Describing, Modelling and Forecasting the Spatial and Temporal Spread of COVID-19: A Short Review
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Summary
Evidence of this spread is provided and modelling efforts undertaken to understand and forecast SARS-CoV-2 are documents, including a short section about the new variants that emerged in late 2020.
- Type
- review
- Published
- 2021-02-04
- Cited by
- 19
- References
- 188
- Access
- Open access
- OpenAlex
- https://openalex.org/W3126783654
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:231801956
Keywords
Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), 2019-20 coronavirus outbreak, Section (typography), Geography
References
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- Θογκγδιδης : the History of the Peloponnesian War
- Spatial deterministic epidemics
- Is population structure sufficient to generate area-level inequalities in influenza rates? An examination using agent-based models
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- Spread of a novel influenza A (H1N1) virus via global airline transportation.
- Initial human transmission dynamics of the pandemic (H1N1) 2009 virus in North America
- Dengue epidemics and human mobility.
- Large-Scale Spatial-Transmission Models of Infectious Disease
- Influences on influenza transmission within terminal based on hierarchical structure of personal contact network
- Application of an individual-based model with real data for transportation mode and location to pandemic influenza
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Cited by
- Epidemic Thresholds of Infectious Diseases on Tie-Decay Networks
- A Multilayer Network Model of the Coevolution of the Spread of a Disease and Competing Opinions
- Nonsmooth Convex Optimization to Estimate the Covid-19 Reproduction Number Space-Time Evolution With Robustness Against Low Quality Data
- Networks of necessity: Simulating COVID-19 mitigation strategies for disabled people and their caregivers
- Covid19 Reproduction Number: Credibility Intervals by Blockwise Proximal Monte Carlo Samplers
- Temporal evolution of the Covid19 pandemic reproduction number: Estimations from proximal optimization to Monte Carlo sampling
- Effects of Asymptomatic Infections on the Spatial Spread of Infectious Diseases
- Bistability in deterministic and stochastic SLIAR-type models with imperfect and waning vaccine protection
- Stability Analysis of Delayed COVID-19 Models
- Analysis of Spatial and Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data
- SPARSEMODr: Rapidly simulate spatially-explicit and stochastic models of COVID-19 and other infectious diseases
- Space-Distributed Traffic-Enhanced LSTM-Based Machine Learning Model for COVID-19 Incidence Forecasting
- The coevolution of the spread of a disease and competing opinions in multiplex networks
- Dynamics of a Fractional-Order Delayed Model of COVID-19 with Vaccination Efficacy
- A new RNN based machine learning model to forecast COVID-19 incidence, enhanced by the use of mobility data from the bike-sharing service in Madrid
- Pandemic Intensity Estimation from Stochastic Approximation-Based Algorithms
- Human-network regions as effective geographic units for disease mitigation
- The Big Bang of an epidemic: a metapopulation approach to identify the spatiotemporal origin of contagious diseases and their universal spreading pattern
- Human-Network Regions as Effective Geographic Units for Disease Mitigation
- Analysis of Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data
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