Optimising self-organised volunteer efforts in response to the COVID-19 pandemic

Crowdsource volunteering efforts contributed significantly to pandemic response during COVID-19. In decentralised systems, volunteers collaborate rapidly to meet emergent community demands. This study quantitatively examines self-organisation in such efforts, proposing a data-driven framework to identify when and how self-organisation emerged and how it relates to organisational effectiveness. Using activity data from a mobile volunteer platform in Shenzhen, China, we find that volunteers’ task participation and social and task preferences show multiple phases of self-organisation in response to changing epidemic situations and centralised interventions. Simulation experiments indicate that self-organised volunteer systems can become more responsive and robust to uncertain community demands with minimal centralised guidance.