France Anne Marie, Grant Juliana, Kammerer J Steve, Navin Thomas R
Am J Epidemiol. 2015 Nov 1;182(9):799-807. doi: 10.1093/aje/kwv121. Epub 2015 Oct 13.
Tuberculosis genotyping data are frequently used to estimate the proportion of tuberculosis cases in a population that are attributable to recent transmission (RT). Multiple factors influence genotype-based estimates of RT and limit the comparison of estimates over time and across geographic units. Additionally, methods used for these estimates have not been validated against field-based epidemiologic assessments of RT. Here we describe a novel genotype-based approach to estimation of RT based on the identification of plausible-source cases, which facilitates systematic comparisons over time and across geographic areas. We compared this and other genotype-based RT estimation approaches with the gold standard of field-based assessment of RT based on epidemiologic investigation in Arkansas, Maryland, and Massachusetts during 1996-2000. We calculated the sensitivity and specificity of each approach for epidemiologic evidence of RT and calculated the accuracy of each approach across a range of hypothetical RT prevalence rates plausible for the United States. The sensitivity, specificity, and accuracy of genotype-based RT estimates varied by approach. At an RT prevalence of 10%, accuracy ranged from 88.5% for state-based clustering to 94.4% with our novel approach. Our novel, field-validated approach allows for systematic assessments over time and across public health jurisdictions of varying geographic size, with an established level of accuracy.
结核病基因分型数据经常被用于估计人群中由近期传播(RT)引起的结核病病例比例。多种因素影响基于基因型的RT估计,并限制了不同时间和不同地理区域之间估计值的比较。此外,用于这些估计的方法尚未根据基于现场的RT流行病学评估进行验证。在此,我们描述了一种基于识别可能来源病例的新型基于基因型的RT估计方法,该方法有助于进行跨时间和跨地理区域的系统比较。我们将这种方法和其他基于基因型的RT估计方法与1996 - 2000年期间在阿肯色州、马里兰州和马萨诸塞州基于流行病学调查的现场RT评估的金标准进行了比较。我们计算了每种方法对于RT流行病学证据的敏感性和特异性,并计算了每种方法在美国一系列合理的假设RT流行率下的准确性。基于基因型的RT估计的敏感性、特异性和准确性因方法而异。在RT流行率为10%时,准确性范围从基于州的聚类方法的88.5%到我们的新方法的94.4%。我们经过现场验证的新方法允许在不同地理规模的公共卫生辖区内进行跨时间的系统评估,并具有既定的准确性水平。