  Policymaking for complex challenges such as pandemics necessitates the
consideration of intricate implications across multiple domains and scales.
Computational models can support policymaking, but a single model is often
insufficient for such multidomain and scale challenges. Multi-models comprising
several interacting computational models at different scales or relying on
different modeling paradigms offer a potential solution. Such multi-models can
be assembled from existing computational models (i.e., integrated modeling) or
be designed conceptually as a whole before their computational implementation
(i.e., integral modeling). Integral modeling is particularly valuable for novel
policy problems, such as those faced in the early stages of a pandemic, where
relevant models may be unavailable or lack standard documentation. Designing
such multi-models through an integral approach is, however, a complex task
requiring the collaboration of modelers and experts from various domains. In
this collaborative effort, modelers must precisely define the domain knowledge
needed from experts and establish a systematic procedure for translating such
knowledge into a multi-model. Yet, these requirements and systematic procedures
are currently lacking for multi-models that are both multiscale and
multi-paradigm. We address this challenge by introducing a procedure for
developing multi-models with an integral approach based on clearly defined
domain knowledge requirements derived from literature. We illustrate this
procedure using the case of school closure policies in the Netherlands during
the COVID-19 pandemic, revealing their potential implications in the short and
long term and across the healthcare and educational domains. The requirements
and procedure provided in this article advance the application of integral
multi-modeling for policy support in multiscale and multidomain contexts.
