A comprehensive database of the geographic spread of past human Ebola outbreaks

Predictive Model for Estimating Annual Ebolavirus Spillover Potential

Forest changes, human population dynamics, and meteorologic conditions have been associated with zoonotic Ebolavirus spillover into humans. High-resolution spatial data for those variables can be used to produce estimates of spillover potential and assess possible annual changes. We developed a model of Ebolavirus spillover during 2001-2021, accounting for variables measured across multiple spatial and temporal scales. We estimated the annual relative odds of Ebolavirus spillover during 2021 and 2022. The highest relative spillover odds estimates occurred in patches that closely followed the spatial distribution of forest loss and fragmentation. Regions throughout equatorial Africa had increased spillover estimates related to changes in forests and human populations. Spillover events in 2022 occurred in locations in the top 0.1% of overall spillover odds estimates or where estimates increased from 2021 to 2022. This model can be used to preemptively target surveillance to identify outbreaks, mitigate disease spread, and educate the public on risk factors for infection.

Constructing a global human epidemic database using open-source digital biosurveillance

We developed a dataset consisting of outbreak data collected from official, open-source surveillance reports representing more than 170 pathogens, 237 countries and territories, and more than 3300 events that occurred primarily between 1963 and 2023. Here we present and analyze a subset of these data, comprising a dataset of human epidemic events with onset between 2015 and 2020. Structuring of epidemiological data in the dataset follows a specific methodology to ensure consistency across all events. This methodology has been designed to produce the most reliable spatiotemporal view of an outbreak as possible. To ensure data are true-to-source, the structured data undergoes multiple rounds of both manual and automated review and validation. The extensive and standardized nature of the dataset makes it well-suited for both descriptive epidemiology and exploring outbreak dynamics and disease emergence.

Fruit-frugivore dependencies are important in Ebolavirus outbreaks in Sub-Saharan Africa

Ebolaviruses have the ability to infect a wide variety of species, with many African mammals potentially serving either as primary reservoirs or secondary amplifying hosts. Previous work has shown that frugivorous bats and primates are often associated with spillover and outbreaks. Yet the role that patterns of biodiversity, either of mammalian hosts or of common fruiting species such as Ficus (figs, fruit resources used by a wide variety of species), play in driving outbreak risk remains unclear. We investigated what factors most directly influence Ebolavirus outbreak risk in Sub-Saharan Africa by using a phylogenetically informed path analysis to compare a wide array of potential models (path diagrams) of spatial dynamics. We considered mammalian frugivore richness, cercopithecid and hominid primate richness, richness of pteropodid (fruit) bats, the spatial distribution of species that have tested positive for Ebolavirus antibodies in the wild, Ficus habitat suitability, and environmental conditions (mean annual and variability in temperature and rainfall). The proximate factors that most influenced whether a given host species range contained a site of a previous outbreak event were 1) habitat suitability for Ficus and 2) the diversity of cercopithecid primates. Frugivore richness overall (including bats, primates, and a few other mammals) and the richness of bats in the family Pteropodidae had a strong effect on which species tested positive for Ebolavirus antibodies, but did not influence outbreak risk directly in pathways explored. We interpret this as evidence that foraging around Ficus and frugivorous mammals (such as cercopithecid primates which are commonly hunted for food) play a prominent role in driving outbreaks into human communities, relative to other factors we considered which influence outbreak risk more indirectly.

Human movement and transmission dynamics early in Ebola outbreaks

Human movement drives the transmission and spread of communicable pathogens. It is especially influential for emerging pathogens when population immunity is low and spillover events are rare. We digitized serial printed maps to measure transportation networks (roads and rivers) in Central and West Africa as proxies for population mobility to assess relationships between movement and Ebola transmission. We find that the lengths of roads and rivers in close proximity to spillover sites at or near the time of spillover events are significantly correlated with the number of EVD cases, particularly in the first 100 days of each outbreak. Early management and containment efforts along transportation networks may be beneficial in mitigation during the early days of transmission and spatial spread for Ebola outbreaks.

The Threat of Impending Pandemics: A Proactive Approach

The incessant occurrence of devastating health-related events, either on a large scale, such as pandemics, or in a local community in the form of sporadic outbreaks due to infectious agents, warrants a rapid, target-oriented, well-organized response team to combat the demonic consequences. While the world has been recovering from the clutches of the recent disastrous COVID-19 pandemic, the struggles against novel emerging and re-emerging pathogens such as monkeypox (mpox), newer evolving strains of influenza, Ebola, Zika, and the yellow fever virus continue to date. Therefore, a multisectoral, intercontinental, collaborative, interdisciplinary, and highly dedicated approach should always be implemented to achieve optimal health and avert future threats.

