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:

COVID-19 pandemic has affected all aspects of people's lives and disrupted the economy. Forecasting the number of cases infected with this virus can help authorities make accurate decisions on the interventions that must be implemented to control the pandemic. Investigation of the studies on COVID-19 forecasting indicates that various techniques such as statistical, mathematical, and machine and deep learning have been utilized. Although deep learning models have shown promising results in this context, their performance can be improved using auxiliary features. Therefore, in this study, we propose two hybrid deep learning methods that utilize the statistical features as auxiliary inputs and associate them with their main input. Specifically, we design a hybrid method of the multihead attention mechanism and the statistical features (ATT_FE) and a combined method of convolutional neural network and the statistical features (CNN_FE) and apply them to COVID-19 data of 10 countries with the highest number of confirmed cases. The results of experiments indicate that the hybrid models outperform their conventional counterparts in terms of performance measures. The experiments also demonstrate the superiority of the hybrid ATT_FE method over the long short-term memory model.
["Epidemic Forecasting"]