Prioritizing surveillance of Nipah virus in India

Measures to prevent and treat Nipah virus disease: research priorities for 2024-29

Nipah virus causes highly lethal disease, with case-fatality rates ranging from 40% to 100% in recognised outbreaks. No treatments or licensed vaccines are currently available for the prevention and control of Nipah virus infection. In 2019, WHO published an advanced draft of a research and development roadmap for accelerating development of medical countermeasures, including diagnostics, therapeutics, and vaccines, to enable effective and timely emergency response to Nipah virus outbreaks. This Personal View provides an update to the WHO roadmap by defining current research priorities for development of Nipah virus medical countermeasures, based primarily on literature published in the last 5 years and consensus opinion of 15 subject matter experts with broad experience in development of medical countermeasures for Nipah virus or experience in the epidemiology, ecology, or public health control of outbreaks of Nipah virus. The research priorities are organised into four main sections: cross-cutting issues (for those that apply to more than one category of medical countermeasures), diagnostics, therapeutics, and vaccines. The strategic goals and milestones identified in each section focus on key achievements that are needed over the next 6 years to ensure that the necessary tools are available for rapid response to future outbreaks of Nipah virus or related henipaviruses.

Identifying life-history patterns along the fast-slow continuum of mammalian viral carriers

Life-history traits have been identified as major indicators of mammals' susceptibility and exposure to viruses due to evolutionary constraints that link life-history speed with species' ecology and immunity. Nonetheless, it is unclear where along the fast-slow continuum of mammalian life-history lies the greatest diversity of host species. Consequently, life-history patterns that govern host-virus associations remain largely unknown. Here we analyse the virome of 1350 wild mammals and detect the characteristics that drive species' compatibility with different groups of viruses. We highlight that mammals with larger body size and either very rapid or very slow life histories are more likely to carry different groups of viruses, particularly zoonotic ones. While some common life-history patterns emerge across carriers, eco-evolutionary characteristics of viral groups appear to determine association with certain carrier species. Our findings underline the importance of incorporating both mammals' life-history information and viruses' ecological diversity into surveillance strategies to identify potential zoonotic carriers in wildlife.

Mapping the distribution of Nipah virus infections: a geospatial modelling analysis

BACKGROUND

Nipah virus is a zoonotic paramyxovirus responsible for disease outbreaks with high fatality rates in south and southeast Asia. However, knowledge of the potential geographical extent and risk patterns of the virus is poor. We aimed to establish an integrated spatiotemporal and phylogenetic database of Nipah virus infections in humans and animals across south and southeast Asia.

METHODS

In this geospatial modelling analysis, we developed an integrated database containing information on the distribution of Nipah virus infections in humans and animals from 1998 to 2021. We conducted phylodynamic analysis to examine the evolution and migration pathways of the virus and meta-analyses to estimate the adjusted case-fatality rate. We used two boosted regression tree models to identify the potential ecological drivers of Nipah virus occurrences in spillover events and endemic areas, and mapped potential risk areas for Nipah virus endemicity.

FINDINGS

749 people and eight bat species across nine countries were documented as being infected with Nipah virus. On the basis of 66 complete genomes of the virus, we identified two clades-the Bangladesh clade and the Malaysia clade-with the time of the most recent common ancestor estimated to be 1863. Adjusted case-fatality rates varied widely between countries and were higher for the Bangladesh clade than for the Malaysia clade. Multivariable meta-regression analysis revealed significant relationships between case-fatality rate estimates and viral clade (p=0·0021), source country (p=0·016), proportion of male patients (p=0·036), and travel time to health-care facilities (p=0·036). Temperature-related bioclimate variables and the probability of occurrence of Pteropus medius were important contributors to both the spillover and the endemic infection models.

INTERPRETATION

The suitable niches for Nipah virus are more extensive than previously reported. Future surveillance efforts should focus on high-risk areas informed by updated projections. Specifically, intensifying zoonotic surveillance efforts, enhancing laboratory testing capacity, and implementing public health education in projected high-risk areas where no human cases have been reported to date will be crucial. Additionally, strengthening wildlife surveillance and investigating potential modes of transmission in regions with documented human cases is needed.

FUNDING

The Key Research and Development Program of China.

Strategic vaccine stockpiles for regional epidemics of emerging viruses: A geospatial modeling framework

Multinational epidemics of emerging infectious diseases are increasingly common, due to anthropogenic pressure on ecosystems and the growing connectivity of human populations. Early and efficient vaccination can contain outbreaks and prevent mass mortality, but optimal vaccine stockpiling strategies are dependent on pathogen characteristics, reservoir ecology, and epidemic dynamics. Here, we model major regional outbreaks of Nipah virus and Middle East respiratory syndrome, and use these to develop a generalized framework for estimating vaccine stockpile needs based on spillover geography, spatially-heterogeneous healthcare capacity and spatially-distributed human mobility networks. Because outbreak sizes were highly skewed, we found that most outbreaks were readily contained (median stockpile estimate for MERS-CoV: 2,089 doses; Nipah: 1,882 doses), but the maximum estimated stockpile need in a highly unlikely large outbreak scenario was 2-3 orders of magnitude higher (MERS-CoV: ∼87,000 doses; Nipah ∼ 1.1 million doses). Sensitivity analysis revealed that stockpile needs were more dependent on basic epidemiological parameters (i.e., death and recovery rate) and healthcare availability than any uncertainty related to vaccine efficacy or deployment strategy. Our results highlight the value of descriptive epidemiology for real-world modeling applications, and suggest that stockpile allocation should consider ecological, epidemiological, and social dimensions of risk.

Current status of diagnostic assays for emerging zoonotic viruses: Nipah and Hendra

INTRODUCTION

Nipah and Hendra viruses belong to the Paramyxoviridae family, which pose a significant threat to human health, with sporadic outbreaks causing severe morbidity and mortality. Early symptoms include fever, cough, sore throat, and headache, which offer little in terms of differential diagnosis. There are no specific therapeutics and vaccines for these viruses.

AREAS COVERED

This review comprehensively covers a spectrum of diagnostic techniques for Nipah and Hendra virus infections, discussed in conjunction with appropriate type of samples during the progression of infection. Serological assays, reverse transcriptase Real-Time PCR assays, and isothermal amplification assays are discussed in detail, along with a listing of few commercially available detection kits. Patents protecting inventions in Nipah and Hendra virus detection are also covered.

EXPERT OPINION

Despite several outbreaks of Nipah and Hendra infections in the past decade, in-depth research into their pathogenesis, Point-of-Care diagnostics, specific therapies, and human vaccines is lacking. A prompt and accurate diagnosis is pivotal for efficient outbreak management, patient treatment, and the adoption of preventative measures. The emergence of rapid point-of-care tests holds promise in enhancing diagnostic capabilities in real-world settings. The patent landscape emphasizes the importance of innovation and collaboration within the legal and business realms.

Novel methods for the rapid and sensitive detection of Nipah virus based on a CRISPR/Cas12a system

Nipah virus (NiV), a bat-borne zoonotic viral pathogen with high infectivity and lethality to humans, has caused severe outbreaks in several countries of Asia during the past two decades. Because of the worldwide distribution of the NiV natural reservoir, fruit bats, and lack of effective treatments or vaccines for NiV, routine surveillance and early detection are the key measures for containing NiV outbreaks and reducing its influence. In this study, we developed two rapid, sensitive and easy-to-conduct methods, RAA-CRISPR/Cas12a-FQ and RAA-CRISPR/Cas12a-FB, for NiV detection based on a recombinase-aided amplification (RAA) assay and a CRISPR/Cas12a system by utilizing dual-labeled fluorophore-quencher or fluorophore-biotin ssDNA probes. These two methods can be completed in 45 min and 55 min and achieve a limit of detection of 10 copies per μL and 100 copies per μL of NiV N DNA, respectively. In addition, they do not cross-react with nontarget nucleic acids extracted from the pathogens causing similar symptoms to NiV, showing high specificity for NiV N DNA detection. Meanwhile, they show satisfactory performance in the detection of spiked samples from pigs and humans. Collectively, the RAA-CRISPR/Cas12a-FQ and RAA-CRISPR/Cas12a-FB methods developed by us would be promising candidates for the early detection and routine surveillance of NiV in resource-poor areas and outdoors.

