Lateral flow immunoassay based on surface-enhanced Raman scattering using pH-induced phage-templated hierarchical plasmonic assembly for point-of-care diagnosis of infectious disease

The outbreak of emerging infectious diseases gave rise to the demand for reliable point-of-care testing methods to diagnose and manage those diseases in early onset. However, the current on-site testing methods including lateral flow immunoassay (LFIA) suffer from the inaccurate diagnostic result due to the low sensitivity. Herein, we present the surface-enhanced Raman scattering-based lateral flow immunoassay (SERS-LFIA) by introducing phage-templated hierarchical plasmonic assembly (PHPA) nanoprobes to diagnose a contagious disease. The PHPA was fabricated using gold nanoparticles (AuNPs) assembled on bacteriophage MS2, where inter-particle gap sizes can be adjusted by pH-induced morphological alteration of MS2 coat proteins to provide the maximum SERS amplification efficiency via plasmon coupling. The plasmonic probes based on the PHPA produce strong and reproducible SERS signal that leads to sensitive and reliable diagnostic results in SERS-LFIA. The developed SERS-LFIA targeting severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) antibodies for a proof of concept had <100 pg/mL detection limits with high specificity in serum, proving it as an effective diagnostic device for the infectious diseases. Clinical validation using human serum samples further confirmed that the PHPA-based SERS-LFIA can distinguish the patients with COVID-19 from healthy controls with significant accuracy. These outcomes prove that the developed SERS-LFIA biosensor can be an alternative point-of-care testing (POCT) method against the emerging infectious diseases, in combination with the commercially available portable Raman devices.

Underdetected dispersal and extensive local transmission drove the 2022 mpox epidemic

The World Health Organization declared mpox a public health emergency of international concern in July 2022. To investigate global mpox transmission and population-level changes associated with controlling spread, we built phylogeographic and phylodynamic models to analyze MPXV genomes from five global regions together with air traffic and epidemiological data. Our models reveal community transmission prior to detection, changes in case reporting throughout the epidemic, and a large degree of transmission heterogeneity. We find that viral introductions played a limited role in prolonging spread after initial dissemination, suggesting that travel bans would have had only a minor impact. We find that mpox transmission in North America began declining before more than 10% of high-risk individuals in the USA had vaccine-induced immunity. Our findings highlight the importance of broader routine specimen screening surveillance for emerging infectious diseases and of joint integration of genomic and epidemiological information for early outbreak control.

Development of a reverse transcriptase digital droplet polymerase chain reaction-based approach for SARS-CoV-2 variant surveillance in wastewater

An urgent need for effective surveillance strategies arose due to the global emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although vaccines and antivirals are available, concerns persist about the evolution of new variants with potentially increased infectivity, transmissibility, and immune evasion. Therefore, variant monitoring is crucial for public health decision-making. Wastewater-based surveillance has proven to be an effective tool to monitor SARS-CoV-2 variants within populations. Specific SARS-CoV-2 variants are detected and quantified in wastewater in this study using a reverse transcriptase digital droplet polymerase chain reaction (RT-ddPCR) approach. The 11 designed assays were first validated in silico using a substantial dataset of high-quality SARS-CoV-2 genomes to ensure comprehensive variant coverage. The assessment of the sensitivity and specificity with reference material showed the capability of the developed assays to reliably identify target mutations while minimizing false positives and false negatives. The applicability of the assays was evaluated using wastewater samples from a wastewater treatment plant in Ghent, Belgium. The quantification of the specific mutations linked to the variants of concern present in these samples was calculated using these assays based on the detection of single mutations, which confirms their use for real-world variant surveillance. In conclusion, this study provides an adaptable protocol to monitor SARS-CoV-2 variants in wastewater with high sensitivity and specificity. Its potential for broader application in other viral surveillance contexts highlights its added value for rapid response to emerging infectious diseases. PRACTITIONER POINTS: Robust RT-ddPCR methodology for specific SARS-CoV-2 variants of concern detection in wastewater. Rigorous validation that demonstrates high sensitivity and specificity. Demonstration of real-world applicability using wastewater samples. Valuable tool for rapid response to emerging infectious diseases.

Vigilance in infectious disease emergencies: Expanding the concept

In their 2010 book, Lorna Weir and Eric Mykhalovskiy conceptualised the role of vigilance in unknown and emerging infectious disease threats. Theirs is a macro-level account which draws on empirical data to describe vigilance as a set of technical and political arrangements that govern collection, analysis, interpretation and communication of data as it pertains to unknown threats. In this paper we expand their work to detail a conceptual analysis of the role of vigilance at the micro-level during periods of high infectious disease threat. Our data are daily press conferences and associated non-discursive tools in New South Wales (NSW), Australia during times of heightened COVID-19 risk. This paper is a conceptual analysis that draws on theories of vigilance and related concepts to show how a key aspect of vigilance is making previously unseen threats visible or present. Communications formulated and encouraged three types of vigilance as a set of governing relations: institutional or authority-based; individual outward-facing; and individual inward-facing. We also describe the relationship between vigilance and related concepts that are used in response to anticipated public threats. Authority based vigilance involved contact tracing and policing of movement and behaviours. In individual outward facing vigilance people were asked to be alert to, analyse, and react to risk in their immediate environment. Inward facing vigilance required people to gather and react to information about their own behaviours and within their own bodies. There was a relationship between different types of vigilance; as risk increased and authority-based vigilance was less successful in containing the spread of infection, individual vigilance had a stronger role to play. This extension of vigilance at the micro-level sees some of the same unintended consequences as Weir and Mykhalovskiy describe at the global level, particularly in how burdens are inequitably distributed and experienced.

Modeling target-density-based cull strategies to contain foot-and-mouth disease outbreaks

Total ring depopulation is sometimes used as a management strategy for emerging infectious diseases in livestock, which raises ethical concerns regarding the potential slaughter of large numbers of healthy animals. We evaluated a farm-density-based ring culling strategy to control foot-and-mouth disease (FMD) in the United Kingdom (UK), which may allow for some farms within rings around infected premises (IPs) to escape depopulation. We simulated this reduced farm density, or "target density", strategy using a spatially-explicit, stochastic, state-transition algorithm. We modeled FMD spread in four counties in the UK that have different farm demographics, using 740,000 simulations in a full-factorial analysis of epidemic impact measures (i.e., culled animals, culled farms, and epidemic length) and cull strategy parameters (i.e., target farm density, daily farm cull capacity, and cull radius). All of the cull strategy parameters listed above were drivers of epidemic impact. Our simulated target density strategy was usually more effective at combatting FMD compared with traditional total ring depopulation when considering mean culled animals and culled farms and was especially effective when daily farm cull capacity was low. The differences in epidemic impact measures among the counties are likely driven by farm demography, especially differences in cattle and farm density. To prevent over-culling and the associated economic, organizational, ethical, and psychological impacts, the target density strategy may be worth considering in decision-making processes for future control of FMD and other diseases.

