Managing Patients with Immune-Mediated Inflammatory Diseases on Disease-Modifying Antirheumatic Drug Therapy in a COVID-19 Endemic World: A Narrative Review and Expert Insights (preprint)

During the coronavirus disease 2019 (COVID-19) pandemic, individuals with immune-mediated inflammatory diseases (IMIDs), such as systemic lupus erythematosus and rheumatoid arthritis, face a heightened risk of infection and severe outcomes due to immunological alterations resulting from their underlying conditions and immunosuppressive treatments. Even as the pandemic has transitioned to an endemic state, it remains crucial to recognize that these patients continue to be at risk. In this narrative review, we analyzed existing literature to explore the impact of IMIDs, clinical risk factors, and the influence of immunosuppressive therapies on COVID-19-related risks and outcomes. Notably, certain disease-modifying antirheumatic drugs (DMARDs), like rituximab, are associated with worse COVID-19 outcomes, and rituximab-treated patients show impaired immune responses to COVID-19 vaccination. Additionally, we outline the diverse effects of glucocorticoids on COVID-19 outcomes and management. To highlight real-life challenges faced by clinicians caring for patients with IMIDs, we present an illustrative scenario that underscores the importance of effective vaccination, timely boosting, and additional mitigation strategies against COVID-19. Given the clinical heterogeneity and diverse disease states within IMIDs, it is crucial to understand the ongoing implications and risks associated with COVID-19 in these patients, to guide the implementation of appropriate measures and optimize care and outcomes in the current endemic era.

Perceptions of COVID-19 Vaccination among Organ Transplant Recipients (preprint)

Understanding vaccine hesitancy in organ transplant recipients (OTR) is critical, given clear, alt-hough attenuated, benefits from vaccination. Adult OTR were surveyed regarding vaccine-related values and a novel outcome variable called Vaccine Acceptance Composite Score (VACS) was built as the average Likert score of 7 domains of vaccination confidence. Of 46 OTR included (93.5% kidney transplant recipients), 32.6% were female, 13.3% Black, 6.77% Hispan-ic/Latino/a/x; median age was 58 years. Patients were most concerned about COVID-19 vac-cine-associated risks (46.3%), its potential effect on allograft (47.6%) and motives of government officials involved with vaccine policy (55.6%). Politically conservative patients were likely to have a significantly lower VACS, while those who lived with someone ≥65 had a higher VACS. The VACS was not significantly associated with race, income, religious beliefs, comorbidities, COVID-19 history, or influenza vaccination status. Higher VACS was significantly associated with ≥3 and ≥4 COVID-19 immunizations. This study highlighted political beliefs and elderly household members as correlates of vaccine acceptance among OTR. The VACS may be a useful tool to help standardize multifaceted analyses in vaccination-focused behavioral research, as well as identify individuals and groups at risk for vaccine hesitancy, who may benefit from tai-lored outreach and educational interventions.

Burnout in Medical Specialists Redeployed to Emergency Care During the COVID-19 Pandemic (preprint)

Burnout represents a concern for all healthcare providers, particularly those specializing in emergency medical care for whom burnout outcomes have been well-documented. What remains unknown is the effect of burnout on redeployed medical specialists during the COVID-19 pandemic from an appointment-centered practice to emergency care directed by public health considerations. This research aims to identify and assess the burnout responses of fourteen medical specialties noted in searched returns of the four most cited articles published since 2020 about non-emergency physicians regarding their burnout brought on by the unanticipated need for them to provide emergency care during the recent pandemic. The hypothesis is that medical specialists accustomed to planning for emergency possibilities in their appointment-centered practice would demonstrate the least burnout regarding COVID-19-related emergencies. Considering coping as a process based on Lazarus's research, comparing and ranking the COVID-19 emergency responses across the various normally appointment-centered medical specialties in their employed coping strategies determines the outcome. With the hypothesis supported, suggested interventions for future pandemics—when these specialists are, again, redeployed to emergency care directed by public health considerations—are those coping strategies identified as most effective in reducing burnout while maintaining the viability of the medical specialty and excellent patient care.

