Modeling approaches for early warning and monitoring of pandemic situations as well as decision support - Botz, Jonas; Wang, Danqi; Lambert, Nicolas; Wagner, Nicolas; Génin, Marie; Thommes, Edward; Madan, Sumit; Coudeville, Laurent; Fröhlich, Holger (Frontiers in Public Health, 2022)
The COVID-19 pandemic has highlighted the lack of preparedness of many healthcare systems against pandemic situations. In response, many population-level computational modeling approaches have been proposed for predicting outbreaks, spatiotemporally forecasting disease spread, and assessing as well as predicting the effectiveness of (non-) pharmaceutical interventions. However, in several countries, these modeling efforts have only limited impact on governmental decision-making so far. In light of this situation, the review aims to provide a critical review of existing modeling approaches and to discuss the potential for future developments.