Background: The WHO Unity Studies initiative supports countries, especially low- and middle-income countries (LMICs), to conduct seroepidemiologic studies for rapidly informing responses to the COVID-19 pandemic. Ten generic study protocols were developed which standardized epidemiologic and laboratory methods. WHO provided technical support, serological assays, and funding for study implementation. An external evaluation was conducted to assess 1) the usefulness of study findings in guiding response strategies, 2) management and support to conduct studies, and 3) capacity built from engagement with the initiative. Methods: . The evaluation focused on the three most used protocols, first few cases, household transmission, and population-based serosurvey, 66% of 339 studies tracked by WHO. All 158 principal investigators (PIs) with contact information were surveyed online. Interviews were conducted with 15 PIs (randomly selected within WHO regions), 14 WHO Unity focal points at country, regional and global levels, 12 WHO global-level stakeholders, and eight external partners. Interviews were coded in MAXQDA™, synthesized into findings, and cross-verified by a second reviewer. Results: . Among 69 (44%) survey respondents, 61 (88%) were from LMICs. Ninety-five percent gave positive feedback on technical support, 87% reported findings contributed to COVID-19 understanding, 65% for guiding public health and social measures, and 58% for guiding vaccination policy. Survey and interview groups responses showed that the main technical barriers to using study findings were study quality, variations in study methods (challenge for meta-analysis), completeness of reporting study details, and clarity of communicating findings. Untimely study findings was another barrier, caused by delays in ethical clearance, receipt of serological assays, and approval to share findings. There was strong agreement that the initiative created equitable research opportunities, connected expertise, and facilitated study implementation. Around 90% of respondents agreed the initiative should continue in the future. Conclusions: . The Unity Studies initiative created a highly valued community of practice, contributed to study implementation and research equity, and serves as valuable framework for future pandemics. To strengthen this platform, WHO should establish emergency-mode procedures to facilitate timeliness and continue to build capacity to rapidly conduct high-quality studies and communicate findings in a format friendly to decision-makers.

ABSTRACT Aedes aegypti vectors the pathogens that cause dengue, yellow fever, Zika virus, and chikungunya, and is a serious threat to public health in tropical regions. Decades of work has illuminated many aspects of Ae. aegypti ’s biology and global population structure, and has identified insecticide resistance genes; however, the size and repetitive nature of the Ae. aegypti genome have limited our ability to detect positive selection in this mosquito. Combining new whole genome sequences from Colombia with publicly available data from Africa and the Americas, we identify multiple strong candidate selective sweeps in Ae. aegypti , many of which overlap genes linked to or implicated in insecticide resistance. We examine the voltage-gated sodium channel gene in three American cohorts, and find evidence for successive selective sweeps in Colombia. The most recent sweep encompasses an intermediate-frequency haplotype containing four candidate insecticide resistance mutations that are in near-perfect linkage disequilibrium with one another in the Colombian sample. We hypothesize that this haplotype may continue to rapidly increase in frequency and perhaps spread geographically in the coming years. These results extend our knowledge of how insecticide resistance has evolved in this species, and add to a growing body of evidence suggesting Ae. aegypti has an extensive genomic capacity to rapidly adapt to insecticide-based vector control.

The mosquito Aedes aegypti is the vector of a number of medically-important viruses, including dengue virus, yellow virus, chikungunya virus, and Zika virus, and as such vector control is a key approach to managing the diseases they cause. Understanding the impact of vector control on these diseases is aided by first understanding its impact on Ae. aegypti population dynamics. A number of detail-rich models have been developed to couple the dynamics of the immature and adult stages of Ae. aegypti . The numerous assumptions of these models enable them to realistically characterize impacts of mosquito control, but they also constrain the ability of such models to reproduce empirical patterns that do not conform to the models’ behavior. In contrast, statistical models afford sufficient flexibility to extract nuanced signals from noisy data, yet they have limited ability to make predictions about impacts of mosquito control on disease caused by pathogens that the mosquitoes transmit without extensive data on mosquitoes and disease. Here, we demonstrate how the differing strengths of mechanistic realism and statistical flexibility can be fused into a single model. Our analysis utilizes data from 176,352 household-level Ae. aegypti aspirator collections conducted during 1999-2011 in Iquitos, Peru. The key step in our approach is to calibrate a single parameter of the model to spatio-temporal abundance patterns predicted by a generalized additive model (GAM). In effect, this calibrated parameter absorbs residual variation in the abundance time-series not captured by other features of the mechanistic model. We then used this calibrated parameter and the literature-derived parameters in the agent-based model to explore Ae. aegypti population dynamics and the impact of insecticide spraying to kill adult mosquitoes. The baseline abundance predicted by the agent-based model closely matched that predicted by the GAM. Following spraying, the agent-based model predicted that mosquito abundance rebounds within about two months, commensurate with recent experimental data from Iquitos. Our approach was able to accurately reproduce abundance patterns in Iquitos and produce a realistic response to adulticide spraying, while retaining sufficient flexibility to be applied across a range of settings. Author Summary The mosquito Aedes aegypti is the vector for a number of the most medically important viruses, including dengue, Zika, chikungunya, and yellow fever. Understanding the population dynamics of this mosquito, and how those dynamics might respond to vector control interventions, is critical to inform the deployment of such interventions. One of the best ways to gain this understanding is through modeling of population dynamics. Such models are often categorizes as either statistical or dynamical, and each of these approaches has advantages and disadvantages – for instance, statistical models may more closely match patterns observed in empirical data, while dynamical models are better able to predict the impact of counterfactual situations such as vector control strategies. In this paper, we present an approach which fuses these two approaches in order to gain the advantages of both: it fits empirical data on Aedes aegypti population dynamics well, while producing realistic responses to vector control interventions. Our approach has the potential to inform and improve the deployment of vector control interventions, and, when used in concert with and epidemiological model, to help reduce the burden of the diseases spread by such vectors.

