Among the ten major virus outbreaks in the last 50 years, Marburg ranked first in terms of the fatality rate with 80 percent. In comparison, the recent novel coronavirus, originating from the Chinese city of Wuhan, had an estimated fatality rate of 2.2 percent as of January 31, 2020.

Alarming COVID-19 fatality rate in Mexico More than 812,000 people worldwide had died from COVID-19 as of August 24, 2020. Three of the most populous countries in the world have reported particularly large numbers of coronavirus-related deaths: Mexico, Brazil, and the United States. Out of those three nations, Mexico has the highest COVID-19 death rate, with around one in ten confirmed cases resulting in death. The high fatality rate in Mexico indicates that cases may be much higher than reported because testing capacity has been severely stretched.

Post-lockdown complacency a real danger In March 2020, each infected person was estimated to transmit the COVID-19 virus to between 1.5 and 3.5 other people, which was a higher infection rate than the seasonal flu. The coronavirus is primarily spread through respiratory droplets, and transmission commonly occurs when people are in close contact. As lockdowns ease around the world, people are being urged not to become complacent; continue to wear face coverings and practice social distancing, which can help to prevent further infections.

In terms of the number of infected people, the novel coronavirus (SARS-CoV-2) ranked third among ten major virus outbreaks as of the end of January 2020. The virus, which originated from the Chinese city of Wuhan, has since spread to around 215 countries and territories worldwide.

China searching for disease’s origins The cumulative number of COVID-19 cases in China topped 89,000 on August 11, 2020. The SARS-CoV-2 virus and the infectious disease it causes were unknown before the outbreak began in China in December 2019. Experts from the World Health Organization are now working with Chinese counterparts to identify the origins of the virus. The most common symptoms reported by Chinese patients were fever, dry cough, and fatigue.

The rapid global spread of the virus In March 2020, it was estimated that the SARS-CoV-2 virus had an infection rate of between 1.5 and 3.5, which is higher than other outbreaks that have emerged worldwide in the past two decades. According to early estimates in January 2020, the case fatality rate was around two percent, but the spread of the coronavirus has overwhelmed many countries. The case fatality rate in China was as high as 5.5 percent in mid-April 2020.

As of May 2, 2023, the outbreak of the coronavirus disease (COVID-19) had spread to almost every country in the world, and more than 6.86 million people had died after contracting the respiratory virus. Over 1.16 million of these deaths occurred in the United States.

Waves of infections Almost every country and territory worldwide have been affected by the COVID-19 disease. At the end of 2021 the virus was once again circulating at very high rates, even in countries with relatively high vaccination rates such as the United States and Germany. As rates of new infections increased, some countries in Europe, like Germany and Austria, tightened restrictions once again, specifically targeting those who were not yet vaccinated. However, by spring 2022, rates of new infections had decreased in many countries and restrictions were once again lifted.

What are the symptoms of the virus? It can take up to 14 days for symptoms of the illness to start being noticed. The most commonly reported symptoms are a fever and a dry cough, leading to shortness of breath. The early symptoms are similar to other common viruses such as the common cold and flu. These illnesses spread more during cold months, but there is no conclusive evidence to suggest that temperature impacts the spread of the SARS-CoV-2 virus. Medical advice should be sought if you are experiencing any of these symptoms.

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

Peru is the country with the highest mortality rate due to the coronavirus disease (COVID-19) in Latin America. As of November 13, 2023, the country registered over 672 deaths per 100,000 inhabitants. It was followed by Brazil, with around 331.5 fatal cases per 100,000 population. In total, over 1.76 million people have died due to COVID-19 in Latin America and the Caribbean.

Are these figures accurate? Although countries like Brazil already rank among the countries most affected by the coronavirus disease (COVID-19), there is still room to believe that the number of cases and deaths in Latin American countries are underreported. The main reason is the relatively low number of tests performed in the region. For example, Brazil, one of the most impacted countries in the world, has performed approximately 63.7 million tests as of December 22, 2022. This compared with over one billion tests performed in the United States, approximately 909 million tests completed in India, or around 522 million tests carried out in the United Kingdom.

Capacity to deal with the outbreak With the spread of the Omicron variant, the COVID-19 pandemic is putting health systems around the world under serious pressure. The lack of equipment to treat acute cases, for instance, is one of the problems affecting Latin American countries. In 2019, the number of ventilators in hospitals in the most affected countries ranged from 25.23 per 100,000 inhabitants in Brazil to 5.12 per 100,000 people in Peru.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

The leading causes of death in Massachusetts are cancer, heart disease, unintentional injury, stroke, and chronic lower respiratory disease. These mortality rates tend to be higher for people of color; and Black residents have a higher premature mortality rate overall and Asian residents have a higher rate of mortality due to stroke.

