Temporal and spatial analysis of the 2014-2015 Ebola virus outbreak in West Africa.

West Africa is currently witnessing the most extensive Ebola virus (EBOV) outbreak so far recorded. Until now, there have been 27,013 reported cases and 11,134 deaths. The origin of the virus is thought to have been a zoonotic transmission from a bat to a two-year-old boy in December 2013 (ref. 2). From this index case the virus was spread by human-to-human contact throughout Guinea, Sierra Leone and Liberia. However, the origin of the particular virus in each country and time of transmission is not known and currently relies on epidemiological analysis, which may be unreliable owing to the difficulties of obtaining patient information. Here we trace the genetic evolution of EBOV in the current outbreak that has resulted in multiple lineages. Deep sequencing of 179 patient samples processed by the European Mobile Laboratory, the first diagnostics unit to be deployed to the epicentre of the outbreak in Guinea, reveals an epidemiological and evolutionary history of the epidemic from March 2014 to January 2015. Analysis of EBOV genome evolution has also benefited from a similar sequencing effort of patient samples from Sierra Leone. Our results confirm that the EBOV from Guinea moved into Sierra Leone, most likely in April or early May. The viruses of the Guinea/Sierra Leone lineage mixed around June/July 2014. Viral sequences covering August, September and October 2014 indicate that this lineage evolved independently within Guinea. These data can be used in conjunction with epidemiological information to test retrospectively the effectiveness of control measures, and provides an unprecedented window into the evolution of an ongoing viral haemorrhagic fever outbreak.

CLASSIFICATION AND REGRESSION TREE ANALYSIS FOR PREDICTING PROGNOSIS IN WILDLIFE REHABILITATION: A CASE STUDY OF LEPTOSPIROSIS IN CALIFORNIA SEA LIONS (ZALOPHUS CALIFORNIANUS).

The spirochete bacterium Leptospira interrogans serovar Pomona is enzootic to California sea lions (CSL; Zalophus californianus) and causes periodic epizootics. Leptospirosis in CSL is associated with a high fatality rate in rehabilitation. Evidence-based tools for estimating prognosis and guiding early euthanasia of animals with a low probability of survival are critical to reducing the severity and duration of animal suffering. Classification and regression tree (CART) analysis of clinical data was used to predict survival outcomes of CSL with leptospirosis in rehabilitation. Classification tree outputs are binary decision trees that can be readily interpreted and applied by a clinician. Models were trained using data from cases treated from 2017 to 2018 at The Marine Mammal Center in Sausalito, CA, and tested against data from cases treated from 2010 to 2012. Two separate classification tree analyses were performed, one including and one excluding data from euthanized animals. When data from natural deaths and euthanasias were included in model-building, the best classification tree predicted outcomes correctly for 84.7% of cases based on four variables: appetite over the first 3 days in care, and blood urea nitrogen (BUN), creatinine, and sodium at admission. When only natural deaths were included, the best model predicted outcomes correctly for 87.6% of cases based on BUN and creatinine at admission. This study illustrates that CART analysis can be successfully applied to wildlife in rehabilitation to establish evidence-based euthanasia criteria with the goal of minimizing animal suffering. In the context of a large epizootic that challenges the limits of a facility's capacity for care, the models can assist in maximizing allocation of resources to those animals with the highest predicted probability of survival. This technique may be a useful tool for other diseases seen in wildlife rehabilitation.

Density dependence and persistence of Morogoro arenavirus transmission in a fluctuating population of its reservoir host.

