ABSTRACT RNA viruses continue to remain a clear and present threat for potential pandemics due to their rapid evolution. To mitigate their impact, we urgently require antiviral agents that can inhibit multiple families of disease-causing viruses, such as arthropod-borne and respiratory pathogens. Potentiating host antiviral pathways can prevent or limit viral infections before escalating into a major outbreak. Therefore, it is critical to identify broad-spectrum antiviral agents. We have tested a small library of innate immune agonists targeting pathogen recognition receptors, including TLRs, STING, NOD, Dectin and cytosolic DNA or RNA sensors. We observed that TLR3, STING, TLR8 and Dectin-1 ligands inhibited arboviruses, Chikungunya virus (CHIKV), West Nile virus (WNV) and Zika virus, to varying degrees. Cyclic dinucleotide (CDN) STING agonists, such as cAIMP, diABZI, and 2’,3’-cGAMP, and Dectin-1 agonist scleroglucan, demonstrated the most potent, broad-spectrum antiviral function. Comparative transcriptome analysis revealed that CHIKV-infected cells had larger number of differentially expressed genes than of WNV and ZIKV. Furthermore, gene expression analysis showed that cAIMP treatment rescued cells from CHIKV-induced dysregulation of cell repair, immune, and metabolic pathways. In addition, cAIMP provided protection against CHIKV in a CHIKV-arthritis mouse model. Cardioprotective effects of synthetic STING ligands against CHIKV, WNV, SARS-CoV-2 and enterovirus D68 (EV-D68) infections were demonstrated using human cardiomyocytes. Interestingly, the direct-acting antiviral drug remdesivir, a nucleoside analogue, was not effective against CHIKV and WNV, but exhibited potent antiviral effects against SARS-CoV-2, RSV (respiratory syncytial virus), and EV-D68. Our study identifies broad-spectrum antivirals effective against multiple families of pandemic potential RNA viruses, which can be rapidly deployed to prevent or mitigate future pandemics.

Emerging communication technologies have seen the proliferation of misleading claims, untruthful narratives, and conspiracies. To map different kinds of misinformation in today’s media landscape, this study proposes a taxonomy of misinformation varying along two dimensions, falsity level and evidence type. The level of falsity ranges from high (fabricated content) to low (misused content), and the type of evidence can be statistical and/or narrative. Using COVID-19 vaccines as cases, the results from an online experiment showed that misused misinformation was perceived as less false than fabricated misinformation and resulted in higher sharing intentions for the issue of vaccine efficacy. Misinformation with narrative evidence, as compared to that with statistical evidence, was perceived as less false and led to lower verification intentions. These findings can be explained by psychological processes such as counterarguing and narrative engagement. Our taxonomy can help researchers and practitioners develop dedicated misinformation correction and media literacy programs.

Fake news has negative impacts on society. It can sometimes cause the death of a person. In Joypurhat, Bangladesh, a garment worker has committed suicide because of fake news. At midnight, a passenger on a bus in Bangladesh's Naogaon district believed Corona had affected his mother. However, after testing, his Corona report came back negative. So, this incident has also happened based on fake news. With the internet, social media have become the most acclaimed tool for freedom of speech, democracy, truth, and as a source of infotainment. In this study, the researchers have attempted to find out whether social media is informing or misinforming the public with regard to the COVID-19 pandemic, adopting the qualitative method of study. The findings of this study will aid in determining whether social media is disseminating accurate or incorrect information to the public about the COVID-19 outbreak. The findings show that social media generates approximately 100 COVID-19-related fake news stories over the course of 150 days, from March 1 to July 30, 2020. In this research, the results also show that 64.6% of respondents get COVID-19 related information through social media. In this aspect, Facebook plays an important role. About 53.0% of social media users acclaimed that they get COVID-19 related fake information through Facebook. Facebook spreads 63.0% of fake news, and it is the quickest way to spread any fake news in a short period of time. Most of the fake news is a combination of text and video (49.0%). So, social media is a large platform for getting COVID-19 related information. Fake news and rumors are new words related to COVID-19. This study reveals that 87.3% of respondents are familiar with these words, whereas 12.7% were not familiar with them before the COVID-19 era. About 47.6% of respondents never try to verify any rumors or information related to COVID-19. However, there is less research analyzing the circulation of false and evidence-based information during health emergencies. Thus, the present study aims at shedding new light on the type of fake news that circulated on social media around the COVID-19 outbreak in order to analyze how false information was shared.