The Psychological Ability to Cope Reduced Infections During the Pandemic: A Two-Year Population-Based Study of The Determinants of 123 Million COVID-19 Test Results in Denmark (preprint)

During the COVID-19 pandemic, a key concern for authorities was to identify and activate the psychological states most likely to motivate the public to engage in protective behavior such as physical distancing and hygienic protection. While feelings of fear and threat were rampant during the pandemic, theories of health psychology have highlighted appraisals related to the ability to cope (e.g., the feeling of being able to cost-effectively adhere to government advice) and argued that coping appraisals are superior predictors of motivations to protect the self against risks. In this study, we provide a massive population-based comparison of the association between, on the one hand, threat appraisals, and coping appraisals and, on the other hand, protection against actual infection during the COVID-19 pandemic. To this end, we utilize a unique data infrastructure from Denmark that couple surveys of 8 % of the adult Danish population (N= 386.633) with the individual results of all 123 million COVID-19 tests performed in Denmark during 23 months of the COVID-19 pandemic. Overall, controlling for a comprehensive range of sociodemographic measures and employing panel data to bolster internal validity, we observe that stronger coping appraisals are consistently associated with lower individual probability of COVID-19 infection risk. We find no con-sistent evidence for a similar association for threat appraisals. Threat appraisals rather seem to index – to some extent, accurately – individual feelings of infection exposure. As appeals to fear also have unintended negative consequences (includ-ing anxiety, fatigue, and stigmatization), the findings provide strong empirical support for relying on coping-oriented public health communication in future societal crises in the domain of health and beyond.

Retrospective Analysis of Clostridioides difficile Infection Rates in Hospitalized Patients during COVID-19 Pandemic. A Unicenter Study in Reus, Spain (preprint)

.Background: Clostridioides difficile infections (CDI) vary in severity from mild diarrhea to life-threatening conditions like pseudomembranous colitis or toxic megacolon, often leading to sepsis and death. The COVID-19 pandemic prompted changes in healthcare practices, potentially affecting CDI incidence, though reported data are inconclusive. We studied factors influencing CDI incidence and outcomes at a university hospital throughout the COVID-19 pandemic years. Methods: We conducted a retrospective study on all adult hospitalized CDI cases from January 1, 2020, to December 31, 2022. We collected demographic information, comorbid conditions, and concurrent infections. Results: While overall CDI and COVID-19 rates decreased in 2022, a nota-ble increase in CDI infections was observed among oncological patients and those undergoing some aggressive treatments, such as colon or gastroscopies. The prevalence of comorbidities remained unmodified, and there were declines in prior gastrointestinal surgeries and proton pump inhibitor prescriptions. Factors associated with patient fatality or prolonged hospitaliza-tion included older age, cancer, chronic kidney disease, higher Charlson and McCabe indices, elevated C-reactive protein, and low albumin concentrations. Conclusion: Our study shows the evolving landscape of CDI during the COVID-19 pandemic and emphasizes the impact of de-layed diagnoses and treatments exacerbated by telemedicine adoption. Identified risk factors for CDI-related mortality or prolonged hospital stays underscore the importance of targeted inter-ventions in high-risk populations.

Saving High-Risk Patients from COVID-19 Severity and Death Mainly with Plant-Based Diets and Supplements (preprint)

Our report presents the findings from a treatment program that involved plant-based diets (PBDs) and supplements for 1,750 elderly cardiology patients diagnosed with COVID-19 between April 2020 and June 2023. At the start of the program, there was no published data supporting the use of PBDs for COVID-19 patients. However, after 18 months, studies were released that indicated the effectiveness of PBDs in decreasing the incidence and severity of COVID-19. Our treatment protocol differed from these studies in several ways. We carefully controlled the quality, quantity, and processing method of the foods we provided, opting for raw instead of cooked vegetables. Additionally, we incorporated supplementation that complemented the nutrients lacking in a PBD and enhanced the anti-viral, anti-inflammatory, antioxidant, antithrombotic, and immunomodulatory properties of a PBD. Our patients recovered faster (12±1.4 days vs. 20.9±4.3 days), with lower severity (2% vs. 10-20%), hospitalizations (0 vs. 5-10%), and deaths (0 vs. 15-17%) compared to the general population. These favorable outcomes are particularly noteworthy given Indonesia's high COVID-19 morbidity and mortality rates, among the highest in Asia. The findings of this report provide valuable insights for practitioners in managing high-risk elderly COVID-19 patients, particularly in avoiding severity and mortality.

