A Prediction Model for Economic Impacts from a Pandemic

Many people become ill and even dying because of the COVID-19 pandemic. Not only does the COVID-19 cause the serious health problems, but it also has brought significant economic impacts. For example, the unemployment rates of North Dakota are 2.4%, 9.1%, 9.1%, and 6.1% in June 2019, April 2020, May 2020, and June 2020, respectively. It is obvious that the pandemic increases the unemployment rate, but it also shows some anomalies like the rate dropped from 9.1% to 6.1% from May to June though the number of COVID cases increased. This research tries to propose a prediction model for economic impacts from a pandemic, so when the next pandemic hits again, we will be well prepared for the worst.

The first step of this research is to collect all economic data as much as possible like the data provided by the US Bureau of Labor Statistics including the numbers and rates of unemployment, productivity, and inflation state by state and month by month. After that, various predictive models such as classification, clustering, or time series will be studied and a suitable model is picked and used to predict the economic impacts from a pandemic. Finally, the accuracy of the prediction will be validated by using the oldest data to predict the old data and see whether the model successfully predicts the impacts.

This research is heavily related to data science including data collection, preparation, indexing & storage, processing & analysis, visualization, sharing, and application. It will study and analyze the collected data, present the results visually by using graphs and charts, and share and apply the results. At the same time, the social and psychological factors will be considered too. For example, a drop of unemployment rate may be because people risk their lives in order to make a living, not because the pandemic subsides.

COVID-19, coronavirus, predictive analytics, Firebase, BigQuery, cloud computing, data processing and management

Take the following steps to build an Internet-enabled system:
  1. Automatically collect data by using web crawlers.
  2. Save the collected data in the cloud-based Firebase.
  3. Use BigQuery to analyze the data saved in the Firebase and display the results on the Web by using various figures and charts.
  4. Summarize the results and give conclusions.
  1. Web search engine
  2. Internet-enabled Firebase database
  3. Google Firebase
  4. Google BigQuery
  5. Stream Collections to BigQuery from Firebase