Abstract This paper is being written at a time when the recent pandemic, namely COVID-19 has shaken the entire world in a manner that has never been seen in modern history. The ecology, socio-economy and weak health systems make Africa an area favorable to the occurrence of various diseases and disease outbreaks. This paper explores forty-eight (48) years of disease outbreaks in the WHO African region of the World Health Organization (WHO). Twenty-five (25) Integrated Disease Surveillance and Response priority diseases were selected, and their outbreaks described and analyzed. Using inferential spatial statistics, spatial clusters at the health district level, specifically hot spots of those outbreaks were produced and analyzed. Population at risk those hot spots were estimated. Results show a consistent report of outbreaks during the selected period with 52 outbreaks on average per year. Poliomyelitis, cholera, yellow fever, meningococcal disease and measles were the most reported epidemics. Democratic Republic of the Congo (DRC) and Nigeria were the countries reporting the highest number of outbreaks (5 on average per year) with the latter country having the highest population at risk (39M people). Despite efforts to limit their number, some disease outbreaks such as malaria, cholera, and measles continue to have a burden in terms of morbidity and mortality, while others such as poliomyelitis, yellow fever and diarrhoeal disease have shown a declining trend and the wild polio virus transmission has been eliminated in the region. Results suggest that concerted public health action may help reduce the occurrences of outbreaks in the region. Results can be used to inform preparedness and prevention activities. Priority public health actions should target DRC and Nigeria, but also identified hot spots and areas with existing risk factors within other countries.

ABSTRACT Vaccines and drugs are two effective medical interventions to mitigate SARS-CoV-2 infection. Three SARS-CoV-2 inhibitors, remdesivir, paxlovid, and molnupiravir, have been approved for treating COVID-19 patients, but more are needed, because each drug has its limitation of usage and SARS-CoV-2 constantly develops drug resistance mutations. In addition, SARS-CoV-2 drugs have the potential to be repurposed to inhibit new human coronaviruses, thus help to prepare for future coronavirus outbreaks. We have screened a library of microbial metabolites to discover new SARS-CoV-2 inhibitors. To facilitate this screening effort, we generated a recombinant SARS-CoV-2 Delta variant carrying the nano luciferase as a reporter for measuring viral infection. Six compounds were found to inhibit SARS-CoV-2 at the half maximal inhibitory concentration (IC50) below 1 μM, including the anthracycline drug aclarubicin that markedly reduced viral RNA-dependent RNA polymerase (RdRp)-mediated gene expression, whereas other anthracyclines inhibited SARS-CoV-2 by activating the expression of interferon and antiviral genes. As the most commonly prescribed anti-cancer drugs, anthracyclines hold the promise of becoming new SARS-CoV-2 inhibitors. IMPORTANCE Microbial metabolites are a rich source of bioactive molecules. The best examples are antibiotics and immunosuppressants that have transformed the practice of modern medicine and saved millions of lives. Recently, some microbial metabolites were reported to have antiviral activity, including the inhibition of Zika virus and Ebola virus. In this study, we discovered several microbial metabolites that effectively inhibit SARS-CoV-2 infection, including anthracyclines that have also been shown to inhibit other viruses including Ebola virus through enhancing interferon responses, which indicates potentially broad antiviral properties of these microbial metabolites and can lead to the discovery of pan-antiviral molecules.

