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Scientists across disciplines, policymakers, and journalists have voiced frustration at the unprecedented polarization and misinformation around coronavirus disease 2019 (COVID-19) pandemic. Several false dichotomies have been used to polarize debates while oversimplifying complex issues. In this comprehensive narrative review, we deconstruct six common COVID-19 false dichotomies, address the evidence on these topics, identify insights relevant to effective pandemic responses, and highlight knowledge gaps and uncertainties. The topics of this review are: 1) Health and lives vs. economy and livelihoods, 2) Indefinite lockdown vs. unlimited reopening, 3) Symptomatic vs. asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, 4) Droplet vs. aerosol transmission of SARS-CoV-2, 5) Masks for all vs. no masking, and 6) SARS-CoV-2 reinfection vs. no reinfection. We discuss the importance of multidisciplinary integration (health, social, and physical sciences), multilayered approaches to reducing risk (“Emmentaler cheese model”), harm reduction, smart masking, relaxation of interventions, and context-sensitive policymaking for COVID-19 response plans. We also address the challenges in understanding the broad clinical presentation of COVID-19, SARS-CoV-2 transmission, and SARS-CoV-2 reinfection. These key issues of science and public health policy have been presented as false dichotomies during the pandemic. However, they are hardly binary, simple, or uniform, and therefore should not be framed as polar extremes. We urge a nuanced understanding of the science and caution against black-or-white messaging, all-or-nothing guidance, and one-size-fits-all approaches. There is a need for meaningful public health communication and science-informed policies that recognize shades of gray, uncertainties, local context, and social determinants of health.

In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from known zoonoses to identify which animal pathogens could someday pose a threat to global health. We synthesize the findings of an interdisciplinary workshop on zoonotic risk technologies to answer the following questions. What are the prerequisites, in terms of open data, equity and interdisciplinary collaboration, to the development and application of those tools? What effect could the technology have on global health? Who would control that technology, who would have access to it and who would benefit from it? Would it improve pandemic prevention? Could it create new challenges? This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.

In 2012, a novel betacoronavirus, designated Middle East respiratory syndrome coronavirus or MERS-CoV and associated with severe respiratory disease in humans, emerged in the Arabian Peninsula. To date, 108 human cases have been reported, including cases of human-to-human transmission. The availability of an animal disease model is essential for understanding pathogenesis and developing effective countermeasures. Upon a combination of intratracheal, ocular, oral, and intranasal inoculation with 7 × 10 ⁶ 50% tissue culture infectious dose of the MERS-CoV isolate HCoV-EMC/2012, rhesus macaques developed a transient lower respiratory tract infection. Clinical signs, virus shedding, virus replication in respiratory tissues, gene expression, and cytokine and chemokine profiles peaked early in infection and decreased over time. MERS-CoV caused a multifocal, mild to marked interstitial pneumonia, with virus replication occurring mainly in alveolar pneumocytes. This tropism of MERS-CoV for the lower respiratory tract may explain the severity of the disease observed in humans and the, up to now, limited human-to-human transmission.

Existing mouse models of lethal Ebola virus infection do not reproduce hallmark symptoms of Ebola hemorrhagic fever, neither delayed blood coagulation and disseminated intravascular coagulation nor death from shock, thus restricting pathogenesis studies to nonhuman primates. Here we show that mice from the Collaborative Cross panel of recombinant inbred mice exhibit distinct disease phenotypes after mouse-adapted Ebola virus infection. Phenotypes range from complete resistance to lethal disease to severe hemorrhagic fever characterized by prolonged coagulation times and 100% mortality. Inflammatory signaling was associated with vascular permeability and endothelial activation, and resistance to lethal infection arose by induction of lymphocyte differentiation and cellular adhesion, probably mediated by the susceptibility allele Tek. These data indicate that genetic background determines susceptibility to Ebola hemorrhagic fever.

The availability of a robust disease model is essential for the development of countermeasures for Middle East respiratory syndrome coronavirus (MERS-CoV). While a rhesus macaque model of MERS-CoV has been established, the lack of uniform, severe disease in this model complicates the analysis of countermeasure studies. Modeling of the interaction between the MERS-CoV spike glycoprotein and its receptor dipeptidyl peptidase 4 predicted comparable interaction energies in common marmosets and humans. The suitability of the marmoset as a MERS-CoV model was tested by inoculation via combined intratracheal, intranasal, oral and ocular routes. Most of the marmosets developed a progressive severe pneumonia leading to euthanasia of some animals. Extensive lesions were evident in the lungs of all animals necropsied at different time points post inoculation. Some animals were also viremic; high viral loads were detected in the lungs of all infected animals, and total RNAseq demonstrated the induction of immune and inflammatory pathways. This is the first description of a severe, partially lethal, disease model of MERS-CoV, and as such will have a major impact on the ability to assess the efficacy of vaccines and treatment strategies as well as allowing more detailed pathogenesis studies.

Stakeholders in public health must lobby policy makers to make decisions based on evidence, not political expediency, particularly when the studies that hang in the balance are critical to understanding the origins of epidemics.

