| Background Ticks are one of the most important kinds of medical arthropods.and are second only to mosquitoes as vectors of infectious diseases.Ticks,as hematophagous parasites,sting hosts to transmit zoonoses with pathogens,thus leading to a great threat to human and animal health around the world.Ticks are widely distributed worldwide,a total of 3 families and 899 species ticks have been recorded worldwide.There are 9 genera and 124 species of ticks recorded in China.As the development of modern spatial information technologies which integrate the data concerning the ecological characteristics of geographical landscape,vectors as well as host animals,and human economic activities,application of such technologies,like Geographic Information System(GIS),remote sensing and global positioning system(GPS),provides new approaches and perspectives for studies of natural focus diseases regarding analyzing the epidemic distribution of diseases,characteristics of structure and landscape in natural epidemic foci,discovering new natural epidemic foci,and predicting vulnerable areas and epidemic strength.In recent years,emerging tick-borne infections have been constantly identified in China,with regional outbreaks from time to time,which can be significantly detrimental to the healthy population entering natural foci.Despite diverse habitat types,complicated distribution of ticks,and numerous tick-associated agents in China,the lack of related information and forecasting techniques of emerging tick-borne infections,limits the access to the development of scientific prevention and control.Therefore,carrying out tick distribution and tick-associated agents research,establishing risk assessment for tick-borne infections will certainly be beneficial to the establishment and implementation of targeted control measures,consequently promoting prevention of tick-borne infections.Objective To clarify the distribution of tick species in China.Make maps of ticks distribution in China by GIS.To summarize the characteristics of distribution of each genus.To understand the distribution and habitats of widely distributed ticks.Boosted regression tree model was established basis on the data of ticks distribution,land use type and altitude to predict potential distribution of ticks,to analyze factors affecting each species and,furthermore,to evaluate the affected population and areas.To clarify the spatial distribution of the main tick-associated agents in China.Establish a database of tick-associated agents in China and make the pathogenic spectrum by GIS.To carry out risk prediction of main tick-borne infections and minutely evaluate the potential threat of each agent according to detection records of tick-associated agents.Methods Mapping the spatial distribution of ticks in China: Based on the former literatures,references from 1950 to May 2017 and our research through investigations,the data of ticks distribution were summarized.After the standardization of ticks names and the administrative division codes,then a database on the distribution of ticks in China was set up.We created distribution maps of each tick genus and species from the aspect of space using ArcGIS 10.0 and then briefly described the results.Assessing and mapping the risk of widely distributed ticks in China: according to spatial distribution of widely distributed ticks,altitudes,climatic variables,land use data(1km*1km),prediction models about the distribution of 20 ticks were developed using boosted regression trees(BRT)method,of which the process was realized in R language environment.The model of each species was established correspondingly and the leading factors concerning the distribution were selected.The prediction results were associated to the map using ArcGIS 10.0.After being standardized,the medians of all variables in the models were associated with their relative contributions to conduct cluster analysis by method of weighted-average linkage in STATA10.0 software.We collected the data of tick-associated agents,and then standardized the tick and agent names.We started by dividing tick-associated pathogens into seven categories and then made maps accordingly through ArcGIS.Risk assessment models were developed in tick-borne infection Spotted fever group rickettsiae,the family Anaplasmataceae,Babesia spp at the county level to analyze the factors including diversty and potential distribution probability of ticks as well as the index of the distance from the positive county and proportion of the rural people.The risk index was ranked from risk free,low risk,middle to high risk.Results A total of 7,024 records of ticks distribution in China was included in the data set.High species richness of ticks appeared in Sipsong Panna,followed in Longnan,Akxoki,Lintsang,Bortala,Nanping,Sanji and Enshi cities.More than 20 species of ticks were recorded in these cities.A total of 26 species of the Ixodes were recorded in 30 provinces,autonomous regions or municipalities,of which 24 species were recorded in 432 counties.A total of 42 species of the Haemaphysalis were recorded in 32 provinces,of which 41 species were recorded in 562 counties.A total of 42 species of the Haemaphysalis were recorded in 32 provinces,of which 41 species were recorded in 562 counties.Ten species of the Amblyomma were recorded in 13 provinces,of which five species were recorded in 37 counties.A total of eight species of the Rhipicephalus,which were recorded in 406 counties in 29 provinces,are rare in Inner Mongolia and Northeast China.A total of 15 species of the Dermacentor were recorded in 26 provinces,of which 14 species were recorded in 571 counties.Most of the Dermacentor are distributed in the Palaearctic boundary.A total of seven species of the Rhipicephalus,which were recorded in 301 counties in 24 provinces,are mainly found in the Northwest.The distribution of three species of Anomalohimalaya were recorded only in the 5 counties of the Mengxin and Qingzang areas.A total of four species of the Ornithodoros were recorded in 36 counties in seven provinces.A total of nine species of the Argas were recorded in seven provinces,of which seven species were recorded in 90 counties.A boosted regression tree model at the county level reveals that D.nuttalli may be distributed in 562 counties of China,mainly