BackgroundIn a given population the age pattern of mortality is an important determinant of total number of deaths, age structure, and through effects on age structure, the number of births and thereby growth. Good mortality models exist for most populations except those experiencing generalized HIV epidemics and some developing country populations. The large number of deaths concentrated at very young and adult ages in HIV-affected populations produce a unique ‘humped’ age pattern of mortality that is not reproduced by any existing mortality models. Both burden of disease reporting and population projection methods require age-specific mortality rates to estimate numbers of deaths and produce plausible age structures. For countries with generalized HIV epidemics these estimates should take into account the future trajectory of HIV prevalence and its effects on age-specific mortality. In this paper we present a parsimonious model of age-specific mortality for countries with generalized HIV/AIDS epidemics.Methods and FindingsThe model represents a vector of age-specific mortality rates as the weighted sum of three independent age-varying components. We derive the age-varying components from a Singular Value Decomposition of the matrix of age-specific mortality rate schedules. The weights are modeled as a function of HIV prevalence and one of three possible sets of inputs: life expectancy at birth, a measure of child mortality, or child mortality with a measure of adult mortality. We calibrate the model with 320 five-year life tables for each sex from the World Population Prospects 2010 revision that come from the 40 countries of the world that have and are experiencing a generalized HIV epidemic. Cross validation shows that the model is able to outperform several existing model life table systems.ConclusionsWe present a flexible, parsimonious model of age-specific mortality for countries with generalized HIV epidemics. Combined with the outputs of existing epidemiological and demographic models, this model makes it possible to project future age-specific mortality profiles and number of deaths for countries with generalized HIV epidemics.

PurposeCardiovascular disease (CVD) is the leading cause of death in the United States, and sepsis significantly contributes to hospitalization and mortality. This study aims to assess the trends of sepsis-associated CVD mortality rates and variations in mortality based on demographics and regions in the US.MethodsThe Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) database was used to identify CVD and sepsis-related deaths from 1999 to 2022. Data on gender, race and ethnicity, age groups, region, and state classification were statistically analyzed to obtain crude and age-adjusted mortality rates (AAMR). The Joinpoint Regression Program was used to determine trends in mortality within the study period.ResultsDuring the study period, there were a total of 1,842,641 deaths with both CVD and sepsis listed as a cause of death. Sepsis-associated CVD mortality decreased between 1999 and 2013, from AAMR of 65.7 in 1999 to 58.8 in 2013 (APC −1.06*%, 95% CI: −2.12% to −0.26%), then rose to 74.3 in 2022 (APC 3.23*%, 95% CI: 2.18%–5.40%). Throughout the study period, mortality rates were highest in men, NH Black adults, and elderly adults (65+ years old). The Northeast region, which had the highest mortality rate in the initial part of the study period, was the only region to see a decline in mortality, while the Northwest, Midwest, and Southern regions experienced significant increases in mortality rates.ConclusionSepsis-associated CVD mortality has increased in the US over the past decade, and both this general trend and the demographic disparities have worsened since the onset of the COVID-19 pandemic.

BackgroundInfluenza and respiratory syncytial virus (RSV) associated mortality has not been well-established in tropical Africa.MethodsWe used the negative binomial regression method and the rate-difference method (i.e. deaths during low and high influenza/RSV activity months), to estimate excess mortality attributable to influenza and RSV using verbal autopsy data collected through a health and demographic surveillance system in Western Kenya, 2007–2013. Excess mortality rates were calculated for a) all-cause mortality, b) respiratory deaths (including pneumonia), c) HIV-related deaths, and d) pulmonary tuberculosis (TB) related deaths.ResultsUsing the negative binomial regression method, the mean annual all-cause excess mortality rate associated with influenza and RSV was 14.1 (95% confidence interval [CI] 0.0–93.3) and 17.1 (95% CI 0.0–111.5) per 100,000 person-years (PY) respectively; and 10.5 (95% CI 0.0–28.5) and 7.3 (95% CI 0.0–27.3) per 100,000 PY for respiratory deaths, respectively. Highest mortality rates associated with influenza were among ≥50 years, particularly among persons with TB (41.6[95% CI 0.0–122.7]); and with RSV were among

Among COVID-19 patients in the United States from February 12 to March 16, 2020, estimated case-fatality rates were highest for adults aged 85 years and older. Younger people appeared to have milder symptoms, and there were no deaths reported among persons aged 19 years and under.