Capacity and needs assessment of veterinary services in Vietnam in biosecurity, biosafety and One Health

The Asia-Pacific region is recognised as an epicentre of emerging infectious diseases (EIDs), of which 75% are zoonotic in nature. Vietnam is recognised as a potential hotspot for zoonotic EIDs. There is a growing recognition that progress towards global health security requires greater focus on collaboration between the human health and animal health sectors to control diseases at their animal source and prevent against human health impacts. Assessment of veterinary epidemiology capacity in Vietnam is paramount to strengthening the health security of Asia-Pacific. This study aims to evaluate the national capacity and needs of veterinary services in Vietnam in biosecurity, biosafety and One Health. A cross-sectional, convergent mixed-methods study was conducted between November 2020 and April 2021. An online questionnaire was administered to government-employed field veterinarians. Descriptive analyses and logistic regression models were performed using survey responses to understand capacity in the field. Semi-structured interviews were also conducted with stakeholders in veterinary services including government, academia, research institutes, non-profit and international organisations. Coding and thematic analysis using a deductive approach was used for data collected from interviews to contextualise findings from the survey and understand institutional capacity. In total, 178 field veterinarians completed the online survey and 25 stakeholders were interviewed. The majority of participants had reported receiving training in biosecurity and biosafety, including use of personal protective equipment. Most respondents reported practicing good biosecurity measures (92%) and good biosafety measures (88%). Physical and socioeconomic barriers to practicing biosecurity were reported to be prevalent for smallholder farmers, which may suggest a gap in the capacity of veterinary services to provide cost-effective and practical biosecurity strategies. Seventy five percent of participants had never or rarely participated in One Health approaches in the field in the last 12 months and 69% reported further training as a high priority. There was a knowledge gap reported amongst district and commune-level veterinary staff about the need for, and awareness of multisectoral collaboration. Respondents that completed postgraduate qualifications in epidemiology or Field Epidemiology Training Programs (adjusted OR: 3.06; 95% CI: 1.01, 9.23, p = 0.046) and had longer job tenure between 10-12 years (OR: 10.38; 95% CI: 3.06, 35.15, p = <0.001) were more likely to have higher levels of experience in One Health. This study identified gaps in knowledge, attitudes and adoption of practices related to biosecurity, biosafety and One Health specifically in lower-level or less experienced veterinary staff without further training opportunities in epidemiology. These findings enable prioritisation of training, policy, and planning activities to further enhance the national capacity of veterinary services in Vietnam.

Gut microbial shifts in vampire bats linked to immunity due to changed diet in human disturbed landscapes

Anthropogenic land-use change alters wildlife habitats and modifies species composition, diversity, and contacts among wildlife, livestock, and humans. Such human-modified ecosystems have been associated with emerging infectious diseases, threatening human and animal health. However, human disturbance also creates new resources that some species can exploit. Common vampire bats (Desmodus rotundus) in Latin America constitute an important example, as their adaptation to human-modified habitats and livestock blood-feeding has implications for e.g., rabies transmission. Despite the well-known links between habitat degradation and disease emergence, few studies have explored how human-induced disturbance influences wildlife behavioural ecology and health, which can alter disease dynamics. To evaluate links among habitat disturbance, diet shifts, gut microbiota, and immunity, we quantified disturbance around roosting caves of common vampire bats in Costa Rica, measured their long-term diet preferences (livestock or wildlife blood) using stable isotopes of carbon and nitrogen, evaluated innate and adaptive immune markers, and characterized their gut microbiota. We observed that bats from roosting caves with more cattle farming nearby fed more on cattle blood. Moreover, gut microbial richness and the abundance of specific gut microbes differed according to feeding preferences. Interestingly, bats feeding primarily on wildlife blood harboured a higher abundance of the bacteria Edwardsiella sp., which tended to be associated with higher immunoglobulin G levels. Our results highlight how human land-use change may indirectly affect wildlife health and emerging infectious diseases through diet-induced shifts in microbiota, with implications for host immunity and potential consequences for susceptibility to pathogens.

Cardiac injury in hospitalized patients with severe fever and thrombocytopenia syndrome

Severe fever with thrombocytopenia syndrome (SFTS), an emerging infectious disease with a high fatality rate. Cardiac injury in SFTS patients is a major concern. This study aimed to evaluate the prevalence of cardiac injury and its association with mortality in hospitalized patients infected with novel Bunyavirus. Cardiac injury was defined as the presence of any of the following abnormalities: (1) blood levels of cardiac biomarkers (creatine kinase-MB, troponin-I, B-type natriuretic peptide or N-terminal pro-B-type natriuretic peptide); (2) new abnormalities in electrocardiography. The 203 SFTS patients were included in the final analysis. The proportion of SFTS patients developing cardiac injury during hospitalization was 71.4% (145/203). Compared with the uninjured group, the cardiac injury group had the severity of cardiac injury was underscored by higher median hospital costs (31420 vs. 12911, p < 0.001), higher proportion of intensive care units admissions (13.1% vs. 3.4%, p = 0.041), and higher hospital mortality rate (33.8% vs. 6.9%, p < 0.001). Multivariable-adjusted Cox proportional hazards regression analysis showed that cardiac injury was associated with higher mortality during hospitalization (hazards ratio, 7.349; 95% CI: 2.352-22.960). Cardiac injury is common among hospitalized SFTS patients, and it is associated with higher risk of mortality.

Development and External Validation of Clinical Features-based Machine Learning Models for Predicting COVID-19 in the Emergency Department

Introduction

Timely diagnosis of patients affected by an emerging infectious disease plays a crucial role in treating patients and avoiding disease spread. In prior research, we developed an approach by using machine learning (ML) algorithms to predict serious acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection based on clinical features of patients visiting an emergency department (ED) during the early coronavirus 2019 (COVID-19) pandemic. In this study, we aimed to externally validate this approach within a distinct ED population.

Methods

To create our training/validation cohort (model development) we collected data retrospectively from suspected COVID-19 patients at a US ED from February 23-May 12, 2020. Another dataset was collected as an external validation (testing) cohort from an ED in another country from May 12-June 15, 2021. Clinical features including patient demographics and triage information were used to train and test the models. The primary outcome was the confirmed diagnosis of COVID-19, defined as a positive reverse transcription polymerase chain reaction test result for SARS-CoV-2. We employed three different ML algorithms, including gradient boosting, random forest, and extra trees classifiers, to construct the predictive model. The predictive performances were evaluated with the area under the receiver operating characteristic curve (AUC) in the testing cohort.

