Introduction

The 2014–2016 Ebola virus disease (EVD) outbreak in West Africa has been the deadliest occurrence of the disease since its discovery in 1976. Between January 2014 and June 2016, the World Health Organization reported 28,616 EVD cases, of which 11,310 were fatal [1]. In September 2014, at the peak of the outbreak, World Health Organization launched a fast-track process to identify potential anti-Ebola drugs and established three criteria for a drug to be acceptable as a candidate for clinical trials, namely i) availability of safety data in humans ii) evidence from preclinical studies of in vivo efficacy against Ebola virus (EBOV) iii) sufficient drug supply.

Favipiravir, a RNA polymerase inhibitor, approved in Japan to treat non complicated influenza infection, met all three criteria [2]. First the drug demonstrated antiviral activity against EBOV both in vitro (with a drug EC₅₀ found between 10.8 μg/mL and 63 μg/mL) and in vivo in mice models [3,4]. Second it had been already safely administered to more than 2000 healthy volunteers and patients worldwide [5] and its pharmacokinetics (PK) was therefore well characterized for the influenza dosing. Briefly, the drug is a small and relatively hydrophilic molecule, with a protein bound fraction of 54% and a distribution volume between 15 and 20 liters [6]. Administered orally, the drug is rapidly absorbed with a t_max ranging from 0.5 to 1 hour and a bioavailability close to 100% [6]. The main elimination pathway involves hepatic metabolism by aldehyde oxidase, and marginally xanthine oxidase, producing a hydrophilic and inactive metabolite M1, which is eliminated in the urine [6]. Favipiravir inhibits aldehyde oxidase, leading to time- and dose-dependent pharmacokinetics [6].

In November 2014, our group decided to perform a historically-controlled, single-arm proof-of-concept trial to assess the tolerance and efficacy of favipiravir in patients with EVD in Guinea (JIKI trial) [7]. Launching an emergency trial in the midst of such an historical outbreak posed many human, logistical, ethical and scientific challenges. Among those was the choice of the dosing regimen to be used against EBOV, which has been explained prior to the trial implementation [8]. In brief the dosing regimen was found such that it achieves safely and rapidly free average concentration comparable to that obtained in mice successfully treated while maintaining free minimal concentrations higher than the drug EC₅₀. Because the pharmacokinetics is nonlinear, the search for an optimal dosing regimen was based on a pharmacokinetic model developed by the manufacturer. Using this model a dosing regimen of 1,200 mg every twelve hours was proposed for the maintenance dose, with a loading dose of 6,000 mg (2,400; 2,400; 1,200 mg) on the first day. This dosing regimen was predicted to achieve stable concentrations after 48 hours, with median total trough (pre-dose) and average concentrations in plasma of 57.0 and 83.3 μg/mL, respectively [8]. One important aspect regarding this model is that it had been developed using data collected in studies in which the highest maintenance dose received was 800 mg twice a day and the largest treatment duration was 5 days. Doses in children were derived from adult doses and adjusted for body weight [7–9].

Overall, the JIKI trial results showed that mortality was strongly associated with baseline viremia. The results provided no evidence that favipiravir monotherapy at this dose might have a favorable benefit/risk ratio in patients with very high viral load at onset, but that it would merit future research in patients with a cycle threshold (Ct) ≥ 20, corresponding to a viral load below 10^7.7 genome copies/mL [7]. We previously published the trial results without reporting drug concentrations because they were not available at the time of the publication.

Here we report the results of the concentrations of favipiravir that were measured in patients of the JIKI trial. We compare them to the concentrations predicted by the model before the trial [8] and we analyse the possible association between drug plasma concentrations, viral loads and biochemical/haematological parameters.

