Maree Gillian, Els Fiona, Naidoo Yashena, Naidoo Laven, Mahamuza Phemelo, Macheke Mokgaetji, Ndlovu Nkosenhle, Rachida Said, Iwu-Jaja Chinwe, Taukobong Setshaba, Maposa Sibonginkosi, O'Reilly Kathleen, Yousif Mukhlid, McCarthy Kerrigan
Gauteng City-Region Observatory (GCRO), a Partnership of the University of Johannesburg, the University of the Witwatersrand, the Gauteng Provincial Government and Organised Local Government in Gauteng (SALGA), Johannesburg, Gauteng, South Africa.
Centre for Vaccines and Immunology, National Institute for Communicable Diseases, Johannesburg, Gauteng, South Africa.
PLoS One. 2025 Feb 25;20(2):e0311332. doi: 10.1371/journal.pone.0311332. eCollection 2025.
Wastewater and environmental surveillance has been promoted as a communicable disease surveillance tool because it overcomes inherent biases in laboratory-based communicable disease surveillance. Yet, little empirical evidence exists to support this notion, and it remains largely an intuitive, though highly plausible hypothesis. Our interdisciplinary study uses WES data to show evidence for underreporting of SARS-CoV-2 in the context of measurable and statistically significant associations between economic conditions and SARS-CoV-2 incidence and testing rates. We obtained geolocated, anonymised, laboratory-confirmed SARS-CoV-2 cases, wastewater SARS-CoV-2 viral load data and socio-demographic data for Gauteng Province, South Africa. We spatially located all data to create a single dataset for sewershed catchments served by two large wastewater treatment plants. We conducted epidemiological, persons infected and principal component analysis to explore the relationships between variables. Overall, we demonstrate the co-contributory influences of socio-economic indicators on access to SARS-CoV-2 testing and cumulative incidence, thus reflecting that apparent incidence rates mirror access to testing and socioeconomic considerations rather than true disease epidemiology. These analyses demonstrate how WES provides valuable information to contextualise and interpret laboratory-based epidemiological data. Whilst it is useful to have these associations established for SARS-CoV-2, the implications beyond SARS-CoV-2 are legion for two reasons, namely that biases inherent in clinical surveillance are broadly applicable across pathogens and all pathogens infecting humans will find their way into wastewater albeit in varying quantities. WES should be implemented to strengthen surveillance systems, especially where economic inequalities limit interpretability of conventional surveillance data.
废水和环境监测已被推广为一种传染病监测工具，因为它克服了基于实验室的传染病监测中固有的偏差。然而，几乎没有实证证据支持这一观点，它在很大程度上仍然是一个直观但看似合理的假设。我们的跨学科研究使用废水和环境监测（WES）数据来证明，在经济状况与新冠病毒（SARS-CoV-2）发病率和检测率之间存在可测量且具有统计学意义的关联的背景下，新冠病毒存在报告不足的情况。我们获取了南非豪登省地理位置明确、匿名且经实验室确认的新冠病毒病例、废水新冠病毒病毒载量数据以及社会人口统计学数据。我们将所有数据进行空间定位，以创建一个由两家大型污水处理厂服务的排水流域集水区的单一数据集。我们进行了流行病学、感染人数和主成分分析，以探索变量之间的关系。总体而言，我们证明了社会经济指标对新冠病毒检测机会和累计发病率的共同影响，从而反映出表观发病率反映的是检测机会和社会经济因素，而非真正的疾病流行病学。这些分析表明了废水和环境监测如何提供有价值的信息来背景化和解释基于实验室的流行病学数据。虽然为新冠病毒建立这些关联很有用，但新冠病毒之外的影响众多，原因有二，即临床监测中固有的偏差广泛适用于各种病原体，而且所有感染人类的病原体都会进入废水，尽管数量不同。应实施废水和环境监测以加强监测系统，特别是在经济不平等限制传统监测数据可解释性的地方。
