Emergence of Zaire Ebola virus disease in Guinea

Sudan virus disease super-spreading, Uganda, 2022

BACKGROUND

On 20 September 2022, Uganda declared its fifth Sudan virus disease (SVD) outbreak, culminating in 142 confirmed and 22 probable cases. The reproductive rate (R) of this outbreak was 1.25. We described persons who were exposed to the virus, became infected, and they led to the infection of an unusually high number of cases during the outbreak.

METHODS

In this descriptive cross-sectional study, we defined a super-spreader person (SSP) as any person with real-time polymerase chain reaction (RT-PCR) confirmed SVD linked to the infection of ≥ 13 other persons (10-fold the outbreak R). We reviewed illness narratives for SSPs collected through interviews. Whole-genome sequencing was used to support epidemiologic linkages between cases.

RESULTS

Two SSPs (Patient A, a 33-year-old male, and Patient B, a 26-year-old male) were identified, and linked to the infection of one probable and 50 confirmed secondary cases. Both SSPs lived in the same parish and were likely infected by a single ill healthcare worker in early October while receiving healthcare. Both sought treatment at multiple health facilities, but neither was ever isolated at an Ebola Treatment Unit (ETU). In total, 18 secondary cases (17 confirmed, one probable), including three deaths (17%), were linked to Patient A; 33 secondary cases (all confirmed), including 14 (42%) deaths, were linked to Patient B. Secondary cases linked to Patient A included family members, neighbours, and contacts at health facilities, including healthcare workers. Those linked to Patient B included healthcare workers, friends, and family members who interacted with him throughout his illness, prayed over him while he was nearing death, or exhumed his body. Intensive community engagement and awareness-building were initiated based on narratives collected about patients A and B; 49 (96%) of the secondary cases were isolated in an ETU, a median of three days after onset. Only nine tertiary cases were linked to the 51 secondary cases. Sequencing suggested plausible direct transmission from the SSPs to 37 of 39 secondary cases with sequence data.

CONCLUSION

Extended time in the community while ill, social interactions, cross-district travel for treatment, and religious practices contributed to SVD super-spreading. Intensive community engagement and awareness may have reduced the number of tertiary infections. Intensive follow-up of contacts of case-patients may help reduce the impact of super-spreading events.

Bridging biological samples to functional nucleic acid biosensor applications: current enzymatic-based strategies for single-stranded DNA generation

The escalating threat of emerging diseases, often stemming from contaminants and lethal pathogens, has precipitated a heightened demand for sophisticated diagnostic tools. Within this landscape, the functional nucleic acid (FNA) biosensor, harnessing the power of single-stranded DNA (ssDNA), has emerged as a preeminent choice for target analyte detection. However, the dependence on ssDNA has raised difficulties in realizing it in biological samples. Therefore, the production of high-quality ssDNA from biological samples is critical. This review aims to discuss strategies for generating ssDNA from biological samples for integration into biosensors. Several innovative strategies for ssDNA generation have been deployed, encompassing techniques, such as asymmetric PCR, Exonuclease-PCR, isothermal amplification, biotin-streptavidin PCR, transcription-reverse transcription, ssDNA overhang generation, and urea denaturation PAGE. These approaches have been seamlessly integrated with biosensors for biological sample analysis, ushering in a new era of disease detection and monitoring. This amalgamation of ssDNA generation techniques with biosensing applications holds significant promise, not only in improving the speed and accuracy of diagnostic processes but also in fortifying the global response to deadly diseases, thereby underlining the pivotal role of cutting-edge biotechnology in public health and disease prevention.

Child and adolescent foraging: New directions in evolutionary research

Young children and adolescents in subsistence societies forage for a wide range of resources. They often target child-specific foods, they can be very successful foragers, and they share their produce widely within and outside of their nuclear family. At the same time, while foraging, they face risky situations and are exposed to diseases that can influence their immune development. However, children's foraging has largely been explained in light of their future (adult) behavior. Here, we reinterpret findings from human behavioral ecology, evolutionary medicine and cultural evolution to center foraging children's contributions to life history evolution, community resilience and immune development. We highlight the need to foreground immediate alongside delayed benefits and costs of foraging, including inclusive fitness benefits, when discussing children's food production from an evolutionary perspective. We conclude by recommending that researchers carefully consider children's social and ecological context, develop cross-cultural perspectives, and incorporate children's foraging into Indigenous sovereignty discourse.

Geographic Disparities in Domestic Pig Population Exposure to Ebola Viruses, Guinea, 2017-2019

Although pigs are naturally susceptible to Reston virus and experimentally to Ebola virus (EBOV), their role in Orthoebolavirus ecology remains unknown. We tested 888 serum samples collected from pigs in Guinea during 2017-2019 (between the 2013-16 epidemic and its resurgence in 2021) by indirect ELISA against the EBOV nucleoprotein. We identified 2 hotspots of possible pig exposure by IgG titer levels: the northern coast had 48.7% of positive serum samples (37/76), and Forest Guinea, bordering Sierra Leone and Liberia, where the virus emerged and reemerged, had 50% of positive serum samples (98/196). The multitarget Luminex approach confirms ELISA results against Ebola nucleoprotein and highlights cross-reactivities to glycoprotein of EBOV, Reston virus, and Bundibugyo virus. Those results are consistent with previous observations of the circulation of Orthoebolavirus species in pig farming regions in Sierra Leone and Ghana, suggesting potential risk for Ebola virus disease in humans, especially in Forest Guinea.

Development of a non-infectious control for viral hemorrhagic fever PCR assays

Assay validation is an essential component of disease surveillance testing, but can be problematic in settings where access to positive control material is limited and a safety risk for handlers. Here we describe a single non-infectious synthetic control that can help develop and validate the PCR based detection of the viral causes of Crimean-Congo hemorrhagic fever, Ebola virus disease, Lassa fever, Marburg virus disease and Rift Valley fever. We designed non-infectious synthetic DNA oligonucleotide sequences incorporating primer binding sites suitable for five assays, and a T7 promotor site which was used to transcribe the sequence. Transcribed RNA was used as template in a dilution series, extracted and amplified with RT-PCR and RT-qPCR to demonstrate successful recovery and determine limits of detection in a range of laboratory settings. Our results show this approach is adaptable to any diagnostic assay requiring validation of nucleic acid extraction and/or amplification, particularly where sourcing reliable, safe material for positive controls is infeasible.

Kernel Bayesian nonlinear matrix factorization based on variational inference for human-virus protein-protein interaction prediction

Identification of potential human-virus protein-protein interactions (PPIs) contributes to the understanding of the mechanisms of viral infection and to the development of antiviral drugs. Existing computational models often have more hyperparameters that need to be adjusted manually, which limits their computational efficiency and generalization ability. Based on this, this study proposes a kernel Bayesian logistic matrix decomposition model with automatic rank determination, VKBNMF, for the prediction of human-virus PPIs. VKBNMF introduces auxiliary information into the logistic matrix decomposition and sets the prior probabilities of the latent variables to build a Bayesian framework for automatic parameter search. In addition, we construct the variational inference framework of VKBNMF to ensure the solution efficiency. The experimental results show that for the scenarios of paired PPIs, VKBNMF achieves an average AUPR of 0.9101, 0.9316, 0.8727, and 0.9517 on the four benchmark datasets, respectively, and for the scenarios of new human (viral) proteins, VKBNMF still achieves a higher hit rate. The case study also further demonstrated that VKBNMF can be used as an effective tool for the prediction of human-virus PPIs.

