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:

BACKGROUND: Three rounds of a repeated cross-sectional serosurvey to estimate the change in seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were conducted from August to October 2020 in the state of Delhi, India, in the general population >/=5 y of age. METHODS: The selection of participants was through a multistage sampling design from all 11 districts and 280 wards of the city-state, with multistage allocation proportional to population size. The blood samples were screened using immunoglobulin G (IgG) enzyme-linked immunosorbent assay kits. RESULTS: We observed a total of 4267 (N=150 46), 4311 (N=17 409) and 3829 (N=15 015) positive tests indicative of the presence of IgG antibody to SARS-CoV-2 during the August, September and October 2020 serosurvey rounds, respectively. The adjusted seroprevalence declined from 28.39% (95% confidence interval [CI] 27.65 to 29.14) in August to 24.08% (95% CI 23.43 to 24.74) in September and 24.71% (95% CI 24.01 to 25.42) in October. On adjusted analysis, participants with lower per capita income, living in slums or overcrowded households and those with diabetes comorbidity had significantly higher statistical odds of having antibody positivity (p<0.01). CONCLUSIONS: Nearly one in four residents in Delhi, India >/=5 y of age had the SARS-CoV-2 infection during August-October 2020.
["Diagnosis"]