Winston Garira
Abstract
Multiscale modelling of infectious disease systems falls within the domain of complexity science—the study of complex systems. However, what should be made clear is that current progress in multiscale modelling of infectious disease dynamics is still as yet insufficient to present it as a mature sub-discipline of complexity science. In this article we present a methodology for development of multiscale models of infectious disease systems. This methodology is a set of partially ordered research and development activities that result in multiscale models of infectious disease systems built from different scientific approaches. Therefore, the conclusive result of this article is a methodology to design multiscale models of infectious diseases. Although this research and development process for multiscale models cannot be claimed to be unique and final, it constitutes a good starting point, which may be found useful as a basis for further refinement in the discourse for multiscale modelling of infectious disease dynamics.
Introduction
A common feature of complex systems is that they are multilevel and multiscale systems. The increasing ability to exhaustively study complex systems such as physical systems, infectious disease systems, food systems, energy systems, water systems, biological systems, chemical systems, artificial systems, and many more, in terms of their levels of organization and their associated scales of observation has raised hopes that this would lead to a systems level description of complex systems using multiscale modelling methods. Multiscale modelling is an emerging scientific method for exploring complex systems. In multiscale modelling of complex systems, there is an appreciation of the complexity of a system arising from its multilevel, multiscale and interconnected relationships occurring within levels of organization and scales of the complex system. In this article, we identify infectious disease systems as one of the complex systems facing major roadblocks due to multiscale needs and formulate a research and development process for multiscale models of infectious disease systems. The conclusive result of this article is a methodology to design multiscale models of infectious diseases. The lack of standardization among scientists using multiscale modelling of infectious diseases research makes it very difficult to achieve consensus in the best methods to create and share these models among the scientific community.
Methods
Before we can present the process model for multiscale modelling of infectious disease systems, there is need to give a common multiscale vision of their overall multilevel and multiscale structure. This helps to avoid the use of arbitrarily defined levels and scales of an infectious disease system which makes it difficult to establish collaboration among scientists with different skills in the research and development process for multiscale models of infectious disease systems. Collaboration among scientists with different skills in the research and development process for multiscale models of infectious disease systems would be possible if there exists a common understanding about the hierarchy of components which constitute an infectious disease system starting with its sub-systems. Then the sub-systems are decomposed into levels. Finally the levels are decomposed into scales. Without this common conceptual understanding of the overall multilevel and multiscale structure of an infectious disease system, any defined multiscale modelling study will likely lack a common multiscale vision to facilitate collaboration among scientists from different disciplines (biology, epidemiology, pharmacology, microbiology, public health, immunology, medicine, veterinary science, mathematical modelling, ecology, statistical modelling, environmental science, etc.). In the following sub-sections, we present key features that help us to build a common multiscale vision of the overall multilevel and multiscale structure of infectious disease systems. These features have not been discussed in the past with sufficient detail to enable us to present an interdisciplinary multiscale vision of the research and development process for multiscale models of infectious disease systems.
Discussion
Multiscale modelling of infectious diseases aims to characterize the complexity of infectious disease systems. It provides us with a set of analytic tools to characterize the multiscale structure of infectious disease systems and how the scales interact with each other through the different multiscale cycles/loops (primary multiscale loop, secondary multiscale loop, tertiary multiscale loop) to establish the observed disease dynamics. The conclusive result of this article is a methodology to design multiscale models of infectious diseases. The methodology is based on implementing a four-stage strategy in the research and development process for multiscale models of infectious disease systems. Further, the methodology is general enough to be applicable (with minor modifications) to multiscale modelling of other structurally organized complex systems beyond infectious disease systems. We eagerly anticipate that this research and development process for multiscale models will support the emergence of multiscale modelling as a branch of complexity science applied to the study of infectious disease systems. While this research and development process for multiscale models cannot be claimed to be unique, complete and final, it constitutes a good starting point, which may be found useful as a basis for further refinement in the discourse for multiscale modelling of infectious disease systems.
Citation: Garira W (2020) The research and development process for multiscale models of infectious disease systems. PLoS Comput Biol 16(4): e1007734. https://doi.org/10.1371/journal.pcbi.1007734
Editor: Jennifer A. Flegg, The University of Melbourne Melbourne School of Psychological Sciences, AUSTRALIA.
Received: October 15, 2019; Accepted: February 13, 2020; Published: April 2, 2020.
Copyright: © 2020 Winston Garira. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: This article has no data.
Funding: The author acknowledges with thanks financial support from South Africa National Research Foundation (NRF) Grant No. IPRR (UID 81235). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The author declares no competing non-financial/financial interests.