Plus-strand RNA viruses are the largest group of viruses. Many are human pathogens that inflict a socio-economic burden. Interestingly, plus-strand RNA viruses share remarkable similarities in their replication. A hallmark of plus-strand RNA viruses is the remodeling of intracellular membranes to establish replication organelles (so-called “replication factories”), which provide a protected environment for the replicase complex, consisting of the viral genome and proteins necessary for viral RNA synthesis. In the current study, we investigate pan-viral similarities and virus-specific differences in the life cycle of this highly relevant group of viruses. We first measured the kinetics of viral RNA, viral protein, and infectious virus particle production of hepatitis C virus (HCV), dengue virus (DENV), and coxsackievirus B3 (CVB3) in the immuno-compromised Huh7 cell line and thus without perturbations by an intrinsic immune response. Based on these measurements, we developed a detailed mathematical model of the replication of HCV, DENV, and CVB3 and show that only small virus-specific changes in the model were necessary to describe the in vitro dynamics of the different viruses. Our model correctly predicted virus-specific mechanisms such as host cell translation shut off and different kinetics of replication organelles. Further, our model suggests that the ability to suppress or shut down host cell mRNA translation may be a key factor for in vitro replication efficiency which may determine acute self-limited or chronic infection. We further analyzed potential broad-spectrum antiviral treatment options in silico and found that targeting viral RNA translation, especially polyprotein cleavage, and viral RNA synthesis may be the most promising drug targets for all plus-strand RNA viruses. Moreover, we found that targeting only the formation of replicase complexes did not stop the viral replication in vitro early in infection, while inhibiting intracellular trafficking processes may even lead to amplified viral growth. Author summary Plus-strand RNA viruses comprise a large group of related and medically relevant viruses. The current global pandemic of COVID-19 caused by the SARS-coronavirus-2 as well as the constant spread of diseases such as dengue and chikungunya fever show the necessity of a comprehensive and precise analysis of plus-strand RNA virus infections. Plus-strand RNA viruses share similarities in their life cycle. To understand their within-host replication strategies, we developed a mathematical model that studies pan-viral similarities and virus-specific differences of three plus-strand RNA viruses, namely hepatitis C, dengue, and coxsackievirus. By fitting our model to in vitro data, we found that only small virus-specific variations in the model were required to describe the dynamics of all three viruses. Furthermore, our model predicted that ribosomes involved in viral RNA translation seem to be a key player in plus-strand RNA replication efficiency, which may determine acute or chronic infection outcome. Furthermore, our in-silico drug treatment analysis suggests that targeting viral proteases involved in polyprotein cleavage, in combination with viral RNA replication, may represent promising drug targets with broad-spectrum antiviral activity.

COVID-19 is a respiratory disease affecting multiple organs including the central nervous system (CNS), with a characteristic loss of smell and taste. Although frequently reported, the neurological symptoms remain enigmatic. There is no consensus on the extent of CNS infection. Here, we derived human induced pluripotent stem cells (hiPSC) into neural progenitor cells (NPCs) and cortical excitatory neurons to study their permissiveness to SARS-CoV-2 infection. Flow cytometry and western blot analysis indicated that NPCs and neurons do not express detectable levels of the SARS-CoV-2 receptor ACE2. We thus generated cells expressing ACE2 by lentiviral transduction to analyze in a controlled manner the properties of SARS-CoV-2 infection relative to ACE2 expression. Sensitivity of parental and ACE2 expressing cells was assessed with GFP- or luciferase-carrying pseudoviruses and with authentic SARS-CoV-2 Wuhan, D614G, Alpha or Delta variants. SARS-CoV-2 replication was assessed by microscopy, RT-qPCR and infectivity assays. Pseudoviruses infected only cells overexpressing ACE2. Neurons and NPCs were unable to efficiently replicate SARS-CoV-2, whereas ACE2 overexpressing neurons were highly sensitive to productive infection. Altogether, our results indicate that primary NPCs and cortical neurons remain poorly permissive to SARS-CoV-2 across the variants’ spectrum, in the absence of ACE2 expression.

