Top

Published in:

Open Access 01-12-2021 | Tuberculosis | Research article

Community transmission of multidrug-resistant tuberculosis is associated with activity space overlap in Lima, Peru

Authors: David P. Bui, Shruthi S. Chandran, Eyal Oren, Heidi E. Brown, Robin B. Harris, Gwenan M. Knight, Louis Grandjean

Published in: BMC Infectious Diseases | Issue 1/2021

Abstract

Background

Transmission of multidrug-resistant tuberculosis (MDRTB) requires spatial proximity between infectious cases and susceptible persons. We assess activity space overlap among MDRTB cases and community controls to identify potential areas of transmission.

Methods

We enrolled 35 MDRTB cases and 64 TB-free community controls in Lima, Peru. Cases were whole genome sequenced and strain clustering was used as a proxy for transmission. GPS data were gathered from participants over seven days. Kernel density estimation methods were used to construct activity spaces from GPS locations and the utilization distribution overlap index (UDOI) was used to quantify activity space overlap.

Results

Activity spaces of controls (median = 35.6 km², IQR = 25.1–54) were larger than cases (median = 21.3 km², IQR = 17.9–48.6) (P = 0.02). Activity space overlap was greatest among genetically clustered cases (mean UDOI = 0.63, sd = 0.67) and lowest between cases and controls (mean UDOI = 0.13, sd = 0.28). UDOI was positively associated with genetic similarity of MDRTB strains between case pairs (P < 0.001). The odds of two cases being genetically clustered increased by 22% per 0.10 increase in UDOI (OR = 1.22, CI = 1.09–1.36, P < 0.001).

Conclusions

Activity space overlap is associated with MDRTB clustering. MDRTB transmission may be occurring in small, overlapping activity spaces in community settings. GPS studies may be useful in identifying new areas of MDRTB transmission.

Available only for authorised users

Yates TA, Khan PY, Knight GM, Taylor JG, McHugh TD, Lipman M, et al. The transmission of Mycobacterium tuberculosis in high burden settings. Lancet Infect Dis. 2016;16:227–38. https://doi.org/10.1016/S1473-3099(15)00499-5.CrossRefPubMed

Zelner JL, Murray MB, Becerra MC, Galea J, Lecca L, Calderon R, et al. Identifying hotspots of multidrug-resistant tuberculosis transmission using spatial and molecular genetic data. J Infect Dis. 2015;213:287–94. https://doi.org/10.1093/infdis/jiv387.CrossRefPubMedPubMedCentral

Chamie G, Wandera B, Marquez C, Kato-Maeda M, Kamya MR, Havlir DV, et al. Identifying locations of recent TB transmission in rural Uganda: a multidisciplinary approach. Trop Med Int Heal. 2015;20:537–45. https://doi.org/10.1111/tmi.12459.CrossRef

Chamie G, Kato-Maeda M, Emperador DM, Wandera B, Mugagga O, Crandall J, et al. Spatial overlap links seemingly unconnected genotype-matched TB cases in rural Uganda. PLoS One. 2018;13:e0192666. https://doi.org/10.1371/journal.pone.0192666.CrossRefPubMedPubMedCentral

Izumi K, Ohkado A, Uchimura K, Murase Y, Tatsumi Y, Kayebeta A, et al. Detection of tuberculosis infection hotspots using activity spaces based spatial approach in an urban Tokyo, from 2003 to 2011. PLoS One. 2015;10:e0138831. https://doi.org/10.1371/journal.pone.0138831.CrossRefPubMedPubMedCentral

Shaweno D, Karmakar M, Alene KA, Ragonnet R, Clements AC, Trauer JM, et al. Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review. BMC Med. 2018;16:193. https://doi.org/10.1186/s12916-018-1178-4.CrossRefPubMedPubMedCentral

