Using Databricks to Develop Stats & Mathe Models to Forecast Monkeypox Outbreak in Washington State

Description

In the spring and summer of 2022, monkeypox was detected in the United States and quickly spread throughout the country. To contain and mitigate the spread of the disease in Washington State, the Washington Department of Health data science team used the Databricks platform to develop a modeling pipeline that employed statistical and mathematical techniques to forecast the course of the monkeypox outbreak throughout the state. These models provided actionable information that helped inform decision making and guide the public health response to the outbreak. We used contact-tracing data, standard line-lists, and published parameters to train a variety of time-series forecasting models, including an ARIMA model, a Poisson regression, and an SEIR compartmental model. We also calculated the daily R-effective rate as an additional output. The compartmental model best fit the reported cases when tested out of sample, but the statistical models were quicker and easier to deploy and helped inform initial decision-making. The R-effective rate was particularly useful throughout the effort. Overall, these efforts highlighted the importance of rapidly deployable and scalable infectious dise…

Description from YouTube. Full content on the video page.