SARS-CoV-2 spike S2 subunit inhibits p53 activation of p21(WAF1), TRAIL Death Receptor DR5 and MDM2 proteins in cancer cells (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and COVID-19 infection has led to worsened outcomes for patients with cancer. SARS-CoV-2 spike protein mediates host cell infection and cell-cell fusion that causes stabilization of tumor suppressor p53 protein. In-silico analysis previously suggested that SARS-CoV-2 spike interacts with p53 directly but this putative interaction has not been demonstrated in cells. We examined the interaction between SARS-CoV-2 spike, p53 and MDM2 (E3 ligase, which mediates p53 degradation) in cancer cells using an immunoprecipitation assay. We observed that SARS-CoV-2 spike protein interrupts p53-MDM2 protein interaction but did not detect SARS-CoV-2 spike bound with p53 protein in the cancer cells. We further observed that SARS-CoV-2 spike suppresses p53 transcriptional activity in cancer cells including after nutlin exposure of wild-type p53-, spike S2-expressing tumor cells and inhibits chemotherapy-induced p53 gene activation of p21(WAF1), TRAIL Death Receptor DR5 and MDM2. The suppressive effect of SARS-CoV-2 spike on p53-dependent gene activation provides a potential molecular mechanism by which SARS-CoV-2 infection may impact tumorigenesis, tumor progression and chemotherapy sensitivity. In fact, cisplatin-treated tumor cells expressing spike S2 were found to have increased cell viability as compared to control cells. Further observations on gamma-H2AX expression in spike S2-expressing cells treated with cisplatin may indicate altered DNA damage sensing in the DNA damage response pathway. The preliminary observations reported here warrant further studies to unravel the impact of SARS-CoV-2 and its various encoded proteins including spike on pathways of tumorigenesis and response to cancer therapeutics.

Characterization of spike processing and entry mechanisms of seasonal human coronaviruses NL63, 229E and HKU1 (preprint)

Although much has been learned about the entry mechanism of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the details of entry mechanisms of seasonal human coronaviruses (HCoVs) remain less well understood. In the present study, we established that 293T cell lines that stably express angiotensin converting enzyme (ACE2), aminopeptidase N (APN), or transmembrane serine protease 2 (TMPRSS2) support high level transduction of lentiviral pseudoviruses bearing spike proteins of seasonal HCoVs, HCoV-NL63, -229E, or -HKU1, respectively. Our results showed that entry of HCoV-NL63, -229E and -HKU1 pseudoviruses is sensitive to endosomal acidification inhibitors (chloroquine and NH4Cl), indicating virus entry via the endocytosis route. Although HCoV-HKU1 pseudovirus infection requires TMPRSS2 expression on cell surface, endocytosis-mediated HCoV-HKU1 entry requires the serine protease domain but not the serine protease activity of TMPRSS2. We also show that amino acids in the predicted S1/S2 junctions of spike proteins of HCoV-NL63, and -229E are essential for optimal entry but non-essential for spike-mediated entry of HCoV-HKU1. Our findings provide insights into entry mechanism of seasonal HCoVs that may support the development of novel treatment strategies.

Associations between SARS-CoV-2 Infection or COVID-19 Vaccination and Human Milk Composition: A Multi-Omics Approach (preprint)

The risk of contracting SARS-CoV-2 via human milk-feeding is virtually non-existent. Adverse effects of COVID-19 vaccination for lactating individuals are not different from the general population, and no evidence has been found that their infants exhibit adverse effects. Yet, there remains substantial hesitation among this population globally regarding the safety of these vaccines. Herein we aimed to determine if compositional changes in milk occur following infection or vaccination, including any evidence of vaccine components. Using an extensive multi-omics approach, we found that compared to unvaccinated individuals SARS-CoV-2 infection was associated with significant compositional differences in 67 proteins, 385 lipids, and 13 metabolites. In contrast, COVID-19 vaccination was not associated with any changes in lipids or metabolites, although it was associated with changes in 13 or fewer proteins. Compositional changes in milk differed by vaccine. Changes following vaccination were greatest after 1-6 hours for the mRNA-based Moderna vaccine (8 changed proteins), 3 days for the mRNA-based Pfizer (4 changed proteins), and adenovirus-based Johnson and Johnson (13 changed proteins) vaccines. Proteins that changed after both natural infection and Johnson and Johnson vaccine were associated mainly with systemic inflammatory responses. In addition, no vaccine components were detected in any milk sample. Together, our data provide evidence of only minimal changes in milk composition due to COVID-19 vaccination, with much greater changes after natural SARS-CoV-2 infection.

