The genetic diversity of Nipah virus across spatial scales.

BACKGROUND: Nipah virus (NiV), a highly lethal virus in humans, circulates in Pteropus bats throughout South and Southeast Asia. Difficulty in obtaining viral genomes from bats means we have a poor understanding of NiV diversity. METHODS: 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). We divide the four major NiV sublineages into 15 genetic clusters. Using Approximate Bayesian Computation fit to a spatial signature of viral diversity, we estimate the presence and the average size of genetic clusters per area. RESULTS: We find that, within any bat roost, there are an average of 2.4 co-circulating genetic clusters, rising to 5.5 clusters at areas of 1500-2000km2. We estimate that each genetic cluster occupies an average area of 1.3million km2 (95%CI: 0.6-2.3 million), with 14 clusters in an area of 100,000km2 (95%CI: 6-24). In the few sites in Bangladesh and Cambodia where genomic surveillance has been concentrated, we estimate that most clusters have been identified, but only ∼15% of overall NiV diversity has been uncovered. CONCLUSION: Our findings are consistent with entrenched co-circulation of distinct lineages, even within roosts, coupled with slow migration over larger spatial scales.

Association of biosecurity and hygiene practices with avian influenza A/H5 and A/H9 virus infections in turkey farms.

High pathogenicity avian influenza (HPAI) H5N1 outbreaks pose a significant threat to the health of livestock, wildlife, and humans. Avian influenza viruses (AIVs) are enzootic in poultry in many countries, including Bangladesh, necessitating improved farm biosecurity measures. However, the comprehension of biosecurity and hygiene practices, as well as the infection of AIV in turkey farms, are poorly understood in Bangladesh. Therefore, we conducted this study to determine the prevalence of AIV subtypes and their association with biosecurity and hygiene practices in turkey farms. We collected oropharyngeal and cloacal swabs from individual turkeys from 197 farms across 9 districts in Bangladesh from March to August 2019. We tested the swab samples for the AIV matrix gene (M gene) followed by H5, H7, and H9 subtypes using real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). We found 24.68% (95% CI:21.54-28.04) of turkey samples were AIV positive, followed by 5.95% (95% CI: 4.33-7.97) for H5, 6.81% (95% CI: 5.06-8.93) for H9 subtype and no A/H7 was found. Using a generalized linear mixed model, we determined 10 significant risk factors associated with AIV circulation in turkey farms. We found that the absence of sick turkeys, the presence of footbaths, the absence of nearby poultry farms, concrete flooring, and the avoidance of mixing newly purchased turkeys with existing stock can substantially reduce the risk of AIV circulation in turkey farms (odds ratio ranging from 0.02 to 0.08). Furthermore, the absence of nearby live bird markets, limiting wild bird access, no visitor access, improved floor cleaning frequency, and equipment disinfection practices also had a substantial impact on lowering the AIV risk in the farms (odds ratio ranging from 0.10 to 0.13). The results of our study underscore the importance of implementing feasible and cost-effective biosecurity measures aimed at reducing AIV transmission in turkey farms. Particularly in resource-constrained environments such as Bangladesh, such findings might assist governmental entities in enhancing biosecurity protocols within their poultry sector, hence mitigating and potentially averting the transmission of AIV and spillover to humans.

SalivaDirect: an alternative to a conventional RNA extraction protocol for molecular detection of SARS-CoV-2 in a clinical setting.

IMPORTANCE: Affordable and accessible tests for COVID-19 allow for timely disease treatment and pandemic management. SalivaDirect is a faster and easier method to implement than NPS sampling. Patients can self-collect saliva samples at home or in other non-clinical settings without the help of a healthcare professional. Sample processing in SalivaDirect is less complex and more adaptable than in conventional nucleic acid extraction methods. We found that SalivaDirect has good diagnostic performance and is ideal for large-scale testing in settings where supplies may be limited or trained healthcare professionals are unavailable.

Determinants for the presence of avian influenza virus in live bird markets in Bangladesh: Towards an easy fix of a looming one health issue.

