Geographic distribution and modeling of ticks in the Republic of Korea and the application of tick models towards understanding the distribution of associated pathogenic agents

Abstract

Encounters with ticks harboring pathogenic agents have demonstrated increasing public health implications. Tick surveillance in the Republic of Korea (ROK) is essential for determining tick distributions and the potential regions where tick-borne pathogens may be found. Extensive tick collections (tick drags and tick flagging) were previously performed by Force Health Protection & Preventive Medicine (FHP&PM), Medical Activity-Korea (MEDDAC-K)/65th Medical Brigade (MED BDE) personnel, in collaboration with the Public Health Activity-Korea in the ROK. A total of 144,131 ticks were collected from 2,019 locations during 2004 to 2016. The associated location data (GPS coordinates) for each of the collection sites were incorporated into distribution maps using ArcGIS and combined with environmental data in the Maxent ecological niche modeling program (n = 733 geographical unique locations from 1,429 presence records/collection locations) to produce estimates of tick distributions for each species. The predominant tick species found and modeled were, in order of prevalence: Haemaphysalis longicornis, H. flava, Ixodes nipponensis, H. phasiana, I. turdus, Amblyomma testudinarium, H. japonica, and I. persulcatus. Haemaphysalis longicornis, H. flava, and I. nipponensis were the most widely distributed and most commonly collected species of ticks. The maps and models of suitable habitat regions produced in this study provide a better understanding of where there are potential risks of encountering a particular tick species, and which, as demonstrated herein with rickettsiae, can be used to study tick-pathogen dynamics of diseases. Knowledge of the distribution of ticks is important in the ROK because of the presence of tick-borne diseases, such as severe fever with thrombocytopenia syndrome, tick-borne encephalitis, rickettsioses, and borrelioses. © 2021 Elsevier GmbH