Dataset History

Cumming African Dataset | HTTK Program
 

Cumming African Dataset

Individual tick distribution records were assembled from published sources (Fig. 3); the total number of records was around 34000. Full details of the sources consulted are given by Cumming (1999a). The data were collected over the period 1900–1997, and most collections occurred between 1950 and 1985. It was assembled from a wide range of published sources and contains the kinds of bias that might be expected in this kind of data; ticks are sampled unevenly in different countries, cattle have been disproportionately sampled relative to wild hosts, and some identifications are unreliable (Cumming, 1998, 2002). The collection records were at varying degrees of accuracy; many were entered from maps using a Calcomp Drawingboard III digitizer, and others from place names or coordinates given by the collector(s). Coordinates for collection localities were obtained from the on-line National Imagery and Mapping Agency database (NIMA 1999) where necessary. All analyses were done at a resolution of 0.25 3 0.25 degrees to allow some leeway for error.

TickMap Methods: Data (Main_tick_database(.txt).ZIP 535KB) sent to me by Graeme Cumming on 15 May 2010. DIVA-GIS check coordinates to identify points outside country and falling in water. Most falling in water points were close to coast. Many country discrepancies due to Zaire or other name difference – these were corrected. Records were annotated as problematic using the join function of ArcGIS 3.3 Outside country points were separated (n = 748), Low reliability points (i.e. rated 3) were separated (n = 463). This left 32778 records for further cleaning – these are the data that I talk about from now on. Uncertainty was assumed to be 7km for reliability score 1 and 20km for reliability score 2 (Score 3 points were put aside for future consideration). Records were sometimes compilations of collections by different people over a time period, and for ticks collected on different hosts. All records listed a host, and up to 21 hosts were identified for a single record. However, for TickMap these are considered separate collections, so records were separated when multiple hosts were listed. This process was aided by an Excel formula for extracting vectors from a matrix to (see http://www.cpearson.com/excel/MatrixToVector.aspx). 36745 records resulted from this process. Host data were cleaned to standardize terminology (e.g. No data for Not individually recorded, not recorded etc), and remove leading spaces. Realised that collecting method conflates the habitat, host and collecting method. So introduced a field called habitat. For example, a record that says from vegetation is habitat=vegetation, host=no data, collecting method=no data. Assumed that collections from a named animal resting/nesting/burrow site meant that the animal was the host, habitat=resting site, collecting method=no data. Abattoir is host=no data, collecting method=no data, habitat=abbatoir, but cows in abbatoir is host=cows, collecting method=Attached or crawling on animal, habitat=abbatoir. In a house is host=human, collecting method=Other[free-living], habitat=in a house. In building is host=no data, collecting method=Other[free-living], habitat=in a building. Likely host was recorded, e.g. not recorded (almost certainly elephant) was recorded as elephant but verbatim recorded in remarks. If two hosts and/or then assume tick on both. If “and not recorded” then did not treat this as separate record. Fowls were assumed to be chickens and “fowls or fowl runs” was treated conservatively as host=chicken, collecting method= Other[free-living], habitat=in a coop. Checked host species names against Mammal’s Planet (http://www.planet-mammiferes.org/drupal/en/node/20) and Mammal species of the world (http://www.bucknell.edu/msw3/). Tick names that did not agree with Guggliammi were referred to Rich Robbins, who assigned synonymys and gave other details, which often appear in Remarks.

Vector format image files for tick species was sent to D. Foley in June 2011. These were converted to raster format and georeferenced according to the following method: Open PowerPoint. Create slide 56 x 56 inches. Insert .wmf image. Resize to 1000%. If save as .jpg from Powerpoint it results in a small file. Therefore, copy and paste into MS Paint program, then save as .jpg. this should result in a file of at least 1MB. Maps were roughly georeferenced in DIVA-GIS (Tools>Georeference Image), which produces a .jpgw file with the coordinates and resolution information. Used the align tool in ArcGIS 3.3 and saved as .tiff, which produces a .tfw file. Used the information in the latter file to update the .jpgw file. Alternatively, aligning was done in ArcMap10, and the details visible when you right click the image layer then Data>Export Data, gives you the information that you can use to update the georeferencing information in DIVA-GIS. By Desmond Foley June 2011.

Some related references:

Cumming, G. S. 1998. Host preference in African ticks (Acari: Ixodida): a quantitative data set. Bulletin of Entomological Research 88:379–406.
Cumming, G. S. 1999a. Host distributions do not limit the species ranges of most African ticks (Acari: Ixodida). Bulletin of Entomological Research 89:303–327.
Cumming, G. S. 1999b. The evolutionary ecology of African ticks. Dissertation. University of Oxford, Oxford, UK.