Highly pathogenic avian influenza virus subtype H5N1 endangers poultry, wildlife, and human health and is enzootic in large parts of Asia, with live bird markets (LBMs) as putative hotspots for their maintenance, amplification, and spread. To mitigate the extent of these and other avian influenza viruses (AIV) of concern, we aimed to increase our quantitative understanding of the factors determining the presence of avian influenza virus in LBM stalls. Between 2016 and 2017, we collected fecal or offal samples from 1008 stalls in 113 LBMs across the Dhaka and Rajshahi districts in Bangladesh. For each stall, samples were pooled and tested for the AIV matrix gene, followed by H5 and H9 subtyping using rRT-PCR. We detected Influenza A viral RNA in 49% of the stalls. Of the AIV positive samples, 52% and 24% were determined to be H5 and H9 viruses, respectively, which are both subtypes of considerable health concern. We used generalized linear mixed effect modelling to study AIV presence in individual stalls within LBMs as a function of 13 out of the 20 risk factors identified by FAO. We found that small and feasible improvements in cleaning and disinfection frequency, installing running water in stalls, and not mixing different breeds of chicken in the same cages had large impacts on the presence of AIV in stalls (Odds ratios 0.03-0.05). Next, cleaning vehicles used in poultry transport, not selling waterfowl with chickens in the same stall, buying stock directly from commercial farms, separating sick birds from healthy ones, and avoiding access by wild birds like house crows, also had major effects on lowering the risk of stalls having AIV (Odds ratios 0.16-0.33). These findings can be directly used in developing practical and affordable measures to reduce the prevalence of AIV in LBMs. Also, in settings with limited resources like Bangladesh, such mitigation may significantly contribute to reducing AIV circulation amongst poultry and spillover to wildlife and humans.

Potential risk zones and climatic factors influencing the occurrence and persistence of avian influenza viruses in the environment of live bird markets in Bangladesh.

Live bird markets (LBMs) are critical for poultry trade in many developing countries that are regarded as hotspots for the prevalence and contamination of avian influenza viruses (AIV). Therefore, we conducted weekly longitudinal environmental surveillance in LBMs to determine annual cyclic patterns of AIV subtypes, environmental risk zones, and the role of climatic factors on the AIV presence and persistence in the environment of LBM in Bangladesh. From January 2018 to March 2020, we collected weekly fecal and offal swab samples from each LBM and tested using rRT-PCR for the M gene and subtyped for H5, H7, and H9. We used Generalized Estimating Equations (GEE) approaches to account for repeated observations over time to correlate the AIV prevalence and potential risk factors and the negative binomial and Poisson model to investigate the role of climatic factors on environmental contamination of AIV at the LBM. Over the study period, 37.8% of samples tested AIV positive, 18.8% for A/H5, and A/H9 was, for 15.4%. We found the circulation of H5, H9, and co-circulation of H5 and H9 in the environmental surfaces year-round. The Generalized Estimating Equations (GEE) model reveals a distinct seasonal pattern in transmitting AIV and H5. Specifically, certain summer months exhibited a substantial reduction of risk up to 70-90% and 93-94% for AIV and H5 contamination, respectively. The slaughtering zone showed a significantly higher risk of contamination with H5, with a three-fold increase in risk compared to bird-holding zones. From the negative binomial model, we found that climatic factors like temperature and relative humidity were also significantly associated with weekly AIV circulation. An increase in temperature and relative humidity decreases the risk of AIV circulation. Our study underscores the significance of longitudinal environmental surveillance for identifying potential risk zones to detect H5 and H9 virus co-circulation and seasonal transmission, as well as the imperative for immediate interventions to reduce AIV at LBMs in Bangladesh. We recommend adopting a One Health approach to integrated AIV surveillance across animal, human, and environmental interfaces in order to prevent the epidemic and pandemic of AIV.

In silico prediction of interaction between Nipah virus attachment glycoprotein and host cell receptors Ephrin-B2 and Ephrin-B3 in domestic and peridomestic mammals.