A global-scale dataset of bat viral detection suggests that pregnancy reduces viral shedding

Understanding viral infection dynamics in wildlife hosts can help forecast zoonotic pathogen spillover and human disease risk. Bats are particularly important reservoirs of zoonotic viruses, including some of major public health concern such as Nipah virus, Hendra virus, and SARS-related coronaviruses. Previous work has suggested that metapopulation dynamics, seasonal reproductive patterns, and other bat life history characteristics might explain temporal variation in spillover of bat-associated viruses into people. Here, we analyze viral dynamics in free-ranging bat hosts, leveraging a multi-year, global-scale viral detection dataset that spans eight viral families and 96 bat species from 14 countries. We fit hierarchical Bayesian models that explicitly control for important sources of variation, including geographic region, specimen type, and testing protocols, while estimating the influence of reproductive status on viral detection in female bats. Our models revealed that late pregnancy had a negative effect on viral shedding across multiple data subsets, while lactation had a weaker influence that was inconsistent across data subsets. These results are unusual for mammalian hosts, but given recent findings that bats may have high individual viral loads and population-level prevalence due to dampening of antiviral immunity, we propose that it would be evolutionarily advantageous for pregnancy to either not further reduce immunity or actually increase the immune response, reducing viral load, shedding, and risk of fetal infection. This novel hypothesis would be valuable to test given its potential to help monitor, predict, and manage viral spillover risk from bats.

The economic burden of Ebola virus disease: a review and recommendations for analysis

BACKGROUND

Ebola virus disease (EVD) continues to be a major public health threat globally, particularly in the low-and-middle-income countries (LMICs) of Africa. The social and economic burdens of EVD are substantial and have triggered extensive research into prevention and control. We aim to highlight the impact and economic implications, identify research gaps, and offer recommendations for future economic studies pertaining to EVD.

METHOD

We conducted a comprehensive librarian-led search in PubMed/Medline, Embase, Google Scholar, EconLit and Scopus for economic evaluations of EVD. After study selection and data extraction, findings on the impact and economics of EVD were synthesized using a narrative approach, while identifying gaps, and recommending critical areas for future EVD economic studies.

RESULTS

The economic evaluations focused on the burden of illness, vaccine cost-effectiveness, willingness-to-pay for a vaccine, EVD funding, and preparedness costs. The estimated economic impact of the 2014 EVD outbreak in Guinea, Liberia, and Sierra Leone across studies ranged from $30 billion to $50 billion. Facility construction and modification emerged as significant cost drivers for preparedness. The EVD vaccine demonstrated cost-effectiveness in a dynamic transmission model; resulting in an incremental cost-effectiveness ratio of about $96 per additional disability adjusted life year averted. Individuals exhibited greater willingness to be vaccinated if it incurred no personal cost, with a minority willing to pay about $1 for the vaccine.

CONCLUSIONS

The severe impact of EVD puts pressure on governments and the international community for better resource utilization and re-allocation. Several technical and methodological issues related to economic evaluation of EVD remain to be addressed, especially for LMICs. We recommend conducting cost-of-sequelae and cost-of-distribution analyses in addition to adapting existing economic analytical methods to EVD. Characteristics of the affected regions should be considered to provide evidence-based economic plans and economic-evaluation of mitigations that enhance resource allocation for prevention and treatment.

A novel viral vaccine platform based on engineered transfer RNA

In recent years, an increasing number of emerging and remerging virus outbreaks have occurred and the rapid development of vaccines against these viruses has been crucial. Controlling the replication of premature termination codon (PTC)-containing viruses is a promising approach to generate live but replication-defective viruses that can be used for potent vaccines. Here, we used anticodon-engineered transfer RNAs (ACE-tRNAs) as powerful precision switches to control the replication of PTC-containing viruses. We showed that ACE-tRNAs display higher potency of reading through PTCs than genetic code expansion (GCE) technology. Interestingly, ACE-tRNA has a site preference that may influence its read-through efficacy. We further attempted to use ACE-tRNAs as a novel viral vaccine platform. Using a human immunodeficiency virus type 1 (HIV-1) pseudotyped virus as an RNA virus model, we found that ACE-tRNAs display high potency for read-through viral PTCs and precisely control their production. Pseudorabies virus (PRV), a herpesvirus, was used as a DNA virus model. We found that ACE-tRNAs display high potency for reading through viral PTCs and precisely controlling PTC-containing virus replication. In addition, PTC-engineered PRV completely attenuated and lost virulence in mice in vivo, and immunization with PRV containing a PTC elicited a robust immune response and provided complete protection against wild-type PRV challenge. Overall, replication-controllable PTC-containing viruses based on ACE-tRNAs provide a new strategy to rapidly attenuate virus infection and prime robust immune responses. This technology can be used as a platform for rapidly developing viral vaccines in the future.

Sequence optimized diagnostic assay for Ebola virus detection

Rapid pathogen identification is a critical first step in patient isolation, treatment, and controlling an outbreak. Real-time PCR is a highly sensitive and specific approach commonly used for infectious disease diagnostics. However, mismatches in the primer or probe sequence and the target organism can cause decreased sensitivity, assay failure, and false negative results. Limited genomic sequences for rare pathogens such as Ebola virus (EBOV) can negatively impact assay performance due to undiscovered genetic diversity. We previously developed and validated several EBOV assays prior to the 2013-2016 EBOV outbreak in West Africa, and sequencing EBOV Makona identified sequence variants that could impact assay performance. Here, we assessed the impact sequence mismatches have on EBOV assay performance, finding one or two primer or probe mismatches resulted in a range of impact from minimal to almost two log sensitivity reduction. Redesigning this assay improved detection of all EBOV variants tested. Comparing the performance of the new assay with the previous assays across a panel of human EBOV samples confirmed increased assay sensitivity as reflected in decreased Cq values with detection of three positive that tested negative with the original assay.

Micro- and nanosystems for the detection of hemorrhagic fever viruses

Hemorrhagic fever viruses (HFVs) are virulent pathogens that can cause severe and often fatal illnesses in humans. Timely and accurate detection of HFVs is critical for effective disease management and prevention. In recent years, micro- and nano-technologies have emerged as promising approaches for the detection of HFVs. This paper provides an overview of the current state-of-the-art systems for micro- and nano-scale approaches to detect HFVs. It covers various aspects of these technologies, including the principles behind their sensing assays, as well as the different types of diagnostic strategies that have been developed. This paper also explores future possibilities of employing micro- and nano-systems for the development of HFV diagnostic tools that meet the practical demands of clinical settings.

Towards a post-pandemic future for global pathogen genome sequencing

Pathogen genome sequencing has become a routine part of our response to active outbreaks of infectious disease and should be an important part of our preparations for future epidemics. In this Essay, we discuss the innovations that have enabled routine pathogen genome sequencing, as well as how genome sequences can be used to understand and control the spread of infectious disease. We also explore the impact of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic on the field of pathogen genomics and outline the challenges we must address to further improve the utility of pathogen genome sequencing in the future.