Our primary objectives were a) to determine the need for, and the availability of point-of-care testing (POCT) for infectious diseases and b) to recommend point-of-care testing strategies and spatial care paths (SCPs) that enhance public health preparedness in regional districts of Thua Thien Hue Province (TTHP), Central Vietnam, where we conducted field surveys. Medical professionals in 7 community health centers (CHCs), 7 district hospitals (DHs) and 1 provincial hospital (PH) participated. Survey questions (English and Vietnamese) determined the status of diagnostic testing capabilities for infectious diseases and other acute medical challenges in TTHP. Infectious disease testing was limited: 6 of 7 CHCs (86%) lacked infectious disease tests. One CHC (14%, 1/7) had two forms of diagnostic tests available for the detection of Malaria. All CHCs lacked adequate microbiology laboratories. District hospitals had few diagnostic tests for infectious diseases (Tuberculosis, Syphilis), blood culture (29%, 2/7), and pathogen culture (57%, 4/7) available. The PH had broader diagnostic testing capabilities but lacked preparedness for highly infectious disease threats (e.g., Ebola, MERS-CoV, SARS, Zika, and Monkeypox). All sites reported having COVID-19 rapid antigen tests; COVID-19 RT-PCR tests were limited to higher tier hospitals. We conclude that infectious disease diagnostic testing should be improved and POC tests must be supplied near patients’ homes and in primary care settings for the early detection of infected individuals and mitigation of the spread of new COVID-19 variants and other highly infectious diseases.

This paper presents the findings of an exploratory study on the continuously generating Big Data on Twitter related to the sharing of information, news, views, opinions, ideas, feedback, and experiences about the COVID-19 pandemic, with a specific focus on the Omicron variant, which is the globally dominant variant of SARS-CoV-2 at this time. A total of 12028 tweets about the Omicron variant were studied, and the specific characteristics of tweets that were analyzed include - sentiment, language, source, type, and embedded URLs. The findings of this study are manifold. First, from sentiment analysis, it was observed that 50.5% of tweets had a neutral emotion. The other emotions - bad, good, terrible, and great were found in 15.6%, 14.0%, 12.5%, and 7.5% of the tweets, respectively. Second, the findings of language interpretation showed that 65.9% of the tweets were posted in English. It was followed by Spanish, French, Italian, and other languages. Third, the findings from source tracking showed that Twitter for Android was associated with 35.2% of tweets. It was followed by Twitter Web App, Twitter for iPhone, Twitter for iPad, and other sources. Fourth, studying the type of tweets revealed that retweets accounted for 60.8% of the tweets, it was followed by original tweets and replies that accounted for 19.8% and 19.4% of the tweets, respectively. Fifth, in terms of embedded URL analysis, the most common domain embedded in the tweets was found to be twitter.com, which was followed by biorxiv.org, nature.com, and other domains. Finally, to support similar research in this field, we have developed a Twitter dataset that comprises more than 500,000 tweets about the SARS-CoV-2 omicron variant since the first detected case of this variant on November 24, 2021.

Non-human primate (NHP)-based model systems are important for biomedical research, due to the close phylogenetic relationship and physiologic similarities of NHP and humans. In infection research, NHP models are used to model various viral diseases including Ebola, influenza, AIDS and Zika. However, only a small number of NHP cell lines are available and generation of additional cell lines could help to refine these models. We immortalized rhesus macaque kidney cells by lentiviral transduction with a vector encoding telomerase reverse transcriptase (TERT). Expression of kidney markers on these cells was analyzed by flow cytometry and quantitative real-time PCR (qRT-PCR) was employed to determine functionality of the interferon (IFN) system. Finally, we assessed susceptibility and permissiveness for virus infection by the use of pseudotyped particles and replication-competent viruses. We report the generation of three TERT-immortalized cell lines derived from rhesus macaque kidney. The cell lines expressed the podocyte marker podoplanin and expressed MX1 upon stimulation with IFN or viral infection. Further, the cell lines were susceptible to entry driven by the glycoproteins of vesicular stomatitis virus, influenza A virus, Ebola virus, Nipah virus and Lassa virus. Finally, these cells supported growth of Zika virus (ZIKV) and the primate simplexviruses Cercopithecine alphaherpesvirus 2 (CeHV2) and Papiine alphaherpesvirus 2 (PaHV2). We developed IFN-responsive rhesus macaque kidney cell lines that allowed entry driven by diverse viral glycoproteins and were permissive to infection with Zika virus and primate simplexviruses. These cell lines will be useful for efforts to analyze viral infections of the kidney in macaque models.

Since the outbreak of COVID-19 on 31 December 2019, different public health systems have been grappling with how to address the spread of the virus. During the cholera outbreak and the Covid-19 pandemic in Zambia, values such as equity, partnership and collaboration have been recognized as central to resilience and an effective response to the pandemic. In this study we identify lessons that can be used for addressing the COVID-19 pandemic from partnership approach used in confronting the cholera outbreak of 2017-2018 in Zambia, Chipata Compound. Method Data was collected using a qualitative approach; 26 interviews were conducted with Public Health Professionals and community Leaders. Document reviews from government institutions and non-government institutions were also conducted. The Bergen model of Collaborative Functioning was used to guide the analysis of data. Results A top-down approach was observed to be important in addressing cholera but there was a need to improve a bottom-up approach. Synergistic results, avoidance of duplication, Oral cholera vaccination intervention and collaborative capacity building. Challenges in the partnership collaboration included inadequate resources, poor communication, poor coordination, lack of clear shared vision, reactive response, poor involvement of the community, hegemonic powers and mistrust and resentment Conclusion From the experience of cholera outbreaks, partnerships are vital in addressing pandemics. Based on the lessons from the cholera outbreaks, we note that there is a need to improve collaboration in partnership if COVID-19 and cholera are to be effectively addressed.

