Department of Disease Control, London School of Hygiene and Tropical Medicine, London, UK.
Centre for Health Informatics, Computing and Statistics (CHICAS), Lancaster University, Lancaster, UK.
Parasit Vectors. 2020 Nov 18;13(1):555. doi: 10.1186/s13071-020-04413-7.
Schistosomiasis control programmes primarily use school-based surveys to identify areas for mass drug administration of preventive chemotherapy. However, as the spatial distribution of schistosomiasis can be highly focal, transmission may not be detected by surveys implemented at districts or larger spatial units. Improved mapping strategies are required to accurately and cost-effectively target preventive chemotherapy to remaining foci across all possible spatial distributions of schistosomiasis.
Here, we use geostatistical models to quantify the spatial heterogeneity of Schistosoma haematobium and S. mansoni across sub-Saharan Africa using the most comprehensive dataset available on school-based surveys. Applying this information to parameterise simulations, we assess the accuracy and cost of targeting alternative implementation unit sizes across the range of plausible schistosomiasis distributions. We evaluate the consequences of decisions based on survey designs implemented at district and subdistrict levels sampling different numbers of schools. Cost data were obtained from field surveys conducted across multiple countries and years, with cost effectiveness evaluated as the cost per correctly identified school.
Models identified marked differences in prevalence and spatial distributions between countries and species; however, results suggest implementing surveys at subdistrict level increase the accuracy of treatment classifications across most scenarios. While sampling intensively at the subdistrict level resulted in the highest classification accuracy, this sampling strategy resulted in the highest costs. Alternatively, sampling the same numbers of schools currently recommended at the district level but stratifying by subdistrict increased cost effectiveness.
This study provides a new tool to evaluate schistosomiasis survey designs across a range of transmission settings. Results highlight the importance of considering spatial structure when designing sampling strategies, illustrating that a substantial proportion of children may be undertreated even when an implementation unit is correctly classified. Control programmes need to weigh the increased accuracy of more detailed mapping strategies against the survey costs and treatment priorities.
血吸虫病控制规划主要利用基于学校的调查来确定大规模药物治疗预防化疗的地区。然而,由于血吸虫病的空间分布可能高度集中,在地区或更大的空间单位实施的调查可能无法检测到传播。需要改进绘图策略,以便在所有可能的血吸虫病空间分布情况下,准确、经济有效地将预防化疗靶向到剩余的焦点。
在这里,我们使用地质统计学模型,利用关于基于学校的调查的最全面的数据集,量化撒哈拉以南非洲地区的曼氏血吸虫和埃及血吸虫的空间异质性。将这些信息应用于参数化模拟,我们评估了针对替代实施单位大小的准确性和成本,跨越了各种可能的血吸虫病分布。我们评估了基于在不同数量的学校中抽样的区和分区级调查设计做出的决策的后果。成本数据是从多个国家和多年的实地调查中获得的,成本效益作为正确识别的学校的成本来评估。
模型确定了国家和物种之间在流行率和空间分布方面的显著差异;然而,结果表明,在大多数情况下,在分区级实施调查可以提高治疗分类的准确性。虽然在分区级密集抽样导致了最高的分类准确性,但这种抽样策略导致了最高的成本。或者,以同样的数量抽样目前在区一级推荐的学校,但按分区分层,可以提高成本效益。
本研究提供了一种新的工具来评估一系列传播环境下的血吸虫病调查设计。结果强调了在设计抽样策略时考虑空间结构的重要性,表明即使正确分类了实施单位,仍有相当一部分儿童可能得不到充分治疗。控制规划需要权衡更详细的绘图策略的增加准确性与调查成本和治疗重点。