The linked article is for SIAM News, the magazine for members of the Society for Industrial and Applied Mathematics (SIAM). However, even though the main audience for this magazine is professional mathematicians, I wrote it to be understandable even if you gloss over the math.

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Multiscale Models Shed Light on Tuberculosis

For SIAM News:

As demonstrated by the ongoing COVID-19 pandemic, a thorough understanding of infectious diseases requires data and models on multiple interconnected levels. Epidemiology addresses population-level issues, transmission models describe individuals within their environments, and a variety of biomedical approaches help researchers comprehend the way in which pathogens infiltrate the body — and the body’s ability to fight back.

Tuberculosis (TB) is one of the deadliest infectious diseases in the world. It accounts for roughly 1.5 million deaths per year and causes the most HIV-related casualties. While decision-makers know in principle how to slow the spread of certain illnesses, TB is more stubborn than most.

“TB is unique compared to many other diseases and the way we treat them,” Denise Kirschner, a mathematical biologist at the University of Michigan Medical School, said. During her plenary talk at the hybrid 2022 SIAM Conference on the Life Sciences (LS22), which took place concurrently with the 2022 SIAM Annual Meeting in Pittsburgh, Pa., this July, Kirschner described the major challenges that surround TB’s characterization.

Read the rest at SIAM News