Investigating and combatting the key drivers of viral zoonoses in Africa: an analysis of eight epidemics

Investigating the interplay of factors that result in a viral zoonotic outbreak is difficult, though it is increasingly important. As anthropogenic influences shift the delicate balance of ecosystems, new zoonoses emerge in humans. Sub-Saharan Africa is a notable hotspot for zoonotic disease due to abundant competent mammalian reservoir hosts. Furthermore, poverty, corruption, and an overreliance on natural resources play considerable roles in depleting biological resources, exacerbating the population's susceptibility. Unsurprisingly, viral zoonoses have emerged in Africa, including HIV/AIDS, Ebola, Avian influenza, Lassa fever, Zika, and Monkeypox. These diseases are among the principal causes of death in endemic areas. Though typically distinct in their manifestations, viral zoonoses are connected by underlying, definitive factors. This review summarises vital findings on viral zoonoses in Africa using nine notable case studies as a benchmark for future studies. We discuss the importance of ecological recuperation and protection as a central strategy to control zoonotic diseases. Emphasis was made on moderating key drivers of zoonotic diseases to forestall future pandemics. This is in conjunction with attempts to redirect efforts from reactive to pre-emptive through a multidisciplinary "one health" approach.

Host–Pathogen Interactions Influencing Zoonotic Spillover Potential and Transmission in Humans

Emerging infectious diseases of zoonotic origin are an ever-increasing public health risk and economic burden. The factors that determine if and when an animal virus is able to spill over into the human population with sufficient success to achieve ongoing transmission in humans are complex and dynamic. We are currently unable to fully predict which pathogens may appear in humans, where and with what impact. In this review, we highlight current knowledge of the key host–pathogen interactions known to influence zoonotic spillover potential and transmission in humans, with a particular focus on two important human viruses of zoonotic origin, the Nipah virus and the Ebola virus. Namely, key factors determining spillover potential include cellular and tissue tropism, as well as the virulence and pathogenic characteristics of the pathogen and the capacity of the pathogen to adapt and evolve within a novel host environment. We also detail our emerging understanding of the importance of steric hindrance of host cell factors by viral proteins using a “flytrap”-type mechanism of protein amyloidogenesis that could be crucial in developing future antiviral therapies against emerging pathogens. Finally, we discuss strategies to prepare for and to reduce the frequency of zoonotic spillover occurrences in order to minimize the risk of new outbreaks.

Epidemiology of Ebolaviruses from an Etiological Perspective

Since the inception of the ebolavirus in 1976, 32 outbreaks have resulted in nearly 15,350 deaths in more than ten countries of the African continent. In the last decade, the largest (2013-2016) and second largest (2018-2020) ebolavirus outbreaks have occurred in West Africa (mainly Guinea, Liberia, and Sierra Leone) and the Democratic Republic of the Congo, respectively. The 2013-2016 outbreak indicated an alarming geographical spread of the virus and was the first to qualify as an epidemic. Hence, it is imperative to halt ebolavirus progression and develop effective countermeasures. Despite several research efforts, ebolaviruses' natural hosts and secondary reservoirs still elude the scientific world. The primary source responsible for infecting the index case is also unknown for most outbreaks. In this review, we summarize the history of ebolavirus outbreaks with a focus on etiology, natural hosts, zoonotic reservoirs, and transmission mechanisms. We also discuss the reasons why the African continent is the most affected region and identify steps to contain this virus.

Approaches to demonstrating the effectiveness of filovirus vaccines: Lessons from Ebola and COVID-19

Zaire ebolavirus (EBOV), Sudan ebolavirus (SUDV) and Marburg virus (MARV), are members of the Filoviridae family that can cause severe disease and death in humans and animals. The reemergence of Ebola, Sudan and Marburg virus disease highlight the need for continued availability of safe and effectives vaccines as well as development of new vaccines. While randomized controlled trials using disease endpoints provide the most robust assessment of vaccine effectiveness, challenges to this approach include the unpredictable size, location, occurrence and duration of filovirus disease outbreaks. Thus, other approaches to demonstrating vaccine effectiveness have been considered. These approaches are discussed using examples of preventive vaccines against other infectious diseases. In addition, this article proposes a clinical immunobridging strategy using licensed EBOV vaccines as comparators for demonstrating the effectiveness of filovirus vaccine candidates that are based on the same licensed vaccine platform technology.

A Review: The Antiviral Activity of Cyclic Peptides

In the design and development of therapeutic agents, macromolecules with restricted structures have stronger competitive edges than linear biological entities since cyclization can overcome the limitations of linear structures. The common issues of linear peptides include susceptibility to degradation of the peptidase enzyme, off-target effects, and necessity of routine dosing, leading to instability and ineffectiveness. The unique conformational constraint of cyclic peptides provides a larger surface area to interact with the target at the same time, improving the membrane permeability and in vivo stability compared to their linear counterparts. Currently, cyclic peptides have been reported to possess various activities, such as antifungal, antiviral and antimicrobial activities. To date, there is emerging interest in cyclic peptide therapeutics, and increasing numbers of clinically approved cyclic peptide drugs are available on the market. In this review, the medical significance of cyclic peptides in the defence against viral infections will be highlighted. Except for chikungunya virus, which lacks specific antiviral treatment, all the viral diseases targeted in this review are those with effective treatments yet with certain limitations to date. Thus, strategies and approaches to optimise the antiviral effect of cyclic peptides will be discussed along with their respective outcomes. Apart from isolated naturally occurring cyclic peptides, chemically synthesized or modified cyclic peptides with antiviral activities targeting coronavirus, herpes simplex viruses, human immunodeficiency virus, Ebola virus, influenza virus, dengue virus, five main hepatitis viruses, termed as type A, B, C, D and E and chikungunya virus will be reviewed herein.

Graphical Abstract

Beyond the Unknown: A Broad Framing for Preparedness for Emerging Infectious Threats

There have been multiple instances of novel pathogen emergence that have affected the health and security of the global community. To highlight that these novel pathogens presented a clear danger to public health, the WHO included "Disease X" on their list of priority pathogens in 2018. Indeed, since the emergence of SARS-CoV-2, Disease X has been pointed to as the looming threat of "the next big thing." However, developing surveillance and preparedness plans with Disease X as the linchpin is too narrow and ignores a large swath of potential threats from already identified, often neglected diseases. We propose instead the idea of "Disease f(x)" as a preferred call to arms with which to prioritize research and programmatic development. The common mathematical notation f(x) represents the knowledge that outbreaks are a function of many variables that define the transmission trajectory of that pathogen. Disease f(x) exploits commonalities across pathogen groupings while recognizing that emergences and outbreaks are fluid and that responses need to be agile and progressively tailored to specific pathogens with cultural and regional context. Adoption of this mindset across sectors, including biotechnology, disaster management, and epidemiology, will allow us to develop more efficient and effective responses to address the next major infectious threat.