A global dataset of pandemic- and epidemic-prone disease outbreaks

This paper presents a new dataset of infectious disease outbreaks collected from the Disease Outbreak News and the Coronavirus Dashboard produced by the World Health Organization. The dataset contains information on 70 infectious diseases and 2227 public health events that occurred over the period from January 1996 to March 2022 in 233 countries and territories around the world. We illustrate the potential use of this dataset to the research community by analysing the spatial distribution of disease outbreaks. We find evidence of spatial clusters of high incidences ("hot spots") in Africa, America, and Asia. This spatial analysis enables policymakers to identify the regions with the greatest likelihood of suffering from disease outbreaks and, taking into account their degree of preparedness and vulnerability, to develop policies that may help contain the spreading of future outbreaks. Further applications could focus on combining our data with other information sources to study, for instance, the link between environmental, globalization, and/or socioeconomic factors with disease outbreaks.

Pathogenicity and Virulence of Ebolaviruses with Species- and Variant-specificity

Ebola virus (EBOV), belonging to the species Zaire ebolavirus in the genus Ebolavirus, causes a severe febrile illness in humans with case fatality rates (CFRs) up to 90%. While there have been six virus species classified, which each have a single type virus in the genus Ebolavirus, CFRs of ebolavirus infections vary among viruses belonging to each distinct species. In this review, we aim to define the ebolavirus species-specific virulence on the basis of currently available laboratory and experimental findings. In addition, this review will also cover the variant-specific virulence of EBOV by referring to the unique biological and pathogenic characteristics of EBOV variant Makona, a new EBOV variant isolated from the 2013-2016 EBOV disease outbreak in West Africa. A better definition of species-specific and variant-specific virulence of ebolaviruses will facilitate our comprehensive knowledge on genus Ebolavirus biology, leading to the development of therapeutics against well-focused pathogenic mechanisms of each Ebola disease.

Mapping of Ebola virus spillover: Suitability and seasonal variability at the landscape scale

The unexpected Ebola virus outbreak in West Africa in 2014 involving the Zaire ebolavirus made clear that other regions outside Central Africa, its previously documented niche, were at risk of future epidemics. The complex transmission cycle and a lack of epidemiological data make mapping areas at risk of the disease challenging. We used a Geographic Information System-based multicriteria evaluation (GIS-MCE), a knowledge-based approach, to identify areas suitable for Ebola virus spillover to humans in regions of Guinea, Congo and Gabon where Ebola viruses already emerged. We identified environmental, climatic and anthropogenic risk factors and potential hosts from a literature review. Geographical data layers, representing risk factors, were combined to produce suitability maps of Ebola virus spillover at the landscape scale. Our maps show high spatial and temporal variability in the suitability for Ebola virus spillover at a fine regional scale. Reported spillover events fell in areas of intermediate to high suitability in our maps, and a sensitivity analysis showed that the maps produced were robust. There are still important gaps in our knowledge about what factors are associated with the risk of Ebola virus spillover. As more information becomes available, maps produced using the GIS-MCE approach can be easily updated to improve surveillance and the prevention of future outbreaks.

Ebola virus disease is a highly pathogenic disease transmitted from wildlife to humans. It was first described in 1976 and its distribution remained restricted to Central Africa until 2014, when an outbreak in West Africa, causing more than 28,000 cases and more than 11,000 deaths, took place. Anthropogenic factors, such as bushmeat hunting, trade and consumption, and environmental and climatic factors, may promote the contact between humans and infected animals, such as bats, primates and duikers, increasing the risk of virus transmission to the human population. In this study, we used the spatial multicriteria evaluation framework to gather all available information on risk factors and animal species susceptible to infection, and produce maps of areas suitable for Ebola virus spillover in regions in Guinea, Congo and Gabon. The resulting maps highlighted high spatial and temporal variability in the suitability for Ebola virus spillover. Data from reported cases of Ebola virus transmission from wild animals to humans were used to validate the maps. The approach developed is capable of integrating a wide diversity of risk factors, and provides a flexible and simple tool for surveillance, which can be updated as more data and knowledge on risk factors become available.

