This article reviews the essential role of mathematical models in
understanding and combatting the pandemic of novel coronaviruses, in
particular focusing the advance in the use of mathematical models in
disease control in Japan. Highlighting the integral role of mathematical
models in public health, the article introduces a model that factors in
the heterogeneity of infectious contacts, concentrating on the
effectiveness of testing and isolation, alongside a model that involves
economic losses. The models exhibit how, given such heterogeneity,
milder behavioral restrictions can still achieve suppression, rigorous
testing and isolation can effectively curb the spread, and containment
measures can mitigate economic losses. These models aid in grasping the
complicated dynamics of disease transmission and optimizing
interventions. The knowledge of population ecology is also considered
effective for public health in statistical analysis, organizing concepts
using dynamic mathematical models, which lead to policy proposals and
deepen understanding. Evolution theory may help the understanding of
virulence subject to change. However, effective prevention necessitates
not only models but also the practical implementation of efficacious
measures. The cooperation of various disciplines is particularly crucial
in achieving a balance between health measures, economic interests, and
human rights. Moreover, the article acknowledges the limitations of
models and underscores the significance of real-world execution.
Overall, the article advocates for a broader outlook to tackle future
pandemics and related challenges, underscoring the importance of ongoing
academic cooperation and global governance to effectively address
emerging infectious diseases and their far-reaching implications.