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:

Rapid and accurate diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and in fl uenza A virus (FluA) antigens in the early stages of virus infection is the key to control the epidemic spread. Here, we developed a two-channel fluorescent immunochromatographic assay (ICA) for ultrasensitive and simultaneous qualification of the two viruses in biological samples. A high-performance quantum dot nanobead (QB) was fabricated by adsorption of multilayers of dense quantum dots (QDs) onto the SiO2 surface and used as the highly luminescent label of the ICA system to ensure the high-sensitivity and stability of the assay. The combination of monodispersed SiO2 core ( approximately 180 nm) and numerous carboxylated QDs formed a hierarchical shell, which ensured that the QBs possessed excellent stability, superior fluorescence signal, and convenient surface functionalization. The developed ICA biosensor achieved simultaneous detection of SARS-CoV-2 and FluA in one test within 15 min, with detection limits reaching 5 pg/mL for SARS-CoV-2 antigen and 50 pfu/mL for FluA H1N1. Moreover, our method showed high accuracy and specificity in throat swab samples with two orders of magnitude improvement in sensitivity compared with traditional AuNP-based ICA method. Hence, the proposed method is a promising and convenient tool for detection of respiratory viruses.
["Diagnosis"]