Karin Ebey, a student from Eckerd College, worked with Dr. Kyle Dahlin and Dr. John Vinson on modelling the effects of demographic and environmental noise on mosquito-borne disease.
Abstract: Mosquito-borne diseases are a significant and growing public health burden globally. Predictions about the future spread and impact of mosquito-borne disease outbreaks can help inform direct control and prevention measures. However, climate change is expected to increase climate variability which may, in turn, shape the future of mosquito-borne disease outbreaks globally. In this study we sought to determine the effects of demographic and environmental noise on the duration and size of outbreaks predicted by models of mosquito-borne disease. We adapted the standard Ross-Macdonald mosquito-borne disease model to include environmental and demographic stochasticity. Using this model, we examined how the presence of demographic and environmental noise affected the probability of endemic disease, probability of an outbreak, peak number of cases, and duration of outbreaks at increasing levels of the basic reproduction number (R0) and environmental noise strength. Increasing environmental noise reduces the risk of endemic disease and outbreaks but the largest outbreaks occur at intermediate levels of environmental noise. If an outbreak does die out, it ends early on in the simulation period. With noise present, R0 alone is insufficient to definitively predict whether an outbreak occurs. Increasing environmental noise associated with climate change may cause reduced risk of endemic disease and outbreaks. Future directions include a sensitivity analysis to examine the influence of parameters in the presence of noise and explore the effects of having only certain parameters impacted by noise.
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