Mathematical modeling and cellular automata simulation of infectious disease dynamics: Applications to the understanding of herd immunity

2020 ◽  
Vol 153 (11) ◽  
pp. 114119 ◽  
Author(s):  
Sayantan Mondal ◽  
Saumyak Mukherjee ◽  
Biman Bagchi
Virulence ◽  
2013 ◽  
Vol 4 (4) ◽  
pp. 295-306 ◽  
Author(s):  
Constantinos I. Siettos ◽  
Lucia Russo

Author(s):  
Odo Diekmann ◽  
Hans Heesterbeek ◽  
Tom Britton

Mathematical modeling is critical to our understanding of how infectious diseases spread at the individual and population levels. This book gives readers the necessary skills to correctly formulate and analyze mathematical models in infectious disease epidemiology, and is the first treatment of the subject to integrate deterministic and stochastic models and methods. The book fully explains how to translate biological assumptions into mathematics to construct useful and consistent models, and how to use the biological interpretation and mathematical reasoning to analyze these models. It shows how to relate models to data through statistical inference, and how to gain important insights into infectious disease dynamics by translating mathematical results back to biology. This comprehensive and accessible book also features numerous detailed exercises throughout; full elaborations to all exercises are provided. The book covers the latest research in mathematical modeling of infectious disease epidemiology; it integrates deterministic and stochastic approaches; and teaches skills in model construction, analysis, inference, and interpretation.


Epidemics ◽  
2018 ◽  
Vol 22 ◽  
pp. 56-61 ◽  
Author(s):  
Sebastian Funk ◽  
Anton Camacho ◽  
Adam J. Kucharski ◽  
Rosalind M. Eggo ◽  
W. John Edmunds

2019 ◽  
Vol 7 (8) ◽  
pp. 277
Author(s):  
Yong-jun Chen ◽  
Qing Liu ◽  
Cheng-peng Wan

Accidents occur frequently in traffic-intensive waters, which restrict the safe and rapid development of the shipping industry. Due to the suddenness, randomness, and uncertainty of accidents in traffic-intensive waters, the probability of the risk factors causing traffic accidents is usually high. Thus, properly analyzing those key risk factors is of great significance to improve the safety of shipping. Based on the analysis of influencing factors of ship navigational risks in traffic-intensive waters, this paper proposes a cloud model to excavate the factors affecting navigational risk, which could accurately screen out the key risk factors. Furthermore, the risk causal model of ship navigation in traffic-intensive waters is constructed by using the infectious disease dynamics method in order to model the key risk causal transmission process. Moreover, an empirical study of the Yangtze River estuary is conducted to illustrate the feasibility of the proposed models. The research results show that the cloud model is useful in screening the key risk factors, and the constructed causal model of ship navigational risks in traffic-intensive waters is able to provide accurate analysis of the transmission process of key risk factors, which can be used to reduce the navigational risk of ships in traffic-intensive waters. This research provides both theoretical basis and practical reference for regulators in the risk management and control of ships in traffic-intensive waters.


2020 ◽  
Vol 14 (1) ◽  
pp. 57-89 ◽  
Author(s):  
Sheryl L. Chang ◽  
Mahendra Piraveenan ◽  
Philippa Pattison ◽  
Mikhail Prokopenko

PLoS ONE ◽  
2013 ◽  
Vol 8 (4) ◽  
pp. e58802 ◽  
Author(s):  
Gonzalo M. Vazquez-Prokopec ◽  
Donal Bisanzio ◽  
Steven T. Stoddard ◽  
Valerie Paz-Soldan ◽  
Amy C. Morrison ◽  
...  

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