Short- and Long-Term Humoral and Cellular Immune Responses to SARS-CoV-2 Vaccination in Patients with Multiple Sclerosis Treated with Disease-Modifying Therapies.

BACKGROUND: This study aimed to evaluate short- and long-term humoral and T-cell-specific immune responses to SARS-CoV-2 vaccines in patients with multiple sclerosis (MS) treated with different disease-modifying therapies (DMTs). METHODS: Single-center observational longitudinal study including 102 patients with MS who consecutively received vaccination against SARS-CoV-2. Serum samples were collected at baseline and after receiving the second dose of the vaccine. Specific Th1 responses following in vitro stimulation with spike and nucleocapsid peptides were analyzed by quantifying levels of IFN-γ. Serum IgG-type antibodies against the spike region of SARS-CoV-2 were studied by chemiluminescent microparticle immunoassay. RESULTS: Patients undergoing fingolimod and anti-CD20 therapies had a markedly lower humoral response than those treated with other DMTs and untreated patients. Robust antigen-specific T-cell responses were detected in all patients except those treated with fingolimod, who had lower IFN-γ levels than those treated with other DMTs (25.8 pg/mL vs. 868.7 pg/mL, p = 0.011). At mid-term follow-up, a decrease in vaccine-induced anti-SARS-CoV-2 IgG antibodies was observed in all subgroups of patients receiving DMTs, although most patients receiving induction DMTs or natalizumab and non-treated patients remained protected. Cellular immunity was maintained above protective levels in all DMT subgroups except the fingolimod subgroup. CONCLUSIONS: SARS-CoV-2 vaccines induce robust and long-lasting humoral and cell-mediated specific immune responses in most patients with MS.

Smartphone-based Platform Assisted by Artificial Intelligence for Reading and Reporting Rapid Diagnostic Tests: Application to SARS-CoV-2 Lateral Flow Immunoassays.

BACKGROUND: Rapid diagnostic tests (RDTs) are being widely used to manage COVID-19 pandemic. However, many results remain unreported or unconfirmed altering a correct epidemiological surveillance. OBJECTIVE: To evaluate an artificial intelligence-based smartphone application, connected to a cloud web platform, to automatically and objectively read rapid diagnostic test (RDT) results and assess its impact on COVID-19 pandemic management. METHODS: Overall, 252 human sera were used to inoculate a total of 1,165 RDTs for training and validation purposes. We then conducted two field studies to assess the performance on real-world scenarios by testing 172 antibody RDTs at two nursing homes and 96 antigen RDTs at one hospital emergency department. RESULTS: Field studies demonstrated high levels of sensitivity (100%) and specificity (94.4%, CI 92.8-96.1%) for reading IgG band of COVID-19 antibodies RDTs compared to visual readings from health workers. Sensitivity of detecting IgM test bands was 100% and specificity was 95.8%, CI 94.3-97.3%. All COVID-19 antigen RDTs were correctly read by the app. CONCLUSIONS: The proposed reading system is automatic, reducing variability and uncertainty associated with RDTs interpretation and can be used to read different RDTs brands. The web platform serves as a real time epidemiological tracking tool and facilitates reporting of positive RDTs to relevant health authorities.

The Negative Impact of COVID-19 in HCV, HIV, and HPV Surveillance Programs During the Different Pandemic Waves

Background The coronavirus disease 2019 (COVID-19) pandemic has been a worldwide stress test for health systems. 2 years have elapsed since the description of the first cases of pneumonia of unknown origin. This study quantifies the impact of COVID-19 in the screening program of chronic viral infections such as human papillomavirus (HPV), human immunodeficiency virus (HIV), and hepatitis C virus (HCV) along the six different pandemic waves in our population. Each wave had particular epidemiological, biological, or clinical patterns. Methods We analyzed the number of samples for screening of these viruses from March 2020 to February 2022, the new infections detected in the pandemic period compared to the previous year, the time elapsed between diagnosis and linking to treatment and follow-up of patients, and the percentage of late HIV diagnosis. Moreover, we used the origin of the samples as a marker for quantifying the restoration of activity in primary care. Results During the first pandemic year, the number of samples received was reduced by 26.7, 22.6, and 22.5% for molecular detection of HPV or serological HCV and HIV status respectively. The highest decrease was observed during the first wave with 70, 40, and 26.7% for HPV, HCV, and HIV. As expected, new diagnoses also decreased by 35.4, 58.2, and 40.5% for HPV, HCV, and HIV respectively during the first year of the pandemic. In the second year of the pandemic, the number of samples remained below pre-pandemic period levels for HCV (−3.6%) and HIV (−9.3%) but was slightly higher for HPV (8.0%). The new diagnoses in the second year of the pandemic were −16.1, −46.8, and −18.6% for HPV, HCV, and HIV respectively. Conclusions Undoubtedly, an important number of new HPV, HCV, and HIV infections were lost during the COVID-19 pandemic, and surveillance programs were disrupted as a consequence of collapse of the health system. It is a priority to reinforce these surveillance programs as soon as possible in order to detect undiagnosed cases before the associated morbidity-mortality increases. New pandemic waves could increase the risk of reversing the achievements made over the last few decades.

