Group Disease
This repository contains a project that focuses on the analysis of the evolution and dynamics of Ebola and Covid using Hawkes Processes. Hawkes Processes are a powerful tool for modelling and understanding the temporal dependencies and self-exciting nature of disease spread.
The main objective of this project is to explore and analyze the spread of Ebola and Covid cases using Hawkes Processes. The project involves the following key steps:
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Data Preprocessing: Clean and preprocess the collected data to ensure consistency and quality. This step involves handling missing values and transforming the data into a suitable format for analysis.
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Hawkes Process Modeling: Apply the Hawkes Process framework to model the temporal dynamics of Ebola and Covid cases. This includes estimating the parameters of the Hawkes Process, such as the baseline intensity and kernel parameters, which capture the self-exciting nature of the events.
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Visualization and Analysis: Visualize the results of the Hawkes Process modeling to gain insights into the patterns and interdependencies of Ebola and Covid cases over time. This includes generating plots and separating data in different ways.
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Interpretation and Evaluation: Interpret the results of the analysis in the context of Ebola and Covid dynamics. Evaluate the effectiveness of the Hawkes Process modeling approach and discuss the implications of the findings for understanding and managing these diseases.
Garske, T., Cori, A., Ariyarajah, A., Blake, I. M., Dorigatti, I., Eckmanns, T., Fraser, C., Hinsley, W., Jombart, T., Mills, H. L., Nedjati-Gilani, G., Newton, E., Nouvellet, P., Perkins, D., Riley, S., Schumacher, D., Shah, A., Kerkhove, M. D. V., Dye, C., . . . Donnelly, C. A. (2017). Heterogeneities in the case fatality ratio in the west african ebola outbreak 2013–2016. Philosophical transactions. Biological sciences, 372(1721), 20160308