Lyme disease is a common vector-borne illness that has experienced a significant rise in cases lately. The frequency of Lyme Disease is highly dependent on the climate as ticks, the primary source of Lyme Disease, change activity based on seasonal weather changes. Therefore, it is safe to assume that climate change will have some influence on the occurrence of Lyme disease. Other research papers have conducted similar investigations, and even though these models only focus on New York, this does not mean the effects described are limited to New York. This model is not intended to simulate the consequences solely in New York, but to serve as a potential microcosm of how climate change can affect Lyme Disease in other areas. The linear regression models (a model created to predict future data based on current data) I used aimed to test this relationship and tested it against a model created by Nicholas H. Ogden. Due to the unpredictability of the spread of disease, reliable models can be challenging to create. However, based on my results, a positive relationship between climate change and the incidence of Lyme Disease is almost certainly not due to random chance and is worth further investigation.
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Phillip Kim (2024) studied this question.
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