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阿尔及利亚结核病的时空分析和季节性。

Spatiotemporal analysis and seasonality of tuberculosis in Algeria.

机构信息

L'IFORCE, IFORCE, Faculty of Mathematics, University of Sciences and Technology Houari Boumediene, Algiers, Algeria.

Beni Messous University Hospital Centre, Ministry of Health, Population and Hospital Reform, Algiers, Algeria.

出版信息

Int J Mycobacteriol. 2021 Jul-Sep;10(3):234-242. doi: 10.4103/ijmy.ijmy_111_21.

DOI:10.4103/ijmy.ijmy_111_21
PMID:34494561
Abstract

BACKGROUND

This study aimed to describe the spatiotemporal distribution, to build a forecasting model, and to determine the seasonal pattern of tuberculosis (TB) in Algeria.

METHODS

The Box-Jenkins methodology was used to develop predictive models and GeoDa software was used to perform spatial autocorrelation.

RESULTS

Between 1982 and 2019, the notification rate per 100,000 population of smear-positive pulmonary TB (SPPTB) has dropped 62.2%, while that of extrapulmonary TB (EPTB) has risen 91.3%. For the last decade, the mean detection rate of PTB was 82.6%. At around, 2% of PTB cases were yearly reported in children under 15 years old, a peak in notification rate was observed in the elderly aged 65 and over, and the sex ratio was in favor of men. Between 52% and 59% of EPTB cases were lymphadenitis TB and between 15% and 23% were pleural TB. About two-third of EPTB cases were females and around 10% were children under the age of 15. The time series analysis showed that (1,1, 2) × (1, 1, 0)4 (respectively (0, 1, 2) × (1, 1, 0)4, (3, 1, 0) × (1, 1, 0)4) offered the best forecasting model to quarterly TB (respectively EPTB, SPPTB) surveillance data. The most hit part was the Tell followed by high plateaus which accounted for 96.6% of notifications in 2017. Significant hot spots were identified in the central part for EPTB notification rate and in the northwestern part for SPPTB.

CONCLUSIONS

There is a need to reframe the set objectives in the state strategy to combat TB taking into account seasonality and spatial clustering to ensure improved TB management through targeted and effective interventions.

摘要

背景

本研究旨在描述结核病(TB)在阿尔及利亚的时空分布,建立预测模型,并确定其季节性模式。

方法

采用 Box-Jenkins 方法建立预测模型,并使用 GeoDa 软件进行空间自相关分析。

结果

1982 年至 2019 年间,每 10 万人中涂阳肺结核(SPPTB)的发病率下降了 62.2%,而肺外结核(EPTB)的发病率上升了 91.3%。过去十年中,PTB 的平均检出率为 82.6%。每年约有 2%的 PTB 病例发生在 15 岁以下儿童中,老年人(65 岁及以上)的发病率达到高峰,男女比例有利于男性。EPTB 病例中约有 52%-59%为淋巴结结核,15%-23%为胸膜炎结核。约 2/3 的 EPTB 病例为女性,约 10%为 15 岁以下儿童。时间序列分析表明,(1,1,2)×(1,1,0)4(分别为(0,1,2)×(1,1,0)4,(3,1,0)×(1,1,0)4)为季度 TB(分别为 EPTB、SPPTB)监测数据提供了最佳预测模型。发病率最高的地区是提济乌祖省,其次是高原地区,这两个地区在 2017 年的报告发病率占比达到 96.6%。EPTB 发病率的热点区域位于中部,SPPTB 发病率的热点区域位于西北部。

结论

有必要根据季节性和空间聚类重新制定国家结核病防治战略的目标,以确保通过有针对性和有效的干预措施改善结核病管理。

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