Climate change poses enormous risks to human health in the emergence of new pandemics and infectious diseases as well as the worsening of already existing ones. COVID-19 is just the latest example of climate change-induced zoonoses and we are likely to see many more viruses jump from animals or vectors to humans as well as more water- food- and airborne diseases if we don’t urgently reduce greenhouse gas emissions, stop deforestation, land degradation, the decline in biodiversity, and the exploitation of animals and natural resources, and closely monitor the melting of permafrost, cattle burial grounds, and anthrax infection in the Arctic. To maximize our ability to prevent future deadly pandemics like COVID-19, it is critical that governments, scientists, researchers, and policy analysts around the globe integrate health, environmental and animal welfare research, policy, and decision-making and no longer treat them as separate unrelated fields.

Background: Outbreaks of dengue fever caused by viruses transmitted by Aedes aegypti mosquitoes are repeatedly reported in West Africa. Burkina Faso has experienced major dengue outbreaks most notably in 2016 and 2017, with 80% of cases recorded in Ouagadougou (Central health region). In order to better understand the ecology of this vector to provide information for control, a study on the productivity of Aedes breeding sites measured by abundance of immature stages, and resultant adult body size, and breeding site characteristics was undertaken in three Health Districts (Baskuy, Bogodogo, and Nongremassom) of the city of Ouagadougou. Methods Adult mosquitoes were collected indoors and outdoors in 643 households during the rainy season from -month- to -month- 2018. Water containers were systematically recorded and prospected for larval presence or absence. Breeding container characteristics including size, temperature, pH and conductivity were recorded as well as water volume. Traditional Stegomyia indices were calculated; generalised mixed models were fitted to larval and pupal densities, and the contribution of each covariate to the model evaluated by the Z-value and associated P-value. Results A total of 1,061 breeding sites were inspected, of which 760 were positive for Aedes aegypti immature stages. Tires, medium (Buckets/Cans/Pots) and large (Bin/barrel/drums) containers were the most frequent, positive and productive larval habitats in each health district. Of the Stegomyia indices, the Breteau, house and container indices exceeded WHO dengue risk thresholds. Generalised Linear Mixed Models (GLMMs) showed that larval and pupal abundances were each associated with container type, physicochemical characteristics and collection month, but with significant differences among container types among health districts. Aedes aegypti body size was positively associated with containers type, diameter, electrical conductivity; and negatively associated with pH, temperature, and a containers’ level of exposure to sunshine. Conclusion We provide data on putative determinants of Aedes aegypti immature habitat productivity, which are useful to better understand Aedes aegypti proliferation. The results suggest that targeting the most productive containers could contribute to dengue vector control strategies in Burkina Faso.

The Rapid outbreak of SARS-Cov created total havoc among the people, which led to an epidemic. People around the world started to believe in the information that passes through the internet without any verification, which is the main cause of an infodemic. Some unverified news may have the capability to harm the people in general. To be more aware of the misinformation or unverified news we will be approaching Natural language processing methodologies that use a neural network model, a language model which is trained in advance i.e., BERT. Bidirectional capabilities of this language model BERT help to detect the hidden message from the piece of information. We will be using a benchmarked dataset of covid-19 which is available publicly. Via computing the linguistic conceptual model between both the claimed and factual information obtained out of a carefully selected COVID-19 datasets, this model checks the claim is true or not and it pulled the accuracy of 89%.

Competent arbovirus vectors are found in the culicid mosquito fauna of south-west Indian Ocean (SWIO) islands. In La Réunion Island, Aedes albopictus and Aedes aegypti mosquitoes are known vectors of dengue and chikungunya viruses. Culex quinquefasciatus is a potential vector of Rift Valley fever and West Nile viruses. To prepare a vector-control field trial against Ae. aegypti , this study aimed at identifying the best baiting scheme to catch adult Ae. aegypti , using BG-Sentinel™ traps (Biogents). It was implemented in two sites in southern La Réunion Island. Catches of Ae. albopictus and Cx. quinquefasciatus mosquitoes were also recorded. A Latin square design was used to estimate the detection probability and the apparent daily density - according to the BG-sentinel trap baiting scheme: none, carbon dioxide (CO 2 ), a commercial attractant - BG-Lure™ (Biogents), or both. The use of CO 2 alone was associated with a higher detection probability for Ae. aegypti and Cx. quinquefasciatus mosquitoes, as well as a large increase in their apparent density. Traps with BG-Lure - alone or in combination with CO 2 , did not improve the detection probability of Ae. aegypti and Cx. quinquefasciatus mosquitoes. The same result was found for male Ae. albopictus . For females, baiting BG traps with CO 2 or BG-Lure had no significant effect. The same apparent densities were found for Ae. aegypti and Ae. albopictus mosquitoes in both study sites - where Ae. aegypti mosquitoes were found at very low densities during previous surveys.

