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:

OBJECTIVES: The recent Covid-19 pandemic has burdened the healthcare facilities, especially in the presence of limited infrastructure. We aimed at applying a queuing model to the Covid-19 screening area so as to optimize the screening services and ensuring that no patient is refused the service. METHODS: The mean arrival time of patients, number of physicians, mean screening time and queue characteristics were observed and entered in the M/M/c/K queuing model using R programming to optimize the number of physicians required in the screening area. RESULTS: Considering the mean arrival of seven patients in 10 minutes and screening of three patients in 10 minutes by one physician, two physicians were assigned. At this capacity, the probability of saturation of the system was 15% with patient loss rate of 1.05 per 10 minutes. Queuing simulation with three physicians reduced the patient loss rate to 0.013 per 10 minutes and saturation probability of 0.2%. However, an increase of arrival rate from 10 to 20 led to an early saturation of the system. CONCLUSION: Queuing models offer an opportunity for the healthcare providers and hospital administrators to optimize patient care services, especially in critical areas with an ever-changing situation such as the current pandemic.
["Prevention"]