Energy-transfer-mediated oxygen activation in carbonyl functionalized carbon nitride nanosheets for high-efficient photocatalytic water disinfection and organic pollutants degradation

Polymeric photocatalysts are promising candidates for water purification, however their catalytic performance are still unsatisfactory due to the fast charge recombination that leads to low reactive oxygen radicals production. In this study, a conceptual energy-transfer-mediated photocatalytic oxygen activation system over polymeric carbon nitride without the need of electron-hole separation is proposed, exhibiting remarkable singlet oxygen triggered bacteria inactivation performance as well as organic pollutants degradation. By structure and excitonic effect modulation, the oxygen activation process changes from the traditional electron-transfer mechanism to the final energy-transfer pathway, leading to the selective generation of singlet oxygen with high efficiency. The generated singlet oxygen is found to fervently attack the bacteria membrane, creating irreparable pores or holes on the cell membrane for cytoplasmic contents leaking out to accelerate bacteria destruction. The work demonstrated here offers a new photocatalytic oxygen activation pathway for achieving high-efficient reactive oxygen species generation performance without the need of charge separation.

Ribavirin does not potentiate favipiravir antiviral activity against Ebola virus in non-human primates

BACKGROUND

In spite of recurrent and dramatic outbreaks, there are no therapeutics approved against Ebola virus disease. Favipiravir, a RNA polymerase inhibitor active against several RNA viruses, recently demonstrated significant but not complete protection in a non-human primate model of Ebola virus disease. In this study, we assessed the benefit of the combination of favipiravir and ribavirin, another broad spectrum antiviral agent, in the same model.

METHODS

15 female cynomolgus macaques were challenged intramuscularly with 1,000 FFU of Ebola virus Gabon 2001 strain and followed for 21 days. All animals received favipiravir 180 mg/kg twice a day (BID), either as monotherapy (n = 5) or in combination with ribavirin (n = 10). Ribavirin was given either at the dose 10 mg/kg BID (n = 5) or 5 mg/kg BID (n = 5). Favipiravir and ribavirin were initiated two and one days before viral challenge respectively and treatment were continued for 14 days. Treatment effects on viral and hematological markers were assessed using a mathematical model. Survival rate of 0% and 20% were obtained in macaques receiving favipiravir plus ribavirin 10 and 5 mg/kg BID, respectively, compared to 40% in the favipiravir monotherapy group (P = 0.061 when comparing monotherapy and bitherapy, log rank). Viral dynamic modeling analysis did not identify an association between plasma concentrations of ribavirin and viral load levels. Using a model of erythropoiesis, plasma concentrations of ribavirin were strongly associated with a hemoglobin drop (p = 0.0015).

CONCLUSION

Ribavirin plus favipiravir did not extend survival rates and did not lower viral replication rate compared to favipiravir monotherapy in this animal model. Patients receiving this combination in other indications, such as Lassa fever, should be closely monitored to prevent potential toxicity associated with anemia.

A database of geopositioned Middle East Respiratory Syndrome Coronavirus occurrences

As a World Health Organization Research and Development Blueprint priority pathogen, there is a need to better understand the geographic distribution of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and its potential to infect mammals and humans. This database documents cases of MERS-CoV globally, with specific attention paid to zoonotic transmission. An initial literature search was conducted in PubMed, Web of Science, and Scopus; after screening articles according to the inclusion/exclusion criteria, a total of 208 sources were selected for extraction and geo-positioning. Each MERS-CoV occurrence was assigned one of the following classifications based upon published contextual information: index, unspecified, secondary, mammal, environmental, or imported. In total, this database is comprised of 861 unique geo-positioned MERS-CoV occurrences. The purpose of this article is to share a collated MERS-CoV database and extraction protocol that can be utilized in future mapping efforts for both MERS-CoV and other infectious diseases. More broadly, it may also provide useful data for the development of targeted MERS-CoV surveillance, which would prove invaluable in preventing future zoonotic spillover.

Measurement(s)	Middle East Respiratory Syndrome • geographic location
Technology Type(s)	digital curation
Factor Type(s)	geographic distribution of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) • year
Sample Characteristic - Organism	Middle East respiratory syndrome-related coronavirus
Sample Characteristic - Location	Earth (planet)

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11108801

Early transmission and case fatality of Ebola virus at the index site of the 2013-16 west African Ebola outbreak: a cross-sectional seroprevalence survey

BACKGROUND

To date, epidemiological studies at the index site of the 2013-16 west African Ebola outbreak in Meliandou, Guinea, have been restricted in their scope. We aimed to determine the occurrence of previously undocumented Ebola virus disease (EVD) cases and infections, and to reconstruct transmission events.