Results

In total, 580 and 946 ED patients were included in the training and testing cohorts, respectively. Of them, 98 (16.9%) and 180 (19.0%) were diagnosed with COVID-19. All the constructed ML models showed acceptable discrimination, as indicated by the AUC. Among them, random forest (0.785, 95% confidence interval [CI] 0.747-0.822) performed better than gradient boosting (0.774, 95% CI 0.739-0.811) and extra trees classifier (0.72, 95% CI 0.677-0.762). There was no significant difference between the constructed models.

Conclusion

Our study validates the use of ML for predicting COVID-19 in the ED and demonstrates its potential for predicting emerging infectious diseases based on models built by clinical features with temporal and spatial heterogeneity. This approach holds promise for scenarios where effective diagnostic tools for an emerging infectious disease may be lacking in the future.

Exploring spatiotemporal pattern in the association between short-term exposure to fine particulate matter and COVID-19 incidence in the continental United States: a Leroux-conditional-autoregression-based strategy

Background

Numerous studies have demonstrated that fine particulate matter (PM2.5) is adversely associated with COVID-19 incidence. However, few studies have explored the spatiotemporal heterogeneity in this association, which is critical for developing cost-effective pollution-related policies for a specific location and epidemic stage, as well as, understanding the temporal change of association between PM2.5 and an emerging infectious disease like COVID-19.

Methods

The outcome was state-level daily COVID-19 cases in 49 native United States between April 1, 2020 and December 31, 2021. The exposure variable was the moving average of PM2.5 with a lag range of 0-14 days. A latest proposed strategy was used to investigate the spatial distribution of PM2.5-COVID-19 association in state level. First, generalized additive models were independently constructed for each state to obtain the rough association estimations, which then were smoothed using a Leroux-prior-based conditional autoregression. Finally, a modified time-varying approach was used to analyze the temporal change of association and explore the potential causes spatiotemporal heterogeneity.

Results

In all states, a positive association between PM2.5 and COVID-19 incidence was observed. Nearly one-third of these states, mainly located in the northeastern and middle-northern United States, exhibited statistically significant. On average, a 1 μg/m3 increase in PM2.5 concentration led to an increase in COVID-19 incidence by 0.92% (95%CI: 0.63-1.23%). A U-shaped temporal change of association was examined, with the strongest association occurring in the end of 2021 and the weakest association occurring in September 1, 2020 and July 1, 2021. Vaccination rate was identified as a significant cause for the association heterogeneity, with a stronger association occurring at a higher vaccination rate.

Conclusion

Short-term exposure to PM2.5 and COVID-19 incidence presented positive association in the United States, which exhibited a significant spatiotemporal heterogeneity with strong association in the eastern and middle regions and with a U-shaped temporal change.

Using phylogeographic link-prediction in primates to prioritize human parasite screening

Objectives

The ongoing risk of emerging infectious disease has renewed calls for understanding the origins of zoonoses and identifying future zoonotic disease threats. Given their close phylogenetic relatedness and geographic overlap with humans, non-human primates (NHPs) have been the source of many infectious diseases throughout human evolution. NHPs harbor diverse parasites, with some infecting only a single host species while others infect species from multiple families.

Materials and Methods

We applied a novel link-prediction method to predict undocumented instances of parasite sharing between humans and NHPs. Our model makes predictions based on phylogenetic distances and geographic overlap among NHPs and humans in six countries with high NHP diversity: Columbia, Brazil, Democratic Republic of Congo, Madagascar, China and Indonesia.

Results

Of the 899 human parasites documented in the Global Infectious Diseases and Epidemiology Network (GIDEON) database for these countries, 12% were shared with at least one other NHP species. The link prediction model identified an additional 54 parasites that are likely to infect humans but were not reported in GIDEON. These parasites were mostly host generalists, yet their phylogenetic host breadth varied substantially.

Discussion

As human activities and populations encroach on NHP habitats, opportunities for parasite sharing between human and non-human primates will continue to increase. Our study identifies specific infectious organisms to monitor in countries with high NHP diversity, while the comparative analysis of host generalism, parasite taxonomy, and transmission mode provides insights to types of parasites that represent high zoonotic risk.

Lessons identified for a future pandemic

Pandemics are complex events requiring a coordinated, global response. The response to the pandemic exposed vulnerabilities in system preparedness. Lessons arising from the COVID-19 pandemic are characterized by four broad themes: (i) investment in public health and health infrastructure, (ii) countermeasures (medical and non-medical), (iii) risk communication and public health measures and (iv) investment in people and partnerships. Learning from the COVID-19 pandemic identifies an approach that focusses on capacities and capabilities that are pathogen agnostic, ensuring that we can respond to diverse emerging infectious disease threats will be essential. The lessons learned from previous and ongoing infectious disease outbreaks should be kept under constant review, in line with technological and scientific advances, to improve our ability to detect, mitigate and respond to new and emerging threats.

Community-Based Digital Contact Tracing of Emerging Infectious Diseases: Design and Implementation Study With Empirical COVID-19 Cases

BACKGROUND

Contact tracing for containing emerging infectious diseases such as COVID-19 is resource intensive and requires digital transformation to enable timely decision-making.

OBJECTIVE

This study demonstrates the design and implementation of digital contact tracing using multimodal health informatics to efficiently collect personal information and contain community outbreaks. The implementation of digital contact tracing was further illustrated by 3 empirical SARS-CoV-2 infection clusters.

METHODS

The implementation in Changhua, Taiwan, served as a demonstration of the multisectoral informatics and connectivity between electronic health systems needed for digital contact tracing. The framework incorporates traditional travel, occupation, contact, and cluster approaches and a dynamic contact process enabled by digital technology. A centralized registry system, accessible only to authorized health personnel, ensures privacy and data security. The efficiency of the digital contact tracing system was evaluated through a field study in Changhua.

RESULTS

The digital contact tracing system integrates the immigration registry, communicable disease report system, and national health records to provide real-time information about travel, occupation, contact, and clusters for potential contacts and to facilitate a timely assessment of the risk of COVID-19 transmission. The digitalized system allows for informed decision-making regarding quarantine, isolation, and treatment, with a focus on personal privacy. In the first cluster infection, the system monitored 665 contacts and isolated 4 (0.6%) cases; none of the contacts (0/665, 0%) were infected during quarantine. The estimated reproduction number of 0.92 suggests an effective containment strategy for preventing community-acquired outbreak. The system was also used in a cluster investigation involving foreign workers, where none of the 462 contacts (0/462, 0%) tested positive for SARS-CoV-2.