Nipah virus (NiV) is a lethal bat-borne zoonotic virus that causes mild to acute respiratory distress and neurological manifestations in humans with a high mortality rate. NiV transmission to humans occurs via consumption of bat-contaminated fruit and date palm sap (DPS), or through direct contact with infected individuals and livestock. Since NiV outbreaks were first reported in pigs from Malaysia and Singapore, non-neutralizing antibodies against NiV attachment Glycoprotein (G) have also been detected in a few domestic mammals. NiV infection is initiated after NiV G binds to the host cell receptors Ephrin-B2 and Ephrin-B3. In this study, we assessed the degree of NiV host tropism in domestic and peridomestic mammals commonly found in Bangladesh that may be crucial in the transmission of NiV by serving as intermediate hosts. We carried out a protein-protein docking analysis of NiV G complexes (n = 52) with Ephrin-B2 and B3 of 13 domestic and peridomestic species using bioinformatics tools. Protein models were generated by homology modelling and the structures were validated for model quality. The different protein-protein complexes in this study were stable, and their binding affinity (ΔG) scores ranged between -8.0 to -19.1 kcal/mol. NiV Bangladesh (NiV-B) strain displayed stronger binding to Ephrin receptors, especially with Ephrin-B3 than the NiV Malaysia (NiV-M) strain, correlating with the observed higher pathogenicity of NiV-B strains. From the docking result, we found that Ephrin receptors of domestic rat (R. norvegicus) had a higher binding affinity for NiV G, suggesting greater susceptibility to NiV infections compared to other study species. Investigations for NiV exposure to domestic/peridomestic animals will help us knowing more the possible role of rats and other animals as intermediate hosts of NiV and would improve future NiV outbreak control and prevention in humans and domestic animals.

Lessons learned from identifying clusters of severe acute respiratory infections with influenza sentinel surveillance, Bangladesh, 2009-2020.

Background: We explored whether hospital-based surveillance is useful in detecting severe acute respiratory infection (SARI) clusters and how often these events result in outbreak investigation and community mitigation. Methods: During May 2009-December 2020, physicians at 14 sentinel hospitals prospectively identified SARI clusters (i.e., ≥2 SARI cases who developed symptoms ≤10 days of each other and lived <30 min walk or <3 km from each other). Oropharyngeal and nasopharyngeal swabs were tested for influenza and other respiratory viruses by real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). We describe the demographic of persons within clusters, laboratory results, and outbreak investigations. Results: Field staff identified 464 clusters comprising 1427 SARI cases (range 0-13 clusters per month). Sixty percent of clusters had three, 23% had two, and 17% had ≥4 cases. Their median age was 2 years (inter-quartile range [IQR] 0.4-25) and 63% were male. Laboratory results were available for the 464 clusters with a median of 9 days (IQR = 6-13 days) after cluster identification. Less than one in five clusters had cases that tested positive for the same virus: respiratory syncytial virus (RSV) in 58 (13%), influenza viruses in 24 (5%), human metapneumovirus (HMPV) in five (1%), human parainfluenza virus (HPIV) in three (0.6%), adenovirus in two (0.4%). While 102/464 (22%) had poultry exposure, none tested positive for influenza A (H5N1) or A (H7N9). None of the 464 clusters led to field deployments for outbreak response. Conclusions: For 11 years, none of the hundreds of identified clusters led to an emergency response. The value of this event-based surveillance might be improved by seeking larger clusters, with stronger epidemiologic ties or decedents.

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.

Development of a neutralization assay using a vesicular stomatitis virus expressing Nipah virus glycoprotein and a fluorescent protein.

Nipah virus (NiV) is a highly pathogenic paramyxovirus with a high case fatality rate. Due to its high pathogenicity, pandemic potential, and lack of therapeutics or approved vaccines, its study requires biosafety level 4 (BSL4) containment. In this report, we developed a novel neutralization assay for use in biosafety level 2 laboratories. The assay uses a recombinant vesicular stomatitis virus expressing NiV glycoprotein and a fluorescent protein. The recombinant virus propagates as a replication-competent virus in a cell line constitutively expressing NiV fusion protein, but it is restricted to a single round of replication in wild-type cells. We used this system to evaluate the neutralization activity of monoclonal and polyclonal antibodies, plasma from NiV-infected hamsters, and serum from human patients. Therefore, this recombinant virus could be used as a surrogate for using pathogenic NiV and may constitute a powerful tool to develop therapeutics in low containment laboratories.

