Department CB, University of Applied Sciences Mittweida, Mittweida, Germany.
PLoS One. 2018 Apr 9;13(4):e0194148. doi: 10.1371/journal.pone.0194148. eCollection 2018.
Reliable measures of transmission intensities can be incorporated into metrics for monitoring disease-control interventions. Genetic (molecular) measures like multiplicity of infection (MOI) have several advantages compared with traditional measures, e.g., R0. Here, we investigate the properties of a maximum-likelihood approach to estimate MOI and pathogen-lineage frequencies. By verifying regulatory conditions, we prove asymptotical unbiasedness, consistency and efficiency of the estimator. Finite sample properties concerning bias and variance are evaluated over a comprehensive parameter range by a systematic simulation study. Moreover, the estimator's sensitivity to model violations is studied. The estimator performs well for realistic sample sizes and parameter ranges. In particular, the lineage-frequency estimates are almost unbiased independently of sample size. The MOI estimate's bias vanishes with increasing sample size, but might be substantial if sample size is too small. The estimator's variance matrix agrees well with the Cramér-Rao lower bound, even for small sample size. The numerical and analytical results of this study can be used for study design. This is exemplified by a malaria data set from Venezuela. It is shown how the results can be used to determine the necessary sample size to achieve certain performance goals. An implementation of the likelihood method and a simulation algorithm for study design, implemented as an R script, is available as S1 File alongside a documentation (S2 File) and example data (S3 File).
可靠的传播强度测量方法可以纳入疾病控制干预措施的监测指标。与传统指标相比，遗传（分子）指标如感染复数（MOI）具有多个优势，例如 R0。在这里，我们研究了一种用于估计 MOI 和病原体谱系频率的最大似然估计方法的特性。通过验证监管条件，我们证明了估计量的渐近无偏性、一致性和有效性。通过系统的模拟研究，在全面的参数范围内评估了有限样本属性关于偏差和方差的问题。此外，还研究了估计器对模型违反情况的敏感性。对于实际的样本量和参数范围，该估计器表现良好。特别是，谱系频率估计几乎没有偏差，与样本量无关。随着样本量的增加，MOI 估计的偏差会消失，但如果样本量太小，偏差可能会很大。估计器的方差矩阵与克拉美-罗下限非常吻合，即使对于小样本量也是如此。本研究的数值和分析结果可用于研究设计。委内瑞拉的疟疾数据集就是一个很好的例子。展示了如何使用这些结果来确定达到特定性能目标所需的样本量。一个实现似然方法的 R 脚本和一个用于研究设计的模拟算法作为 S1 文件提供，同时还提供了文档（S2 文件）和示例数据（S3 文件）。