Diseases caused by new viruses costs thousands if not millions of human lives and trillions of dollars in damage to the global economy. Despite the rapid development of vaccines for SARS-CoV-2, the lack of small molecule antiviral drugs that work against multiple viral families (broad-spectrum antivirals; BSAs) has left the entire world’s human population vulnerable to the infection between the beginning of the outbreak and the widespread availability of vaccines. Developing BSAs is an attractive, yet challenging, approach that could prevent the next, inevitable, viral outbreak from becoming a global catastrophe. To explore whether historical medicinal chemistry efforts suggest the possibility of discovering novel BSAs, we (i) identified, collected, curated, and integrated all chemical bioactivity data available in ChEMBL for molecules tested in respective assays for 13 emerging viruses that, based on published literature, hold the greatest potential threat to global human health; (ii) identified and solved the challenges related to data annotation accuracy including assay description ambiguity, missing cell or target information, and incorrect BioAssay Ontology (BAO) annotations; (iii) developed a highly curated and thoroughly annotated database of compounds tested in both phenotypic (21,392 entries) and target-based (11,123 entries) assays for these viruses; and (iv) identified a subset of compounds showing BSA activity. For the latter task, we eliminated inconclusive and annotated duplicative entries by checking the concordance between multiple assay results and identified eight compounds active against 3-4 viruses from the phenotypic data, 16 compounds active against two viruses from the target-based data, and 35 compounds active in at least one phenotypic and one target-based assay. The pilot version of our SMACC (Small Molecule Antiviral Compound Collection) database contains over 32,500 entries for 13 viruses. Our analysis indicates that previous research yielded very small number of BSA compounds. We posit that focused and coordinated efforts strategically targeting the discovery of such agents must be established and maintained going forward. The SMACC database publicly available at https://smacc.mml.unc.edu may serve as a reference for virologists and medicinal chemists working on the development of novel BSA agents in preparation for future viral outbreaks.

Since the beginning of worldwide vaccination against coronavirus disease 2019 (COVID-19), studies have reported a possible association between vaccination and Guillain-Barré syndrome (GBS). In this regard, we conducted a systematic review assessing different demographic, clinical, and neurophysiological aspects of patients with GBS following immunization with COVID-19 vaccines. A comprehensive search of PubMed, Web of Science, Scopus, and Google Scholar was performed. Articles in English between January 2020 and November 2021 were included. Data on demographics, clinical characteristics, vaccines information, treatment approaches, and outcomes were extracted. The data of a total of 88 patients out of 41 studies was included. The mean age of patients was 58.7 ± 16.6 years and 55 cases (62.5%) were male. AstraZeneca was the most-reported vaccine associated with GBS with 52 cases (59.1%) followed by Pfizer with 20 cases (22.7%). GBS occurred after the first dose of vaccination in 70 cases (79.5%). The mean time interval between vaccination and symptom onset was 13.9 ± 7.4 days. Limb weakness (47.7%), sensory disturbance (38.6%), and facial weakness (27.3%) were the most common reported symptoms, respectively. Albuminocytologic dissociation was seen in 65% of patients who underwent lumbar puncture (n = 65). Acute inflammatory demyelinating polyradiculopathy was the most common GBS subtype, which was reported in 38 patients (43.2%). While one-fifth of patients underwent intubation (n = 17), a favorable outcome was achieved in the majority of subjects (n = 46, 63%). Overall, a small rise in GBS incidence, following various COVID-19 vaccines, was observed. Notably, 85% of affected individuals experienced at least a partial recovery.

Background: Mechanisms underlying acute brain injury in SARS-CoV-2 patients remain poorly understood. A better characterization of such mechanisms remains essential to preventing long-term neurological sequelae. Our present aim was to study a panel of biomarkers of neuroinflammation and neurodegeneration in the cerebrospinal fluid (CSF) of NeuroCOVID patients. Methods: : We retrospectively collected clinical and CSF biomarkers data from 24 NeuroCOVID adults seen at the University Hospital of Guadeloupe between March and June 2021. Results: : Among 24 NeuroCOVID patients, 71% had encephalopathy and 29% a meningoencephalitis. A number of these patients also experienced de novo movement disorder (33%) or stroke (21%). The CSF analysis revealed intrathecal immunoglobulin synthesis in 54% of NeuroCOVID patients (two with a type 2 pattern and 11 with a type 3) and elevated neopterin levels in 75% of them (median 9.1 nM, IQR 5.6-22.1). CSF neurofilament light chain (NfL) was also increased compared to a control group of non-COVID-19 patients with psychiatric illnesses (2905 ng/L, IQR 1428-7124 versus 1222 ng/L, IQR 1049-1566). Total-tau was elevated in the CSF of 24% of patients, whereas protein 14-3-3, generally undetectable, reached intermediate levels in two patients. Finally, CSF Aß1-42 was reduced in 52.4% of patients (median 536 ng/L, IQR 432-904) with no change in the Aß1-42/Aß1-40 ratio (0.082, IQR 0.060-0.096). Conclusions: : We showed an elevation of CSF biomarkers of neuroinflammation in NeuroCOVID patients and a rise of CSF NfL, evocative of neuronal damage. However, longitudinal studies are needed to determine whether NeuroCOVID could evolve into a chronic neurodegenerative condition.

