Epidemic models: why and how to use them

Holistic One Health Surveillance Framework: Synergizing Environmental, Animal, and Human Determinants for Enhanced Infectious Disease Management

“…These models incorporate nonlinear equations that describe disease incidence as a function of both susceptible and infected populations, shaping the trajectory of the epidemic. 161 During the COVID-19 pandemic, epidemic modeling has played a crucial role in assessing risks, predicting its impact on healthcare systems, providing rationale for implementing measures, optimizing vaccine distribution, and influencing various aspects of our response to the virus. 162,163 ACS Infectious Diseases Modern drug discovery has entered the Big Data era due to the vast data sets available for drug candidates.…”

“…160 AI-driven epidemic modeling encompasses a range of methodologies that employ mathematical, statistical, and computational techniques to analyze and understand the dissemination of infectious pathogens within populations. 161 This field relies on a combination of empirical data and theoretical assumptions to describe various factors including demographic dynamics, environmental conditions, modes of transmission, and the resulting health impacts associated with communicable diseases. Through these approaches, researchers aim to gain insights into how diseases spread, how they interact with their host populations, and what measures can be taken to mitigate their impact on public health.…”

“…An archetypal example is the “S-I-R” model, which classifies individuals as initially susceptible (S), then infected and contagious (I), and eventually removed from transmission due to recovery or mortality (R). These models incorporate nonlinear equations that describe disease incidence as a function of both susceptible and infected populations, shaping the trajectory of the epidemic . During the COVID-19 pandemic, epidemic modeling has played a crucial role in assessing risks, predicting its impact on healthcare systems, providing rationale for implementing measures, optimizing vaccine distribution, and influencing various aspects of our response to the virus. , …”

From descriptive epidemiology to interventional epidemiology: The central role of epidemiologists in COVID-19 crisis management

“…The compelling need to develop epidemiological models was first identified in a report by scientists at Imperial College at the end of February 2020 [4] , as discussed by Sofonea et al in this issue [5] .…”

A Mathematical Study for the Transmission of Coronavirus Disease

“…It makes use of information and theories that describe the demographic trends, environmental traits, chances for disease transmission, and health effects of diseases [1]. It can be applied to quantification, a hypothesis based on creating forecasts and scenarios, and logical verification because it comes with appropriate evolution equations [2]. These models, like those used in other scientific fields, concentrate on the subset of characteristics and mechanisms thought to be the primary causes of a phenomenon.…”