1 Background

The Política Nacional para a População em Situação de Rua (PNPSR) defines the population group of people experiencing homelessness (PEH) as heterogeneous, with common characteristics such as extreme poverty, interrupted or fragile family ties, and lack of regular housing [1]. The reasons why people end up living on the streets are diverse, including excessive alcohol and drug use, unemployment, violence, family conflicts, or the loss of loved ones [2]. Regardless of the causes, it is evident that this population is marginalized, with their basic human needs being denied, as well as their human and social rights [3].

Brazil is a country marked by social inequalities, and it is undeniable that the COVID-19 pandemic has affected all segments of society, including the PEH. According to data from the Instituto de Pesquisa Econômica Aplicada (IPEA) [4], homelessness in Brazil grew by 38% from 2019 to 2022, totaling 281,472 people just in the last year. This increase occurred mainly due to job loss, homelessness, and/or income loss, placing the PEH in various situations of social vulnerability that impact the basic structures necessary for life and human survival.

In light of all the aspects contributing to the violation of the basic rights of the PEH, it is important to highlight that the country has a high rate of food insecurity, which conceptually refers to the difficulty of accessing adequate food [5] in terms of quantity, quality, and regularity of access. It is primarily linked to income, as this is a guiding factor for the availability and accessibility of food [6].

It becomes important to pay attention to the income of the PEH, as it is a directly related indicator of food insecurity and limits their ability to ensure adequate nutrition. Often, this result in dependence on meals provided by charitable organizations or restricted food choices to more economical, albeit less nutritious options [7]. A study carried out with data from the Sistema de Informação de Agravos de Notificação (SINAN) and the Cadastro Único para Programas Sociais (CadÚnico) found that 90.2% of the PEH was in a situation of extreme poverty [8], which affected their access to food and basic essential services, such as healthcare.

High social inequality and the inadequacy of effective public policies exacerbate their living conditions, resulting in significant difficulties in accessing basic services such as food, hygiene, and shelter. In the realm of health, the lack of personal documents, social stigma, and the scarcity of specialized health programs create additional barriers [9] for PEH, mainly because they are more exposed to risks of infectious diseases, mental health issues, and violence, perpetuating a cycle of marginalization and vulnerability. Furthermore, it is important to emphasize that the absence of an integrated and comprehensive support network hinders these individuals from accessing adequate healthcare, further complicating the historically entrenched situation they find themselves in [10, 11].

In a literature review, we observe that various studies have been seeking to understand how and to what extent the COVID-19 pandemic has impacted the PEH. For example, in Italy [12], the strategies used by the Italian government to contain COVID-19 in this population are highlighted. A European study [13] also assessed the issue of mobility and how it impacted the spread of COVID-19. A study in China revealed the devastating impacts of the disease on these populations due to lack of food, access to healthcare, and the absence of state monitoring, uncovering the catastrophic risks of an unprecedented humanitarian crisis [14].

In the United States, there was also an evident impact of the pandemic, particularly on the social context and mental health of the PEH [15]. In Australia, a study also highlighted the impacts on the social context and mental health in the PEH of COVID-19, noting the absence of measures to mitigate the deleterious effects of the pandemic [16]. A systematic review conducted among PEH revealed that these populations are at greater risk of infection, hospitalization, and death from COVID-19 [17], focusing on clinical-biological issues.

In the Brazilian context, the existing literature on the PEH often comprehensively address the challenges faced by this population, focusing on specific geographical areas of the country [18,19,20]. However, there is a notable lack of nationwide studies addressing fundamental issues such as food insecurity and loss of income among PHE which warrant further investigation. Therefore, it is imperative to investigate issues related to food, alongside other essential survival aspects such as health, housing, and crucial social services, including nutrition and income.

In this sense, the study advances knowledge and assumes importance, even in the current post-pandemic scenario, by elucidating the impacts resulting from the COVID-19 pandemic on PEH such repercussions more intensely, mainly due to socially and structurally imposed vulnerability. Here, the study aimed to investigate the socioeconomic and healthcare access inequalities associated with increased exposure to income loss and food insecurity among PEH during the COVID-19 pandemic.

