Nowcasting methods to improve the performance of respiratory sentinel surveillance: lessons from the COVID-19 pandemic.
Sci Rep
; 14(1): 12582, 2024 05 31.
Article
en En
| MEDLINE
| ID: mdl-38822070
ABSTRACT
Respiratory diseases, including influenza and coronaviruses, pose recurrent global threats. This study delves into the respiratory surveillance systems, focusing on the effectiveness of SARI sentinel surveillance for total and severe cases incidence estimation. Leveraging data from the COVID-19 pandemic in Chile, we examined 2020-2023 data (a 159-week period) comparing census surveillance results of confirmed cases and hospitalizations, with sentinel surveillance. Our analyses revealed a consistent underestimation of total cases and an overestimation of severe cases of sentinel surveillance. To address these limitations, we introduce a nowcasting model, improving the precision and accuracy of incidence estimates. Furthermore, the integration of genomic surveillance data significantly enhances model predictions. While our findings are primarily focused on COVID-19, they have implications for respiratory virus surveillance and early detection of respiratory epidemics. The nowcasting model offers real-time insights into an outbreak for public health decision-making, using the same surveillance data that is routinely collected. This approach enhances preparedness for emerging respiratory diseases by the development of practical solutions with applications in public health.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Vigilancia de Guardia
/
COVID-19
Límite:
Humans
País/Región como asunto:
America do sul
/
Chile
Idioma:
En
Revista:
Sci Rep
Año:
2024
Tipo del documento:
Article
País de afiliación:
Chile
Pais de publicación:
ENGLAND
/
ESCOCIA
/
GB
/
GREAT BRITAIN
/
INGLATERRA
/
REINO UNIDO
/
SCOTLAND
/
UK
/
UNITED KINGDOM