Methods

Results

Patient’s characteristics

Of the 126 patients included in the JIKI trial, 10 were not included in the PK sub-study because they also received convalescent plasma. In addition, 21 patients died before the PK sampling time at Day-2 and 29 patients did not have enough plasma sample volume for drug concentration measurement. Thus a total of 66 patients were analysed in the PK sub-study (see flowchart in Fig 1), out of which 46 survived and 20 died. The median time from favipiravir initiation to death was 5 days (min-max: 2–17), with 8 patients who died between Day-2 and Day-4, 11 who died between Day-4 and Day-7 and one who died at Day-17. Patients took favipiravir as per the protocol and two missed doses were reported, both occurring the first day of drug initiation.

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Fig 1. Flowchart of the patients included in the PK analysis of the JIKI trial

https://doi.org/10.1371/journal.pntd.0005389.g001

The characteristics of the patients included in the analysis are given in Table 1 and are compared with those of patients included in the main analysis of the JIKI trial but not included in the PK sub-study. The patients included in this sub-PK analysis had significantly higher Ct values, lower creatinine, CRP values at baseline and significantly lower mortality rate than those who were not included (30% vs 82%, p<10⁻⁷). This is due in particular to the fact that the 21 patients who died before the PK sampling time at Day-2 could not be included in this sub-PK analysis (Fig 1).

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Table 1. Characteristics at inclusion of the 66 patients included and the 50 patients not included in the PK analysis of the JIKI trial.

https://doi.org/10.1371/journal.pntd.0005389.t001

Drug concentrations

Overall, 94 favipiravir trough concentrations were collected, 44 at Day-2 and 50 at Day-4. Among these 94 concentrations, 67 were obtained from plasma samples and 27 were from serum samples, and concentration in plasma and serum samples were largely similar (S3 Text). The median sampling time for the Day-2 measurement was 2.6 days after treatment initiation (min-max: 1.6–2.9) and the median sampling time for the Day-4 measurement was 4.6 days after treatment initiation (3.3–7.6). At Day-2, the median observed trough concentration was 46.1 μg/mL (23–106.9) and was close to the targeted trough concentration (57 μg/mL). However the concentrations dropped at Day-4 and the median concentration was 25.9 μg/mL (0–173.2) (Fig 2). This trend was observed in both plasma and serum samples (S3 Text). In patients having measurements at Day-2 and Day-4, the median reduction was -19.8 μg/mL (-54.6–-1.7) and was significantly different from 0 (p<10⁻⁵).

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Fig 2. Observed trough concentrations of favipiravir at Day-2 (n = 44) and Day-4 (n = 50) after treatment initiation.

Red points represent concentrations measured in patients who died during the trial, green points represent concentrations measured in those who survived. Concentrations obtained in patients receiving adult dose or weighted-based dose are presented in circles and stars, respectively. Lines connect data obtained in the 28 patients who had both measurements at Day-2 and Day-4. Boxplots represent the distribution of the concentrations. The lower and upper hinges correspond to the first and third quartiles. The upper whisker extends from the hinge to the highest value that is within 1.5 * IQR of the hinge, where IQR is the inter-quartile range, or distance between the first and third quartiles. The lower whisker extends from the hinge to the lowest value within 1.5 * IQR of the hinge.

https://doi.org/10.1371/journal.pntd.0005389.g002

Model-based analysis

Next, we refined our comparisons by adjusting the model’s predictions for the individual dosing regimen, sampling time, age and weight for the predicted concentrations (Fig 3 and Table 2). In the 5 patients for whom the information was not available (Table 1), a weight of 70 kg was assumed. At Day-2 the median observed concentration was equal to 46.1 μg/mL and the median predicted concentration was equal to 54.3 μg/mL (p = 0.01). At Day-4, the difference was more pronounced, with a median observed concentration of 25.9 μg/mL compared to a median predicted concentration of 64.4 μg/mL (p<10⁻⁶). While the model predicted a modest median increase in concentrations equal to 5.1 μg/mL between Day-2 and Day-4, the drug concentrations actually had a marked median decrease equal to -19.8 μg/mL (p<10⁻⁸).