Tracking the virus in the United States The outbreak of a previously unknown viral pneumonia was first reported in China toward the end of December 2019. The first U.S. case of COVID-19 was recorded in mid-January 2020, confirmed in a patient who had returned to the United States from China. The virus quickly started to spread, and the first community-acquired case was confirmed one month later in California. Overall, there had been approximately 4.5 million coronavirus cases in the country by the start of August 2020.

U.S. health care system stretched California, Florida, and Texas are among the states with the most coronavirus cases. Even the best-resourced hospitals in the United States have struggled to cope with the crisis, and certain areas of the country were dealt further blows by new waves of infections in July 2020. Attention is rightly focused on fighting the pandemic, but as health workers are redirected to care for COVID-19 patients, the United States must not lose sight of other important health care issues.

Yellow fever virus (Flavivirus genus) is an arthropod-borne pathogen, which can infect humans, causing a severe viscerotropic disease with a high mortality rate. Adapted viral strains allow the reproduction of yellow fever disease in hamsters with features similar to the human disease. Here, we used the Infectious Subgenomic Amplicons reverse genetics method to produce an equivalent to the hamster-virulent strain, Yellow Fever Ap7, by introducing a set of four synonymous and six nonsynonymous mutations into a single subgenomic amplicon, derived from the sequence of the Asibi strain. The resulting strain, Yellow Fever Ap7M, induced a disease similar to that described for Ap7 in terms of symptoms, weight evolution, viral loads in the liver and lethality. Using the same methodology, we produced mutant strains derived from either Ap7M or Asibi viruses and investigated the role of each of Ap7M nonsynonymous mutations in its in vivo phenotype. This allowed identifying key components of the virulence mechanism in hamsters. In Ap7M virus, the reversion of either E/Q27H or E/D155A mutations led to an important reduction of both virulence and in vivo replicative fitness. In addition, the introduction of the single D155A Ap7M mutation within the E protein of the Asibi virus was sufficient to drastically modify its phenotype in hamsters toward both a greater replication efficiency and virulence. Finally, inspection of the Asibi strain E protein structure combined to in vivo testing revealed the importance of an exposed α-helix in domain I, containing residues 154 and 155, for Ap7M virulence in hamsters.

Highly pathogenic avian influenza virus (HPAIV) has caused extensive mortalities in wild birds, with a disproportionate impact on raptors since 2021. The population-level impact of HPAIV can be informed by telemetry studies that track large samples of initially healthy, wild birds. We leveraged movement data from 71 rough-legged hawks (Buteo lagopus) across all major North American migratory bird flyways concurrent with the 2022–2023 HPAIV outbreak and identified a total of 29 mortalities, of which 11 were confirmed, and an additional ~9 were estimated to have been caused by HPAIV. We estimated a 28% HPAIV cause-specific mortality rate among rough-legged hawks during a single year concurrent with the HPAIV outbreak in North America. Additionally, the overall annual mortality rate during the HPAIV outbreak (47%) was significantly higher than baseline annual mortality rates (3–17%), suggesting that HPAIV-caused deaths were additive above baseline mortality levels. HPAIV mortalities were concentrated within the Central and Atlantic flyways during pre-breeding migration and peaked in April 2022 when large-scale HPAIV mortalities were reported in other wild birds throughout North America. HPAIV exposure was most likely caused by scavenging or preying on infected waterfowl, as rough-legged hawks are known to opportunistically scavenge during the nonbreeding season. We utilized movement data to identify a continental-scale HPAIV cause-specific mortality event in rough-legged hawks that has the potential to exacerbate ongoing population declines. Our study highlights the usefulness of monitoring movement data to pinpoint sources of mortality that can help better understand the drivers of population change, even if studies are focused on other research questions.

