TB Hackathon: Development and Comparison of Five Models to Predict Subnational Tuberculosis Prevalence in Pakistan.
TB Hackathon: Development and Comparison of Five Models to Predict Subnational Tuberculosis Prevalence in Pakistan.
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DOI：
10.3390/tropicalmed7010013
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发表时间：
2022-01-17
影响因子：
2.9
通讯作者：
Latif A
中科院分区：
文献类型：
--
作者：
Alba S;Rood E;Mecatti F;Ross JM;Dodd PJ;Chang S;Potgieter M;Bertarelli G;Henry NJ;LeGrand KE;Trouleau W;Shaweno D;MacPherson P;Qin ZZ;Mergenthaler C;Giardina F;Augustijn EW;Baloch AQ;Latif A
巴基斯坦的国家结核病控制规划是世界上许多重视国家以下各级结核病负担估计数对支持疾病控制工作的重要性的规划之一，但没有可靠的估计数。因此，组织了一次黑客会议，征求发展和比较几个模型的小面积估计结核病。TB黑客程序于2019年4月启动。参与小组被要求编制2018年成人（15岁以上）细菌阳性结核病患病率的地区级估计数。NTP提供了2010-2011年结核病患病率调查的病例数据，沿着2010-2011年至2018年期间结核病筛查、检测和治疗的相关数据。五个小组提交了地区一级结核病流行率估计数、方法细节和方案编制代码。尽管结核病患病率的地理分布在不同模型中差异很大，但我们确定了几个报告患病率持续较低的地区。黑客们强调了根据横截面流行率调查数据和其他数据源生成粒度时空结核病流行率预测的挑战。尽管如此，它为国家以下各级疾病建模提供了一系列方法。国家结核控制规划对这些产出的使用和计划表明，尽管存在局限性，但它们对方案规划可能很有价值。
Pakistan’s national tuberculosis control programme (NTP) is among the many programmes worldwide that value the importance of subnational tuberculosis (TB) burden estimates to support disease control efforts, but do not have reliable estimates. A hackathon was thus organised to solicit the development and comparison of several models for small area estimation of TB. The TB hackathon was launched in April 2019. Participating teams were requested to produce district-level estimates of bacteriologically positive TB prevalence among adults (over 15 years of age) for 2018. The NTP provided case-based data from their 2010–2011 TB prevalence survey, along with data relating to TB screening, testing and treatment for the period between 2010–2011 and 2018. Five teams submitted district-level TB prevalence estimates, methodological details and programming code. Although the geographical distribution of TB prevalence varied considerably across models, we identified several districts with consistently low notification-to-prevalence ratios. The hackathon highlighted the challenges of generating granular spatiotemporal TB prevalence forecasts based on a cross-sectional prevalence survey data and other data sources. Nevertheless, it provided a range of approaches to subnational disease modelling. The NTP’s use and plans for these outputs shows that, limitations notwithstanding, they can be valuable for programme planning.
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