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:

Serological assays have been widely employed during the coronavirus disease 2019 (COVID-19) pandemic to measure antibody responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and to track seroconversion in populations. However, currently available assays do not allow determination of neutralization capacity within the assay protocol. Furthermore, commercial serology assays have a high buy-in cost that is inaccessible for many research groups. We have replicated the serological enzyme-linked immunosorbent assay for the detection of SARS-CoV-2 antibody isotypes, developed at the Icahn School of Medicine at Mount Sinai, New York. Additionally, we have modified the protocol to include a neutralization assay with only a minor modification to this protocol. We used this assay to screen local COVID-19 patient sera (n = 91) and pre-COVID-19 control sera (n = 103), and obtained approximate parity with approved commercial anti-nucleoprotein-based assays with these sera. Furthermore, data from our neutralization assay closely aligns with that generated using a spike-based pseudovirus infection model when a subset of patient sera was analyzed.
["Diagnosis"]