2 Methods

2.1 Study design

This is a cross-sectional [21, 22], which was conducted through field interviews from February 2021 to October 2023. This study originates from a parent research project titled “Termômetro Social—COVID-19 no Brasil”, in which the studied population was approached in the capitals of 24 Brazilian federative units and the Federal District, which together correspond to about 21.73% of the total population of Brazil [23], 17.64% of confirmed COVID-19 cases, and 45.05% of confirmed COVID-19 deaths [24] (see Table 1).

Table 1 Description of the capitals of the federative units and the Brazilian Federal District, including population numbers and confirmed cases and deaths from COVID-19
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Brazil is in the American Continent, specifically in South America, and it is considered the fifth largest country in the world in terms of territorial extension, with a land area of 8,510,417.771 km2 [25]. It is the third largest country on the continent and the largest country in South America, occupying almost 50% of its total area. Brazil shares borders with 10 of the 12 South American countries: Argentina, Bolivia, Colombia, French Guiana, Guyana, Paraguay, Peru, Suriname, Uruguay, and Venezuela, only Chile and Ecuador do not share borders with Brazil [26]. According to the Instituto Brasileiro de Geografia e Estatística (IBGE), the Brazilian population reached 203,080,756 inhabitants on August 1, 2022 [27].

2.2 Population and samples

The study population consisted of individuals who were experiencing homelessness at the time of data collection. Brazilian citizens, whether native or naturalized, who understood the language spoken in Brazil (Brazilian Portuguese), and who had been homeless for at least six months, were included, provided they were aged 18 years or older.

Due to the characteristics of the studied population, particularly their invisibility to society and the state, participation in the study was conducted through sequential sampling [28], where participants were included as they were located, whether in public places, shelters, hostels, boarding houses, or other types of temporary housing, and who promptly agreed to participate in the study. Additionally, this approach was used because it involves samples of variable size, maintaining a non-fixed sample size.

Even so, simple random sampling calculation was used for finite populations, following classical references in opinion studies, epidemiology, and surveys, according to the following parameters: confidence level 95%, random sampling error 5%, power of the test 80%, and variance 50%, since we do not know the event, with an additional 10% referring to possible losses, conforming a minimum sample of 163 people. It is worth noting that the population size used in the calculation considered the survey conducted by IPEA [4], which estimated that approximately 281,472 people were experiencing homelessness in Brazil in the year 2022.

2.3 Instruments and data collection

The study used a questionnaire that was adapted and validated for use in Brazil using the Delphi technique [29], titled ‘‘Termômetro social da COVID-19: Opinião Social’’ (https://doi.org/10.6084/m9.figshare.25917571). This instrument was originally developed and validated by researchers from the Escola Nacional de Saúde Pública da Universidade NOVA de Lisboa (ENSP-UNL) in Portugal, and it had been used in previous studies [30,31,32].

The instrument was hosted on the REDCap platform [33, 34]. The questionnaire administration was carried out by field interviewers enlisted in the study, using mobile devices (cell phones and/or tablets). The interviewers received training to minimize measurement bias. Additionally, they were asked to consider the pandemic period starting on March 11, 2020, when the World Health Organization (WHO) declared COVID-19 a pandemic [35], up to the time of the interview. The average time to complete the questionnaire was 20 to 30 min.

2.4 Study variables

2.4.1 Dependent variables

Table 2 shows the dependent variables of our study as derived from the questionnaire, along with their corresponding response patterns. Additionally, it presents the version used in the binary logistic regression analysis, which has been dichotomized into values of 0 and 1.

Table 2 Operationalization of the dependent variable under study
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Individuals who did not respond to the dependent variables were excluded from the binary logistic regression models.