Animals and their viruses are connected by a sprawling, tangled network of species interactions. Data on the host-virus network are available from several sources, which use different naming conventions and often report metadata in different levels of detail. Data that catalogue viral diversity on Earth have been fragmented across sources, disciplines, formats, and various degrees of open sharing, posing challenges for research on macroecology, evolution, and public health. Here, we solve this problem by establishing a dynamically maintained database of vertebrate-virus associations, called The Global Virome in One Network (VIRION). The VIRION database has been assembled through both reconciliation of static data sets and integration of dynamically updated databases. These data sources are all harmonized against one taxonomic backbone, including metadata on host and virus taxonomic validity and higher classification; additional metadata on sampling methodology and evidence strength are also available in a harmonized format. In total, the VIRION database is the largest open-source, open-access database of its kind, with roughly half a million unique records that include 9,521 resolved virus “species” (of which 1,661 are ICTV ratified), 3,692 resolved vertebrate host species, and 23,147 unique interactions between taxonomically valid organisms. Together, these data cover roughly a quarter of mammal diversity, a 10th of bird diversity, and ∼6% of the estimated total diversity of vertebrates, and a much larger proportion of their virome than any previous database. We show how these data can be used to test hypotheses about microbiology, ecology, and evolution and make suggestions for best practices that address the unique mix of evidence that coexists in these data. IMPORTANCE Animals and their viruses are connected by a sprawling, tangled network of species interactions. Data on the host-virus network are available from several sources, which use different naming conventions and often report metadata in different levels of detail. VIRION is a new database that combines several of these existing data sources, reconciles taxonomy to a single consistent backbone, and reports metadata in a format designed by and for virologists. Researchers can use VIRION to easily answer questions like “Can any fish viruses infect humans?” or “Which bats host coronaviruses?” or to build more advanced predictive models, making it an unprecedented step toward a full inventory of the global virome.

Transmission of Ebola virus (EBOV) primarily occurs via contact exposure of mucosal surfaces with infected body fluids. Historically, nonhuman primate (NHP) challenge studies have employed intramuscular (i.m.) or small particle aerosol exposure, which are largely lethal routes of infection, but mimic worst-case scenarios such as a needlestick or intentional release, respectively. When exposed by more likely routes of natural infection, limited NHP studies have shown delayed onset of disease and reduced mortality. Here, we performed a series of systematic natural history studies in cynomolgus macaques with a range of conjunctival exposure doses. Challenge with 10,000 plaque forming units (PFU) of EBOV was uniformly lethal, whereas 5/6 subjects survived lower dose challenges (100 or 500 PFU). Conjunctival challenge resulted in a protracted time-to death compared to i.m. Asymptomatic infection was observed in survivors with limited detection of EBOV replication. Inconsistent seropositivity in survivors may suggest physical or natural immunological barriers are sufficient to prevent widespread viral dissemination.

Kyasanur Forest disease virus (KFDV) and the closely related Alkhurma hemorrhagic disease virus (AHFV) are emerging flaviviruses that cause severe viral hemorrhagic fevers in humans. Increasing geographical expansion and case numbers, particularly of KFDV in southwest India, class these viruses as a public health threat. Viral pathogenesis is not well understood and additional vaccines and antivirals are needed to effectively counter the impact of these viruses. However, current animal models of KFDV pathogenesis do not accurately reproduce viral tissue tropism or clinical outcomes observed in humans. Here, we show that pigtailed macaques ( Macaca nemestrina ) infected with KFDV or AHFV develop viremia that peaks 2 to 4 days following inoculation. Over the course of infection, animals developed lymphocytopenia, thrombocytopenia, and elevated liver enzymes. Infected animals exhibited hallmark signs of human disease characterized by a flushed appearance, piloerection, dehydration, loss of appetite, weakness, and hemorrhagic signs including epistaxis. Virus was commonly present in the gastrointestinal tract, consistent with human disease caused by KFDV and AHFV where gastrointestinal symptoms (hemorrhage, vomiting, diarrhea) are common. Importantly, RNAseq of whole blood revealed that KFDV downregulated gene expression of key clotting factors that was not observed during AHFV infection, consistent with increased severity of KFDV disease observed in this model. This work characterizes a nonhuman primate model for KFDV and AHFV that closely resembles human disease for further utilization in understanding host immunity and development of antiviral countermeasures.

Modern molecular technology, and particularly high-throughput sequencing (HTS), has revolutionized virus discovery and expanded the depth and breadth of the virome. Recent HTS was used to identify and discover a previously undescribed member of the family Flaviviridae that has genomic features characteristic of both hepaciviruses and pegiviruses. This virus, designated human hepegivirus-1 (HHpgV-1), may represent a previously undescribed new genus in the Flaviviridae family with implications for public health and blood supply safety. Detecting uncharacterized viruses such as HHpgV-1 in clinical samples requires an unbiased screening method that is as sensitive as PCR, while simultaneously detecting multiple rare viral sequences. The virome-capture-sequencing platform for vertebrate viruses (VirCapSeq-VERT) uses positive-selection oligonucleotide capture to sensitively detect sequences from every known vertebrate virus, even in high-background specimens with low-abundance viruses. VirCapSeq-VERT can also detect uncharacterized viruses with sequence homology to known viruses, enabling a new paradigm for virus detection.