Knowledge Graph:Applications in Tracing the Source of Large-Scale Outbreak—Beijing Municipality,China,2020–2021

Introduction:Tracing transmission paths and identifying infection sources have been effective in curbing the spread of coronavirus disease 2019(COVID-19).However,when facing a large-scale outbreak,this is extremely time-consuming and laborintensive,and resources for infection source tracing become limited.In this study,we aimed to use knowledge graph(KG)technology to automatically infer transmission paths and infection sources.Methods:We constructed a KG model to automatically extract epidemiological information and contact relationships from case reports.We then used an inference engine to identify transmission paths and infection sources.To test the model’s performance,we used data from two COVID-19 outbreaks in Beijing.Results:The KG model performed well for both outbreaks.In the first outbreak,20 infection relationships were identified manually,while 42 relationships were determined using the KG model.In the second outbreak,32 relationships were identified manually and 31 relationships were determined using the KG model.All discrepancies and omissions were reasonable.Discussion:The KG model is a promising tool for predicting and controlling future COVID-19 epidemic waves and other infectious disease pandemics.By automatically inferring the source of infection,limited resources can be used efficiently to detect potential risks,allowing for rapid outbreak control.

Superior effectiveness and acceptability of saliva samples for the detection of SARS-CoV-2 in China

In response to problems of poor sampling quality,low sensitivity,and high demand for medical personnel regarding the current severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)oropharyngeal(OP)swab sampling used in China,we aimed to evaluate the diagnostic performance and acceptability of saliva-based nucleic acid amplification tests(NAATs)in China.The results showed that,using nasopharyngeal(NP)swab results as the gold standard,the overall sensitivities for saliva specimens and OP swabs were 93.3%and 85.0%,the specificities were 92.6%and 93.8%,respectively.The results of an acceptability survey showed that the scores for saliva,OP,and NP samples were 9.46±1.69,8.11±2.42,and 4.58±3.82 out of 10,respectively,with significant differences among the three groups(P<0.05).With higher sensitivity,comparable specificity,and strong public preference,saliva-based NAATs represent a convenient and effective method for detecting SARS-CoV-2 in future epidemics.