Using serosurveys to optimize surveillance for zoonotic pathogens

Zoonotic pathogens pose a significant risk to human health, with spillover into human populations contributing to chronic disease, sporadic epidemics, and occasional pandemics. Despite the widely recognized burden of zoonotic spillover, our ability to identify which animal populations serve as primary reservoirs for these pathogens remains incomplete. This challenge is compounded when prevalence reaches detectable levels only at specific times of year. In these cases, statistical models designed to predict the timing of peak prevalence could guide field sampling for active infections. Here we develop a general model that leverages routinely collected serosurveillance data to optimize sampling for elusive pathogens. Using simulated data sets we show that our methodology reliably identifies times when pathogen prevalence is expected to peak. We then apply our method to two putative Ebolavirus reservoirs, straw-colored fruit bats (Eidolon helvum) and hammer-headed bats (Hypsignathus monstrosus) to predict when these species should be sampled to maximize the probability of detecting active infections. In addition to guiding future sampling of these species, our method yields predictions for the times of year that are most likely to produce future spillover events. The generality and simplicity of our methodology make it broadly applicable to a wide range of putative reservoir species where seasonal patterns of birth lead to predictable, but potentially short-lived, pulses of pathogen prevalence.

Nipah Virus: A Multidimensional Update

Nipah virus (NiV) is an emerging zoonotic paramyxovirus to which is attributed numerous high mortality outbreaks in South and South-East Asia; Bangladesh's Nipah belt accounts for the vast majority of human outbreaks, reporting regular viral emergency events. The natural reservoir of NiV is the Pteropus bat species, which covers a wide geographical distribution extending over Asia, Oceania, and Africa. Occasionally, human outbreaks have required the presence of an intermediate amplification mammal host between bat and humans. However, in Bangladesh, the viral transmission occurs directly from bat to human mainly by ingestion of contaminated fresh date palm sap. Human infection manifests as a rapidly progressive encephalitis accounting for extremely high mortality rates. Despite that, no therapeutic agents or vaccines have been approved for human use. An updated review of the main NiV infection determinants and current potential therapeutic and preventive strategies is exposed.

Langya henipavirus: Is it a potential cause for public health concern?

A new virus, named Langya henipavirus (LayV), has recently been identified in Shandong and Henan provinces in China and has so far infected 35 individuals between April 2018 and August 2021. It is closely related to other known henipaviruses (Nipah and Hendra viruses) that can cause up to 70% human case fatality. Even though LayV has not been shown to be fatal in humans and does not appear to be transmitted from human-to-human, it is an RNA virus with the capacity to evolve genetically in the infected hosts (e.g. shrews) and can infect humans (e.g. farmers who have been in close contacts with shrews). It is therefore important to be vigilant about this new viral outbreak.

In silico screening of herbal phytochemicals to develop a Rasayana for immunity against Nipah virus

BACKGROUND

The first emergence of the Nipah virus (NiV) in 1998 from Malaysia became a major concern when it came to light and resurfaced on different occasions thereafter. NiV is a bat-borne zoonotic and pleomorphic virus that causes severe infection in human and animal hosts. Studies revealed fruit bats are the major reservoirs as natural hosts and pigs as intermediate hosts for the spread of this infection. This became a major concern as the disease was characterized by high pathogenicity varying from 40% to 80% depending on its acuteness. Moreover, the solemnity lies in the fact that the infection transcends from being a mere mild illness to an acute respiratory infection leading to fatal encephalitis with a reportedly high mortality rate. Currently, there is no treatment or vaccine available against the NiV. Many antiviral drugs have been explored and developed but with limited efficacy.

METHODOLOGY

In search of high-affinity ayurvedic alternatives, we conducted a pan-proteome in silico exploration of the NiV proteins for their interaction with the best-suited phytoconstituents. The toxicity prediction of thirty phytochemicals based on their LD50 value identified thirteen potential candidates. Molecular docking studies of those thirteen phytochemicals with five important NiV proteins identified Tanshinone I as the potential compound with a high binding affinity.

RESULTS

The pharmacokinetics and pharmacodynamics studies also aided in determining the absorption, distribution, metabolism, excretion, and toxicity of the selected phytoconstituent. Interestingly, docking studies also revealed Rosmariquinone as a potent alternative to the antiviral drug Remdesivir binding the same pocket of RNA-dependent RNA polymerase of the NiV. A molecular dynamics simulation study of the surface glycoprotein of NiV against Tanshinone I showed a stable complex formation and significant allosteric changes in the protein structure, implying that these phytochemicals could be a natural alternative to synthetic drugs against NiV.

CONCLUSION

This study provides preliminary evidence based on in silico analysis that the herbal molecules showed an effect against NiV. However, it is essential to further evaluate the efficacy of this approach through cell-based experiments, organoid models, and eventually clinical trials.

Viral genomic features predict orthopoxvirus reservoir hosts

Orthopoxviruses (OPVs), including the causative agents of smallpox and mpox have led to devastating outbreaks in human populations worldwide. However, the discontinuation of smallpox vaccination, which also provides cross-protection against related OPVs, has diminished global immunity to OPVs more broadly. We apply machine learning models incorporating both host ecological and viral genomic features to predict likely reservoirs of OPVs. We demonstrate that incorporating viral genomic features in addition to host ecological traits enhanced the accuracy of potential OPV host predictions, highlighting the importance of host-virus molecular interactions in predicting potential host species. We identify hotspots for geographic regions rich with potential OPV hosts in parts of southeast Asia, equatorial Africa, and the Amazon, revealing high overlap between regions predicted to have a high number of potential OPV host species and those with the lowest smallpox vaccination coverage, indicating a heightened risk for the emergence or establishment of zoonotic OPVs. Our findings can be used to target wildlife surveillance, particularly related to concerns about mpox establishment beyond its historical range.

Nipah Virus: An Overview of the Current Status of Diagnostics and Their Role in Preparedness in Endemic Countries

Nipah virus (NiV) is a paramyxovirus responsible for a high mortality rate zoonosis. As a result, it has been included in the list of Blueprint priority pathogens. Bats are the main reservoirs of the virus, and different clinical courses have been described in humans. The Bangladesh strain (NiV-B) is often associated with severe respiratory disease, whereas the Malaysian strain (NiV-M) is often associated with severe encephalitis. An early diagnosis of NiV infection is crucial to limit the outbreak and to provide appropriate care to the patient. Due to high specificity and sensitivity, qRT-PCR is currently considered to be the optimum method in acute NiV infection assessment. Nasal swabs, cerebrospinal fluid, urine, and blood are used for RT-PCR testing. N gene represents the main target used in molecular assays. Different sensitivities have been observed depending on the platform used: real-time PCR showed a sensitivity of about 103 equivalent copies/reaction, SYBRGREEN technology's sensitivity was about 20 equivalent copies/reaction, and in multiple pathogen card arrays, the lowest limit of detection (LOD) was estimated to be 54 equivalent copies/reaction. An international standard for NiV is yet to be established, making it difficult to compare the sensitivity of the different methods. Serological assays are for the most part used in seroprevalence studies owing to their lower sensitivity in acute infection. Due to the high epidemic and pandemic potential of this virus, the diagnosis of NiV should be included in a more global One Health approach to improve surveillance and preparedness for the benefit of public health. Some steps need to be conducted in the diagnostic field in order to become more efficient in epidemic management, such as development of point-of-care (PoC) assays for the rapid diagnosis of NiV.

