More than 1% of the Dutch population is currently active on a citizen assistance platform. Examples are HartslagNu for out-of-hospital cardiac arrest and Burgernet for police investigations. Thus, there are already quite a few people willing to help in emergencies, but with more volunteers the response times could be reduced even further. And that could be life-saving. It is important to know where exactly organizations need to recruit the largest number of new volunteers. That is why Caroline Jagtenberg builds mathematical models to optimize the recruitment and dispatchment of volunteers.
Medical volunteers in Auckland
Jagtenberg got the inspiration for her research while working at the University of Auckland in New Zealand for two years. Jagtenberg: “I got in touch with the St John ambulance service for my research on ambulances. They have a system (GoodSAM) through which they alert trained volunteers for resuscitation (CPR), because they can often reach the scene faster than an ambulance can. Based on their data, I was able to build a model that allows us to estimate how many volunteers should be recruited in different parts of the city, given that people move around a city somewhat randomly during the day."
The study in which she used GoodSAM in Auckland as a case study was published in the academic journal Management Science in April.
The model can also be used in other countries looking to expand their use of community first responders. The Netherlands has already been working with community first responders who can be deployed for CPR, but there is also a lot of potential for other types of help. For example, the Red Cross recently started working with volunteers (Ready2Helpers) who can help in case of high water (for example, by helping to lay sandbags or inform residents). And the Amsterdam-Amstelland Fire Department has the ambition to recruit 100,000 citizen responders for support in the coming years. The fire fighters are fast, the neighbor is faster, is the idea behind it.
Jagtenberg is partnering with the Red Cross and the fire department, among others, to further improve community first response. "We are figuring out how volunteers can be deployed in the best way, quickly and effectively, but without people being overburdened. You don't want volunteers to be called up all the time unnecessarily, so it's important to optimize these kinds of systems," Jagtenberg explains.
SPRINTER – Strategic Prescriptive Response for Immediate Needs Through Empowered Residents
With a €500,000 research grant from Dinalog, Caroline Jagtenberg will conduct more research on citizen assistance in the coming years, together with Pieter van den Berg of Erasmus University Rotterdam and Rob van der Mei of the Center for Mathematics and Computer Science (CWI).
The SPRINTER project, a collaborative endeavour between knowledge institutes, emergency services, and volunteer dispatch systems, promises to introduce prescriptive analytics. These analytics will optimise CFR systems through innovative mathematical models utilising optimisation and machine learning algorithms. The project aims to quantify the impact of volunteers, determine optimal recruitment and training strategies, and optimise real-time alerting decisions.
SPRINTER not only presents opportunities for scientific advancement but also seeks to prepare the Netherlands for widespread CFR integration, ultimately revolutionising the country’s emergency response capabilities.
Partners in the project are the Red Cross, Fire Department Amsterdam-Amstelland, Veiligheidsregio Rotterdam-Rijnmond, Beep For Help, LIVES, NIPV, and Axira.