Limitations

Limitations to this study include the potential for gaps in coverage in certain geographic regions, reflecting limiting our searches to English-language publications. These gaps may be particularly evident in countries with long histories of vector-borne disease management, such as China and Russia, that have extensive bodies of research not readily accessible due to language barriers in the literature (Ruzek et al. 2019, Zhang et al. 2019). While we included many types of mapping approaches and attempted to describe the range of those approaches, those that we perceived as not quantitative were excluded, as was gray literature such as reports and conference abstracts.

Table 2.

Bacteria and protozoan parasites included in the study

Table 3.

Eight types of study methodologies defined in this review

Results

Our initial database searches returned 12,482 records, which yielded 8,608 unique publications. An overview of the literature screening process, following PRISMA guidelines, is shown in Fig. 1. The final screened dataset comprised 303 studies on tick-borne pathogens with a mapped spatial component published between 1995 and 2020. The full database of screened literature is accessible via github.com/viralemergence/tickmaps. Four out of twenty-seven pathogens of interest did not have any associated mapping studies that met our screening criteria: Omsk hemorrhagic fever virus, sawgrass virus, Colorado tick fever virus, and Rickettsia africae (Rickettsiales: Rickettsiaceae). Only nine pathogens had more than ten associated mapping studies: ASF virus, CCHF virus, tick-borne encephalitis virus (TBEV), Borrelia burgdorferi (Johnson et al.; Spirocheatales: Spirochaetaceae), Anaplasma phagocytophilum (Dumler et al.; Foggie; Rickettsiales: Anaplasmataceae), Coxiella burnetii ((Derrick); Philip; Legionellales: Coxiellaceae), Ehrlichia chaffeensis (Anderson, Dawson and Wilson; Rickettsiales: Anaplasmataceae), Francisella tularensis (Dorofe'ev; McCoy and Chapin; Thiotrichales: Francisellaceae), and Rickettsia rickettsii (Brumpt; Rickettsiales: Rickettsiaceae). While the majority of studies focused on Lyme disease (40.26%) or tick-borne encephalitis (15.51%), the overall number of published work with a mapping component has increased dramatically across taxa in the past decade (Fig. 2). Tick vectors from seven genera were represented in the final dataset: Amblyomma, Dermacentor, Haemaphysalis, Hyalomma, Ixodes, Ornithodoros, and Rhipicephalus (Fig. 2). Studies with data from Ixodes were the most prevalent, featured in 65.42% of studies including information on the vector. These typically focused on three species of medical concern: Ixodes scapularis (Say, Ixodida: Ixodidae), Ixodes ricinus (L., Ixodida: Ixodida), Ixodes pacificus (Cooley & Kohls, Ixodida: Ixodidae).

Fig. 1.

PRISMA flow diagram outlining the literature search and screening process.

Fig. 2.

The cumulative number of studies that collected data about a given genus of tick vector (A) or tick-borne disease (B).

The eight mapping approaches (Table 3) used to classify studies were all represented in the final dataset of screened papers (Fig. 3). Mapping raw occurrence points of pathogens and vectors were the most frequently used approach in communicating spatial information and was used in nearly half (47.85%) of screened studies. Risk mapping (31.02%) and endemicity mapping (29.70%) were also commonly used to communicate the spatial distribution of tick-borne pathogens or the risk of exposure to ticks. Ecological niche modeling was used to estimate distributions, typically for tick vectors, in 22.11% of studies, and the majority (76.11%) of these studies produced niche models with the maximum entropy (MaxEnt) method (Phillips et al. 2006). Cluster analysis was used in 18.48% of studies, where tests for spatial autocorrelation (n = 15) and spatial scanning statistics implemented in SaTScan (n = 31) were frequently used for cluster detection. Prevalence modeling (8.58%) and genetic mapping (4.62%) were the methods least used in the final dataset of screened literature.

Fig. 3.

The cumulative number of studies using any of eight given methodologies.

Fig. 4.

The proportion of studies using different data sources to generate maps of tick-borne disease distribution, transmission, or risk. Many studies use (A) pathogen data directly (75%) and (B) human case data (40%), while fewer use (C) livestock infection data (12%) or (D) wildlife infection data (10%).

Data sources used to generate maps varied between studies, where 74.92% used pathogen records as inputs, and a quarter (25.08%) used tick vectors as proxies for the pathogens they transmit (Fig. 4). Previously published datasets were used in 20.79% of studies, where resources including museum records, online databases, and literature reviews were commonly leveraged as data sources for spatial analyses. Human cases were used as data inputs in 39.60% of mapping efforts, and data from other vertebrate hosts such as domesticated livestock (11.88%) and wildlife (9.57%) were less common (Fig. 4). The relative proportions of domesticated and wildlife hosts sampled for pathogens across studies are presented in Fig. 5. Livestock sampled for pathogens in the literature largely consisted of hoofstock (i.e., cattle, sheep, and pigs) and domestic dogs; rodents, ungulates, and suids were the groups most frequently sampled for pathogens in wildlife serology studies.