The genetic diversity of Nipah virus across spatial scales

Nipah virus (NiV), a highly lethal virus in humans, circulates silently in Pteropus bats throughout South and Southeast Asia. Difficulty in obtaining genomes from bats means we have a poor understanding of NiV diversity, including how many lineages circulate within a roost and the spread of NiV over increasing spatial scales. Here we develop phylogenetic approaches applied to the most comprehensive collection of genomes to date (N=257, 175 from bats, 73 from humans) from six countries over 22 years (1999-2020). In Bangladesh, where most human infections occur, we find evidence of increased spillover risk from one of the two co-circulating sublineages. We divide the four major NiV sublineages into 15 genetic clusters (emerged 20-44 years ago). Within any bat roost, there are an average of 2.4 co-circulating genetic clusters, rising to 5.5 clusters at areas of 1,500-2,000 km2. Using Approximate Bayesian Computation fit to a spatial signature of viral diversity, we estimate that each genetic cluster occupies an average area of 1.3 million km2 (95%CI: 0.6-2.3 million), with 14 clusters in an area of 100,000 km2 (95%CI: 6-24). In the few sites in Bangladesh and Cambodia where genomic surveillance has been concentrated, we estimate that most of the genetic clusters have been identified, but only ~15% of overall NiV diversity has been uncovered. Our findings are consistent with entrenched co-circulation of distinct lineages, even within individual roosts, coupled with slow migration over larger spatial scales.

Novel "GaEl Antigenic Patches" Identified by a "Reverse Epitomics" Approach to Design Multipatch Vaccines against NIPAH Infection, a Silent Threat to Global Human Health

Nipah virus (NiV) is a zoonotic virus that causes lethal encephalitis and respiratory disease with the symptom of endothelial cell-cell fusion. Several NiV outbreaks have been reported since 1999 with nearly annual occurrences in Bangladesh. The outbreaks had high mortality rates ranging from 40 to 90%. No specific vaccine has yet been reported against NiV. Recently, several vaccine candidates and different designs of vaccines composed of epitopes against NiV were proposed. Most of the vaccines target single protein or protein complex subunits of the pathogen. The multiepitope vaccines proposed also cover a largely limited number of epitopes, and hence, their efficiency is still uncertain. To address the urgent need for a specific and effective vaccine against NiV infection, in the present study, we have utilized the "reverse epitomics" approach ("overlapping-epitope-clusters-to-patches" method) to identify "antigenic patches" (Ag-Patches) and utilize them as immunogenic composition for multipatch vaccine (MPV) design. The designed MPVs were analyzed for immunologically crucial parameters, physiochemical properties, and interaction with Toll-like receptor 3 ectodomain. In total, 30 CTL (cytotoxic T lymphocyte) and 27 HTL (helper T lymphocyte) antigenic patches were identified from the entire NiV proteome based on the clusters of overlapping epitopes. These identified Ag-Patches cover a total of discrete 362 CTL and 414 HTL epitopes from the entire proteome of NiV. The antigenic patches were utilized as immunogenic composition for the design of two CTL and two HTL multipatch vaccines. The 57 antigenic patches utilized here cover 776 overlapping epitopes targeting 52 different HLA class I and II alleles, providing a global ethnically distributed human population coverage of 99.71%. Such large number of epitope coverage resulting in large human population coverage cannot be reached with single-protein/subunit or multiepitope based vaccines. The reported antigenic patches also provide potential immunogenic composition for early detection diagnostic kits for NiV infection. Further, all the MPVs and Toll-like receptor ectodomain complexes show a stable nature of molecular interaction with numerous hydrogen bonds, salt bridges, and nonbounded contact formation and acceptable root mean square deviation and fluctuation. The cDNA analysis shows a favorable large-scale expression of the MPV constructs in a human cell line. By utilizing the novel "reverse epitomics" approach, highly immunogenic novel "GaEl antigenic patches" (GaEl Ag-Patches), a synonym term for "antigenic patches", were identified and utilized as immunogenic composition to design four MPVs against NiV. We conclude that the novel multipatch vaccines are potential candidates to combat NiV, with greater effectiveness, high specificity, and large human population coverage worldwide.

Tackling a global epidemic threat: Nipah surveillance in Bangladesh, 2006-2021

Human Nipah virus (NiV) infection is an epidemic-prone disease and since the first recognized outbreak in Bangladesh in 2001, human infections have been detected almost every year. Due to its high case fatality rate and public health importance, a hospital-based Nipah sentinel surveillance was established in Bangladesh to promptly detect Nipah cases and respond to outbreaks at the earliest. The surveillance has been ongoing till present. The hospital-based sentinel surveillance was conducted at ten strategically chosen tertiary care hospitals distributed throughout Bangladesh. The surveillance staff ensured that routine screening, enrollment, data, and specimen collection from suspected Nipah cases were conducted daily. The specimens were then processed and transported to the reference laboratory of Institute of Epidemiology, Disease Control and Research (IEDCR) and icddr,b for confirmation of diagnosis through serology and molecular detection. From 2006 to 2021, through this hospital-based surveillance platform, 7,150 individuals were enrolled and tested for Nipah virus. Since 2001, 322 Nipah infections were identified in Bangladesh, 75% of whom were laboratory confirmed cases. Half of the reported cases were primary cases (162/322) having an established history of consuming raw date palm sap (DPS) or tari (fermented date palm sap) and 29% were infected through person-to-person transmission. Since the initiation of surveillance, 68% (218/322) of Nipah cases from Bangladesh have been identified from various parts of the country. Fever, vomiting, headache, fatigue, and increased salivation were the most common symptoms among enrolled Nipah patients. Till 2021, the overall case fatality rate of NiV infection in Bangladesh was 71%. This article emphasizes that the overall epidemiology of Nipah virus infection in Bangladesh has remained consistent throughout the years. This is the only systematic surveillance to detect human NiV infection globally. The findings from this surveillance have contributed to early detection of NiV cases in hospital settings, understanding of Nipah disease epidemiology, and have enabled timely public health interventions for prevention and containment of NiV infection. Although we still have much to learn regarding the transmission dynamics and risk factors of human NiV infection, surveillance has played a significant role in advancing our knowledge in this regard.

A big data-model integration approach for predicting epizootics and population recovery in a keystone species

Infectious diseases pose a significant threat to global health and biodiversity. Yet, predicting the spatiotemporal dynamics of wildlife epizootics remains challenging. Disease outbreaks result from complex nonlinear interactions among a large collection of variables that rarely adhere to the assumptions of parametric regression modeling. We adopted a nonparametric machine learning approach to model wildlife epizootics and population recovery, using the disease system of colonial black-tailed prairie dogs (BTPD, Cynomys ludovicianus) and sylvatic plague as an example. We synthesized colony data between 2001 and 2020 from eight USDA Forest Service National Grasslands across the range of BTPDs in central North America. We then modeled extinctions due to plague and colony recovery of BTPDs in relation to complex interactions among climate, topoedaphic variables, colony characteristics, and disease history. Extinctions due to plague occurred more frequently when BTPD colonies were spatially clustered, in closer proximity to colonies decimated by plague during the previous year, following cooler than average temperatures the previous summer, and when wetter winter/springs were preceded by drier summers/falls. Rigorous cross-validations and spatial predictions indicated that our final models predicted plague outbreaks and colony recovery in BTPD with high accuracy (e.g., AUC generally >0.80). Thus, these spatially explicit models can reliably predict the spatial and temporal dynamics of wildlife epizootics and subsequent population recovery in a highly complex host-pathogen system. Our models can be used to support strategic management planning (e.g., plague mitigation) to optimize benefits of this keystone species to associated wildlife communities and ecosystem functioning. This optimization can reduce conflicts among different landowners and resource managers, as well as economic losses to the ranching industry. More broadly, our big data-model integration approach provides a general framework for spatially explicit forecasting of disease-induced population fluctuations for use in natural resource management decision-making.