Middle East Respiratory Syndrome coronavirus (MERS-CoV) is classified as a Category C priority pathogen (Coronaviridae) by the National Institute of Allergy and Infectious Diseases (NIAID), and is known to cause severe respiratory disease with high mortality rates in humans. Lethal host-pathogen invasion mechanisms and the cellular intricacies behind these fatal infections still remain unclear. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013-2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. Herein, PNNL sub-projects provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open-access to viral Omics datasets and project lifecycle metadata. Secondary host-pathogen viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics (P), metabolomics (M), lipidomics (L), and transcriptomics (T) dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific MERS-CoV [NCBITAXON:1335626] experimental infection study. Host sample types include human lung adenocarcinoma cells ["Calu-3", BTO:0002750], human bronchial epithelial cells ["Calu-3 clone 2B4"; BTO:0002022], primary human fibroblasts ["FB"; BTO:0000452], primary human airway epithelial cells ["HAE"; BTO:0005571], human microvascular endothelial cells ["HMVE"; BTO:0003123], and whole mouse lung [BTO:0000763] tissue collections.

Nipah Virus Testing Market Outlook

The Nipah Virus Testing Market is projected to experience significant growth, with the market size valued at approximately USD 250 million in 2023 and expected to reach around USD 750 million by 2032, growing at a CAGR of 12.7%. The global market for Nipah virus testing is driven by the urgent need for effective diagnostic methods due to the recurrent outbreaks of the virus, the high fatality rate associated with Nipah virus infections, and the increasing awareness and preparedness for potential pandemics.

One of the primary growth factors for the Nipah virus testing market is the increased frequency and severity of Nipah virus outbreaks. Countries in Southeast Asia, particularly Bangladesh and India, have reported multiple outbreaks over the years, emphasizing the need for rapid and accurate diagnostics. This demand is further fueled by the high mortality rate associated with Nipah virus infections, which ranges from 40% to 75%, making it imperative to develop reliable testing methods to contain the spread of the virus effectively.

Another significant growth factor is the advancements in diagnostic technologies that have made testing more accessible and accurate. Innovations such as Real-Time Polymerase Chain Reaction (RT-PCR) and Enzyme-Linked Immunosorbent Assay (ELISA) have revolutionized the detection of Nipah virus, allowing for quicker and more precise identification of the virus in infected individuals. These advanced diagnostics not only contribute to better patient outcomes but also help in implementing timely public health interventions to prevent widespread transmission.

Moreover, increasing investments in healthcare infrastructure and research are also contributing to the market growth. Governments and private organizations are investing heavily in the development of diagnostic laboratories and research institutes dedicated to studying and combating emerging infectious diseases. Such investments are crucial in enhancing the capabilities of healthcare systems to respond swiftly to Nipah virus outbreaks, thereby driving the demand for Nipah virus testing solutions.

Regionally, the Asia Pacific region is expected to dominate the Nipah virus testing market due to the higher incidence of Nipah virus outbreaks in this region. Countries like India, Bangladesh, and Malaysia are investing significantly in healthcare infrastructure and diagnostic capabilities to tackle the Nipah virus effectively. In contrast, regions like North America and Europe are witnessing growth in the market due to increased awareness and preparedness for potential outbreaks, further supported by robust healthcare systems and substantial research funding.

Arbovirus Testing is becoming increasingly relevant in the context of global health as the prevalence of arboviruses, such as dengue, Zika, and chikungunya, continues to rise. These viruses, transmitted by arthropods like mosquitoes, pose significant public health challenges, particularly in tropical and subtropical regions. The development of efficient and accurate arbovirus testing methods is crucial for timely diagnosis and management of these infections. Advances in molecular diagnostics, including RT-PCR and serological assays, have enhanced the ability to detect arboviruses quickly and accurately, thereby aiding in the implementation of effective control measures. As the threat of arboviruses grows, the demand for comprehensive testing solutions is expected to increase, paralleling the trends observed in the Nipah virus testing market.

Test Type Analysis

The test type segment in the Nipah virus testing market includes Real-Time Polymerase Chain Reaction (RT-PCR), Enzyme-Linked Immunosorbent Assay (ELISA), Virus Isolation, and other diagnostic methods. Real-Time Polymerase Chain Reaction (RT-PCR) is currently the leading test type due to its high sensitivity and specificity. RT-PCR allows for the rapid detection of Nipah virus RNA in clinical samples, making it an invaluable tool in the timely diagnosis and management of Nipah virus infections. This methodÂ’s ability to detect even low levels of viral RNA contributes to its widespread adoption in diagnostic laboratories.