2.4.2 Independent variables

The independent variables considered were:

  • Age: 18 to 29 years (1 = Yes; 0 = No); 30 to 59 years (1 = Yes; 0 = No); 60 years or older (1 = Yes; 0 = No);

  • Gender (1 = Male; 0 = Female);

  • Color/Race/Ethnicity: White (1 = Yes; 0 = No); Black/Mixed race (1 = Yes; 0 = No); Asian (1 = Yes; 0 = No); Indigenous; No color/race/ethnicity declared (1 = Yes; 0 = No);

  • Marital status: Single (1 = Yes; 0 = No); Married or in a stable union (1 = Yes; 0 = No); Widowed (1 = Yes; 0 = No); Divorced, separated, or legally separated (1 = Yes; 0 = No);

  • Having some kind of occupation or employment (1 = Yes; 0 = No);

  • Having the street as the primary form of housing (1 = Yes; 0 = No);

  • Education: No schooling and incomplete elementary education (1 = Yes; 0 = No); Complete elementary education to incomplete secondary education (1 = Yes; 0 = No); Complete secondary education to incomplete higher education (1 = Yes; 0 = No); Complete higher education or higher (1 = Yes; 0 = No);

  • Monthly family income: Less than one minimum wage (1 = Yes; 0 = No); Monthly family income above one minimum wage or more (1 = Yes; 0 = No);

  • Received any kind of government aid (1 = Yes; 0 = No);

  • Uses the Sistema Único de Saúde (Brazilian Public Health System—SUS) (1 = Yes; 0 = No).

2.5 Statistical analysis

Initially, database consistency and standardization analysis were conducted using Microsoft Office Excel 2010 software. To characterize the study participants, absolute frequency (n) and relative frequency (%) analyses were also conducted. Data were tabulated in spreadsheets using Microsoft Office Excel 2010 and imported for analysis into R software version 4.1.1 [36]. The normality distribution of quantitative variables was assessed using the Shapiro–Wilk test. Variables with p-value > 0.05 were considered to have a normal distribution.

Next, five variables of interest were selected for the construction of the maps, namely: Having some kind of occupation or employment (yes or no); Use of the SUS (yes or no); Financial difficulty in acquiring food during the COVID-19 pandemic (yes or no); Received any kind of government aid (yes or no); and temporary loss of income due to the pandemic (yes or no). The dichotomized responses were grouped according to the macroregion (North, Northeast, South, Southeast, or Midwest) of residence of the research participants, in order to visualize in which Brazilian macroregions the PEH exhibited greater social vulnerability. The variables were organized in spreadsheets using Microsoft Office Excel 2010, and then the maps were constructed with the information, using ArcGIS 10.5 software, making use of shapefiles provided by IBGE [37].

The independent variables of the final binary logistic regression model were selected in two stages. In the first stage, variables statistically associated with outcomes were identified through univariate analyzes using the Chi-square test, considering a significance level of p ≤ 0.20 [38, 39] for inclusion in multivariate models, as well as those theoretically important. The crude odds ratios (OR) were calculated along with their respective 95% confidence intervals (95% CI). In the second stage, multicollinearity was assessed to avoid the insertion of correlated variables into the model. The presence of multicollinearity was tested using the Variance Inflation Factor (VIF), one of the most used measures, defined by the following expression:

$${VIF}_{j}= \frac{1}{1- {R}_{j}^{2}}$$

where \({R}_{j}^{2}\) is the coefficient of multiple correlations resulting from regressing \({X}_{j}\) on the other p – 1 regressors. The higher the degree of dependence of \({X}_{j}\) on the remaining regressors, the stronger the dependence and the higher the value of \({R}_{j}^{2}\). A cutoff value of VIF > 10 was adopted [40].

The selection of independent variables for the final model was performed using the Backward stepwise selection method, starting with a full model (including all independent variables that had VIF < 10) and removing one variable at a time while observing the behavior of the model. The best model was selected based on the criterion of the lowest Akaike Information Criterion (AIC) value [41]. For the final model, adjusted odds ratios (aOR) were calculated along with their respective 95% CI.