Background Dengue which is endemic in India and has been occurring for decades apparently witnessed a rise in disease burden in 2021 in specific regions of the nation. We aim to explore less studied risk factors of Dengue occurrence and severity in the post-COVID-19 and post-COVID-19 vaccination era. Methods This was an exploratory analysis involving participants from two prior observational studies conducted during the period of Feb 2021-April 2022 in a tertiary hospital in North India. Healthcare workers constituted the majority of study participants. Individuals were stratified into five groups based on COVID-19 infection and timing of vaccination: CovidNoVaccine (CNV), VaccineNoCOVID (VNC), CovidAfterVaccine (CAV), VaccineAfterCOVID (VAC) and NoVaccineNoCovid (NVNC) groups. The occurrence of lab-confirmed Dengue and severe forms of Dengue were the main outcomes of interest. We tried to predict determinants of Dengue occurrence and severity with a particular focus on COVID-19 history and vaccination status. Results A total of 1520 vaccinated individuals and 181 unvaccinated individuals were included. Of these 1701 participants, symptomatic Dengue occurred in 133 (7.8%) and was of ‘severe’ category in 42 (31.6%). Individuals with a history of COVID-19 in 2020 had 2 times higher odds of developing symptomatic Dengue. The VAC group had 3.6, 2- and 1.9 times higher odds of developing Dengue than the NVNC, VNC, and CAV groups. The severity of dengue was not affected by COVID-19 or COVID-19 vaccination. Conclusions COVID-19 may enhance the risk of developing symptomatic dengue. Future research dealing with long COVID should explore the propensity of COVID-19 victims towards symptomatic forms of other viral illnesses. Individuals receiving the COVID-19 vaccine after recovering from COVID-19 particularly seem to be at greater risk of symptomatic dengue and need long-term watchfulness. Possible mechanisms, such as antibody-mediated enhancement or T-cell dysfunction, should be investigated in COVID-19-recovered and vaccinated individuals. Further large-scale, multicentric, robust studies with a better enrolment of unvaccinated people will help understand the interplay of factors involved in COVID-19 and Dengue.

During the 2015/16 Zika virus (ZIKV) epidemic, ZIKV associated neurological diseases were reported in adults, including microcephaly, Guillain-Barre syndrome, myelitis, meningoencephalitis, and fatal encephalitis. However, the mechanisms underlying the neuropathogenesis of ZIKV infection are not yet fully understood. In this study, we used an adult ZIKV-infection mouse model ( Ifnar1 −/− ) to investigate the mechanisms underlying neuroinflammation and neuropathogenesis. ZIKV infection induced the expression of proinflammatory cytokines, including IL-1β, IL-6, IFN-γ, and TNF-α, in the brains of Ifnar1 −/− mice. RNA-seq analysis of the infected mouse brain also revealed that genes involved in innate immune responses and cytokine-mediated signaling pathways were significantly upregulated at 6 days post infection. Furthermore, ZIKV infection induced macrophage infiltration and activation, and augmented IL-1β expression, whereas microgliosis was not observed in the brain. Using human monocyte THP-1 cells, we confirmed that ZIKV infection promotes inflammatory cell death and increases IL-1β secretion. In addition, the expression of complement component C3, which is associated with neurodegenerative diseases and known to be upregulated by proinflammatory cytokines, was induced by ZIKV infection through the IL-1β-mediated pathway. An increase in C5a produced by complement activation in the brains of ZIKV-infected mice was also confirmed. Taken together, our results suggest that ZIKV infection of the brain in this animal model augments IL-1β expression in infiltrating macrophages and elicits IL-1β-mediated inflammation, which can lead to the destructive consequences of neuroinflammation. Importance Zika virus (ZIKV) associated neurological impairments are an important global health problem. Our results suggest that ZIKV infection of the mouse brain can induce IL-1β-mediated inflammation and complement activation, contributing to the development of neurological disorders. Thus, our findings reveal a mechanism by which ZIKV induces neuroinflammation in the mouse brain. Although we used adult type I IFN receptor IFNAR knockout ( Ifnar1 −/− ) mice owing to the limited mouse model of ZIKV pathogenesis, our conclusion could contribute to understanding ZIKV associated neurological diseases to develop treatment strategies based on these findings for the patients with ZIKV infection.

Guillain-Barre syndrome (GBS) is a rare autoimmune disease that often manifests as a post-viral complication. However, its association with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is unclear. We present a rare case of GBS secondary to COVID-19 infection complicated by rapidly progressive sensorimotor deterioration resistant to plasma exchange therapy.