A key aim in wildlife disease ecology is to understand how host and parasite characteristics influence parasite transmission and persistence. Variation in host population density can have strong impacts on transmission and outbreaks, and theory predicts particular transmission-density patterns depending on how parasites are transmitted between individuals. Here, we present the results of a study on the dynamics of Morogoro arenavirus in a population of multimammate mice (Mastomys natalensis). This widespread African rodent, which is also the reservoir host of Lassa arenavirus in West Africa, is known for its strong seasonal density fluctuations driven by food availability. We investigated to what degree virus transmission changes with host population density and how the virus might be able to persist during periods of low host density. A seven-year capture-mark-recapture study was conducted in Tanzania where rodents were trapped monthly and screened for the presence of antibodies against Morogoro virus. Observed seasonal seroprevalence patterns were compared with those generated by mathematical transmission models to test different hypotheses regarding the degree of density dependence and the role of chronically infected individuals. We observed that Morogoro virus seroprevalence correlates positively with host density with a lag of 1-4 months. Model results suggest that the observed seasonal seroprevalence dynamics can be best explained by a combination of vertical and horizontal transmission and that a small number of animals need to be infected chronically to ensure viral persistence. Transmission dynamics and viral persistence were best explained by the existence of both acutely and chronically infected individuals and by seasonally changing transmission rates. Due to the presence of chronically infected rodents, rodent control is unlikely to be a feasible approach for eliminating arenaviruses such as Lassa virus from Mastomys populations.

When Viruses Don't Go Viral: The Importance of Host Phylogeographic Structure in the Spatial Spread of Arenaviruses.

Many emerging infections are RNA virus spillovers from animal reservoirs. Reservoir identification is necessary for predicting the geographic extent of infection risk, but rarely are taxonomic levels below the animal species considered as reservoir, and only key circumstances in nature and methodology allow intrinsic virus-host associations to be distinguished from simple geographic (co-)isolation. We sampled and genetically characterized in detail a contact zone of two subtaxa of the rodent Mastomys natalensis in Tanzania. We find two distinct arenaviruses, Gairo and Morogoro virus, each spatially confined to a single M. natalensis subtaxon, only co-occurring at the contact zone's centre. Inter-subtaxon hybridization at this centre and a continuum of quality habitat for M. natalensis show that both viruses have the ecological opportunity to spread into the other substaxon's range, but do not, strongly suggesting host-intrinsic barriers. Such barriers could explain why human cases of another M. natalensis-borne arenavirus, Lassa virus, are limited to West Africa.

Estimating Time of Infection Using Prior Serological and Individual Information Can Greatly Improve Incidence Estimation of Human and Wildlife Infections.

Diseases of humans and wildlife are typically tracked and studied through incidence, the number of new infections per time unit. Estimating incidence is not without difficulties, as asymptomatic infections, low sampling intervals and low sample sizes can introduce large estimation errors. After infection, biomarkers such as antibodies or pathogens often change predictably over time, and this temporal pattern can contain information about the time since infection that could improve incidence estimation. Antibody level and avidity have been used to estimate time since infection and to recreate incidence, but the errors on these estimates using currently existing methods are generally large. Using a semi-parametric model in a Bayesian framework, we introduce a method that allows the use of multiple sources of information (such as antibody level, pathogen presence in different organs, individual age, season) for estimating individual time since infection. When sufficient background data are available, this method can greatly improve incidence estimation, which we show using arenavirus infection in multimammate mice as a test case. The method performs well, especially compared to the situation in which seroconversion events between sampling sessions are the main data source. The possibility to implement several sources of information allows the use of data that are in many cases already available, which means that existing incidence data can be improved without the need for additional sampling efforts or laboratory assays.

Analysis of Diagnostic Findings From the European Mobile Laboratory in Guéckédou, Guinea, March 2014 Through March 2015.

