Quantification of SARS-CoV-2 in urban wastewaters has emerged as a cheap, efficient strategy to follow trends of active COVID-19 cases in populations. Moreover, mathematical models have been developed that allow the prediction of active cases following the temporal patterns of viral loads in wastewaters. In Mexico, no systematic efforts have been reported in the use of these strategies. In this work, we quantified SARS-CoV-2 in rivers and irrigation canals in the Mezquital Valley, Hidalgo, an agricultural region where wastewater from Mexico City is distributed and used for irrigation. Using quantitative RT-PCR, we detected the virus in six out of eight water samples from rivers and five out of eight water samples from irrigation canals. Notably, samples showed a general consistent trend of having the highest viral loads in the sites closer to Mexico City, indicating that this is the main source that contributes to detection. Using the data for SARS-CoV-2 concentration in the river samples, we generated a simplified transport model that describes the spatial patterns of dispersion of virus in the river. We suggest that this model can be extrapolated to other wastewater systems where knowledge of spatial patterns of viral dispersion, at a geographic scale, is required. Our work highlights the need for improved practices and policies related to the use of wastewater for irrigation in Mexico and other countries.

城市废水中 SARS-CoV-2 的定量已成为追踪人群中活跃的 COVID-19 病例趋势的一种廉价、有效的策略。此外，已经开发出数学模型，可以根据废水中病毒载量的时间模式来预测活跃病例。在墨西哥，尚未有关于使用这些策略的系统性努力的报告。在这项工作中，我们对伊达尔戈州梅斯基塔尔谷的河流和灌溉渠中的 SARS-CoV-2 进行了定量，该地区是一个农业区，墨西哥城的废水被分配并用于灌溉。使用定量 RT-PCR，我们在河流的八分之六和灌溉渠的八分之五的水样中检测到了该病毒。值得注意的是，样本显示出在靠近墨西哥城的地点病毒载量最高的总体趋势，表明这是有助于检测的主要来源。利用河流样本中 SARS-CoV-2 浓度的数据，我们生成了一个简化的传输模型，该模型描述了病毒在河流中传播的空间模式。我们建议该模型可以外推到其他废水系统，这些系统需要了解地理范围内病毒传播的空间模式。我们的工作强调需要改进墨西哥和其他国家与废水灌溉相关的做法和政策。