Background: Surveillance is an essential component of global programs to eliminate infectious diseases and avert epidemics of (re-)emerging diseases. As the numbers of cases decline, costs of treatment and control diminish but those for surveillance remain high even after the 'last' case. Reducing surveillance may risk missing persistent or (re-)emerging foci of disease. Here, we use a simulation-based approach to determine the minimal number of passive surveillance sites required to ensure maximum coverage of a population at-risk (PAR) of an infectious disease. Methodology and Principal Findings: For this study, we use Gambian human African trypanosomiasis (g-HAT) in north-western Uganda, a neglected tropical disease (NTD) which has been reduced to historically low levels (<1000 cases/year globally), as an example. To quantify travel time to diagnostic facilities, a proxy for surveillance coverage, we produced a high spatial-resolution resistance surface and performed cost-distance analyses. We simulated travel time for the PAR with different numbers (1-170) and locations (170,000 total placement combinations) of diagnostic facilities, quantifying the percentage of the PAR within 1h and 5h travel of the facilities, as per in-country targets. Our simulations indicate that a 70% reduction (51/170) in diagnostic centres still exceeded minimal targets of coverage even for remote populations, with >95% of a total PAR of ~3million individuals living 1h from a diagnostic centre, and we demonstrate an approach to best place these facilities, informing a minimal impact scale back. Conclusions: Our results highlight that surveillance of g-HAT in north-western Uganda can be scaled back without substantially reducing coverage of the PAR. The methodology described can contribute to cost-effective and equable strategies for the surveillance of NTDs and other infectious diseases approaching elimination or (re-)emergence.

中文翻译：

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在消灭时代优化对被忽视的热带病的被动监测：模型研究

背景：监测是消除传染病和避免（再）新兴疾病流行的全球计划的重要组成部分。随着案件数量的减少，治疗和控制的费用减少，但即使在“最后一个”案件之后，用于监视的费用仍然很高。减少监视可能会冒着遗漏病灶或复发病灶的风险。在这里，我们使用基于模拟的方法来确定确保最大程度覆盖传染病风险人群（PAR）所需的最少数量的被动监视站点。方法和主要发现：在这项研究中，我们使用乌干达西北部的冈比亚人类非洲锥虫病（g-HAT），这是一种被忽视的热带病（NTD），已降低至历史低位（全球<1000例/年），举个例子。为了量化前往诊断机构（作为监视覆盖范围的代理人）的旅行时间，我们制作了高空间分辨率的电阻表面并进行了成本-距离分析。我们模拟了具有不同数量（1-170）和位置（共170,000个诊断设施）的PAR的旅行时间，并根据国家/地区目标量化了设施在1小时和5小时旅行中PAR的百分比。我们的模拟表明，即使对于偏远人群，诊断中心的覆盖率降低了70％（51/170）仍然超出了最低覆盖目标，在约300万人口中，诊断中心居住1h的PAR的> 95％，我们证明了方法以最佳方式放置这些设施，从而使影响最小化。结论：我们的结果表明，在不大幅减少PAR覆盖率的情况下，可以缩减对乌干达西北部g-HAT的监测。所描述的方法可以为监视NTD和其他即将消灭或（重新）出现的传染病提供经济有效且公平的策略。