GCRF_NF98_Building an Early Warning System for community-wide infectious disease spread: SARS-CoV-2 tracking in Africa via environment fingerprinting

缓解新冠肺炎在全球的快速传播需要社区感染流行的实时数据，以便在区域、国家和全球范围内指导有针对性的干预措施。个人诊断检测对于大流行的短期和长期管理至关重要，但对能力的限制(包括试剂盒和训练有素的工作人员)意味着，医疗保健环境优先于社区。在这里，我们提出了一种新的补充低资源方法，用于广泛的社区范围内监测SARS-CoV-2感染流行情况。我们的目标是建立一个实时的新冠肺炎风险预测平台，通过基于废水的流行病学进行社区范围的诊断(图1)。生活污水中存在的疾病标志物可以反映贡献人群的健康状况，我们认为这包括SARS-CoV-2感染的流行情况。对这种新型冠状病毒在南非(开普敦)和尼日利亚(拉各斯)几个地点的城市水中的实时时空估计将提供社区感染流行的概貌，即使是无症状病例，以及获得性免疫水平，从而确定优先检测、接触者追踪和检疫的热点，并将提供更准确的病毒传播和感染死亡率预测。由于社区直接造成废水，我们将能够估计社区一级的真实感染率，也包括无症状和无症状的人。病毒载量水平将用于确定状态和时间趋势。这将能够通过有针对性的干预措施快速识别管理热点，并可能支持有关进入和离开“禁闭期”的重要决策，以及对选定社区的重点筛查。

Mitigating the rapid global spread of Covid-19 requires real-time data on community infection prevalence in order to guide targeted intervention measures on regional, national and global scales. Individual diagnostic testing is of paramount importance for short- and long-term management of the pandemic, but limits on capacity (both of kits and trained workers) mean that healthcare settings are prioritised over the community. Here we propose a novel supplemental low-resource approach for broad community-wide surveillance of SARS-CoV-2 infection prevalence. We aim for a real-time Covid-19 risk prediction platform for community-wide diagnostics via wastewater-based epidemiology (Figure 1). Disease markers present in domestic wastewater can reveal the health status of contributing population, and we propose that this includes the infection prevalence by SARS-CoV-2. Real-time spatiotemporal estimation of this novel coronavirus in urban water across several sites in South Africa (Cape Town) and Nigeria (Lagos) will provide a broad picture of community infection prevalence, even for asymptomatic cases, as well as the level of acquired immunity, thus identifying hotspots for priority testing, contact-tracing and quarantine and will provide more accurate projections of the spread of the virus and the infection fatality rate. As communities contribute directly to wastewater, we will be able to estimate true infection rate at the community level, including also asymptomatic and pre-symptomatic people. The virus loading levels will be used to establish status and time trends. This would enable rapid identification of hot spots for management via targeted intervention measures and potentially support important decisions regarding entry into and exit from 'lockdown' periods as well as focussed screening of selected communities.