Machine Learning for Affordable Diagnosis of SARS-COV-2 from Hematological and Biochemical Tests (preprint)

COVID-19, caused by the SARS-CoV-2 virus, has spread around the world and killed around 6.9 million people. Rapid and accurate diagnosis is essential for preventing and controlling the disease, reducing transmission and consequently saving lives. RT-PCR is the gold standard test used to detect the disease. However, the test is expensive and the result is time-consuming, which makes mass testing difficult, especially in countries with limited resources. In addition, the test has high analytical specificity and low diagnostic sensitivity, which leads to false-negative results. Several studies in the literature report the presence of hematological and biochemical alterations in infected patients and use these alterations with machine learning algorithms to help diagnose the disease. Therefore, this article presents the results obtained by different neural network architectures based on Adaptive Resonance Theory (ART) for the diagnosis of COVID-19. The study was conducted in two distinct stages: the first consisted of selecting the best ART network among several, using three open-access datasets and comparing the results with the literature. In the second stage, the chosen model was tested on a dataset containing patients from various hospitals in four countries. In addition, the model was subjected to external validation, including data from a country not present during the training and adjustment of the model, in order to validate the robustness and generalization capacity of the model. The results obtained by the ART networks in this study are promising, outperforming not only classical models, but also the deep learning models often used in the literature. Validation on data from different countries strengthens the model’s reliability and effectiveness.

Precision medicine for pandemics: stratification of COVID-19 molecular phenotypes defined by topological analysis of global blood gene expression. (preprint)

Precision medicine offers a promising avenue for better therapeutic responses to pandemics such as COVID-19. This study leverages independent patient cohorts in Florence and Liege gathered under the umbrella of the DRAGON consortium for the stratification of molecular phenotypes associated with COVID-19 using topological analysis of global blood gene expression. Whole blood from 173 patients was collected and RNA was sequenced on the Novaseq platform. Molecular phenotypes were defined through topological analysis of gene expression relative to the biological network using the TopMD algorithm. The two cohorts from Florence and Liege allowed for independent validation of the findings in this study. Clustering of the topological maps of differential pathway activation revealed three distinct molecular phenotypes of COVID-19 in the Florence patient cohort, which were also observed in the Liege cohort. Cluster 1, was characterised by high activation of pathways associated with ESC pluripotency, NRF2, and TGF-B; receptor signalling. Cluster 2 displayed high activation of pathways including focal adhesion-PI3K-Akt-mTOR signalling and type I interferon induction and signalling, while Cluster 3 exhibited low IRF7-related pathway activation. TopMD was also used with the Drug-Gene Interaction Database (DGIdb), revealing pharmaceutical interventions targeting mechanisms across multiple phenotypes and individuals. The data illustrates the utility of molecular phenotyping from topological analysis of blood gene expression, and holds promise for informing personalised therapeutic strategies not only for COVID-19 but also for Disease X. Its potential transferability across multiple diseases highlights the value in pandemic response efforts, offering insights before large-scale clinical studies are initiated.

A Critical Analysis of UK Media Characterisations of Long Covid in Children and Young People (preprint)

Long Covid is the continuation or development of symptoms related to a SARSCoV2 infection. Those with Long Covid may face epistemic injustice, where they are unjustifiably viewed as unreliable evaluators of their own illness experiences. Media articles both reflect and influence perception and subsequently how people regard children and young people (CYP) with Long Covid, and may contribute to epistemic injustice.? We aimed to explore how the UK media characterises Long Covid in CYP through examining three key actor groups: parents, healthcare professionals, and CYP with Long Covid, through the lens of epistemic injustice. A systematic search strategy resulted in the inclusion of 103 UK media articles. We used an adapted corpus-assisted Critical Discourse Analysis in tandem with thematic analysis. Specifically, we utilised search terms to locate concordances of key actor groups. In the corpus, parents highlighted minimisation of Long Covid, barriers to care, and experiences of personal attacks. Mothers were presented as also having Long Covid. Fathers were not mentioned once. Healthcare professionals emphasised the rarity of Long Covid in CYP, avoided pathologizing Long Covid, and overemphasised psychological components. CYP rarely were consulted in media articles but were presented as formerly very able. Manifestations of Long Covid in CYP were validated or invalidated in relation to adults. Media characterisations contributed to epistemic injustice. The disempowering portrayal of parents promote stigma and barriers to care. Healthcare professionals' narratives often contributed to negative healthcare experiences and enacted testimonial injustice, where CYP and parents credibility was diminished due to unfair identity prejudice, in their invalidation of Long Covid. Media characterisations reveal and maintain a lack of societal framework for understanding Long Covid in CYP. The findings of this study illustrate the discursive practices employed by journalists that contribute to experiences of epistemic injustice. Based on our findings, we propose recommendations for journalists.