CONCLUSIONS

By integrating the multisectoral database, the contact tracing process can be digitalized to provide the information required for risk assessment and decision-making in a timely manner to contain a community-acquired outbreak when facing the outbreak of emerging infectious disease.

Mapping regional funding for COVID-19 research in the Asia-Pacific region

INTRODUCTION

The Global Research Collaboration for Infectious Disease Preparedness (GloPID-R) is a network of funders supporting research on infectious diseases of epidemic/pandemic potential. GloPID-R is establishing regional hubs to strengthen stakeholder engagement particularly among low-income and middle-income countries. The first pilot hub, led from Republic of Korea (South Korea), has been launched in the Asia-Pacific region, a region highly prone to outbreaks of emerging infectious diseases. We present findings of mapping research undertaken in support of the hub's development.

METHODS

We analysed five COVID-19 research databases in September 2022 to identify research funders and intermediary funding sources supporting research in infectious diseases in the Asia-Pacific region. This was complemented with an in-depth analysis of the UK Collaborative on Development Research (UKCDR) and GloPID-R COVID-19 Research Project Tracker to assess the alignment of funded projects in the region to the WHO COVID-19 research priorities.

RESULTS

We identified 453 funders and funding sources supporting COVID-19 research in the Asia-Pacific Region including public, private and philanthropic organisations and universities. However, these organisations were clustered in few countries in the region. The in-depth analysis of the UKCDR and GloPID-R COVID-19 Research project Tracker found limited research involving Asia-Pacific countries with the 117 funders supporting these projects investing at least US$604m in COVID-19 research in the region. Social Sciences was the dominant theme on which funded projects focused whereas the priority areas with the least number of projects were research on 'animal and environmental health' and 'ethics considerations for research'.

CONCLUSION

Our analyses show the diversity of funding sources for research on infectious diseases in the Asia-Pacific region. Engagement between multiple actors in the health research system is likely to promote enhanced coordination for greater research impact. GloPID-R's Asia-Pacific regional hub aims to support activities for the enhancement of preparedness for outbreaks of emerging infectious diseases in the region.

Prototype Pathogens for Vaccine and Monoclonal Antibody Countermeasure Development: NIAID Workshop Process and Outcomes for Viral Families of Pandemic Potential

Given the increased risk of pandemics driven by emerging and reemerging infectious diseases, it is imperative that the United States and global scientific community be better prepared for future threats by prioritizing and launching key research programs and strategies. In December 2021, the National Institute of Allergy and Infectious Diseases (NIAID) published its pandemic preparedness plan, which focuses on the prototype pathogen approach for medical countermeasure development. The plan was introduced before its release at a NIAID-hosted workshop in November 2021 that featured scientific experts from the extramural community, government, and the private sector and focused on selection of prototype pathogens from 10 viral families with pandemic risk and moderate resources. This article will serve as an introduction to this special issue and will briefly define the prototype pathogen approach, describe the workshop goals and process for outcomes, and provide an outline of the viral working group articles to follow and future directions for NIAID.

Factors influencing nursing students' knowledge, attitudes, and infection management behavior for emerging respiratory infectious diseases: A cross-sectional study

Understanding the factors influencing infection management behavior related to Emerging Respiratory Infectious Diseases (ERIDs) among nursing students is important because nursing students play a vital role in preventing the spread of ERIDs. This study aimed to determine factors influencing infection management behavior related to ERIDs among nursing students in Korea. In this cross-sectional survey study, data were collected from May 3 to June 30, 2022, using a questionnaire. Data collected from 481 nursing students were analyzed using descriptive statistics, an independent t-test, a one-way analysis of variance, Pearson correlation coefficients, and hierarchical multiple regression using the SPSS program. The key factors influencing respondents' ERID-related infection management behavior were attitude (β = 0.554, p<0.001) and knowledge (β = 0.282, p<0.001). The explanatory power of this model was 40.2%, and the regression model was found to be statistically significant (F = 27.935, p<0.001). To improve nursing students' ERID-related infection management behavior, their knowledge of and attitudes toward ERIDs should be enhanced by repeatedly providing them with accurate professional information about ERIDs. Therefore, intensive efforts should be taken to develop a systematic educational program that can help nursing students better perform infection management.

Genome mining shows that retroviruses are pervasively invading vertebrate genomes

Endogenous retroviruses (ERVs) record past retroviral infections, providing molecular archives for interrogating the evolution of retroviruses and retrovirus-host interaction. However, the vast majority of ERVs are not active anymore due to various disruptive mutations, and ongoing retroviral invasion of vertebrate genomes has been rarely documented. Here we analyze genomics data from 2004 vertebrates for mining invading ERVs (ERVi). We find that at least 412 ERVi elements representing 217 viral operational taxonomic units are invading the genomes of 123 vertebrates, 18 of which have been assessed to be threatened species. Our results reveal an unexpected prevalence of ongoing retroviral invasion in vertebrates and expand the diversity of retroviruses recently circulating in the wild. We characterize the pattern and nature of ERVi in the historical and biogeographical context of their hosts, for instance, the generation of model organisms, sympatric speciation, and domestication. We suspect that these ERVi are relevant to conservation of threatened species, zoonoses in the wild, and emerging infectious diseases in humans.

Monitoring and responding to emerging infectious diseases in a university setting: A case study using COVID-19

Emerging infection diseases (EIDs) are an increasing threat to global public health, especially when the disease is newly emerging. Institutions of higher education (IHEs) are particularly vulnerable to EIDs because student populations frequently share high-density residences and strongly mix with local and distant populations. In fall 2020, IHEs responded to a novel EID, COVID-19. Here, we describe Quinnipiac University's response to SARS-CoV-2 and evaluate its effectiveness through empirical data and model results. Using an agent-based model to approximate disease dynamics in the student body, the University established a policy of dedensification, universal masking, surveillance testing via a targeted sampling design, and app-based symptom monitoring. After an extended period of low incidence, the infection rate grew through October, likely due to growing incidence rates in the surrounding community. A super-spreader event at the end of October caused a spike in cases in November. Student violations of the University's policies contributed to this event, but lax adherence to state health laws in the community may have also contributed. The model results further suggest that the infection rate was sensitive to the rate of imported infections and was disproportionately impacted by non-residential students, a result supported by the observed data. Collectively, this suggests that campus-community interactions play a major role in campus disease dynamics. Further model results suggest that app-based symptom monitoring may have been an important regulator of the University's incidence, likely because it quarantined infectious students without necessitating test results. Targeted sampling had no substantial advantages over simple random sampling when the model incorporated contact tracing and app-based symptom monitoring but reduced the upper boundary on 90% prediction intervals for cumulative infections when either was removed. Thus, targeted sampling designs for surveillance testing may mitigate worst-case outcomes when other interventions are less effective. The results' implications for future EIDs are discussed.