Interpretation of molecular detection of avian influenza A virus in respiratory specimens collected from live bird market workers in Dhaka, Bangladesh: infection or contamination?

OBJECTIVES: Interpreting real-time reverse transcription-polymerase chain reaction (rRT-PCR) results for human avian influenza A virus (AIV) detection in contaminated settings like live bird markets (LBMs) without serology or viral culture poses a challenge. METHODS: During February-March 2012 and November 2012-February 2013, we screened workers at nine LBMs in Dhaka, Bangladesh, to confirm molecular detections of AIV RNA in respiratory specimens with serology. We tested nasopharyngeal (NP) and throat swabs from workers with influenza-like illness (ILI) and NP, throat, and arm swabs from asymptomatic workers for influenza virus by rRT-PCR and sera for seroconversion and antibodies against HPAI A(H5N1) and A(H9N2) viruses. RESULTS: Among 1273 ILI cases, 34 (2.6%) had A(H5), 56 (4%) had A(H9), and six (0.4%) had both A(H5) and A(H9) detected by rRT-PCR. Of 192 asymptomatic workers, A(H5) was detected in eight (4%) NP and 38 (20%) arm swabs. Of 28 ILI cases with A(H5) or A(H9) detected, none had evidence of seroconversion, but one (3.5%) and 12 (43%) were seropositive for A(H5) and A(H9), respectively. CONCLUSION: Detection of AIV RNA in respiratory specimens from symptomatic and asymptomatic LBM workers without evidence of seroconversion or virus isolation suggests environmental contamination, emphasizing caution in interpreting rRT-PCR results in high viral load settings.

Beta, Delta, and Omicron, Deadliest Among SARS-CoV-2 Variants: A Computational Repurposing Approach.

SARS-CoV-2 has been highly susceptible to mutations since its emergence in Wuhan, China, and its subsequent propagation due to containing an RNA as its genome. The emergence of variants with improved transmissibility still poses a grave threat to global health. The spike protein mutation is mainly responsible for higher transmissibility and risk severity. This study retrieved SARS-CoV-2 variants structural and nonstructural proteins (NSPs) sequences from several geographic locations, including Africa, Asia, Europe, Oceania, and North and South America. First, multiple sequence alignments with BioEdit and protein homology modeling were performed using the SWISS Model. Then the structure visualization and structural analysis were performed by superimposing against the Wuhan sequence by Pymol to retrieve the RMSD values. Sequence alignment revealed familiar, uncommon regional among variants and, interestingly, a few unique mutations in Beta, Delta, and Omicron. Structural analysis of such unique mutations revealed that they caused structural deviations in Beta, Delta, and Omicron spike proteins. In addition, these variants were more severe in terms of hospitalization, sickness, and higher mortality, which have a substantial relationship with the structural deviations because of those unique mutations. Such evidence provides insight into the SARS-CoV-2 spike protein vulnerability toward mutation and their structural and functional deviations, particularly in Beta, Delta, and Omicron, which might be the cause of their broader coverage. This knowledge can help us with regional vaccine strain selection, virus pathogenicity testing, diagnosis, and treatment with more specific vaccines.

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.

Epidemiology and phylodynamics of multiple clades of H5N1 circulating in domestic duck farms in different production systems in Bangladesh.

