This chapter discusses resilience in informal settlements amid the COVID-19 pandemic of 2019–2022, focussing on the case of Favela Paraisópolis, a large informal settlement in São Paulo, Brazil. It highlights the importance of community organisation in building resilience while arguing the importance of the State's action in structuring informal spaces as a condition for greater success of community resilience. It seeks to clarify factors leading to community resilience in Paraisópolis and whether these factors can contribute to an expanded understanding of the concept. It does so by revisiting resilience theory and conducting a critical analysis of the history of the pandemic inside the favela, informed by interviews with key stakeholders and health and demographic statistics. It subsequently highlights the limits of these actions organised by an economically and politically oppressed population that lacks the necessary capital to face a health crisis of this magnitude. It draws attention to the risks of a neoliberal appropriation of the concept of resilience as a narrative that delegates the solution of societal problems solely to individuals and communities, taking the State off the hook. Finally, it highlights the power of resilience as a dimension of oppressed communities’ struggles for effective public policies.

Purpose: Compensation for respiratory motion is important during abdominal cancer treatments. In this work we report the results of the 2015 MICCAI Challenge on Liver Ultrasound Tracking and extend the 2D results to relate them to clinical relevance in form of reducing treatment margins and hence sparing healthy tissues, while maintaining full duty cycle. Methods: We describe methodologies for estimating and temporally predicting respiratory liver motion from continuous ultrasound imaging, used during ultrasound-guided radiation therapy. Furthermore, we investigated the trade-off between tracking accuracy and runtime in combination with temporal prediction strategies and their impact on treatment margins. Results: Based on 2D ultrasound sequences from 39 volunteers, a mean tracking accuracy of 0.9 mm was achieved when combining the results from the 4 challenge submissions (1.2 to 3.3 mm). The two submissions for the 3D sequences from 14 volunteers provided mean accuracies of 1.7 and 1.8 mm. In combination with temporal prediction, using the faster (41 vs 228 ms) but less accurate (1.4 vs 0.9 mm) tracking method resulted in substantially reduced treatment margins (70% vs 39%) in contrast to mid-ventilation margins, as it avoided non-linear temporal prediction by keeping the treatment system latency low (150 vs 400 ms). Acceleration of the best tracking method would improve the margin reduction to 75%. Conclusions: Liver motion estimation and prediction during free-breathing from 2D ultrasound images can substantially reduce the in-plane motion uncertainty and hence treatment margins. Employing an accurate tracking method while avoiding non-linear temporal prediction would be favorable. This approach has the potential to shorten treatment time compared to breath-hold and gated approaches, and increase treatment efficiency and safety.