Use of High-Resolution Geospatial and Genomic Data to Characterize Recent Tuberculosis Transmission, Botswana
Chelsea R. Baker
1, Ivan Barilar
1, Leonardo S. de Araujo, Anne W. Rimoin, Daniel M. Parker, Rosanna Boyd, James L. Tobias, Patrick K. Moonan, Eleanor S. Click, Alyssa Finlay, John E. Oeltmann, Vladimir N. Minin, Chawangwa Modongo, Nicola M. Zetola
2, Stefan Niemann
2, and Sanghyuk S. Shin
2
Author affiliations: University of California, Irvine, California, USA (C.R. Baker, D.M. Parker, V.N. Minin, S.S. Shin); Forschungszentrum, Borstel, Germany (I. Barilar, L.S. de Araujo, S. Niemann); University of California, Los Angeles, California, USA (A.W. Rimoin); US Centers for Disease Control and Prevention, Gaborone, Botswana (R. Boyd, A. Finlay); US Centers for Disease Control and Prevention, Atlanta, Georgia, USA (J.L. Tobias, P.K. Moonan, R. Boyd, E.S. Click, A. Finlay, J.E. Oeltmann); Botswana–UPenn Partnership, Gaborone (C. Modongo, N.M. Zetola); Victus Global Botswana Organisation, Gaborone (C. Modongo, N.M. Zetola)
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Figure 4
Figure 4. K-function differences for Mycobacterium tuberculosis genotypic groups A–E (≤5 single-nucleotide polymorphisms) compared with ungrouped strains in study of high-resolution geospatial and genomic data to characterize recent tuberculosis transmission, Gaborone, Botswana, 2012–2016. Differences in K-functions were used to assess geospatial clustering among participants in each group relative to participants with ungrouped strains. Observations falling above the upper 95% envelope indicate significant spatial clustering.
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