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Li M, Lu L, Jiang Q, Jiang Y, Yang C, Li J, Zhang Y, Zou J, Li Y, Dai W, Hong J, Takiff H, Shen X, Guo X, Yuan Z, Gao Q. Genotypic and spatial analysis of transmission dynamics of tuberculosis in Shanghai, China: a 10-year prospective population-based surveillance study. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 38:100833. [PMID: 37790084 PMCID: PMC10544272 DOI: 10.1016/j.lanwpc.2023.100833] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 06/02/2023] [Accepted: 06/15/2023] [Indexed: 10/05/2023]
Abstract
Background With improved tuberculosis (TB) control programs, the incidence of TB in China declined dramatically over the past few decades, but recently the rate of decrease has slowed, especially in large cities such as Shanghai. To help formulate strategies to further reduce TB incidence, we performed a 10-year study in Songjiang, a district of Shanghai, to delineate the characteristics, transmission patterns, and dynamic changes of the local TB burden. Methods We conducted a population-based study of culture-positive pulmonary TB patients diagnosed in Songjiang during 2011-2020. Genomic clusters were defined with a threshold distance of 12-single-nucleotide-polymorphisms based on whole-genome sequencing, and risk factors for clustering were identified by logistic regression. Transmission inference was performed using phybreak. The distances between the residences of patients were compared to the genomic distances of their isolates. Spatial patient hotspots were defined with kernel density estimation. Findings Of 2212 enrolled patients, 74.7% (1652/2212) were internal migrants. The clustering rate (25.2%, 558/2212) and spatial concentrations of clustered and unclustered patients were unchanged over the study period. Migrants had significantly higher TB rates but less clustering than residents. Clustering was highest in male migrants, younger patients and both residents and migrants employed in physical labor. Only 22.1% of transmission events occurred between residents and migrants, with residents more likely to transmit to migrants. The clustering risk decreased rapidly with increasing distances between patient residences, but more than half of clustered patient pairs lived ≥5 km apart. Epidemiologic links were identified for only 15.6% of clustered patients, mostly in close contacts. Interpretation Although some of the TB in Songjiang's migrant population is caused by strains brought by infected migrants, local, recent transmission is an important driver of the TB burden. These results suggest that further reductions in TB incidence require novel strategies to detect TB early and interrupt urban transmission. Funding Shanghai Municipal Science and Technology Major Project (ZD2021CY001), National Natural Science Foundation of China (82272376), National Research Council of Science and Technology Major Project of China (2017ZX10201302-006).
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Affiliation(s)
- Meng Li
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China
| | - Liping Lu
- Department of Tuberculosis Control, Songjiang District Center for Disease Control and Prevention, Shanghai, China
| | - Qi Jiang
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China
- School of Public Health, Renmin Hospital Public Health Research Institute, Wuhan University, Wuhan, China
| | - Yuan Jiang
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
- Shanghai Institute of Preventive Medicine, Shanghai, China
| | - Chongguang Yang
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Jing Li
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
- Shanghai Institute of Preventive Medicine, Shanghai, China
| | - Yangyi Zhang
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
- Shanghai Institute of Preventive Medicine, Shanghai, China
| | - Jinyan Zou
- Department of Tuberculosis Control, Songjiang District Center for Disease Control and Prevention, Shanghai, China
| | - Yong Li
- Department of Tuberculosis Control, Songjiang District Center for Disease Control and Prevention, Shanghai, China
| | - Wenqi Dai
- Department of Clinical Laboratory, Songjiang District Central Hospital, Shanghai, China
| | - Jianjun Hong
- Department of Tuberculosis Control, Songjiang District Center for Disease Control and Prevention, Shanghai, China
| | - Howard Takiff
- Laboratorio de Genética Molecular, CMBC, Instituto Venezolano de Investigaciones Científicas, IVIC, Caracas, Venezuela
| | - Xin Shen
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
- Shanghai Institute of Preventive Medicine, Shanghai, China
| | - Xiaoqin Guo
- Department of Tuberculosis Control, Songjiang District Center for Disease Control and Prevention, Shanghai, China
| | - Zhengan Yuan
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
- Shanghai Institute of Preventive Medicine, Shanghai, China
| | - Qian Gao
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Science, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China
