# APBA Kısa Özet

CDC applied a nowcasting model to measles surveillance data from South Carolina during the October 2025–March 2026 outbreak. The model corrected for reporting delays to estimate real-time case counts and the effective reproduction number (Rₜ), improving situational awareness compared with provisional data.

# Çalışma neyi araştırdı?

This study evaluated the performance of a nowcasting model used to estimate real-time transmission trends during a measles outbreak. The objective was to correct for reporting delays in surveillance data and produce timely case counts and Rₜ estimates. Researchers assessed how well the nowcast aligned with provisional case counts and examined how changes in reporting patterns affected model accuracy.

# Yöntem

The nowcasting model used historical reporting delay distributions to adjust case counts and calculate Rₜ in near real-time. Data were drawn from South Carolina’s measles surveillance system during the October 2025–March 2026 outbreak. The model estimated daily case counts and cumulative outbreak size, then compared these nowcast estimates with provisional data reported by the state health department. Performance metrics included mean absolute error and directionality of transmission trends.

# Temel bulgular

  • The nowcast model produced real-time case counts and effective reproduction numbers (Rₜ) that reflected transmission dynamics more promptly than provisional data.
  • Nowcast estimates of daily cases were generally accurate, with mean absolute error lower than that of provisional counts during periods of stable reporting.
  • Nowcasts improved estimates of cumulative outbreak size compared with provisional data throughout the outbreak period.
  • Model accuracy depended on the stability of case reporting patterns. When reporting became more complete or changed rapidly, model performance shifted accordingly.

# Bulgular ne anlama geliyor?

Nowcasting provided more reliable real-time signals than provisional case counts alone, enabling public health officials to detect changes in transmission sooner. The model improved situational awareness during the early and middle phases of the outbreak. However, accuracy declined in January when a rapid increase in cases led to less complete provisional data, demonstrating that nowcast performance is sensitive to sudden changes in reporting behavior. Overall, nowcasting proved a useful tool for real-time outbreak monitoring in this context.

# Klinik önem

This report is based on public health surveillance and does not contain clinical data or clinical guidance. The findings inform outbreak management and resource allocation at the population level. No clinical recommendations are provided.

# Sınırlılıklar

  • Findings are limited to a single state measles outbreak and may not generalize to other diseases, settings, or larger geographic areas.
  • Model performance decreased when reporting patterns changed rapidly, particularly during January when case counts surged.
  • Nowcast estimates rely on the completeness of reporting dates; under-ascertainment of cases may affect accuracy.
  • The model was not validated for use in other infectious diseases; generalizability beyond measles is unknown.
  • Results reflect one outbreak experience and should not be extrapolated to future events without further validation.