Virus infection involves the manipulation of key host cell functions by specialized virulence proteins. The SARS-CoV-2 small accessory proteins ORF3a and ORF7a have been implicated in favoring virus replication and spreading by inhibiting the autophagic flux within the host cell. Here, we apply yeast models to gain insights into the physiological functions of both SARS-CoV-2 small ORFs. ORF3a and ORF7a can be stably overexpressed in yeast cells, producing a decrease in cellular fitness. Both proteins show a distinguishable intracellular localization. ORF3a specifically localizes to the vacuolar membrane, whereas ORF7a targets the endoplasmic reticulum. Overexpression of ORF3a and ORF7a leads to the accumulation of Atg8 specific autophagosomes. However, the underlying mechanism is different for each viral protein as assessed by the quantification of the autophagic degradation of Atg8-GFP fusion proteins, which is inhibited by ORF3a and stimulated by ORF7a. Overexpression of both SARS-CoV-2 ORFs decreases cellular fitness upon starvation conditions, where autophagic processes become essential. These data are in agreement with a model where both small ORFs have synergistic functions in stimulating intracellular autophagosome accumulation, ORF3a by inhibiting autophagosome processing at the vacuole and ORF7a by promoting autophagosome formation at the ER. ORF3a has an additional function in Ca 2+ homeostasis. The overexpression of ORF3a confers calcineurin-dependent Ca 2+ tolerance and activates a Ca 2+ sensitive FKS2-luciferase reporter, suggesting a possible ORF3a-mediated Ca 2+ efflux from the vacuole. Taken together, we show that viral accessory proteins can be functionally investigated in yeast cells and that SARS-CoV-2 ORF3a and ORF7a proteins interfere with autophagosome formation and processing as well as with Ca 2+ homeostasis from distinct cellular targets.

Extracellular vesicles (EVs), produced during viral infections, are of emerging interest in understanding infectious processes and host-pathogen interactions. EVs and exosomes in particular have the natural ability to transport nucleic acids, proteins, and other components of cellular or viral origin. Thus, they participate in intercellular communication, immune responses, infectious and pathophysiological processes. Some viruses are known to hijack the cell production and content of EVs for their benefit. Here, we investigated whether two pathogenic flaviviruses i.e. Zika Virus (ZIKV) and Dengue virus (DENV2) could have an impact on the features of EVs. Analysis of EVs produced by infected cells allowed us to identify that the non-structural protein 1 (NS1), described as a viral toxin, was associated with exosomes. This observation could be confirmed under conditions of overexpression of recombinant NS1 from each flavivirus. Using different isolation methods (i.e. exosome isolation kit, size exclusion chromatography, Polyethylene Glycol enrichment, and ELISA capture), we showed that NS1 was present as a dimer at the surface of excreted exosomes and that this association could occur in the extracellular compartment. This finding could be of major importance in a physiological context. Indeed, this capacity of NS1 to address EVs and its implication in the pathophysiology during Dengue or Zika diseases should be explored. Furthermore, exosomes that have demonstrated a natural capacity to vectorize NS1 could serve as useful tools for vaccine development.

Human adenoviruses are one of the most important pathogens detected in acute respiratory diseases in pediatrics and immunocompromised patients. In 1953, Wallace Rowe described it for the first time in oropharyngeal lymphatic tissue. To date, more than 85 types of HAdV have been described, with different cellular tropisms. They can cause respiratory and gastrointestinal symptoms, even urinary tract inflammation, although most infections are asymptomatic. However, there is a population at risk that can develop serious and even lethal conditions. These viruses have a double-stranded DNA genome, 25-48 kbp, 90 nm in diameter, without a mantle, stable in the environment, and resistant to fat-soluble detergents. Currently the diagnosis is made with lateral flow immunochromatography or molecular biology through a polymerase chain reaction. The objective of this review is to recognize the variability of HAdV, the pandemic potential that a recombinant could present between HAdV-3 and 7 viral types, known to produce aggressive outbreaks in health facilities. The review determined the characteristics of HAdV, from the infection to treatment, vaccine development and the evaluation of the social determinants of health associated with HAdV, guiding the necessary measures for future sanitary control, and preventing disasters such as the SARS-CoV-2 pandemic.

