Determining the Risk-factors for Molecular Clustering of Drug-resistant Tuberculosis in South Africa

Overview

Journal BMC Public Health

Publisher Biomed Central

Specialty Public Health

Date 2023 Nov 24

PMID 38001453

Authors

Halima Said

Elizabeth Kachingwe

Yasmin Gardee

Zaheda Bhyat

John Ratabane

Linda Erasmus

Tiisetso Lebaka

Minty van der Meulen

Thabisile Gwala

Shaheed Omar

Farzana Ismail

Nazir Ismail

Affiliations

Soon will be listed here.

Abstract

Background: Drug-resistant tuberculosis (DR-TB) epidemic is driven mainly by the effect of ongoing transmission. In high-burden settings such as South Africa (SA), considerable demographic and geographic heterogeneity in DR-TB transmission exists. Thus, a better understanding of risk-factors for clustering can help to prioritise resources to specifically targeted high-risk groups as well as areas that contribute disproportionately to transmission.

Methods: The study analyzed potential risk-factors for recent transmission in SA, using data collected from a sentinel molecular surveillance of DR-TB, by comparing demographic, clinical and epidemiologic characteristics with clustering and cluster sizes. A genotypic cluster was defined as two or more patients having identical patterns by the two genotyping methods used. Clustering was used as a proxy for recent transmission. Descriptive statistics and multinomial logistic regression were used.

Result: The study identified 277 clusters, with cluster size ranging between 2 and 259 cases. The majority (81.6%) of the clusters were small (2-5 cases) with few large (11-25 cases) and very large (≥ 26 cases) clusters identified mainly in Western Cape (WC), Eastern Cape (EC) and Mpumalanga (MP). In a multivariable model, patients in clusters including 11-25 and ≥ 26 individuals were more likely to be infected by Beijing family, have XDR-TB, living in Nelson Mandela Metro in EC or Umgungunglovo in Kwa-Zulu Natal (KZN) provinces, and having history of imprisonment. Individuals belonging in a small genotypic cluster were more likely to infected with Rifampicin resistant TB (RR-TB) and more likely to reside in Frances Baard in Northern Cape (NC).

Conclusion: Sociodemographic, clinical and bacterial risk-factors influenced rate of Mycobacterium tuberculosis (M. tuberculosis) genotypic clustering. Hence, high-risk groups and hotspot areas for clustering in EC, WC, KZN and MP should be prioritized for targeted intervention to prevent ongoing DR-TB transmission.

Citing Articles

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References

Wilkinson D, Pillay M, CRUMP J, Lombard C, Davies G, Sturm A . Molecular epidemiology and transmission dynamics of Mycobacterium tuberculosis in rural Africa. Trop Med Int Health. 1997; 2(8):747-53. DOI: 10.1046/j.1365-3156.1997.d01-386.x. View

Fok A, Numata Y, Schulzer M, FitzGerald M . Risk factors for clustering of tuberculosis cases: a systematic review of population-based molecular epidemiology studies. Int J Tuberc Lung Dis. 2008; 12(5):480-92. View

Johnson R, Warren R, Strauss O, Jordaan A, Falmer A, Beyers N . An outbreak of drug-resistant tuberculosis caused by a Beijing strain in the western Cape, South Africa. Int J Tuberc Lung Dis. 2006; 10(12):1412-4. View

Gebregergs G, Alemu W . Household Contact Screening Adherence among Tuberculosis Patients in Northern Ethiopia. PLoS One. 2015; 10(5):e0125767. PMC: 4425649. DOI: 10.1371/journal.pone.0125767. View

Karmakar M, Trauer J, Ascher D, Denholm J . Hyper transmission of Beijing lineage Mycobacterium tuberculosis: Systematic review and meta-analysis. J Infect. 2019; 79(6):572-581. DOI: 10.1016/j.jinf.2019.09.016. View

Chihota V, Niehaus A, Streicher E, Wang X, Sampson S, Mason P . Geospatial distribution of Mycobacterium tuberculosis genotypes in Africa. PLoS One. 2018; 13(8):e0200632. PMC: 6070189. DOI: 10.1371/journal.pone.0200632. View

