TY - JOUR
T1 - Application of a forecasting model to mitigate the consequences of unexpected RSV surge
T2 - Experience from the post-COVID-19 2021/22 winter season in a major metropolitan centre, Lyon, France
AU - Casalegno, Jean Sebastien
AU - Bents, Samantha
AU - Paget, John
AU - Gillet, Yves
AU - Ploin, Dominique
AU - Javouhey, Etienne
AU - Lina, Bruno
AU - Morfin, Florence
AU - Grenfell, Bryan T.
AU - Baker, Rachel E.
N1 - Publisher Copyright:
© 2023 The Author(s)
PY - 2023
Y1 - 2023
N2 - Background The emergence of COVID-19 triggered the massive implementation of non-pharmaceutical interventions (NPI) which impacted the circulation of respiratory syncytial virus (RSV) during the 2020/2021 season. Methods A time-series susceptible-infected-recovered (TSIR) model was used early September 2021 to forecast the implications of this disruption on the future 2021/2022 RSV epidemic in Lyon urban population. Results When compared to observed hospital-confirmed cases, the model successfully captured the early start, peak timing, and end of the 2021/2022 RSV epidemic. These simulations, added to other streams of surveillance data, shared and discussed among the local field experts were of great value to mitigate the consequences of this atypical RSV outbreak on our hospital paediatric department. Conclusions TSIR model, fitted to local hospital data covering large urban areas, can produce plausible post-COVID-19 RSV simulations.
AB - Background The emergence of COVID-19 triggered the massive implementation of non-pharmaceutical interventions (NPI) which impacted the circulation of respiratory syncytial virus (RSV) during the 2020/2021 season. Methods A time-series susceptible-infected-recovered (TSIR) model was used early September 2021 to forecast the implications of this disruption on the future 2021/2022 RSV epidemic in Lyon urban population. Results When compared to observed hospital-confirmed cases, the model successfully captured the early start, peak timing, and end of the 2021/2022 RSV epidemic. These simulations, added to other streams of surveillance data, shared and discussed among the local field experts were of great value to mitigate the consequences of this atypical RSV outbreak on our hospital paediatric department. Conclusions TSIR model, fitted to local hospital data covering large urban areas, can produce plausible post-COVID-19 RSV simulations.
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U2 - 10.7189/jogh.13.04007
DO - 10.7189/jogh.13.04007
M3 - Article
C2 - 36757127
AN - SCOPUS:85147724103
SN - 2047-2978
VL - 13
JO - Journal of Global Health
JF - Journal of Global Health
M1 - 04007
ER -