Real Time National Policy Adjustment and Evaluation on the Basis of a Computational Model for COVID19
The current COVID-19 pandemic presents an unprecedented challenge for policy makers. Although the major consequences from the uninhibited spread of COVID-19 virus in Western European countries have abated due to far reaching social distancing measures, these measures carry enormous economic and social costs. Furthermore, basic epidemiological mechanics dictate that some form of containment policy will be necessary for the foreseeable future in order to prevent a recurrent outbreak and keep the impact of COVID-19 manageable. The challenge then is to design public policy interventions informed by epidemiological models. However, these models suffer from what has been termed in other fields the curse of locality: while the basic biology of the virus is the same everywhere, the outcomes will differ according to the local circumstances: the host population in each country is different, societal norms and customs vary and spatial patterns governing movement of people in their daily lives differ. This means that Dutch policy must be informed by a model that is tailored to circumstances in the Netherlands. In this project, work will continue on developing an epidemiological model that can be used to inform public health interventions and is specifically tailored to circumstances in the Netherlands.
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Kernel Tuner greatly simplifies the development of highly-optimized and auto-tuned CUDA, OpenCL, and C code, supporting many advanced use-cases and optimization strategies that speed up the auto-tuning process.