Fig. 5.

Proportion of studies with data on different wildlife (A) and livestock species (B).

Fig. 6.

Number of studies describing the geography of tick-borne disease by country, excluding a handful of explicitly continental studies (most notably 20 in Europe, as well as four in Africa, two in the eastern Mediterranean, one in Asia, and four global mapping studies).

The geographic foci and extent of studies included in the final dataset varied considerably, ranging from highly localized areas to mapped outputs with global extent. We found four global mapping studies on tick-borne pathogens, and a number of explicitly continental studies focused on Europe (n = 20), Africa (n = 4), the eastern Mediterranean (n = 2), and Asia (n = 1). Regionally, North American locations were heavily represented in the literature, where 35.31% of studies were conducted in the United States, 11.55% in Canada, and 2.64% in Mexico (Fig. 6). While global mapping efforts are comparably low compared to North America, there are conspicuous regional gaps in mapped tick-borne disease studies, notably in portions of South America, Africa, the Middle East, Central Asia, and Southeast Asia.

Why Tick-Borne Diseases Are Difficult to Map

Maps are commonly used to provide a tangible (and graphical) perspective on the “where” of disease risk and can be used as part of the surveillance, prevention, and intervention toolbox in public health. Maps of vector-borne diseases carry an additional layer of complexity, as transmission risk is a combination of the abundance and behavior of vectors, the presence of the disease, and the opportunity for human infection. The data streams to describe vector and pathogen distributions often arise from data collection in historically disparate fields (i.e., entomology and infectious disease epidemiology, respectively). In some instances, key vectors for zoonoses also remain unknown, as is the case for Crimean-Congo hemorrhagic fever virus (Okely et al. 2020), which may have different principal tick vectors by region. Resolving these data barriers and knowledge gaps is one step towards better geospatial studies.

Tick-borne diseases also pose a unique problem, given that nearly all tick-borne viruses are zoonotic, which necessitates a view of their emergence and risk landscapes based on sylvatic and enzootic cycles. For comparison, these transmission cycles are very well researched for some mosquito-borne diseases, such as yellow fever, and knowledge of pathogen-vector-host relationships can be used to improve risk mapping efforts (Jentes et al. 2011). While we have a firm understanding of sylvatic cycles for some tickborne diseases, namely Lyme disease, that operationalized view of transmission does not exist for most tick-borne pathogens, and vertebrate hosts were only considered in a fraction of studies in our literature database. There are many instances where the full components of tick-borne enzootic transmission cycles are either poorly understood or completely unknown (Kemenesi and Bányai 2018, Orkun and Emir 2020). This presents a challenge in accurately mapping distributions of tick-borne diseases, particularly when tick vectors are widespread relative to the pathogens they transmit (Lippi et al. 2020). In these instances, geographic transmission risk and the potential for spillover events would perhaps be better estimated with data on wildlife reservoirs and enzootic transmission patterns. This is a challenging endeavor, however, as establishing enzootic cycles for tick-borne pathogens typically requires extensive data collection in the field and laboratory, often calling for specialized expertise in wildlife sampling that is not typically incorporated into traditional public health surveillance systems (Hamer et al. 2012). Data gaps are again characterized by disciplinary divides, as wildlife disease surveillance usually occurs separately from acarological collections, within-vector pathogen surveillance collection, and human public health records collections. Gaps in our knowledge regarding transmission cycles, therefore, present a major obstacle to quantifying and mapping the risk of exposure.

How Tick-Borne Diseases Are Mapped

Although we recorded a tremendous diversity of approaches, we found that simple occurrence maps (i.e., displaying raw data points for either pathogens or their vectors) were the most common form of spatial data visualization. Dot maps of disease cases have long been used in epidemiology to communicate basic spatial information, and they remain a frequently used mapping approach that may complement more advanced quantitative methods (Smith et al. 2015). We also found that approximately one-quarter of the studies in this review relied on tick presence as a proxy for pathogen presence and transmission risk. This is an intuitive way to formalize knowledge about the geographic range of risk when pathogen distributions are poorly sampled or unknown. However, maps derived solely from vector data underscore a clear need to refine perceptions of geographic risk through sampling efforts that focus on pathogens.