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Marquez C, Chen Y, Atukunda M, Chamie G, Balzer LB, Kironde J, Ssemmondo E, Mwangwa F, Kabami J, Owaraganise A, Kakande E, Abbott R, Ssekyanzi B, Koss C, Kamya MR, Charlebois ED, Havlir DV, Petersen ML. The Association Between Social Network Characteristics and Tuberculosis Infection Among Adults in 9 Rural Ugandan Communities. Clin Infect Dis 2023; 76:e902-e909. [PMID: 35982635 PMCID: PMC10169405 DOI: 10.1093/cid/ciac669] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 08/02/2022] [Accepted: 08/16/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Social network analysis can elucidate tuberculosis transmission dynamics outside the home and may inform novel network-based case-finding strategies. METHODS We assessed the association between social network characteristics and prevalent tuberculosis infection among residents (aged ≥15 years) of 9 rural communities in Eastern Uganda. Social contacts named during a census were used to create community-specific nonhousehold social networks. We evaluated whether social network structure and characteristics of first-degree contacts (sex, human immunodeficiency virus [HIV] status, tuberculosis infection) were associated with revalent tuberculosis infection (positive tuberculin skin test [TST] result) after adjusting for individual-level risk factors (age, sex, HIV status, tuberculosis contact, wealth, occupation, and Bacillus Calmette-Guérin [BCG] vaccination) with targeted maximum likelihood estimation. RESULTS Among 3 335 residents sampled for TST, 32% had a positive TST results and 4% reported a tuberculosis contact. The social network contained 15 328 first-degree contacts. Persons with the most network centrality (top 10%) (adjusted risk ratio, 1.3 [95% confidence interval, 1.1-1.1]) and the most (top 10%) male contacts (1.5 [1.3-1.9]) had a higher risk of prevalent tuberculosis, than those in the remaining 90%. People with ≥1 contact with HIV (adjusted risk ratio, 1.3 [95% confidence interval, 1.1-1.6]) and ≥2 contacts with tuberculosis infection were more likely to have tuberculosis themselves (2.6 [ 95% confidence interval: 2.2-2.9]). CONCLUSIONS Social networks with higher centrality, more men, contacts with HIV, and tuberculosis infection were positively associated with tuberculosis infection. Tuberculosis transmission within measurable social networks may explain prevalent tuberculosis not associated with a household contact. Further study on network-informed tuberculosis case finding interventions is warranted.
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Affiliation(s)
- Carina Marquez
- Division of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California, San Francisco, California, USA
| | - Yiqun Chen
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | | | - Gabriel Chamie
- Division of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California, San Francisco, California, USA
| | - Laura B Balzer
- Division of Biostatistics, School of Public Health, University of California, Berkeley, Berkeley, California, USA
| | - Joel Kironde
- Infectious Diseases Research Collaboration, Kampala, Uganda
| | | | | | - Jane Kabami
- Infectious Diseases Research Collaboration, Kampala, Uganda
| | | | - Elijah Kakande
- Infectious Diseases Research Collaboration, Kampala, Uganda
| | - Rachel Abbott
- Division of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California, San Francisco, California, USA
| | - Bob Ssekyanzi
- Infectious Diseases Research Collaboration, Kampala, Uganda
| | - Catherine Koss
- Division of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California, San Francisco, California, USA
| | - Moses R Kamya
- Infectious Diseases Research Collaboration, Kampala, Uganda
- School of Medicine, Makerere University College of Health Sciences, Kampala, Uganda
| | - Edwin D Charlebois
- Center for AIDS Prevention Studies, School of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Diane V Havlir
- Division of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California, San Francisco, California, USA
| | - Maya L Petersen
- Division of Biostatistics, School of Public Health, University of California, Berkeley, Berkeley, California, USA
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Yuen CM, Brooks MB, Millones AK, Acosta D, Del Águila-Rojas E, Campos H, Farroñay S, Morales G, Ramirez-Sandoval J, Nichols TC, Jimenez J, Jenkins HE, Lecca L. Geospatial analysis of reported activity locations to identify sites for tuberculosis screening. Sci Rep 2022; 12:14094. [PMID: 35982104 PMCID: PMC9387880 DOI: 10.1038/s41598-022-18456-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 08/11/2022] [Indexed: 11/13/2022] Open
Abstract
Mobile screening units can help close tuberculosis case detection gaps. Placing screening units where people at high risk for undiagnosed tuberculosis preferentially spend time could make screening more resource-effective. We conducted a case–control study in Lima, Peru to identify locations where people with tuberculosis were more likely to spend time than community controls. We surveyed participants about activity locations over the past 6 months. We used density-based clustering to assess how patient and control activity locations differed, and logistic regression to compare location-based exposures. We included 109 tuberculosis patients and 79 controls. In density-based clustering analysis, the two groups had similar patterns of living locations, but their work locations clustered in distinct areas. Both groups were similarly likely to use public transit, but patients predominantly used buses and were less likely to use rapid transit (adjusted odds ratio [aOR] 0.31, 95% confidence interval [CI] 0.10–0.96) or taxis (aOR 0.42, 95% CI 0.21–0.85). Patients were more likely to have spent time in prison (aOR 11.55, 95% CI 1.48–90.13). Placing mobile screening units at bus terminals serving locations where tuberculosis patients have worked and within and around prisons could help reach people with undiagnosed tuberculosis.
