Characterizing the effectiveness of COVID-19 mitigation measures: A data-centric approach
46th International Conference on Telecommunications and Signal Processing, TSP 2023, Virtual, Online, Çek Cumhuriyeti, 12 - 14 Temmuz 2023, ss.254-259, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/tsp59544.2023.10197711
- Basıldığı Şehir: Virtual, Online
- Basıldığı Ülke: Çek Cumhuriyeti
- Sayfa Sayıları: ss.254-259
- Anahtar Kelimeler: clustering, COVID-19, data-centric engineering pandemic, performance statistic, SARS-CoV-2
- Ankara Yıldırım Beyazıt Üniversitesi Adresli: Evet
Özet
COVID-19 represents a serious threat to both national health and economic systems. To curb this pandemic, the World Health Organization (WHO) issued a series of COVID-19 public safety guidelines. Different countries around the world initiated different measures in line with the WHO guidelines to mitigate and investigate the spread of COVID-19 in their territories. The aim of this investigation is to use a data-centric approach to quantitatively weigh the effectiveness of these control measures. We propose a simple performance statistic that quantifies general performance in light of the different measures that were initiated and implemented. This would be beneficial in informing policy-makers when it is safe to ease the measures and avoid further disaster. Lastly, a COVID-19 web-based time-line visualization that enables comparison of performances and cases across continents and subregions is presented. In our work, we achieved to provide a performance index that can help quantify how response measures, and provide quick feedback to augment decision-making processes with the evaluation of COVID-19 response measures. Also, we introduce a simple and computationally efficient performance metric for understanding the influence of control measures in different countries across different continents.