BACKGROUND: A unit of the European Mobile Laboratory (EMLab) consortium was deployed to the Ebola virus disease (EVD) treatment unit in Guéckédou, Guinea, from March 2014 through March 2015. METHODS: The unit diagnosed EVD and malaria, using the RealStar Filovirus Screen reverse transcription-polymerase chain reaction (RT-PCR) kit and a malaria rapid diagnostic test, respectively. RESULTS: The cleaned EMLab database comprised 4719 samples from 2741 cases of suspected EVD from Guinea. EVD was diagnosed in 1231 of 2178 hospitalized patients (57%) and in 281 of 563 who died in the community (50%). Children aged <15 years had the highest proportion of Ebola virus-malaria parasite coinfections. The case-fatality ratio was high in patients aged <5 years (80%) and those aged >74 years (90%) and low in patients aged 10-19 years (40%). On admission, RT-PCR analysis of blood specimens from patients who died in the hospital yielded a lower median cycle threshold (Ct) than analysis of blood specimens from survivors (18.1 vs 23.2). Individuals who died in the community had a median Ct of 21.5 for throat swabs. Multivariate logistic regression on 1047 data sets revealed that low Ct values, ages of <5 and ≥45 years, and, among children aged 5-14 years, malaria parasite coinfection were independent determinants of a poor EVD outcome. CONCLUSIONS: Virus load, age, and malaria parasite coinfection play a role in the outcome of EVD.

Dilemmas in Managing Pregnant Women With Ebola: 2 Case Reports.

We report 2 cases of Ebola viral disease (EVD) in pregnant women who survived, initially with intact pregnancies. Respectively 31-32 days after negativation of the maternal blood EVD-polymerase chain reaction (PCR) both patients delivered a stillborn fetus with persistent EVD-PCR amniotic fluid positivity.

Ammonium improves elution of fixed dried blood spots without affecting immunofluorescence assay quality.

OBJECTIVE: To solve the problem of fixed dried blood spot elution without damaging IgG antibodies. METHODS: The minimum effective concentration of liquid ammonium (NH3 ) in a PBS solution, which was found to elute fixed blood, was determined. By using a dilution series, the effects of NH3 on IgG antibody quality were assessed using immunofluorescence assays. RESULTS: The minimum effective concentration of 0.2% NH3 has no detectable effects on IgG quality. CONCLUSION: Ammonium greatly improves blood elution from fixed DBS while maintaining IgG antibody quality. These results are encouraging and provide a basis for further testing of the efficacy of ammonium in different situations as well as its effect on other compounds.

Twenty-nine years of continuous monthly capture-mark-recapture data of multimammate mice (Mastomys natalensis) in Morogoro, Tanzania.

The multimammate mice (Mastomys natalensis) is the most-studied rodent species in sub-Saharan Africa, where it is an important pest species in agriculture and carrier of zoonotic diseases (e.g. Lassa virus). Here, we provide a unique dataset that consists of twenty-nine years of continuous monthly capture-mark-recapture entries on one 3 ha mosaic field (MOSA) in Morogoro, Tanzania. It is one of the most accurate and long-running capture-recapture time series on a small mammal species worldwide and unique to Africa. The database can be used by ecologists to test hypotheses on the population dynamics of small mammals (e.g. to test the effect of climate change), or to validate new algorithms on real long-term field data (e.g. new survival analyses techniques). It is also useful for both scientists and decision-makers who want to optimize rodent control strategies and predict outbreaks of multimammate mice.

The symptomatology and diagnosis of domoic acid toxicosis in stranded California sea lions (Zalophus californianus): a review and evaluation of 20 years of cases to guide prognosis.

Introduction: Domoic acid (DA) is a glutaminergic excitatory neurotoxin that causes the morbidity and mortality of California sea lions (Zalophus californianus; CSL) and other marine mammals due to a suite of effects mostly on the nervous and cardiac systems. Between 1998 and 2019, 11,737 live-stranded CSL were admitted to The Marine Mammal Center (TMMC; Sausalito, CA, USA), over 2,000 of which were intoxicated by DA. A plethora of clinical research has been performed over the past 20 years to characterize the range of toxic effects of DA exposure on CSLs, generating the largest dataset on the effects of natural exposure to this toxin in wildlife. Materials and methods: In this study, we review published methods for diagnosing DA intoxication, clinical presentation, and treatment of DA-intoxicated CSL and present a practical, reproducible scoring system called the neuroscore (NS) to help assess whether a DA-affected CSL is fit for release to the wild following rehabilitation. Logistic regression models were used to assess the relationships between outcome (released vs. euthanized or died) and multiple variables to predict the outcome for a subset of 92 stranded CSLs. Results: The largest proportion of DA-intoxicated CSLs was adult females (58.6%). The proportions of acute and chronic cases were 63.5 and 36.5% respectively, with 44% of affected CSL released and 56% either dying naturally or euthanized. The average time in rehabilitation was 15.9 days (range 0-169) for all outcomes. The best-performing model (85% accuracy; area under the curve = 0.90) assessing the relationship between outcome and predictor variables consisted of four variables: final NS, change in NS over time, whether the animal began eating in rehabilitation, and the state of nutrition on admission. Discussion: Our results provide longitudinal information on the symptomatology of CSL intoxicated by domoic acid and suggest that a behavioral scoring system is a useful tool to assess the fitness for the release of DA-intoxicated CSL.