Highly Multiplexed Serology for Nonhuman Mammals

Emerging infectious diseases represent a serious and ongoing threat to humans. Most emerging viruses are maintained in stable relationships with other species of animals, and their emergence within the human population results from cross-species transmission. Therefore, if we want to be prepared for the next emerging virus, we need to broadly characterize the diversity and ecology of viruses currently infecting other animals (i.e., the animal virosphere). High-throughput metagenomic sequencing has accelerated the pace of virus discovery. However, molecular assays can detect only active infections and only if virus is present within the sampled fluid or tissue at the time of collection. In contrast, serological assays measure long-lived antibody responses to infections, which can be detected within the blood, regardless of the infected tissues. Therefore, serological assays can provide a complementary approach for understanding the circulation of viruses, and while serological assays have historically been limited in scope, recent advancements allow thousands to hundreds of thousands of antigens to be assessed simultaneously using <1 μL of blood (i.e., highly multiplexed serology). The application of highly multiplexed serology for the characterization of the animal virosphere is dependent on the availability of reagents that can be used to capture or label antibodies of interest. Here, we evaluate the utility of commercial immunoglobulin-binding proteins (protein A and protein G) to enable highly multiplexed serology in 25 species of nonhuman mammals, and we describe a competitive fluorescence-linked immunosorbent assay (FLISA) that can be used as an initial screen for choosing the most appropriate capture protein for a given host species. IMPORTANCE Antibodies are generated in response to infections with viruses and other pathogens, and they help protect against future exposures. Mature antibodies are long lived, are highly specific, and can bind to their protein targets with high affinity. Thus, antibodies can also provide information about an individual's history of viral exposures, which has important applications for understanding the epidemiology and etiology of disease. In recent years, there have been large advances in the available methods for broadly characterizing antibody-binding profiles, but thus far, these have been utilized primarily with human samples only. Here, we demonstrate that commercial antibody-binding reagents can facilitate modern antibody assays for a wide variety of mammalian species, and we describe an inexpensive and fast approach for choosing the best reagent for each animal species. By studying antibody-binding profiles in captive and wild animals, we can better understand the distribution and prevalence of viruses that could spill over into humans.

The potential of genomics for infectious disease forecasting

Genomic technologies have led to tremendous gains in understanding how pathogens function, evolve and interact. Pathogen diversity is now measurable at high precision and resolution, in part because over the past decade, sequencing technologies have increased in speed and capacity, at decreased cost. Alongside this, the use of models that can forecast emergence and size of infectious disease outbreaks has risen, highlighted by the coronavirus disease 2019 pandemic but also due to modelling advances that allow for rapid estimates in emerging outbreaks to inform monitoring, coordination and resource deployment. However, genomics studies have remained largely retrospective. While they contain high-resolution views of pathogen diversification and evolution in the context of selection, they are often not aligned with designing interventions. This is a missed opportunity because pathogen diversification is at the core of the most pressing infectious public health challenges, and interventions need to take the mechanisms of virulence and understanding of pathogen diversification into account. In this Perspective, we assess these converging fields, discuss current challenges facing both surveillance specialists and modellers who want to harness genomic data, and propose next steps for integrating longitudinally sampled genomic data with statistical learning and interpretable modelling to make reliable predictions into the future.

Development of a Well-Characterized Cynomolgus Macaque Model of Sudan Virus Disease for Support of Product Development

The primary objective of this study was to characterize the disease course in cynomolgus macaques exposed to Sudan virus (SUDV), to determine if infection in this species is an appropriate model for the evaluation of filovirus countermeasures under the FDA Animal Rule. Sudan virus causes Sudan virus disease (SVD), with an average case fatality rate of approximately 50%, and while research is ongoing, presently there are no approved SUDV vaccines or therapies. Well characterized animal models are crucial for further developing and evaluating countermeasures for SUDV. Twenty (20) cynomolgus macaques were exposed intramuscularly to either SUDV or sterile phosphate-buffered saline; 10 SUDV-exposed animals were euthanized on schedule to characterize pathology at defined durations post-exposure and 8 SUDV-exposed animals were not part of the scheduled euthanasia cohort. Survival was assessed, along with clinical observations, body weights, body temperatures, hematology, clinical chemistry, coagulation, viral load (serum and tissues), macroscopic observations, and histopathology. There were statistically significant differences between SUDV-exposed animals and mock-exposed animals for 26 parameters, including telemetry body temperature, clinical chemistry parameters, hematology parameters, activated partial thromboplastin time, serum viremia, and biomarkers that characterize the disease course of SUDV in cynomolgus macaques.

Primate hemorrhagic fever-causing arteriviruses are poised for spillover to humans

Simian arteriviruses are endemic in some African primates and can cause fatal hemorrhagic fevers when they cross into primate hosts of new species. We find that CD163 acts as an intracellular receptor for simian hemorrhagic fever virus (SHFV; a simian arterivirus), a rare mode of virus entry that is shared with other hemorrhagic fever-causing viruses (e.g., Ebola and Lassa viruses). Further, SHFV enters and replicates in human monocytes, indicating full functionality of all of the human cellular proteins required for viral replication. Thus, simian arteriviruses in nature may not require major adaptations to the human host. Given that at least three distinct simian arteriviruses have caused fatal infections in captive macaques after host-switching, and that humans are immunologically naive to this family of viruses, development of serology tests for human surveillance should be a priority.

The Efficient Antiviral Response of A549 Cells Is Enhanced When Mitochondrial Respiration Is Promoted

When exposed to a viral infection, the attacked cells promptly set up defense mechanisms. As part of the antiviral responses, the innate immune interferon pathway and associated interferon-stimulated genes notably allow the production of proteins bearing antiviral activity. Numerous viruses are able to evade the interferon response, highlighting the importance of controlling this pathway to ensure their efficient replication. Several viruses are also known to manipulate the metabolism of infected cells to optimize the availability of amino acids, nucleotides, and lipids. They then benefit from a reprogramming of the metabolism that favors glycolysis instead of mitochondrial respiration. Given the increasingly discussed crosstalk between metabolism and innate immunity, we wondered whether this switch from glycolysis to mitochondrial respiration would be beneficial or deleterious for an efficient antiviral response. We used a cell-based model of metabolic reprogramming. Interestingly, we showed that increased mitochondrial respiration was associated with an enhanced interferon response following polyriboinosinic:polyribocytidylic acid (poly:IC) stimulation. This suggests that during viral infection, the metabolic reprogramming towards glycolysis is also part of the virus’ strategies to inhibit the antiviral response.

Using a grey relational analysis in an improved Grunow-Finke assessment tool to detect unnatural epidemics

The Grunow-Finke epidemiological assessment tool (GFT) has several limitations in its ability to differentiate between natural and man-made epidemics. Our study aimed to improve the GFT and analyze historical epidemics to validate the model. Using a gray relational analysis (GRA), we improved the GFT by revising the existing standards and adding five new standards. We then removed the artificial weights and final decision threshold. Finally, by using typically unnatural epidemic events as references, we used the GRA to calculate the unnatural probability and obtain assessment results. Using the advanced tool, we conducted retrospective and case analyses to test its performance. In the validation set of 13 historical epidemics, unnatural and natural epidemics were divided into two categories near the unnatural probability of 45%, showing evident differences (p < 0.01) and an assessment accuracy close to 100%. The unnatural probabilities of the Ebola virus disease of 2013 and Middle East Respiratory Syndrome of 2012 were 30.6% and 36.1%, respectively. Our advanced epidemic assessment tool improved the accuracy of the original GFT from approximately 55% to approximately 100% and reduced the impact of human factors on these outcomes effectively.