After selecting the final model based on the lowest AIC value, the Hosmer–Lemeshow test was conducted to validate the model and verify the reliability and accuracy of the predictions obtained from the logistic regression analysis. Additionally, likelihood ratio test was performed to assess the adequacy of the statistical model used, identify significant variables, validate the statistical significance of results, compare different models, and provide a more robust interpretation of the statistical analysis results. The likelihood ratio test compared the null model (reference) with the full model and also with the final model. Additionally, the predictive capacity and accuracy of the models were assessed based on the area under the Receiver Operating Characteristic (ROC) curve with their respective 95%CI values [42]. All the analysis and validation tests were conducted using RStudio software, version 4.1.1 [36].

3 Results

The study involved 1,512 PEH from the capitals of 24 Brazilian states and the Federal District. The median age of the participants was 37 years (minimum = 18 and maximum = 89). The majority of the participants were male (n = 1,183; 78.2%), black/mixed race (n = 1,137; 75.2%), single (n = 1095; 72.4%), unemployed (n = 906; 59.9%), had street as the primary form of housing (n = 983; 65.0%), with incomplete elementary education (n = 596; 39.4%), with no income (n = 618; 40.9%) or a monthly family income of less than one minimum wage (n = 647; 42.8%), received some kind of government aid (n = 854; 56.5%), and used the SUS (n = 1,317; 87.1%) (see Table 3).

Table 3 Socioeconomic and health access characteristics of people experiencing homelessness included in the study, Brazil, 2021–2023 (n = 1512)
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Individuals were surveyed regarding financial difficulties in acquiring food during the COVID-19 pandemic and income loss attributable to it (see Table 4). The majority of respondents reported facing challenges in obtaining food throughout the pandemic (n = 635; 42.0%), with a significant portion also indicating a lack of income affected by the COVID-19 pandemic (n = 398; 26.3%).

Table 4 Characteristics of financial difficulties in acquiring food during the COVID-19 pandemic and and loss of income due to the pandemic among people experiencing homelessness, Brazil, 2021–2023 (n = 1512)
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In Brazil's five macroregions, the prevalence of individuals declaring no formal or informal employment was notable in four macroregions (Fig. 1a: North = 71.0%; Midwest = 58.3%; Southeast = 60.2%; South = 62.3%). These same regions showed reliance on the SUS across the board (Fig. 1b: North = 73.2%; Midwest = 92.9%; Southeast = 88.1%; South = 89.0%; Northeast = 89.6%), as well as facing financial difficulties in acquiring food during the COVID-19 pandemic (Fig. 1c: North = 76.2%; Midwest = 84.3%; Southeast = 72.6%; South = 78.8%; Northeast = 85.3%). In the North (72.7%) and Northeast (51.9%), individuals predominantly did not receive any form of government aid (see Fig. 1d). The Midwest macroregion (51.6%) had a prevalent temporary loss of income due to the pandemic (see Fig. 1e).

Fig. 1
figure 1

Prevalence of socioeconomic and health access challenges among people experiencing homelessness in Brazil's macroregions during the COVID-19 pandemic, 2021–2023

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In the first binary logistic regression analysis (refer to Table 5), it was found that male individuals (aOR = 2.00; 95% CI 1.48–2.72), black and mixed race individuals (aOR = 1.34; 95% CI 1.03–1.76), those who were married or in a stable union (aOR = 1.60; 95% CI 1.09–2.36), those who received some type of government assistance (aOR = 1.38; 95% CI 1.09–1.74), and those who utilized the SUS (aOR = 1.55; 95% CI  1.09–2.21) were more likely to experience financial difficulty in acquiring food during the COVID-19 pandemic.

Table 5 Sociodemographic variables associated with financial difficulty in acquiring food among people experiencing homelessness during the COVID-19 pandemic, Brazil, 2021–2023
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For the model validation presented in Table 5, the accuracy of the model through the area under the ROC curve was found to be 0.70. The Hosmer–Lemeshow test (p = 0.87) and likelihood ratio test (p < 0.01) were also evaluated.