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Fig 3. Observed trough concentrations (y-axis) versus predicted trough concentrations (x-axis) at Day-2 (left, n = 44 observations) and Day-4 (right, n = 50) after treatment initiation.

Red points represent concentrations measured in patients who died during the trial, green points represent concentrations measured in those who survived.

https://doi.org/10.1371/journal.pntd.0005389.g003

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Table 2. Observed and adjusted predicted (from the pharmacokinetic model provided by the manufacturer) trough concentrations of favipiravir at Day-2 and Day-4 in the 66 patients included in the PK analysis of the JIKI trial.

https://doi.org/10.1371/journal.pntd.0005389.t002

Relationship with virological response and mortality

One patient for whom no initial Ct value was available was not included in this sub-study and two PK measurements did not have corresponding Ct values. Overall 65 patients with 90 simultaneous measurements of favipiravir concentrations and Ct values were included in the analysis (41 and 49 observations at Day-2 and Day-4, respectively). Regardless of the day considered, no significant relationship between the EBOV viral decline in plasma (increase in Ct value) and favipiravir concentrations could be established (Fig 4) and no significant association between mortality and drug concentrations was found (Table 3).

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Fig 4. Difference in Ct values at Day-2 (left) or Day-4 (right) from baseline (the larger the value the larger the viral decline) versus drug concentrations.

Top: patients with a low baseline Ct value (Ct<20) (n = 15 and 12); bottom: patients with a high baseline Ct value (Ct>=20) (bottom, n = 26 and 37). Red points represent concentrations measured in patients who died during the trial, green points represent concentrations measured in those who survived. Triangles indicate Ct values that were above 40 (detection limit) and were treated as equal to 40, and circles are observed values. Black lines are Loess trend lines.

https://doi.org/10.1371/journal.pntd.0005389.g004

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Table 3. Observed trough concentrations of favipiravir at Day-2 and Day-4 in patients who died and those who survived according to the initial baseline EBOV viral load.

https://doi.org/10.1371/journal.pntd.0005389.t003

Discussion

We reported here the favipiravir plasma concentrations obtained in 66 patients of the JIKI trial. The main finding of our analysis was that favipiravir concentration was significantly below but still close to the predicted value target concentration at Day-2, but decreased by nearly 50% between Day-2 and Day-4. Consequently, the concentrations at Day-4, with a median value of 25.9 μg/mL, were much below the predicted model-based value. With a protein binding of 54%, free favipiravir trough concentrations at Day-4 remained thus slightly larger than the in vitro EC₅₀ reported in Oestereich et al., which was estimated at 10.5 μg/mL [4], but lower than those reported in another publication, where the EC₅₀ of favipiravir was found larger than 31 μg/mL[3]. The conclusion was similar when model predictions were adjusted for individual dosing regimen or individual characteristics. In particular, these low concentrations were not due to a lack of compliance, as only two doses were not taken and both occurred on the first day of treatment initiation. Of note the assay technique was only validated for plasma samples and we did not distinguish these two types of drug concentrations. Yet serum and plasma are close matrices and similar values were observed in both plasma and serum samples, including the strong reduction in drug concentrations between day 2 and day 4 (S3 Text). Lastly, we did not find any significant correlation between the drug exposure and the virological response. Taken together, these results indicate that it is possible that the favipiravir concentrations in the JIKI trial were not sufficient to strongly inhibit the viral replication.

Yet this conclusion should be nuanced and taken cautiously for several reasons. First the analysis relied only on plasma favipiravir concentrations and intracellular concentrations of the active phosphorylated moiety were not available. For instance, intracellular concentrations of HIV nucleotide reverse transcriptase inhibitors were associated with antiviral efficacy, but not with the plasma concentrations of the corresponding nucleoside analogue [10]. Second our analysis only relied on pre-dose concentrations but other PK factors that could not be determined here (e.g., AUC, time above EC₅₀ or EC₉₉) could be a better marker of drug efficacy. Third, the fact that no significant correlation was found between the drug exposure and the virological response could also be due to the delay between infection and treatment initiation. For instance viral dynamic modelling shows that a drug affecting viral replication, such as favipiravir, will only have a limited impact on viraemia if treatment is initiated after the viraemia peak, regardless of drug efficacy [11]. Lastly, our study included only patients with drug measurements at Day-2 or after, which excluded the most severe patients who died before Day-2. Thus the patients analysed here are not representative of the JIKI population study and this is why they differed in terms of mortality, initial Ct, viral load or biochemical parameters (Table 1).

