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Mapping ticks and tick-borne pathogens in China

Distribution of tick species in mainland China

We compiled a database comprising 7344 unique records on geographic distributions of 124 known tick species, including 113 hard tick species in seven genera and 11 soft tick species in two genera, together with 103 tick-associated agents detected in either ticks or humans, which were recorded in 1134 counties (39% of all counties in the mainland of China) (Supplementary Fig. 1 and Supplementary Note 1). The most widely distributed tick genus was Dermacentor (in 574 counties), followed by Heamaphysalis (570), Ixodes (432), Rhipicephalus (431), Hyalomma (298), Argas (90), Ornithodoros (38), Amblyomma (37), and Anomalohimalaya (5) (Supplementary Data 1 and Supplementary Figs. 2‒10). At the species level, D. nuttalli, Ha. longicornis, D. silvarum, Hy. scupense, and R. sanguineus were each found in >200 counties, followed by R. microplus, I. persulcatus, I. sinensis, I. granulatus, and Hy. asiaticum that were each detected in 100‒200 counties (Supplementary Data 1). We identified 19 predominant ticks that were detected in more than 40 counties, including five Ixodes species, four Heamaphysalis, four Dermacentor, three Rhipicephalus, two Hyalomma, and one Argas tick species. Forest and meadowlands are the major vegetation types for these 19 tick species, accounting for a median of 46.4% (IQR: 40.0%‒68.9%) of their habitats (Supplementary Data 1).

The abundance of tick species varies substantially across the seven biogeographic zones which are defined by climatic and ecological characteristics (Fig. 1)18,19. Tick species are most abundant in Central China, South China, and Inner Mongolia–Xinjiang districts, hosting 61, 57, and 50 tick species, respectively (Supplementary Data 2). Eight prefectures reported ≥20 tick species, three in Xinjiang Autonomous Region of northwestern China, two in Yunnan Province of southwestern China, and one in each of Gansu, Hubei, and Fujian provinces of northwestern, central, and southeastern China, respectively (Fig. 1). Most genera except for Amblyomma were found in northwestern China, particularly in Xinjiang Autonomous Region. In contrast, less tick diversity was observed in northeastern China, which only harbors Ixodes, Heamaphysalis, and Dermacentor (Supplementary Figs. 2‒10).

Fig. 1: Tick species richness (circles) at the prefecture level in seven biogeographic zones in mainland China from 1950 to 2018.

I = Northeast district (NE), II = North China district (N), III = Inner Mongolia–Xinjiang district (IMX), IV = Qinghai–Tibet district (QT), V = Southwest district (SW), VI = Central China district (C), and VII = South China district (S). Source data are provided as a Source Data file.

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Risk mapping and risk factors for 19 predominant tick species

The ecological modeling results for the 19 predominant tick species showed highly accurate predictions, with the average testing area-under-curve (AUC) ranging from 0.83 to 0.97 (Table 1) and the testing partial AUC ratio ranging from 1.30 to 1.78 (Supplementary Tables 1‒5), indicating decent predictive power. The ecoclimatic and environmental variables that were predictive of the geographic distribution of the ticks differed among the species, even for those in the same genus (Fig. 2f, Supplementary Tables 1‒5). Temperature seasonality and mean temperature in the driest quarter were the two most important drivers, contributing ≥5% to the ensemble of models for 14- and 12- tick species, respectively, followed by elevation contributing ≥5% to the models for seven tick species (Fig. 2f, Supplementary Tables 1‒5). The same predictor, however, may drive the risk in different directions for different tick species (Supplementary Figs. 11‒29). For example, a high temperature in the driest quarter was associated with a high probability of presence for I. granulatus and R. haemaphysaloide but with a low probability for I. persulcatus and Ha. longicornis (Supplementary Figs. 11, 13, 16, 22).

Table 1 The average testing areas under the curve (AUC) of the BRT models at the county level and model-predicted numbers, areas and population sizes of affected counties for the 19 most prevalent tick species in China.

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Fig. 2: Clustering of tick species based on their ecological features and spatial distributions at the county level.

Panels ae indicate the spatial distribution of the five clusters (clusters I‒V). The boundaries of the seven biogeographic zones are shown as black solid lines. The dendrogram in panel f displays the clusters I‒V of tick species. The features used for clustering are three quantities associated with each predictor in the BRT models. Two of the three quantities were displayed in panel f to indicate the possible level of ecological suitability: relative contributions (colors in ascending order from yellow to red) and the standardized median value of the predictor (numbers in the heatmap) among counties with tick occurrence (numbers 1‒4 indicate the position of this median in reference to the quartiles of this predictor among all counties). Source data are provided as a Source Data file.

