Update models/forge4flame.md

Co-authored-by: Robert Chisholm <[email protected]>

Author: mondus

models/forge4flame.md

@@ -5,7 +5,7 @@ permalink: "models/forge4flame"
 
 ![Testing Interventions for Infectious Disease Spread within Buildings ]({{ "/assets/images/models/forge4flame.png" | relative_url }}){: .align-right .no-shadow} 
 
-With support from the FLAME GPU team, the Department of Computer Science from the University of Turin developed Forge4Flame, a user-friendly interface that makes it easier to harness the full power of FLAME GPU 2. Specifically, the tool streamlines the design, execution, and analysis of models by automatically generating the necessary FLAME GPU 2 code and incorporating valuable visualisation and post-processing features. This makes the tool more accessible to a broader audience of researchers and public health professionals.
+The [QBio group](https://qbio.di.unito.it/) in the Department of Computer Science at the University of Turin, with support from the FLAME GPU team, developed Forge4Flame, a user-friendly interface that makes it easier to harness the full power of FLAME GPU 2. Specifically, the tool streamlines the design, execution, and analysis of models by automatically generating the necessary FLAME GPU 2 code and incorporating valuable visualisation and post-processing features. This makes the tool more accessible to a broader audience of researchers and public health professionals.
 
 By running large-scale epidemiological models of infectious disease spread within buildings on GPUs, FLAME GPU 2 enables researchers to capture complex interactions in detail and deliver results dramatically faster than traditional CPU-based approaches. This performance opens up new opportunities for exploring dynamic behaviours in epidemiology and beyond. In the COVID-19 case study, FLAME GPU 2 made it possible to model disease spread in an Italian middle school at unprecedented detail and speed, allowing rapid testing of interventions and vaccination strategies. While Forge4FLAME helped to streamline access, the true impact came from FLAME GPU 2’s ability to combine scale, speed, and accuracy. This brought advanced agent-based modelling within the reach of public health researchers, demonstrating its potential to influence decision-making in real-world crises.