A box, a trough and marbles: How the Reed-Frost epidemic theory shaped epidemiological reasoning in the 20th century

The article takes the renewed popularity and interest in epidemiological modelling for Covid-19 as a point of departure to ask how modelling has historically shaped epidemiological reasoning. The focus lies on a particular model, developed in the late 1920s through a collaboration of the former field-epidemiologists and medical officer, Wade Hampton Frost, and the biostatistician and population ecologist Lowell Reed. Other than former approaches to epidemic theory in mathematical formula, the Reed-Frost epidemic theory was materialised in a simple mechanical analogue: a box with coloured marbles and a wooden trough. The article reconstructs how the introduction of this mechanical model has reshaped epidemiological reasoning by shifting the field from purely descriptive to analytical practices. It was not incidental that the history of this model coincided with the foundation of epidemiology as an academic discipline, as it valorised and institutionalised new theoretical contributions to the field. Through its versatility, the model shifted the field’s focus from mono-causal explanations informed by bacteriology, eugenics or sanitary perspectives towards the systematic consideration of epidemics as a set of interdependent and dynamic variables.

A Study of Malware Propagation Dynamics in Wireless Sensor Network using Spatially Correlated Security Model

: Security is one of the important concern in both types of the network. The network may be wired or wireless. In case of wireless network security provisioning is more difficult in comparison to wired network. Wireless Sensor Network (WSN) is also a type of wireless network. And due to resource constraints WSN is vulnerable against malware attacks. Initially, the malware (virus, worm, malicious code, etc.) targets a single node of WSN for attack. When a node of WSN gets infected then automatically start to spread in the network. If nodes are strongly correlated the malware spreads quickly in the network. On the other hand, if nodes are weakly correlated the speed of malware spread is slow. A mathematical model is proposed for the study of malware propagation dynamics in WSN with combination of spatial correlation and epidemic theory. This model is based on epidemic theory with spatial correlation. The proposed model is Susceptible-Exposed-Infectious-Recover-Dead (SEIRD) with spatial correlation. We deduced the expression of basic reproduction number. It helps in the study of malware propagation dynamics in WSN. The stability analysis of the network has been investigated through proposed model. This model also helps in reduction of redundant information and saving of sensor nodes’ energy in WSN. The theoretical investigation verified by simulation results. A spatial correlation based epidemic model has been formulated for the study of dynamic behaviour of malware attacks in WSN.

Joseph Mark Gani 1924–2016

Joe Gani, as he was universally known, was born in Cairo, Egypt, on 15 December 1924 and died in Canberra on 12 April 2016. A visionary leader, mentor, and brilliant organizer, he created the Journal of Applied Probability, and was Chief of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Division of Mathematics and Statistics. A distinguished academic career included posts at the Universities of Sheffield, Kentucky, California at Santa Barbara, and the Australian National University. His numerous research contributions are dominated by stochastic modelling, especially epidemic theory.

Propagation of Spurious Data for Wireless Cognitive Sensor Network in the Smart Grid: A Social Network Method

The nature of white space utilization, tremendous data processing, heterogeneous coexistence and security guarantees in Wireless Cognitive Sensor Network (WCSN) brings significant advantages over traditional Wireless Sensor Network (WSN) used in the smart grid. However, one of the main security threats to WCSN in the smart grid is the transmission of spurious data by malicious secondary users, which can induce the control center to make a wrong spectrum allocation and power dispatching decisions. In this paper, after analyzing the reference structure of smart grid and the feasibility of applying the epidemic theory into WCSN, we propose the UDG model of WCSN in the smart grid. Based on the epidemic theory in social network, we model and analyze the spurious data propagation process and identify key factors determining potential epidemic outbreaks in WCSN. In conclusion, we validate the feasibility of SIS model and perform investigations on the system dynamics.