Millions of people are infected by the Dengue and Zika viruses each year, which can result in serious illness, permanent disability or death. There are currently no FDA-approved antivirals for treating infection by these viruses. Galidesivir is an adenosine nucleoside analog which can attenuate flavivirus replication in cell-based and animal models of infection. Galidesivir is converted to the triphosphorylated form by host kinases, and subsequently incorporated into viral RNA by viral RNA-dependent RNA polymerases, leading to the termination of RNA synthesis via an unknown mechanism. Here we report the direct in vitro testing of the effects of Galidesivir triphosphate on RNA synthesis by the polymerases of Dengue-2 and Zika virus. Galidesivir triphosphate was chemically synthesized and inhibition of RNA synthesis followed using a continuous fluorescence-based assay. Galidesivir triphosphate was equipotent against the polymerase activity of Dengue-2 and Zika, with IC 50 values of 42 ± 12 μM and 47 ± 5 μM, respectively. This modest potency in vitro is consistent with results previously obtained in cell-based antiviral assays and suggests that the binding affinity for Galidesivir triphosphate is similar to the natural ATP substrate that it closely mimics. The inhibition assay we have developed will allow the rapid screening of Galidesivir and related compounds against other flavivirus polymerases, and the availability of Galidesivir triphosphate will allow detailed analysis of its mechanism of action. Highlights Galidesivir triphosphate was chemically synthesized. A continuous assay detecting double-stranded RNA formation was optimized for polymerase inhibition studies. Galidesivir triphosphate has moderate potency against DENV2 and ZIKA polymerase activity. The availability of Galidesivir triphosphate will facilitate study of its mechanism of action.

Zika virus (ZIKV) is transmitted to humans by the infectious bite of mosquitoes like Aedes aegypti. After a viremic blood meal, the virus must infect the midgut, disseminate to tissues, and reach the salivary gland to be transmitted to a vertebrate host. Many factors influence the mosquito’s ability to become infected and transmit viruses, such as the mosquito’s genetic diversity, intrinsic antiviral barriers, and midgut microbiota. This study evaluated the patterns of ZIKV infection in Ae. aegypti field populations of a city. The infection rate, disseminated infection rate, viral transmission rate, and transmission efficiency were measured by quantitative PCR at 14 days post-infection. The results showed that all Ae. aegypti populations had individuals susceptible to ZIKV infection and able to transmit the virus. The infection parameters showed the city’s geographical area of origin of the Ae. aegypti influences their vector competence for ZIKV transmission.

Flaviviruses like dengue virus (DENV) and Zika virus (ZIKV) are mosquito-borne viruses that cause febrile, hemorrhagic, and neurological diseases in humans, resulting in 400 million infections annually. Due to their co-circulation in many parts of the world, flaviviruses must replicate in the presence of pre-existing adaptive immune responses targeted at serologically closely related pathogens, which can provide protection or enhance disease. However, the impact of pre-existing cross-reactive immunity as a driver of flavivirus evolution, and subsequently the implications on the emergence of immune escape variants, is poorly understood. Therefore, we investigated how replication in the presence of convalescent dengue serum drives ZIKV evolution. We used an in vitro directed evolution system, passaging ZIKV in the presence of serum from humans previously infected with DENV (anti-DENV) or serum from DENV-naïve patients (control serum). Following five passages in the presence of serum, we performed next-generation sequencing to identify mutations that arose during passaging. We studied two non-synonymous mutations found in the anti-DENV passaged population (E-V355I and NS1-T139A) by generating individual ZIKV mutants and assessing fitness in mammalian cells and live mosquitoes, as well as their sensitivity to antibody neutralization. Both viruses had increased fitness in Vero cells with and without the addition of anti-DENV serum and in human lung epithelial and monocyte cells. In Aedes aegypti mosquitoes—using blood meals with and without anti-DENV serum—the mutant viruses had significantly reduced fitness compared to wild-type ZIKV. These results align with the trade-off hypothesis of constrained mosquito-borne virus evolution. Notably, only the NS1-T139A mutation escaped neutralization, while E-V335I demonstrated enhanced neutralization sensitivity to neutralization by anti-DENV serum, indicating that neutralization escape is not necessary for viruses passaged under cross-reactive immune pressures. Future studies are needed to assess cross-reactive immune selection in humans and relevant animal models or with different flaviviruses.

