Essentials of filoviral load quantification

The Evolution of Medical Countermeasures for Ebola Virus Disease: Lessons Learned and Next Steps

The Ebola virus disease outbreak that occurred in Western Africa from 2013-2016, and subsequent smaller but increasingly frequent outbreaks of Ebola virus disease in recent years, spurred an unprecedented effort to develop and deploy effective vaccines, therapeutics, and diagnostics. This effort led to the U.S. regulatory approval of a diagnostic test, two vaccines, and two therapeutics for Ebola virus disease indications. Moreover, the establishment of fieldable diagnostic tests improved the speed with which patients can be diagnosed and public health resources mobilized. The United States government has played and continues to play a key role in funding and coordinating these medical countermeasure efforts. Here, we describe the coordinated U.S. government response to develop medical countermeasures for Ebola virus disease and we identify lessons learned that may improve future efforts to develop and deploy effective countermeasures against other filoviruses, such as Sudan virus and Marburg virus.

Evaluation of viral load in patients with Ebola virus disease in Liberia: a retrospective observational study

Background

Viral load in patients with Ebola virus disease affects case fatality rate and is an important parameter used for diagnostic cutoffs, stratification in randomised controlled trials, and epidemiological studies. However, viral load in Ebola virus disease is currently estimated using numerous different assays and protocols that were not developed or validated for this purpose. Here, our aim was to conduct a laboratory-based re-evaluation of the viral loads of a large cohort of Liberian patients with Ebola virus disease and analyse these data in the broader context of the west Africa epidemic.

Methods

In this retrospective observational study, whole blood samples from patients at the Eternal Love Winning Africa Ebola treatment unit (Monrovia, Liberia) were re-extracted with an optimised protocol and analysed by droplet digital PCR (ddPCR) using a novel semi-strand specific assay to measure viral load. To allow for more direct comparisons, the ddPCR viral loads were also back-calculated to cycle threshold (C_t) values. The new viral load data were then compared with the C_t values from the original diagnostic quantitative RT-PCR (qRT-PCR) testing to identify differing trends and discrepancies.

Findings

Between Aug 28 and Dec 18, 2014, 727 whole blood samples from 528 individuals were collected. 463 (64%) were first-draw samples and 409 (56%) were from patients positive for Ebola virus (EBOV), species Zaire ebolavirus. Of the 307 first-draw EBOV-positive samples, 127 (41%) were from survivors and 180 (59%) were from non-survivors; 155 (50%) were women, 145 (47%) were men, and seven (2%) were not recorded, and the mean age was 29·3 (SD 15·0) years for women and 31·8 (SD 14·8) years for men. Survivors had significantly lower mean viral loads at presentation than non-survivors in both the reanalysed dataset (5·61 [95% CI 5·34–5·87] vs 7·19 [6·99–7·38] log₁₀ EBOV RNA copies per mL; p<0·0001) and diagnostic dataset (C_t value 28·72 [27·97–29·47] vs 26·26 [25·72–26·81]; p<0·0001). However, the prognostic capacity of viral load increased with the reanalysed dataset (odds ratio [OR] of death 8·06 [95% CI 4·81–13·53], p<0·0001 for viral loads above 6·71 log₁₀ EBOV RNA copies per mL vs OR of death 2·02 [1·27–3·20], p=0·0028 for C_t values below 27·37). Diagnostic qRT-PCR significantly (p<0·0001) underestimated viral load in both survivors and non-survivors (difference in diagnostic C_t value minus laboratory C_t value of 1·79 [95% CI 1·16–2·43] for survivors and 5·15 [4·43–5·87] for non-survivors). Six samples that were reported negative by diagnostic testing were found to be positive upon reanalysis and had high viral loads.

Interpretation

Inaccurate viral load estimation from diagnostic C_t values is probably multifactorial; however, unaddressed PCR inhibition from tissue damage in patients with fulminant Ebola virus disease could largely account for the discrepancies observed in our study. Testing protocols for Ebola virus disease require further standardisation and validation to produce accurate viral load estimates, minimise false negatives, and allow for reliable epidemiological investigation.

A meta-analysis of clinical studies conducted during the West Africa Ebola virus disease outbreak confirms the need for randomized control groups

Recent Ebola virus disease outbreaks affirm the dire need for treatments with proven efficacy. Randomized controlled clinical trials remain the gold standard but, during disease outbreaks, may be difficult to conduct due to ethical concerns and challenging field conditions. In the absence of a randomized control group, statistical modeling to create a control group could be a possibility. Such a model-based reference control would only be credible if it had the same mortality risk as that of the experimental group in the absence of treatment. One way to test this counterfactual assumption is to evaluate whether reasonable similarity exists across nonrandomized control groups from different clinical studies, which might suggest that a future control group would be similarly homogeneous. We evaluated similarity across six clinical studies conducted during the 2013-2016 West Africa outbreak of Ebola virus disease. These studies evaluated favipiravir, the biologic ZMapp, the antimalarial drug amodiaquine, or administration of convalescent plasma or convalescent whole blood. We compared the nonrandomized control groups of these six studies comprising 1147 individuals infected with Ebola virus. We found considerable heterogeneity, which did not disappear after statistical modeling to adjust for prognostic variables. Mortality risk varied widely (31 to 66%) across the nonrandomized control arms of these six studies. Models adjusting for baseline covariates (age, sex, and cycle threshold, a proxy for viral load) failed to sufficiently recalibrate these studies and showed that heterogeneity remained. Our findings highlight concerns about making invalid conclusions when comparing nonrandomized control groups to cohorts receiving experimental treatments.