METHODS

This cross-sectional seroprevalence survey of the adult population of Meliandou used a highly specific oral fluid test and detailed interviews of all households in the village and key informants. Each household was interviewed, with all members prompted to describe the events of the outbreak, any illness within the household, and possible contact with suspected cases. Information for deceased individuals was provided by relatives living in the same household. Symptoms were based on Ebola virus Makona variant EVD case definitions (focusing on fever, vomiting, and diarrhoea). For antibody testing, we used an Ebola virus glycoprotein IgG capture enzyme immunoassay developed from a previously validated assay. A maximum exposure level was assigned to every participant using a predetermined scale. We used a generalised linear model (logit function) to estimate odds ratios for the association of sociodemographic variables and exposure level with Ebola virus infection. We adjusted estimates for age and maximum exposure, as appropriate.

FINDINGS

Between June 22, and July 9, 2017, we enrolled 237 participants from 27 households in Meliandou. Two households refused to participate and one was absent. All adults in participating households who were present for the interview provided an oral fluid swab for testing, of which 224 were suitable for analysis. In addition to the 11 EVD deaths described previously, on the basis of clinical description and oral fluid testing, we found two probable EVD deaths and eight previously unrecognised anti-Ebola virus IgG-positive survivors, including one who had mild symptoms and one who was asymptomatic, resulting in a case fatality of 55·6% (95% CI 30·8-78·5) for adults. Health-care work (adjusted odds ratio 6·64, 1·54-28·56; p=0·001) and level of exposure (odds ratio adjusted for linear trend across five levels 2·79, 1·59-4·883; p<0·0001) were independent risk factors for infection.

INTERPRETATION

Ebola virus infection was more widespread in this spillover population than previously recognised (21 vs 11 cases). We show the first serological evidence of survivors in this population (eight anti-Ebola virus IgG seropositive) and report a case fatality lower than previously reported (55·6% vs 100% in adults). These data show the high community coverage achievable by using a non-invasive test and, by accurately documenting the beginnings of the west African Ebola virus outbreak, reveal important insight into transmission dynamics and risk factors that underpin Ebola virus spillover events.

FUNDING

US Food and Drug Administration, Wellcome Trust, and German Research Council.

Utilizing general human movement models to predict the spread of emerging infectious diseases in resource poor settings

Human mobility is an important driver of geographic spread of infectious pathogens. Detailed information about human movements during outbreaks are, however, difficult to obtain and may not be available during future epidemics. The Ebola virus disease (EVD) outbreak in West Africa between 2014-16 demonstrated how quickly pathogens can spread to large urban centers following one cross-species transmission event. Here we describe a flexible transmission model to test the utility of generalised human movement models in estimating EVD cases and spatial spread over the course of the outbreak. A transmission model that includes a general model of human mobility significantly improves prediction of EVD's incidence compared to models without this component. Human movement plays an important role not only to ignite the epidemic in locations previously disease free, but over the course of the entire epidemic. We also demonstrate important differences between countries in population mixing and the improved prediction attributable to movement metrics. Given their relative rareness, locally derived mobility data are unlikely to exist in advance of future epidemics or pandemics. Our findings show that transmission patterns derived from general human movement models can improve forecasts of spatio-temporal transmission patterns in places where local mobility data is unavailable.

Survey of Ebola Viruses in Frugivorous and Insectivorous Bats in Guinea, Cameroon, and the Democratic Republic of the Congo, 2015-2017

To clarify the role of bats in the ecology of Ebola viruses, we assessed the prevalence of Ebola virus antibodies in a large-scale sample of bats collected during 2015–2017 from countries in Africa that have had previous Ebola outbreaks (Guinea, the Democratic Republic of the Congo) or are at high risk for outbreaks (Cameroon). We analyzed 4,022 blood samples of bats from >12 frugivorous and 27 insectivorous species; 2–37 (0.05%–0.92%) bats were seropositive for Zaire and 0–30 (0%–0.75%) bats for Sudan Ebola viruses. We observed Ebola virus antibodies in 1 insectivorous bat genus and 6 frugivorous bat species. Certain bat species widespread across Africa had serologic evidence of Zaire and Sudan Ebola viruses. No viral RNA was detected in the subset of samples tested (n = 665). Ongoing surveillance of bats and other potential animal reservoirs are required to predict and prepare for future outbreaks.

