New collaborative work on balancing information gains and losses when collecting outputs from multiple epidemic models is published in Epidemics.
During outbreaks like COVID-19, policymakers rely heavily on epidemic models to make decisions. Our recent study sheds light on how to enhance these models by comparing different methods of collecting and analyzing data. Together with scientists from various teams in the European COVID-19 Scenario Modelling Hub, we looked at projections for Belgium, the Netherlands, and Spain from July 2022. Traditionally, modelers provide summaries of their predictions, but in this new study we compared this method to collecting and analyzing simulated trajectories directly.
We found that collecting modeled trajectories instead of summary statistics provides more useful information for policymakers. Trajectories captured important epidemic characteristics more accurately than summary statistics. Ensembles created from these trajectories were better at representing the range of possible outcomes and could be continuously updated with new data.
This new approach could lead to more accurate and adaptable epidemic models. By understanding the strengths and limitations of different data collection methods, scientists can better communicate their findings to policymakers and improve decision-making during disease outbreaks.
The study highlights the importance of continuously refining epidemic models to better inform public health responses. By collecting modeled trajectories and evaluating their performance over time, researchers can provide more accurate and reliable projections for policymakers to use in guiding their decisions.
Read the full story: https://doi.org/10.1016/j.epidem.2024.100765