Infectious disease outbreak surveillance and control - overview
IBM scientists are applyling their data analytics expertise to monitor outbreaks of infectious diseases.
Over the past two decades, a number of extremely high-profile infectious disease outbreaks — including SARS, pandemic influenza, Ebola and Zika, as well as the looming threat of highly pathogenic avian influenza (HPAI) — have strained both local and international health response systems. In particular, the Ebola virus outbreak from 2013 to 2016, sent a shock through society and authorities and triggered calls for further investment in preparedness and surveillance systems among national and international health agencies
With this growing awareness of the risk of emerging infectious diseases, there has been enormous scientific progress in the modelling and analysis of outbreaks. However, much of this progress is currently inaccessible to public health workers on the frontlines fighting disease. At IBM, we are uniquely placed to incorporate these scientific advances into a coherent, accessible technological framework and, at IBM Research – Australia, we are developing a data analytics tool that will serve as decision support software to epidemiologists working on outbreak control. This tool will allow the analysis of outbreaks while they are emerging, when a pathogen from an animal source is in the process of adapting to the human population, as well as simulating and analysing the spread of a human-adapted pathogen across a wide geographic area.
For example, for a project with IBM's Health Corps initiative and the Taiwan Centers for Disease Control (CDC), scientists of the Australian lab helped to create computer models that might be useful in predicting the effect of interventions to fight dengue fever. Dengue fever is a major cause of death in the tropics and subtropics. Globally, it is the most rapidly spreading mosquito-borne virus and in Taiwan significant outbreaks with tens of thousands of new cases have occurred in recent years.
IBM created computer models that can simulate the impact of an infection with Wolbachia bacteria, which makes it harder for mosquitoes to carry and transmit the dengue virus, on the mosquito population and on the number of human dengue cases. IBM also created models that examined correlations between various factors, such as the relationship between a village's education level and the number of local mosquito eggs, and the relationship between temperature and larva level. The goal of the project was to help the Taiwan CDC make more informed decisions to combat the disease.