Daily COVID-19 Cases in Singapore with Calendar-Aware Smoothing

5.5 KB of daily COVID-19 case data from Singapore, used to evaluate an outbreak detection framework. The dataset supports analysis of calendar effects like public holidays on case reporting and effective reproduction number (Rt) estimates. It was created by Lengyang Wang in a 2026 study comparing smoothing methods for reliable outbreak detection.

Use Cases

• Apply the working-day moving average (MAH) method to smooth daily case counts and adjust for public holiday effects.
• Calculate the effective reproduction number (Rt) from the smoothed daily case data to signal potential outbreak onset.
• Compare the performance of the proposed detection framework against established methods like EARS and EpiEstim using the provided case data.
• Quantify the uncertainty of smoothed Rt estimates using bootstrap inference as described in the source study.

Strengths

• Data is derived from a peer-reviewed methodological study on outbreak detection published in 2026.
• The dataset is small (5.5 KB) and focused, making it easy to download and inspect for the specific analytical methods described.
• It is licensed under CC BY 4.0, permitting flexible reuse with attribution.

Limitations

• The dataset is extremely small (5.5 KB), indicating very limited scope, likely containing only summary or illustrative data rather than a full time series.
• The exact number of rows, columns, and the raw case data structure are unknown from the provided input.
• The data's primary purpose is to demonstrate a specific methodological framework, not to provide a comprehensive epidemiological record.

Provenance

Source

figshare, uploaded by author Lengyang Wang.

Collection Method

Derived from daily COVID-19 case data from Singapore, processed with calendar-aware smoothing methods for a research study.

Time Range

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Freshness

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Geography

Singapore