With the second binary logistic regression (see Table 6), it was found that male PEH (aOR = 0.55; 95% CI 0.37–0.79), with incomplete secondary education to incomplete higher education (aOR = 0.69; 95% CI 0.49–0.98), and with monthly family income above one minimum wage or more (aOR = 0.47; 95% CI 0.30–0.75) were less likely to experience temporary income loss due to the COVID-19 pandemic. Individuals of black and mixed race (aOR = 1.64; 95% CI  1.19–2.26) and those with the street as their main form of housing (aOR = 3.10; 95% CI  2.28–4.22) had a higher likelihood of experiencing temporary income loss due to the COVID-19 pandemic.

Table 6 Sociodemographic variables associated with income loss among people experiencing homelessness due to the COVID-19 pandemic, Brazil, 2021–2023
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For the model validation presented in Table 6, the accuracy of the model through the area under the ROC curve was found to be 0.61. The Hosmer–Lemeshow test (p = 0.47) and likelihood ratio test (p < 0.01) were also evaluated.

4 Discussion

The study aimed to investigate the socioeconomic and healthcare access inequalities associated with increased exposure to income loss and food insecurity among PEH during the COVID-19 pandemic. The majority of participants were male, black/mixed race, single, unemployed, had street as the primary form of housing, with incomplete elementary education, and with a monthly family income of less than one minimum wage.

Other studies have identified the main sociodemographic characteristics present in the PEH, where 82% were men, 67% were Black, 43.21% were young, and 17.1% were illiterate [43], which is consistent with the findings of the present study. The same survey found that 70.9% of individuals reported engaging in some form of paid activity, and 58.9% had some profession, demonstrating that, despite being PEH, they are still a productive group, strongly impacted by the COVID-19 pandemic and increasing the number of unemployed individuals, as seen in this study.

The findings showed that the PEH equally had high prevalence of absence of work/occupation (formal or informal), use of the SUS, and financial difficulty in acquiring food during to the COVID-19 pandemic across the five macroregions, as well as non-receipt of government aid in the North and Northeast macroregions, and temporary income loss due to the COVID-19 pandemic in the Midwest macroregion.

The Brazilian people have unique histories, developments relative to their realities, as well as diverse population, economy, and culture [44]. Brazil is also highlighted as a country of continental proportions, with 26 states and a Federal District, and approximately 5570 municipalities [45]. These findings demonstrate that there are considerable regional disparities and inequalities, which are even more pronounced in vulnerable populations, such as in the North and Northeast macroregions, which continue to concentrate the lowest development indices and the highest numbers of municipalities with high poverty rates [46].

The research also revealed that males were less likely to face financial difficulties in acquiring food and less likely to temporarily lose their income due to the COVID-19 pandemic. Studies have shown that employment and income dynamics vary significantly between genders, with heteronormative patterns having easier access [47]. Additionally, social support networks, which play a crucial role in mitigating food insecurity and serve as a source of income support for PEH, may be more accessible to men compared to other groups [48]. This finding underscores the importance of a gender-sensitive approach in developing policies and interventions aimed at reducing food insecurity and income loss among PEH. It ensures that the specific needs of different gender identities are considered and addressed.

The COVID-19 pandemic exacerbated existing inequalities, disproportionately affecting PEH, especially black and mixed race individuals. The findings of the study showed that these groups faced greater financial difficulties in acquiring food during the COVID-19 pandemic and suffered income loss due to the health crisis. This highlighted a troubling combination of economic and food insecurity, which was heightened primarily by the physical distancing measures imposed during the pandemic [49].

Historically, black and mixed race individuals have been marginalized and excluded from economic, educational, and labor market opportunities, in addition to having lower wage levels in the job market. Vasquez Reyes [50] highlights in his study that about 40% of African American workers, besides having low wages, are employed in jobs that deny them paid sick leave.

