Tracking the Wings of Covid-19 by Modeling Adaptability with Open Mobility Data

Figures & data

Figure 1. Global Impact of travel restrictions (27Jan-25 April, source: Flightradar)

Figure 2. Impact of travel restrictions to China (30Dec-23 March, source: Flightradar)

Figure 3. The machine self-supervised statistical learning architecture

Figure 4. Aerial connectivity modeled from data collected from Wikipedia on 21st March 2020

Figure 5. Modeling China mobility index

Figure 6. Measurements of betweenness and entropy to model the significance and interdependence of change. The labels on 1 and 2 represent the mobility index and the associated cities

Figure 7. Hong Kong air connectivity modeled considering the closeness and the betweenness (Node “1” refers to Hong Kong; strong connectivity identified to London; source dataset: Department of Health (2020)

Table 1. The interdependence results for the Hong Kong node (source: (https://www.chp.gov.hk/files/misc/)

From	To	Interdependence
Hong Kong	London	22
Hong Kong	Manila	9
Hong Kong	Dubai	9
Singapore	Hong Kong	9
Hong Kong	Frankfurt	8
Hong Kong	New York	7
Hong Kong	Vancouver	6
Hong Kong	Zurich	6
Hong Kong	Bangkok	6
Hong Kong	Kuala Lumpur	6
Hong Kong	Madrid	4

Department of Health. 2020. List of Flights/Trains/Ships/Cars Taken by Probable/Confirmed Cases of COVID-19 during the symptomatic phase in the past 14 days. 2020. https://data.gov.hk/en-data/dataset/hk-dh-chpsebcddr-novel-infectious-agent/resource/1bda2bd2-8c00-4379-8ed9-e0afb495d5de.

 Google Scholar