About this Research Topic
The COVID-19 pandemic has underscored the importance of accurate estimates of size and duration of epidemics and pandemics. Unfortunately, inaccurate and often conflicting estimates or estimates that do not express the range of uncertainty inherent in modeling a novel pathogen tend to undermine trust and confidence in models and science’s ability to predict size, duration, and impact on society.
While prediction especially during the early stages of an epidemic when data are incomplete is especially difficult, it is the purpose of this Research Topic to improve our ability to confidently model the epidemic/pandemic process in order to yield better estimates both of the size and duration of the epidemic and epidemiological characteristics of the disease in order to better inform interventions to control the spread of SARS-CoV-2 .
We seek research papers on the following or related topics :
• Novel or unique mathematical models
• Novel or unique methods for expressing uncertainty in models
• Models from other disciplines, e.g. physics, wildlife ecology
• Impact on infrastructure like hospitals
• Models based on:
o Characteristics of the disease
o Population and population density
o Economic and social conditions of the population
o Policy decisions made by public health departments
o Intrinsic immunity or receptivity to the disease
o Transmission vectors and environment
o Network science and complexity theory models
o Curve-fitting, product adoption, and biological models
While prediction especially during the early stages of an epidemic when data are incomplete is especially difficult, it is the purpose of this Research Topic to improve our ability to confidently model the epidemic/pandemic process in order to yield better estimates both of the size and duration of the epidemic and epidemiological characteristics of the disease in order to better inform interventions to control the spread of SARS-CoV-2 .
We seek research papers on the following or related topics :
• Novel or unique mathematical models
• Novel or unique methods for expressing uncertainty in models
• Models from other disciplines, e.g. physics, wildlife ecology
• Impact on infrastructure like hospitals
• Models based on:
o Characteristics of the disease
o Population and population density
o Economic and social conditions of the population
o Policy decisions made by public health departments
o Intrinsic immunity or receptivity to the disease
o Transmission vectors and environment
o Network science and complexity theory models
o Curve-fitting, product adoption, and biological models
Keywords: logistics curve, epidemics, COVID-19, mathematical models, spread of disease, pandemic
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