Background: Some viruses cause outbreaks which require immediate attention. Neutralizing antibodies could be developed for viral outbreak management. However, development of monoclonal antibodies is often long, laborious, and unprofitable. Here we report a Norwegian platform for development of chicken polyclonal neutralizing antibodies with powerful therapeutic potential. Methods: Layers were immunized twice with 14-day interval using purified RBD of SARS-CoV-2. Eggs were harvested 14 days after the second immunization. Polyclonal IgY antibodies were extracted. Binding of anti-RBD IgY to RBD was measured by indirect ELISA. Neutralization capacity of anti-RBD IgYs was measured in Vero-E6 cells infected with SARS-CoV-2-mCherry strain using fluorescence and cell viability assay. In addition, the effect of IgYs on the expression of SARS-CoV-2 and host cytokine genes in lungs of Syrian Golden hamsters was examined using qRT-PCR. Results: Anti-RBD IgYs efficiently bind RBD of S protein of SARS-CoV-2 in situ, neutralize the virus in vitro, and lower viral RNA amplification without significant alteration of virus-mediated immune gene expression in vivo. Conclusions: Altogether, our results indicated that chicken polyclonal IgYs can be attractive targets for pre-clinical and clinical development for rapid management of outbreaks of emerging and re-emerging viruses.

Introduction: Zika virus infection during pregnancy is often associated with the occurrence of numerous neurologic malformations in new-born babies. Usually, the transmission of the Zika virus happens through the bite of an infected mosquito of the Aedes genus but might as well occur through sexual contact or blood transfusions. Currently, there is no approved specific treatment, medication-based prophylaxis or vaccine available against Zika virus infection, thus prevention measures play an important role in combating the spread of this infectious disease. This scoping review aims to collect data about public health programmes in context of the Zika virus epidemic in Latin America that employ the principles of a community-based participatory research. Methods: Three scientific databases (Medline, Cochrane Library and Scopus) were screened for relevant literature and additionally, official websites of health organizations such as WHO, UNICEF, ECDC, CDC and PAHO were included in the search. The review was conducted following the Preferred Reporting Items for Scoping Reviews and Meta-Analysis extension for Scoping Reviews (PRISMA-ScR) checklist. The authors developed a data-charting map to collect relevant information from each publication to analyse the content. Results: Overall, 46 papers were included in the review. Each of the studies contained at least one of the following indicators: actual participation or involvement in a public health intervention, assessment of knowledge or awareness degree and preventative actions, assessment of disease perception or behaviour changes. Key topics were divided into four broad categories: 1) Mosquito vector control initiatives, 2) Contraception and reproductive healthcare, 3) Family support programmes and 4) Assessment of knowledge, perception and barriers. Conclusions: Through engaging local communities, especially vulnerable groups, awareness of risks associated with a Zika virus infection can be raised and enable people to protect themselves. The current work demonstrates that community engagement is an essential strategy to implement preventive measures and improve health-outcomes.

Throughout the current SARS-CoV-2 pandemic, limited diagnostic testing capacity prevented sentinel testing of the population, demonstrating the need for novel testing strategies and infrastructures. Here, we describe the set-up of an alternative testing platform, which allows scalable surveillance testing as an acute pandemic response tool and for pandemic preparedness purposes, exemplified by SARS-CoV-2 diagnostics in an academic environment. The testing strategy involves self-sampling based on gargling saline, pseudonymized sample handling, automated 96-well plate-based RNA extraction, and viral RNA detection using a semi-quantitative multiplexed colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay with an analytical sensitivity comparable to RT-quantitative polymerase chain reaction (RT-qPCR). We provide standard operating procedures and an integrated software solution for all workflows, including sample logistics, LAMP assay analysis by colorimetry or by sequencing (LAMP-seq), and communication of results to participants and the health authorities. Using large sample sets including longitudinal sample series we evaluated factors affecting the viral load and the stability of gargling samples as well as the diagnostic sensitivity of the RT-LAMP assay. We performed >35,000 tests during the pandemic, with an average turnover time of fewer than 6 hours from sample arrival at the test station to result announcement. Altogether, our work provides a blueprint for fast, sensitive, scalable, cost- and labor-efficient RT-LAMP diagnostics. As RT-LAMP-based testing requires advanced, but non-specialized laboratory equipment, it is independent of potentially limiting clinical diagnostics supply chains. One-sentence summary A blueprint for scalable RT-LAMP test capacity for the sensitive detection of viral genomes demonstrated by SARS-CoV-2 surveillance testing.

Brazil has experienced an increase in outbreaks caused by flaviviruses. The high incidence of Dengue fever, the morbidity of Zika in children, and the high mortality of yellow fever affected millions in the recent years. Deciphering host-virus interactions is important to treat viral infections, and the mitogen-activated protein kinases (MAPK) are an interesting target because of their role in flavivirus replication. In particular, the mitogen-activated protein kinase kinase (MEK), which targets the extracellular signal-regulated kinase (ERK), is necessary to dengue and yellow fever infections. In this study, we evaluated the role of the MEK/ERK pathway, and the effect of the MEK inhibitor, Trametinib, in ZIKV PE243 Asian strain and the prototype ZIKV MR766 African strain, addressing genome replication, morphogenesis and viral release. ZIKV infection stimulated ERK phosphorylation in Vero cells at 12 and 18 hours post-infection (hpi). Trametinib showed a sustained antiviral activity, inhibiting both ZIKV strains for at least four days and electron microscopy showed a probable inhibition of ZIKV morphogenesis. ZIKV PE243 can complete one cycle in Vero cells in 14 hours: genome replication was detected around 8 hpi, intracellular viral particles at 12 hpi, and extracellular progeny at 14 hpi. Treatments of 6-hour intervals evidenced that Trametinib inhibited late stages of viral replication, and the titration of intra- or extracellular virions showed that the treatment especially affected viral morphogenesis and release. Thus, ZIKV stimulated ERK phosphorylation during viral morphogenesis and release, which correlated with Trametinib inhibiting both, the signaling pathway and the viral replication all together.