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The model-predicted high-risk areas of the 19 tick species were much more extensive than have been observed, 31‒520% greater in the number of affected counties, 14‒476% larger in the size of affected geographic area, and 25‒556% larger in the affected population size (Table 1, Supplementary Figs. 30‒34). Ha. longicornis was predicted to have the widest distribution that potentially affected 588 million people in 1140 counties, followed by I. sinensis and R. microplus that affected 363 and 350 million people in 630 and 678 counties, respectively (Table 1). High-risk areas of these three tick species collectively covered nearly all densely populated areas in China, mainly provinces in the central, eastern, southern, and southwestern China (Supplementary Figs. 30(b), 31(a), and 32(b)). R. sanguineus, and R. haemaphysaloides each affected more than 200 million people. D. nuttalli, I. crenulatus, Hy. asiaticum, Ar. persicus, and D. daghestanicus ticks were the top five tick species affecting the largest areas at the scale of 2.0‒3.8 million km2 (Table 1).

Ecological clustering of tick species

Based on the ecological similarity represented by the environmental and ecoclimatic predictors, the 19 tick species were grouped into five clusters with clear patterns of spatial aggregation (Fig. 2). D. nuttalli and D. silvarum constituted cluster I that covered the vast region in northern (including northeastern and northwestern) China. This cluster stretches over biogeographic zones I‒IV characterized by middle to high elevations, shrub grassland, strong seasonality in temperature, relatively low temperature in the wettest quarter (often also the warmest quarter), and low precipitation in the driest month (Fig. 2 and Supplementary Figs. 23, 24). Ha. longicornis, Hy. scupense, and R. sanguineus were grouped into Cluster II which was mainly found in biogeographic zones II, III, and VI, featuring the landscape of shrub grassland and irrigated or rainfed croplands at low-middle elevations (<1600 m) in central, eastern, and northwestern China (Fig. 2 and Supplementary Figs. 16, 20, 27). R. microplus, R. haemaphysaloides, I. granulatus and Ha. hystricis were grouped into Cluster III that was mainly distributed in biogeographic zones V‒VII covered by coniferous or broad-leaved woods at low elevations in southern and central China where the weather is warm and humid with low seasonality in temperature (Fig. 2 and Supplementary Figs. 13, 19, 21, 22). Cluster IV, composed of I. persulcatus, Ha. concinna and Ha. japonica, ecologically fits biogeographic zones I and III in northwestern and northeastern China covered by coniferous or broad-leaved forests as well as cropland, featuring strong seasonality in temperature and low temperatures in the driest season (Fig. 2 and Supplementary Figs. 11, 17, 18). Cluster V comprises of Hy. asiaticum, D. marginatus, D. daghestanicus and Ar. persicus, the natural habitats of which are meadow, desert grassland and cropland in biogeographic zone III as well as part of zone IV in northern and northwestern China, featuring low precipitations in the wettest/warmest quarter or month (Fig. 2 and Supplementary Figs. 25, 26, 28). Three tick species, I. ovatus, I. sinensis and I. crenulatus, have their own unique ecological niches and are thus not clustered with others. In terms of geographic distribution, however, I. crenulatus is similar to Cluster V, and I. ovatus and I. sinensis are similar to Cluster III (Fig. 2 and Supplementary Fig. 2).

Distribution of tick-borne agents

Among the 103 tick-borne agents detected in China, 65 were newly identified in the past two decades (Fig. 3). Ha. longicornis is the tick species harboring the highest variety of tick-borne agents, as many as 44 known species including seven Rickettsia species, seven Babesia, 12 Anaplasmataceae, four Theileria, four Borrelia, nine viruses, and Francisella tularensis (F. tularensis) (Fig. 3). Other competent tick species that carry 20 or more agents are I. persulcatus (36 agents), D. nutalli (32 agents), R. microplus (31), D. silvarum (30), Ha. concinna (24), and Hy. asiaticum (23). Agents that parasitize more than ten tick species are R. raoultii (in 15 tick species), R. heilongjiangensis (14), Anaplasma (A.) phagocytophilum (22), Ehrlichia (E.) chaffeensis (16), A. bovis (ten), B. burgdorferi sensu stricto (20), B. garinii (18), B. afzelii (11), Coxiella (C.) burnetii (14), Jingmen tick virus (12), and Theileria (T.) annulata (11) (Fig. 3).

Fig. 3: The tick species and their corresponding tick-borne agents in China from 1950 to 2018.

The tick-borne agents marked in blue indicate the newly identified agents in the past two decades. Source data are provided as a Source Data file.

