Combining molecular typing and spatial pattern analysis to identify areas of high tuberculosis transmission in a moderate-incidence county in Taiwan

Chen, Yih Yuan; Chang, Jia Ru; Wu, Chih-Da; Yeh, Yen-Po; Yang, Shiu Ju; Hsu, Chih Hao; Lin, Ming Ching; Tsai, Ching Fang; Lin, Mingxiang; Su, Ih Jen; Dou, Horng-Yunn

doi:10.1038/s41598-017-05674-6

Cited by 5 publications

(4 citation statements)

References 29 publications

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“…The primersNTF-5ʹ-CCAGATATCGGGTGTGTCGACandNTF-3ʹ-TGCCGTTCTCGAAATCTAAACAA were designed based on the NTF (nuclear transcription factor) region of M. tuberculosis . 19 The strain was defined as “modern-type” in the presence of the IS6110 insertion or “ancient type” in the absence of theIS6110 insertion according to a previous report. 20 …”

Section: Methodsmentioning

confidence: 99%

Pyrazinamide Resistance and Mutation Patterns Among Multidrug-Resistant Mycobacterium tuberculosis from Henan Province

Shi¹,

Su²,

Zheng³

et al. 2020

IDR

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This study was designed to identify the phenotypic and genotypic characteristics of pyrazinamide (PZA) resistance among multidrug-resistant Mycobacterium tuberculosis (MDR-TB) from Henan and to evaluate the efficacy of pncA, rpsA, and panD mutations in predicting PZA resistance. Materials and Methods: A total of 152 MDR strains were included in this study. The Bactec MGIT system was used to determine PZA susceptibility for all strains. The pncA, rpsA, and panD genes were sequenced to identify any mutations, and the sequences were then aligned with the sequence of standard strain H37Rv. Moreover, the correlations between PZA-resistant phenotypes and treatment outcomes were analysed. Results: Of the152 strains, 105 had a PZA-resistant phenotype, and 102 harboured the pncA mutation. The PZA resistance rate was higher in the strains with resistance to all four firstline drugs and those that were pre-extensively drug-resistant (pre-XDR) and extensively drug-resistant (XDR). A total of 100 different pncA mutation patterns were identified, including 80 point mutations and 20 insertions/deletions, and 32 new pncA mutation patterns were detected. In this study, 13 strains had multiple mutations. Of the11 PZA-resistant strains without pncA mutations, two harboured the rpsA mutation, and one harboured the panD mutation. With PZA susceptibility results as the reference, single-gene pncA sequencing had sensitivity of 89.52% and specificity of 89.36%. With the combination of rpsA and panD, the sensitivity increased to 92.38%, and the specificity remained the same. No significant differences were observed in the sputum smear/culture conversion rate between PZAresistant patients and PZA-sensitive patients. However, PZA resistance was related to the time to sputum smear/culture conversion (P = 0.018). Conclusion: The combination of pncA, rpsA, and panD was beneficial for the timely diagnosis of PZA resistance and could provide a laboratory basis for customizing treatment regimens for MDR-TB patients.

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Section: Methodsmentioning

confidence: 99%

Pyrazinamide Resistance and Mutation Patterns Among Multidrug-Resistant Mycobacterium tuberculosis from Henan Province

Shi¹,

Su²,

Zheng³

et al. 2020

IDR

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“…2,3,4,5 Recently, several studies have found significant association between TB and spatial factors. 6,7,8,9 However, most studies investigating risk factors for TB have separately analyzed epidemiological and spatial factors using different designs, which made it impossible to assess their respective effects by controlling the effects of the other factors.…”

mentioning

confidence: 99%

Epidemiological and spatial factors for tuberculosis: a matched case-control study in Nagata, Japan