Waterfowl are considered to be natural reservoirs of the avian influenza virus (AIV). However, the dynamics of transmission and evolutionary patterns of AIV and its subtypes within duck farms in Bangladesh remain poorly documented. Hence, a cross-sectional study was conducted in nine districts of Bangladesh between 2019 and 2021, to determine the prevalence of AIV and its subtypes H5 and H9, as well as to identify risk factors and the phylodynamics of H5N1 clades circulating in domestic duck farms. The oropharyngeal and cloacal swab samples were tested for the AIV Matrix gene (M-gene) followed by H5, H7, and H9 subtypes using rRT-PCR. The exploratory analysis was performed to estimate AIV and its subtype prevalence in different production systems, and multivariable logistic regression model was used to identify the risk factors that influence AIV infection in ducks. Bayesian phylogenetic analysis was conducted to generate a maximum clade credibility (MCC) tree and the maximum likelihood method to determine the phylogenetic relationships of the H5N1 viruses isolated from ducks. AIV was detected in 40% (95% CI: 33.0-48.1) of the duck farms. The prevalence of AIV was highest in nomadic ducks (39.8%; 95% CI: 32.9-47.1), followed by commercial ducks (24.6%; 95% CI: 14.5-37.3) and backyard ducks (14.4%; 95% CI: 10.5-19.2). The H5 prevalence was also highest in nomadic ducks (19.4%; 95% CI: 14.0-25.7). The multivariable logistic regression model revealed that ducks from nomadic farms (AOR: 2.4; 95% CI: 1.45-3.93), juvenile (AOR: 2.2; 95% CI: 1.37-3.61), and sick ducks (AOR: 11.59; 95% CI: 4.82-32.44) had a higher risk of AIV. Similarly, the likelihood of H5 detection was higher in sick ducks (AOR: 40.8; 95% CI: 16.3-115.3). Bayesian phylogenetic analysis revealed that H5N1 viruses in ducks belong to two distinct clades, 2.3.2.1a, and 2.3.4.4b. The clade 2.3.2.1a (reassorted) has been evolving silently since 2015 and forming at least nine subgroups based on >90% posterior probability. Notably, clade 2.3.4.4b was introduced in ducks in Bangladesh by the end of the year 2020, which was genetically similar to viruses detected in wild birds in Japan, China, and Africa, indicating migration-associated transmission of an emerging panzootic clade. We recommend continuing AIV surveillance in the duck production system and preventing the intermingling of domestic ducks with migratory waterfowl in wetlands.

Annual trading patterns and risk factors of avian influenza A/H5 and A/H9 virus circulation in turkey birds (Meleagris gallopavo) at live bird markets in Dhaka city, Bangladesh.

The impacts of the avian influenza virus (AIV) on farmed poultry and wild birds affect human health, livelihoods, food security, and international trade. The movement patterns of turkey birds from farms to live bird markets (LBMs) and infection of AIV are poorly understood in Bangladesh. Thus, we conducted weekly longitudinal surveillance in LBMs to understand the trading patterns, temporal trends, and risk factors of AIV circulation in turkey birds. We sampled a total of 423 turkeys from two LBMs in Dhaka between May 2018 and September 2019. We tested the swab samples for the AIV matrix gene (M-gene) followed by H5, H7, and H9 subtypes using real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). We used exploratory analysis to investigate trading patterns, annual cyclic trends of AIV and its subtypes, and a generalized estimating equation (GEE) logistic model to determine the factors that influence the infection of H5 and H9 in turkeys. Furthermore, we conducted an observational study and informal interviews with traders and vendors to record turkey trading patterns, demand, and supply and turkey handling practices in LBM. We found that all trade routes of turkey birds to northern Dhaka are unidirectional and originate from the northwestern and southern regions of Bangladesh. The number of trades from the source district to Dhaka depends on the turkey density. The median distance that turkey was traded from its source district to Dhaka was 188 km (Q1 = 165, Q3 = 210, IQR = 45.5). We observed seasonal variation in the median and average distance of turkey. The qualitative findings revealed that turkey farming initially became reasonably profitable in 2018 and at the beginning of 2019. However, the fall in demand and production in the middle of 2019 may be related to unstable market pricing, high feed costs, a shortfall of adequate marketing facilities, poor consumer knowledge, and a lack of advertising. The overall prevalence of AIV, H5, and H9 subtypes in turkeys was 31% (95% CI: 26.6-35.4), 16.3% (95% CI: 12.8-19.8), and 10.2% (95% CI: 7.3-13.1) respectively. None of the samples were positive for H7. The circulation of AIV and H9 across the annual cycle showed no seasonality, whereas the circulation of H5 showed significant seasonality. The GEE revealed that detection of AIV increases in retail vendor business (OR: 1.71; 95% CI: 1.12-2.62) and the bird's health status is sick (OR: 10.77; 95% CI: 4.31-26.94) or dead (OR: 11.33; 95% CI: 4.30-29.89). We also observed that winter season (OR: 5.83; 95% CI: 2.80-12.14) than summer season, dead birds (OR: 61.71; 95% CI: 25.78-147.75) and sick birds (OR 8.33; 95% CI: 3.36-20.64) compared to healthy birds has a higher risk of H5 infection in turkeys. This study revealed that the turkeys movements vary by time and season from the farm to the LBM. This surveillance indicated year-round circulation of AIV with H5 and H9 subtypes in turkey birds in LBMs. The seasonality and health condition of birds influence H5 infection in birds. The trading pattern of turkey may play a role in the transmission of AIV viruses in the birds. The selling of sick turkeys infected with H5 and H9 highlights the possibility of virus transmission to other species of birds sold at LBMs and to people.