Enzyme-Linked Immunosorbent Assay (ELISA) is another prominent test type used in Nipah virus testing. ELISA tests are crucial for detecting antibodies against the Nipah virus in patient samples, providing valuable information about the immune response to the infection. T

Data from influenza A virus (IAV) infected ferrets (Mustela putorius furo) provides invaluable information towards the study of novel and emerging viruses that pose a threat to human health. This gold standard animal model can recapitulate many clinical signs of infection present in IAV-infected humans, support virus replication of human and zoonotic strains without prior adaptation, and permit evaluation of virus transmissibility by multiple modes. While ferrets have been employed in risk assessment settings for >20 years, results from this work are typically reported in discrete stand-alone publications, making aggregation of raw data from this work over time nearly impossible. Here, we describe a dataset of 746 ferrets inoculated with 129 unique IAV, conducted by a single research group (NCIRD/ID/IPB/Pathogenesis Laboratory Team) under a uniform experimental protocol. This collection of morbidity, mortality, and viral titer data represents the largest publicly available dataset to date of in vivo-generated IAV infection outcomes on a per-individual ferret level.

Published Data Descriptor for more information: Kieran TJ, Sun X, Creager HM, Tumpey TM, Maine TR, Belser JA. 2024. An aggregated dataset of serial morbidity and titer measurements from influenza A virus-infected ferrets. Sci Data 11, 510. https://doi.org/10.1038/s41597-024-03256-6

Additional publications using and describing data: Kieran TJ, Sun X, Maines TR, Beauchemin CAA, Belser JA. 2024. Exploring associations between viral titer measurements and disease outcomes in ferrets inoculated with 125 contemporary influenza A viruses. J Virol. 98:e01661-23. https://doi.org/10.1128/jvi.01661-23

Belser JA, Kieran TJ, Mitchell ZA, Sun X, Mayfield K, Tumpey TM, Spengler JR, Maines TR. 2024. Key considerations to improve the normalization, interpretation and reproducibility of morbidity data in mammalian models of viral disease. Dis Model Mech; 17 (3): dmm050511. https://doi.org/10.1242/dmm.050511

Kieran TJ, Sun X, Maines TR, Belser JA. 2024. Machine learning approaches for influenza A virus risk assessment identifies predictive correlates using ferret model in vivo data. Communications Biology 7, 927. https://doi.org/10.1038/s42003-024-06629-0

Additional publications supporting responsible use and interpretation of data by others: Kieran TJ, Maine TR, Belser JA. 2025. Eleven quick tips to unlock the power of in vivo data science. PLoS Comput Biol, 21(4):e1012947. https://doi.org/10.1371/journal.pcbi.1012947

Kieran TJ, Maine TR, Belser JA. 2025. Data alchemy, from lab to insight: Transforming in vivo experiments into data science gold. PLoS Pathog, 20(8):e1012460. https://doi.org/10.1371/journal.ppat.1012460

Change / Update Log: Nov 7, 2024: Corrected typographical errors in Origin column for A/Ohio/13/2017 and A/Hawaii/28/2020

July 1, 2025: Added 3 viruses (A/Texas/36/1991, A/Texas/37/2024, A/Michigan/90/2024, total n=18 new rows)

The graph displays the heart disease death rate per 100,000 people in the United States from 2000 to 2022, categorized by gender. The x-axis represents the years, ranging from 2000 to 2022, while the y-axis indicates the death rate per 100,000 individuals. The data includes three categories: "All," "Males," and "Females." Overall, there is a general downward trend in death rates for all groups from 2000 to around 2011. In 2000, the highest death rates are recorded, with "All" at 334.6, "Males" at 351.3, and "Females" at 317.2 per 100,000 people. By 2011, the rates decrease to some of their lowest values: 251.4 for "All," 251.5 for "Males," and 251.3 for "Females." After 2011, the death rates fluctuate slightly, with a slight increase observed in recent years. Notably, in 2020, there is an uptick in death rates across all categories, with "All" at 275.7, "Males" at 292.2, and "Females" at 259.5.

