A workflow for software development within computational epidemiology

Abstract

A critical investigation into computational models developed for studying the spread of communicable disease is presented. The case in point is a spatially explicit micro-meso-macro model for the entire Swedish population built on registry data, thus far used for smallpox and for influenzalike illnesses. The lessons learned from a software development project of more than 100 person months are collected into a check list. The list is intended for use by computational epidemiologists and policy makers, and the workflow incorporating these two roles is described in detail.

Sensemaking in Intelligent Health Data Analytics

“…Finally, we have elsewhere explained how data science and computational approaches can influence as well as learn from health care policymaking [7]. We have here largely dealt with the individual as a future stakeholder, always keeping in mind the fact that the policymaker is the current one.…”

“…This leads to a situation where the workflow between data scientists and practitioners in medicine is under rapid methodological development, incorporating critical perspectives [30], highly contingent on policy developments (cf. [7]), and linked to foresight.…”

Syndromic surveillance in the United Arab Emirates

“…Microdata are today widely employed for understanding the spread of infectious disease, both through the new science of computational epidemiology [20] and through the monitoring of individual ICT use. Macrodata, by contrast, are at the heart of traditional models of infectious disease [21], resting on differential equations and statistics for estimating the expected trends of communicable diseases at the population level.…”

Social computational systems

“…Vahid Dabbaghian, Valerie Spicer, Suraj K. Singh, Peter Borwein, and Patricia Brantigham in their article "The Social Impact on the High-Rate Criminal Offending: A Cellular Automata Model" [8] examine the spread of criminal behavior and hard drug consumption using a mathematical approach called cellular automata (CA). The CA model is based on two behavioral concepts -(i) peer association impacts criminal involvement and (ii) addiction can heighten criminal activity.…”