The ability to detect seasonality of disease incidence is an important factor in mitigating the spread of the disease, because it helps public health officials prepare for potential outbreaks. Some diseases, such as Buruli ulcer, are rare, and seasonality may be hard to detect due to the low number of cases. On top of having a low number of cases, there is a long incubation period, and people who are infected may delay seeking treatment, which can potentially lead to a lower probability of detecting true seasonality in disease transmission or incidence. We conducted simulations to see if delay in seeking treatment among infected individuals reduces our ability to accurately capture the underlying seasonality of the causative disease. We used Buruli ulcer as our disease of interest, because there has yet to be confirmation of seasonality, although it is highly suspected it occurs around the rainy seasons in endemic countries. We created a simulated seasonality for Buruli ulcer with high probability of detection of seasonality in the absence of incubation and treatment delays. We next introduced delays such as incubation period and time-to-seek treatment to quantify the resulting reduction in detecting seasonality. Our results indicate a delay in seeking treatment can have a measureable effect on our ability to detect seasonality for a disease such as Buruli ulcer.
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About this Master's Thesis
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|Committee Chair / Thesis Advisor|
|Examining the impact of heterogeneity in timing of health seeking behavior on the power to detect seasonal effects of disease, using Buruli ulcer as the example ()||2018-04-17||