Trends in Bacterial Pathogens of Bats: Global Distribution and Knowledge Gaps

Bats have received considerable recent attention for infectious disease research because of their potential to host and transmit viruses, including Ebola, Hendra, Nipah, and multiple coronaviruses. These pathogens are occasionally transmitted from bats to wildlife, livestock, and to humans, directly or through other bridging (intermediate) hosts. Due to their public health relevance, zoonotic viruses are a primary focus of research attention. In contrast, other emerging pathogens of bats, such as bacteria, are vastly understudied despite their ubiquity and diversity. Here, we describe the currently known host ranges and geographic distributional patterns of potentially zoonotic bacterial genera in bats, using published presence-absence data of pathogen occurrence. We identify apparent gaps in our understanding of the distribution of these pathogens on a global scale. The most frequently detected bacterial genera in bats are Bartonella, Leptospira, and Mycoplasma. However, a wide variety of other potentially zoonotic bacterial genera are also occasionally found in bats, such as Anaplasma, Brucella, Borrelia, Coxiella, Ehrlichia, Francisella, Neorickettsia, and Rickettsia. The bat families Phyllostomidae, Vespertilionidae, and Pteropodidae are most frequently reported as hosts of bacterial pathogens; however, the presence of at least one bacterial genus was confirmed in all 15 bat families tested. On a spatial scale, molecular diagnostics of samples from 58 countries and four overseas departments and island states (French Guiana, Mayotte, New Caledonia, and Réunion Island) reported testing for at least one bacterial pathogen in bats. We also identified geographical areas that have been mostly neglected during bacterial pathogen research in bats, such as the Afrotropical region and Southern Asia. Current knowledge on the distribution of potentially zoonotic bacterial genera in bats is strongly biased by research effort towards certain taxonomic groups and geographic regions. Identifying these biases can guide future surveillance efforts, contributing to a better understanding of the ecoepidemiology of zoonotic pathogens in bats.

Identifying the genetic basis of viral spillover using Lassa virus as a test case

The rate at which zoonotic viruses spill over into the human population varies significantly over space and time. Remarkably, we do not yet know how much of this variation is attributable to genetic variation within viral populations. This gap in understanding arises because we lack methods of genetic analysis that can be easily applied to zoonotic viruses, where the number of available viral sequences is often limited, and opportunistic sampling introduces significant population stratification. Here, we explore the feasibility of using patterns of shared ancestry to correct for population stratification, enabling genome-wide association methods to identify genetic substitutions associated with spillover into the human population. Using a combination of phylogenetically structured simulations and Lassa virus sequences collected from humans and rodents in Sierra Leone, we demonstrate that existing methods do not fully correct for stratification, leading to elevated error rates. We also demonstrate, however, that the Type I error rate can be substantially reduced by confining the analysis to a less-stratified region of the phylogeny, even in an already-small dataset. Using this method, we detect two candidate single-nucleotide polymorphisms associated with spillover in the Lassa virus polymerase gene and provide generalized recommendations for the collection and analysis of zoonotic viruses.

A cross-sectional survey on fruit bat-human interaction in Pakistan; one health perspective

OBJECTIVE

Several factors, such as residential area topography, population density, and lack of infrastructure, were hypothesized to contribute toward respondents' knowledge, attitude, and practice regarding disease transmission. The present study was designed to investigate the knowledge, attitudes, and perception of human-fruit bat interaction by student respondents located in ten districts within the Punjab and Khyber Pakhtunkhwa provinces in Pakistan.

METHOD

A cross-sectional survey was conducted by trained enumerators in academic institutions using a structured questionnaire among student respondents (n = 1466), living in two topographically distinct (Mountainous and Plain) residential regions of the Punjab and Khyber Pakhtunkhwa (KPK) provinces in Pakistan regarding their history of bat encounters.

RESULTS

Our study revealed that 71.4% of the 1466 respondents had observed bats in their geographic region. 21% of our survey respondents reported bat bites incidents over their lifetime, but only 40% actively sought medical care for wound management despite reporting they had a close family member that had contracted rabies (27-35%). Our generalized linear models (GLMs) highlighted that a respondent residing in a residential region had a greater association with reporting a suspected bat bite over their lifetime and reported rabies victims in both near and extended family members (OR = -0,85, p-value = 0.03, 95% CI). This appeared to be due to delaying consulting a doctor or medical facility for treatment following a suspected bat bite in the topographic residential group as compared to the respondents in the provincial residential group (OR 1.12, p-value = 0.04, 95% CI).

CONCLUSION

Our findings indicate the necessity of a One Health comprehensive surveillance system in Pakistan for emerging and re-emerging zoonotic pathogens in Pteropodidae.

Correction: Prioritizing surveillance of Nipah virus in India

[This corrects the article DOI: 10.1371/journal.pntd.0007393.].

A study on the design of an in silico self-amplifying mRNA vaccine against Nipah virus using immunoinformatics

The scientific community continues to be impressed with RNA-based vaccines with great efficacy, quick synthesis and speed-to-market. The traditional vaccine may require large doses or repeat injections to achieve an expression for protection against the virus; the self-amplifying mRNA vaccine addresses this limitation. Therefore, a thorough examination of the most antigenic component of the Nipah virus was carried out to design the coding sequence of an antigen, which will provoke a virus-specific immune response. After that, we predicted and evaluated epitopes from NiV G-protein. We employed 8 HTL, 2 CTL and 3 B-cell epitopes. The study of structural compatibility was done by performing docking between HLA alleles and epitopes to get insights into the immune response of epitopes. The entire peptide coding sequence of an antigen was linked using a linker to design the structure of the vaccine. Physicochemical parameters of the designed vaccine constructs were assessed using a protparam server. Later, the vaccine sequence was converted into cDNA. We inserted a gene-expressing replicase at the start of a coding sequence for self-amplification. Next, to formulate the final version of vaccine signal sequences were added. Based on these findings, this mRNA vaccine appears to be a promising option against the Nipah virus.Communicated by Ramaswamy H. Sarma.

Exploring the structural basis to develop efficient multi-epitope vaccines displaying interaction with HLA and TAP and TLR3 molecules to prevent NIPAH infection, a global threat to human health

Nipah virus (NiV) is an emerging zoonotic virus that caused several serious outbreaks in the south asian region with high mortality rates ranging from 40 to 90% since 2001. NiV infection causes lethal encephalitis and respiratory disease with the symptom of endothelial cell-cell fusion. No specific and effective vaccine has yet been reported against NiV. To address the urgent need for a specific and effective vaccine against NiV infection, in the present study, we have designed two Multi-Epitope Vaccines (MEVs) composed of 33 Cytotoxic T lymphocyte (CTL) epitopes and 38 Helper T lymphocyte (HTL) epitopes. Out of those CTL and HTL combined 71 epitopes, 61 novel epitopes targeting nine different NiV proteins were not used before for vaccine design. Codon optimization for the cDNA of both the designed MEVs might ensure high expression potential in the human cell line as stable proteins. Both MEVs carry potential B cell linear epitope overlapping regions, B cell discontinuous epitopes as well as IFN-γ inducing epitopes. Additional criteria such as sequence consensus amongst CTL, HTL and B Cell epitopes was implemented for the design of final constructs constituting MEVs. Hence, the designed MEVs carry the potential to elicit cell-mediated as well as humoral immune response. Selected overlapping CTL and HTL epitopes were validated for their stable molecular interactions with HLA class I and II alleles and in case of CTL epitopes with human Transporter Associated with antigen Processing (TAP) cavity. The structure based epitope cross validation for interaction with TAP cavity was used as another criteria choosing final epitopes for NiV MEVs. Finally, human Beta-defensin 2 and Beta-defensin 3 were used as adjuvants to enhance the immune response of both the MEVs. Molecular dynamics simulation studies of MEVs-TLR3 ectodomain (Human Toll-Like Receptor 3) complex indicated the stable molecular interaction. We conclude that the MEVs designed and in silico validated here could be highly potential vaccine candidates to combat NiV infections, with great effectiveness, high specificity and large human population coverage worldwide.