Two non-exclusive explanations for the lower-than-predicted concentrations and the unexpected drop between Day-2 and Day-4 can be proposed, namely the effect of the disease/treatment on the drug pharmacokinetics and the non-linear PK of favipiravir which has never been documented at this dosing regimen.

Many disease symptoms can affect the drug pharmacokinetic processes and lead to reduced concentrations. For instance reduced plasma favipiravir concentrations and altered kinetics of absorption and elimination were observed in a hamster model of arenaviral haemorrhagic fever [12]. Here in absence of frequent data points and historical data with the same dosing regimen, the effect of the disease cannot be evaluated. Obviously, the disease symptoms such as dehydration, diarrhoea, vomiting, and reduction of gut perfusion can hamper or modify favipiravir absorption. Likewise, the disease symptoms could also affect the bioavailability and the hepatic first pass, in particular through an increase in the activity of the main metabolic enzyme of favipiravir (aldehyde oxidase) with temperature [13]. In the JIKI trial, only 30 episodes of vomiting were reported within 30 minutes of drug intake, which represent 2% of the overall number of drug intakes during the trial [7]. Altered pharmacokinetics could also involve the distribution volume of favipiravir, which may be increased in Ebola patients due to treatment or to the disease itself and may explain at least in part the reduced plasma concentrations. Favipiravir’s apparent volume of distribution ranges from 15 to 20 L and is likely restricted to vascular and extra vascular fluids [5,6]. This distribution volume can be influenced by two factors, namely change in volume of body fluid and/or favipiravir protein binding. In this sub-study of the JIKI trial, 89.4% of patients received IV fluid rehydration during treatment [7], which may be responsible for haemodilution. Here, the modest decline in haemoglobin does not suggest a massive haemodilution but some vascular leakage resulting from infusion of a large volume of rehydration fluid [14] or from the disease [15] cannot be ruled out and could affect to some extent the favipiravir volume of distribution. However, such effects of infusion or disease are unlikely to solely explain the 50% reduction of favipiravir concentrations at Day-4 which would require a doubled volume of distribution. Another possible alteration of the drug PK might be due to the reduction in albumin concentrations. With a protein binding of 54%, a mean decline of about 20% in albumin levels between Day-0 and Day-4 observed in this study is unlikely to have a major effect on favipiravir distribution or elimination. Lastly, liver failure could impact favipiravir concentrations [16,17] but this should rather favour drug accumulation than accelerate elimination. Of note, no significant correlation was found between biochemical and haematological parameters and drugs concentrations but the number of observations available was limited (S2 Fig).

The other main cause of these lower-than-predicted concentrations could be the fact that the model used to predict the drug exposure in the JIKI trial was based on data collected in a very different context. Indeed, the drug was historically developed against influenza virus and the model was therefore developed using data collected with much lower doses of favipiravir (at most 800 mg BID) for shorter period of time (at most 5 days). Favipiravir is known to have non-linear pharmacokinetics due to its inhibitory effect on its main metabolic enzyme, aldehyde oxidase [5,6], which is also known to have several genetic polymorphisms with different catalytic activities [18]. The fact that the non-linearity of favipiravir pharmacokinetics was evaluated at doses much lower than those used in the JIKI trial [5] and that only few data on patients of African ethnicity were previously available made it complicated to predict the exposure of favipiravir with high doses in the JIKI study population. In addition, reduction in the drug concentrations over 14 days of treatment was also observed in uninfected non-human primates receiving high doses of favipiravir [19], suggesting that reduction in drug concentrations over time may be an unanticipated feature of the drug that is independent of the disease [19].