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Affiliation(s)
- Courtney M Yuen
- Division of Global Health Equity, Brigham and Women's Hospital, Boston, MA, USA. .,Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA.
| | - Meredith B Brooks
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA
| | | | | | | | | | | | | | | | - Tim C Nichols
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA
| | | | - Helen E Jenkins
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Leonid Lecca
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA.,Socios En Salud Sucursal Peru, Lima, Peru
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Yu W, Alipio C, Wan J, Mane H, Nguyen QC. Social Network Analysis on the Mobility of Three Vulnerable Population Subgroups: Domestic Workers, Flight Crews, and Sailors during the COVID-19 Pandemic in Hong Kong. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19137565. [PMID: 35805223 PMCID: PMC9265614 DOI: 10.3390/ijerph19137565] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 06/12/2022] [Accepted: 06/20/2022] [Indexed: 11/17/2022]
Abstract
Background: Domestic workers, flight crews, and sailors are three vulnerable population subgroups who were required to travel due to occupational demand in Hong Kong during the COVID-19 pandemic. Objective: The aim of this study was to explore the social networks among three vulnerable population subgroups and capture temporal changes in their probability of being exposed to SARS-CoV-2 via mobility. Methods: We included 652 COVID-19 cases and utilized Exponential Random Graph Models to build six social networks: one for the cross-sectional cohort, and five for the temporal wave cohorts, respectively. Vertices were the three vulnerable population subgroups. Edges were shared scenarios where vertices were exposed to SARS-CoV-2. Results: The probability of being exposed to a COVID-19 case in Hong Kong among the three vulnerable population subgroups increased from 3.38% in early 2020 to 5.78% in early 2022. While domestic workers were less mobile intercontinentally compared to flight crews and sailors, domestic workers were 1.81-times in general more likely to be exposed to SARS-CoV-2. Conclusions: Vulnerable populations with similar ages and occupations, especially younger domestic workers and flight crew members, were more likely to be exposed to SARS-CoV-2. Social network analysis can be used to provide critical information on the health risks of infectious diseases to vulnerable populations.
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Affiliation(s)
- Weijun Yu
- Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 20742, USA;
- Correspondence: (W.Y.); (Q.C.N.)
| | - Cheryll Alipio
- Walter H. Shorenstein Asia-Pacific Research Center, Freeman Spogli Institute for International Studies, Stanford University, Stanford, CA 94305, USA;
| | - Jia’an Wan
- Samuel Curtis Johnson Graduate School of Management, Cornell University, Ithaca, NY 14850, USA;
| | - Heran Mane
- Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 20742, USA;
| | - Quynh C. Nguyen
- Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 20742, USA;
- Correspondence: (W.Y.); (Q.C.N.)
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Bui DP, Chandran SS, Oren E, Brown HE, Harris RB, Knight GM, Grandjean L. Community transmission of multidrug-resistant tuberculosis is associated with activity space overlap in Lima, Peru. BMC Infect Dis 2021; 21:275. [PMID: 33736597 PMCID: PMC7977184 DOI: 10.1186/s12879-021-05953-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 02/24/2021] [Indexed: 11/10/2022] Open
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. Supplementary Information The online version contains supplementary material available at 10.1186/s12879-021-05953-8.