The asymptomatic proportion of SARS-CoV-2 Omicron-variant infections in households: A systematic review (preprint)

Background Understanding the clinical spectrum of SARS-CoV-2 infection, including the asymptomatic fraction, is important as asymptomatic individuals are still able to infect other individuals and contribute to ongoing transmission. The WHO Unity Household transmission investigation (HHTI) protocol provides a platform for the prospective and systematic collection of high-quality clinical, epidemiological, serological, and virological data from SARS-CoV-2 confirmed cases and their household contacts. These data can be used to understand key severity and transmissibility parameters - including the asymptomatic proportion - in relation to local epidemic context and help inform public health response. Methods We aimed to estimate the asymptomatic proportion of SARS-CoV-2 Omicron-variant infections in Unity-aligned HHTIs. We conducted a systematic review and meta-analysis in alignment with the PRISMA 2020 guidelines and registered our systematic review on PROSPERO (CRD42022378648). We searched EMBASE, Web of Science, MEDLINE, and bioRxiv and medRxiv from 1 November 2021 to 22 August 2023. Results We identified 8,368 records, of which 98 underwent full text review. We identified only three studies for data extraction, with substantial variation in study design and corresponding estimates of the asymptomatic proportion. As a result, we did not generate a pooled estimate or I2 metric. Conclusions The limited number of quality studies that we identified highlights the need for improved preparedness and response capabilities to facilitate robust HHTI implementation, analysis and reporting, to better inform national, regional and global risk assessments and policy making.

Physical activity, low-grade inflammation, and psychological responses to the COVID-19 pandemic among older adults in England (preprint)

Mental health responses to the COVID-19 pandemic have been widely studied, but less is known about the potentially protective role of physical activity (PA) and the impact of low-grade inflammation. Using a sample of older adults from England, this study tested (1) if pre-pandemic PA and its changes during the pandemic were associated with mental health responses; (2) if older adults with low-grade inflammation experienced greater increases in depression and anxiety, compared to pre-pandemic levels; (3) if PA attenuated the association between inflammation and depression/anxiety. The study used data from the English Longitudinal Study of Ageing, a cohort study following a national sample aged 50+. Information on mental health and PA were collected before the pandemic (2016/17 and 2018/19) and during November and December 2020. Inflammation was ascertained using pre-pandemic C-reactive protein (CRP). Analyses were adjusted for sociodemographic and health-related factors and pre-pandemic mental health. Increasing PA from before to during the pandemic was linked to reduced odds of depression (OR = 0.955, 95%CI [0.937, 0.974]) and anxiety (OR = 0.954, 95%CI [0.927; 0.982]). Higher pre-pandemic PA was associated with reduced odds of depression (OR = 0.964, 95%CI [0.948, 0.981]) and anxiety (OR = 0.976, 95%CI [0.953, 1.000]), whereas elevated CRP was associated with 1.343 times higher odds of depression (95%CI [1.100, 1.641]). PA did not attenuate the inflammation-depression association. The findings suggest that PA may contribute to psychological resilience among older adults, independently of inflammation. Further research is needed to explore the psychobiological pathways underlying this protective mechanism.

Precision Phenotyping for Curating Research Cohorts of Patients with Post-Acute Sequelae of COVID-19 (PASC) as a Diagnosis of Exclusion (preprint)