Pathogenic Leptospira are widespread in the urban wildlife of southern California.

Leptospirosis, the most widespread zoonotic disease in the world, is broadly understudied in multi-host wildlife systems. Knowledge gaps regarding Leptospira circulation in wildlife, particularly in densely populated areas, contribute to frequent misdiagnoses in humans and domestic animals. We assessed Leptospira prevalence levels and risk factors in five target wildlife species across the greater Los Angeles region: striped skunks (Mephitis mephitis), raccoons (Procyon lotor), coyotes (Canis latrans), Virginia opossums (Didelphis virginiana), and fox squirrels (Sciurus niger). We sampled more than 960 individual animals, including over 700 from target species in the greater Los Angeles region, and an additional 266 sampled opportunistically from other California regions and species. In the five target species seroprevalences ranged from 5 to 60%, and infection prevalences ranged from 0.8 to 15.2% in all except fox squirrels (0%). Leptospira phylogenomics and patterns of serologic reactivity suggest that mainland terrestrial wildlife, particularly mesocarnivores, could be the source of repeated observed introductions of Leptospira into local marine and island ecosystems. Overall, we found evidence of widespread Leptospira exposure in wildlife across Los Angeles and surrounding regions. This indicates exposure risk for humans and domestic animals and highlights that this pathogen can circulate endemically in many wildlife species even in densely populated urban areas.

The General Growth Tendency: A tool to improve publication trend reporting by removing record inflation bias and enabling quantitative trend analysis.

The trend of the number of publications on a research field is often used to quantify research interest and effort, but this measure is biased by general publication record inflation. This study introduces a novel metric as an unbiased and quantitative tool for trend analysis and bibliometrics. The metric was used to reanalyze reported publication trends and perform in-depth trend analyses on patent groups and a broad range of field in the life-sciences. The analyses confirmed that inflation bias frequently results in the incorrect identification of field-specific increased growth. It was shown that the metric enables a more detailed, quantitative and robust trend analysis of peer reviewed publications and patents. Some examples of the metric's uses are quantifying inflation-corrected growth in research regarding microplastics (51% ± 10%) between 2012 and 2018 and detecting inflation-corrected growth increase for transcriptomics and metabolomics compared to genomics and proteomics (Tukey post hoc p<0.0001). The developed trend-analysis tool removes inflation bias from bibliometric trend analyses. The metric improves evidence-driven decision-making regarding research effort investment and funding allocation.

SARS-CoV-2: Cross-scale Insights from Ecology and Evolution.

Ecological and evolutionary processes govern the fitness, propagation, and interactions of organisms through space and time, and viruses are no exception. While coronavirus disease 2019 (COVID-19) research has primarily emphasized virological, clinical, and epidemiological perspectives, crucial aspects of the pandemic are fundamentally ecological or evolutionary. Here, we highlight five conceptual domains of ecology and evolution - invasion, consumer-resource interactions, spatial ecology, diversity, and adaptation - that illuminate (sometimes unexpectedly) the emergence and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We describe the applications of these concepts across levels of biological organization and spatial scales, including within individual hosts, host populations, and multispecies communities. Together, these perspectives illustrate the integrative power of ecological and evolutionary ideas and highlight the benefits of interdisciplinary thinking for understanding emerging viruses.

