Analysis of 179 new Ebola virus sequences from patient samples collected in Guinea between March 2014 and January 2015 shows how different lineages evolved and spread in West Africa. Miles Carroll and colleagues report describe the genetic evolution of Ebola virus circulating in West Africa, based on 179 new virus sequences from patient samples collected in Guinea between March 2014 and January 2015. Their analysis shows how different lineages evolved and spread in West Africa between Sierra Leone, Guinea and Liberia. West Africa is currently witnessing the most extensive Ebola virus (EBOV) outbreak so far recorded1,2,3. Until now, there have been 27,013 reported cases and 11,134 deaths. The origin of the virus is thought to have been a zoonotic transmission from a bat to a two-year-old boy in December 2013 (ref. 2). From this index case the virus was spread by human-to-human contact throughout Guinea, Sierra Leone and Liberia. However, the origin of the particular virus in each country and time of transmission is not known and currently relies on epidemiological analysis, which may be unreliable owing to the difficulties of obtaining patient information. Here we trace the genetic evolution of EBOV in the current outbreak that has resulted in multiple lineages. Deep sequencing of 179 patient samples processed by the European Mobile Laboratory, the first diagnostics unit to be deployed to the epicentre of the outbreak in Guinea, reveals an epidemiological and evolutionary history of the epidemic from March 2014 to January 2015. Analysis of EBOV genome evolution has also benefited from a similar sequencing effort of patient samples from Sierra Leone. Our results confirm that the EBOV from Guinea moved into Sierra Leone, most likely in April or early May. The viruses of the Guinea/Sierra Leone lineage mixed around June/July 2014. Viral sequences covering August, September and October 2014 indicate that this lineage evolved independently within Guinea. These data can be used in conjunction with epidemiological information to test retrospectively the effectiveness of control measures, and provides an unprecedented window into the evolution of an ongoing viral haemorrhagic fever outbreak.

Fatal Ebola virus disease is characterized by a high proportion of CD4+ and CD8+ T cells expressing the inhibitory molecules CTLA-4 and PD-1, correlating with high virus load; individuals who survive the infection exhibit lower expression of these inhibitory molecules and generate Ebola-specific CD8+ T cells, suggesting that dysregulation of the T cell response is a key component of Ebola virus disease pathophysiology. César Muñoz-Fontela and colleagues have tracked the T cell response in individuals infected with Ebola virus in Guinea. Following patients from the time of their admission at the Ebola Treatment Centre in Guinea until their discharge or death, the authors identify an immune signature that is characteristic of fatal Ebola virus disease. In fatal infection, a high proportion of CD4+ and CD8+ cells expressed the inhibitory molecules CTLA-4 and PD-1, correlating with high virus load. By contrast, individuals who survived the infection showed lower expression of these inhibitory molecules, suggesting that dysregulation of the T cell response is a key component of Ebola virus disease pathophysiology. Despite the magnitude of the Ebola virus disease (EVD) outbreak in West Africa, there is still a fundamental lack of knowledge about the pathophysiology of EVD1. In particular, very little is known about human immune responses to Ebola virus2,3. Here we evaluate the physiology of the human T cell immune response in EVD patients at the time of admission to the Ebola Treatment Center in Guinea, and longitudinally until discharge or death. Through the use of multiparametric flow cytometry established by the European Mobile Laboratory in the field, we identify an immune signature that is unique in EVD fatalities. Fatal EVD was characterized by a high percentage of CD4+ and CD8+ T cells expressing the inhibitory molecules CTLA-4 and PD-1, which correlated with elevated inflammatory markers and high virus load. Conversely, surviving individuals showed significantly lower expression of CTLA-4 and PD-1 as well as lower inflammation, despite comparable overall T cell activation. Concomitant with virus clearance, survivors mounted a robust Ebola-virus-specific T cell response. Our findings suggest that dysregulation of the T cell response is a key component of EVD pathophysiology.

Specific memory B cells and antibodies are a reliable read-out of vaccine efficacy. We analysed these biomarkers after one and two doses of BNT162b2 vaccine. The second dose significantly increases the level of highly specific memory B cells and antibodies. Two months after the second dose, specific antibody levels decline, but highly specific memory B cells continue to increase, thus predicting a sustained protection from COVID-19. We show that although mucosal IgA is not induced by the vaccination, memory B cells migrate in response to inflammation and secrete IgA at mucosal sites. We show that the first vaccine dose may lead to an insufficient number of highly specific memory B cells and low concentration of serum antibodies, thus leaving vaccinees without the immune robustness needed to ensure viral elimination and herd immunity. We also clarify that the reduction of serum antibodies does not diminish the force and duration of the immune protection induced by vaccination. The vaccine does not induce sterilizing immunity. Infection after vaccination may be caused by the lack of local preventive immunity because of the absence of mucosal IgA.

SARS-CoV-2 serum neutralization assay represents the gold standard for assessing antibody-mediated protection in naturally infected and vaccinated individuals. In the present study, 662 serum samples collected from February 2020 to January 2021 from acute and convalescent COVID-19 patients were tested to determine neutralizing antibody (NAb) titers using a microneutralization test (MNT) for live SARS-CoV-2. Moreover, anti-SARS-CoV-2 IgG, IgA, and IgM directed against different viral antigens were measured by high-throughput automated platforms. We observed higher levels of NAbs in elderly (>60 years old) individuals and in patients presenting acute respiratory distress syndrome. SARS-CoV-2 NAbs develop as soon as five days from symptom onset and, despite a decline after the second month, persist for over 11 months, showing variable dynamics. Through correlation and receiver operating characteristic (ROC) curve analysis, we set up a testing algorithm, suitable for the laboratory workload, by establishing an optimal cutoff value of anti-SARS-CoV-2 IgG for convalescent plasma donors to exclude from MNT samples foreseen to have low/negative NAb titers and ineligible for plasma donation. Overall, MNT, although cumbersome and not suitable for routine testing of large sample sizes, remains the reference tool for the assessment of antibody-mediated immunity after SARS-CoV-2 infection. Smart testing algorithms may optimize the laboratory workflow to monitor antibody-mediated protection in COVID-19 patients, plasma donors, and vaccinated individuals.

The study was aimed to evaluate the malaria over/underdiagnosis and over/underprescription of antimalarial drugs. Between February and March 2007 blood samples were collected from 336 non-severe febrile outpatients attended in two peripheral Tanzanian hospitals. Microscopy and a rapid diagnostic test (RDT) were done locally and the accuracy evaluated by qualitative polymerase chain reaction (PCR) for Plasmodium spp. The testing was performed at National Institute for Infectious Diseases Lazzaro Spallanzani (INMI), Rome, Italy. As a result of PCR, we identified 26 malaria cases out of 336 (7.7%) patients. Microscopy and RDT accuracies were 93.5% and 97.6%, respectively. Overprescription and underdiagnosis rates were 29.3% and 30.8%, respectively. On-field training, clinical management of febrile illness, and malaria microscopy in remote settings should be considered.