Gardy JL, Johnston JC, Sui SJH, Cook VJ, Shah L, Brodkin E, et al. Whole-genome sequencing and social-network analysis of a tuberculosis outbreak. N Engl J Med. 2011;364:730–9. https://doi.org/10.1056/NEJMoa1003176.CrossRefPubMed

Klovdahl AS, Graviss EA, Yaganehdoost A, Ross MW, Wanger A, Adams GJ, et al. Networks and tuberculosis: an undetected community outbreak involving public places. Soc Sci Med. 2001;52:681–94 http://www.ncbi.nlm.nih.gov/pubmed/11218173.CrossRef

Dowdy DW, Golub JE, Chaisson RE, Saraceni V. Heterogeneity in tuberculosis transmission and the role of geographic hotspots in propagating epidemics. Proc Natl Acad Sci U S A. 2012;109:9557–62. https://doi.org/10.1073/pnas.1203517109.CrossRefPubMedPubMedCentral

10.

Hirsch JA, Winters M, Clarke P, McKay H. Generating GPS activity spaces that shed light upon the mobility habits of older adults: a descriptive analysis. Int J Health Geogr. 2014;13:51. https://doi.org/10.1186/1476-072X-13-51.CrossRefPubMedPubMedCentral

11.

Sherman JE, Spencer J, Preisser JS, Gesler WM, Arcury TA. A suite of methods for representing activity space in a healthcare accessibility study. Int J Health Geogr. 2005;4:24. https://doi.org/10.1186/1476-072X-4-24.CrossRefPubMedPubMedCentral

12.

Worrell MC, Kramer M, Yamin A, Ray SM, Goswami ND. Use of activity space in a tuberculosis outbreak: bringing homeless persons into spatial analyses. Open Forum Infect Dis. 2017;4. https://doi.org/10.1093/ofid/ofw280.

13.

Peterson ML, Gandhi NR, Clennon J, Nelson KN, Morris N, Ismail N, et al. Extensively drug-resistant tuberculosis “hotspots” and sociodemographic associations in Durban, South Africa. Int J Tuberc Lung Dis. 2019;23:720–7.CrossRef

14.

Lee NC, Voss C, Frazer AD, Hirsch JA, McKay HA, Winters M. Does activity space size influence physical activity levels of adolescents?—a GPS study of an urban environment. Prev Med Reports. 2016;3:75–8. https://doi.org/10.1016/j.pmedr.2015.12.002.CrossRef

15.

Shareck M, Kestens Y, Gauvin L. Examining the spatial congruence between data obtained with a novel activity location questionnaire, continuous GPS tracking, and prompted recall surveys. Int J Health Geogr. 2013;12:40. https://doi.org/10.1186/1476-072x-12-40.CrossRefPubMedPubMedCentral

16.

Paz-Soldan VA, Reiner RC, Morrison AC, Stoddard ST, Kitron U, Scott TW, et al. Strengths and weaknesses of global positioning system (GPS) data-loggers and semi-structured interviews for capturing fine-scale human mobility: findings from Iquitos. Peru PLoS Negl Trop Dis. 2014;8:e2888. https://doi.org/10.1371/journal.pntd.0002888.CrossRefPubMed

17.

Thierry B, Chaix B, Kestens Y. Detecting activity locations from raw GPS data: a novel kernel-based algorithm. Int J Health Geogr. 2013;12:14. https://doi.org/10.1186/1476-072x-12-14.CrossRefPubMedPubMedCentral

18.

Vazquez-Prokopec GM, Bisanzio D, Stoddard ST, Paz-Soldan V, Morrison AC, Elder JP, et al. Using GPS technology to quantify human mobility, Dynamic Contacts and Infectious Disease Dynamics in a Resource-Poor Urban Environment. PLoS One. 2013;8:e58802. https://doi.org/10.1371/journal.pone.0058802.CrossRefPubMedPubMedCentral

19.