CROI 2023: Epidemiology, Diagnosis, and Management of MPox

The 2023 Conference on Retroviruses and Opportunistic Infections (CROI) emphasized emerging infectious diseases such as COVID-19 and mpox. Despite emerging from countries in which it was endemic only 9 months before the conference, mpox was well covered, with more than 60 presentations addressing various topics. There was a focus on the rapid development and implementation of tests to reduce the time to diagnosis, as well as multiplex panels to increase the accuracy of differential diagnosis. Presenters also highlighted the ability to diagnose mpox from multiple compartments, such as with rectal and pharyngeal swabs, and provided crucial information on the duration of positivity that may impact isolation requirements. Clinical experiences were described, including risk factors for severe disease and syndemic management. High rates of concomitant sexually transmitted infection (STI) were reported. Finally, prevention was a key topic, with presenters pointing to the contributions of individual behavioral changes and vaccine efficacy to reducing new cases.

Enhanced Viral Metagenomics with Lazypipe 2

Viruses are the main agents causing emerging and re-emerging infectious diseases. It is therefore important to screen for and detect them and uncover the evolutionary processes that support their ability to jump species boundaries and establish themselves in new hosts. Metagenomic next-generation sequencing (mNGS) is a high-throughput, impartial technology that has enabled virologists to detect either known or novel, divergent viruses from clinical, animal, wildlife and environmental samples, with little a priori assumptions. mNGS is heavily dependent on bioinformatic analysis, with an emerging demand for integrated bioinformatic workflows. Here, we present Lazypipe 2, an updated mNGS pipeline with, as compared to Lazypipe1, significant improvements in code stability and transparency, with added functionality and support for new software components. We also present extensive benchmarking results, including evaluation of a novel canine simulated metagenome, precision and recall of virus detection at varying sequencing depth, and a low to extremely low proportion of viral genetic material. Additionally, we report accuracy of virus detection with two strategies: homology searches using nucleotide or amino acid sequences. We show that Lazypipe 2 with nucleotide-based annotation approaches near perfect detection for eukaryotic viruses and, in terms of accuracy, outperforms the compared pipelines. We also discuss the importance of homology searches with amino acid sequences for the detection of highly divergent novel viruses.

Viral Metagenomics for the Identification of Emerging Infections in Clinical Samples with Inconclusive Dengue, Zika, and Chikungunya Viral Amplification

Viral metagenomics is increasingly being used for the identification of emerging and re-emerging viral pathogens in clinical samples with unknown etiology. The objective of this study was to shield light on the metavirome composition in clinical samples obtained from patients with clinical history compatible with an arboviral infection, but that presented inconclusive results when tested using RT-qPCR. The inconclusive amplification results might be an indication of the presence of an emerging arboviral agent that is inefficiently amplified by conventional PCR techniques. A total of eight serum samples with inconclusive amplification results for the routinely tested arboviruses—dengue (DENV), Zika (ZIKV), and Chikungunya (CHIKV) obtained during DENV and CHIKV outbreaks registered in the state of Alagoas, Northeast Brazil between July and August 2021—were submitted to metagenomic next-generation sequencing assay using NextSeq 2000 and bioinformatic pipeline for viral discovery. The performed bioinformatic analysis revealed the presence of two arboviruses: DENV type 2 (DENV-2) and CHIKV with a high genome coverage. Further, the metavirome of those samples revealed the presence of multiple commensal viruses apparently without clinical significance. The phylogenetic analysis demonstrated that the DENV-2 genome belonged to the Asian/American genotype and clustered with other Brazilian strains. The identified CHIKV genome was taxonomically assigned as ECSA genotype, which is circulating in Brazil. Together, our results reinforce the utility of metagenomics as a valuable tool for viral identification in samples with inconclusive arboviral amplification. Viral metagenomics is one of the most potent methods for the identification of emerging arboviruses.

Clinical symptoms associated with fatality of severe fever with thrombocytopenia syndrome: A systematic review and meta-analysis

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infection disease that is deadly if left untreated. Identification of potential risk factors with prognosis value may help to focus clinical management and reduce case fatality. However, information about these factors is conflicting and scattered. In this study, documents on SFTS were collected by searching PubMed, Web of Science, Chinese National Knowledge Infrastructure (CNKI) and Chinese Wan Fang Database through 12 January 2021. Meta-analysis was performed by using Stata and Review Manage software. 29 studies were included, involving 3011 participants with 38 clinical symptoms. The following factors were strongly (OR>5) and significantly (P-value<0.05) associated with mortality: hematemesis (OR=13.73), slurred speech (OR=5.05), disturbance of consciousness (OR=9.20), coma (OR=47.84), disseminated intravascular coagulation (OR=11.79), multiple organ dysfunction (OR=21.30), shock (OR=8.20) and acute kidney injury (OR=6.22). Non-specific symptoms, underlying diseases, respiratory symptoms and gastrointestinal symptoms were not associated with mortality of SFTS patients. Neurological symptoms and severe complications significantly increasing the death risk of SFTS cases can be identified by medical staff in resource-constrained settings and should be considered as core factors in future researchers that aim at improving the prognosis of SFTS patients.

The Endless Wars: Severe Fever With Thrombocytopenia Syndrome Virus, Host Immune and Genetic Factors

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging arboviral infectious disease with a high rate of lethality in susceptible humans and caused by severe fever with thrombocytopenia syndrome bunyavirus (SFTSV). Currently, neither vaccine nor specific antiviral drugs are available. In recent years, given the fact that both the number of SFTS cases and epidemic regions are increasing year by year, SFTS has become a public health problem. SFTSV can be internalized into host cells through the interaction between SFTSV glycoproteins and cell receptors and can activate the host immune system to trigger antiviral immune response. However, SFTSV has evolved multiple strategies to manipulate host factors to create an optimal environment for itself. Not to be discounted, host genetic factors may be operative also in the never-ending winning or losing wars. Therefore, the identifications of SFTSV, host immune and genetic factors, and their interactions are critical for understanding the pathogenic mechanisms of SFTSV infection. This review summarizes the updated pathogenesis of SFTS with regard to virus, host immune response, and host genetic factors to provide some novel perspectives of the prevention, treatment, as well as drug and vaccine developments.

