Risk Assessment of the Overseas Imported COVID-19 of Ocean-Going Ships Based on AIS and Infection Data
Article dans une revue avec comité de lecture
Date
2020Journal
ISPRS International Journal of Geo-InformationAbstract
Preventing and controlling the risk of importing the coronavirus disease (COVID-19) has rapidly become a major concern. In addition to air freight, ocean-going ships play a non-negligible role in spreading COVID-19 due to frequent visits to countries with infected populations. This research introduces a method to dynamically assess the infection risk of ships based on a data-driven approach. It automatically identifies the ports and countries these ships approach based on their Automatic Identification Systems (AIS) data and a spatio-temporal density-based spatial clustering of applications with noise (ST_DBSCAN) algorithm. We derive daily and 14 day cumulative ship exposure indexes based on a series of country-based indices, such as population density, cumulative confirmed cases, and increased rate of confirmed cases. These indexes are classified into high-, middle-, and low-risk levels that are then coded as red, yellow, and green according to the health Quick Response (QR) code based on the reference exposure index of Wuhan on April 8, 2020. This method was applied to a real container ship deployed along a Eurasian route. The results showed that the proposed method can trace ship infection risk and provide a decision support mechanism to prevent and control overseas imported COVID-19 cases from international shipping.
Files in this item
- Name:
- IRENav-Claramunt-2020-ISPRS.pdf
- Size:
- 2.059Mb
- Format:
- Description:
- Article principal
Collections
Related items
Showing items related by title, author, creator and subject.
-
Article dans une revue avec comité de lectureWU, Huafeng; MENG, Qingshun; XIAN, Jiangfeng; MEI, Xiaojun; CLARAMUNT, Christophe; CAO, Junkuo (MDPI, 2019)Wireless Sensor Networks (WSNs) have been extensively applied in ecological environment monitoring. Typically, event boundary detection is an effective method to determine the scope of an event area in large-scale environment ...
-
Article dans une revue avec comité de lectureWANG, Zhihuan; CLARAMUNT, Christophe; WANG, Yinhai (MDPI, 2019)The increasing availability of big Automatic Identification Systems (AIS) sensor data offers great opportunities to track ship activities and mine spatial-temporal patterns of ship traffic worldwide. This research proposes ...
-
Article dans une revue avec comité de lectureSILAVI, Tolue; HAKIMPOUR, Farshad; CLARAMUNT, Christophe; NOURIAN, Farshad (Elsevier, 2015)This paper introduces a spatial database and ontology-enabled framework that models and operationalizes the relation between urban forms and their responsiveness to the needs of its user. The objective is to offer a framework ...
-
Article dans une revue avec comité de lectureAFYOUNI, Imad; RAY, Cyril; CLARAMUNT, Christophe; ILARRI, Sergio (Lavoisier, 2015)Cet article développe une représentation de données spatiales d’un environnement intérieur dit “indoor” qui tient compte des dimensions contextuelles centrées sur l’utilisateur et aborde les enjeux de gestion de données ...
-
Article dans une revue avec comité de lectureLE YAOUANC, Jean-Marie; SAUX, Eric; CLARAMUNT, Christophe (Springer Verlag, 2010)The modeling of a landscape environment is a cognitive activity that requires appropriate spatial representations. The research presented in this paper introduces a structural and semantic categorization of a landscape ...