Coevolving spreading dynamics of negative information and epidemic on multiplex networks

The widespread dissemination of negative information on vaccine may arise people's concern on the safety of vaccine and increase their hesitancy in vaccination, which can seriously impede the progress of epidemic control. Existing works on information-epidemic coupled dynamics focus on the suppression effects of information on epidemic. Here we propose a negative information and epidemic coupled propagation model on two-layer multiplex networks to study the effects of negative information of vaccination on epidemic spreading, where the negative information propagates on the virtual communication layer and the disease spreads on the physical contact layer. In our model, an individual getting an adverse event after vaccination will spread negative information and an individual affected by the negative information will reduce his/her willingness to get vaccinated and spread the negative information. By using the microscopic Markov chain method, we analytically predict the epidemic threshold and final infection density, which agree well with simulation results. We find that the spread of negative information leads to a lower epidemic outbreak threshold and a higher final infection density. However, the individuals' vaccination activities, but not the negative information spreading, has a leading impact on epidemic spreading. Only when the individuals obviously reduce their vaccination willingness due to negative information, the negative information can impact the epidemic spreading significantly.

Protection against Marburg Virus and Sudan Virus in NHP by an Adenovector-Based Trivalent Vaccine Regimen Is Correlated to Humoral Immune Response Levels

The Marburg virus (MARV) and Sudan virus (SUDV) belong to the filovirus family. The sporadic human outbreaks occur mostly in Africa and are characterized by an aggressive disease course with high mortality. The first case of Marburg virus disease in Guinea in 2021, together with the increased frequency of outbreaks of Ebola virus (EBOV), which is also a filovirus, accelerated the interest in potential prophylactic vaccine solutions against multiple filoviruses. We previously tested a two-dose heterologous vaccine regimen (Ad26.Filo, MVA-BN-Filo) in non-human primates (NHP) and showed a fully protective immune response against both SUDV and MARV in addition to the already-reported protective effect against EBOV. The vaccine-induced glycoprotein (GP)-binding antibody levels appear to be good predictors of the NHP challenge outcome as indicated by the correlation between antibody levels and survival outcome as well as the high discriminatory capacity of the logistic model. Moreover, the elicited GP-specific binding antibody response against EBOV, SUDV, and MARV remains stable for more than 1 year. Overall, the NHP data indicate that the Ad26.Filo, MVA-BN-Filo regimen may be a good candidate for a prophylactic vaccination strategy in regions at high risk of filovirus outbreaks.

Recent Progress in the Discovery and Development of Monoclonal Antibodies against Viral Infections

Monoclonal antibodies (mAbs), the new revolutionary class of medications, are fast becoming tools against various diseases thanks to a unique structure and function that allow them to bind highly specific targets or receptors. These specialized proteins can be produced in large quantities via the hybridoma technique introduced in 1975 or by means of modern technologies. Additional methods have been developed to generate mAbs with new biological properties such as humanized, chimeric, or murine. The inclusion of mAbs in therapeutic regimens is a major medical advance and will hopefully lead to significant improvements in infectious disease management. Since the first therapeutic mAb, muromonab-CD3, was approved by the U.S. Food and Drug Administration (FDA) in 1986, the list of approved mAbs and their clinical indications and applications have been proliferating. New technologies have been developed to modify the structure of mAbs, thereby increasing efficacy and improving delivery routes. Gene delivery technologies, such as non-viral synthetic plasmid DNA and messenger RNA vectors (DMabs or mRNA-encoded mAbs), built to express tailored mAb genes, might help overcome some of the challenges of mAb therapy, including production restrictions, cold-chain storage, transportation requirements, and expensive manufacturing and distribution processes. This paper reviews some of the recent developments in mAb discovery against viral infections and illustrates how mAbs can help to combat viral diseases and outbreaks.

Characterization of replication and variations in genome segments of a bat reovirus, BatMRV/B19-02, by RNA-seq in infected Vero-E6 cells

Mammalian orthoreoviruses (MEVs) that can cause enteric, respiratory, and encephalitic infections have been identified in a wide variety of mammalian species. Here, we report a novel MRV type 1 strain detected in Miniopterus schreibersii that may have resulted from reassortment events. Using next-generation RNA sequencing (RNA-seq), we found that the ratios of the RNA levels of the 10 reovirus segments in infected cells were constant during the late stages of infection. We also discovered that the relative abundance of each segment differed. Notably, the relative abundance of M2 (encoding the µ1 protein) and S4 (encoding the σ3 protein) RNAs was higher than that of the others throughout the infection. Additionally, massive junctions were identified. These results support the hypothesis that defective genome segments are generated and that cross-family recombination occurs. These data may further the study of gene function, viral replication, and virus evolution.

Rapid diagnostic tests versus RT-PCR for Ebola virus infections: a systematic review and meta-analysis

Objective

To evaluate the clinical accuracy of rapid diagnostic tests for the detection of Ebola virus.

Methods

We searched MEDLINE®, Embase® and Web of Science for articles published between 1976 and October 2021 reporting on clinical studies assessing the performance of Ebola virus rapid diagnostic tests compared with reverse transcription polymerase chain reaction (RT-PCR). We assessed study quality using the QUADAS-2 criteria. To estimate the pooled sensitivity and specificity of these rapid diagnostic tests, we used a bivariate random-effects meta-analysis.

Findings

Our search identified 113 unique studies, of which nine met the inclusion criteria. The studies were conducted in the Democratic Republic of the Congo, Guinea, Liberia and Sierra Leone and they evaluated 12 rapid diagnostic tests. We included eight studies in the meta-analysis. The pooled sensitivity and specificity of the rapid tests were 86% (95% confidence interval, CI: 80-91) and 95% (95% CI: 91-97), respectively. However, pooled sensitivity decreased to 83% (95% CI: 77-88) after removing outliers. Pooled sensitivity increased to 90% (95% CI: 82-94) when analysis was restricted to studies using the RT-PCR from altona Diagnostics as gold standard. Pooled sensitivity increased to 99% (95% CI: 67-100) when the analysis was restricted to studies using whole or capillary blood specimens.

Conclusion

The included rapid diagnostic tests did not detect all the Ebola virus disease cases. While the sensitivity and specificity of these tests are moderate, they are still valuable tools, especially useful for triage and detecting Ebola virus in remote areas.

