ArticleHealthcare analytics (New York, N.Y.)2021
SCORECOVID: A Python Package Index for scoring the individual policies against COVID-19.
Article in Healthcare analytics (New York, N.Y.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 15 citations in OpenAlex.
- How to build disaster-resilient cities and societies for making people happy.Building and environment · 2023Review
- Policy analysis and data mining tools for controlling COVID-19 policies.Network modeling and analysis in health informatics and bioinformatics · 2023Article
- Time-series COVID-19 policymaker analysis of the UAE, Taiwan, New Zealand, Japan and Hungary.Dialogues in health · 2022Article
- scorecovid for scoring individual country COVID-19 policies in the world.Software impacts · 2022Article
- Discovering COVID-19 state sustainable policies for mitigating and ending the pandemic.Cities (London, England) · 2022Article
- Sustainable policy: Don't get infected and don't infect others.Journal of hazardous materials advances · 2022Article
- A herd immunity approach to the COVID-19 pandemic?Health and technology · 2022Article
- Deathdaily: A Python Package Index for predicting the number of daily COVID-19 deaths.Network modeling and analysis in health informatics and bioinformatics · 2022Article
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study proposes SCORECOVID, a new Python Package Index (PyPI) for scoring individual policies against covid-19 and mitigating the pandemic. The new PyPI package consists of two modules. The first module automatically scrapes the latest information on the number of deaths and population by COVID-19 to score individual policies for a given country. The second module calculates the score by dividing the number of deaths by the population in millions. The Federal Communications Commission (FCC) in the US estimates the economic value of a statistical life to be $9.5 million per individual. The higher the number of deaths, the greater the economic loss. To use the best policies to reduce the number of deaths, we should adopt measures and methods from exceptional countries with high scores. The proposed method reveals two groups: a high-scored group and a low-scored group. The number of deaths is an indicator of economic and health policy scores. SCORECOVID is the world's first open-source policy scoring tool for COVID-19. It is designed to help many countries utilize state-of-the-art analytics methods to effectively mitigate the COVID-19 pandemic.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.