Recent increases in emergent infectious diseases have raised concerns about the population stability of some marine species. The complexity and expense of studying diseases in marine systems often dictate that conservation and management decisions are made without quantitative data on population-level impacts of disease. Mark-recapture is a powerful, underutilized, tool for calculating impacts of disease on population size and structure, even in the absence of etiological information. We applied logistic regression models to mark-recapture data to obtain estimates of disease-associated mortality rates in three commercially-important marine species: snow crab (Chionoecetes opilio) in Newfoundland, Canada, that experience sporadic epizootics of bitter crab disease; striped bass (Morone saxatilis) in the Chesapeake Bay, USA, that experience chronic dermal and visceral mycobacteriosis; and American lobster (Homarus americanus) in the Southern New England stock, that experience chronic epizootic shell disease. All three diseases decreased survival of diseased hosts. Survival of diseased adult male crabs was 1% (0.003 – 0.022, 95% CI) that of uninfected crabs indicating nearly complete mortality of infected crabs in this life stage. Survival of moderately and severely diseased striped bass (which comprised 15% and 11% of the population, respectively) was 84% (70 – 100%, 95% CI), and 54% (42- 68%, 95% CI) and that of healthy striped bass. The disease-adjusted yearly natural mortality rate for striped bass was 0.29, nearly double the previously accepted value, which did not include disease. Survival of moderately and severely diseased lobsters was 30% (15 – 60%, 95% CI) that of healthy lobsters and survival of mildly diseased lobsters was 45% (27 – 75%, 95% CI) that of healthy lobsters. High disease mortality in ovigerous females may explain the poor recruitment and rapid declines observed in this population. Stock assessments should account for disease-related mortality when resource management options are evaluated.

This horizontal bar chart displays deaths (people) by disease using the aggregation sum. The data is filtered where the disease is COVID-19. The data is about diseases per day.

BackgroundEbola virus disease (EVD) is a highly lethal condition for which no specific treatment has proven efficacy. In September 2014, while the Ebola outbreak was at its peak, the World Health Organization released a short list of drugs suitable for EVD research. Favipiravir, an antiviral developed for the treatment of severe influenza, was one of these. In late 2014, the conditions for starting a randomized Ebola trial were not fulfilled for two reasons. One was the perception that, given the high number of patients presenting simultaneously and the very high mortality rate of the disease, it was ethically unacceptable to allocate patients from within the same family or village to receive or not receive an experimental drug, using a randomization process impossible to understand by very sick patients. The other was that, in the context of rumors and distrust of Ebola treatment centers, using a randomized design at the outset might lead even more patients to refuse to seek care.Therefore, we chose to conduct a multicenter non-randomized trial, in which all patients would receive favipiravir along with standardized care. The objectives of the trial were to test the feasibility and acceptability of an emergency trial in the context of a large Ebola outbreak, and to collect data on the safety and effectiveness of favipiravir in reducing mortality and viral load in patients with EVD. The trial was not aimed at directly informing future guidelines on Ebola treatment but at quickly gathering standardized preliminary data to optimize the design of future studies.Methods and FindingsInclusion criteria were positive Ebola virus reverse transcription PCR (RT-PCR) test, age ≥ 1 y, weight ≥ 10 kg, ability to take oral drugs, and informed consent. All participants received oral favipiravir (day 0: 6,000 mg; day 1 to day 9: 2,400 mg/d). Semi-quantitative Ebola virus RT-PCR (results expressed in “cycle threshold” [Ct]) and biochemistry tests were performed at day 0, day 2, day 4, end of symptoms, day 14, and day 30. Frozen samples were shipped to a reference biosafety level 4 laboratory for RNA viral load measurement using a quantitative reference technique (genome copies/milliliter). Outcomes were mortality, viral load evolution, and adverse events. The analysis was stratified by age and Ct value. A “target value” of mortality was defined a priori for each stratum, to guide the interpretation of interim and final analysis.Between 17 December 2014 and 8 April 2015, 126 patients were included, of whom 111 were analyzed (adults and adolescents, ≥13 y, n = 99; young children, ≤6 y, n = 12). Here we present the results obtained in the 99 adults and adolescents. Of these, 55 had a baseline Ct value ≥ 20 (Group A Ct ≥ 20), and 44 had a baseline Ct value < 20 (Group A Ct < 20). Ct values and RNA viral loads were well correlated, with Ct = 20 corresponding to RNA viral load = 7.7 log10 genome copies/ml. Mortality was 20% (95% CI 11.6%–32.4%) in Group A Ct ≥ 20 and 91% (95% CI 78.8%–91.1%) in Group A Ct < 20. Both mortality 95% CIs included the predefined target value (30% and 85%, respectively). Baseline serum creatinine was ≥110 μmol/l in 48% of patients in Group A Ct ≥ 20 (≥300 μmol/l in 14%) and in 90% of patients in Group A Ct < 20 (≥300 μmol/l in 44%). In Group A Ct ≥ 20, 17% of patients with baseline creatinine ≥110 μmol/l died, versus 97% in Group A Ct < 20. In patients who survived, the mean decrease in viral load was 0.33 log10 copies/ml per day of follow-up. RNA viral load values and mortality were not significantly different between adults starting favipiravir within

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.