Monitoring SARS-CoV-2 variants in wastewater of Dhaka City, Bangladesh: approach to complement public health surveillance systems.

BACKGROUND: Wastewater-based epidemiological surveillance has been considered a powerful tool for early detection and monitoring of the dynamics of SARS-CoV-2 and its lineages circulating in a community. This study is aimed to investigate the complexity of SARS-CoV-2 infection dynamics in Dhaka city by examining its genetic variants in wastewater. Also, the study seeks to determine a connection between the SARS-CoV-2 variations detected in clinical testing and those found in wastewater samples. RESULTS: Out of 504 samples tested in RT-qPCR, 185 (36.7%) tested positive for SARS-CoV-2 viral RNA. The median log10 concentration of SARS-CoV-2 N gene copies/Liter of wastewater (gc/L) was 5.2, and the median log10 concentration of ORF1ab was 4.9. To further reveal the genetic diversity of SARS-CoV-2, ten samples with ORF1ab real-time RT-PCR cycle threshold (Ct) values ranging from 28.78 to 32.13 were subjected to whole genome sequencing using nanopore technology. According to clade classification, sequences from wastewater samples were grouped into 4 clades: 20A, 20B, 21A, 21J, and the Pango lineage, B.1, B.1.1, B.1.1.25, and B.1.617.2, with coverage ranging from 94.2 to 99.8%. Of them, 70% belonged to clade 20B, followed by 10% to clade 20A, 21A, and 21J. Lineage B.1.1.25 was predominant in Bangladesh and phylogenetically related to the sequences from India, the USA, Canada, the UK, and Italy. The Delta variant (B.1.617.2) was first identified in clinical samples at the beginning of May 2021. In contrast, we found that it was circulating in the community and was detected in wastewater in September 2020. CONCLUSION: Environmental surveillance is useful for monitoring temporal and spatial trends of existing and emerging infectious diseases and supports evidence-based public health measures. The findings of this study supported the use of wastewater-based epidemiology and provided the baseline data for the dynamics of SARS-CoV-2 variants in the wastewater environment in Dhaka, Bangladesh.

Prevalence and risk factors for avian influenza virus (H5 and H9) contamination in peri-urban and rural live bird markets in Bangladesh.

Avian influenza viruses (AIV) have been frequently detected in live bird markets (LBMs) around the world, primarily in urban areas, and have the ability to spillover to other species, including humans. Despite frequent detection of AIV in urban LBMs, the contamination of AIV on environmental surfaces in rural and peri-urban LBMs in Bangladesh is poorly documented. Therefore, we conducted this study to determine the prevalence of AIV subtypes within a subset of peri-urban and rural LBMs in Bangladesh and to further identify associated risk factors. Between 2017 and 2018, we collected faecal and offal samples from 200 stalls in 63 LBMs across four sub-districts. We tested the samples for the AIV matrix gene (M-gene) followed by H5, H7, and H9 subtypes using real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). We performed a descriptive analysis of market cleanliness and sanitation practices in order to further elucidate the relationship between LBM biosecurity and AIV subtypes by species, sample types, and landscape. Subsequently, we conducted a univariate analysis and a generalized linear mixed model (GLMM) to determine the risk factors associated with AIV contamination at individual stalls within LBMs. Our findings indicate that practices related to hygiene and the circulation of AIV significantly differed between rural and peri-urban live bird markets. 42.5% (95% CI: 35.56-49.67) of stalls were positive for AIV. A/H5, A/H9, and A HA/Untyped were detected in 10.5% (95% CI: 6.62-15.60), 9% (95% CI: 5.42-13.85), and 24.0% (95% CI: 18.26-30.53) of stalls respectively, with no detection of A/H7. Significantly higher levels of AIV were found in the Sonali chicken strain compared to the exotic broiler, and in offal samples compared to fecal samples. In the GLMM analysis, we identified several significant risk factors associated with AIV contamination in LBMs at the stall level. These include: landscape (AOR: 3.02; 95% CI: 1.18-7.72), the number of chicken breeds present (AOR: 2.4; 95% CI: 1.01-5.67), source of birds (AOR: 2.35; 95% CI: 1.0-5.53), separation of sick birds (AOR: 3.04; 95% CI: 1.34-6.92), disposal of waste/dead birds (AOR: 3.16; 95% CI: 1.41-7.05), cleaning agent (AOR: 5.99; 95% CI: 2.26-15.82), access of dogs (AOR: 2.52; 95% CI: 1.12-5.7), wild birds observed on site (AOR: 2.31; 95% CI: 1.01-5.3). The study further revealed a substantial prevalence of AIV with H5 and H9 subtypes in peri-urban and rural LBMs. The inadequate biosecurity measures at poultry stalls in Bangladesh increase the risk of AIV transmission from poultry to humans. To prevent the spread of AIV to humans and wild birds, we suggest implementing regular surveillance at live bird markets and enhancing biosecurity practices in peri-urban and rural areas in Bangladesh.