Vazquez-Prokopec GM, Stoddard ST, Paz-Soldan V, Morrison AC, Elder JP, Kochel TJ, et al. Usefulness of commercially available GPS data-loggers for tracking human movement and exposure to dengue virus. Int J Health Geogr. 2009;8:68. https://doi.org/10.1186/1476-072x-8-68.CrossRefPubMedPubMedCentral

20.

Alarcon V, Alarcon E, Figueroa C, Mendoza-Ticona A. Tubersulosis en el Perú: situación epidemiológica, avances y desafíos para su control. Rev Peru Med Exp Salud Publica. 2017;34:299–310.CrossRef

21.

Grandjean L, Gilman RH, Martin L, Soto E, Castro B, Lopez S, et al. Transmission of multidrug-resistant and drug-susceptible tuberculosis within households: a prospective cohort study. PLoS Med. 2015;12:e1001843. https://doi.org/10.1371/journal.pmed.1001843.CrossRefPubMedPubMedCentral

22.

Grandjean L, Gilman RH, Iwamoto T, Köser CU, Coronel J, Zimic M, et al. Convergent evolution and topologically disruptive polymorphisms among multidrug-resistant tuberculosis in Peru. PLoS One. 2017;12:e0189838. https://doi.org/10.1371/journal.pone.0189838.CrossRefPubMedPubMedCentral

23.

Grandjean L, Monteserin J, Gilman R, Pauschardt J, Bonilla C, Ritacco V, et al. Association between bacterial homoplastic variants and radiological pathology in tuberculosis Tuberculosis. Thorax. 2020. https://doi.org/10.1136/thoraxjnl-2019-213281.

24.

Meehan CJ, Moris P, Kohl TA, Pečerska J, Akter S, Merker M, et al. The relationship between transmission time and clustering methods in Mycobacterium tuberculosis epidemiology. EBioMedicine. 2018;37:410–6. https://doi.org/10.1016/j.ebiom.2018.10.013.CrossRefPubMedPubMedCentral

25.

Powell RA, Mitchell MS. What is a home range? J Mammal. 2012;93:948–58. https://doi.org/10.1644/11-MAMM-S-177.1.CrossRef

26.

Fieberg J, Kochanny CO. Quantifying home-range overlap: the importance of the utilization distribution. J Wildl Manag. 2005;69:1346–59.CrossRef

27.

Worton BJ. Kernel methods for estimating the utilization distribution in home-range studies. Ecology. 1989;70:164–8. https://doi.org/10.2307/1938423.CrossRef

28.

Clapp JG, Beck JL. Evaluating distributional shifts in home range estimates. Ecol Evol. 2015;5:3869–78. https://doi.org/10.1002/ece3.1655.CrossRefPubMedPubMedCentral

29.

Walter WD, Onorato DP, Fischer JW. Is there a single best estimator?Selection of home range estimators using area-under-the-curve. Mov Ecol. 2015;3:10. https://doi.org/10.1186/s40462-015-0039-4.CrossRefPubMedPubMedCentral

30.

Calenge C. Home range estimation in R: the adehabitatHR package. 2015. https://cran.r-project.org/web/packages/adehabitatHR/vignettes/adehabitatHR.pdf.

31.

Bui DP, Oren E, Roe DJ, Brown HE, Harris RB, Knight GM, et al. A Case Control Study to Identify Community Venues Associated with Genetically Clustered Multidrug-Resistant Tuberculosis Disease in Lima, Peru. Clin Infect Dis. 2018:ciy746. https://doi.org/10.1093/cid/ciy746.

32.

Cudahy PGT, Andrews JR, Bilinski A, Dowdy DW, Mathema B, Menzies NA, et al. Spatially targeted screening to reduce tuberculosis transmission in high-incidence settings. Lancet Infect Dis. 2019;19:e89–95. https://doi.org/10.1016/S1473-3099(18)30443-2.CrossRefPubMed

33.