Spatiotemporal Fluctuations and Triggers of Ebola Virus Spillover

Because the natural reservoir of Ebola virus remains unclear and disease outbreaks in humans have occurred only sporadically over a large region, forecasting when and where Ebola spillovers are most likely to occur constitutes a continuing and urgent public health challenge. We developed a statistical modeling approach that associates 37 human or great ape Ebola spillovers since 1982 with spatiotemporally dynamic covariates including vegetative cover, human population size, and absolute and relative rainfall over 3 decades across sub-Saharan Africa. Our model (area under the curve 0.80 on test data) shows that spillover intensity is highest during transitions between wet and dry seasons; overall, high seasonal intensity occurs over much of tropical Africa; and spillover intensity is greatest at high (>1,000/km²) and very low (<100/km²) human population densities compared with intermediate levels. These results suggest strong seasonality in Ebola spillover from wild reservoirs and indicate particular times and regions for targeted surveillance.

Local, national, and regional viral haemorrhagic fever pandemic potential in Africa: a multistage analysis

BACKGROUND

Predicting when and where pathogens will emerge is difficult, yet, as shown by the recent Ebola and Zika epidemics, effective and timely responses are key. It is therefore crucial to transition from reactive to proactive responses for these pathogens. To better identify priorities for outbreak mitigation and prevention, we developed a cohesive framework combining disparate methods and data sources, and assessed subnational pandemic potential for four viral haemorrhagic fevers in Africa, Crimean-Congo haemorrhagic fever, Ebola virus disease, Lassa fever, and Marburg virus disease.

METHODS

In this multistage analysis, we quantified three stages underlying the potential of widespread viral haemorrhagic fever epidemics. Environmental suitability maps were used to define stage 1, index-case potential, which assesses populations at risk of infection due to spillover from zoonotic hosts or vectors, identifying where index cases could present. Stage 2, outbreak potential, iterates upon an existing framework, the Index for Risk Management, to measure potential for secondary spread in people within specific communities. For stage 3, epidemic potential, we combined local and international scale connectivity assessments with stage 2 to evaluate possible spread of local outbreaks nationally, regionally, and internationally.

FINDINGS

We found epidemic potential to vary within Africa, with regions where viral haemorrhagic fever outbreaks have previously occurred (eg, western Africa) and areas currently considered non-endemic (eg, Cameroon and Ethiopia) both ranking highly. Tracking transitions between stages showed how an index case can escalate into a widespread epidemic in the absence of intervention (eg, Nigeria and Guinea). Our analysis showed Chad, Somalia, and South Sudan to be highly susceptible to any outbreak at subnational levels.

INTERPRETATION

Our analysis provides a unified assessment of potential epidemic trajectories, with the aim of allowing national and international agencies to pre-emptively evaluate needs and target resources. Within each country, our framework identifies at-risk subnational locations in which to improve surveillance, diagnostic capabilities, and health systems in parallel with the design of policies for optimal responses at each stage. In conjunction with pandemic preparedness activities, assessments such as ours can identify regions where needs and provisions do not align, and thus should be targeted for future strengthening and support.

FUNDING

Paul G Allen Family Foundation, Bill & Melinda Gates Foundation, Wellcome Trust, UK Department for International Development.

Ecological Niche Modeling for Filoviruses: A Risk Map for Ebola and Marburg Virus Disease Outbreaks in Uganda

INTRODUCTION

Uganda has reported eight outbreaks caused by filoviruses between 2000 to 2016, more than any other country in the world. We used species distribution modeling to predict where filovirus outbreaks are likely to occur in Uganda to help in epidemic preparedness and surveillance.

METHODS

The MaxEnt software, a machine learning modeling approach that uses presence-only data was used to establish filovirus - environmental relationships. Presence-only data for filovirus outbreaks were collected from the field and online sources. Environmental covariates from Africlim that have been downscaled to a nominal resolution of 1km x 1km were used. The final model gave the relative probability of the presence of filoviruses in the study area obtained from an average of 100 bootstrap runs. Model evaluation was carried out using Receiver Operating Characteristic (ROC) plots. Maps were created using ArcGIS 10.3 mapping software.