Optimising predictive models to prioritise viral discovery in zoonotic reservoirs

Despite the global investment in One Health disease surveillance, it remains difficult and costly to identify and monitor the wildlife reservoirs of novel zoonotic viruses. Statistical models can guide sampling target prioritisation, but the predictions from any given model might be highly uncertain; moreover, systematic model validation is rare, and the drivers of model performance are consequently under-documented. Here, we use the bat hosts of betacoronaviruses as a case study for the data-driven process of comparing and validating predictive models of probable reservoir hosts. In early 2020, we generated an ensemble of eight statistical models that predicted host-virus associations and developed priority sampling recommendations for potential bat reservoirs of betacoronaviruses and bridge hosts for SARS-CoV-2. During a time frame of more than a year, we tracked the discovery of 47 new bat hosts of betacoronaviruses, validated the initial predictions, and dynamically updated our analytical pipeline. We found that ecological trait-based models performed well at predicting these novel hosts, whereas network methods consistently performed approximately as well or worse than expected at random. These findings illustrate the importance of ensemble modelling as a buffer against mixed-model quality and highlight the value of including host ecology in predictive models. Our revised models showed an improved performance compared with the initial ensemble, and predicted more than 400 bat species globally that could be undetected betacoronavirus hosts. We show, through systematic validation, that machine learning models can help to optimise wildlife sampling for undiscovered viruses and illustrates how such approaches are best implemented through a dynamic process of prediction, data collection, validation, and updating.

Identifying priority areas for bat conservation in the Western Ghats mountain range, peninsular India

Understanding patterns of species distribution and diversity plays a vital role in biodiversity conservation. Such documentation is frequently lacking for bats, which are relatively little studied and often threatened. The Western Ghats biodiversity hotspot in peninsular India is a bat hotspot with 63 species. We conducted a comprehensive bat survey across the southern Western Ghats and used maximum entropy modeling (MaxEnt) to model the potential distribution of 37 bat species for which sufficient data were available. We generated binary maps of each species using species-specific thresholds to estimate suitable habitat areas and overlaid binary maps of species to produce bat hotspots (we use the term “bat hotspot” for regions that were suitable for more than 25 bat species). We also estimated species richness across protected area networks in the southern Western Ghats to assess the level of protection. The highest levels of species richness were found mainly along the southmost Periyar–Agastyamalai landscape. The study also identified a 1,683 km2 area of potential bat hotspot and 726 km2 (43%) of the total bat hotspots are currently within the protected area network. However, more than 50% of suitable habitats for each of the 37 species remain unprotected. Therefore, conservation decisions are needed to take into account both bat hotspots and species with restricted distributions.

Reviewing the Past, Present, and Future Risks of Pathogens in Ghana and What This Means for Rethinking Infectious Disease Surveillance for Sub-Saharan Africa

The current epidemiological transition makes us wonder how the parallel of infectious diseases (IDs) might be at the end of each passing year. Yet, the surveillance of these IDs continues to focus on high-profile diseases of public health importance without keeping track of the broad spectrum of the IDs we face. Here, we presented the prevalence of the broad spectrum of IDs in Ghana. Data from the annual reports on Gold Coast now Ghana, Global Infectious Diseases and Epidemiology Network (GIDEON), and the District Health Information Management System II (DHIMS2) databases were examined for records of ID prevalence in Ghana. Using the IDs from these databases, the paper assessed the epidemiological transition, pathogen-host interactions, spatiotemporal distribution, transmission routes, and their potential areas of impact in Ghana. The topmost ID recorded in health facilities in Ghana transitioned from yaws in the 1890s to malaria in the 1950s through 2020. We then presented the hosts of a pathogen and the pathogens of a host, the administrative districts where a pathogen was found, and the pathogens found in each district of Ghana. The highest modes of transmission routes were through direct contact for bacteria and airborne or droplet-borne for viral pathogens. From GIDEON, 226 IDs were identified as endemic or potentially endemic in Ghana, with 42% cited in peer-reviewed articles from 2000 to 2020. From the extent of risk of endemic or potentially endemic IDs, Ghana faces a high risk of ID burden that we should be mindful of their changing patterns and should keep track of the state of each of them.

Interaction between Old World fruit bats and humans: From large scale ecosystem services to zoonotic diseases

The Old World tropical and subtropical frugivorous bat genus Rousettus (Pteropodidae) contains species with broad distributions, as well as those occurring in restricted geographical areas, particularly islands. Herein we review the role of Rousettus as a keystone species from a global "One Health" approach and related to ecosystem functioning, zoonotic disease and public health. Rousettus are efficient at dispersing seeds and pollinating flowers; their role in forest regeneration is related to their ability to fly considerable distances during nightly foraging bouts and their relatively small body size, which allows them to access fruits in forested areas with closed vegetation. Rousettus are also reservoirs for various groups of pathogens (viruses, bacteria, fungi, protozoa), which, by definition, are infectious agents causing disease. The study of day roosts of different species of Rousettus and the successful establishment of captive breeding colonies have provided important details related to the infection dynamics of their associated pathogens. Large-scale conversion of forested areas into agricultural landscapes has increased contact between humans and Rousettus, therefore augmenting the chances of infectious agent spillover. Many crucial scientific details are still lacking related to members of this genus, which have direct bearing on the prevention of emerging disease outbreaks, as well as the conservation of these bats. The public should be better informed on the capacity of fruit bats as keystone species for large scale forest regeneration and in spreading pathogens. Precise details on the transmission of zoonotic diseases of public health importance associated with Rousettus should be given high priority.

Virus isolation data improve host predictions for New World rodent orthohantaviruses

Identifying reservoir host species is crucial for understanding the ecology of multi-host pathogens and predicting risks of pathogen spillover from wildlife to people. Predictive models are increasingly used for identifying ecological traits and prioritizing surveillance of likely zoonotic reservoirs, but these often employ different types of evidence for establishing host associations. Comparisons between models with different infection evidence are necessary to guide inferences about the trait profiles of likely hosts and identify which hosts and geographical regions are likely sources of spillover. Here, we use New World rodent-orthohantavirus associations to explore differences in the performance and predictions of models trained on two types of evidence for infection and onward transmission: RT-PCR and live virus isolation data, representing active infections versus host competence, respectively. Orthohantaviruses are primarily carried by muroid rodents and cause the diseases haemorrhagic fever with renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS) in humans. We show that although boosted regression tree (BRT) models trained on RT-PCR and live virus isolation data both performed well and capture generally similar trait profiles, rodent phylogeny influenced previously collected RT-PCR data, and BRTs using virus isolation data displayed a narrower list of predicted reservoirs than those using RT-PCR data. BRT models trained on RT-PCR data identified 138 undiscovered hosts and virus isolation models identified 92 undiscovered hosts, with 27 undiscovered hosts identified by both models. Distributions of predicted hosts were concentrated in several different regions for each model, with large discrepancies between evidence types. As a form of validation, virus isolation models independently predicted several orthohantavirus-rodent host associations that had been previously identified through empirical research using RT-PCR. Our model predictions provide a priority list of species and locations for future orthohantavirus sampling. More broadly, these results demonstrate the value of multiple data types for predicting zoonotic pathogen hosts. These methods can be applied across a range of systems to improve our understanding of pathogen maintenance and increase efficiency of pathogen surveillance.