in the northern provinces of China.Based on results of cluster analysis,20 widespread tick species were classified into seven categories.The first included D.nuttalli,D.silvarum,D.marginatus,Hae.japonica,Ar.persicus,of which the spatial distribution was characterized by mainly inhabiting in the north and at relatively high altitudes.Higher coverage of shrubland and coniferous forest were likely to contribute to the breeding of them.Furthermore,predicted areas were about 20 percent to 360 percent increase of actual recorded areas,with a 35 percent to 165 percent increase of affected population.The second included Hy.asiaticum,D.daghestanicus,I.crenulatus of which the spatial distribution was characterized by mainly inhabiting in Xinjiang and around,where there was a large but sparsely-populated area.Cumulative precipitation of the moistest or the hottest seasons contributed mostly to the distribution of them.In contrast,the larger the amount of rainfall,the less likely the breeding of ticks.Predicted areas were about 44 percent to 199 percent increase of actual recorded areas,with a 23 percent to 119 percent increase of affected population.The third included I.persulcatus and Hae.concinna,of which the spatial distribution was characterized by mainly inhabiting in Heilongjiang,Liaoning and northern areas in Xinjiang.Predicted areas were about the 114 percent to 142 percent increase of actual recorded areas,with a 143 percent to 235 percent increase of affected population.The fourth included Hae.longicornis,Hy.scupense and R.sanguineus.Higher coverage of shrubland contributed mostly here,where the larger the coverage of shrubland,the more likely the breed of the aforementioned ticks.Predicted areas were about the 28 percent to 167 percent increase of actual recorded areas,with a 104 percent to 353 percent increase of affected population.The fifth included only I.ovatus,which was dispersively spatially distributed,possibly inhabiting 321 counties in our country but mainly in the southern Tibet,part of Yunnan and Sichuan,where there were relatively high altitudes,small changes of temperature seasonality,and more coverage of mixed coniferous and broad leaved with less coverage of shrubland.Predicted areas were about the 323 percent of actual recorded areas,with a 427 percent increase of affected population.The sixth included R.microplus,R.haemaphysaloides,Hae.lagrangei and Hae.hystricis,which were sparsely-distributed in the central and southwest China.The distribution is mainly affected by temperature seasonality,and the relatively small temperature seasonality in the south is suitable for the breeding of the aforementioned ticks.Predicted areas were about the 101 percent to 400 percent increase of actual recorded areas,with a 110 percent to 522 percent increase of affected population.The seventh included I.granulatus and I.sinensis,which were mainly distributed in the south coastal China.Temperature and rainfall contributed mostly here,where some regions of higher temperature with smaller changes were the ideal place for the breed of the aforementioned ticks.As I.sinensis was especially affected by the rainfall in the winter,rainy regions were suitable for its breeding and growth.Predicted areas were about the 233 percent to 378 percent increase of actual recorded areas,with a 286 percent to 433 percent increase of affected population.A total of 1,190 records of tick-associated agents in China was included in the data set.Understand the two-dimensional matrix relationship between 44 species of ticks and 62 tick-associated agents.The ticks that detected most of the agents were Hae.longicornis(32),followed by I.persulcatus(20)and D.silvarum(20).The data showed that there were 13 species of spotted fever group rickettsiae were detected from at least 29 species of ticks,the main vector ticks were D.silvarum and Hae.longicornis.14 species of the family Anaplasmataceae were detected from 22 species of ticks.16 species of Babesia were detected in at least 17 ticks,and the most reported were R.sanguineus and I.persulcatus.Six species of theileria were detected in at least 16 ticks.Six genospecies of Borrelia burgdorferi sensu lato were detected in 28 ticks.Borrelia persica and Borrelia latyshewi were detected in the O.papillipes and O.tartakovskyi,respectively.The main vector of tick-borne encephalitis is I.persulcatus.Tick-borne encephalitis virus was also detected in D.silvarum,I.ovatus,Hae.concinna and Hy.asiaticum.The main vector of Severe fever with thrombocytopenia syndrome is Hae.longicornis.Severe fever with thrombocytopenia syndrome virus was also detected in R.microplus,Hae.concinna and R.sanguineus.The vector tick of the Crimean-Congo haemorrhagic fever is Hy.asiaticum.Francisella tularensis was detected in I.persulcatus,Hae.longicornis,D.silvarum,D.everestianus and Hy.asiaticum.Up to 14 species ticks were detected Coxiella burnetii.The risk assessment indicated that 217 counties are high risk areas of spotted fever group rickettsiae,372 counties are high-risk areas of the family Anaplasmataceae,and 303 counties are the high-risk areas of Babesia.In Heilongjiang,the counties in high risk areas are obviously more than those in the surrounding areas,the risk grades of northern Xinjiang,southern Gansu and most of Shaanxi are also higher.Conclusion For the first time,the spatial distribution of 124 species ticks,9 genera were presented use the geographical information system in China.The potential distribution area of widely distributed species ticks in China was predicted by boosted regression tree model,and the prediction maps were made.The relationship between the types of land use,climatic variables and altitude affecting the distribution of ticks was analyzed,and the area and population affected by ticks were predicted.The greatest highlight of the study is to use both positive and negative areas in the process of forecasting modeling,so that the prediction results are more reliable.A database of tick borne pathogens recorded in China was set up,and a series of spatial distribution maps were made.The risk assessment of tick borne infectious such as Spotted fever group rickettsiae,the family Anaplasmataceae and Babesia,was assessed using risk assessment model. |
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