SARS-CoV-2 antigen detection by saliva; an alternative to nasopharyngeal specimen: A cross-sectional study.

Background and Aims: Saliva samples are less invasive and more convenient for patients than naso- and/or oropharynx swabs (NOS). However, there is no US Food and Drug Administration-approved severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rapid antigen test kit, which can be useful in a prolonged pandemic to reduce transmission by allowing suspected individuals to self-sampling. We evaluated the performances of High sensitive AQ+ Rapid SARS-CoV-2 Antigen Test (AQ+ kit) using nasopharyngeal swabs (NPs) and saliva specimens from the same patients in laboratory conditions. Methods: The real-time reverse transcription-polymerase chain reaction (rRT-PCR) test result was used for screening the inrolled individuals and compared as the gold standard. NP and saliva samples were collected from 100 rRT-PCR positives and 100 negative individuals and tested with an AQ+ kit. Results: The AQ+ kit showed good performances in both NP and saliva samples with an overall accuracy of 98.5% and 94.0%, and sensitivity of 97.0% and 88.0%, respectively. In both cases, specificity was 100%. AQ+ kit performance with saliva was in the range of the World Health Organization recommended value. Conclusion: xOur findings indicate that the saliva specimen can be used as an alternative and less invasive to NPs for quick and reliable SARS-CoV-2 antigen detection.

Culture-Independent Workflow for Nanopore MinION-Based Sequencing of Influenza A Virus.

Whole-genome sequencing (WGS) of influenza A virus (IAV) is crucial for identifying diverse subtypes and newly evolved variants and for selecting vaccine strains. In developing countries, where facilities are often inadequate, WGS is challenging to perform using conventional next-generation sequencers. In this study, we established a culture-independent, high-throughput native barcode amplicon sequencing workflow that can sequence all influenza subtypes directly from a clinical specimen. All segments of IAV in 19 clinical specimens, irrespective of their subtypes, were amplified simultaneously using a two-step reverse transcriptase PCR (RT-PCR) system. First, the library was prepared using the ligation sequencing kit, barcoded individually using the native barcodes, and sequenced on the MinION MK 1C platform with real-time base-calling. Then, subsequent data analyses were performed with the appropriate tools. WGS of 19 IAV-positive clinical samples was carried out successfully with 100% coverage and 3,975-fold mean coverage for all segments. This easy-to-install and low-cost capacity-building protocol took only 24 h complete from extracting RNA to obtaining finished sequences. Overall, we developed a high-throughput portable sequencing workflow ideal for resource-limited clinical settings, aiding in real-time surveillance, outbreak investigation, and the detection of emerging viruses and genetic reassortment events. However, further evaluation is required to compare its accuracy with other high-throughput sequencing technologies to validate the widespread application of these findings, including WGS from environmental samples. IMPORTANCE The Nanopore MinION-based influenza sequencing approach we are proposing makes it possible to sequence the influenza A virus, irrespective of its diverse serotypes, directly from clinical and environmental swab samples, so that we are not limited to virus culture. This third-generation, portable, multiplexing, and real-time sequencing strategy is highly convenient for local sequencing, particularly in low- and middle-income countries like Bangladesh. Furthermore, the cost-efficient sequencing method could provide new opportunities to respond to the early phase of an influenza pandemic and enable the timely detection of the emerging subtypes in clinical samples. Here, we meticulously described the entire process that might help the researcher who will follow this methodology in the future. Our findings suggest that this proposed method is ideal for clinical and academic settings and will aid in real-time surveillance and in the detection of potential outbreak agents and newly evolved viruses.