Henipavirus Immune Evasion and Pathogenesis Mechanisms: Lessons Learnt from Natural Infection and Animal Models

Nipah henipavirus (NiV) and Hendra henipavirus (HeV) are zoonotic emerging paramyxoviruses causing severe disease outbreaks in humans and livestock, mostly in Australia, India, Malaysia, Singapore and Bangladesh. Both are bat-borne viruses and in humans, their mortality rates can reach 60% in the case of HeV and 92% for NiV, thus being two of the deadliest viruses known for humans. Several factors, including a large cellular tropism and a wide zoonotic potential, con-tribute to their high pathogenicity. This review provides an overview of HeV and NiV pathogenicity mechanisms and provides a summary of their interactions with the immune systems of their different host species, including their natural hosts bats, spillover-hosts pigs, horses, and humans, as well as in experimental animal models. A better understanding of the interactions between henipaviruses and their hosts could facilitate the development of new therapeutic strategies and vaccine measures against these re-emerging viruses.

Knowledge, Attitudes, Risk Perception, Preparedness and Vaccine Intent of Health Care Providers towards the Nipah Virus in South India

Nipah virus (NiV) disease (NVD) remains a re-emerging public health threat in India. We assessed the knowledge, attitudes, and risk perception of NVD and future vaccine intent among a convenience sample of health care providers (HCP). The primary outcome measures were the knowledge, attitudes, and risk perception scores. Of 261 participants surveyed, 203 (77.8%) had heard of NiV and associated symptoms. The majority (248, 95%) identified the fruit bat as a primary NiV reservoir and 205 (79.8%) were aware of human-to-human transmission via droplets. Only 101 (38.7%) participants were aware that drinking date palm sap is a risk factor for transmission. Most HCP either agreed (117 (44.8%)) or strongly agreed (131 (50.2%)) that NiV is a serious illness. Less than half (121 (46.4%)) were aware of any institutional protocol for NiV; 235 (90.7%) of HCP stated that they need more information about prevention and treatment options. Knowledge scores were significantly higher among physicians compared to nurses whereas nurses and academic providers were more likely to have higher attitudes scores. A majority of respondents (20,779.9%) were willing to be vaccinated and willing to recommend the NiV vaccine to their patients (21,682.8%). Future strategies include education of HCP to bridge the knowledge gaps and enhance preparedness through disease-specific training for NiV infection.

Nipah Virus-Another Threat From the World of Zoonotic Viruses

Among the diseases that pose a serious threat to public health, those caused by viruses are of great importance. The Nipah virus (NiV) belonging to the Paramyxoviridae family was reported in Malaysia in 1998/1999. Due to its high mortality in humans, its zoonotic nature, the possibility of human-to-human transmission, and the lack of an available vaccine, the World Health Organization (WHO) has recognized it as a global health problem. Depending on strain specificity, neurological symptoms and severe respiratory disorders are observed in NiV infection. In most confirmed cases of NiV epidemics, the appearance of the virus in humans was associated with the presence of various animal species, but generally, bats of Pteropus species are considered the most important natural animal NiV reservoir and vector. Consumption of contaminated food, contact with animals, and “human-to-human” direct contact were identified as NiV transmission routes. Due to the lack of vaccines and drugs with proven effectiveness against NiV, treatment of patients is limited to supportive and prophylactic.

Experimental Evidence of Intrinsic Disorder and Amyloid Formation by the Henipavirus W Proteins

Henipaviruses are severe human pathogens within the Paramyxoviridae family. Beyond the P protein, the Henipavirus P gene also encodes the V and W proteins which share with P their N-terminal, intrinsically disordered domain (NTD) and possess a unique C-terminal domain. Henipavirus W proteins antagonize interferon (IFN) signaling through NTD-mediated binding to STAT1 and STAT4, and prevent type I IFN expression and production of chemokines. Structural and molecular information on Henipavirus W proteins is lacking. By combining various bioinformatic approaches, we herein show that the Henipaviruses W proteins are predicted to be prevalently disordered and yet to contain short order-prone segments. Using limited proteolysis, differential scanning fluorimetry, analytical size exclusion chromatography, far-UV circular dichroism and small-angle X-ray scattering, we experimentally confirmed their overall disordered nature. In addition, using Congo red and Thioflavin T binding assays and negative-staining transmission electron microscopy, we show that the W proteins phase separate to form amyloid-like fibrils. The present study provides an additional example, among the few reported so far, of a viral protein forming amyloid-like fibrils, therefore significantly contributing to enlarge our currently limited knowledge of viral amyloids. In light of the critical role of the Henipavirus W proteins in evading the host innate immune response and of the functional role of phase separation in biology, these studies provide a conceptual asset to further investigate the functional impact of the phase separation abilities of the W proteins.

Nipah Virus: An Updated Review and Emerging Challenges

Many hospitals are teetering on the edge of being overwhelmed, with many already there because of the COVID-19 pandemic. Moreover, a recent report has also warned about the Nipah virus (NiV). NiV is a pleomorphic enveloped virus that belongs to the Paramyxoviridae family (genus Henipavirus); it affects both the respiratory and central nervous systems, with a fatality rate ranging from 40% to 75%, as documented by the World Health Organization. The first reported NiV outbreak was in early 1999 in Malaysia among people who contacted infected pigs. NiV also affected Bangladesh and India, where the main infection route was the consumption of raw date palm sap contaminated by bats. The World Health Organization has listed NiV as one of the emerging pathogens that can lead to severe outbreaks at any moment in the future with limited medical preparations and only a few projects in pharmaceutical firms. There is no licensed treatment for human use against NiV until now, and the management is limited to supportive care and symptomatic treatment. In severe cases with neurologic and respiratory complications, intensive care is needed. This article reviews the published literature and highlights the latest updates about this emerging pathogen and the methods to avoid the spread of this disease during this critical period.

Changing spectrum of acute encephalitis syndrome in India and a syndromic approach

Acute encephalitis syndrome (AES) refers to an acute onset of fever and clinical neurological manifestation that includes mental confusion, disorientation, delirium, or coma, which may occur because of infectious or non-infectious causes. Cerebrospinal fluid (CSF) pleocytosis generally favors infectious etiology, and a normal CSF favors an encephalopathy or non-infectious AES. Among the infectious AES, viral, bacterial, rickettsial, fungal, and parasitic causes are the commonest. Geographical and seasonal clustering and other epidemiological characteristics are important in clinical decision making. Clinical markers like eschar, skin rash, myalgia, hepatosplenomegaly, thrombocytopenia, liver and kidney dysfunction, elevated serum CK, fronto-temporal or thalamic involvement on MRI, and anterior horn cell involvement are invaluable clues for the etiological diagnosis. Categorizing the AES cases into neurologic [Herpes simplex encephalitis (HSE), Japanese encephalitis (JE), and West Nile encephalitis (WNE)] and systemic (scrub typhus, malaria, dengue, and Chikungunya) helps in rational utilization of diagnostic and management resources. In neurological AES, cranial CT/MRI revealing frontotemporal lesion is consistent with HSE, and thalamic and basal ganglia lesions are consistent with JE. Cerebrospinal fluid nucleic acid detection test or IgM antibody for JE and HSE are confirmatory. Presence of frontotemporal involvement on MRI indicates acyclovir treatment pending virological confirmation. In systemic AES, CT/MRI, PCR for HSE and JE, and acyclovir therapy may not be useful, rather treatable etiologies such as malaria, scrub typhus, and leptospirosis should be looked for. If smear or antigen for malaria is positive, should receive antimalarial, if negative doxycycline and ceftriaxone should be started pending serological confirmation of scrub typhus, leptospira, or dengue. A syndromic approach of AES based on the prevalent infection in a geographical region may be developed, which may be cost-effective.