RESULTS

We showed that bats as potential reservoirs of filoviruses are distributed all over Uganda. Potential outbreak areas for Ebola and Marburg virus disease were predicted in West, Southwest and Central parts of Uganda, which corresponds to bat distribution and previous filovirus outbreaks areas. Additionally, the models predicted the Eastern Uganda region and other areas that have not reported outbreaks before to be potential outbreak hotspots. Rainfall variables were the most important in influencing model prediction compared to temperature variables.

CONCLUSIONS

Despite the limitations in the prediction model due to lack of adequate sample records for outbreaks, especially for the Marburg cases, the models provided risk maps to the Uganda surveillance system on filovirus outbreaks. The risk maps will aid in identifying areas to focus the filovirus surveillance for early detection and responses hence curtailing a pandemic. The results from this study also confirm previous findings that suggest that filoviruses are mainly limited by the amount of rainfall received in an area.

Mapping the spatial distribution of the Japanese encephalitis vector, Culex tritaeniorhynchus Giles, 1901 (Diptera: Culicidae) within areas of Japanese encephalitis risk

BACKGROUND

Japanese encephalitis (JE) is one of the most significant aetiological agents of viral encephalitis in Asia. This medically important arbovirus is primarily spread from vertebrate hosts to humans by the mosquito vector Culex tritaeniorhynchus. Knowledge of the contemporary distribution of this vector species is lacking, and efforts to define areas of disease risk greatly depend on a thorough understanding of the variation in this mosquito's geographical distribution.

RESULTS

We assembled a contemporary database of Cx. tritaeniorhynchus presence records within Japanese encephalitis risk areas from formal literature and other relevant resources, resulting in 1,045 geo-referenced, spatially and temporally unique presence records spanning from 1928 to 2014 (71.9% of records obtained between 2001 and 2014). These presence data were combined with a background dataset capturing sample bias in our presence dataset, along with environmental and socio-economic covariates, to inform a boosted regression tree model predicting environmental suitability for Cx. tritaeniorhynchus at each 5 × 5 km gridded cell within areas of JE risk. The resulting fine-scale map highlights areas of high environmental suitability for this species across India, Nepal and China that coincide with areas of high JE incidence, emphasising the role of this vector in disease transmission and the utility of the map generated.

CONCLUSIONS

Our map contributes towards efforts determining the spatial heterogeneity in Cx. tritaeniorhynchus distribution within the limits of JE transmission. Specifically, this map can be used to inform vector control programs and can be used to identify key areas where the prevention of Cx. tritaeniorhynchus establishment should be a priority.

Geographic potential of disease caused by Ebola and Marburg viruses in Africa

Filoviruses represent a significant public health threat worldwide. West Africa recently experienced the largest-scale and most complex filovirus outbreak yet known, which underlines the need for a predictive understanding of the geographic distribution and potential for transmission to humans of these viruses. Here, we used ecological niche modeling techniques to understand the relationship between known filovirus occurrences and environmental characteristics. Our study derived a picture of the potential transmission geography of Ebola virus species and Marburg, paired with views of the spatial uncertainty associated with model-to-model variation in our predictions. We found that filovirus species have diverged ecologically, but only three species are sufficiently well known that models could be developed with significant predictive power. We quantified uncertainty in predictions, assessed potential for outbreaks outside of known transmission areas, and highlighted the Ethiopian Highlands and scattered areas across East Africa as additional potentially unrecognized transmission areas.

Rethinking Urban Epidemiology: Natures, Networks and Materialities

How should we understand the relationship between urban environments and infectious diseases? This article addresses this question from three particular perspectives: that of the materialities of health, that of nature and that of networks. The first perspective analytically blends biological dynamics, environmental influence and social practice. The second perspective, mainly influenced by multispecies ethnographies, foregrounds the liveliness and unboundedness of cities. Finally, the third perspective analyses how health is drawn into the domain of security. The article argues that while globalization and urbanization are often discussed as having triggered the emergence and spread of pathogens, urban epidemics are not self-evident and 'natural' consequences of these pro-cesses. They do not fall neatly into universal categories of space, modernity or risk; rather, they are produced and shaped by a range of social, political, biological and economic sites and scales. Accordingly, the emergence of pathogens depends on its articulation through specific analytical frameworks. This article suggests that a critical focus on how infectious diseases manifest themselves differently in different local contexts may not only provide insights into the manifold forms of urban life, but also into the multiple, complex and highly political constitution of health.