Scalable identification of patients with the post-acute sequelae of COVID-19 (PASC) is challenging due to a lack of reproducible precision phenotyping algorithms and the suboptimal accuracy, demographic biases, and underestimation of the PASC diagnosis code (ICD-10 U09.9). In a retrospective case-control study, we developed a precision phenotyping algorithm for identifying research cohorts of PASC patients, defined as a diagnosis of exclusion. We used longitudinal electronic health records (EHR) data from over 295 thousand patients from 14 hospitals and 20 community health centers in Massachusetts. The algorithm employs an attention mechanism to exclude sequelae that prior conditions can explain. We performed independent chart reviews to tune and validate our precision phenotyping algorithm. Our PASC phenotyping algorithm improves precision and prevalence estimation and reduces bias in identifying Long COVID patients compared to the U09.9 diagnosis code. Our algorithm identified a PASC research cohort of over 24 thousand patients (compared to about 6 thousand when using the U09.9 diagnosis code), with a 79.9 percent precision (compared to 77.8 percent from the U09.9 diagnosis code). Our estimated prevalence of PASC was 22.8 percent, which is close to the national estimates for the region. We also provide an in-depth analysis outlining the clinical attributes, encompassing identified lingering effects by organ, comorbidity profiles, and temporal differences in the risk of PASC. The PASC phenotyping method presented in this study boasts superior precision, accurately gauges the prevalence of PASC without underestimating it, and exhibits less bias in pinpointing Long COVID patients. The PASC cohort derived from our algorithm will serve as a springboard for delving into Long COVID's genetic, metabolomic, and clinical intricacies, surmounting the constraints of recent PASC cohort studies, which were hampered by their limited size and available outcome data.

A spatio-temporal model to detect potential outliers in disease mapping (preprint)

Spatio-temporal disease mapping models are commonly used to estimate the relative risk of a disease over time and across areas. For each area and time point, the disease count is modelled with a Poisson distribution whose mean is the product of an offset and the disease relative risk. This relative risk is commonly decomposed in the log scale as the sum of fixed and latent effects. The Rushworth model allows for spatio-temporal autocorrelation of the random effects. We build on the Rushworth model to accommodate and identify potentially outlying areas with respect to their disease relative risk evolution, after taking into account the fixed effects. An area may display outlying behaviour at some points in time but not all. At each time point, we assume the latent effects to be spatially structured and include scaling parameters in the precision matrix, to allow for heavy-tails. Two prior specifications are considered for the scaling parameters: one where they are independent across space and one with spatial autocorrelation. We investigate the performance of the different prior specifications of the proposed model through simulation studies and analyse the weekly evolution of the number of COVID-19 cases across the 33 boroughs of Montreal and the 96 French departments during the second wave. In Montreal, 6 boroughs are found to be potentially outlying. In France, the model with spatially structured scaling parameters identified 21 departments as potential outliers. We find that these departments tend to be close to each other and within common French regions.

Completeness of the COVID-19 Vaccination Schedule among Persons Experiencing Homelessness in Brazil (preprint)

Almost four years after COVID-19 was declared a global health emergency, equitable distribution of the vaccine remains a challenge, especially among homeless people, the fastest growing population in Brazil. Therefore, we sought to identify the factors associated with completion of the COVID-19 vaccination schedule among homeless people in Brazil. Materials and Methods: We carried out a cross-sectional study in the capital cities of Brazil's Federative Units, considering people living on the streets as the target population. We used a sequential inclusion approach, with individual interviews conducted by trained professionals, using a validated questionnaire. We used descriptive statistics to analyze the data and a binary logistic regression model to identify factors associated with homeless individuals who completed the COVID-19 vaccination schedule. Results: It was identified that the highest density of homeless people and indicators related to COVID-19 is located in the Northeast, Southeast and South regions of Brazil. The primary data sample consisted of 1,392 participants, predominantly male (n: 961; 69.0%), with an average age of 38.3±15.2 years, belonging to the black/brown race/color (n: 1,097; 78.8%), with an elementary school education (n: 1,060; 76.1%). The factors associated with completing the vaccination schedule were: receiving government aid (OR: 1.58; 95%CI: 1.09 - 2.30), visits from Health Agents from the Street Clinic (OR: 3.19; 95%CI: 1.95 - 5.36), history of COVID-19 (OR: 5.77; 95%CI: 3.17 - 11.15), support for mandatory vaccination against COVID-19 (OR: 3.76; 95%CI: 2.48 - 5.76), trust in the efficacy of vaccines (OR: 3.92; 95%CI: 2.63 - 5.89), seeking information from NGOs, street clinics, community leaders (OR: 1.91; 95%CI: 1.01 - 3.88) and trust in the Federal Government's statements on vaccines (OR: 1.57; 95%CI: 1.06 - 2.31).Conclusion: The study advances knowledge by highlighting the completeness of the COVID-19 vaccination schedule among the homeless population. The source of information proved to be one of the determinants of completeness, and the Unified Health System played a leading role in raising awareness among homeless people, notably through its strategy of street clinics, when available. The evidence points to the importance of affirmative and inclusive actions that guarantee access to the vaccine for homeless people.