In conclusion, we have demonstrated that favipiravir plasma concentrations decreased with time and were likely too low in most patients. We advocate for a dose-ranging study on healthy volunteers to assess the pharmacokinetics and the tolerance of higher dosing regimen.

Supporting information

Acknowledgments

We are indebted to all patients who participated in the JIKI trial.

The contribution of each member of the JIKI study group in the JIKI trial and the main analysis can be found in Sissoko et al (2016), Plos Medicine, 13(3): e1001967.

We gratefully acknowledge the members of the Data Safety Monitoring Board of the JIKI trial:

• Raphaël Porcher, Paris Descartes University, Paris, France (Chair).
• Daniel Bausch, U.S. Naval Medical Research, Lima, Peru.
• Brigitte Bazin, ANRS, Paris, France.
• Emmanuel Bottieau, Institute of Tropical Medicine, Antwerp, Belgium.
• Albert Faye, Robert Debré Hospital, Paris, France.
• Rodolphe Garraffo, University and Hospital of Nice, France.
• Peter Redfield, University of Nord Carolina, USA.

We gratefully acknowledge the members of the Scientific Advisory Board of the JIKI trial:

• Laurent Abel, University Paris Descartes, France
• Gail Carson, ISARIC Coordinating Centre, University of Oxford, United Kingdom
• Gerry Davies, University of Liverpool, United Kingdom
• Béatrice Godard, University of Montreal, Canada
• Anne Kelly, London School of Hygiene & Tropical Medicine, United Kingdom
• Nathalie Morgensztejn, ANSM, Paris, France
• Angélique Ndjoyi Mbiguino, Faculté de Médecine, Université des Sciences de la Santé, Libreville, Gabon
• Caroline Semaille, ANSM, Paris, France
• Michel Van Herp, MSF Belgique, Brussels, Belgium
• Yazdan Yazdanpanah, APHP, Paris, France

We thank Inserm for the support (Thierry Damerval, Jean-François Delfraissy, Yves Levy), and Toyama Chemical Co., LTD, for the donation of favipiravir (Koichi Yamada, Hiroshi Kitaguchi, Takashi Kuroda)

We thank Pr Dominique Lombardo, head of unit INSERM UMR_S 911, and Joseph Ciccolini (same unit, PK platform) for facilitating the implementation of favipiravir HPLC PK dosage.