Ecological Contexts of Index Cases and Spillover Events of Different Ebolaviruses

Ebola virus disease afflicts both human and animal populations and is caused by four ebolaviruses. These different ebolaviruses may have distinct reservoir hosts and ecological contexts that determine how, where, and when different ebolavirus spillover events occur. Understanding these virus-specific relationships is important for preventing transmission of ebolaviruses from wildlife to humans. We examine the ecological contexts surrounding 34 human index case infections of ebolaviruses from 1976-2014. Determining possible sources of spillover from wildlife, characterizing the environment of each event, and creating ecological niche models to estimate habitats suitable for spillover, we find that index case infections of two ebolaviruses, Ebola virus and Sudan virus, have occurred under different ecological contexts. The index cases of Ebola virus infection are more associated with tropical evergreen broadleaf forests and consuming bushmeat than the cases of Sudan virus. Given these differences, we emphasize caution when generalizing across different ebolaviruses and that location and virus-specific ecological knowledge will be essential to unravelling how human and animal behavior lead to the emergence of Ebola virus disease.

Updates to the zoonotic niche map of Ebola virus disease in Africa

As the outbreak of Ebola virus disease (EVD) in West Africa is now contained, attention is turning from control to future outbreak prediction and prevention. Building on a previously published zoonotic niche map (Pigott et al., 2014), this study incorporates new human and animal occurrence data and expands upon the way in which potential bat EVD reservoir species are incorporated. This update demonstrates the potential for incorporating and updating data used to generate the predicted suitability map. A new data portal for sharing such maps is discussed. This output represents the most up-to-date estimate of the extent of EVD zoonotic risk in Africa. These maps can assist in strengthening surveillance and response capacity to contain viral haemorrhagic fevers.

DOI:http://dx.doi.org/10.7554/eLife.16412.001

Host-Primed Ebola Virus GP Exposes a Hydrophobic NPC1 Receptor-Binding Pocket, Revealing a Target for Broadly Neutralizing Antibodies

The filovirus surface glycoprotein (GP) mediates viral entry into host cells. Following viral internalization into endosomes, GP is cleaved by host cysteine proteases to expose a receptor-binding site (RBS) that is otherwise hidden from immune surveillance. Here, we present the crystal structure of proteolytically cleaved Ebola virus GP to a resolution of 3.3 Å. We use this structure in conjunction with functional analysis of a large panel of pseudotyped viruses bearing mutant GP proteins to map the Ebola virus GP endosomal RBS at molecular resolution. Our studies indicate that binding of GP to its endosomal receptor Niemann-Pick C1 occurs in two distinct stages: the initial electrostatic interactions are followed by specific interactions with a hydrophobic trough that is exposed on the endosomally cleaved GP1 subunit. Finally, we demonstrate that monoclonal antibodies targeting the filovirus RBS neutralize all known filovirus GPs, making this conserved pocket a promising target for the development of panfilovirus therapeutics.

IMPORTANCE

Ebola virus uses its glycoprotein (GP) to enter new host cells. During entry, GP must be cleaved by human enzymes in order for receptor binding to occur. Here, we provide the crystal structure of the cleaved form of Ebola virus GP. We demonstrate that cleavage exposes a site at the top of GP and that this site binds the critical domain C of the receptor, termed Niemann-Pick C1 (NPC1). We perform mutagenesis to find parts of the site essential for binding NPC1 and map distinct roles for an upper, charged crest and lower, hydrophobic trough in cleaved GP. We find that this 3-dimensional site is conserved across the filovirus family and that antibody directed against this site is able to bind cleaved GP from every filovirus tested and neutralize viruses bearing those GPs.

Ebolavirus comparative genomics

The 2014 Ebola outbreak in West Africa is the largest documented for this virus. To examine the dynamics of this genome, we compare more than 100 currently available ebolavirus genomes to each other and to other viral genomes. Based on oligomer frequency analysis, the family Filoviridae forms a distinct group from all other sequenced viral genomes. All filovirus genomes sequenced to date encode proteins with similar functions and gene order, although there is considerable divergence in sequences between the three genera Ebolavirus, Cuevavirus and Marburgvirus within the family Filoviridae. Whereas all ebolavirus genomes are quite similar (multiple sequences of the same strain are often identical), variation is most common in the intergenic regions and within specific areas of the genes encoding the glycoprotein (GP), nucleoprotein (NP) and polymerase (L). We predict regions that could contain epitope-binding sites, which might be good vaccine targets. This information, combined with glycosylation sites and experimentally determined epitopes, can identify the most promising regions for the development of therapeutic strategies.This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Mapping the zoonotic niche of Lassa fever in Africa

