In the ongoing battle against infectious diseases, mathematicians and epidemiologists harness the power of mathematics to predict and understand the dynamics of disease spread. The fundamental concept is deceptively simple: observe the growth pattern and use mathematical expressions to project how a disease might propagate over time. If the number of infections doubles at a consistent rate, then predicting future cases becomes a matter of mathematical extrapolation. Yet, amidst the mathematical precision, a crucial question looms: Are these models realistic? The answer lies in the diverse nature of infectious diseases, each presenting unique challenges. Models, while based on certain assumptions, strive to capture the essence of a disease’s dynamics. For novel viruses like COVID-19, where uncertainties abound, modelers grapple with missing information, making educated extrapolations and decisions about parameter importance.
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This is great! I also think that it would be beneficial for field epidemiologists to have access to a wide range of tools to apply these mathematical concepts
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This just showcases how important maths is everywhere.
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