We also gratefully acknowledge the valuable contributions of the following persons: Kabirou Abdou, Marc Aletti, Anne Astruc, Sadick Bachar, Wowo Balamou, Serge Balandine, Sadio Balde, Mamadou Barry, Monique Beavogui, Nicole Anne Margaret Blackwell, Joachim Tamba Bongono, Claire-Anne Bost, Giorgio Calarco, Djigui Camara, Koumba Camara, Lonceni Camara, Nestor Camara, Souleymane Camara, Maboro Camara, Vanessa Catherine, Mohammed Cisse, Matengbe Conde, Pierre-Yves Cordier, Dominique Costagliola, Jean Cotte, Henri Dampierre, Paul Parfat Delamou, Felix Dembadouno, Julien Demeildre, Evelyn Deportere, Mariama Cire Diallo, Fadima Diawara, Idrissa Dieng, Adam Doble, Moussa Donzo, Aubin Achim Dopavogui, Pascal Doualamou Niankoye, Mamadou Doumbouya, Amadou Elhadji Djibrillou, Mamadi Fadiga, Faya Fidel Feindouno, Vincent Foissaud, Mahamadou Gado, Doriana Gaspari, Zaoro Gbamaou, Simon Gbanamou, Gaston Kona Geopogui, Alphonse Goepogui, Hervé Granier, Voro Grovogui, Pauline Guilavogui, Maïmouna Guilavogui, Agnès Haba, Madeleine Haba, Pauline Haba, Victoire Hubert, Kekoura Iffono, Saa Salomon Ifono, Frédéric Janvier, Ludovic Joxe, Grévisse Kakule, Oumou Kalissa, Alice Tewa Kamano, Fidele Tamba Kamano, Francis Kamano, Tamba André Kamano, Tamba Moussa Kamano, Finda Fanta Kamano, Saa Iv Kamano, Tamba Martin Kamano, Tewa Mariame Kamano, Sandy Kampelle Smith, Georges Saâ Bakary Kantambadouno, Jackson Katembo, Almamy Keita, Mamadou Aliou Keita, Nankoria Keita, Saa Sekou Keita, Sayon Keïta, Molou Koivogui, Pierre Koivogui Akoi, Emmanuel Koivogui Koho, Yoyo Kolie, André Kolie Niankoye, Tamba François Kondiano, Lambert Kondiano, Emmanuel N’gandou Kondiano, Faya Michel Kondiano, Pakpagne Kouchiakbe, Kekoura Koulemou, Fassou Koulibaly, Saa Yawo Koumassadouno, Fara Alain Koumbassadouno, Saa Fidel Koundouno, Tamba Augustin Koundouno, Mariam Kourouma, Niankoye Lucien Kponghomou, Simbiano Kumba, Béatrice Labrosse, Nathanael Lamah, Pythagore Lamah, Yoyo Lamah, Simone Waly Lamah, Jean Baptiste Lamah, Guillaume Le Duc, Fodé Lelano, Elisa Toffa Leno, Eloi Leno, Philomène Leno, Makoura Leno, Camus N'bemba Leno, Faya Patrice Lèno, Bonda Leno, Carolina Lopez, Papus Loua, Antony Loua Cece, Odile Mahomy Seny, Claude Mahoudeau, Johanna Maikoouva, Tamba Lucien Mamadurno, Aly Mansare, Rachelle Sawe Mansare, Annette Mansare, Saa Martin Mara, Pierre Martineau, Sophie Masson, Nancy Maugey, Conte M'beila Conte, Pauline Michavila, Cecile Millimono, Fassa Etienne Millimono, Saâ Jules Millimouno, Saa Lucien Millimouno, Saa David Millimouno, Noel Millimouno, Fara Emile Millimouno, Faya Maurice Millimouno, Camille Montfort, Nicolas Mouly, Sitta Moundekeno, Stéphanie Mundweiller, Colette Oliano, Delphine Lendö Oliano, Sia Maragbe Emeline Oliano, Marguerite Ouamouno, Mariame Ouamouno, Tamba Eloi Ouendeno, Diallo Oumou, Jean Oyengue, Iliana Petrini, Edith Pommerol, Alexis Reouhiri Dermbaye, Jean Rivenc, Renata Rodrigues, Virginie Rouille, Emmanuel Sagui, Ouo Ouo Sakovogui, Sayon Samouro, Honoré Leno San, Fatou Sandouno, Sandouno, Tamba Mathos Sandouno, Sia Marthe Sandouno, Noufé Sanzan, Tolno Saran, Koniono Sia, Ramatoulaye Sidibe, Sonole Sonole, Dauda Souare Dauda, Ibrahima Soumaoro, Asmaou Sow, Djenabou Sow, Saa Eloi Tagbino, Christine Tenguiano, Joseph Thea, Damien Thomas, Marie Koumba Tinkiano, Julien Fara Tolno, Jean Tolno, Saa Etienne Tolno, Sekou Tolno, Nazouo Touaro, Sébastien Touboulic, Bakary Tounkara, Brahima Toure, Nandjelima Toure, Sory Toure, Dan Traore, Fanta Traore, Kadiatou Traore, Sidikiba Traore, Simon Traore, Pierre Trebovic, Thomas Vandamme, Rose Wammo, Justine Séré Yaradouno, Marthe Yatara, Ousmane Youssoufou Nouhou. This work is done for the JIKI study group whose members are listed as follows:

Daouda Sissoko^2,7, Cédric Laouénan^1,4, Elin Folkesson⁹, Abdoul-Bing M’Lebing¹⁰, Abdoul-Habib Beavogui¹⁹, Sylvain Baize⁶, Alseny-Modet Camara⁹, Piet Maes^15,20, Susan Shepherd¹⁰, Christine Danel^2,10,3, Sara Carazo⁹, Mamoudou N. Conde¹⁰, Jean-Luc Gala^11,12,13,14, Géraldine Colin^2,3,21, Hélène Savini²², Joseph Akoi Bore^15,16,17, Frederic Le Marcis²³, Fara Raymond Koundouno^15,16,17, Frédéric Petitjean¹⁰, Marie-Claire Lamah⁹, Sandra Diederich^15,24, Alexis Tounkara⁹, Geertrui Poelart⁹, Emmanuel Berbain⁹, Jean-Michel Dindart¹⁰, Sophie Duraffour^15,20, Annabelle Lefevre⁹, Tamba Leno⁹, Olivier Peyrouset¹⁰, Léonid Irenge^11,14, N’Famara Bangoura⁹, Romain Palich¹⁰, Julia Hinzmann^15,25, Annette Kraus^15,26, Thierno Sadou Barry¹⁰, Sakoba Berette¹⁰, André Bongono¹⁰, Mohamed Seto Camara¹⁰, Valérie Chanfreau Munoz¹⁰, Lanciné Doumbouya¹⁰, Souley Harouna¹⁰, Patient Mumbere Kighoma¹⁰, Fara Roger Koundouno¹⁰, Réné Lolamou¹⁰, Cécé Moriba Loua¹⁰, Vincent Massala¹⁰, Kinda Moumouni¹⁰, Célia Provost¹⁰, Nenefing Samake¹⁰, Conde Sekou¹⁰, Abdoulaye Soumah¹⁰, Isabelle Arnould⁹, Michel Saa Komano⁹, Lina Gustin⁹, Carlotta Berutto⁹, Diarra Camara⁹, Fodé Saydou Camara⁹, Joliene Colpaert⁹, Léontine Delamou⁹, Lena Jansson⁹, Etienne Kourouma⁹, Maurice Loua⁹, Kristian Malme⁹, Emma Manfrin⁹, André Maomou⁹, Adele Milinouno⁹, Sien Ombelet⁹, Aboubacar Youla Sidiboun⁹, Isabelle Verreckt⁹, Pauline Yombouno⁹, Anne Bocquin¹⁸, Caroline Carbonnelle¹⁸, Thierry Carmoi²², Pierre Frange²⁷, Stéphane Mely¹⁸, Vinh-Kim Nguyen²⁸, Delphine Pannetier¹⁸, Anne-Marie Taburet⁵, Jean-Marc Treluyer²⁷, Jacques Kolie¹⁹, Raoul Moh^2,3, Minerva Cervantes-Gonzalez^1,4, Eeva Kuisma^15,29, Britta Liedigk^15,30, Didier Ngabo^15,29, Martin Rudolf^15,30, Ruth Thom^15,29, Romy Kerber^15,30, Martin Gabriel^15,30, Antonino Di Caro^15,31, Roman Wölfel^15,32, Jamal Badir^11,12, Mostafa Bentahir^11,14, Yann Deccache^11,14, Catherine Dumont^11,14, Jean-François Durant^11,13, Karim El Bakkouri^11,13, Marie Gasasira Uwamahoro^11,13, Benjamin Smits^11,13, Nora Toufik^11,12, Stéphane Van Cauwenberghe^11,14, Khaled Ezzedine², Eric D’Ortenzio³³, Louis Pizarro³³, Aurélie Etienne^1,4, Jérémie Guedj^1,4, Alexandra Fizet⁶, Eric Barte de Sainte Fare¹⁰, Bernadette Murgue³⁴, Tuan Tran-Minh²¹, Christophe Rapp²², Pascal Piguet⁹, Marc Poncin⁹, Bertrand Draguez⁹, Thierry Allaford Duverger¹⁰, Solenne Barbe¹⁰, Guillaume Baret¹⁰, Isabelle Defourny¹⁰, Miles Carroll^15,29,35, Hervé Raoul¹⁸, Augustin Augier¹⁰, Serge P. Eholie^2,3,36, Yazdan Yazdanpanah⁴, Claire Levy-Marchal³⁴, Annick Antierens⁹, Michel Van Herp⁹, Stephan Günther^15,30, Xavier de Lamballerie⁸, Sakoba Keïta³⁷, France Mentré^1,4, Xavier Anglaret^2,3, Denis Malvy^2,7

