Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA.
Analytics, Intelligence and Technology Division, Los Alamos National Laboratory, Los Alamos, NM, USA.
Proc Biol Sci. 2024 Mar 27;291(2019):20232805. doi: 10.1098/rspb.2023.2805. Epub 2024 Mar 20.
Cholera continues to be a global health threat. Understanding how cholera spreads between locations is fundamental to the rational, evidence-based design of intervention and control efforts. Traditionally, cholera transmission models have used cholera case-count data. More recently, whole-genome sequence data have qualitatively described cholera transmission. Integrating these data streams may provide much more accurate models of cholera spread; however, no systematic analyses have been performed so far to compare traditional case-count models to the phylodynamic models from genomic data for cholera transmission. Here, we use high-fidelity case-count and whole-genome sequencing data from the 1991 to 1998 cholera epidemic in Argentina to directly compare the epidemiological model parameters estimated from these two data sources. We find that phylodynamic methods applied to cholera genomics data provide comparable estimates that are in line with established methods. Our methodology represents a critical step in building a framework for integrating case-count and genomic data sources for cholera epidemiology and other bacterial pathogens.
霍乱仍然是全球卫生威胁。了解霍乱在不同地点之间的传播方式对于合理、基于证据的干预和控制措施的设计至关重要。传统上，霍乱传播模型使用霍乱病例数数据。最近，全基因组序列数据已经定性地描述了霍乱的传播。整合这些数据流可能会提供更准确的霍乱传播模型；然而，到目前为止，还没有进行系统分析来比较传统的病例计数模型与基于基因组数据的霍乱传播系统发育模型。在这里，我们使用来自 1991 年至 1998 年阿根廷霍乱流行的高保真病例计数和全基因组测序数据，直接比较从这两个数据源估计的流行病学模型参数。我们发现，应用于霍乱基因组学数据的系统发育方法提供了可比的估计值，与既定方法一致。我们的方法代表了为霍乱流行病学和其他细菌病原体建立整合病例计数和基因组数据源框架的关键步骤。
