Mathematics Institute, University of Warwick, Coventry, United Kingdom.
Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Coventry, United Kingdom.
Clin Infect Dis. 2021 Jun 14;72(Suppl 3):S146-S151. doi: 10.1093/cid/ciab190.
The gambiense human African trypanosomiasis (gHAT) elimination programme in the Democratic Republic of Congo (DRC) routinely collects case data through passive surveillance and active screening, with several regions reporting no cases for several years, despite being endemic in the early 2000s.
We use mathematical models fitted to longitudinal data to estimate the probability that selected administrative regions have already achieved elimination of transmission (EOT) of gHAT. We examine the impact of active screening coverage on the certainty of model estimates for transmission and therefore the role of screening in the measurement of EOT.
In 3 example health zones of Sud-Ubangi province, we find there is a moderate (>40%) probability that EOT has been achieved by 2018, based on 2000-2016 data. Budjala and Mbaya reported zero cases during 2017-18, and this further increases our respective estimates to 99.9% and 99.6% (model S) and to 87.3% and 92.1% (model W). Bominenge had recent case reporting, however, that if zero cases were found in 2021, it would substantially raise our certainty that EOT has been met there (99.0% for model S and 88.5% for model W); this could be higher with 50% coverage screening that year (99.1% for model S and 94.0% for model W).
We demonstrate how routine surveillance data coupled with mechanistic modeling can estimate the likelihood that EOT has already been achieved. Such quantitative assessment will become increasingly important for measuring local achievement of EOT as 2030 approaches.
刚果民主共和国（DRC）的冈比亚人体锥虫病（gHAT）消除计划常规通过被动监测和主动筛查收集病例数据，尽管在 21 世纪初该地区就已流行，但有几个地区已经连续数年没有报告病例。
我们使用拟合纵向数据的数学模型来估计选定行政区域是否已经实现冈比亚锥虫病传播消除（EOT）的概率。我们研究了主动筛查覆盖率对传播模型估计的确定性的影响，以及筛查在 EOT 测量中的作用。
在南乌班吉省的 3 个卫生区中，根据 2000-2016 年的数据，我们发现到 2018 年 EOT 已经实现的概率较高（>40%）。布贾拉和姆巴亚在 2017-18 年期间没有报告任何病例，这进一步提高了我们各自的估计值，分别达到 99.9%和 99.6%（模型 S）和 87.3%和 92.1%（模型 W）。博米纳格最近有病例报告，但如果在 2021 年未发现任何病例，这将大大提高我们对那里 EOT 已经达到的确定性（模型 S 为 99.0%，模型 W 为 88.5%）；如果当年的筛查覆盖率为 50%，这一数字可能会更高（模型 S 为 99.1%，模型 W 为 94.0%）。
我们展示了如何使用常规监测数据和机制模型来估计 EOT 已经实现的可能性。随着 2030 年的临近，这种定量评估将对衡量当地实现 EOT 的情况变得越来越重要。