 

Human Tick Test Kit Program

 

The Tick-Borne Disease Laboratory of the Entomological Sciences Program of the U.S. Army Center for Health Promotion and Preventive Medicine (USACHPPM), Aberdeen Proving Ground, MD, provides a tick identification and testing service (the Department of Defense [DOD] Human Tick Test Kit Program) for ticks removed in the continental U.S. (CONUS) from military personnel, military dependents and DOD civilian employees. The service was initiated in 1989 in response to the threat of Lyme disease, and then offered only immunofluorescent antibody (IFA) testing of ticks for Borrelia burgdorferi, the etiological agent of Lyme disease. The method of pathogen analysis was changed to polymerase chain reaction (PCR) in 1997, and the list of target pathogens has expanded to include Anaplasma phagocytophilum, the agent of human granulocytic anaplasmosis, Babesia microti, an agent of human babesiosis, Borrelia lonestari, the agent of southern tick-associated rash illness (STARI), Ehrlichia chaffeensis, the etiological agent of human monocytic ehrlichiosis (HME), Ehrlichia ewingii, spotted fever group (SFG) rickettsiae, specifically, Rickettsia rickettsii, the agent of Rocky Mountain spotted fever and Rickettsia parkeri. Most of the ticks received are Amblyomma americanum, Dermacentor varibilis and Ixodes scapularis from installations in the mid-Atlantic, south, northeast and upper midwest regions, but infrequently Rhipicephalus sanguineus, Amblyomma maculatum, Ixodes pacificus, Dermacentor andersoni, Dermacentor albopictus, Ixodes cookei are also submitted. The methods of tick identification and PCR used have been described previously in Stromdahl et al. (2001), Stromdahl et al. (2003) and Stromdahl et al. (2011).

Data was provided to VectorMap by Ellen Stromdahl (Army Institute of Public Health, U.S. Army Public Health Command, Aberdeen Proving Ground, MD, USA) as an MS Access file in June 2011. A spreadsheet file (MS Excel) was generated by an Access query by Mr Tom Hollowell of the Smithsonian’s NMNH. Records were georeferenced by a variety of methods, by Desmond Foley and David Pecor of the WRBU, who were also responsible for quality control of taxonomy information and standardization of data according to the TickMap schema.

In the absence of maps detailing individual sites we opted to summarize their location by defining the centroid of the DoD facility and estimating uncertaintly using published information about the area of the base. Biogeomancer, Google Earth, and 2010 Census TIGER/Line Shapefiles: Military Installations (U.S Census Bureau, 2011) were the primary sources of information for georeferencing data. Google searches were useful to identify location spelling errors (of which there were many) and incorrect associations of county and city information. For the 2010 census data, area of land was used to calculate the radius in meters of a circle of equivalent area, as a measure of the uncertainty in meters. When area was given in acres, uncertainty in meters was calculated using the formula =SQRT((D2*4046.85642)/3.1416). Records were originally replicated for different pathogens tested, so these were compiled into single records with a list of pathogens tested and the results of testing in the respective pathogen data fields.

Of 43623 records, 25878 had ‘on post’ where tick was acquired, and 4475 records had no information about locality or just had State. Of those records with location of tick bite information available, 102 were set aside that had no tick, the specimen was not a tick, or had no identification, and 99 could not reliably be georeferenced. A total of 17,238 records from the U.S. Army Institute of Public Health's "Human Tick Test Kit Program", 1995-2010 were loaded into TickMap on 30 Apr 2012.

References

Stromdahl, E. Y., S. R. Evans, J. J. O'Brien, and A. G. Gutierrez, 2001: Prevalence of infection in ticks submitted to the human tick test kit program of the U.S. Army Center for Health Promotion and Preventive Medicine. J. Med. Entomol. 38, 67- 74.

Stromdahl, E. Y., P. C. Williamson, T. M. Kollars, Jr, S. R. Evans, R. K. Barry, M. A. Vince, and N. A. Dobbs, 2003: Evidence of Borrelia lonestari DNA in Amblyomma americanum (Acari: Ixodidae) removed from humans. J. Clin. Microbiol. 41, 5557-5562.

Stromdahl, E. Y., J. Jiang, M. Vince, and A. L. Richards, 2011: Infrequency of Rickettsia rickettsii in Dermacentor variabilis removed from humans, with comments on the role of other human-biting ticks associated with spotted fever group Rickettsiae in the United States. Vector Borne Zoonotic Dis. 11, 969-977.

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