Detecting Sentiment toward Emerging Infectious Diseases on Social Media: A Validity Evaluation of Dictionary-Based Sentiment Analysis

Despite the popularity and efficiency of dictionary-based sentiment analysis (DSA) for public health research, limited empirical evidence has been produced about the validity of DSA and potential harms to the validity of DSA. A random sample of a second-hand Ebola tweet dataset was used to evaluate the validity of DSA compared to the manual coding approach and examine the influences of textual features on the validity of DSA. The results revealed substantial inconsistency between DSA and the manual coding approach. The presence of certain textual features such as negation can partially account for the inconsistency between DSA and manual coding. The findings imply that scholars should be careful and critical about findings in disease-related public health research that use DSA. Certain textual features should be more carefully addressed in DSA.

What drives willingness to receive a new vaccine that prevents an emerging infectious disease? A discrete choice experiment among university students in Uganda

Background

There is a critical need to identify the drivers of willingness to receive new vaccines against emerging and epidemic diseases. A discrete choice experiment is the ideal approach to evaluating how individuals weigh multiple attributes simultaneously. We assessed the degree to which six attributes were associated with willingness to be vaccinated among university students in Uganda.

Methods

We conducted a single-profile discrete choice experiment at Makerere University in 2019. Participants were asked whether or not they would be vaccinated in 8 unique scenarios where attributes varied by disease risk, disease severity, advice for or against vaccination from trusted individuals, recommendations from influential figures, whether the vaccine induced indirect protection, and side effects. We calculated predicted probabilities of vaccination willingness using mixed logistic regression models, comparing health professional students with all other disciplines.

Findings

Of the 1576 participants, 783 (49.8%) were health professional students and 685 (43.5%) were female. Vaccination willingness was high (78%), and higher among health students than other students. We observed the highest vaccination willingness for the most severe disease outcomes and the greatest exposure risks, along with the Minister of Health’s recommendation or a vaccine that extended secondary protection to others. Mild side effects and recommendations against vaccination diminished vaccination willingness.

Interpretation

Our results can be used to develop evidence-based messaging to encourage uptake for new vaccines. Future vaccination campaigns, such as for COVID-19 vaccines in development, should consider acknowledging individual risk of exposure and disease severity and incorporate recommendations from key health leaders.

Lessons Learned from Coronavirus Disease 2019 (COVID-19) Therapies: Critical Perspectives From the Infectious Diseases Society of America (IDSA) COVID-19 Treatment Guideline Panel

Despite the challenges of the pandemic, there has been substantial progress with coronavirus disease 2019 (COVID-19) therapies. Pivotal COVID-19 trials like SOLIDARITY, RECOVERY, and ACCT-1 were rapidly conducted and data disseminated to support effective therapies. However, critical shortcomings remain on trial conduct, dissemination and interpretation of study results, and regulatory guidance in pandemic settings. The lessons that we learned have implications for both the current pandemic and future emerging infectious diseases. There is a need for establishing and standardizing clinical meaningful outcomes in therapeutic trials and for targeting defined populations and phenotypes that will most benefit from specific therapies. Standardized processes should be established for rapid and critical data review and dissemination to ensure scientific integrity. Clarity around the evidence standards needed for issuance of both emergency use authorization (EUA) and biologic license application (BLA) should be established and an infrastructure for executing rapid trials in epidemic settings maintained.

High Rickettsial Diversity in Rodents and Their Ectoparasites From the Central Highlands of Madagascar

Rickettsioses are among emerging infectious diseases around the world. In Madagascar, little information is available regarding Rickettsia (Rickettsiales: Rickettsiaceae) diversity and their potential impacts on public health. In fact, molecular screening of ectoparasites of mammals reported the presence of three species, Rickettsia africae, Rickettsia typhi, and Rickettsia felis. The present study aims to investigate the diversity of Rickettsia in small mammals and associated ectoparasites (fleas and ticks) using a molecular approach. In September and December 2016, fieldworks were undertaken in two districts of Madagascar to capture small mammals using standard traps (Tomahawk and Sherman traps) and collect associated ectoparasites. In total, 12 taxa of ectoparasites (5 flea and 7 tick species) were collected from 89 individuals of four species of terrestrial small mammals. Rickettsia spp. were molecularly identified in one specimen of Rattus rattus (Rodentia: Muridae), one specimen of Pulex irritans (Siphonaptera: Pulicidae) as well as four specimens of Ixodes cf. colasbelcouri (Ixodida: Ixodidae). This study showed the presence of three phylogenetically distinct taxa of Rickettsia in small mammals and their ectoparasites. The current study broadens our knowledge on the diversity of Rickettsia in the Central Highlands of Madagascar and highlights for the first time the presence of Ri. felis in R. rattus and in tick, I. cf. colasbelcouri in Madagascar. Additional studies are needed to have exhaustive information on Rickettsia in small mammals and their ectoparasites, to determine their pathogenicity as well as their potential effects on public health in order to update the national policy for the control of emerging infectious diseases in Madagascar.

Site- and Individual-Level Contaminations Affect Infection Prevalence of an Emerging Infectious Disease of Amphibians

Emerging infectious disease outbreaks are one of multiple stressors responsible for amphibian declines globally. In the northeastern United States, ranaviral diseases are prevalent in amphibians and other ectothermic species, but there is still uncertainty as to whether their presence is leading to population-level effects. Further, there is also uncertainty surrounding the potential interactions among disease infection prevalence in free-ranging animals and habitat degradation (co-occurrence of chemical stressors). The present study was designed to provide field-based estimates of the relationship between amphibian disease and chemical stressors. We visited 40 wetlands across three protected areas, estimated the prevalence of ranavirus among populations of larval wood frogs and spotted salamanders, and assessed chemical and biological stressors in wetland habitats and larval amphibians using a suite of selected bioassays, screening tools, and chemical analyses. Ranavirus was detected on larval amphibians from each protected area with an estimated occupancy ranging from 0.27 to 0.55. Considerable variation in ranavirus occupancy was also observed within and among each protected area. Of the stressors evaluated, ranavirus prevalence was strongly and positively related to concentrations of metalloestrogens (metals with the potential to bind to estrogen receptors) and total metals in wetland sediments and weakly and negatively related to total pesticide concentrations in larval amphibians. These results can be used by land managers to refine habitat assessments to include such environmental factors with the potential to influence disease susceptibility. Environ Toxicol Chem 2022;41:781-791. © 2022 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Current knowledge of vector-borne zoonotic pathogens in Zambia: A clarion call to scaling-up "One Health" research in the wake of emerging and re-emerging infectious diseases

Background

Although vector-borne zoonotic diseases are a major public health threat globally, they are usually neglected, especially among resource-constrained countries, including those in sub-Saharan Africa. This scoping review examined the current knowledge and identified research gaps of vector-borne zoonotic pathogens in Zambia.

