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Scott LE, Shapiro AN, Da Silva MP, Tsoka J, Jacobson KR, Emch M, Moultrie H, Jenkins HE, Moore D, Van Rie A, Stevens WS. Integrating Molecular Diagnostics and GIS Mapping: A Multidisciplinary Approach to Understanding Tuberculosis Disease Dynamics in South Africa Using Xpert MTB/RIF. Diagnostics (Basel) 2023; 13:3163. [PMID: 37891984 PMCID: PMC10606157 DOI: 10.3390/diagnostics13203163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 08/30/2023] [Accepted: 09/14/2023] [Indexed: 10/29/2023] Open
Abstract
An investigation was carried out to examine the use of national Xpert MTB/RIF data (2013-2017) and GIS technology for MTB/RIF surveillance in South Africa. The aim was to exhibit the potential of using molecular diagnostics for TB surveillance across the country. The variables analysed include Mycobacterium tuberculosis (Mtb) positivity, the mycobacterial proportion of rifampicin-resistant Mtb (RIF), and probe frequency. The summary statistics of these variables were generated and aggregated at the facility and municipal level. The spatial distribution patterns of the indicators across municipalities were determined using the Moran's I and Getis Ord (Gi) statistics. A case-control study was conducted to investigate factors associated with a high mycobacterial load. Logistic regression was used to analyse this study's results. There was striking spatial heterogeneity in the distribution of Mtb and RIF across South Africa. The median patient age, urban setting classification, and number of health care workers were found to be associated with the mycobacterial load. This study illustrates the potential of using data generated from molecular diagnostics in combination with GIS technology for Mtb surveillance in South Africa. Spatially targeted interventions can be implemented in areas where high-burden Mtb persists.
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Affiliation(s)
- Lesley Erica Scott
- Wits Diagnostic Innovation Hub, Faculty of Health Science, University of the Witwatersrand, Johannesburg 2093, South Africa; (M.P.D.S.); (J.T.); (W.S.S.)
| | - Anne Nicole Shapiro
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA; (A.N.S.); (H.E.J.)
| | - Manuel Pedro Da Silva
- Wits Diagnostic Innovation Hub, Faculty of Health Science, University of the Witwatersrand, Johannesburg 2093, South Africa; (M.P.D.S.); (J.T.); (W.S.S.)
- National Priority Program of the National Health Laboratory Services (NHLS), Johannesburg 2131, South Africa
| | - Jonathan Tsoka
- Wits Diagnostic Innovation Hub, Faculty of Health Science, University of the Witwatersrand, Johannesburg 2093, South Africa; (M.P.D.S.); (J.T.); (W.S.S.)
| | - Karen Rita Jacobson
- Division of Infectious Diseases, Boston Medical Center, Boston, MA 02118, USA;
| | - Michael Emch
- Department of Epidemiology, University of North Carolina School, Chapel Hill, NC 27127, USA;
- Department of Geography and Environment, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Harry Moultrie
- National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg 2192, South Africa;
| | - Helen Elizabeth Jenkins
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA; (A.N.S.); (H.E.J.)
| | - David Moore
- Department of Clinical Research, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK;
| | - Annelies Van Rie
- Faculty of Medicine and Health Sciences, University of Antwerp, 2000 Antwerpen, Belgium;
| | - Wendy Susan Stevens
- Wits Diagnostic Innovation Hub, Faculty of Health Science, University of the Witwatersrand, Johannesburg 2093, South Africa; (M.P.D.S.); (J.T.); (W.S.S.)
- National Priority Program of the National Health Laboratory Services (NHLS), Johannesburg 2131, South Africa
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Fofana AM, Moultrie H, Scott L, Jacobson KR, Shapiro AN, Dor G, Crankshaw B, Silva PD, Jenkins HE, Bor J, Stevens WS. Cross-municipality migration and spread of tuberculosis in South Africa. Sci Rep 2023; 13:2674. [PMID: 36792792 PMCID: PMC9930008 DOI: 10.1038/s41598-023-29804-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 02/10/2023] [Indexed: 02/17/2023] Open
Abstract
Human migration facilitates the spread of infectious disease. However, little is known about the contribution of migration to the spread of tuberculosis in South Africa. We analyzed longitudinal data on all tuberculosis test results recorded by South Africa's National Health Laboratory Service (NHLS), January 2011-July 2017, alongside municipality-level migration flows estimated from the 2016 South African Community Survey. We first assessed migration patterns in people with laboratory-diagnosed tuberculosis and analyzed demographic predictors. We then quantified the impact of cross-municipality migration on tuberculosis incidence in municipality-level regression models. The NHLS database included 921,888 patients with multiple clinic visits with TB tests. Of these, 147,513 (16%) had tests in different municipalities. The median (IQR) distance travelled was 304 (163 to 536) km. Migration was most common at ages 20-39 years and rates were similar for men and women. In municipality-level regression models, each 1% increase in migration-adjusted tuberculosis prevalence was associated with a 0.47% (95% CI: 0.03% to 0.90%) increase in the incidence of drug-susceptible tuberculosis two years later, even after controlling for baseline prevalence. Similar results were found for rifampicin-resistant tuberculosis. Accounting for migration improved our ability to predict future incidence of tuberculosis.