Background

Lassa fever is a viral haemorrhagic illness responsible for disease outbreaks across West Africa. It is a zoonosis, with the primary reservoir species identified as the Natal multimammate mouse, Mastomys natalensis. The host is distributed across sub-Saharan Africa while the virus' range appears to be restricted to West Africa. The majority of infections result from interactions between the animal reservoir and human populations, although secondary transmission between humans can occur, particularly in hospital settings.

Methods

Using a species distribution model, the locations of confirmed human and animal infections with Lassa virus (LASV) were used to generate a probabilistic surface of zoonotic transmission potential across sub-Saharan Africa.

Results

Our results predict that 37.7 million people in 14 countries, across much of West Africa, live in areas where conditions are suitable for zoonotic transmission of LASV. Four of these countries, where at-risk populations are predicted, have yet to report any cases of Lassa fever.

Conclusions

These maps act as a spatial guide for future surveillance activities to better characterise the geographical distribution of the disease and understand the anthropological, virological and zoological interactions necessary for viral transmission. Combining this zoonotic niche map with detailed patient travel histories can aid differential diagnoses of febrile illnesses, enabling a more rapid response in providing care and reducing the risk of onward transmission.

A review of epidemiological parameters from Ebola outbreaks to inform early public health decision-making

The unprecedented scale of the Ebola outbreak in West Africa has, as of 29 April 2015, resulted in more than 10,884 deaths among 26,277 cases. Prior to the ongoing outbreak, Ebola virus disease (EVD) caused relatively small outbreaks (maximum outbreak size 425 in Gulu, Uganda) in isolated populations in central Africa. Here, we have compiled a comprehensive database of estimates of epidemiological parameters based on data from past outbreaks, including the incubation period distribution, case fatality rate, basic reproduction number (R 0 ), effective reproduction number (R t ) and delay distributions. We have compared these to parameter estimates from the ongoing outbreak in West Africa. The ongoing outbreak, because of its size, provides a unique opportunity to better understand transmission patterns of EVD. We have not performed a meta-analysis of the data, but rather summarize the estimates by virus from comprehensive investigations of EVD and Marburg outbreaks over the past 40 years. These estimates can be used to parameterize transmission models to improve understanding of initial spread of EVD outbreaks and to inform surveillance and control guidelines.

A global compendium of human Crimean-Congo haemorrhagic fever virus occurrence

In order to map global disease risk, a geographic database of human Crimean-Congo haemorrhagic fever virus (CCHFV) occurrence was produced by surveying peer-reviewed literature and case reports, as well as informal online sources. Here we present this database, comprising occurrence data linked to geographic point or polygon locations dating from 1953 to 2013. We fully describe all data collection, geo-positioning, database management and quality-control procedures. This is the most comprehensive database of confirmed CCHF occurrence in humans to-date, containing 1,721 geo-positioned occurrences in total.

Mapping the zoonotic niche of Marburg virus disease in Africa

Background

Marburg virus disease (MVD) describes a viral haemorrhagic fever responsible for a number of outbreaks across eastern and southern Africa. It is a zoonotic disease, with the Egyptian rousette (Rousettus aegyptiacus) identified as a reservoir host. Infection is suspected to result from contact between this reservoir and human populations, with occasional secondary human-to-human transmission.

Methods

Index cases of previous human outbreaks were identified and reports of infection in animals recorded. These data were modelled within a species distribution modelling framework in order to generate a probabilistic surface of zoonotic transmission potential of MVD across sub-Saharan Africa.

Results

Areas suitable for zoonotic transmission of MVD are predicted in 27 countries inhabited by 105 million people. Regions are suggested for exploratory surveys to better characterise the geographical distribution of the disease, as well as for directing efforts to communicate the risk of practices enhancing zoonotic contact.

Conclusions

These maps can inform future contingency and preparedness strategies for MVD control, especially where secondary transmission is a risk. Coupling this risk map with patient travel histories could be used to guide the differential diagnosis of highly transmissible pathogens, enabling more rapid response to outbreaks of haemorrhagic fever.