Sympatric occurrence of 3 arenaviruses, Tanzania.

To determine the specificity of Morogoro virus for its reservoir host, we studied its host range and genetic diversity in Tanzania. We found that 2 rodent species other than Mastomys natalensis mice carry arenaviruses. Analysis of 340 nt of the viral RNA polymerase gene showed sympatric occurrence of 3 distinct arenaviruses.

Why Hantavirus Prevalence Does Not Always Increase With Host Density: Modeling the Role of Host Spatial Behavior and Maternal Antibodies.

For wildlife diseases, one often relies on host density to predict host infection prevalence and the subsequent force of infection to humans in the case of zoonoses. Indeed, if transmission is mainly indirect, i.e., by way of the environment, the force of infection is expected to increase with host density, yet the laborious field data supporting this theoretical claim are often absent. Hantaviruses are among those zoonoses that have been studied extensively over the past decades, as they pose a significant threat to humans. In Europe, the most widespread hantavirus is the Puumala virus (PUUV), which is carried by the bank vole and causes nephropathia epidemica (NE) in humans. Extensive field campaigns have been carried out in Central Finland to shed light on this supposed relationship between bank vole density and PUUV prevalence and to identify other drivers for the infection dynamics. This resulted in the surprising observation that the relationship between bank vole density and PUUV prevalence is not purely monotonic on an annual basis, contrary to what previous models predicted: a higher vole density does not necessary result in a higher infection prevalence, nor in an increased number of humans reported having NE. Here, we advance a novel individual-based spatially-explicit model which takes into account the immunity provided by maternal antibodies and which simulates the spatial behavior of the host, both possible causes for this discrepancy that were not accounted for in previous models. We show that the reduced prevalence in peak years can be attributed to transient immunity, and that the density-dependent spatial vole behavior, i.e., the fact that home ranges are smaller in high density years, plays only a minor role. The applicability of the model is not limited to the study and prediction of PUUV (and NE) occurrence in Europe, as it could be easily adapted to model other rodent-borne diseases, either with indirect or direct transmission.

Quantifying antibody kinetics and RNA detection during early-phase SARS-CoV-2 infection by time since symptom onset.

Understanding and mitigating SARS-CoV-2 transmission hinges on antibody and viral RNA data that inform exposure and shedding, but extensive variation in assays, study group demographics and laboratory protocols across published studies confounds inference of true biological patterns. Our meta-analysis leverages 3214 datapoints from 516 individuals in 21 studies to reveal that seroconversion of both IgG and IgM occurs around 12 days post-symptom onset (range 1-40), with extensive individual variation that is not significantly associated with disease severity. IgG and IgM detection probabilities increase from roughly 10% at symptom onset to 98-100% by day 22, after which IgM wanes while IgG remains reliably detectable. RNA detection probability decreases from roughly 90% to zero by day 30, and is highest in feces and lower respiratory tract samples. Our findings provide a coherent evidence base for interpreting clinical diagnostics, and for the mathematical models and serological surveys that underpin public health policies.

The linear no-threshold model is less realistic than threshold or hormesis-based models: An evolutionary perspective.

The linear no-threshold (LNT) risk model is the current human health risk assessment paradigm. This model states that adverse stochastic biological responses to high levels of a stressor can be used to estimate the response to low or moderate levels of that stressor. In recent years the validity of the LNT risk model has increasingly been questioned because of the recurring observation that an organism's response to high stressor doses differs from that to low doses. This raises important questions about the biological and evolutionary validity of the LNT model. In this review we reiterate that the LNT model as applied to stochastic biological effects of low and moderate stressor levels has less biological validity than threshold or, particularly, hormetic models. In so doing, we rely heavily on literature from disciplines like ecophysiology or evolutionary ecology showing how exposure to moderate amounts of stress can have severe impacts on phenotype and organism reproductive fitness. We present a mathematical model that illustrates and explores the hypothetical conditions that make a particular kind of hormesis (conditioning hormesis) ecologically and evolutionarily plausible.