Mapping studies that employed more analytical approaches for spatial statistics or modeling (such as interpolated risk mapping, ecological niche models, and cluster analysis) have become more common especially in the past five years, likely due to advances in the diversity of modeling algorithms, availability of open-source software, and increasing adoption of these methods in disease ecology. Perhaps most of all, we observed that these approaches relied on the existence of an ecosystem of open, accessible raw data describing the occurrence of ticks, pathogens, and clinical and veterinary cases. This secondary use of data was perhaps most evident in ecological niche modeling studies, where species presence data are commonly used as input for modeling algorithms (Elith and Leathwick 2009). This practice, while pragmatic, comes with the caveat that much work on establishing the spatial risk of tick-borne diseases is hinged on a relatively small pool of existing data. This problem is exacerbated when diseases are rare events under current surveillance practices, or when tick vectors are challenging to sample, such as soft ticks in the genus Ornithodoros (Donaldson et al. 2016). We, therefore, recommend an emphasis on novel data collections, when possible, in future research.

Finally, we noted that despite substantial interest in the expansion of tick-borne diseases over time, there was fairly limited work that conclusively established this pattern. We encountered hundreds of examples of something akin to risk maps for tick-borne diseases, but most are so different in input and mapping technique as to be incomparable across studies, a lack of intercomparability that can stymie attempts to describe change over time. This can be addressed by direct work using a combination of modeling and endemicity mapping to update historical or baseline distributions, and project future areas of vulnerability; like other work, we note that this kind of work is heavily reliant on detailed, real-time primary data.

Which Tick-Borne Diseases Are Mapped

A small number of tick-borne diseases have been exceptionally well-studied and well-mapped. We found a preponderance of studies with information about Lyme disease and its vectors. Lyme disease has become the most frequently reported vector-borne disease in the United States, Canada, and Europe, a trend which underlies the geographic distribution of the research identified in this study (Lindgren and Jaenson 2006, Shapiro 2014, Lindsay 2016). The prevalence of Lyme disease mapping studies in the literature is unsurprising, as Lyme disease has been previously identified as a major research target, both in disease ecology and public health efforts (Han and Ostfeld 2019, Mac et al. 2019). Similarly, TBEV is also prioritized, likely due to its relative prevalence in humans, long history of its presence as a livestock-related issue, and the intensity of research on this particular disease in Russia (National Academies of Sciences, Engineering, and Medicine et al. 2016, Ruzek et al. 2019, Bojkiewicz et al. 2020). The wealth of existing data for Lyme disease and TBEV, combined with ongoing surveillance efforts, translate into transmission systems that are extensively mapped across spatial and temporal scales, compared to other tick-borne diseases.

With these few exceptions, the majority of tick-borne pathogens are undermapped. Expanded pathogen diversity in mapping studies is mostly relegated to the past decade, a period which coincides with gains in the knowledge of tick-borne pathogen taxonomy, increased awareness of burden, and heightened public health interest (Vayssier-Taussat et al. 2013, Eisen and Eisen 2018, Pollet et al. 2020). Nevertheless, pathogens better represented in mapping studies are typically those that share common vectors with extensively studied pathogens. For example, pathogens that are also transmitted by I. scapularis and I. ricinus (the primary vectors of Lyme borreliosis and TBEV, respectively) tended to be better described in our data, often as part of integrative surveillance focused on these specific vectors instead of anyone pathogen. Pathogens capable of transmission through agricultural production systems were also the focus of many mapping studies, even when the human burden of zoonotic transmission is comparatively low, as is the case with African swine fever and Q fever. In these instances, the bulk of mapped studies stem from the existence of established surveillance in livestock, management of wildlife populations, or testing of agricultural products (e.g., bulk tank milk testing) (Hilbert et al. 2015, Food and Agriculture Organization of the United Nations 2019).

In this review, we find several pathogens of increasing public health importance that would make good candidates for targeted surveillance efforts, where areas of transmission risk are largely derived from vector distributions. For example, four pathogens—Omsk hemorrhagic fever virus, sawgrass virus, Colorado tick fever virus, and Rickettsia africae—were entirely absent from the results of our literature searches, and represent important future priorities. Similarly, proportionally understudied pathogens transmitted by I. scapularis—including A. phagocytophilum, E. chaffeensis, and Powassan virus—could be more regularly involved in vector surveillance efforts. In a similar vein, the geographic distribution of reviewed literature indicates several regional disparities in mapped tick-borne disease research, highlighting potential opportunities for increased research efforts. South America, for example, is represented in the tick mapping literature by only two studies conducted in Brazil, despite having confirmed cases of tick-borne diseases and known tick species of medical importance (Guglielmone et al. 2006). Documentation of zoonotic pathogens on the continent is similarly underfunded, and tick-borne transmission cycles are an active area of research (Guglielmone et al. 2006, Rodriguez-Morales et al. 2018). Identifying regional priorities for surveillance based on clinical and veterinary significance, and expanding the purview of tick-borne disease mapping using participatory approaches alongside quantitative and GIS work, will help manage the burden of tick-borne disease where it remains the highest.