How mathematical epidemiology became a field of biology: a commentary on Anderson and May (1981) ‘The population dynamics of microparasites and their invertebrate hosts’

We discuss the context, content and importance of the paper ‘The population dynamics of microparasites and their invertebrate hosts’, by R. M. Anderson and R. M. May, published in the Philosophical Transactions of the Royal Society as a stand-alone issue in 1981. We do this from the broader perspective of the study of infectious disease dynamics, rather than the specific perspective of the dynamics of insect pathogens. We argue that their 1981 paper fits seamlessly in the systematic study of infectious disease dynamics that was initiated by the authors in 1978, combining effective use of simple mathematical models, firmly rooted in biology, with observable or empirically measurable ingredients and quantities, and promoting extensive capacity building. This systematic approach, taking ecology and biology rather than applied mathematics as the motivation for advance, proved essential for the maturation of the field, and culminated in their landmark textbook of 1991. This commentary was written to celebrate the 350th anniversary of the journal Philosophical Transactions of the Royal Society .

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Real-time forecasting of infectious disease dynamics with a stochastic semi-mechanistic model

Epidemics ◽

10.1016/j.epidem.2016.11.003 ◽

2018 ◽

Vol 22 ◽

pp. 56-61 ◽

Cited By ~ 44

Author(s):

Sebastian Funk ◽

Anton Camacho ◽

Adam J. Kucharski ◽

Rosalind M. Eggo ◽

W. John Edmunds

Keyword(s):

Infectious Disease ◽

Real Time ◽

Mechanistic Model ◽

Disease Dynamics ◽

Infectious Disease Dynamics

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Risk Causal Analysis of Traffic-Intensive Waters Based on Infectious Disease Dynamics

Journal of Marine Science and Engineering ◽

10.3390/jmse7080277 ◽

2019 ◽

Vol 7 (8) ◽

pp. 277

Author(s):

Yong-jun Chen ◽

Qing Liu ◽

Cheng-peng Wan

Keyword(s):

Infectious Disease ◽

Risk Factors ◽

Causal Model ◽

Cloud Model ◽

Rapid Development ◽

River Estuary ◽

Yangtze River Estuary ◽

Disease Dynamics ◽

Transmission Process ◽

Infectious Disease Dynamics

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.

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