Risk of SARS-CoV-2 Reinfections in a Prospective Inception Cohort Study: Impact of COVID-19 Vaccination.

The risk of reinfection could be related to the initial SARS-CoV-2 clinical presentation, but there are no data about the risk change after SARS-CoV-2 vaccination. We evaluated the rate of reinfection in an inception cohort study of 4943 health care workers (HCWs) according to symptoms and serologic results during March-May 2020. Incidence rates (IR) and IR ratios (IRR) before and after SARS-CoV-2 vaccination were determined by adjusting Poisson models. Overall, 1005 HCWs (20.3%) referred COVID-19 suggestive symptoms during the first surge of disease, and 33.5% and 55% presented a positive PCR or serology result, respectively. Meanwhile, 13% of asymptomatic HCWs had specific antibodies. During a follow up of 3422.2 person-years before vaccination, the rate of reinfection among seropositive individuals was 81% lower for those who were symptomatic compared with those who were asymptomatic (IRR of 0.19; 95% CI, 0.05-0.67; p = 0.003). During the 3100 person-years period after vaccination, an overall 74% decrease in the rate of infection was observed (IRR of 0.26; 95% CI, 0.21-0.32; p < 0.001), with a significant 83% and 70% decrease in seropositive and seronegative HCWs, respectively. In conclusion, the risk of SARS-CoV-2 reinfections is closely related to the clinical and serological presentation of COVID-19. COVID-19 vaccination further decreases the risk of reinfection more markedly among seropositive.

Pre-existing T cell immunity determines the frequency and magnitude of cellular immune response to two doses of mRNA vaccine against SARS-CoV-2.

Little is known about the factors associated with lack of T-cell response to mRNA vaccines against SARS-CoV-2. In a prospective cohort of 61 health care workers (HCWs), 21% and 16% after the first dose of mRNA BNT162b vaccine, and 12% and 7% after the second dose, showed lack of CD4+ and CD8+ T-cell response, respectively. Pre-existing T-cell immunity, due to past infection (46%) or cross-reactive cellular response (26%), was significantly associated with T-cell response in frequency (CD4+ T-cell, 100% vs 82% after two doses; p = 0.049) and in the magnitude of T-cell response during follow up. Furthermore, baseline CD4+ T-cell correlated positively with the titer of specific IgG-antibodies after first and second vaccine dose. Our data demonstrate that cross-reactive T-cells correlate with a better cellular response as well as an enhanced humoral response, and we confirm the close correlation of humoral and cellular response after mRNA vaccination.

T-cell response after first dose of BNT162b2 SARS-CoV-2 vaccine among healthcare workers with previous infection or cross-reactive immunity.

OBJECTIVES: Antibody response to the first dose of BNT162b2 SARS-CoV-2 is greater in COVID-19-convalescent than in infection-naïve individuals. However, there are no data about T-cell response in individuals with pre-existing cellular immunity. METHODS: We evaluated T-cell responses in parallel with SARS-CoV-2 antibody level after first dose of BNT162b2 vaccine in 23 infection-naïve and 27 convalescent healthcare workers (HCWs) previously included in a study about humoral and T-cell immunity. RESULTS: Overall, the antibody response was lower in the infection-naïve group than in convalescent individuals (18 895 vs 662.7 AU mL-1, P < 0.001), and intermediate but significantly lower in convalescent HCWs with previous negative serology (25 174 vs 1793 AU mL-1; P = 0.015). Indeed, anti-spike IgG titres after the first dose correlated with baseline anti-nucleocapsid IgG titres (rho = 0.689; P < 0.001). Pre-existing T-cell immunity was observed in 78% of convalescent and 65% of the infection-naïve HCWs. T-cell response after the first dose of the vaccine was observed in nearly all the cases with pre-existing T-cell immunity, reaching 94% in convalescent HCWs and 93% in those with cross-reactive T cells. It was lower in the infection-naïve group (50%; P = 0.087) and in convalescent HCWs with negative serology (56%; P = 0.085). Notably, systemic reactogenicity after vaccination was mainly observed in those with pre-existing T-cell immunity (P = 0.051). CONCLUSION: Here, we report that the first dose of BTN162b2 elicits a similar S-specific T-cell response in cases of either past infection or cross-reactive T cells, but lower in the rest of infection-naïve individuals and in convalescent HCWs who have lost detectable specific antibodies during follow-up.

The silent epidemic of lymphogranuloma venereum inside the COVID-19 pandemic in Madrid, Spain, March 2020 to February 2021.

Despite social distancing measures implemented in Madrid to prevent the propagation of SARS-CoV-2, a significant increase (57.1%; 28.5 to 38.5 cases/month) in cases of lymphogranuloma venereum was detected during the COVID-19 pandemic. This unusual scenario might have accelerated a shift in Chlamydia trachomatis (CT) epidemiology towards a higher proportion of L genotypes compared with non-L genotypes in CT-positive samples. Our data underscore the importance of surveillance of sexually transmitted infections during the pandemic, in particular among vulnerable populations.