Role of Modelling in Emerging Infectious Diseases

Background: Emerging infectious diseases (EIDs) pose significant challenges to public healthAvailable online at:systems globally. They are diseases that are caused by an infectious pathogen that has evolved in thejhiphalexu.journals.ekb.egpopulation in the past two decades, changed pathogenesis, or increased in incidence, geographic,impact, host, or vector range. Most EIDs are of animal origin. Climate change and increasedinternational travel and trade facilitate the rapid spread of infectious agents across borders causingPrint ISSN: 2357-0601epidemics. Control and prevention strategies of EIDs are complicated and stressful as they require aOnline ISSN: 2357-061XOne Health approach which involves collaboration between human, animal, environmental, and otherCC BY-SA 4.0disciplines. Modelling and prediction of EIDs outbreaks had gained attention due to the advance inbig data and machine learning. Modelling is classified into broad categories; compartmental modelswhich divide the population into compartments based on the disease status, agent-based models thatsimulate the behavior of individual agents, network models which represent interactions between¥Correspondence:individuals as a network (nodes and edges), and spatial models which incorporate geographicEmail: [email protected] to study how diseases spread across physical space.Conclusion: Each modelling technique has strengths and limitations, and the choice of modeldepends on the specific policymaker questions, available data, and computational resources.Integrated approaches combining multiple techniques provide more comprehensive insights intoinfectious disease dynamics.