In this sense, it is observed that the lack of access to support services and basic resources significantly increases the vulnerability of black and mixed race individuals, especially those experiencing homelessness, highlighting the intersection between the health crisis and racial inequalities. The absence of effective policies for social and economic inclusion targeted at homeless individuals during the pandemic underscored the urgent need for more focused approaches to improving living conditions and ensuring access to essential goods and services.

The family's financial management is significantly influenced by contextual factors of social, cultural, and economic nature, which shape the living conditions in a society. The findings revealed that individuals who were married or in a stable union were more likely to experience financial difficulty in acquiring food during the COVID-19 pandemic. This finding prompts us to consider potential income reductions due to financial setbacks caused by disruptions in the labor market during the pandemic, whether through reduced work hours or the need to suspend work activities [51].

Furthermore, the additional pressure on family finances may stem from challenges faced by the fact that the more productive member of the couple, regardless of gender, tends to devote more time to the labor market, be it formal or informal, while the other reduces their participation to focus on family and household responsibilities [52], mainly when they previously relied on external services such as daycare [53] and household responsibilities [42], mainly when they previously relied on external services such as daycare and subsidized school meals, which were disrupted, limited, or lost during the pandemic [54]. Thus, these findings underscore the importance of policies and support programs targeted at families during health crises, aiming to mitigate the negative impacts that lead to income deficits for families.

It is important to note that the relationship between educational level and economic factors associated with food acquisition during the COVID-19 pandemic was observed in this study. Individuals with completed high school and incomplete higher education had a lower probability of experiencing temporary income loss due to the COVID-19 pandemic. A study conducted in Vietnam found that education was associated with increased family income [55]. These observations highlight the importance not only of education itself but also of the skills acquired and the potential capacity to navigate available resources, providing them with skills or access to opportunities that can mitigate adverse socioeconomic impacts resulting from the pandemic.

Another aspect to highlight is the relationship between monthly family income above one minimum wage and a lower probability of experiencing temporary income loss due to the COVID-19 pandemic. This finding is consistent with a study conducted in California, which found that income and job loss were more pronounced among PEH compared to low-income Californians [56]. In this sense, there may be a relationship between the level of family income and the ability to cope with the impacts of the pandemic, as those with higher income have additional resources to mitigate food insecurity.

Receiving government aid showed a relationship with a greater probability of having financial difficulties in acquiring food during the COVID-19 pandemic. This finding highlights the importance of social assistance coverage as mechanisms to meet the needs for income security, health, employment, education, food, and decent housing [57]. However, it is important to note that PEH face several difficulties in accessing these benefits, such as limited access to the internet, lack of electronic devices, and insufficient civil documentation [58, 59], putting this population at a social disadvantage.

This context reinforces the notion that PEH were particularly affected by the pandemic and government actions. Studies have shown that during the pandemic, there was a reduction in access to social and health assistance for PEH, along with an increase in diseases and infections [60]. Social assistance benefits play a crucial role in maintaining the income of PEH, considering that work activities were heavily impacted due to isolation and physical distancing measures [59, 61].

Indeed, addressing the pandemic depended on strengthening the SUS, recognizing its role in providing care to the population and its value for public good. Therefore, it is important to understand the relationship between the use of SUS and a higher probability of experiencing financial difficulty in acquiring food during the COVID-19 pandemic. SUS is one of the largest and most complex public health systems in the world, covering everything from primary health care to specialized care (secondary and tertiary), which includes outpatient and specialized hospital care, respectively, of medium and high complexity [62]. It is important to note the increased demand for high-complexity health care services by PEH during the pandemic, especially in terms of hospitalization numbers [63,64,65]. A study conducted with PEH in New York found that 64% of those with confirmed cases were hospitalized [66], making this an aspect that impacts individual and/or family income due to the need to take time off work (formal or informal).

