COVID-19 and SARS-CoV-2. Modeling the present, looking at the future

Area of Science:

• Epidemiology
• Virology
• Computational Biology

Background:

• The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic, beginning in December 2019, has had a profound global impact.
• SARS-CoV-2 shares genetic similarities and the ACE2 receptor with SARS-CoV-1, yet exhibits greater transmissibility and lethality.
• Effective pandemic response requires sophisticated modeling to forecast disease spread and intervention impacts.

Purpose of the Study:

• To review and synthesize the literature on modeling strategies applied to SARS-CoV-2 and COVID-19.
• To provide a guide for modelers navigating the rapidly expanding research landscape.
• To highlight the role of modeling in addressing drug repurposing and vaccine development.

Main Methods:

• Review of diverse modeling approaches including deterministic, data-driven, stochastic, and agent-based models.
• Analysis of models incorporating societal complexities like social networks and transport systems.
• Examination of computational modeling techniques for drug discovery and vaccine design.

Main Results:

• Modeling is essential for forecasting epidemic progression and evaluating non-pharmaceutical interventions.
• Computational modeling aids in identifying potential drug repurposing candidates and designing new vaccines.
• The reviewed literature provides insights into strategies for managing the current pandemic and preparing for future outbreaks.

Conclusions:

• Modeling plays a critical role in understanding, forecasting, and mitigating the impact of pandemics like COVID-19.
• The integration of epidemiological, drug repurposing, and vaccine design modeling is vital for a comprehensive response.
• This review serves as a resource for modelers to leverage existing strategies and prepare for future global health emergencies.