Getting out of crises: Environmental, social-ecological and evolutionary research is needed to avoid future risks of pandemics

The implementation of One Health/EcoHealth/Planetary Health approaches has been identified as key (i) to address the strong interconnections between risk for pandemics, climate change and biodiversity loss and (ii) to develop and implement solutions to these interlinked crises. As a response to the multiple calls from scientists on that subject, we have here proposed seven long-term research questions regarding COVID-19 and emerging infectious diseases (EIDs) that are based on effective integration of environmental, ecological, evolutionary, and social sciences to better anticipate and mitigate EIDs. Research needs cover the social ecology of infectious disease agents, their evolution, the determinants of susceptibility of humans and animals to infections, and the human and ecological factors accelerating infectious disease emergence. For comprehensive investigation, they include the development of nature-based solutions to interlinked global planetary crises, addressing ethical and philosophical questions regarding the relationship of humans to nature and regarding transformative changes to safeguard the environment and human health. In support of this research, we propose the implementation of innovative multidisciplinary facilities embedded in social ecosystems locally: ecological health observatories and living laboratories. This work was carried out in the frame of the European Community project HERA (www.HERAresearchEU.eu), which aims to set priorities for an environment, climate and health research agenda in the European Union by adopting a systemic approach in the face of global environmental change.

The science of the host-virus network

Better methods to predict and prevent the emergence of zoonotic viruses could support future efforts to reduce the risk of epidemics. We propose a network science framework for understanding and predicting human and animal susceptibility to viral infections. Related approaches have so far helped to identify basic biological rules that govern cross-species transmission and structure the global virome. We highlight ways to make modelling both accurate and actionable, and discuss the barriers that prevent researchers from translating viral ecology into public health policies that could prevent future pandemics.

Mitigating vector-borne pathogen spread risks through promoting Gmelina arborea-based afforestation and agroforestry on private farms

Bat-borne pathogens such as Nipah virus, SARS-CoV2, and Ebola have been causing significant losses to the global economy and human lives. In this paper, the role of afforestation and agroforestry in mitigating risk of bat-borne disease transmission to humans is explored using an epidemiological-agroforestry model of land use decision on private farms. Farmers owning land in fragmented forest areas are financially incentivized to grow Gmelina arborea-based forests or intermix them with agricultural crops. This reduces forest fragmentation through creating connectivity between forest patches. While agroforestry may increase the chances of contact between bats and humans, a reduction in forest fragmentation improves the carrying capacity of bats and reduces their risk of migration and roosting near human dwellings. Results indicate that afforestation on private lands or promoting agroforestry can help reduce the risk of virus transmission to humans. A small sum paid under a payment for ecosystem services (PES) scheme would be sufficient to incentivize farmers to convert their farmlands into Gmelina arborea-based agroforestry or forests. In absence of substantial PES incentives, private landowners may delay land conversion when financial benefits generated through agroforestry timber sales carry higher weight in their optimization decisions. Whereas the socially optimal land use option would be to immediately convert farmland in affected areas to agroforestry or forests. Therefore, from a policy perspective, promoting PES-based forestry and agroforestry in fragmented bat habitats can help prevent spread of deadly viruses in the future.

Data Proliferation, Reconciliation, and Synthesis in Viral Ecology

The fields of viral ecology and evolution are rapidly expanding, motivated in part by concerns around emerging zoonoses. One consequence is the proliferation of host–virus association data, which underpin viral macroecology and zoonotic risk prediction but remain fragmented across numerous data portals. In the present article, we propose that synthesis of host–virus data is a central challenge to characterize the global virome and develop foundational theory in viral ecology. To illustrate this, we build an open database of mammal host–virus associations that reconciles four published data sets. We show that this offers a substantially richer view of the known virome than any individual source data set but also that databases such as these risk becoming out of date as viral discovery accelerates. We argue for a shift in practice toward the development, incremental updating, and use of synthetic data sets in viral ecology, to improve replicability and facilitate work to predict the structure and dynamics of the global virome.

Mammals, wildlife trade, and the next global pandemic

Most new infectious diseases emerge when pathogens transfer from animals to humans.^1,2 The suspected origin of the COVID pandemic in a wildlife wet market has resurfaced debates on the role of wildlife trade as a potential source of emerging zoonotic diseases.^3-5 Yet there are no studies quantitatively assessing zoonotic disease risk associated with wildlife trade. Combining data on mammal species hosting zoonotic viruses and mammals known to be in current and future wildlife trade,⁶ we found that one-quarter (26.5%) of the mammals in wildlife trade harbor 75% of known zoonotic viruses, a level much higher than domesticated and non-traded mammals. The traded mammals also harbor distinct compositions of zoonotic viruses and different host reservoirs from non-traded and domesticated mammals. Furthermore, we highlight that primates, ungulates, carnivores, and bats represent significant zoonotic disease risks as they host 132 (58%) of 226 known zoonotic viruses in present wildlife trade, whereas species of bats, rodents, and marsupials represent significant zoonotic disease risks in future wildlife trade. Thus, the risk of carrying zoonotic diseases is not equal for all mammal species in wildlife trade. Overall, our findings strengthen the evidence that wildlife trade and zoonotic disease risks are strongly associated, and that mitigation measures should prioritize species with the highest risk of carrying zoonotic viruses. Curbing the sales of wildlife products and developing principles that support the sustainable and healthy trade of wildlife could be cost-effective investments given the potential risk and consequences of zoonotic outbreaks.

Two decades of one health surveillance of Nipah virus in Thailand

BACKGROUND

Nipah virus (NiV) infection causes encephalitis and has > 75% mortality rate, making it a WHO priority pathogen due to its pandemic potential. There have been NiV outbreak(s) in Malaysia, India, Bangladesh, and southern Philippines. NiV naturally circulates among fruit bats of the genus Pteropus and has been detected widely across Southeast and South Asia. Both Malaysian and Bangladeshi NiV strains have been found in fruit bats in Thailand. This study summarizes 20 years of pre-emptive One Health surveillance of NiV in Thailand, including triangulated surveillance of bats, and humans and pigs in the vicinity of roosts inhabited by NiV-infected bats.

METHODS

Samples were collected periodically and tested for NiV from bats, pigs and healthy human volunteers from Wat Luang village, Chonburi province, home to the biggest P. lylei roosts in Thailand, and other provinces since 2001. Archived cerebrospinal fluid specimens from encephalitis patients between 2001 and 2012 were also tested for NiV. NiV RNA was detected using nested reverse transcription polymerase chain reaction (RT-PCR). NiV antibodies were detected using enzyme-linked immunosorbent assay or multiplex microsphere immunoassay.

RESULTS

NiV RNA (mainly Bangladesh strain) was detected every year in fruit bats by RT-PCR from 2002 to 2020. The whole genome sequence of NiV directly sequenced from bat urine in 2017 shared 99.17% identity to NiV from a Bangladeshi patient in 2004. No NiV-specific IgG antibodies or RNA have been found in healthy volunteers, encephalitis patients, or pigs to date. During the sample collection trips, 100 community members were trained on how to live safely with bats.

CONCLUSIONS

High identity shared between the NiV genome from Thai bats and the Bangladeshi patient highlights the outbreak potential of NiV in Thailand. Results from NiV cross-sectoral surveillance were conveyed to national authorities and villagers which led to preventive control measures, increased surveillance of pigs and humans in vicinity of known NiV-infected roosts, and increased vigilance and reduced risk behaviors at the community level. This proactive One Health approach to NiV surveillance is a success story; that increased collaboration between the human, animal, and wildlife sectors is imperative to staying ahead of a zoonotic disease outbreak.

