Globally, there are over 1 billion people infected with soil-transmitted helminths (STHs), mostly living in marginalized settings with inadequate sanitation in sub-Saharan Africa and Southeast Asia. The World Health Organization recommends an integrated approach to STH morbidity control through improved access to sanitation and hygiene education and the delivery of preventive chemotherapy (PC) to school-age children delivered through schools. Progress of STH control programs is currently estimated using a baseline (pre-PC) school-based prevalence survey and then monitored using periodical school-based prevalence surveys, known as Impact Assessment Surveys (IAS). We investigated whether integrating geostatistical methods with a Markov model or a mechanistic transmission model for projecting prevalence forward in time from baseline can improve IAS design strategies. To do this, we applied these 2 methods to prevalence data collected in Kenya, before evaluating and comparing their performance in accurately informing optimal survey design for a range of IAS sampling designs. We found that, although both approaches performed well, the mechanistic method more accurately projected prevalence over time and provided more accurate information for guiding survey design. Both methods performed less well in areas with persistent STH hotspots where prevalence did not decrease despite multiple rounds of PC. Our findings show that these methods can be useful tools for more efficient and accurate targeting of PC. The general framework built in this paper can also be used for projecting prevalence and informing survey design for other neglected tropical diseases.

中文翻译：

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调查设计背景下土源性蠕虫患病率预测的马尔可夫模型和机制模型的比较

全球有超过 10 亿人感染土源性蠕虫 (STH)，他们大多生活在撒哈拉以南非洲和东南亚卫生条件不足的边缘化环境中。世界卫生组织建议采取综合方法来控制 STH 发病率，通过改善环境卫生和个人卫生教育以及通过学校向学龄儿童提供预防性化疗 (PC) 来实现。目前，STH 控制计划的进展是使用基线（前 PC）学校流行率调查来估计的，然后使用定期的学校流行率调查（称为影响评估调查（IAS））进行监测。我们研究了将地统计方法与马尔可夫模型或机械传播模型相结合以从基线及时预测患病率是否可以改进 IAS 设计策略。为此，我们将这两种方法应用于在肯尼亚收集的流行率数据，然后评估和比较它们在准确告知一系列 IAS 抽样设计的最佳调查设计方面的表现。我们发现，尽管两种方法都表现良好，但机械方法可以更准确地预测随时间变化的患病率，并为指导调​​查设计提供更准确的信息。这两种方法在 STH 热点持续存在的地区表现较差，尽管进行了多轮 PC，患病率并未下降。我们的研究结果表明，这些方法可以成为更有效、更准确地定位 PC 的有用工具。本文构建的总体框架还可用于预测其他被忽视的热带病的患病率并为调查设计提供信息。