PDF(Sci-hub)
Abstract：
Fecal source tracking (FST) may be useful to assess pathways of fecal contamination in domestic environments and to estimate the impacts of water, sanitation, and hygiene (WASH) interventions in low-income settings. We measured two nonspecific and two human-associated fecal indicators in water, soil, and surfaces before and after a shared latrine intervention from low-income households in Maputo, Mozambique, participating in the Maputo Sanitation (MapSan) trial. Up to a quarter of households were impacted by human fecal contamination, but trends were unaffected by improvements to shared sanitation facilities. The intervention reduced Escherichia coli gene concentrations in soil but did not impact culturable E. coli or the prevalence of human FST markers in a difference-in-differences analysis. Using a novel Bayesian hierarchical modeling approach to account for human marker diagnostic sensitivity and specificity, we revealed a high amount of uncertainty associated with human FST measurements and intervention effect estimates. The field of microbial source tracking would benefit from adding measures of diagnostic accuracy to better interpret findings, particularly when FST analyses convey insufficient information for robust inference. With improved measures, FST could help identify dominant pathways of human and animal fecal contamination in communities and guide the implementation of effective interventions to safeguard health.
摘要：
粪便源跟踪（FST）可能有助于评估家庭环境中粪便污染的途径并评估水的影响。卫生，和低收入环境中的卫生（WASH）干预措施。我们测量了水中两种非特异性和两种与人类相关的粪便指标，土壤,在马普托低收入家庭共同干预厕所前后浮出水面，莫桑比克,参加马普托卫生（MapSan）试验。多达四分之一的家庭受到人类粪便污染的影响，但是趋势不受共享卫生设施改善的影响。在差异差异分析中，干预措施降低了土壤中大肠杆菌的基因浓度，但不影响可培养的大肠杆菌或人类FST标记的流行。使用一种新的贝叶斯分层建模方法来解释人类标记诊断的敏感性和特异性，我们揭示了与人类FST测量和干预效果估计相关的大量不确定性.微生物源跟踪领域将受益于增加诊断准确性的措施，以更好地解释发现，特别是当FST分析传达的信息不足以进行稳健推理时。通过改进措施，FST可以帮助确定社区中人类和动物粪便污染的主要途径，并指导实施有效的干预措施以维护健康。