Rapid detection of viruses: Based on silver nanoparticles modified with bromine ions and acetonitrile

Nearly 200 million people have been diagnosed with COVID-19 since the outbreak in 2019, and this disease has claimed more than 5 million lives worldwide. Currently, researchers are focusing on vaccine development and the search for an effective strategy to control the infection source. This work designed a detection platform based on Surface-Enhanced Raman Spectroscopy (SERS) by introducing acetonitrile and calcium ions into the silver nanoparticle reinforced substrate system to realize the rapid detection of novel coronavirus. Acetonitrile may amplify the calcium-induced hot spots of silver nanoparticles and significantly enhanced the stability of silver nanoparticles. It also elicited highly sensitive SERS signals of the virus. This approach allowed us to capture the characteristic SERS signals of SARS-CoV-2, Human Adenovirus 3, and H1N1 influenza virus molecules at a concentration of 100 copies/test (PFU/test) with upstanding reproduction and signal-to-noise ratio. Machine learning recognition technology was employed to qualitatively distinguish the three virus molecules with 1000 groups of spectra of each virus. Acetonitrile is a potent internal marker in regulating the signal intensity of virus molecules in saliva and serum. Thus, we used the SERS peak intensity to quantify the virus content in saliva and serum. The results demonstrated a satisfactory linear relationship between peak intensity and protein concentration. Collectively, this rapid detection method has a broad application prospect in clinical diagnosis of viruses, management of emergent viral infectious diseases, and exploration of the interaction between viruses and host cells.

Strengthening laboratory networks in the Central Africa region: A milestone for epidemic preparedness and response

Background

Health systems in the Central Africa region are among the weakest and least funded in the world. The lack of laboratory networks and adequately trained personnel with clearly defined responsibilities has hampered the implementation of laboratory quality improvement programmes. Global Health Systems Solutions (GHSS) obtained a grant from the Africa Centres for Disease Control and Prevention to develop laboratory networks for disease surveillance and strengthen the quality of laboratory testing in the Central Africa region.

Intervention

One year after the grant was awarded on 01 October 2018, GHSS has launched a Regional Integrated Surveillance and Laboratory Network (RISLNET) for Central Africa and developed National Laboratory Strategic Plans and Policies for member states, eight frameworks and guideline documents, as well as a website for RISLNET Central Africa. GHSS has also launched an Extension for Community Health Outcomes platform to supervise laboratories enrolled for accreditation, installed a Basic Laboratory Information System (BLIS) in four laboratories in four member states, and trained 247 laboratory personnel and laboratory experts on BLIS, quality assurance, external quality assurance, Strengthening Laboratory Management Towards Accreditation (SLMTA), quality management systems, and equipment maintenance and calibration.

Lessons learnt

Participating laboratories now serve as reference laboratories for COVID-19 testing in various countries. Point-of-care testing, using the GeneXpert platform, has been the central strategy for the scale-up of COVID-19 testing in the Central Africa region.

Recommendations

Expanding SLMTA to other laboratories within Central Africa will significantly improve the quality management of laboratories for a better healthcare system.

Evaluation of the first two Frontline cohorts of the field epidemiology training program in Guinea, West Africa

BACKGROUND

The 2014-2016 Ebola virus disease outbreak in West Africa revealed weaknesses in the health systems of the three most heavily affected countries, including a shortage of public health professionals at the local level trained in surveillance and outbreak investigation. In response, the Frontline Field Epidemiology Training Program (FETP) was created by CDC in 2015 as a 3-month, accelerated training program in field epidemiology that specifically targets the district level. In Guinea, the first two FETP-Frontline cohorts were held from January to May, and from June to September 2017. Here, we report the results of a cross-sectional evaluation of these first two cohorts of FETP-Frontline in Guinea.

METHODS

The evaluation was conducted in April 2018 and consisted of interviews with graduates, their supervisors, and directors of nearby health facilities, as well as direct observation of data reports and surveillance tools at health facilities. Interviews and site visits were conducted using standardized questionnaires and checklists. Qualitative data were coded under common themes and analyzed using descriptive statistics.

RESULTS

The evaluation revealed a significant perception of improvement in all assessed skills by the graduates, as well as high levels of self-reported involvement in key activities related to data collection, analysis, and reporting. Supervisors highlighted improvements to systematic and quality case and summary reporting as key benefits of the FETP-Frontline program. At the health facility level, staff reported the training had resulted in improvements to information sharing and case notifications. Reported barriers included lack of transportation, available support personnel, and other resources. Graduates and supervisors both emphasized the importance of continued and additional training to solidify and retain skills.

CONCLUSIONS

The evaluation demonstrated a strongly positive perceived benefit of the FETP-Frontline training on the professional activities of graduates as well as the overall surveillance system. However, efforts are needed to ensure greater gender equity and to recruit more junior trainee candidates for future cohorts. Moreover, although improvements to the surveillance system were observed concurrent with the completion of the two cohorts, the evaluation was not designed to directly measure impact on surveillance or response functions. Combined with the rapid implementation of FETP-Frontline around the world, this suggests an opportunity to develop standardized evaluation toolkits, which could incorporate metrics that would directly assess the impact of equitable field epidemiology workforce development on countries' abilities to prevent, detect, and respond to public health threats.

Seq-BEL: Sequence-Based Ensemble Learning for Predicting Virus-Human Protein-Protein Interaction

Infectious diseases are currently the most important and widespread health problem, and identifying viral infection mechanisms is critical for controlling diseases caused by highly infectious viruses. Because of the lack of non-interactive protein pairs and serious imbalance between positive and negative sample ratios, the supervised learning algorithm is not suitable for prediction. At the same time, due to the lack of information on viral proteins and significant dissimilarity in sequence, some ensemble learning models have poor generalization ability. In this paper, we propose a Sequence-Based Ensemble Learning (Seq-BEL) method to predict the potential virus-human PPIs. Specifically, based on the amino acid sequence of proteins and the currently known virus-human PPI network, Seq-BEL calculates various features and similarities of human proteins and viral proteins, and then combines these similarities and features to score the potential of virus-human PPIs. The computational results show that Seq-BEL achieves success in predicting potential virus-human PPIs and outperforms other state-of-the-art methods. More importantly, Seq-BEL also has good predictive performance for new human proteins and new viral proteins. In addition, the model has the advantages of strong robustness and good generalization ability, and can be used as an effective tool for virus-human PPI prediction.

deepHPI: a comprehensive deep learning platform for accurate prediction and visualization of host-pathogen protein-protein interactions

Host-pathogen protein interactions (HPPIs) play vital roles in many biological processes and are directly involved in infectious diseases. With the outbreak of more frequent pandemics in the last couple of decades, such as the recent outburst of Covid-19 causing millions of deaths, it has become more critical to develop advanced methods to accurately predict pathogen interactions with their respective hosts. During the last decade, experimental methods to identify HPIs have been used to decipher host-pathogen systems with the caveat that those techniques are labor-intensive, expensive and time-consuming. Alternatively, accurate prediction of HPIs can be performed by the use of data-driven machine learning. To provide a more robust and accurate solution for the HPI prediction problem, we have developed a deepHPI tool based on deep learning. The web server delivers four host-pathogen model types: plant-pathogen, human-bacteria, human-virus and animal-pathogen, leveraging its operability to a wide range of analyses and cases of use. The deepHPI web tool is the first to use convolutional neural network models for HPI prediction. These models have been selected based on a comprehensive evaluation of protein features and neural network architectures. The best prediction models have been tested on independent validation datasets, which achieved an overall Matthews correlation coefficient value of 0.87 for animal-pathogen using the combined pseudo-amino acid composition and conjoint triad (PAAC_CT) features, 0.75 for human-bacteria using the combined pseudo-amino acid composition, conjoint triad and normalized Moreau-Broto feature (PAAC_CT_NMBroto), 0.96 for human-virus using PAAC_CT_NMBroto and 0.94 values for plant-pathogen interactions using the combined pseudo-amino acid composition, composition and transition feature (PAAC_CTDC_CTDT). Our server running deepHPI is deployed on a high-performance computing cluster that enables large and multiple user requests, and it provides more information about interactions discovered. It presents an enriched visualization of the resulting host-pathogen networks that is augmented with external links to various protein annotation resources. We believe that the deepHPI web server will be very useful to researchers, particularly those working on infectious diseases. Additionally, many novel and known host-pathogen systems can be further investigated to significantly advance our understanding of complex disease-causing agents. The developed models are established on a web server, which is freely accessible at http://bioinfo.usu.edu/deepHPI/.

