Background Lymphatic filariasis (LF) is a debilitating, poverty-promoting, neglected tropical disease (NTD) targeted for worldwide elimination as a public health problem (EPHP) by 2030. Evaluating progress towards this target for national programmes is challenging, due to differences in disease transmission and interventions at the subnational level. Mathematical models can help address these challenges by capturing spatial heterogeneities and evaluating progress towards LF elimination and how different interventions could be leveraged to achieve elimination by 2030. Methods Here we used a novel approach to combine historical geo-spatial disease prevalence maps of LF in Ethiopia with 3 contemporary disease transmission models to project trends in infection under different intervention scenarios at subnational level. Results Our findings show that local context, particularly the coverage of interventions, is an important determinant for the success of control and elimination programmes. Furthermore, although current strategies seem sufficient to achieve LF elimination by 2030, some areas may benefit from the implementation of alternative strategies, such as using enhanced coverage or increased frequency, to accelerate progress towards the 2030 targets. Conclusions The combination of geospatial disease prevalence maps of LF with transmission models and intervention histories enables the projection of trends in infection at the subnational level under different control scenarios in Ethiopia. This approach, which adapts transmission models to local settings, may be useful to inform the design of optimal interventions at the subnational level in other LF endemic regions.

中文翻译：

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埃塞俄比亚地方各级淋巴丝虫病消除目标预测，以支持国家一级政策

背景 淋巴丝虫病 (LF) 是一种使人衰弱、促进贫困、被忽视的热带病 (NTD)，目标是到 2030 年作为公共卫生问题 (EPHP) 在全球范围内消除。由于各国计划的差异，评估国家计划实现这一目标的进展具有挑战性。国家以下各级的疾病传播和干预措施。数学模型可以通过捕获空间异质性并评估消除 LF 的进展以及如何利用不同的干预措施在 2030 年前实现消除 LF 来帮助应对这些挑战。方法在这里，我们使用了一种新颖的方法来结合埃塞俄比亚 LF 的历史地理空间疾病患病率地图使用 3 种当代疾病传播模型来预测国家以下各级不同干预方案下的感染趋势。结果 我们的研究结果表明，当地情况，特别是干预措施的覆盖范围，是控制和消除计划成功的重要决定因素。此外，尽管目前的战略似乎足以在 2030 年之前消除低频，但某些领域可能会受益于替代战略的实施，例如扩大覆盖范围或增加频率，以加快实现 2030 年目标的进展。结论 将 LF 地理空间疾病患病率图与传播模型和干预历史相结合，能够预测埃塞俄比亚不同控制方案下国家以下各级的感染趋势。这种方法使传播模型适应当地环境，可能有助于为其他LF流行地区在国家以下一级设计最佳干预措施提供信息。