Cross-species pathogen spillover across ecosystem boundaries: mechanisms and theory.

Pathogen spillover between different host species is the trigger for many infectious disease outbreaks and emergence events, and ecosystem boundary areas have been suggested as spatial hotspots of spillover. This hypothesis is largely based on suspected higher rates of zoonotic disease spillover and emergence in fragmented landscapes and other areas where humans live in close vicinity to wildlife. For example, Ebola virus outbreaks have been linked to contacts between humans and infected wildlife at the rural-forest border, and spillover of yellow fever via mosquito vectors happens at the interface between forest and human settlements. Because spillover involves complex interactions between multiple species and is difficult to observe directly, empirical studies are scarce, particularly those that quantify underlying mechanisms. In this review, we identify and explore potential ecological mechanisms affecting spillover of pathogens (and parasites in general) at ecosystem boundaries. We borrow the concept of 'permeability' from animal movement ecology as a measure of the likelihood that hosts and parasites are present in an ecosystem boundary region. We then discuss how different mechanisms operating at the levels of organisms and ecosystems might affect permeability and spillover. This review is a step towards developing a general theory of cross-species parasite spillover across ecosystem boundaries with the eventual aim of improving predictions of spillover risk in heterogeneous landscapes. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.

Evaluation of rodent control to fight Lassa fever based on field data and mathematical modelling.

The Natal multimammate mouse (Mastomys natalensis) is the reservoir host of Lassa virus, an arenavirus that causes Lassa haemorrhagic fever in humans in West Africa. Because no vaccine exists and therapeutic options are limited, preventing infection through rodent control and human behavioural measures is currently considered to be the only option. In order to assess the efficacy of rodent control, we performed a 4-year field experiment in rural Upper Guinea and developed a mathematical model to simulate different control strategies (annual density control, continuous density control, and rodent vaccination). For the field study, rodenticide baits were placed each year in three rural villages, while three other villages were used as controls. Rodents were trapped before and after every treatment and their antibody status and age were determined. Data from the field study were used to parameterize the mathematical model. In the field study, we found a significant negative effect of rodent control on seroprevalence, but this effect was small especially given the effort. Furthermore, the rodent populations recovered rapidly after rodenticide application, leading us to conclude that an annual control strategy is unlikely to significantly reduce Lassa virus spillover to humans. In agreement with this finding, the mathematical model suggests that the use of continuous control or rodent vaccination is the only strategy that could lead to Lassa virus elimination. These field and model results can serve as a guide for determining how long and frequent rodent control should be done in order to eliminate Lassa virus in rural villages.

Rodent-borne infections in rural Ghanaian farming communities.

Rodents serve as reservoirs and/or vectors for several human infections of high morbidity and mortality in the tropics. Population growth and demographic shifts over the years have increased contact with these mammals, thereby increasing opportunities for disease transmission. In Africa, the burden of rodent-borne diseases is not well described. To investigate human seroprevalence of selected rodent-borne pathogens, sera from 657 healthy adults in ten rural communities in Ghana were analyzed. An in-house enzyme-linked immunosorbent assay (ELISA), for immunoglobulin G (IgG) antibodies to Lassa virus was positive in 34 (5%) of the human samples. Using commercial kits, antibodies to hantavirus serotypes, Puumala and Dobrava, and Leptospira bacteria were detected in 11%, 12% and 21% of the human samples, respectively. Forty percent of residents in rural farming communities in Ghana have measurable antibodies to at least one of the rodent-borne pathogens tested, including antibodies to viral hemorrhagic fever viruses. The high seroprevalence found in rural Ghana to rodent-borne pathogens associated with both sporadic cases and larger disease outbreaks will help define disease threats and inform public health policy to reduce disease burden in underserved populations and deter larger outbreaks.