Murakami

Matsuo²,

Ueda³

et al. 2019

int j tuberc lung dis

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A hospital-based case-control study using medical records was conducted. In total, 103 TB patients as a case were collected and 299 patients without TB as a control in which age and sex were matched with each case sampled from January 2000 to December 2016 at the targeted hospital in Nagata, Kobe, Japan. Logistic regression, kernel density estimation, Cross-L function and Poisson regression model were applied. RESULTS: Epidemiological factors associated with TB were healthcare workers (OR: 10.1) and lower serum albumin levels (OR: 0.5). Spatial analyses found that TB was positively associated with population density (RR: 32.1), the proportion of single households (RR:-1.85) and person 65 years of age and higher (RR: 2.65), and one spatial clustering. CONCLUSION: These findings could identify high-risk individuals and districts for TB. TB control combined with spatial analysis provided useful information for the assessment of the important factors.

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“…Using various spatial statistical methods, previous research confirmed that the risk of TB transmission is spatially heterogeneous. These methods included Moran’s I and spatial panel data models [ 16 ], Kernel density estimation [ 17 ], spatial regression models [ 18 ] and geographically weighted regression models [ 19 ]. However, as these studies analysed only spatial aspects of TB transmission, they cannot reveal spatio-temporal variation in TB incidence and risk determinants of the disease in regions with unbalanced socio-economic development.…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal variation in tuberculosis incidence and risk factors for the disease in a region of unbalanced socio-economic development

Wang

et al. 2021

BMC Public Health

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Background Previous research pointed to a close relationship between the incidence of tuberculosis (TB) in aging populations and socio-economic conditions, however there has been lack of studies focused on a region of unbalanced socio-economic development. The aim of this paper is to explore the spatio-temporal variation in TB incidence and examine risk determinants of the disease among aging populations in a typical region. Methods Data on TB-registered cases between 2009 and 2014, in addition to social-economic factors, were collected for each district/county in Beijing, Tianjin and Hebei, a region characterized by an aging population and disparities in social-economic development. A Bayesian space–time hierarchy model (BSTHM) was used to reveal spatio-temporal variation in the incidence of TB among the elderly in this region between 2009 to 2014. GeoDetector was applied to measure the determinant power (q statistic) of risk factors for TB among the elderly. Results The incidence of TB among the elderly exhibited geographical spatial heterogeneity, with a higher incidence in underdeveloped rural areas compared with that in urban areas. Hotspots of TB incidence risk among the elderly were mostly located in north-eastern and southern areas in the study region, far from metropolitan areas. Areas with low risk were distributed mainly in the Beijing-Tianjin metropolitan areas. Social-economic factors had a non-linear influence on elderly TB incidence, with the dominant factors among rural populations being income (q = 0.20) and medical conditions (q = 0.17). These factors had a non-linear interactive effect on the incidence of TB among the elderly, with medical conditions and the level of economic development having the strongest effect (q = 0.54). Conclusions The findings explain spatio-temporal variation in TB incidence and risk determinants of elderly TB in the presence of disparities in social-economic development. High-risk zones were located mainly in rural areas, far from metropolitan centres. Medical conditions and the economic development level were significantly associated with elderly TB incidence, and these factors had a non-linear interactive effect on elderly TB incidence. The findings can help to optimize the allocation of health resources and to control TB transmission in the aging population in this region.

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Combining molecular typing and spatial pattern analysis to identify areas of high tuberculosis transmission in a moderate-incidence county in Taiwan

Cited by 5 publications

References 29 publications

<p>Pyrazinamide Resistance and Mutation Patterns Among Multidrug-Resistant <em>Mycobacterium tuberculosis</em> from Henan Province</p>

<p>Pyrazinamide Resistance and Mutation Patterns Among Multidrug-Resistant <em>Mycobacterium tuberculosis</em> from Henan Province</p>

Epidemiological and spatial factors for tuberculosis: a matched case-control study in Nagata, Japan

Spatio-temporal variation in tuberculosis incidence and risk factors for the disease in a region of unbalanced socio-economic development

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