Operational Research during the Ebola Emergency

Operational research aims to identify interventions, strategies, or tools that can enhance the quality, effectiveness, or coverage of programs where the research is taking place. Médecins Sans Frontières admitted ≈5,200 patients with confirmed Ebola virus disease during the Ebola outbreak in West Africa and from the beginning nested operational research within its emergency response. This research covered critical areas, such as understanding how the virus spreads, clinical trials, community perceptions, challenges within Ebola treatment centers, and negative effects on non-Ebola healthcare. Importantly, operational research questions were decided to a large extent by returning volunteers who had first-hand knowledge of the immediate issues facing teams in the field. Such a method is appropriate for an emergency medical organization. Many challenges were also identified while carrying out operational research across 3 different countries, including the basic need for collecting data in standardized format to enable comparison of findings among treatment centers.

Ebola virus disease: Biological and diagnostic evolution from 2014 to 2017

The Ebola virus disease outbreak observed in West Africa from March 2014 to June 2016 has led to many fundamental and applied research works. Knowledge of this virus has substantially increased. Treatment of many patients in epidemic countries and a few imported cases in developed countries led to developing new diagnostic methods and to adapt laboratory organization and biosafety precautions to perform conventional biological analyses. Clinical and biological monitoring of patients infected with Ebola virus disease helped to determine severity criteria and bad prognosis markers. It also contributed to showing the possibility of viral sanctuaries in patients and the risk of transmission after recovery. After a summary of recent knowledge of environmental and clinical viral persistence, we aimed to present new diagnostic methods and other biological tests that led to highlighting the pathophysiological consequences of Ebola virus disease and its prognostic markers. We also aimed to describe our lab experience in the care of Ebola virus-infected patients, especially technical and logistical changes between 2014 and 2017.

Different features of Vδ2 T and NK cells in fatal and non-fatal human Ebola infections

Background

Human Ebola infection is characterized by a paralysis of the immune system. A signature of αβ T cells in fatal Ebola infection has been recently proposed, while the involvement of innate immune cells in the protection/pathogenesis of Ebola infection is unknown. Aim of this study was to analyze γδ T and NK cells in patients from the Ebola outbreak of 2014–2015 occurred in West Africa, and to assess their association with the clinical outcome.

Methodology/Principal findings

Nineteen Ebola-infected patients were enrolled at the time of admission to the Ebola Treatment Centre in Guinea. Patients were divided in two groups on the basis of the clinical outcome. The analysis was performed by using multiparametric flow cytometry established by the European Mobile Laboratory in the field. A low frequency of Vδ2 T-cells was observed during Ebola infection, independently from the clinical outcome. Moreover, Vδ2 T-cells from Ebola patients massively expressed CD95 apoptotic marker, suggesting the involvement of apoptotic mechanisms in Vδ2 T-cell loss. Interestingly, Vδ2 T-cells from survivors expressed an effector phenotype and presented a lower expression of the CTLA-4 exhaustion marker than fatalities, suggesting a role of effector Vδ2 T-cells in the protection. Furthermore, patients with fatal Ebola infection were characterized by a lower NK cell frequency than patients with non fatal infection. In particular, both CD56^bright and CD56^dim NK frequency were very low both in fatal and non fatal infections, while a higher frequency of CD56^neg NK cells was associated to non-fatal infections. Finally, NK activation and expression of NKp46 and CD158a were independent from clinical outcome.

Conclusions/Significances

Altogether, the data suggest that both effector Vδ2 T-cells and NK cells may play a role in the complex network of protective response to EBOV infection. Further studies are required to characterize the protective effector functions of Vδ2 and NK cells.

Human Ebola infection presents a high lethality rate and is characterized by a paralysis of the immune response. The definition of the protective immune profile during Ebola infection represents a main challenge useful in vaccine and therapy design.

In particular, the protective/pathogenetic involvement of innate immune cells during Ebola infection in humans remains to be clarified. Nineteen Ebola-infected patients were enrolled at the time of admission to the Ebola Treatment Center in Guinea, and the profiling of innate immunity was correlated with the clinical outcome. Our results show that both effector Vδ2 T-cells and NK cells were associated with survival, suggesting their involvement in the complex network of protective response to EBOV infection.

Development, Evaluation, and Integration of a Quantitative Reverse-Transcription Polymerase Chain Reaction Diagnostic Test for Ebola Virus on a Molecular Diagnostics Platform

BACKGROUND

The 2013-2016 Ebola epidemic in West Africa resulted in accelerated development of rapid diagnostic tests for emergency outbreak preparedness. We describe the development and evaluation of the Idylla™ prototype Ebola virus test, a fully automated sample-to-result molecular diagnostic test for rapid detection of Zaire ebolavirus (EBOV) and Sudan ebolavirus (SUDV).

METHODS

The Idylla™ prototype Ebola virus test can simultaneously detect EBOV and SUDV in 200 µL of whole blood. The sample is directly added to a disposable cartridge containing all reagents for sample preparation, RNA extraction, and amplification by reverse-transcription polymerase chain reaction analysis. The performance was evaluated with a variety of sample types, including synthetic constructs and whole blood samples from healthy volunteers spiked with viral RNA, inactivated virus, and infectious virus.

RESULTS

The 95% limits of detection for EBOV and SUDV were 465 plaque-forming units (PFU)/mL (1010 copies/mL) and 324 PFU/mL (8204 copies/mL), respectively. In silico and in vitro analyses demonstrated 100% correct reactivity for EBOV and SUDV and no cross-reactivity with relevant pathogens. The diagnostic sensitivity was 97.4% (for EBOV) and 91.7% (for SUDV), the specificity was 100%, and the diagnostic accuracy was 95.9%.

CONCLUSIONS

The Idylla™ prototype Ebola virus test is a fast, safe, easy-to-use, and near-patient test that meets the performance criteria to detect EBOV in patients with suspected Ebola.