Abstract

Citation

Researchers should cite this work as follows:

• Adler, F. (2023). 2017-Fred_Adler-Mathematically Modeling Asthma. SIMIODE, QUBES Educational Resources. doi:10.25334/XG39-V558

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Article Context

Description

Adler, Fred. 2017 Mathematically Modeling Asthma. Blog Posting.  3 pp.

See https://sinews.siam.org/Details-Page/mathematically-modeling-asthma . Accessed 28 March 2023.

From the article, “Asthma—like diabetes, heart disease, and cancer—does not have a single initiating cause, making the development of models that start with cause and end with effect impossible to formulate. It doesn’t have well-defined triggers like the human immunodeficiency virus (HIV) for AIDS or the Cystic fibrosis transmembrane conductance regulator (CFTR) gene for cystic fibrosis.Growing rates of asthma, particularly in urban areas, increase the urgency of finding ways to unravel the causal pathways underlying this condition in order to find places to effectively intervene. Mathematical models provide one of the most powerful approaches to analyzing such complex problems.”

“First, the frequency of infections in infants depends on transmission at home and at daycare centers, and we have modeled how the distribution of family size and age can affect early exposure and infection. One key result is that transmission of rhinovirus is strongly dependent on symptoms. Given the general consensus that most symptoms are a consequence of the immune response, which in turn depends on each individual's history of infection, embedding the transmission dynamics for a given rhinovirus serotype (of which there are well over 100) into a long-term high-dimensional system will be crucial. Modeling the immune response is thus the second and most important component of a comprehensive modeling approach to asthma.

“Third, the triggers for asthma, as noted above, center around the immune response, whether to severe early infections, allergens, or lack of exposure to the right kind of dirt. Our models have examined how a viral infection can tip the immune system into a different state, with the potential to predispose an individual to future asthma.”

Keywords:  asthma, differential equation, system, model, infections, immune response,