Coronavirus disease 2019 (COVID-19) is a protean disease causing different degrees of clinical severity including fatality. In addition to humoral immunity, antigen-specific T cells may play a critical role in defining the protective immune response against SARS-CoV-2, the virus that causes this disease. As a part of a longitudinal cohort study in Bangladesh to investigate B and T cell-specific immune responses, we sought to evaluate the activation-induced marker (AIM) and the status of different immune cell subsets during a COVID-19 infection. We analyzed a total of 115 participants, which included participants with asymptomatic, mild, moderate, and severe clinical symptoms. We observed decreased mucosal-associated invariant T (MAIT) cell frequency on the initial days of the COVID-19 infection in symptomatic patients compared to asymptomatic patients. However, natural killer (NK) cells were found to be elevated in symptomatic patients just after the onset of the disease compared to both asymptomatic patients and healthy individuals. Moreover, we found a significant increase of AIM+ (both OX40+CD137+ and OX40+CD40L+) CD4+ T cells in moderate and severe COVID-19 patients in response to SARS-CoV-2 peptides (especially spike peptides) compared to pre-pandemic controls who are unexposed to SARS-CoV-2. Notably, we did not observe any significant difference in the CD8+ AIMs (CD137+CD69+), which indicates the exhaustion of CD8+ T cells during a COVID-19 infection. These findings suggest that patients who recovered from moderate and severe COVID-19 were able to mount a strong CD4+ T-cell response against shared viral determinants that ultimately induced T cells to mount further immune responses to SARS-CoV-2.

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The longevity of immune responses induced by different degrees of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection provides information important to understanding protection against coronavirus disease 2019 (COVID-19). Here, we report the persistence of SARS-CoV-2 spike receptor-binding domain (RBD) specific antibodies and memory B cells recognizing this antigen in sequential samples from patients in Bangladesh with asymptomatic, mild, moderate and severe COVID-19 out to six months following infection. Since the development of long-lived memory B cells, as well as antibody production, is likely to be dependent on T helper (Th) cells, we also investigated the phenotypic changes of Th cells in COVID-19 patients over time following infection. Our results show that patients with moderate to severe COVID-19 mounted significant levels of IgG antibodies out to six months following infection, while patients with asymptomatic or mild disease had significant levels of IgG antibodies out to 3 months following infection, but these then fell more rapidly at 6 months than in patients with higher disease severity. Patients from all severity groups developed circulating memory B cells (MBCs) specific to SARS-CoV-2 spike RBD by 3 months following infection, and these persisted until the last timepoint measured at 6 months. A T helper cell response with an effector memory phenotype was observed following infection in all symptomatic patients, while patients with asymptomatic infection had no significant increases in effector Th1, Th2 and Th17 effector memory cell responses. Our results suggest that the strength and magnitude of antibody and memory B cells induced following SARS-CoV-2 infection depend on the severity of the disease. Polarization of the Th cell response, with an increase in Th effector memory cells, occurs in symptomatic patients by day 7 following infection, with increases seen in Th1, Th2, Th17 and follicular helper T cell subsets.

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. Following infection, antibodies are formed against the spike (S) and nucleocapsid (N) proteins, which are the primary viral antigens of SARS-CoV-2. This study aims to determine the antibody response three weeks post-infection and its persistence. To study antibody responses in COVID-19-positive individuals and to compare the degree of antibody response in symptomatic and asymptomatic individuals. The persistence of the antibody response was also assessed. Adult patients (> 15 years of age) who were diagnosed as COVID-19-positive by RT-PCR, three weeks after swab positivity were tested for total antibody levels against COVID-19 antigens by electrochemiluminescence assay. Out of 226 individuals, 129 were symptomatic and 97 were asymptomatic. Among the 129 symptomatic individuals, 74 exhibited an antibody response, whereas in the asymptomatic individuals, only 10 exhibited an antibody response. The antibody response was found to be significant in symptomatic individuals compared to that in asymptomatic individuals (p < 0.05). All follow-up individuals were seropositive at the end of both 6 and 8 months. Antibodies against SARS-CoV-2 persist for 8 months following infection. Despite the waning of antibodies against the nucleocapsid antigen, there was no complete disappearance of antibodies.

Background: Many children with pulmonary tuberculosis remain undiagnosed and untreated with related high morbidity and mortality. Diagnostic challenges in children include low bacterial burden, challenges around specimen collection, and limited access to diagnostic expertise. Algorithms that guide decisions to initiate tuberculosis treatment in resource-limited settings could help to close the persistent childhood tuberculosis treatment gap. Recent advances in childhood tuberculosis algorithm development have incorporated prediction modelling, but studies conducted to date have been small and localised, with limited generalizability. Methods: We collated individual participant data including clinical, bacteriological, and radiologic information from prospective diagnostic studies in high-tuberculosis incidence settings enrolling children <10 years with presumptive pulmonary tuberculosis. Using this dataset, we first retrospectively evaluated the performance of several existing treatment-decision algorithms and then developed multivariable prediction models, investigating model generalisability using internal-external cross-validation. A team of experts provided input to adapt the models into a pragmatic treatment-decision algorithm with a pre-determined sensitivity threshold of 85% for use in resource-limited, primary healthcare settings. Findings: Of 4,718 children from 13 studies from 12 countries, 1,811 (38.4%) were classified as having pulmonary tuberculosis; 541 (29.9%) bacteriologically confirmed and 1,270 (70.1%) unconfirmed. Existing treatment-decision algorithms had highly variable diagnostic performance. Our prediction model had a combined sensitivity of 86% [95% confidence interval (CI): 0.68-0.94] and specificity of 37% [95% CI: 0.15-0.66] against a composite reference standard. Interpretation: We adopted an evidence-based approach to develop pragmatic algorithms to guide tuberculosis treatment decisions in children, irrespective of the resources locally available. This approach will empower health workers in resource-limited, primary healthcare settings to initiate tuberculosis treatment in children in order to improve access to care and reduce tuberculosis-related mortality. These algorithms have been included in the operational handbook accompanying the latest WHO guidelines on the management of tuberculosis in children and adolescents. Funding: World Health Organization, US National Institutes of Health