From Protein to Pandemic: The Transdisciplinary Approach Needed to Prevent Spillover and the Next Pandemic

Pandemics are a consequence of a series of processes that span scales from viral biology at 10-9 m to global transmission at 106 m. The pathogen passes from one host species to another through a sequence of events that starts with an infected reservoir host and entails interspecific contact, innate immune responses, receptor protein structure within the potential host, and the global spread of the novel pathogen through the naive host population. Each event presents a potential barrier to the onward passage of the virus and should be characterized with an integrated transdisciplinary approach. Epidemic control is based on the prevention of exposure, infection, and disease. However, the ultimate pandemic prevention is prevention of the spillover event itself. Here, we focus on the potential for preventing the spillover of henipaviruses, a group of viruses derived from bats that frequently cross species barriers, incur high human mortality, and are transmitted among humans via stuttering chains. We outline the transdisciplinary approach needed to prevent the spillover process and, therefore, future pandemics.

COVID-19 and Preparing for Future Ecological Crises: Hopes from Metagenomics in Facing Current and Future Viral Pandemic Challenges

The current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak demonstrates the potential of coronaviruses, especially bat-derived beta coronaviruses to rapidly escalate to a global pandemic that has caused deaths in the order of several millions already. The huge efforts put in place by the scientific community to address this emergency have disclosed how the implementation of new technologies is crucial in the prepandemic period to timely face future ecological crises. In this context, we argue that metagenomics and new approaches to understanding ecosystems and biodiversity offer veritable prospects to innovate therapeutics and diagnostics against novel and existing infectious agents. We discuss the opportunities and challenges associated with the science of metagenomics, specifically with an eye to inform and prevent future ecological crises and pandemics that are looming on the horizon in the 21st century.

Emergency preparedness for public health threats, surveillance, modelling & forecasting

In the interconnected world, safeguarding global health security is vital for maintaining public health and economic upliftment of any nation. Emergency preparedness is considered as the key to control the emerging public health challenges at both national as well as international levels. Further, the predictive information systems based on routine surveillance, disease modelling and forecasting play a pivotal role in both policy building and community participation to detect, prevent and respond to potential health threats. Therefore, reliable and timely forecasts of these untoward events could mobilize swift and effective public health responses and mitigation efforts. The present review focuses on the various aspects of emergency preparedness with special emphasis on public health surveillance, epidemiological modelling and capacity building approaches. Global coordination and capacity building, funding and commitment at the national and international levels, under the One Health framework, are crucial in combating global public health threats in a holistic manner.

Multi-step molecular docking and dynamics simulation-based screening of large antiviral specific chemical libraries for identification of Nipah virus glycoprotein inhibitors

Nipah virus (NiV) infections are highly contagious and can cause severe febrile encephalitis. An outbreak of NiV infection has reported high mortality rates in Southeast Asian countries including Bangladesh, East Timor, Malaysia, Papua New Guinea, Vietnam, Cambodia, Indonesia, Madagascar, Philippines, Thailand and India. Considering the high risk for an epidemic outbreak, the World Health Organization (WHO) declared NiV as an emerging priority pathogen. However, there are no effective therapeutics or any FDA approved drugs available for the treatment of this infection. Among the known nine proteins of NiV, glycoprotein plays an important role in initiating the entry of viruses and attaching to the host cell receptors. Herein, three antiviral databases consisting of 79,892 chemical entities have been computationally screened against NiV glycoprotein (NiV-G). Particularly, multi-step molecular docking followed by extensive molecular binding interactions analyses, binding free energy estimation, in silico pharmacokinetics, synthetic accessibility and toxicity profile evaluations have been carried out for initial identification of potential NiV-G inhibitors. Further, molecular dynamics (MD) simulation has been performed to understand the dynamic properties of NiV-G protein-bound with proposed five inhibitors (G1-G5) and their interactions behavior, and any conformational changes in NiV-G protein during simulations. Moreover, Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) based binding free energies (∆G) has been calculated from all MD simulation trajectories to understand the energy contribution of each proposed compound in maintaining and stabilizing the complex binding interactions with NiV-G protein. Proposed compounds showed high negative ∆G values ranging from -166.246 to -226.652 kJ/mol indicating a strong affinity towards the NiV-G protein.

Genetic diversity of Nipah virus in Bangladesh

BACKGROUND

Nipah virus (NiV) infection, often fatal in humans, is primarily transmitted in Bangladesh through the consumption of date palm sap contaminated by Pteropus bats. Person-to-person transmission is also common and increases the concern of large outbreaks. This study aimed to characterize the molecular epidemiology, phylogenetic relationship, and the evolution of the nucleocapsid gene (N gene) of NiV.

METHODS

We conducted molecular detection, genetic characterization, and Bayesian time-scale evolution analyses of NiV using pooled Pteropid bat roost urine samples from an outbreak area in 2012 and archived RNA samples from NiV case patients identified during 2012-2018 in Bangladesh.

RESULTS

NiV-RNA was detected in 19% (38/456) of bat roost urine samples and among them; nine N gene sequences were recovered. We also retrieved sequences from 53% (21 out of 39) of archived RNA samples from patients. Phylogenetic analysis revealed that all Bangladeshi strains belonged to NiV-BD genotype and had an evolutionary rate of 4.64 × 10^-4 substitutions/site/year. The analyses suggested that the strains of NiV-BD genotype diverged during 1995 and formed two sublineages.

CONCLUSION

This analysis provides further evidence that the NiV strains of the Malaysian and Bangladesh genotypes diverged recently and continue to evolve. More extensive surveillance of NiV in bats and human will be helpful to explore strain diversity and virulence potential to infect humans through direct or person-to-person virus transmission.

Neural Network Based Country Wise Risk Prediction of COVID-19

The recent worldwide outbreak of the novel coronavirus (COVID-19) has opened up new challenges to the research community. Artificial intelligence (AI) driven methods can be useful to predict the parameters, risks, and effects of such an epidemic. Such predictions can be helpful to control and prevent the spread of such diseases. The main challenges of applying AI is the small volume of data and the uncertain nature. Here, we propose a shallow long short-term memory (LSTM) based neural network to predict the risk category of a country. We have used a Bayesian optimization framework to optimize and automatically design country-specific networks. The results show that the proposed pipeline outperforms state-of-the-art methods for data of 180 countries and can be a useful tool for such risk categorization. We have also experimented with the trend data and weather data combined for the prediction. The outcome shows that the weather does not have a significant role. The tool can be used to predict long-duration outbreak of such an epidemic such that we can take preventive steps earlier.

Beyond Infection: Integrating Competence into Reservoir Host Prediction

Most efforts to predict novel reservoirs of zoonotic pathogens use information about host exposure and infection rather than competence, defined as the ability to transmit pathogens. Better obtaining and integrating competence data into statistical models as covariates, as the response variable, and through postmodel validation should improve predictive research.

Bat-borne virus diversity, spillover and emergence

Most viral pathogens in humans have animal origins and arose through cross-species transmission. Over the past 50 years, several viruses, including Ebola virus, Marburg virus, Nipah virus, Hendra virus, severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory coronavirus (MERS-CoV) and SARS-CoV-2, have been linked back to various bat species. Despite decades of research into bats and the pathogens they carry, the fields of bat virus ecology and molecular biology are still nascent, with many questions largely unexplored, thus hindering our ability to anticipate and prepare for the next viral outbreak. In this Review, we discuss the latest advancements and understanding of bat-borne viruses, reflecting on current knowledge gaps and outlining the potential routes for future research as well as for outbreak response and prevention efforts.