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Landscape analysis of modelling activities around the world regarding the impact of SARS-CoV-2 on influenza activity.
Wiegersma, S., Del Riccio, M., Staadegaard, L., Paget, J. Landscape analysis of modelling activities around the world regarding the impact of SARS-CoV-2 on influenza activity. Utrecht: Nivel, 2022. 10 p.
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Main findings
Our landscape analysis aimed to identify research modelling groups which have assessed the impact of SARS-CoV-2 on influenza activity, and could be approached to jointly develop models to predict influenza activity in the coming seasons based on different scenarios. We performed a scoping review and web search, and identified 7 research groups working on the interaction between influenza and SARS-CoV-2 or the impact of NPIs on influenza activity, and 4 additional studies that were slightly out of the scope of the review but used relevant modelling approaches. Of these, a research group at Princeton fits best with the FluCov aims and thus seems to be the most suitable candidate for further collaboration.
A second research group that was identified in the landscape analysis was the Bansal Lab (Disease
ecology and network epidemiology research lab) at Georgetown University, who work on the
impact of NPIs on infection spread and the interaction between COVID-19 and influenza. Finally,
there is a group at the Yale School of Public Health, that also works on future modelling of
respiratory infections, especially Respiratory Syncytial Virus (RSV), and as such could also be an
interesting partner.
Our landscape analysis aimed to identify research modelling groups which have assessed the impact of SARS-CoV-2 on influenza activity, and could be approached to jointly develop models to predict influenza activity in the coming seasons based on different scenarios. We performed a scoping review and web search, and identified 7 research groups working on the interaction between influenza and SARS-CoV-2 or the impact of NPIs on influenza activity, and 4 additional studies that were slightly out of the scope of the review but used relevant modelling approaches. Of these, a research group at Princeton fits best with the FluCov aims and thus seems to be the most suitable candidate for further collaboration.
A second research group that was identified in the landscape analysis was the Bansal Lab (Disease
ecology and network epidemiology research lab) at Georgetown University, who work on the
impact of NPIs on infection spread and the interaction between COVID-19 and influenza. Finally,
there is a group at the Yale School of Public Health, that also works on future modelling of
respiratory infections, especially Respiratory Syncytial Virus (RSV), and as such could also be an
interesting partner.