SIMULATION AND MODELING FOR EPIDEMIOLOGY AND PUBLIC HEALTH

Epidemiologists and public health professionals rely heavily on simulation and modelling because it helps them better understand the dynamics of infectious illnesses and makes evidence-based decisions. Data availability and quality, assumptions and simplifications, parameter uncertainty, and ethical considerations are just some of the limits of simulation and modelling methodologies that are covered. Despite these caveats, simulation and modelling provide useful information for understanding epidemiological trends, measuring the success of interventions, and making policy decisions in the public interest. To improve the validity, precision, and ethical rigour of simulation and modelling in epidemiology and public health, the paper concludes by stressing the need to address these constraints and collaborate across disciplines. Future improvements in disease management techniques and public health protection offer much potential thanks to continual improvements in data collecting, model development, and computer capability.