A prospective, multi-site, cohort study to estimate incidence of infection and disease due to Lassa fever virus in West African countries (the Enable Lassa research programme)-Study protocol.

BACKGROUND: Lassa fever (LF), a haemorrhagic illness caused by the Lassa fever virus (LASV), is endemic in West Africa and causes 5000 fatalities every year. The true prevalence and incidence rates of LF are unknown as infections are often asymptomatic, clinical presentations are varied, and surveillance systems are not robust. The aim of the Enable Lassa research programme is to estimate the incidences of LASV infection and LF disease in five West African countries. The core protocol described here harmonises key study components, such as eligibility criteria, case definitions, outcome measures, and laboratory tests, which will maximise the comparability of data for between-country analyses. METHOD: We are conducting a prospective cohort study in Benin, Guinea, Liberia, Nigeria (three sites), and Sierra Leone from 2020 to 2023, with 24 months of follow-up. Each site will assess the incidence of LASV infection, LF disease, or both. When both incidences are assessed the LASV cohort (nmin = 1000 per site) will be drawn from the LF cohort (nmin = 5000 per site). During recruitment participants will complete questionnaires on household composition, socioeconomic status, demographic characteristics, and LF history, and blood samples will be collected to determine IgG LASV serostatus. LF disease cohort participants will be contacted biweekly to identify acute febrile cases, from whom blood samples will be drawn to test for active LASV infection using RT-PCR. Symptom and treatment data will be abstracted from medical records of LF cases. LF survivors will be followed up after four months to assess sequelae, specifically sensorineural hearing loss. LASV infection cohort participants will be asked for a blood sample every six months to assess LASV serostatus (IgG and IgM). DISCUSSION: Data on LASV infection and LF disease incidence in West Africa from this research programme will determine the feasibility of future Phase IIb or III clinical trials for LF vaccine candidates.

Development, Use, and Impact of a Global Laboratory Database During the 2014 Ebola Outbreak in West Africa.

Background: The international impact, rapid widespread transmission, and reporting delays during the 2014 Ebola outbreak in West Africa highlighted the need for a global, centralized database to inform outbreak response. The World Health Organization and Emerging and Dangerous Pathogens Laboratory Network addressed this need by supporting the development of a global laboratory database. Methods: Specimens were collected in the affected countries from patients and dead bodies meeting the case definitions for Ebola virus disease. Test results were entered in nationally standardized spreadsheets and consolidated onto a central server. Results: From March 2014 through August 2016, 256343 specimens tested for Ebola virus disease were captured in the database. Thirty-one specimen types were collected, and a variety of diagnostic tests were performed. Regular analysis of data described the functionality of laboratory and response systems, positivity rates, and the geographic distribution of specimens. Conclusion: With data standardization and end user buy-in, the collection and analysis of large amounts of data with multiple stakeholders and collaborators across various user-access levels was made possible and contributed to outbreak response needs. The usefulness and value of a multifunctional global laboratory database is far reaching, with uses including virtual biobanking, disease forecasting, and adaption to other disease outbreaks.

Transcriptomic signatures differentiate survival from fatal outcomes in humans infected with Ebola virus.

BACKGROUND: In 2014, Western Africa experienced an unanticipated explosion of Ebola virus infections. What distinguishes fatal from non-fatal outcomes remains largely unknown, yet is key to optimising personalised treatment strategies. We used transcriptome data for peripheral blood taken from infected and convalescent recovering patients to identify early stage host factors that are associated with acute illness and those that differentiate patient survival from fatality. RESULTS: The data demonstrate that individuals who succumbed to the disease show stronger upregulation of interferon signalling and acute phase responses compared to survivors during the acute phase of infection. Particularly notable is the strong upregulation of albumin and fibrinogen genes, which suggest significant liver pathology. Cell subtype prediction using messenger RNA expression patterns indicated that NK-cell populations increase in patients who survive infection. By selecting genes whose expression properties discriminated between fatal cases and survivors, we identify a small panel of responding genes that act as strong predictors of patient outcome, independent of viral load. CONCLUSIONS: Transcriptomic analysis of the host response to pathogen infection using blood samples taken during an outbreak situation can provide multiple levels of information on both disease state and mechanisms of pathogenesis. Host biomarkers were identified that provide high predictive value under conditions where other predictors, such as viral load, are poor prognostic indicators. The data suggested that rapid analysis of the host response to infection in an outbreak situation can provide valuable information to guide an understanding of disease outcome and mechanisms of disease.

Nomenclature- and database-compatible names for the two Ebola virus variants that emerged in Guinea and the Democratic Republic of the Congo in 2014.

In 2014, Ebola virus (EBOV) was identified as the etiological agent of a large and still expanding outbreak of Ebola virus disease (EVD) in West Africa and a much more confined EVD outbreak in Middle Africa. Epidemiological and evolutionary analyses confirmed that all cases of both outbreaks are connected to a single introduction each of EBOV into human populations and that both outbreaks are not directly connected. Coding-complete genomic sequence analyses of isolates revealed that the two outbreaks were caused by two novel EBOV variants, and initial clinical observations suggest that neither of them should be considered strains. Here we present consensus decisions on naming for both variants (West Africa: "Makona", Middle Africa: "Lomela") and provide database-compatible full, shortened, and abbreviated names that are in line with recently established filovirus sub-species nomenclatures.