Viral haemorrhagic fevers and malaria co-infections among febrile patients seeking health care in Tanzania

Background

In recent years there have been reports of viral haemorrhagic fever (VHF) epidemics in sub-Saharan Africa where malaria is endemic. VHF and malaria have overlapping clinical presentations making differential diagnosis a challenge. The objective of this study was to determine the prevalence of selected zoonotic VHFs and malaria co-infections among febrile patients seeking health care in Tanzania.

Methods

This facility-based cross-sectional study was carried out between June and November 2018 in Buhigwe, Kalambo, Kyela, Kilindi, Kinondoni, Kondoa, Mvomero, and Ukerewe districts in Tanzania. The study involved febrile patients seeking health care from primary healthcare facilities. Blood samples were collected and tested for infections due to malaria, Crimean-Congo haemorrhagic fever (CCHF), Ebola virus disease (EVD), Marburg virus disease (MVD), Rift Valley fever (RVF) and yellow fever (YF). Malaria infections were tested using rapid diagnostics tests while exposure to VHFs was determined by screening for immunoglobulin M antibodies using commercial enzyme-linked immunosorbent assays. The Chi-square test was used to compare the proportions.

Results

A total of 308 participants (mean age = 35 ± 19 years) were involved in the study. Of these, 54 (17.5%) had malaria infection and 15 (4.8%) were positive for IgM antibodies against VHFs (RVF = 8; CCHF = 2; EBV = 3; MBV = 1; YF = 1). Six (1.9%) individuals had both VHF (RVF = 2; CCHF = 1; EVD = 2; MVD = 1) and malaria infections. The highest co-infection prevalence (0.6%) was observed among individuals aged 46‒60 years (P < 0.05). District was significantly associated with co-infection (P < 0.05) with the highest prevalence recorded in Buhigwe (1.2%) followed by Kinondoni (0.9%) districts. Headache (100%) and muscle, bone, back and joint pains (83.3%) were the most significant complaints among those infected with both VHFs and malaria (P = 0.001).

Conclusions

Co-infections of VHF and malaria are prevalent in Tanzania and affect more the older than the younger population. Since the overlapping symptoms in co-infected individuals may challenge accurate diagnosis, adequate laboratory diagnosis should be emphasized in the management of febrile illnesses.

From viral evolution to spatial contagion: a biologically modulated Hawkes model

SUMMARY

Mutations sometimes increase contagiousness for evolving pathogens. During an epidemic, scientists use viral genome data to infer a shared evolutionary history and connect this history to geographic spread. We propose a model that directly relates a pathogen's evolution to its spatial contagion dynamics-effectively combining the two epidemiological paradigms of phylogenetic inference and self-exciting process modeling-and apply this phylogenetic Hawkes process to a Bayesian analysis of 23 421 viral cases from the 2014 to 2016 Ebola outbreak in West Africa. The proposed model is able to detect individual viruses with significantly elevated rates of spatiotemporal propagation for a subset of 1610 samples that provide genome data. Finally, to facilitate model application in big data settings, we develop massively parallel implementations for the gradient and Hessian of the log-likelihood and apply our high-performance computing framework within an adaptively pre-conditioned Hamiltonian Monte Carlo routine.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Journey of remdesivir from the inhibition of hepatitis C virus to the treatment of COVID-19

If a planned path reaches a dead-end, one can simply stop. Or one can turn around, walk back to the last intersection and take another path, or one can consider taking few paths in parallel. The last scenario is reflective of the journey of remdesivir, the first antiviral for the treatment of COVID-19, that was approved by FDA less than 10 months after the isolation of SARS-CoV-2, the virus responsible for the COVID-19 pandemic. As of January 2022, 10 million COVID-19 patients have been treated with remdesivir worldwide, but the journey of this molecule started more than a decade earlier with the search for a cure of hepatitis C virus. The development path of remdesivir before the emergence of COVID-19 represents a valuable example of a preemptive pandemic preparedness, but the pursuit of this path would not have been possible without sustaining support of John C. Martin, whom we will sorely miss for his piercing vision, uncompromising leadership, and genuine compassion for patients suffering around the world.

Epidemic Spreading in Trajectory Networks

Epidemics of infectious diseases, such as the one caused by the rapid spread of the coronavirus disease 2019 (COVID-19), have tested the world's more advanced health systems and have caused an enormous societal and economic damage. The mechanism of contagion is well understood. As people move around, over time, they regularly engage in social interactions. The spatiotemporal network representing these interactions constitutes the backbone on which an epidemic spreads, causing outbreaks. At the same time, advanced technological responses have claimed some success in controlling the epidemic based on digital contact tracing technologies. Motivated by these observations, we design, develop and evaluate a stochastic agent-basedSEIRmodel of epidemic spreading in spatiotemporal networks informed by mobility data of individuals (trajectories). The model focuses on individual variation in mobility patterns that affects the degree of exposure to the disease. Understanding the role that individual nodes play in the process of disease spreading through network effects is fundamental as it allows to (i) assess the risk of infection of individuals, (ii) assess the size of a disease outbreak due to specific individuals, and (iii) assess targeted intervention strategies that aim to control the epidemic spreading. We perform a comprehensive analysis of the model employing COVID-19 as a use case. The results indicate that simple individual-based intervention strategies that exhibit significant network effects can effectively control the spread of an epidemic. We have also demonstrated that targeted interventions can outperform generic intervention strategies. Overall, our work provides an evidence-based data-driven model to support decision making and inform public policy regarding intervention strategies for containing or mitigating the epidemic spread.

pH-EVD: A pH-Paper-Based Extraction and Visual Detection System for Instrument-Free SARS-CoV-2 Diagnostics

The ongoing pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of deaths worldwide. However, most SARS-CoV-2 detection methods depend on time-consuming sample preparation and large detection instruments. Herein, a method employing nonbleeding pH paper to achieve both RNA extraction and visual isothermal amplification is proposed, enabling rapid, instrument-free SARS-CoV-2 detection. By taking advantage of capillary forces, pH-paper-based RNA extraction can be accomplished within 1 min without need for any equipment. Further, the pH paper can mediate dye-free visual isothermal amplification detection. In less than a 46-min sample-to-answer time, pH-paper-based extraction and visual detection (termed pH-EVD) can consistently detect 1200 genome equivalents per microliter of SARS-CoV-2 in saliva, which is comparable to TaqMan probe-based quantitative reverse transcription PCR (RT-qPCR). Through coupling with a chemically heated incubator called a smart cup, the instrument-free, pH-EVD-based SARS-CoV-2 detection method on 30 nasopharyngeal swab samples and 33 contrived saliva samples is clinically validated. Thus, the pH-EVD method provides simple, rapid, reliable, low-cost, and instrument-free SARS-CoV-2 detection and has the potential to streamline onsite COVID-19 diagnostics.