Malaria is a global public health priority causing over 600,000 deaths annually, mostly young children living in Sub-Saharan Africa. Molecular surveillance can provide key information for malaria control, such as the prevalence and distribution of antimalarial drug resistance. However, genome sequencing capacity in endemic countries can be limited. Here, we have implemented an end-to-end workflow for P. falciparum genomic surveillance in Ghana using Oxford Nanopore Technologies, targeting antimalarial resistance markers and the leading vaccine antigen circumsporozoite protein ( csp ). The workflow was rapid, robust, accurate, affordable and straightforward to implement, and could be deployed using readily collected dried blood spot samples. We found that P. falciparum parasites in Ghana had become largely susceptible to chloroquine, with persistent sulfadoxine-pyrimethamine (SP) resistance, and no evidence of artemisinin resistance. Multiple Single Nucleotide Polymorphism (SNP) differences from the vaccine csp sequence were identified, though their significance is uncertain. This study demonstrates the potential utility and feasibility of malaria genomic surveillance in endemic settings using Nanopore sequencing.

Spondweni virus (SPONV) is the closest known relative of Zika virus (ZIKV). SPONV pathogenesis resembles that of ZIKV in pregnant mice, and both viruses are transmitted by Aedes aegypti mosquitoes. We aimed to develop a translational model to further understand SPONV transmission and pathogenesis. We found that cynomolgus macaques ( Macaca fascicularis ) inoculated with ZIKV or SPONV were susceptible to ZIKV, but resistant to SPONV infection. In contrast, rhesus macaques ( Macaca mulatta ) supported productive infection with both ZIKV and SPONV and developed robust neutralizing antibody responses. Crossover serial challenge in rhesus macaques revealed that SPONV immunity did not protect against ZIKV infection, whereas ZIKV immunity was fully protective against SPONV infection. These findings establish a viable model for future investigation into SPONV pathogenesis, and suggest the risk of SPONV emergence is low in areas with high ZIKV seroprevalence due to one-way cross-protection between ZIKV and SPONV. Teaser Identification of asymmetric immune interactions between Zika and Spondweni viruses in macaque monkeys.

Zika virus (ZIKV) is a mosquito-borne virus that has been associated with adult and neonatal neurological conditions. So far, there is no approved drug or vaccine against ZIKV infection; thus, ZIKV remains a global health threat. Here, we explored the effects of chelerythrine (CTC), a known protein kinase C (PKC) inhibitor, against ZIKV infection in cell culture models to determine its potential as a therapeutic agent for ZIKV infection. We found that CTC protected Vero cells from ZIKV-induced cytopathic effects in a dose-dependent manner. It also reduced the production of ZIKV in Vero and A549 cells. In contrast, other PKC inhibitors failed to protect Vero cells from ZIKV-induced cytopathic effects, indicating PKC-independent mechanisms underlying the effects of CTC on ZIKV. Further investigation suggested that CTC inhibited ZIKV attachment/binding rather than internalization in the host cells. Pretreatment of cell-free ZIKV particles rather than pretreatment of cells with CTC resulted in reduced ZIKV infectivity in vitro , indicating that CTC blocked the attachment/binding of the ZIKV particles to host factors. In silico analyses suggested that these effects are potentially due to the binding of CTC to the ZIKV E protein, which may occlude the interaction of the E protein with attachment factors or receptors on the host cell surface. Overall, our findings suggest that CTC reduces the infectivity of ZIKV particles through PKC- and cell-independent mechanisms. Our findings also support further exploration of CTC as an anti-ZIKV agent.

Background There remains significant uncertainty in the definition of the long COVID disease, its expected clinical course, and its impact on daily functioning. Social media platforms can generate valuable insights into patient-reported health outcomes as the content is produced at high resolution by patients and caregivers, representing experiences that may be unavailable to most clinicians. Objective We aim to determine the validity and effectiveness of advanced NLP approaches built to derive insight into Long COVID-related patient-reported health outcomes from social media platforms. Methodology We use Transformer-based BERT models to extract and normalize long COVID Symptoms and Conditions (SyCo) from English posts on Twitter and Reddit. Furthermore, we estimate the occurrence and co-occurrence of SyCo terms at any point or across time and locations. Finally, we compare the extracted health outcomes with human annotations and highly utilized clinical outcomes grounded in the medical literature. Result Based on our findings, the top three most commonly occurring groups of long COVID symptoms are systemic (such as “fatigue”), neuropsychiatric (such as “anxiety” and “brain fog”), and respiratory (such as “shortness of breath”). Regarding the co-occurring symptoms, the pair of ‘fatigue & headaches’ is most common. In addition, we show that other conditions, such as infection, hair loss, and weight loss, as well as mentions of other diseases, such as flu, cancer, or Lyme disease, are among the top reported terms by social media users. Conclusion The outcome of our social media-derived pipeline is comparable with the outcomes of peer-reviewed articles relevant to long COVID symptoms. Overall, this study provides unique insights into patient-reported health outcomes from long COVID and valuable information about the patient’s journey that can help healthcare providers anticipate future needs.

