Research article Open Access
Like 0


Geographical mapping of infectious diseases is an important tool for detecting and characterising outbreaks. Two common mapping methods, dot maps and incidence maps, have important shortcomings. The former does not represent population density and can compromise case privacy, and the latter relies on pre-defined administrative boundaries. We propose a method that overcomes these limitations: dot map cartograms. These create a point pattern of cases while reshaping spatial units, such that spatial area becomes proportional to population size. We compared these dot map cartograms with standard dot maps and incidence maps on four criteria, using two example datasets. Dot map cartograms were able to illustrate both incidence and absolute numbers of cases (criterion 1): they revealed potential source locations (Q fever, the Netherlands) and clusters with high incidence (pertussis, Germany). Unlike incidence maps, they were insensitive to choices regarding spatial scale (criterion 2). Dot map cartograms ensured the privacy of cases (criterion 3) by spatial distortion; however, this occurred at the expense of recognition of locations (criterion 4). We demonstrate that dot map cartograms are a valuable method for detection and visualisation of infectious disease outbreaks, which facilitates informed and appropriate actions by public health professionals, to investigate and control outbreaks.


Article metrics loading...

Loading full text...

Full text loading...



  1. Smith CM, Le Comber SC, Fry H, Bull M, Leach S, Hayward AC. Spatial methods for infectious disease outbreak investigations: systematic literature review. Euro Surveill. 2015;20(39):30026.
  2. Heywood I, Cornelius S, Carver S. An introduction to geographical information systems. New Jersey: Prentice-Hall; 2011. ISBN: 9780273722595.
  3. Openshaw S. Ecological fallacies and the analysis of areal census data. Environ Plann A. 1984;16(1):17-31.  https://doi.org/10.1068/a160017  PMID: 12265900 
  4. Gastner MT, Newman ME. From The Cover: Diffusion-based method for producing density-equalizing maps. Proc Natl Acad Sci USA. 2004;101(20):7499-504.  https://doi.org/10.1073/pnas.0400280101  PMID: 15136719 
  5. Wijk- en buurtkaart 2008. [District and neighborhood maps 2008]. Den Haag: Statistics Netherlands. [Accessed: 20 Jan 2016]. Dutch. Available from: http://www.cbs.nl/nl-NL/menu/themas/dossiers/nederland-regionaal/publicaties/geografische-data/archief/2009/2010-wijk-en-buurtkaart-2008.htm
  6. [email protected] 2.0. Berlin: Robert Koch Institute. [Accessed: 3 Feb 2016]. Available from: https://survstat.rki.de/
  7. Open Data - Freie Daten und Dienste des BKG. [Open data – free data and services of the BKG]. Leipzig: Federal Agency for Cartography and Geodesy (BKG). [Accessed: 15 Nov 2015]. German. Available from: http://www.geodatenzentrum.de/geodaten/gdz_rahmen.gdz_div?gdz_spr=deu&gdz_akt_zeile=5&gdz_anz_zeile=0&gdz_user_id=0
  8. Brewer CA, Pickle L. Evaluation of methods for classifying epidemiological data on choropleth maps in series. Ann Assoc Am Geogr. 2002;92(4):662-81.  https://doi.org/10.1111/1467-8306.00310 
  9. Harrower M, Brewer CA. ColorBrewer.org: An online tool for selecting colour schemes for maps. Cartogr J. 2003;40(1):27-37.  https://doi.org/10.1179/000870403235002042 
  10. Alam MJ, Kobourov SG, Veeramoni S. Quantitative Measures for Cartogram Generation Techniques. Comput Graph Forum. 2015;34(3):351-60.  https://doi.org/10.1111/cgf.12647 
