## 1 Introduction  
Social factors crucial to health have gained even more importance in recent decades. Advances in knowledge about risk factors and technologies for their mitigation have put disease control in the hands of public health managers. These managers play a fundamental role in deciding how, where, and when to implement new information and technologies, directly impacting who will benefit from them [1]. The growing understanding of epidemiological factors, shaped by the causes and consequences of epidemics, outbreaks, endemics, and pandemics, highlights social factors as significant health risks [2]. With increased knowledge and control, human policies and behaviours shape epidemiological outcomes, affecting existing patterns of disease and death [3]. Historically, social factors had less influence when the understanding of measures for prevention or treatment was limited. However, the effective use of this knowledge has been neglected intellectually and in terms of financial research support [4]. This has resulted in sub-optimal population health. Recognising and leveraging the influence of social factors to achieve optimal health for all can significantly improve global well-being [5]. Public health preparedness has become a critical concept in the face of global health crises, particularly highlighted by recent events such as the COVID-19 pandemic. This concept encompasses the capacity of health systems to anticipate, respond to, and recover from public health emergencies. As the authors of [6] demonstrated in their analysis of the 2022 monkeypox outbreak, clear case definitions and effective contact tracing are crucial components of preparedness, enabling rapid response to emerging threats. The connection between epidemiology and sociology, proposed in [7], identifies that social phenomena directly influence the emergence and course of diseases. Recent studies, such as [8; 9], have shown that poor socio-economic conditions are associated with a higher incidence of infectious diseases such as dengue and tuberculosis. Given this evidence, could low socio-economic status be a risk factor for COVID-19 and other future epidemics? In study [10], low income was associated with higher rates of chronic health conditions, such as diabetes and heart disease, indicating that people in lower strata are 10% more likely to develop chronic conditions, which could make COVID-19 up to 10 times more deadly [11]. This suggests that social factors influence the proliferation of infectious diseases and increase the likelihood of developing chronic diseases under unfavourable conditions. In the current coronavirus pandemic, the mortality risk for people in areas with low human development index (HDI) may be up to 10 times higher. A study conducted in Sao Paulo showed that the most privileged areas had a death rate of 0.7 per 100,000 inhabitants for the 40-44 age group, while in areas with low quality of life this figure rose to 6.7 per 100,000. This study also found that considering all age groups, the rate increased to 8.7 per 100,000. Families in these areas often lack adequate sanitation, clean water and energy and are more vulnerable. With high vulnerability, families tend to conglomerate in a few spaces in peripheral neighbourhoods and favalas, making social isolation more difficult [12]. The present study emerges as part of ongoing efforts to enhance preparedness for potential future pandemics, leveraging lessons learned during the COVID-19 crisis. We investigate how social variables influence epidemic forecasts in socio-economically vulnerable regions, utilising an adapted compartmental epidemiological model (SEPAI3R3O) and a synthetic multi-agent community. We focus on simulating epidemic dynamics in Ilha Joana Bezerra, a socio-economically disadvantaged neighbourhood in Recife, Brazil. This study examines the impact of social distancing strategies and other control measures, such as face masks and moderate social isolation.