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 5
Figure 5. Incident tuberculosis by geographic distance from first study participant by genotypic cluster group (≤5 single-nucleotide polymorphisms) in study of high-resolution geospatial and genomic data to characterize recent tuberculosis transmission, Gaborone, Botswana, 2012–2016. Plots represent each participant by date of tuberculosis diagnosis and by geographic distance (based on participant’s primary residence) from the first participant (shown in each plot at a distance of 0 km) in each genotypic cluster group.
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