Yang C, Lu L, Warren JL, Wu J, Jiang Q, Zuo T, et al. Internal migration and transmission dynamics of tuberculosis in Shanghai, China: an epidemiological, spatial, genomic analysis. Lancet Infect Dis. 2018;18:788–95. https://doi.org/10.1016/S1473-3099(18)30218-4.CrossRefPubMedPubMedCentral

34.

Warren JL, Grandjean L, Moore DAJ, Lithgow A, Coronel J, Sheen P, et al. Investigating spillover of multidrug-resistant tuberculosis from a prison: a spatial and molecular epidemiological analysis. BMC Med. 2018;16:122. https://doi.org/10.1186/s12916-018-1111-x.CrossRefPubMedPubMedCentral

35.

Kestens Y, Thierry B, Shareck M, Steinmetz-Wood M, Chaix B. Integrating activity spaces in health research: comparing the VERITAS activity space questionnaire with 7-day GPS tracking and prompted recall. Spat Spatiotemporal Epidemiol. 2018;25:1–9. https://doi.org/10.1016/J.SSTE.2017.12.003.CrossRefPubMed

36.

Hatherell H-A, Colijn C, Stagg HR, Jackson C, Winter JR, Abubakar I. Interpreting whole genome sequencing for investigating tuberculosis transmission: a systematic review. BMC Med. 2016;14:21. https://doi.org/10.1186/s12916-016-0566-x.CrossRefPubMedPubMedCentral

37.

Siła-Nowicka K, Vandrol J, Oshan T, Long JA, Demšar U, Fotheringham AS. Analysis of human mobility patterns from GPS trajectories and contextual information. Int J Geogr Inf Sci. 2016;30:881–906. https://doi.org/10.1080/13658816.2015.1100731.CrossRef

Title: Community transmission of multidrug-resistant tuberculosis is associated with activity space overlap in Lima, Peru
Authors: David P. Bui
Shruthi S. Chandran
Eyal Oren
Heidi E. Brown
Robin B. Harris
Gwenan M. Knight
Louis Grandjean
Publication date: 01-12-2021
Publisher: BioMed Central
Keywords: Tuberculosis
Mycobacterium Tuberculosis
Tuberculosis
Published in: BMC Infectious Diseases / Issue 1/2021
Electronic ISSN: 1471-2334
DOI: https://doi.org/10.1186/s12879-021-05953-8

ACC 2024 Congress Coverage

Heart Failure Video

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Community transmission of multidrug-resistant tuberculosis is associated with activity space overlap in Lima, Peru

Abstract

Background

Methods

Results

Conclusions

ACC 2024 Congress Coverage

Year in Review: Heart failure and cardiomyopathies

Semaglutide benefits people with type 2 diabetes and obesity-related heart failure

Incentivised to exercise

New intervention for STEMI-related cardiogenic shock

» View more highlights on the ACC 2024 congress hub page

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

Please log in to get access to this content

Other articles of this Issue 1/2021

Transmitted drug resistance to Tenofovir/Emtricitabine among persons with newly diagnosed HIV infection in Shenyang city, Northeast China from 2016 to 2018

Public health impact and cost effectiveness of routine and catch-up vaccination of girls and women with a nine-valent HPV vaccine in Japan: a model-based study

Correction to: Transmission dynamics and control of two epidemic waves of SARS-CoV-2 in South Korea

Effectiveness of joint 3 + 1 malaria strategy along China–Myanmar cross border areas

A cluster randomized trial of interferon ß-1a for the reduction of transmission of SARS-Cov-2: protocol for the Containing Coronavirus Disease 19 trial (ConCorD-19)

Spectrum of antibiotic resistance in UTI caused by Escherichia coli among HIV-infected patients in Uganda: a cross-sectional study

ACC 2024 Congress Coverage

Year in Review: Heart failure and cardiomyopathies

Semaglutide benefits people with type 2 diabetes and obesity-related heart failure

Incentivised to exercise

New intervention for STEMI-related cardiogenic shock

» View more highlights on the ACC 2024 congress hub page