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Affiliation(s)
- Abdou M Fofana
- Institute for Health System Innovation & Policy, Boston University, Questrom School of Business, Boston, USA.
- Boston University School of Public Health, Boston, USA.
| | - Harry Moultrie
- Centre for Tuberculosis, National Institute for Communicable Diseases, a division of the National Health Laboratory Services, Johannesburg, South Africa
| | - Lesley Scott
- Wits Diagnostic Innovation Hub, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Karen R Jacobson
- Section of Infectious Diseases, Boston University School of Medicine and Boston Medical Center, Boston, USA
| | | | - Graeme Dor
- Wits Diagnostic Innovation Hub, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Beth Crankshaw
- Centre for Tuberculosis, National Institute for Communicable Diseases, a division of the National Health Laboratory Services, Johannesburg, South Africa
| | - Pedro Da Silva
- National Health Laboratory Service, Johannesburg, South Africa
| | | | - Jacob Bor
- Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Boston University School of Public Health, Boston, USA
| | - Wendy S Stevens
- Wits Diagnostic Innovation Hub, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- National Health Laboratory Service, Johannesburg, South Africa
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Space-time cluster detection techniques for infectious diseases: A systematic review. Spat Spatiotemporal Epidemiol 2023; 44:100563. [PMID: 36707196 DOI: 10.1016/j.sste.2022.100563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 12/08/2022] [Accepted: 12/14/2022] [Indexed: 12/23/2022]
Abstract
BACKGROUND Public health organizations have increasingly harnessed geospatial technologies for disease surveillance, health services allocation, and targeting place-based health promotion initiatives. METHODS We conducted a systematic review around the theme of space-time clustering detection techniques for infectious diseases using PubMed, Web of Science, and Scopus. Two reviewers independently determined inclusion and exclusion. RESULTS Of 2,887 articles identified, 354 studies met inclusion criteria, the majority of which were application papers. Studies of airborne diseases were dominant, followed by vector-borne diseases. Most research used aggregated data instead of point data, and a significant proportion of articles used a repetition of a spatial clustering method, instead of using a "true" space-time detection approach, potentially leading to the detection of false positives. Noticeably, most articles did not make their data available, limiting replicability. CONCLUSION This review underlines recent trends in the application of space-time clustering methods to the field of infectious disease, with a rapid increase during the COVID-19 pandemic.
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Sy KTL, Leavitt SV, de Vos M, Dolby T, Bor J, Horsburgh CR, Warren RM, Streicher EM, Jenkins HE, Jacobson KR. Spatial heterogeneity of extensively drug resistant-tuberculosis in Western Cape Province, South Africa. Sci Rep 2022; 12:10844. [PMID: 35760977 PMCID: PMC9237070 DOI: 10.1038/s41598-022-14581-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 06/09/2022] [Indexed: 02/04/2023] Open
Abstract
Tuberculosis (TB) remains a leading infectious disease killer globally. Treatment outcomes are especially poor among people with extensively drug-resistant (XDR) TB, until recently defined as rifampicin-resistant (RR) TB with resistance to an aminoglycoside (amikacin) and a fluoroquinolone (ofloxacin). We used laboratory TB test results from Western Cape province, South Africa between 2012 and 2015 to identify XDR-TB and pre-XDR-TB (RR-TB with resistance to one second-line drug) spatial hotspots. We mapped the percentage and count of individuals with RR-TB that had XDR-TB and pre-XDR-TB across the province and in Cape Town, as well as amikacin-resistant and ofloxacin-resistant TB. We found the percentage of pre-XDR-TB and the count of XDR-TB/pre-XDR-TB highly heterogeneous with geographic hotspots within RR-TB high burden areas, and found hotspots in both percentage and count of amikacin-resistant and ofloxacin-resistant TB. The spatial distribution of percentage ofloxacin-resistant TB hotspots was similar to XDR-TB hotspots, suggesting that fluoroquinolone-resistace is often the first step to additional resistance. Our work shows that interventions used to reduce XDR-TB incidence may need to be targeted within spatial locations of RR-TB, and further research is required to understand underlying drivers of XDR-TB transmission in these locations.
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Affiliation(s)
- Karla Therese L Sy
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Sarah V Leavitt
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Margaretha de Vos
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research/South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Tania Dolby
- National Health Laboratory Service, Cape Town, South Africa
| | - Jacob Bor
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - C Robert Horsburgh
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Global Health, Boston University School of Public Health, Boston, MA, USA
- Section of Infectious Diseases, School of Medicine and Boston Medical Center, Boston University, Boston, MA, USA
| | - Robin M Warren
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research/South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Elizabeth M Streicher
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research/South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Helen E Jenkins
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Karen R Jacobson
- Section of Infectious Diseases, School of Medicine and Boston Medical Center, Boston University, Boston, MA, USA.
