You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:

- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.
- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.
- Prevention: The content covers measures to prevent the spread of COVID-19.
- Mechanism: The paragraph explains the biological mechanisms of the virus.
- Case Report: The content is a report of a COVID-19 case.
- Transmission: The paragraph discusses how COVID-19 is transmitted.
- Diagnosis: The content is about diagnosing COVID-19 in individuals.

Your classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: ["Topic1", "Topic2", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.

Article:

The coronavirus disease (COVID-19) is the global public health challenge currently persisting at a grand scale. A method that meets the rapid quantitative detection of antibodies to assess the body's immune response from natural COVID-19 illness or vaccines' effects is urgently needed. In the present study, an attempt was made to integrate a newly designed spectrometer to the COVID-19 test strip procedure; this augmentation provides the quantitative capacity to a lateral flow immunoassay (LFIA). Optical interpretation of results by quantitative alpha index, rather than visual qualification, can be done quickly, in 5-10 minutes. The developed product was compared with several other serological IgM/IgG antibody reagents on the market by recruiting 111 participants suspected of having COVID-19 infection from March to May 2020 in a hospital. Taking RT-PCR as the diagnostic gold standard, the quantitative spectral LIFA platform could correctly detect all 12 COVID-19 patients. Concerning RT-PCR negative patients, all three antibody testing methods found positive cases. The optical-based platform exhibited the ability of early detection of immunoglobulins of RT-PCR negative patients. There was an apparent trend that elevation of IgM levels in the acute phase of infection; then IgG levels rose later. It exhibited the risk of a false-negative diagnosis of RT-PCR in COVID-19 testing. The significant detection ability of this new optical-based platform demonstrated clinical potential.
["Diagnosis"]