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By the end of 2018, totally 2786, 415, 215, and 129 human cases had been confirmed for infections with Borrelia (five species and uncharacterized species), Anaplasmataceae (four species), Babesia spp. (five species and uncharacterized species), and spotted fever group rickettsiae (six specific species and uncharacterized species), respectively. Additional 216 human cases were infected with other bacteria (three species) including 120 with Francisella tularesis, 95 with Coxiella burnetii, and one with Colpodella spp. (Fig. 4). In the spotted fever group rickettsiae, R. heilongjiangensis and R. raoultii were the most widely distributed, covering the west, north, and northeast of China (Fig. 4a; Supplementary Fig. 35; Supplementary Note 2). R. heilongjiangensis was also found sporadically in southern China. From 1996 to 2007, human cases infected with R. heilongjiangensis were reported in Heilongjiang (1‒10) and Jilin provinces (11‒12) in the northeast and Hainan Province (11‒16) in the south. A few human cases of R. raoultii (1‒10) were reported in Xinjiang (1‒5), Inner Mongolia (6), and Heilongjiang (1‒5) provinces in northern China. Henan Province reported five R. sibirica spp XY-99 cases, and Anhui reported one R. sibirica spp BJ-90 patient. Human cases with uncharacterized Rickettsia species were mostly reported in Heilongjiang and Hainan provinces.

Fig. 4: The distributions of human cases by species of tick-borne agents in China during 1950–2018.

Human cases are positioned at the center of either province (triangles) or prefectures/counties (circles) depending on data availability. a spotted fever group rickettsiae; b Anaplasmataceae; c Borrelia; d Babesia spp.; e bacteria; f viruses. Human cases of SFTSV and TBEV are not shown as they are described in other figures. Another five tick-borne viruses, including Huangpi tick virus, Lihan tick virus, Wenzhou tick virus, Wuhan tick virus, and Yongjia tick virus, were not displayed in the map due to lack of location information. Source data are provided as a Source Data file.

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As the most commonly recorded agent in the Anaplasmataceae, A. phagocytophilum was scattered over the whole nation except for the southwest (Fig. 4b; Supplementary Fig. 36; Supplementary Note 2). Most human cases were reported in central and central-east China, primarily in Hubei and Shandong provinces. Cases were also seen in the northeast and the southeast. E. chaffeensis had a comparably wide geographic scope, except that it was also detected in the southwest (Yunnan Province), and sporadic human cases were reported in Inner Mongolia, Beijing, Tianjin, Shandong, and Guangdong provinces. A. capra was the third most commonly detected agent in humans in the family with a total of about 29 reported case in the northeast, although it was also found in ticks in the central and the west. Another widely distributed agent was E. canis, found in the east, the south, and the northwest.

As to Borrelia burgdorferi sensu lato complexes in the genus Borrelia, which are the etiological agent of Lyme disease, ticks carrying B. garinii, B. afzelii, and B. burgdorferi sensu stricto shared similar distributions across northwestern, northern, northeastern, and southern China, although B. garinii was more widely detected in ticks (Fig. 4c; Supplementary Fig. 37; Supplementary Note 2). B. garinii, B. afzelii, and B. burgdorferi sensu stricto are the major causative agents for human Lyme disease20. The Changbai Mountain area on the border of Heilongjiang and Jilin provinces in northeastern China was a hotspot of human cases where all the four major agents, as well as B. valaisiana were found. In addition, cases infected with B. garinii were reported in Xinjiang, Inner Mongolia, and Hainan provinces, B. afzelii cases were seen in Xinjiang, Chongqing and Shandong provinces, and B. burgdorferi sensu stricto infected cases in Shandong and Guangdong. Most Lyme disease pathogens detected in humans were however uncharacterized. B. miyamotoi is the causative agent for human relapsing fever, and patients were seen in Heilongjiang and Jilin provinces, northeastern China21.

The distributions of Babesia spp. species were mostly focal, but Ba. microti was found in the north, the northeast, the east, the southeast, and the southwest of the country (Fig. 4d; Supplementary Fig. 38; Supplementary Note 2). Human infections with Ba. microti occurred in the east near Shanghai and in Yunnan Province of the southwest. Ba. divergens was found in human cases in Xinjiang, Gansu, and Shandong provinces, extending from the northwest to the central and to the east of the country, but was detected in ticks only in the northeast. Ticks harboring Ba. venatorum were only found in the northeast, but human infections were reported in both the northeast and the northwest. Ba. crassa-like agents parasitized ticks and infected humans in the northeast, mainly in Heilongjiang Province. A human infection with Ba. spp. XXB/Hangzhou was recorded in Zhejiang Province, but detection of this agent in ticks has not been reported yet. Human infections with uncharacterized Babesia spp. were mostly reported in Inner Mongolia in the north, Zhejiang Province in the east, and Yunnan Province in the southwest.

T. annulata was the most widely distributed agent in the Theileria genus, followed by T. sergenti and T. luwenshuni. All three agents were reported in the western, northern, northeastern, and central parts of China, with T. annulata also detected in the south (Supplementary Fig. 39; Supplementary Note 2). Other Theileria agents, including T. sinensis, T. ovis, T. equi, and T. uilenbergi, were only found in Xinjiang in the northwest or Gansu in the central west. Thus far, Theileria agents have not been associated with human infection in China.

