The COVID-19 pandemic, which caused over 6.9 million deaths worldwide, exposed critical weaknesses in healthcare systems and deepened structural inequalities, particularly in low- and middle-income countries (LMICs). In Brazil, some favela communities effectively led their responses to the crisis, creating successful initiatives based on solidarity and leveraging existing social structures, often surpassing government-led efforts and highlighting the vital role of community engagement and empowerment in public health responses. This thesis explores strategies for addressing public health emergencies in vulnerable populations, aiming to establish a comprehensive, all-hazards preparedness system for future crises. The study focuses on community-based interventions, including public health and social measures, vaccination campaigns, risk communication, infodemic management, community engagement, and cohort studies, integrating epidemiological surveillance data to mitigate COVID-19 s impact. These interventions were implemented in Complexo da Maré, one of Rio de Janeiro s largest favela complexes with over 140,000 inhabitants. The research employs advanced data analysis techniques, such as descriptive and inferential statistics, deterministic and probabilistic linkage, Inverse Probability Weighting (IPW), survival analysis, and Difference-in-Differences (DiD) analysis. The dataset includes serosurvey results, COVID-19 testing data, case and death notifications, vaccination records, and national census data. The thesis, structured as a compilation of four articles, demonstrated the effectiveness of a proposed multicomponent intervention in improving case detection, reducing mortality, and mitigating healthcare inequities in favelas. Results highlighted the impact of locally adapted strategies, such as widely distributed vaccination sites in accessible community locations with flexible hours, significantly enhancing vaccination coverage. The study also established a community-based prospective cohort study to describe COVID-19 seroprevalence, sociodemographic characteristics, and the burden of COVID-19, followed by an estimate of the association of socioeconomic factors and disease burden with seroprevalence. Our results identified critical sociodemographic, geographic, and behavioural factors influencing booster vaccine adherence, reinforcing the importance of healthcare access and socioeconomic conditions in shaping public health outcomes. These findings provided valuable insights for global health strategies and policies, particularly in guiding resource allocation and designing targeted actions to address community-specific needs. Besides, they support the establishment of a public health data repository and strengthen communication and mobilisation efforts, fostering data-driven decision-making and public health responses, especially in LMICs. By emphasising the role of community-based interventions and evidence-based policymaking, this research contributes to building more resilient and equitable healthcare systems, enhancing preparedness and response capabilities for future infectious disease outbreaks.