Alene Kefyalew Addis, Xu Zuhui, Bai Liqiong, Yi Hengzhong, Tan Yunhong, Gray Darren, Viney Kerri, Clements Archie Ca
Faculty of Health Sciences, Curtin University, Bentley, Western Australia, Australia
Telethon Kids Institute, Nedlands, Western Australia, Australia.
BMJ Open. 2021 Apr 1;11(4):e043685. doi: 10.1136/bmjopen-2020-043685.
This study aimed to investigate the spatial distribution of drug-resistant tuberculosis (DR-TB) in Hunan province, China.
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.
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.
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.
本研究旨在调查中国湖南省耐多药结核病（DR-TB）的空间分布情况。
采用生态研究方法，利用2012年至2018年期间从湖南省结核病防治所收集的耐多药结核病数据。使用Getis-Ord统计量探索耐多药结核病的空间聚集性。采用具有条件自回归先验结构的泊松回归模型，并使用贝叶斯马尔可夫链蒙特卡罗模拟估计后验参数，以量化与可能的危险因素的关联并识别耐多药结核病高风险聚集区。
2012年至2018年期间，湖南省结核病防治所共报告了2649例耐多药结核病患者。大多数患者为男性（74.8%，n = 1983），并有结核病治疗史（88.53%，n = 2345）。所有耐多药结核病患者中广泛耐药结核病的比例为3.3%（95%CI 2.7%至4.1%），从2012年的2.8%增至2018年的4.4%。在1287例有登记治疗结果的耐多药结核病患者中，434例（33.8%）治愈，198例（15.3%）完成治疗，92例（7.1%）死亡，108例（8.3%）治疗失败，455例（35.3%）失访。一半（50.9%，n = 655）患者治疗结果不佳。报告的耐多药结核病的年累积发病率随时间从2012年的每10万人0.25例增至2018年的每10万人0.83例。观察到明显的空间异质性，在湖南省北部和东部的县检测到热点地区。报告的耐多药结核病的累积发病率与城市社区显著相关。
湖南省报告的耐多药结核病年发病率随时间增加。检测到耐多药结核病的空间聚集性，且与城市化显著相关。这一发现表明，针对最高风险地区和人群开展干预措施将有效减轻耐多药结核病的负担并减少其持续传播。
