How can geospatial modelling improve public health decision-making?
Making the right decisions under time pressure in safety-critical situations such as the COVID-19 pandemic is an extremely hard task that demands the support of the most advanced and cutting-edge technologies. In such a situation, simulating the consequences of whether or not to impose a lockdown or ban international travel could cost or save millions of lives and help authorities to make informed and fair decisions.
Hadean has been working with domain specialists at Imperial College London and the University of Oxford to create a geospatial model of COVID-19 transmission. Thanks to its high-performance cloud computing architecture, the Hadean platform can provide decision-makers with real-time, interactive data about a wide range of scenarios that may arise during a pandemic or other time-critical situations. Critically, this can include interactive application of possible policy responses, with the consequences simulated and presented in real-time. The fact that thousands of simulations can be run at the same time means that meaningful insights can be generated extremely quickly.
In urgent and rapidly evolving situations such as a global pandemic, where the arrival of a new variant could suddenly change the whole scenario, providing precise answers in near real-time is fundamental to an effective public health policy response. Decision-makers must be equipped with a series of analysis and visualisation tools that allow them to interact with the simulation results and explore the impact of each decision they may want to make.
Creating a Geospatial COVID-19 Model
A network model of COVID-19 spread was placed into the Hadean decision support platform and used to simulate a disease outbreak starting in Manchester, and progressing across the United Kingdom. The time-series response of different parameters was analysed in Glasgow, Birmingham, and Manchester, including the number of infected people, the number of people in hospital, and a critical infrastructure parameter: the available hospital capacity.
If, for example, your policy target is to ensure that the number of hospital patients doesn’t exceed the number of beds in the hospital, the Decision Support Platform allows you to explore different strategies by probing the data from thousands of simulations scaled by Hadean’s technology. The data is visually represented on different graphs that can be easily analysed by the decision-makers. Several policy intervention parameters such as imposing a lockdown or a travel ban on a specific day or city can be adjusted in order to observe the consequences.
For example, if you are considering a travel ban on entering or leaving Manchester you can look at what the consequences of this action are, and understand whether this policy would be effective , or how well it would work in tandem with other policy options..
The model simplifies decision-making, allowing you to interact with multivariant models and intuitively explore the outcomes in real-time. In addition, contingencies for new data can also be considered. For example, what if a new, more infectious viral variant arrives? What if it arrives sooner or later than expected? Is your strategy still optimal in these cases?
In this way, the Decision Support Platform can also provide resilience by helping search for unexpected consequences. The lockdown policies can be adjusted in light of this contingency, to once again ensure that hospital capacity is not overwhelmed.
Watch the video below to have more information and download the whitepaper to understand more about the Hadean technology.