fagan2888 / pci-outbreak

Policy Change Index for Outbreak (PCI-Outbreak)

Website: policychangeindex.org

Developers

Core maintainers:

• Julian TszKin Chan (julian.chan [AT] policychangeindex.org);
• Weifeng Zhong (weifeng.zhong [AT] policychangeindex.org).

External contributors:

• Kwan-Yuet "Stephen" Ho (KwanYuet.Ho [AT] leidos.com);
• Kit Lee;
• Kawai Leung.

What is the Policy Change Index for Outbreak (PCI-Outbreak)?

How severe was the COVID-19 outbreak in China, really? It is widely suspected that its official numbers understate the extent of the outbreak, and even the official numbers themselves are incoherent. On February 13, 2020, the Chinese authorities confirmed over 15 thousand new cases in the country, 40 times the previous day's number, due to a change in counting criteria. On April 17, they revised the death toll for Wuhan, the epicenter, upward by 50%, citing various omissions previously.

The PCI-Outbreak uses a machine learning method to gauge the true scale of COVID-19 in China, not through its official numbers but through how its state-controlled media covered the outbreak. The algorithm is trained on SARS-era articles in the People's Daily, the official newspaper of the Communist Party of China, to understand the wax and wane of the narrative as the epidemic cycle evolved. The algorithm then assesses future outbreaks' severity against the SARS benchmark.

The PCI-Outbreak is built on the idea that words can be more accurate than (some) numbers. While it may be trivial to release false statistics outright, it is more difficult to conceal the truth when the government has to address a public health crisis at length in national media. Take the beginning of COVID-19 for example: When the Chinese government announced the lockdown of Wuhan, a city with a population of 11 million people, and warned of a nationwide spread of the virus, the authorities had only confirmed fewer than 600 cases across the entire country. Changes in language, therefore, may provide us with a clearer picture of the severity than the questionable official numbers.

For details about the methodology and findings of this project, please see our forthcoming research paper.

Disclaimer

Results will change as the underlying models improve. A fundamental reason for adopting open source methods in this project is so that people from all backgrounds can contribute to the models that our society uses to assess and predict changes in public policy; when community-contributed improvements are incorporated, the model will produce better results.

Getting Started

The first step for everyone (users and developers) is to open a free GitHub account. And then you can specify how you want to "watch" the PCI repository by clicking on the Watch button in the upper-right corner of the repository's main page.

The second step is to get familiar with the PCI-Outbreak repository by reading the documentation.

If you want to ask a question or report a bug, create a new issue here and post your question or tell us what you think is wrong with the repository.

If you want to request an enhancement, create a new issue here and provide details on what you think should be added to the repository.

Citing the Policy Change Index for Outbreak (PCI-Outbreak)

Please cite the source of the latest Policy Change Index for Outbreak (PCI-Outbreak) by the website: https://policychangeindex.org.

For academic work, please see our forthcoming research paper and cite it when it is available.