Here, we utilized the wastewater surveillance tool to monitor the Coronavirus disease 19 (COVID-19) outbreak for the first time in Korea. The sampling campaigns have been done from the wastewater treatment plants (WWTPs) in the capital city of Korea, Seoul, and in the first place of a severe outbreak, the Daegu. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA has been extracted from the collected wastewater influent and primary sewage sludge samples. The results were compared with the COVID-19 cases in the WWTPs served area. In addition, microbial community changes before and after the COVID-19 outbreak and SARS-CoV-2 variants by whole transcriptome sequencing were analyzed.Results showed that the trends in SARS-CoV-2 RNA concentrations in the influent and sludge matched the trends of reported COVID-19 cases, especially sludge showed high-resolution data, which is well-matched when fewer COVID-19 cases (0~250) are reported. We detected the SARS-CoV-2 Beta variant (South Africa, B.1.351) in the wastewater 1 month earlier than the clinical report. In addition, the microbial community was compared before and after the outbreak and found that the Aeromonas bacterial species was dominated (21.2%) among other bacterial species, indicating the possible indirect microbial indicator of the COVID-19 outbreak. Our findings suggest a potential pandemic disease monitoring system via community-level wastewater infrastructure with appropriate control strategies.

Coinfections have a potential role in increased morbidity and mortality rates during pandemics. Our investigation is aimed at evaluating the viral coinfection prevalence in COVID-19 patients. Rapid diagnostic tests are tools with a paramount impact both on improving patient care. Particularly in the case of respiratory infections, it is of great importance to quickly confirm/exclude the involvement of pathogens. The COVID-19 pandemic has been associated with changes in respiratory virus infections worldwide, which have differed between virus types. In this paper, we systematically searched the percentage of coinfection of various respiratory viruses in COVID-19-positive samples. We included patients of all ages, in all settings. The main outcome was the proportion of patients with viral coinfection. By describing the differences in changes between viral species across different geographies over the course of the COVID-19 pandemic, we may better understand the complex factors involved in the community cocirculation of respiratory viruses.

Zika virus (ZIKV) is a flavivirus, and ZIKV infections in the past 15 years have been linked to Guillain-Barre syndrome and severe complications during pregnancy associated with congenital Zika syndrome. There are no approved therapies or vaccines for ZIKV. In recent years, advances in structure-based drug design methodologies have accelerated drug development pipelines for identifying promising inhibitory compounds against viral diseases. Among ZIKV proteins, NS2B-NS3 protease is an attractive target for antiviral drug development due to its vital role in the proteolytic processing of the single polyprotein. To find potential inhibitors against ZIKV, we used molecular docking at the NS2B-NS3 protease active site as a virtual screening approach with small molecules diverse scaffold-based library with rigorous druglikeness filters. The top-hit compounds with stable molecular dynamics trajectories were then subjected to in-vitro efficacy testing against ZIKV. In docking and molecular dynamics simulation studies, compound F1289-0194 showed stable binding to the NS2B-NS3 protease active site. Furthermore, viral load assays, immunofluorescence, and plaque reduction assays demonstrated that compound F1289-0194 significantly reduced ZIKV load and replication in Vero cells while maintaining cellular integrity. Thus, the compound F1289-0194 merits further investigation as a novel inhibitor against ZIKV replication.