As the coronavirus SARS-CoV-2 continues to mutate into Variants of Concern (VOC), there is a growing and urgent need to develop effective antivirals to combat the newly emerged infectious disease COVID-19. Recent data indicate that monoclonal antibodies developed early in the pandemic are no longer capable of effectively neutralizing currently active VOCs. This report describes the design of a class of variant-agnostic chimeric molecules consisting of an Angiotensin Converting Enzyme-2 (ACE-2) domain mutated to retain ultrahigh affinity binding to a wide variety of SARS-CoV-2 variants, coupled to an Fc-silent immunoglobulin domain that eliminates antibody-dependent enhancement (ADE) and simultaneously extends biological half-life compared to existing mABs. Molecular modeling revealed that ACE-2 mutations L27, V34 and E90 resulted in ultrahigh affinity binding of the LVE-ACE-2 domain to the widest variety of VOCs, with KDs of 93 pM, 507 pM and 73 pM for binding to the Alpha B1.1.7, Delta B.1.617.2 and Omicron B.1.1.529 variants, and notably, 78fM affinity to the Omicron BA.2 variant, respectively. Surrogate viral neutralization assays (sVNT) revealed titers of ≥4.9ng/ml , for neutralization of recombinant viral proteins corresponding to the Alpha, Delta and Omicron variants. The values above were obtained with LVE-ACE-2/mAB chimeras containing the Y-T-E sequence that enhances binding to the FcRn receptor, which in turn is expected to extend biological half-life 3-4-fold. It is proposed that this new class of chimeric ACE-2/mABs will constitute variant-agnostic and cost-effective prophylactics against SARS-CoV-2, particularly when administered by nasal delivery systems.

Fast, precise, and low-cost diagnostic testing to identify persons infected with SARS– CoV-2 virus is pivotal to control the global pandemic of COVID-19 that began in late 2019. The gold standard method of diagnostic recommended is the RT-qPCR test. However, this method is not universally available, and is time-consuming and requires specialized personnel, as well as sophisticated laboratories. Currently, machine learning is a useful predictive tool for biomedical applications, being able to classify data from diverse nature. Relying on the artificial intelligence learning process, spectroscopic data from nasopharyngeal swab and tracheal aspirate samples can be used to leverage characteristic patterns and nuances in healthy and infected body fluids, which allows to identify infection regardless of symptoms or any other clinical or laboratorial tests. Hence, when new measurements are performed on samples of unknown status and the corresponding data is submitted to such an algorithm, it will be possible to predict whether the source individual is infected or not. This work presents a new methodology for rapid and precise label-free diagnosing of SARS-CoV-2 infection in clinical samples, which combines spectroscopic data acquisition and analysis via artificial intelligence algorithms. Our results show an accuracy of 85% for detection of SARS-CoV-2 in nasopharyngeal swab samples collected from asymptomatic patients or with mild symptoms, as well as an accuracy of 97% in tracheal aspirate samples collected from critically ill COVID-19 patients under mechanical ventilation. Moreover, the acquisition and processing of the information is fast, simple, and cheaper than traditional approaches, suggesting this methodology as a promising tool for biomedical diagnosis vis-à-vis the emerging and re-emerging viral SARS-CoV-2 variant threats in the future.

Background The genomes of SARS-CoV-2 are classified into variants, some of which are monitored as variants of concern (e.g. the delta variant B.1.617.2 or omicron variant B.1.1.529). Proportions of these variants in a population are typically estimated by large-scale sequencing of individual patient samples. Sequencing a mixture of SARS-CoV-2 RNA molecules from wastewater provides a cost-effective alternative, but requires methods for estimating variant proportions in a mixed sample. Results We propose a new method based on a probabilistic model of sequencing reads, capturing sequence diversity present within individual variants, as well as sequencing errors. The algorithm is implemented in an open source Python program called VirPool. We evaluated the accuracy of VirPool on several simulated and real sequencing data sets from both Illumina and nanopore sequencing platforms, including wastewater samples from Austria and France monitoring the onset of alpha and delta variants. Conclusions VirPool is a versatile tool for wastewater and other mixed-sample analysis that can handle both short- and long-read sequencing data. Our approach does not require pre-selection of characteristic mutations for variant profiles, it is able to use the entire length of reads instead of just the most informative positions, and can also capture haplotype dependencies within a single read. Availability VirPool is an open source software available at https://github.com/fmfi-compbio/virpool .