Of the seven known tick-borne bacteria in China, C. bumetii, the causative agent for Q fever, was the most widely distributed, found in either ticks or humans across the country except for the central and southern provinces (Fig. 4e; Supplementary Fig. 40; Supplementary Note 2). The distribution of F. tularensis was comparable to that of C. bumetii, except that it was not detected in Xinjiang and Yunnan provinces. Tibet had a relatively high disease burden for both pathogens, about 46 C. bumetii cases and 31 F. tularensis cases. Most of the remaining patients were reported in Shandong Province for F. tularensis and in Yunnan Province for C. bumetii. Bartonella spp. and Alcaligenes faecalis were found in ticks in northeastern China, particularly around the Daxing’an Mountains. Colpodella spp.-carrying ticks were only found in the northern part of Qinghai–Tibet Plateau, but a human case was reported in Heilongjiang Province in 201322. Brucella melitensis and Brucella abortus were found in D. marginatus ticks in northwestern Xinjiang. Brucellosis is a common zoonotic disease in China, predominantly caused by Brucella melitensis23. However, as the transmission of brucellosis by ticks is rare, we do not show human cases on the map.

Altogether 19 tick-borne viruses have been identified in China, six of which were associated with human patients (Fig. 4f and Fig. 5; Supplementary Fig. 41; Supplementary Note 2). Among them, SFTSV and TBE virus (TBEV) were responsible for the enormous disease burden unparalleled by any other tick-borne pathogens (Fig. 5). Hundreds of human cases infected by Crimean–Congo hemorrhagic fever virus (CCHFV) were reported in Xinjiang, with a few reported in Yunnan Province (Fig. 4f). Jingmen tick virus was first found in 2010 and was distributed in central, eastern, and northeastern China (Supplementary Fig. 41), with 12 human cases reported in Heilongjiang Province (Fig. 4f). Another recently discovered agent, Alongshan virus (ALSV), was detected in ticks in the northern tips of Inner Mongolia and Heilongjiang, as well as in human cases across the two provinces.

Fig. 5: The reported and model-predicted distributions of SFTSV and TBEV at the county level in China.

a Reported annual incidence rate of human SFTS and locations of SFTSV detected from ticks. b Spatial distribution of model-predicted probabilities of SFTSV presence. c Reported annual incidence rate of human TBE and locations of TBEV detected from ticks. d Spatial distribution of model-predicted probabilities of TBEV presence. Source data are provided as a Source Data file.

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Risk mapping and risk factors for pathogens associated with major TBDs

The majority of human SFTS cases during 2010‒2018 were diagnosed in Liaoning Province in the northeast, Shandong, Jiangsu, and Zhejiang provinces on the east coast, and Henan, Hubei and Anhui provinces in central China (Fig. 5a). The etiological virus, SFTSV, was detected primarily in Ha. longicornis, but also in D. nuttalli in northern Xinjiang. The model-predicted risk areas resembled the current reporting regions (Fig. 5b). Approximately 251.5 million people reside in high-risk areas where the model-predicted probability of SFTSV presence exceeds 50%. Temperature seasonality, mean temperatures during the wettest quarter, elevation, annual temperature range, closed woodland, mean temperatures during the driest quarter24 were the leading risk determinants for the presence of SFTSV with RC >7% (Table 2). SFTSV ecologically prefers regions at low to moderate elevations (<1000 m) and with strong seasonality and wide annual variation range in temperature, a low mean temperature in the winter (driest quarter), and a high mean temperature and precipitation in the summer (wettest quarter or month) (Supplementary Fig. 42).

Table 2 BRT-model-estimated mean (standard deviation) relative contributions of major ecoclimatic and environmental factors (RC ≥ 4%) to the spatial distributions of SFTSV and TBEV.

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Human cases of TBEV primarily clustered in northeastern China, coinciding with the model predicted high-risk areas (Fig. 5c). The northwestern region where the virus was found only in ticks was classified as having mild to moderate risks (Fig. 5d). In total, about 94.5 million residents live in the high-risk areas. Temperature seasonality was by far the most influential predictor with RC = 54.0% (Table 2), which was also a leading predictor for the presence of I. persulcatus, a major carrier of TBEV (Supplementary Table 1). Additional important contributors included mean temperature in the driest quarter, elevation, and closed woodland (RC > 7%). High risks of TBEV were flagged by low to medium elevations (<1000 m), strong seasonality in both temperature and precipitation, and low temperature in both winter (driest quarter) and summer (warmest month) (Supplementary Fig. 43).


Source: Ecology - nature.com

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