Nasal swab as an alternative specimen for the detection of severe acute respiratory syndrome coronavirus 2.

Background and Aims: The coronavirus disease 2019 (COVID-19) has brought serious threats to public health worldwide. Nasopharyngeal, nasal swabs, and saliva specimens are used to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, limited data are available on the performance of less invasive nasal swab for testing COVID-19. This study aimed to compare the diagnostic performance of nasal swabs with nasopharyngeal swabs using real-time reverse transcription polymerase chain reaction (RT-PCR) considering viral load, onset of symptoms, and disease severity. Methods: A total of 449 suspected COVIDCOVID-19 individuals were recruited. Both nasopharyngeal and nasal swabs were collected from the same individual. Viral RNA was extracted and tested by real-time RT-PCR. Metadata were collected using structured questionnaire and analyzed by SPSS and MedCalc software. Results: The overall sensitivity of the nasopharyngeal swab was 96.6%, and the nasal swab was 83.4%. The sensitivity of nasal swabs was more than 97.7% for low and moderate C t values. Moreover, the performance of nasal swab was very high (>87%) for hospitalized patients and at the later stage >7 days of onset of symptoms. Conclusion: Less invasive nasal swab sampling with adequate sensitivity can be used as an alternative to nasopharyngeal swabs for the detection of SARS-CoV-2 by real-time RT-PCR.

S-Adenosyl-l-Homocysteine Exhibits Potential Antiviral Activity Against Dengue Virus Serotype-3 (DENV-3) in Bangladesh: A Viroinformatics-Based Approach.

Dengue outbreak is one of the concerning issues in Bangladesh due to the annual outbreak with the alarming number of death and infection. However, there is no effective antiviral drug available to treat dengue-infected patients. This study evaluated and screened antiviral drug candidates against dengue virus serotype 3 (DENV-3) through viroinformatics-based analyses. Since 2017, DENV-3 has been the predominant serotype in Bangladesh. We selected 3 non-structural proteins of DENV-3, named NS3, NS4A, and NS5, as antiviral targets. Protein modeling and validation were performed with VERIFY-3D, Ramachandran plotting, MolProbity, and PROCHECK. We found 4 drug-like compounds from DRUGBANK that can interact with these non-structural proteins of DENV-3. Then, the ADMET profile of these compounds was determined by admetSAR2, and molecular docking was performed with AutoDock, SWISSDOCK, PatchDock, and FireDock. Furthermore, they were subjected to molecular dynamics (MD) simulation study using the DESMOND module of MAESTRO academic version 2021-4 (force field OPLS_2005) to determine their solution's stability in a predefined body environment. Two drug-like compounds named Guanosine-5'-Triphosphate (DB04137) and S-adenosyl-l-homocysteine (DB01752) were found to have an effective binding with these 3 proteins (binding energy > 33.47 KJ/mole). We found NS5 protein was stable and equilibrated in a 100 ns simulation run along with a negligible (<3Å) root-mean-square fluctuation value. The root-mean-square deviation value of the S-adenosyl-l-homocysteine-NS5 complex was less than 3Å, indicating stable binding between them. The global binding energy of S-adenosyl-l-homocysteine with NS5 was -40.52 KJ/mole as ∆G. Moreover, these 2 compounds mentioned above are non-carcinogenic according to their ADMET (chemical absorption, distribution, metabolism, excretion, and toxicity) profile (in silico). These outcomes suggest the suitability of S-adenosyl-l-homocysteine as a potential drug candidate for dengue drug discovery research.