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SARS-CoV-2 caused the pandemic situation experienced since the beginning of 2020, and many countries faced the rapid spread and severe form of the disease. Mechanisms of interaction between the virus and the host were observed during acute phase, but few data are available when related to immunity dynamics in convalescents. We conducted a longitudinal study, with 51 healthy donors and 62 COVID-19 convalescent patients, which these had a 2-month follow-up after symptoms recovery. Venous blood sample was obtained from all participants to measure blood count, subpopulations of monocytes, lymphocytes, natural killer cells and dendritic cells. Serum was used to measure cytokines, chemokines, growth factors, anti-N IgG and anti-S IgG/IgM antibodies. Statistic was performed by Kruskal–Wallis test, and linear regression with days post symptoms and antibody titers. All analysis had confidence interval of 95%. Less than 35% of convalescents were anti-S IgM+, while more than 80% were IgG+ in D30. Anti-N IgG decreased along time, with loss of seroreactivity of 13%. Eosinophil count played a distinct role on both antibodies during all study, and the convalescence was orchestrated by higher neutrophil-to-lymphocyte ratio and IL-15, but initial stages were marked by increase in myeloid DCs, B1 lymphocytes, inflammatory and patrolling monocytes, G-CSF and IL-2. Later convalescence seemed to change to cytotoxicity mediated by T lymphocytes, plasmacytoid DCs, VEGF, IL-9 and CXCL10. Anti-S IgG antibodies showed the longest perseverance and may be a better option for diagnosis. The inflammatory pattern is yet present on initial stage of convalescence, but quickly shifts to a reparative dynamic. Meanwhile eosinophils seem to play a role on anti-N levels in convalescence, although may not be the major causative agent. We must highlight the importance of immunological markers on acute clinical outcomes, but their comprehension to potentialize adaptive system must be explored to improve immunizations and further preventive policies. [ABSTRACT FROM AUTHOR]

Introduction: Leukemia is the most common cancer in children and has the highest rates of incidence in industrialized countries, followed by developing countries. This epidemiologic profile can mainly be attributed to the availability of diagnostic resources. In Brazil, leukemia diagnosis is a challenge due to financial viability, lack of hemovigilance services in isolated regions and the vast size of the territory. Its incidence in the state of Amazonas has been increasing since 2010. Therefore, this study aims to describe the epidemiological pattern and spatial distribution of patients with acute lymphoid leukemia and acute myeloid leukemia in Amazonas and identify the predictors of comorbidity and death. Materials and methods: A retrospective cross-sectional study was carried out based on patients’ data which was obtained from the database of a referral center for the period of 2005 to 2015. Variables included age, gender, ethnicity, civil status, schooling, income, location of residence, subtype of leukemia, comorbidities, and date of death. The spatial distribution was performed using QGIS v.2.18. Stata software was used for univariable and multivariable logistic regression to evaluate the association between both comorbidities and death for all characteristic groups of ALL and AML. Results: The group that was studied was composed of 577 ALL and 266 AML patients. For both, most patients were male, with a schooling period of 1–4 years, received<1 minimum wage, and lived mostly in Manaus, followed by the municipality of Tefé. There was no association between the development of comorbidities and analyzed variables in patients with ALL. AML patients that were >60 years old and with family history of the disease had the highest risk of developing comorbidities (OR = 5.06, p = 0.038; OR = 2.44, p = 0.041, respectively). Furthermore, patients with ALL and in the 41-50-year age group had a higher risk of death (OR = 31.12; p = 0.001). No association between death and explanatory variables were found in patients with AML. In addition, significant difference was observed in time to death (chi2 = 4,098.32, p = 0.000), with 50% of patients with AML dying within two years after diagnosis, whereas in ALL, this percentual of death only is reached in approximately 5 years. Conclusion: Our study describes the data of patients with acute leukemia in Amazonas, a remote region in the north of Brazil. In addition, it highlights the importance of hemovigilance in an Amazon region state, while focusing on peripheral areas which don't have prevention, diagnosis and treatment tools for this disease. [ABSTRACT FROM AUTHOR]