  11. Andrieu D, Kaiser C, Ourednik A. ScapeToad: not just one metric. [Accessed: 20 Sep 2015]. Lausanne: Choros Laboratory, Available from: http://scapetoad.choros.ch/
  12. Khalakdina A, Selvin S, Merrill DW, Erdmann CA, Colford JM Jr. Analysis of the spatial distribution of cryptosporidiosis in AIDS patients in San Francisco using density equalizing map projections (DEMP). Int J Hyg Environ Health. 2003;206(6):553-61.  https://doi.org/10.1078/1438-4639-00245  PMID: 14626902 
  13. van der Hoek W, van de Kassteele J, Bom B, de Bruin A, Dijkstra F, Schimmer B, et al. Smooth incidence maps give valuable insight into Q fever outbreaks in The Netherlands. Geospat Health. 2012;7(1):127-34.  https://doi.org/10.4081/gh.2012.111  PMID: 23242690 
  14. Dodd PJ, Sismanidis C, Seddon JA. Global burden of drug-resistant tuberculosis in children: a mathematical modelling study. Lancet Infect Dis. 2016;16(10):1193-201.  https://doi.org/10.1016/S1473-3099(16)30132-3  PMID: 27342768 
  15. Dorling D, Barford A, Newman M. WORLDMAPPER: the world as you’ve never seen it before. IEEE Trans Vis Comput Graph. 2006;12(5):757-64.  https://doi.org/10.1109/TVCG.2006.202  PMID: 17080797 
  16. Tobler WR. Democratic representation and apportionment: a continous transformation useful for districting. Ann N Y Acad Sci. 1973;219:215-20.  https://doi.org/10.1111/j.1749-6632.1973.tb41401.x  PMID: 4518429 
  17. Dougenik JA, Chrisman NR, Niemeyer DR. An algorithm to construct continuous area cartograms. Prof Geogr. 1985;37(1):75-81.  https://doi.org/10.1111/j.0033-0124.1985.00075.x 
  18. Gusein-Zade SM, Tikunov VS. A new technique for constructing continuous cartograms. Cartogr Geogr Inf Syst. 1993;20(3):167-73.  https://doi.org/10.1559/152304093782637424 
  19. Keim DA, North SC, Panse C. CartoDraw: a fast algorithm for generating contiguous cartograms. IEEE Trans Vis Comput Graph. 2004;10(1):95-110.  https://doi.org/10.1109/TVCG.2004.1260761  PMID: 15382701 
  20. Keim DA, Panse C, North SC. Medial-axis-based cartograms. IEEE Comput Graph Appl. 2005;25(3):60-8.  https://doi.org/10.1109/MCG.2005.64  PMID: 15943089 
  21. Kämper JH, Kobourov SG, Nöllenburg M. Circular-arc cartograms. 2013 IEEE Pacific Visualization Symposium (PacificVis). Sydney; 2013. http://dx.doi.org/10.1109/PacificVis.2013.6596121
  22. Dorling D. Area cartograms: their use and creation. In: The map reader: theories of mapping practice and cartographic representation. Dodge M, Kitchin R, Perkins C, eds. Chichester: John Wiley & Sons; 2011. p. 252-60. http://dx.doi.org/10.1002/9780470979587.ch33
  23. Edelsbrunner H, Waupotitsch R. A combinatorial approach to cartograms. J. Comput. Geom.1997;7(5-6):343-60.
  24. House DH, Kocmoud CJ. Continuous cartogram construction. Proceedings of the IEEE Visualization. Research Triangle Park; 18-23 Oct 1998. p. 197-204. https://dx.doi.org/10.1109/VISUAL.1998.745303
  25. Schulman J, Selvin S, Merrill DW. Density equalized map projections: a method for analysing clustering around a fixed point. Stat Med. 1988;7(4):491-505.  https://doi.org/10.1002/sim.4780070406  PMID: 3368676 
  26. Selvin S, Merrill D, Schulman J, Sacks S, Bedell L, Wong L. Transformations of maps to investigate clusters of disease. Soc Sci Med. 1988;26(2):215-21.
  27. Nusrat S, Alam MJ, Kobourov SG. Evaluating cartogram effectiveness. IEEE Trans Vis Comput Graph. 2016. https://dx.doi.org/10.1109/TVCG.2016.2642109

Data & Media loading...

Comment has been disabled for this content
Submit comment
Comment moderation successfully completed
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error