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: The need for early identification of coronavirus disease (COVID-19) cases in communities was high in Yemen during the first wave of the COVID-19 epidemic because most cases presenting to health facilities were severe. Early detection of cases would allow early interventions to interrupt the transmission chains. This study aimed to describe the implementation of community-based surveillance (CBS) in in internally displaced people (IDP) camps and urban settings in Yemen from 15 April 2020 to 30 September 2020. METHODS: Following the Centers for Disease Control and Prevention guidance for evaluation of surveillance systems, we assessed the usefulness and acceptability of CBS. For acceptability, we calculated the proportion of trained volunteers who reported disease alerts. To assess the usefulness, we compared the alerts reported through the electronic diseases early warning system (eDEWS) with the alerts reported through CBS and described the response activities implemented. RESULTS: In Al-Mukalla City, 18% (14/78) of the volunteers reported at least one alert. In IDP camps, 58% (18/31) of volunteers reported at least one alert. In Al-Mukalla City, CBS detected 49 alerts of influenza-like illness, whereas health facilities detected 561 cases of COVID-19. In IDP camps, CBS detected 91 alerts of influenza-like illness, compared to 10 alerts detected through eDEWS. In IDP camps, CBS detected three other syndromes besides influenza-like illness (febrile illness outbreak suspicion, acute diarrhoea, and skin disease). In IDP camps, public health actions were implemented for each disease detected and no further cases were reported. CONCLUSIONS: In Yemen, CBS was useful for detecting suspected outbreaks in IDP camps. CBS implementation did not yield expected results in general communities in urban areas in the early stage of the COVID-19 pandemic when little was known about the disease. In the urban setting, the system failed to detect suspected COVID-19 cases and other diseases despite the ongoing outbreaks reported through eDEWS. In Yemen, as in other countries, feasibility and acceptability studies should be conducted few months before CBS expansion in urban communities. The project should be expanded in IDP camps, by creating COVID-19 and other disease outbreak reporting sites.
["Prevention"]