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Affiliation(s)
- David P Bui
- Department of Epidemiology and Biostatistics, The University of Arizona, Mel and Enid Zuckerman College of Public Health, 1295 N Martin Ave., Tucson, AZ, 85724, USA
| | - Shruthi S Chandran
- The London School of Hygiene and Tropical Medicine, Keppel Street, London, UK
| | - Eyal Oren
- San Diego State University, School of Public Health, 5500 Campanile Drive, San Diego, California, 92182, USA
| | - Heidi E Brown
- Department of Epidemiology and Biostatistics, The University of Arizona, Mel and Enid Zuckerman College of Public Health, 1295 N Martin Ave., Tucson, AZ, 85724, USA
| | - Robin B Harris
- Department of Epidemiology and Biostatistics, The University of Arizona, Mel and Enid Zuckerman College of Public Health, 1295 N Martin Ave., Tucson, AZ, 85724, USA
| | - Gwenan M Knight
- The London School of Hygiene and Tropical Medicine, Keppel Street, London, UK
| | - Louis Grandjean
- Universidad Peruana Cayetano Heredia, Lima, Peru. .,Institute of Child Health, University College London, 30 Guilford Street, London, UK.
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Cheng B, Behr MA, Howden BP, Cohen T, Lee RS. Reporting practices for genomic epidemiology of tuberculosis: a systematic review of the literature using STROME-ID guidelines as a benchmark. THE LANCET. MICROBE 2021; 2:e115-e129. [PMID: 33842904 PMCID: PMC8034592 DOI: 10.1016/s2666-5247(20)30201-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
BACKGROUND Pathogen genomics have become increasingly important in infectious disease epidemiology and public health. The Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases (STROME-ID) guidelines were developed to outline a minimum set of criteria that should be reported in genomic epidemiology studies to facilitate assessment of study quality. We evaluate such reporting practices, using tuberculosis as an example. METHODS For this systematic review, we initially searched MEDLINE, Embase Classic, and Embase on May 3, 2017, using the search terms "tuberculosis" and "genom* sequencing". We updated this initial search on April 23, 2019, and also included a search of bioRxiv at this time. We included studies in English, French, or Spanish that recruited patients with microbiologically confirmed tuberculosis and used whole genome sequencing for typing of strains. Non-human studies, conference abstracts, and literature reviews were excluded. For each included study, the number and proportion of fulfilled STROME-ID criteria were recorded by two reviewers. A comparison of the mean proportion of fulfilled STROME-ID criteria before and after publication of the STROME-ID guidelines (in 2014) was done using a two-tailed t test. Quasi-Poisson regression and tobit regression were used to examine associations between study characteristics and the number and proportion of fulfilled STROME-ID criteria. This study was registered with PROSPERO, CRD42017064395. FINDINGS 976 titles and abstracts were identified by our primary search, with an additional 16 studies identified in bioRxiv. 114 full texts (published between 2009 and 2019) were eligible for inclusion. The mean proportion of STROME-ID criteria fulfilled was 50% (SD 12; range 16-75). The proportion of criteria fulfilled was similar before and after STROME-ID publication (51% [SD 11] vs 46% [14], p=0·26). The number of criteria reported (among those applicable to all studies) was not associated with impact factor, h-index, country of affiliation of senior author, or sample size of isolates. Similarly, the proportion of criteria fulfilled was not associated with these characteristics, with the exception of a sample size of isolates of 277 or more (the highest quartile). In terms of reproducibility, 100 (88%) studies reported which bioinformatic tools were used, but only 33 (33%) reported corresponding version numbers. Sequencing data were available for 86 (75%) studies. INTERPRETATION The reporting of STROME-ID criteria in genomic epidemiology studies of tuberculosis between 2009 and 2019 was low, with implications for assessment of study quality. The considerable proportion of studies without bioinformatics version numbers or sequencing data available highlights a key concern for reproducibility.
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Affiliation(s)
- Brianna Cheng
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
| | - Marcel A Behr
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
| | - Benjamin P Howden
- The Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia
| | | | - Robyn S Lee
- Epidemiology Division, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
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