Contributions of single-particle cryoelectron microscopy toward fighting COVID-19

Single-particle cryoelectron microscopy (cryo-EM), whose full capabilities have been realized only within the past decade, has had a pivotal role in the fight against COVID-19. This is due to the technique's intrinsic power to depict both structural and dynamic features of molecules; in this case, of the spike protein of SARS-CoV-2. By now, numerous cryo-EM studies have furthered our understanding of spike protein-angiotensin-converting enzyme 2 (ACE2) receptor interactions, which has informed the design of effective vaccines, and have enabled the characterization of neutralizing antibody binding sites, which will lead to the design of novel therapeutics as the virus evolves.

Clinical presentations, diagnostics, treatments and treatment costs of children and adults with febrile illness in a tertiary referral hospital in south-eastern Guinea: A retrospective longitudinal cohort study

Background

Febrile illness is frequent among patients in the tropics. It is caused by a wide variety of common diseases such as malaria or gastrointestinal infections but also by less common but highly contagious pathogens with epidemic potential. This study describes the clinical features of adult and paediatric patients with febrile illness in in the largest tertiary referral hospital in south-eastern Guinea, a region at high risk for viral haemorrhagic fever outbreaks. The study further compares their diagnostic characteristics, treatments and outcomes with non-febrile patients in order to contribute to the local epidemiology of febrile illness.

Methods

We used retrospective data collection to record demographic and clinical data of all incoming patients during a study period of three months. For the follow-up study of inpatients, we retrospectively reviewed patient charts for diagnostic characteristics, diagnoses and outcomes.

Results

Of the 4317 incoming patients during the study period, 9.5% had a febrile illness. The most used diagnostic measures to identify causative agents in febrile patients were point-of-care tests and most treatments relied on antibiotics. Most common discharge diagnoses for febrile inpatients were malaria (9.6% adults, 56.7% children), salmonella gastroenteritis/typhoid (10.6% adults, 7.8% children) and respiratory infection/pneumonia (5.3% adults, 18.7% children). Inpatient mortality for children was significantly higher in febrile than non-febrile children (18.5% vs. 5.1%, p<0.001) and considerably higher in febrile than non-febrile adults (29.8% vs. 25.0%, p = 0.404).

Conclusions

Malaria, respiratory infection and gastroenteritis are considered the main causes for febrile illness. The wide reliance on rapid diagnostic tests to diagnose febrile patients not only risks to over- or under-diagnose certain diseases but also leaves the possibility of highly infectious diseases in febrile patients unexplored. Furthermore, the heavy reliance on antibiotics risks to cause antimicrobial resistance. High mortality rates in febrile patients, especially children, should be of concern to public health authorities.

Analysis of immune response induction mechanisms implicating the dose-sparing effect of transcutaneous immunization using a self-dissolving microneedle patch

Transcutaneous immunization (TCI) is an effective vaccination method that is easier and less painful than the conventional injectable vaccination method. We previously developed self-dissolving microneedle patches (sdMN) and demonstrated that this TCI method has a high vaccination efficacy in mice and humans. To elucidate the mechanism of immune response induction, which is the basis for the efficacy and safety of TCI with sdMN, we examined the local reaction of the skin where sdMN was applied and the kinetics and differentiation status of immune cells in the draining lymph nodes (DLNs). We found that gene expression of the proinflammatory cytokine Il1b and the downstream transcription factor Irf7 was markedly upregulated in skin tissues after sdMN application. Moreover, activation of Langerhans cells and CD207^- dermal dendritic cells, which are subsets of antigen-presenting cells (APCs) in the skin, and their migration to the DLNs were promoted. Furthermore, the activated APC subsets promoted CD4⁺ T cell and B cell differentiation and the formation of germinal centers, which are the sites of high-affinity antibody production. These phenomena associated with sdMN application may contribute to the efficient production of antigen-specific antibodies after TCI using sdMN. These findings provide essential information regarding immune response induction mechanisms for the development and improvement of TCI preparations.

Ebola virus delta peptide is an enterotoxin

During the 2013-2016 West African (WA) Ebola virus (EBOV) outbreak, severe gastrointestinal symptoms were common in patients and associated with poor outcome. Delta peptide is a conserved product of post-translational processing of the abundant EBOV soluble glycoprotein (sGP). The murine ligated ileal loop model was used to demonstrate that delta peptide is a potent enterotoxin. Dramatic intestinal fluid accumulation follows injection of biologically relevant amounts of delta peptide into ileal loops, along with gross alteration of villous architecture and loss of goblet cells. Transcriptomic analyses show that delta peptide triggers damage response and cell survival pathways and downregulates expression of transporters and exchangers. Induction of diarrhea by delta peptide occurs via cellular damage and regulation of genes that encode proteins involved in fluid secretion. While distinct differences exist between the ileal loop murine model and EBOV infection in humans, these results suggest that delta peptide may contribute to EBOV-induced gastrointestinal pathology.

[Introduction of high containment laboratories in abroad]

Recently, outbreaks of highly pathogenic viruses, such as those of Ebola and Lassa viruses, have become a global public health issue. Such viruses must be handled in biosafety level 4 (BSL-4) laboratories. Currently, 62 BSL-4 laboratories are in operation, under construction, or planned in 24 counties. In this review, I provide an overview of the current status and characteristics of BSL-4 facilities in abroad and introduce my research on the wild-type Ebola virus at the BSL-4 facility in the USA.

Cardiovascular Complications in Major 21st Century Viral Epidemics and Pandemics: an Insight into COVID-19

There have many major history-defining epidemics and pandemics in the 21st century. It is well known that acute infections can cause cardiovascular (CV) complications, especially in those with underlying cardiac disease. The variation in rates and types of CVD complications in major 21st century epidemics and pandemics varies greatly. The coronavirus disease 2019 (COVID-19) pandemic has caused the turmoil of the century and has COVID-19 has resulted in substantial human and economic loss. The novelty of COVID-19 and emerging CV effects is a new entity. In this review, we discuss the major epidemics and pandemics of the 21st century and associated CVD complications.

Can Major Public Health Emergencies Affect Changes in International Oil Prices?

In order to deepen the understanding of the impact of major public health emergencies on the oil market and to enhance the risk response capability, this study analyzed the logical relationship between major public health emergencies and international oil price changes, identified the change points, and calculated the probability of abrupt changes to international oil prices. Based on monthly data during six major public health emergencies from 2009 to 2020, this study built a product partition model. The results show that only the influenza A (H1N1) and COVID-19 pandemics were significant reasons for abrupt changes in international oil prices. Furthermore, the wild poliovirus epidemic, the Ebola epidemic, the Zika epidemic, and the Ebola epidemic in the Democratic Republic of the Congo had limited effects. Overall, the outbreak of a Public Health Emergency of International Concern (PHEIC) in major global economies has a more pronounced impact on international oil prices.