NS2B protein of the Zika virus acts as a co-factor for NS3 protease where only the cytosolic domain of NS2B is sufficient for the protease activity. At the same time, NS2B also involves in remodeling the NS3 protease structure. In isolation, we previously proved the NS2B cytosolic domain (residues 49-95) as a disordered type peptide conformation. Further, this study investigated the overall dynamics of NS2B full-length protein. Our Alphafold2 structure modeling system revealed surprising similarities between selected flavivirus NS2B proteins. This similarity reflects that the NS2B protein across flavivirus is conserved fold-wise. The MD simulation of Zika virus NS2B full-length protein shows that the cytosolic domain as a part of full-length protein is a disorder region supporting our previous experimental finding, which suggests the disordered nature of the cytosolic domain in isolation. Since the cytosolic domain of NS2B is essential for protease activity, we have also investigated the folding and dynamics of the NS2B cytosolic domain (residues 49-95) that shows the disorder to alpha helix transition in TFE. On the other hand, in the presence of SDS, macromolecular crowder like ficoll and PEG do not induce secondary structural change. This dynamics study could have implications for some unknown folds of the NS2B protein.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes significant morbidity and mortality worldwide, seriously impacting not only human health but also the global economy. Furthermore, over 1 million cases of newly emerging or re-emerging viral infections, specifically dengue virus (DENV), are known to occur annually. Because no virus-specific and fully effective treatments against these and many other viruses have been approved, they continue to be responsible for large-scale epidemics and global pandemics. Thus, there is an urgent need for novel, effective therapeutic agents. Here, we identified 2-thiouridine (s2U) as a broad-spectrum antiviral nucleoside analogue that exhibited antiviral activity against SARS-CoV-2 and its variants of concern, including the Delta and Omicron variants, as well as a number of other positive-sense single-stranded RNA (ssRNA+) viruses, including DENV. s2U inhibits RNA synthesis catalyzed by viral RNA-dependent RNA polymerase, thereby reducing viral RNA replication, which improved the survival rate of mice infected with SARS-CoV-2 or DENV in our animal models. Our findings demonstrate that s2U is a potential broad-spectrum antiviral agent not only against SARS-CoV-2 and DENV but other ssRNA+ viruses.

Background The time-varying reproduction number (R t ) is an important measure of epidemic transmissibility; it can directly inform policy decisions and the optimisation of control measures. EpiEstim is a widely used software tool that uses case incidence and the serial interval (SI, time between symptoms in a case and their infector) to estimate R t in real-time. The incidence and the SI distribution must be provided at the same temporal resolution, which limits the applicability of EpiEstim and other similar methods, e.g. for pathogens with a mean SI shorter than the frequency of incidence reporting. Methods We use an expectation-maximisation algorithm to reconstruct daily incidence from temporally aggregated data, from which R t can then be estimated using EpiEstim. We assess the validity of our method using an extensive simulation study and apply it to COVID-19 and influenza data. The method is implemented in the opensource R package EpiEstim. Findings For all datasets, the influence of intra-weekly variability in reported data was mitigated by using aggregated weekly data. R t estimated on weekly sliding windows using incidence reconstructed from weekly data was strongly correlated with estimates from the original daily data. The simulation study revealed that R t was well estimated in all scenarios and regardless of the temporal aggregation of the data. In the presence of weekend effects, R t estimates from reconstructed data were more successful at recovering the true value of R t than those obtained from reported daily data. Interpretation R t can be successfully recovered from aggregated data, and estimation accuracy can even be improved by smoothing out administrative noise in the reported data. Funding MRC doctoral training partnership, MRC centre for global infectious disease analysis, the NIHR HPRU in Modelling and Health Economics, and the Academy of Medical Sciences Springboard, funded by the AMS, Wellcome Trust, BEIS, the British Heart Foundation and Diabetes UK.

This paper presents a spectral approach to the uncertainty management in epidemic models through the formulation of chance-constrained stochastic optimal control problems. Specifically, a statistical moment-based polynomial expansion is used to calculate surrogate models of the stochastic state variables of the problem that allow for the efficient computation of their main statistics as well as their marginal and joint probability density functions at each time instant, which enable the uncertainty management in the epidemic model. Moreover, the surrogate models are employed to perform the corresponding sensitivity and risk analyses. The proposed methodology provides the designers of the optimal control policies with the capability to increase the predictability of the outcomes by adding suitable chance constraints to the epidemic model and formulating a proper cost functional. The chance-constrained optimal control of a COVID-19 epidemic model is considered in order to illustrate the practical application of the proposed methodology.