1 INSERM, IAME, UMR 1137, F-75018 Paris, France; Université Paris Diderot, IAME, UMR 1137, Sorbonne Paris Cité, F-75018 Paris, France

2 Inserm, UMR 1219, Université de Bordeaux, Bordeaux, France

3 Programme PACCI/site ANRS de Côte d’Ivoire, Abidjan, Côte d’Ivoire

4 Assistance Publique–Hôpitaux de Paris, Hôpital Bichat Claude Bernard, Paris, France,

5 Assistance Publique–Hôpitaux de Paris, Hôpital Bicêtre, Paris, France and Inserm UMR1184, Université Paris-Sud

6 UBIVE, Institut Pasteur, Centre International de Recherche en Infectiologie, Lyon, France

7 Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France

8 Université Aix Marseille, Institut de Recherche pour le Développement, École des Hautes Études en Santé Publique, EPV, Marseille, France

9 Médecins Sans Frontières Belgique, Brussels, Belgium

10 ALIMA, Dakar, Senegal

11 Biological Light Fieldable Laboratory for Emergencies (B-LiFE)/Belgian First Aid and Support (B-FAST), Brussels, Belgium

12 Cliniques Universitaires Saint-Luc, Brussels, Belgium

13 Université Catholique de Louvain, Louvain-la-Neuve, Belgium

14 Belgian Ministry of Defense, Brussels, Belgium

15 European Mobile Laboratory Project, Hamburg, Germany

16 Institut National de Santé Publique, Conakry, Guinea

17 Laboratoire des Fièvres Hémorragiques en Guinée, Université Gamal Abdel Nasser de Conakry, Conakry, Guinea

18 Inserm, Laboratoire P4 Jean Mérieux, Lyon, France

19 Centre de Recherche en Santé Rurale, Maférinya, Guinea,

20 Rega Institute for Medical Research, Leuven, Belgium,

21 Croix Rouge Française, Paris, France,

22 Service de Santé des Armées, Paris, France,

23 Ecole Normale Supérieure, Lyon, France,

24 Friedrich Loeffler Institute–Federal Research Institute for Animal Health, Greifswald, Island of Riems, Germany,

25 Robert Koch Institute, Berlin, Germany,

26 Public Health Agency of Sweden, Solna, Sweden,

27 Assistance Publique–Hôpitaux de Paris, Hôpital Necker–Enfants Malades, Paris, France,

28 Université de Montréal, Québec, Montréal, Canada,

29 Public Health England, Porton Down, United Kingdom,

30 Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany,

31 National Institute for Infectious Diseases "L. Spallanzani", Rome, Italy,

32 Bundeswehr Institute of Microbiology, Munich, Germany,

33 Solidarité Thérapeutique et Initiatives pour la Santé (Solthis), Paris, France,

34 Inserm, Paris, France,

35 Southampton General Hospital, University of Southampton, Southampton, United Kingdom,

36 Centre Hospitalier Universitaire de Treichville, Abidjan, Côte d’Ivoire,

37 Cellule de Coordination Nationale de Lutte contre la Maladie à Virus Ebola Conakry, Guinea