Editorial: Mathematical modelling of infectious diseases

Area of Science:

• Disease ecology
• Mathematical modeling
• Epidemiology

Background:

• Mathematical models have been used for over a century to study disease spread, host density effects, and control strategies.
• The late 1970s and early 1980s saw a surge in mathematical modeling in disease ecology, with foundational work by Anderson and May.
• Key concepts like the basic reproduction number (R0) and critical community size were established, remaining central to the field.

Discussion:

• Disease ecology research has evolved from a focus on human diseases to include livestock and wildlife systems.
• Theoretical models now explore evolutionary aspects such as parasite virulence and drug resistance.
• Recent efforts aim to move beyond simple one-host-one-parasite models to capture natural system complexities.

Key Insights:

• Mathematical modeling is a cornerstone of disease ecology, providing frameworks to understand pathogen dynamics.
• The field has broadened significantly, incorporating diverse host-parasite systems and evolutionary questions.
• Current research emphasizes incorporating greater complexity, including multiple hosts and parasite interactions.

Outlook:

• Future research will likely focus on more complex, multi-host, multi-parasite models.
• Integrating ecological and evolutionary dynamics will be crucial for a comprehensive understanding of disease.
• Advanced mathematical approaches will continue to drive innovation in disease ecology and public health strategies.