Hayward A, Goss S, Drobniewski F, Saunders N, Shaw R, Goyal M . The molecular epidemiology of tuberculosis in inner London. Epidemiol Infect. 2002; 128(2):175-84. PMC: 2869810. DOI: 10.1017/s0950268801006690. View

Godfrey-Faussett P, Sonnenberg P, Shearer S, Bruce M, Mee C, Morris L . Tuberculosis control and molecular epidemiology in a South African gold-mining community. Lancet. 2000; 356(9235):1066-71. DOI: 10.1016/s0140-6736(00)02730-6. View

Sekandi J, Neuhauser D, Smyth K, Whalen C . Active case finding of undetected tuberculosis among chronic coughers in a slum setting in Kampala, Uganda. Int J Tuberc Lung Dis. 2009; 13(4):508-13. PMC: 2842997. View

10.

Love J, Sonnenberg P, Glynn J, Gibson A, Gopaul K, Fang Z . Molecular epidemiology of tuberculosis in England, 1998. Int J Tuberc Lung Dis. 2009; 13(2):201-7. View

11.

Sousa P, Oliveira A, Gomes M, Gaio A, Duarte R . Longitudinal clustering of tuberculosis incidence and predictors for the time profiles: the impact of HIV. Int J Tuberc Lung Dis. 2016; 20(8):1027-32. DOI: 10.5588/ijtld.15.0522. View

12.

Lienhardt C . From exposure to disease: the role of environmental factors in susceptibility to and development of tuberculosis. Epidemiol Rev. 2002; 23(2):288-301. DOI: 10.1093/oxfordjournals.epirev.a000807. View

13.

Rodwell T, Kapasi A, Barnes R, Moser K . Factors associated with genotype clustering of Mycobacterium tuberculosis isolates in an ethnically diverse region of southern California, United States. Infect Genet Evol. 2012; 12(8):1917-25. PMC: 3723456. DOI: 10.1016/j.meegid.2012.08.022. View

14.

Lohmann E, Koster B, le Cessie S, Kamst-van Agterveld M, van Soolingen D, Arend S . Grading of a positive sputum smear and the risk of Mycobacterium tuberculosis transmission. Int J Tuberc Lung Dis. 2012; 16(11):1477-84. DOI: 10.5588/ijtld.12.0129. View

15.

Murray E, Marais B, Mans G, Beyers N, Ayles H, Godfrey-Faussett P . A multidisciplinary method to map potential tuberculosis transmission 'hot spots' in high-burden communities. Int J Tuberc Lung Dis. 2009; 13(6):767-74. View

16.

Brudey K, Driscoll J, Rigouts L, Prodinger W, Gori A, Al-Hajoj S . Mycobacterium tuberculosis complex genetic diversity: mining the fourth international spoligotyping database (SpolDB4) for classification, population genetics and epidemiology. BMC Microbiol. 2006; 6:23. PMC: 1468417. DOI: 10.1186/1471-2180-6-23. View

17.

Noppert G, Yang Z, Clarke P, Ye W, Davidson P, Wilson M . Individual- and neighborhood-level contextual factors are associated with Mycobacterium tuberculosis transmission: genotypic clustering of cases in Michigan, 2004-2012. Ann Epidemiol. 2017; 27(6):371-376.e5. PMC: 5583706. DOI: 10.1016/j.annepidem.2017.05.009. View

18.

Small P, Hopewell P, Singh S, Paz A, Parsonnet J, Ruston D . The epidemiology of tuberculosis in San Francisco. A population-based study using conventional and molecular methods. N Engl J Med. 1994; 330(24):1703-9. DOI: 10.1056/NEJM199406163302402. View

19.

Glynn J, Crampin A, Yates M, Traore H, Mwaungulu F, Ngwira B . The importance of recent infection with Mycobacterium tuberculosis in an area with high HIV prevalence: a long-term molecular epidemiological study in Northern Malawi. J Infect Dis. 2005; 192(3):480-7. DOI: 10.1086/431517. View

20.

Melsew Y, Doan T, Gambhir M, Cheng A, McBryde E, Trauer J . Risk factors for infectiousness of patients with tuberculosis: a systematic review and meta-analysis. Epidemiol Infect. 2018; 146(3):345-353. PMC: 9134570. DOI: 10.1017/S0950268817003041. View