The findings also demonstrated that individuals whose primary residence was the street had a higher probability of experiencing temporary income loss due to the COVID-19 pandemic. The lack of stable housing not only exposes these individuals to a limited social support network but also places them in a position of extreme economic vulnerability, making them more susceptible to various diseases and infections [67,68,69,70]. It is important to highlight that homelessness has been increasing in several countries during the pandemic, as evidenced by a study conducted in Canada, which showed an average of over 235,000 PEH in 2021 [71]. A study conducted in France revealed that 77% of PEH reported facing significant financial challenges [72]. This condition exposes the most vulnerable individuals to numerous consequences [73, 74], both economic and social.

The study has contributed to the understanding of inequalities among PEH during the COVID-19 pandemic. It is the first study conducted extensively in Brazil, recruiting PEH from all five macroregions. The findings reveal disparities in the adoption of inclusive measures across different regions, with some areas demonstrating more comprehensive support for this population than others. The pandemic has disproportionately affected not only the entire Brazilian population but particularly PEH, as revealed by the study. Aligned with the United Nations' 17 Sustainable Development Goals [75], the study's contribution lies in providing evidence to promote social policy and therefore greater access to fundamental goods for human development, fostering fairness, and enhancing dignity.

5 Strengths and limitations of the study

The main limitation of this study is the possibility of information bias. However, several measures were taken to mitigate this bias, such as conducting a pilot study and using a questionnaire validated by researchers with expertise in the themes addressed in the research. Additionally, participants were recruited only in the capitals of the 24 Brazilian states and the Federal District; however, these territories were chosen because these populations mainly migrate to major cities in search of better living and health conditions and opportunities.

The findings presented here, from a non-probabilistic sample, although not generalizable to the reality of all PEH in Brazil, advance knowledge by contributing an important portrait of the factors associated with food insecurity and loss of income in the individuals studied. This sheds light on these populations, which are still invisible to the government and public policies, and which still suffer from the depreciative nature that society attributes to them, leading to discriminatory, oppressive, and stigmatizing practices. In addition, being a cross-sectional study, there is a limitation stemming from the absence of temporal continuity. Without following the participants longitudinally, it was not possible to observe progressive changes in the variables of interest or to assess the effects of interventions or exposures over time.

6 Implications of the study

The study results point to significant impacts of the COVID-19 pandemic on the PSR in Brazil, highlighting the urgent need for appropriate and effective interventions in public policies and health services. The pandemic has exacerbated unemployment, loss of income, food insecurity, and other social inequalities seen in the present study. These issues, combined, make the situation especially concerning for the PSR, especially during a health crisis.

The study serves as a way to demonstrate areas where coordinated efforts are needed to provide adequate assistance to the PSR in Brazil, including measures to ensure access to food, promote job opportunities, and ensure the availability of quality health services, both physical and mental. In addition, the study suggests the need to improve and expand government assistance programs, to help mitigate the various repercussions of a health crisis, mainly the loss of income observed during the pandemic. In short, the findings should be taken into account by public policy makers and health professionals, in order to develop and implement strategies that can mitigate these impacts and provide more effective support to the PSR in the context of a health crisis.

7 Conclusions

The study aimed to investigate the socioeconomic and healthcare access inequalities associated with increased exposure to income loss and food insecurity among people experiencing homelessness during the COVID-19 pandemic. This study provides a clear reflection of the multiplicity of social and structural challenges that were exacerbated during the COVID-19 pandemic.

Based on the descriptive analysis, a critical view of the socioeconomic aspects of PEH was noticeable, bringing to light the clear social inequality intrinsic to this group, seen through the prevalence of black and mixed race people, with no employment, using the streets as their main form of residence, with lower levels of education, and little to no financial income. These characteristics perpetuate a profile historically linked to social exclusion and limited access to opportunities within society, in addition to demonstrating how homeless people became even more exposed and vulnerable during the COVID-19 pandemic.

Therefore, it is essential to promote collaborative action strategies among various groups, institutions, and sectors to guide the formulation of effective public policies aimed at reducing the vulnerabilities faced by these individuals. Such policies should focus not only on meeting immediate needs but also on addressing the root causes of exclusion and promoting long-term social and economic inclusion.