xiangzhen; Rost, Jasmijn; Teurlincx, Sven; Troost, Tineke A; van Wijk, Dianneke; Mooij, Wolf M (2019-02-01). "How to model algal blooms in any lake on earth". Current Opinion in Environmental Sustainability. Environmental Change Assessment. 36: 1–10. Bibcode:2019COES...36....1J. doi:10.1016/j.cosust.2018.09.001. ISSN 1877-3435.
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