Seroepidemiology of trachoma for the elimination endgame

由眼部沙眼衣原体感染引起的沙眼是导致失明的主要感染性原因。 在全球范围内，并被作为一个公共卫生问题在2030年前作为全球消除的目标。当我们接近 最终，人们对使用血清学调查来支持控制计划有广泛的兴趣。免疫球蛋白抗体 儿童对沙眼衣原体的反应使人群水平能够准确评估沙眼地方性 因为它们结合了随着时间的推移而暴露的情况，并反映了最近的传播。经过多年的化验开发， 该领域的一个关键空白是将用于沙眼血清学调查的流行病学方法正规化。 我们的总体目标是改进用于沙眼血清学设计和分析的方法。 调查。我们将汇集一个大型的、当代的全球沙眼血清学数据集， 地方性，与临床症状和感染的分子指标(&gt；100,000份血液样本在 2010-2024年的19项研究)。目标1将开发强大的方法将抗体反应转化为群体- 衡量从流行环境到消灭后传播的水平。我们假设随着人口的增加 接近消除年龄-血清阳性率曲线将持平和血清转换率，衡量力量 感染，将接近于零。我们将半参数估计年龄-血清阳性率曲线，并推导出 从曲线中汇总衡量标准(例如，血清阳性率、感染力)。我们将比较血清学 不同地方性种群之间的措施。我们进一步假设不同的血清学 汇总指标(平均免疫球蛋白水平、血清阳性率、感染力)将提供类似的信息 传播中的异质性。我们将对血清检测方法进行相互比较，并将其与单独的 从村庄到地区不同地理尺度的沙眼测量(聚合酶链式反应感染、临床体征)。目标2 将确定基于模型的地统计学是否提高了血清学调查设计的效率，并使 随着人口接近消灭，控制计划的规模目标。我们假设这是沙眼 接近消除，它将成为更多的焦点，随着儿童血清阳性率升高的“热点” 这一规模从地区到个别村庄都在缩小。我们假设，如果调查说明了这一点 空间结构在他们的设计中，他们将比仅仅随机抽样更有效地监测沙眼，并且 使用空间预测在较小的空间尺度上做出治疗决定的控制程序可能会 狭隘地瞄准抗生素的分配。在对11项地理参考研究的分析中，这些研究跨越了一系列特有的地区， 我们将把地理空间设计的最新进展应用于沙眼血清学，并比较患病率估计。 将新方法与当前标准的、基于总体的随机样本一起使用。我们试图找出 最有效的抽样策略，在人口接近灭绝时为决策提供信息，并进行研究 使用空间预测在更精细的空间尺度上靶向阿奇霉素的影响。完成这些目标 将导致用于支持沙眼终末期的血清流行病学方法的重大进展。

Trachoma, caused by ocular Chlamydia trachomatis infection, is the leading infectious cause of blindness worldwide and been targeted for global elimination as a public health problem by 2030. As we approach the endgame, there is broad interest in the use of serologic surveys to support control programs. IgG antibody responses to C. trachomatis in children enable accurate population-level assessments of trachoma endemicity because they integrate exposure over time and reflect recent transmission. After years of assay development, a key gap in the field is to formalize the epidemiologic methods used for trachoma serology surveys. Our overall objective is to advance the methods used for the design and analysis of trachoma serology surveys. We will assemble a large, contemporary global dataset for trachoma serology across a gradient of endemicity, paired with clinical signs and molecular measures of infection (>100,000 blood specimens tested in 19 studies from 2010-2024). Aim 1 will develop robust methods to translate antibody response into population- level measures of transmission from endemic settings to post-elimination. We hypothesize that as populations approach elimination age-seroprevalence curves will flatten and seroconversion rates, a measure of force of infection, will approach zero. We will estimate age-seroprevalence curves semi-parametrically, and derive summary measures from the curves (e.g., seroprevalence, force of infection). We will compare serologic measures between populations of different endemicity. We further hypothesize that different serologic summary measures (mean IgG levels, seroprevalence, force of infection) will provide similar information about heterogeneity in transmission. We will compare serologic measures with one-another and with separate measures of trachoma (PCR infection, clinical signs) across geographic scales from villages to districts. Aim 2 will determine if model-based geostatistics improve the efficiency of serological survey design and enable finer scale targeting of control programs as populations approach elimination. We hypothesize that as trachoma approaches elimination, it will become more focal with “hotspots” of elevated seroprevalence among children that shrink in scale from districts down to individual villages. We hypothesize that if surveys account for this spatial structure in their design they will more efficiently monitor trachoma than random samples alone, and control programs that use spatial predictions to make treatment decisions at smaller spatial scales could more narrowly target antibiotic distribution. In analyses of 11 georeferenced studies that span a range of endemicity, we will apply recent advances in geospatial design to trachoma serology and compare prevalence estimates using the new approach with the current standard, population-based random samples. We seek to identify the most efficient sampling strategies to inform decision making as populations approach elimination, and to study the impact of using spatial predictions to target azithromycin at finer spatial scales. Completion of these aims will lead to significant advances in the seroepidemiologic methods used to support the trachoma endgame.