On the Challenges for the Diagnosis of SARS-CoV-2 Based on a Review of Current Methodologies

被引:74
|
作者
Mattioli, Isabela A. [1 ]
Hassan, Ayaz [1 ]
Oliveira Jr, Osvaldo N. [2 ]
Crespilho, Frank N. [1 ]
机构
[1] Univ Sao Paulo, Sao Carlos Inst Chem, BR-13560970 Sao Carlos, SP, Brazil
[2] Univ Sao Paulo, Sao Carlos Inst Phys, BR-13560590 Sao Carlos, SP, Brazil
来源
ACS SENSORS | 2020年 / 5卷 / 12期
基金
巴西圣保罗研究基金会;
关键词
SARS-CoV-2; point-of-care; COVID-19; diagnosis; biosensors; lateral flow devices; RT-PCR; surface plasmon resonance; nanoparticles; LINKED-IMMUNOSORBENT-ASSAY; NUCLEIC-ACID DETECTION; CHEMILUMINESCENCE IMMUNOASSAY; SARS CORONAVIRUS; LATERAL FLOW; RT-PCR; ULTRASENSITIVE DETECTION; VIRAL-RNA; MERS-COV; PROTEIN;
D O I
10.1021/acssensors.0c01382
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Diagnosis of COVID-19 has been challenging owing to the need for mass testing and for combining distinct types of detection to cover the different stages of the infection. In this review, we have surveyed the most used methodologies for diagnosis of COVID-19, which can be basically categorized into genetic-material detection and immunoassays. Detection of genetic material with real-time polymerase chain reaction (RT-PCR) and similar techniques has been achieved with high accuracy, but these methods are expensive and require time-consuming protocols which are not widely available, especially in less developed countries. Immunoassays for detecting a few antibodies, on the other hand, have been used for rapid, less expensive tests, but their accuracy in diagnosing infected individuals has been limited. We have therefore discussed the strengths and limitations of all of these methodologies, particularly in light of the required combination of tests owing to the long incubation periods. We identified the bottlenecks that prevented mass testing in many countries, and proposed strategies for further action, which are mostly associated with materials science and chemistry. Of special relevance are the methodologies which can be integrated into point-of-care (POC) devices and the use of artificial intelligence that do not require products from a well-developed biotech industry.
引用
收藏
页码:3655 / 3677
页数:23
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