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Alene KA, Xu Z, Bai L, Yi H, Tan Y, Gray D, Viney K, Clements AC. Spatial clustering of drug-resistant tuberculosis in Hunan province, China: an ecological study. BMJ Open 2021; 11:e043685. [PMID: 33795303 PMCID: PMC8021748 DOI: 10.1136/bmjopen-2020-043685] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
OBJECTIVE This study aimed to investigate the spatial distribution of drug-resistant tuberculosis (DR-TB) in Hunan province, China. METHODS An ecological study was conducted using DR-TB data collected from the Tuberculosis Control Institute of Hunan Province between 2012 and 2018. Spatial clustering of DR-TB was explored using the Getis-Ord statistic. A Poisson regression model was fitted with a conditional autoregressive prior structure, and with posterior parameters estimated using a Bayesian Markov chain Monte Carlo simulation, to quantify associations with possible risk factors and identify clusters of high DR-TB risk. RESULTS A total of 2649 DR-TB patients were reported to Hunan TB Control Institute between 2012 and 2018. The majority of the patients were male (74.8%, n=1983) and had a history of TB treatment (88.53%, n=2345). The proportion of extensively DR-TB among all DR-TB was 3.3% (95% CI 2.7% to 4.1%), which increased from 2.8% in 2012 to 4.4% in 2018. Of 1287 DR-TB patients with registered treatment outcomes, 434 (33.8%) were cured, 198 (15.3%) completed treatment, 92 (7.1%) died, 108 (8.3%) had treatment failure and 455 (35.3%) were lost to follow-up. Half (50.9%, n=655) had poor treatment outcomes. The annual cumulative incidence rate of notified DR-TB increased over time from 0.25 per 100 000 people in 2012 to 0.83 per 100 000 people in 2018. Substantial spatial heterogeneity was observed, and hotspots were detected in counties located in the North and East parts of Hunan province. The cumulative incidence of notified DR-TB was significantly associated with urban communities. CONCLUSION The annual incidence of notified DR-TB increased over time in Hunan province. Spatial clustering of DR-TB was detected and significantly associated with urbanisation. This finding suggests that targeting interventions to the highest risk areas and population groups would be effective in reducing the burden and ongoing transmission of DR-TB.
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Affiliation(s)
- Kefyalew Addis Alene
- Faculty of Health Sciences, Curtin University, Bentley, Western Australia, Australia
- Telethon Kids Institute, Nedlands, Western Australia, Australia
| | - Zuhui Xu
- Department of Tuberculosis Control, Tuberculosis Control Institute of Hunan Province, Changsha, Hunan, China
| | - Liqiong Bai
- Department of Director's Office, Hunan Tuberculosis Control Institute, Changsha, Hunan, China
| | - Hengzhong Yi
- Department of MDR-TB, Internal Medicine, Hunan Chest Hospital, Changsha, China
| | - Yunhong Tan
- Department of MDR-TB, Internal Medicine, Hunan Chest Hospital, Changsha, China
| | - Darren Gray
- Research School of Population Health, Australian National University, Canberra, ACT, Australia
| | - Kerri Viney
- Research School of Population Health, Australian National University, Canberra, ACT, Australia
- Public Health Sciences, Karolinska Institute, Stockholm, Sweden
- School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Archie Ca Clements
- Faculty of Health Sciences, Curtin University, Bentley, Western Australia, Australia
- Telethon Kids Institute, Nedlands, Western Australia, Australia
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Leavitt SV, Jacobson KR, Ragan EJ, Bor J, Hughes J, Bouton TC, Dolby T, Warren RM, Jenkins HE. Decentralized Care for Rifampin-Resistant Tuberculosis, Western Cape, South Africa. Emerg Infect Dis 2021; 27:728-739. [PMID: 33622466 PMCID: PMC7920662 DOI: 10.3201/eid2703.203204] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
In 2011, South Africa implemented a policy to decentralize treatment for rifampin-resistant tuberculosis (TB) to reduce durations of hospitalization and enable local treatment. We assessed policy implementation in Western Cape Province, where services expanded from 6 specialized TB hospitals to 406 facilities, by analyzing National Health Laboratory Service data on TB during 2012-2015. We calculated the percentage of patients who visited a TB hospital <1 year after rifampin-resistant TB diagnosis, the median duration of their hospitalizations, and the total distance between facilities visited. We assessed temporal changes with linear regression and stratified results by location. Of 2,878 patients, 65% were from Cape Town. In Cape Town, 29% visited a TB hospital; elsewhere, 68% visited a TB hospital. We found that hospitalizations and travel distances were shorter in Cape Town than in the surrounding areas.
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Suthar AB, Moonan PK, Alexander HL. Towards national systems for continuous surveillance of antimicrobial resistance: Lessons from tuberculosis. PLoS Med 2018; 15:e1002658. [PMID: 30216354 PMCID: PMC6138360 DOI: 10.1371/journal.pmed.1002658] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
In a Perspective on the research article from Jacobson and colleagues, Amitabh Suthar and colleagues from the Centers for Disease Control and Prevention discuss the importance of and considerations for developing real-time and large-scale reporting systems for tracking and controlling antimicrobial resistance.
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Affiliation(s)
- Amitabh B. Suthar
- Center for Global Health, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Patrick K. Moonan
- Center for Global Health, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Heather L. Alexander
- Center for Global Health, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
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