Publication: Disease ecology of rickettsial species: A data science approach
Issued Date
2020-05-01
Resource Type
ISSN
24146366
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2-s2.0-85084400773
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Mahidol University
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SCOPUS
Bibliographic Citation
Tropical Medicine and Infectious Disease. Vol.5, No.2 (2020)
Suggested Citation
Serge Morand, Kittipong Chaisiri, Anamika Kritiyakan, Rawadee Kumlert Disease ecology of rickettsial species: A data science approach. Tropical Medicine and Infectious Disease. Vol.5, No.2 (2020). doi:10.3390/tropicalmed5020064 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/56205
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Title
Disease ecology of rickettsial species: A data science approach
Abstract
© 2020 by the authors. We present an approach to assess the disease ecology of rickettsial species by investigating open databases and by using data science methodologies. First, we explored the epidemiological trend and changes of human rickettsial disease epidemics over the years and compared this trend with knowledge on emerging rickettsial diseases given by published reviews. Second, we investigated the global diversity of rickettsial species recorded in humans, domestic animals and wild mammals, using the Enhanced Infectious Disease Database (EID2) and employing a network analysis approach to represent and quantify transmission ecology of rickettsial species among their carriers, arthropod vectors or mammal reservoirs and humans. Our results confirmed previous studies that emphasized the increasing incidence in rickettsial diseases at the onset of 1970. Using the Global Infectious Diseases and Epidemiology Online Network (GIDEON) database, it was even possible to date the start of this increase of global outbreaks in rickettsial diseases in 1971. Network analysis showed the importance of domestic animals and peridomestic mammals in sharing rickettsial diseases with humans and other wild animals, acting as important hubs or connectors for rickettsial transmission.