A new handbook on mathematical models has been released by Chalmers University of Technology, the University of Gothenburg, and several Swedish government agencies, aiming to support better decision-making in future pandemics, according to an April 17 announcement.
The handbook addresses challenges faced during the COVID-19 pandemic when experts' advice was crucial but often led to debates due to differing conclusions from various models. It seeks to guide how mathematical models can inform policy decisions and be communicated effectively during crises.
Torbjörn Lundh, professor of biomathematics at Chalmers University of Technology and the University of Gothenburg, is one of the authors. He used mathematical modeling during the pandemic to help Sahlgrenska University Hospital estimate intensive care demand. The handbook provides practical guidance for using these models under uncertain conditions. Philip Gerlee, lead researcher for the project and professor at both universities, said: "No model can provide a definitive answer, but they can still be very useful. For us, the handbook arose out of frustration at the misconceptions and, at times, the harsh tone of exchanges between different groups that emerged in Sweden during the pandemic - and which also occurred in other countries. We want to show that all models are simplifications, but that with the right assumptions they can be helpful to decision-makers and that different models can complement one another. Hopefully, this will lead to better collaboration between experts so that we can provide better advice, more effectively, to decision-makers during the next pandemic."
Anders Tegnell from the Public Health Agency of Sweden contributed as a co-author. He said: "As everything happened so quickly and many people wanted to contribute their expertise, there was a certain amount of confusion over terminology and even mistrust between different groups. One example of how this played out was in opinion pieces in the Swedish media that were not particularly constructive."
Lundh noted that using a variety of models offers broader understanding: "Different models and results can provide a broader picture and a deeper understanding. It is rarely a good idea to rely solely on one model... For example AI models were difficult to use at the start... when there was not yet enough data." He also warned about relying on overly complex approaches: "The more complex a model is, the harder it is to explain and understand...the results can vary greatly based on even very minor changes."
The article highlights ongoing efforts like SEMAFOR (Swedish Epidemic Modelling and Force network), where government agencies and universities conduct training exercises together for preparedness.
Lundh concluded by describing collaborative rehearsals such as mock press conferences as important steps toward improving national readiness.