Methods and findings

Major scientific databases (Web of Science, PubMed, Scopus, Google Scholar, CABI, Scientific Information Database (SID)) were searched for articles describing vector-borne (mosquitoes, ticks, fleas and tsetse flies) zoonotic pathogens in Zambia. Several mosquito-borne arboviruses have been reported including Yellow fever, Ntaya, Mayaro, Dengue, Zika, West Nile, Chikungunya, Sindbis, and Rift Valley fever viruses. Flea-borne zoonotic pathogens reported include Yersinia pestis and Rickettsia felis. Trypanosoma sp. was the only tsetse fly-borne pathogen identified. Further, tick-borne zoonotic pathogens reported included Crimean-Congo Haemorrhagic fever virus, Rickettsia sp., Anaplasma sp., Ehrlichia sp., Borrelia sp., and Coxiella burnetii.

Conclusions

This study revealed the presence of many vector-borne zoonotic pathogens circulating in vectors and animals in Zambia. Though reports of human clinical cases were limited, several serological studies provided considerable evidence of zoonotic transmission of vector-borne pathogens in humans. However, the disease burden in humans attributable to vector-borne zoonotic infections could not be ascertained from the available reports and this precludes the formulation of national policies that could help in the control and mitigation of the impact of these diseases in Zambia. Therefore, there is an urgent need to scale-up “One Health” research in emerging and re-emerging infectious diseases to enable the country to prepare for future epidemics, including pandemics.

Despite vector-borne zoonoses being a major public health threat globally, they are often overlooked, particularly among resource-constrained countries in sub-Saharan Africa, including Zambia. Therefore, we reviewed the current knowledge and identified research gaps of vector-borne zoonotic pathogens in Zambia. We focussed on mosquito-, tick-, flea- and tsetse fly-borne zoonotic pathogens reported in the country. Although we found evidence of circulation of several vector-borne zoonotic pathogens among vectors, animals and humans, clinical cases in humans were rarely reported. This suggests sparse capacity for diagnosis of vector-borne pathogens in healthcare facilities in the country and possibly limited awareness and knowledge of the local epidemiology of these infectious agents. Establishment of facility-based surveillance of vector-borne zoonoses in health facilities could provide valuable insights on morbidity, disease severity, and mortalities associated with infections as well as immune responses. In addition, there is also need for increased genomic surveillance of vector-borne pathogens in vectors and animals and humans for a better understanding of the molecular epidemiology of these diseases in Zambia. Furthermore, vector ecology studies aimed at understanding the drivers of vector abundance, pathogen host range (i.e., including the range of vectors and reservoirs), parasite-host interactions and factors influencing frequency of human-vector contacts should be prioritized. The study revealed the need for Zambia to scale-up One Health research in emerging and re-emerging infectious diseases to enable the country to be better prepared for future epidemics, including pandemics.

Henipaviruses-A constant threat to livestock and humans

In this review, we highlight the risk to livestock and humans from infections with henipaviruses, which belong to the virus family Paramyxoviridae. We provide a comprehensive overview of documented outbreaks of Nipah and Hendra virus infections affecting livestock and humans and assess the burden on the economy and health systems. In an increasingly globalized and interconnected world, attention must be paid to emerging viruses and infectious diseases, as transmission routes can be rapid and worldwide.

Is overwintering mortality driving enigmatic declines? Evaluating the impacts of trematodes and the amphibian chytrid fungus on an anuran from hatching through overwintering

Emerging infectious diseases are increasing globally and are an additional challenge to species dealing with native parasites and pathogens. Therefore, understanding the combined effects of infectious agents on hosts is important for species’ conservation and population management. Amphibians are hosts to many parasites and pathogens, including endemic trematode flatworms (e.g., Echinostoma spp.) and the novel pathogenic amphibian chytrid fungus (Batrachochytrium dendrobatidis [Bd]). Our study examined how exposure to trematodes during larval development influenced the consequences of Bd pathogen exposure through critical life events. We found that prior exposure to trematode parasites negatively impacted metamorphosis but did not influence the effect of Bd infection on terrestrial growth and survival. Bd infection alone, however, resulted in significant mortality during overwintering—an annual occurrence for most temperate amphibians. The results of our study indicated overwintering mortality from Bd could provide an explanation for enigmatic declines and highlights the importance of examining the long-term consequences of novel parasite exposure.

Evidence of Coronavirus (CoV) Pathogenesis and Emerging Pathogen SARS-CoV-2 in the Nervous System: A Review on Neurological Impairments and Manifestations

The coronavirus disease 2019 (COVID-19) pandemic is an issue of global significance that has taken the lives of many across the world. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus responsible for its pathogenesis. The pulmonary manifestations of COVID-19 have been well described in the literature. Initially, it was thought to be limited to the respiratory system; however, we now recognize that COVID-19 also affects several other organs, including the nervous system. Two similar human coronaviruses (CoV) that cause severe acute respiratory syndrome (SARS-CoV-1) and Middle East respiratory syndrome (MERS-CoV) are also known to cause disease in the nervous system. The neurological manifestations of SARS-CoV-2 infection are growing rapidly, as evidenced by several reports. There are several mechanisms responsible for such manifestations in the nervous system. For instance, post-infectious immune-mediated processes, direct virus infection of the central nervous system (CNS), and virus-induced hyperinflammatory and hypercoagulable states are commonly involved. Guillain-Barré syndrome (GBS) and its variants, dysfunction of taste and smell, and muscle injury are numerous examples of COVID-19 PNS (peripheral nervous system) disease. Likewise, hemorrhagic and ischemic stroke, encephalitis, meningitis, encephalopathy acute disseminated encephalomyelitis, endothelialitis, and venous sinus thrombosis are some instances of COVID-19 CNS disease. Due to multifactorial and complicated pathogenic mechanisms, COVID-19 poses a large-scale threat to the whole nervous system. A complete understanding of SARS-CoV-2 neurological impairments is still lacking, but our knowledge base is rapidly expanding. Therefore, we anticipate that this comprehensive review will provide valuable insights and facilitate the work of neuroscientists in unfolding different neurological dimensions of COVID-19 and other CoV associated abnormalities.

