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The Hard Lessons and Shifting Modeling Trends of COVID-19 Dynamics: Multiresolution Modeling Approach
- Source :
- Bulletin of Mathematical Biology
- Publication Year :
- 2021
- Publisher :
- Springer US, 2021.
-
Abstract
- The COVID-19 pandemic has placed epidemiologists, modelers, and policy makers at the forefront of the global discussion of how to control the spread of coronavirus. The main challenges confronting modelling approaches include real-time projections of changes in the numbers of cases, hospitalizations, and fatalities, the consequences of public health policy, the understanding of how best to implement varied non-pharmaceutical interventions and potential vaccination strategies, now that vaccines are available for distribution. Here, we: (i) review carefully selected literature on COVID-19 modeling to identify challenges associated with developing appropriate models along with collecting the fine-tuned data, (ii) use the identified challenges to suggest prospective modeling frameworks through which adaptive interventions such as vaccine strategies and the uses of diagnostic tests can be evaluated, and (iii) provide a novel Multiresolution Modeling Framework which constructs a multi-objective optimization problem by considering relevant stakeholders' participatory perspective to carry out epidemic nowcasting and future prediction. Consolidating our understanding of model approaches to COVID-19 will assist policy makers in designing interventions that are not only maximally effective but also economically beneficial.
- Subjects :
- Optimization problem
Nowcasting
Computer science
General Mathematics
Immunology
Control (management)
Psychological intervention
Participatory modeling
Multi-objective optimization
General Biochemistry, Genetics and Molecular Biology
Pandemic
Humans
Prospective Studies
Pandemics
General Environmental Science
Pharmacology
SARS-CoV-2
General Neuroscience
COVID-19
Citizen journalism
Mathematical Concepts
Computational Theory and Mathematics
Risk analysis (engineering)
General Agricultural and Biological Sciences
Perspectives
Subjects
Details
- Language :
- English
- ISSN :
- 15229602 and 00928240
- Volume :
- 84
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Bulletin of Mathematical Biology
- Accession number :
- edsair.doi.dedup.....8148879f676e3a22b900ac2a6fcdac11