Japanese encephalitis virus (JEV) is a mosquito-borne flavivirus, and leading cause of neurological infection in Asia and the Pacific, with recent emergence in multiple territories in Australia in 2022. Patients may experience devastating socioeconomic consequences; JEV infection (JE) predominantly affects children in poor rural areas, has a 20-30% case fatality rate, and 30-50% of survivors suffer long-term disability. JEV RNA is rarely detected in patient samples, and the standard diagnostic test is an anti-JEV IgM ELISA with sub-optimal specificity; there is no means of detection in more remote areas. We aimed to test the hypothesis that there is a diagnostic protein signature of JE in human cerebrospinal fluid (CSF), and contribute to understanding of the host response and predictors of outcome during infection. We retrospectively tested a cohort of 163 patients recruited as part of the Laos central nervous system infection study. Application of liquid chromatography and tandem mass spectrometry (LC-MS/MS), using extensive offline fractionation and tandem mass tag labelling, enabled a comparison of the CSF proteome in 68 JE patient vs 95 non-JE neurological infections. 5,070 proteins were identified, including 4,805 human proteins and 265 pathogen proteins. We incorporated univariate analysis of differential protein expression, network analysis and machine learning techniques to build a ten-protein diagnostic signature of JE with >99% diagnostic accuracy. Pathways related to JE infection included neuronal damage, anti-apoptosis, heat shock and unfolded protein responses, cell adhesion, macrophage and dendritic cell activation as well as a reduced acute inflammatory response, hepatotoxicity, activation of coagulation, extracellular matrix and actin regulation. We verified the results by performing DIA LC-MS/MS in 16 (10%) of the samples, demonstrating 87% accuracy using the same model. Ultimately, antibody-based validation will be required, in a larger group of patients, in different locations and in field settings, to refine the list to 2-3 proteins that could be harnessed in a rapid diagnostic test. Author summary Japanese encephalitis virus (JEV) is a leading cause of brain infection in Asia and the Pacific, with recent introduction in multiple territories in Australia in 2022. Patients may experience devastating socioeconomic consequences; JEV infection (JE) predominantly affects children in poor rural areas, has a 20-30% case fatality rate, and 30-50% of survivors suffer long-term disability. The disease is difficult to diagnose, and there are no rapid tests that may be performed in remote areas that it exists such that we remain unclear of the burden of disease and the effects of control measures. We aimed to apply a relatively novel method to analyse the proteins in patients with JE as compared to other neurological infections, to see if this could be useful for making a diagnosis. We tested the brain fluid of 163 patients recruited as part of the Laos central nervous system infection study. We used a method, ‘liquid chromatography mass spectrometry’ that does not require prior knowledge of the proteins present, that is you do not target any specific protein. Over 5,000 proteins were identified, and these were analysed by various methods. We grouped the proteins into different clusters that provided insight into their function. We also filtered the list to 10 proteins that predicted JE as compared to other brain infections. Future work will require confirmation of the findings in a larger group of patients, in different locations and in field settings, to refine the list to 2-3 proteins that could be harnessed in a rapid diagnostic test.

Introduction Contemporary literature has revealed that Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) causes acute sialadenitis and related symptoms, such as discomfort, pain, swelling, and secretory dysfunction in salivary glands. The secretory dysfunction is due to SARS-CoV-2 infection-induced xerostomia and other associated clinical courses such as sore tongue, mucosal ulcer, and gingivitis in the oral cavity. Furthermore, it has been reported that COVID-19 causes the development of other oral manifestations. Materials and Methods A prospective clinical follow-up (a prevalent cohort) study was conducted to identify the possible oral manifestations of SARS-CoV-2 infection among patients admitted at the Eka General Hospital COVID-19 treatment center. Furthermore, the study aimed to calculate the prevalence rate of oral clinical courses in the cohorts. The study had two follow-up phases: Hospital and patient-home-based. Results A total of 55 patients (36 males and 19 females) met the inclusion criteria and were followed for 7.5 weeks. The 3.5 weeks’ hospital-based prospective follow-up study documented an 18% (n=10) prevalence rate of oral clinical courses among the cohorts. Twelve oral symptoms appeared in these ten patients. The manifested oral symptoms were oral mucosal lesions (n=6), xerostomia (n=5), and thickening of saliva (n=1). The oral mucosal lesions per se consisted of aphthous lesions (n=3), candidiasis (n=1), geographic tongue (n=1), and localized gingivitis (n=1). On the other hand, the four weeks’ home-based follow-up study disclosed four newly manifested oral symptoms: hemorrhagic crust, bulla, buccal mucositis, and petechiae. These manifestations appeared among six patients (four males and two females) who had not manifested any oral symptoms during the hospital-based follow-up. Accordingly, the overall prevalence of oral clinical courses among patients presented with SARS-CoV-2 is raised from 18% (n=10) to 29% (n=16). Similarly, the number of clinical courses increased from 12 to 16 after four additional weeks of follow-up. Discussion The study’s findings suggest the importance of initiating oral health care for patients with COVID-19. Therefore, multidisciplinary healthcare approaches should be delivered to assure optimal health outcomes. Accordingly, oral health professionals must be a substantial part of the interdisciplinary approach in caring for patients with COVID-19.