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Modelling the Risk of Imported COVID-19 Infections at Maritime Ports Based on the Mobility of International-Going Ships.
- Source :
- ISPRS International Journal of Geo-Information; Jan2022, Vol. 11 Issue 1, p60, 1p
- Publication Year :
- 2022
-
Abstract
- Maritime ports are critical logistics hubs that play an important role when preventing the transmission of COVID-19-imported infections from incoming international-going ships. This study introduces a data-driven method to dynamically model infection risks of international ports from imported COVID-19 cases. The approach is based on global Automatic Identification System (AIS) data and a spatio-temporal clustering algorithm that both automatically identifies ports and countries approached by ships and correlates them with country COVID-19 statistics and stopover dates. The infection risk of an individual ship is firstly modeled by considering the current number of COVID-19 cases of the approached countries, increase rate of the new cases, and ship capacity. The infection risk of a maritime port is mainly calculated as the aggregation of the risks of all of the ships stopovering at a specific date. This method is applied to track the risk of the imported COVID-19 of the main cruise ports worldwide. The results show that the proposed method dynamically estimates the risk level of the overseas imported COVID-19 of cruise ports and has the potential to provide valuable support to improve prevention measures and reduce the risk of imported COVID-19 cases in seaports. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 22209964
- Volume :
- 11
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- ISPRS International Journal of Geo-Information
- Publication Type :
- Academic Journal
- Accession number :
- 154815903
- Full Text :
- https://doi.org/10.3390/ijgi11010060