Facilitating the deployment of Japanese human resources for responding global outbreaks of emerging and Re-emerging infectious diseases: A cross-sectional study

INTRODUCTION

In response to global outbreaks of infectious diseases, the need for support from organizations such as the World Health Organization Global Outbreak Alert and Response Network (GOARN) is increasing. Identifying the obstacles and support needs for applicants could increase GOARN deployments from Japan.

METHODS

This cross-sectional study involved a web-based, self-administered questionnaire survey targeting Japanese participants in the GOARN Tier 1.5 training workshop, held in Tokyo in December 2019.

RESULTS

All 47 Japanese participants in the workshop responded to the survey. Most responders were male and in their 30s and 40s. Participants specialized in case management (42.6%), infection prevention and control (25.6%), epidemiology and surveillance (19.1%). Only two participants (4.6%) had experienced a GOARN deployment. Their motivations for joining the GOARN training workshop were "Desire to be part of an international emerging infectious disease response team" (44.6%), "Interest in making an international contribution" (19.1%), and "Interest in working for the Japanese government in the field of international infectious diseases" (14.9%). Obstacles to GOARN deployments were "Making time for deployments" (45.7%) and "Lack of required professional skills and knowledge" (40.4%). The support needs for GOARN deployments constituted "Periodic simulation training" (51.1%), "Financial support during deployments" (44.7%), and "Technical support for deployments" (40.4%).

CONCLUSIONS

Our study revealed the obstacles and support needs of Japanese candidates for GOARN deployment. Making time and upskilling for GOARN deployment were the main obstacles. More practical training (like GOARN Tier 2.0) with other supports are needed. The national framework is desirable to realize these supports.

Environmental Correlates of Lyme Disease Emergence in Southwest Virginia, 2005-2014

Lyme disease is the most common tick-borne disease in North America. Though human infection is mostly transmitted in a limited geography, the range has expanded in recent years. One notable area of recent expansion is in the mountainous region of southwestern Virginia. The ecological factors that facilitate or constrain the range of human Lyme disease in this region remain uncertain. To evaluate this further, we obtained ecological data, including remotely sensed data on forest structure and vegetation, weather data, and elevation. These data were aggregated within the census block groups of a 9,153 km2 area around the cities of Blacksburg and Roanoke, VA, an area with heterogeneous Lyme disease transmission. In this geographic area, 755 individuals were reported to have Lyme disease in the 10 yr from 2006 to 2015, and these cases were aggregated by block group. A zero-inflated negative binomial model was used to evaluate which environmental variables influenced the abundance of Lyme disease cases. Higher elevation and higher vegetation density had the greatest effect size on the abundance of Lyme disease. Measures of forest edge, forest integrity, temperature, and humidity were not associated with Lyme disease cases. Future southward expansion of Lyme disease into the southeastern states may be most likely in ecologically similar mountainous areas.

Setting the Terms for Zoonotic Diseases: Effective Communication for Research, Conservation, and Public Policy

Many of the world's most pressing issues, such as the emergence of zoonotic diseases, can only be addressed through interdisciplinary research. However, the findings of interdisciplinary research are susceptible to miscommunication among both professional and non-professional audiences due to differences in training, language, experience, and understanding. Such miscommunication contributes to the misunderstanding of key concepts or processes and hinders the development of effective research agendas and public policy. These misunderstandings can also provoke unnecessary fear in the public and have devastating effects for wildlife conservation. For example, inaccurate communication and subsequent misunderstanding of the potential associations between certain bats and zoonoses has led to persecution of diverse bats worldwide and even government calls to cull them. Here, we identify four types of miscommunication driven by the use of terminology regarding bats and the emergence of zoonotic diseases that we have categorized based on their root causes: (1) incorrect or overly broad use of terms; (2) terms that have unstable usage within a discipline, or different usages among disciplines; (3) terms that are used correctly but spark incorrect inferences about biological processes or significance in the audience; (4) incorrect inference drawn from the evidence presented. We illustrate each type of miscommunication with commonly misused or misinterpreted terms, providing a definition, caveats and common misconceptions, and suggest alternatives as appropriate. While we focus on terms specific to bats and disease ecology, we present a more general framework for addressing miscommunication that can be applied to other topics and disciplines to facilitate more effective research, problem-solving, and public policy.

Acute Flaccid Myelitis

Acute flaccid myelitis (AFM) is an incompletely understood neurologic disorder occurring in epidemic fashion causing weakness ranging from mild paresis to devastating paralysis in children and some adults. This article reviews the case definition of AFM as well as its epidemiology and association with enteroviral infection. The clinical presentation, diagnostic investigation with particular attention to electrodiagnostics, acute management, and surgical options are described. Clinical outcomes and considerations for acute and long-term rehabilitation management are discussed extensively based on review of current literature, highlighting avenues for further study.

A signaling pathway-driven bioinformatics pipeline for predicting therapeutics against emerging infectious diseases

Background: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the etiological agent of coronavirus disease-2019 (COVID-19), is a novel Betacoronavirus that was first reported in Wuhan, China in December of 2019. The virus has since caused a worldwide pandemic that highlights the need to quickly identify potential prophylactic or therapeutic treatments that can reduce the signs, symptoms, and/or spread of disease when dealing with a novel infectious agent. To combat this problem, we constructed a computational pipeline that uniquely combines existing tools to predict drugs and biologics that could be repurposed to combat an emerging pathogen. Methods: Our workflow analyzes RNA-sequencing data to determine differentially expressed genes, enriched Gene Ontology (GO) terms, and dysregulated pathways in infected cells, which can then be used to identify US Food and Drug Administration (FDA)-approved drugs that target human proteins within these pathways. We used this pipeline to perform a meta-analysis of RNA-seq data from cells infected with three Betacoronavirus species including severe acute respiratory syndrome coronavirus (SARS-CoV; SARS), Middle East respiratory syndrome coronavirus (MERS-CoV; MERS), and SARS-CoV-2, as well as respiratory syncytial virus and influenza A virus to identify therapeutics that could be used to treat COVID-19.  Results: This analysis identified twelve existing drugs, most of which already have FDA-approval, that are predicted to counter the effects of SARS-CoV-2 infection. These results were cross-referenced with interventional clinical trials and other studies in the literature to identify drugs on our list that had previously been identified or used as treatments for COIVD-19 including canakinumab, anakinra, tocilizumab, sarilumab, and baricitinib. Conclusions: While the results reported here are specific to Betacoronaviruses, such as SARS-CoV-2, our bioinformatics pipeline can be used to quickly identify candidate therapeutics for future emerging infectious diseases.

A signaling pathway-driven bioinformatics pipeline for predicting therapeutics against emerging infectious diseases

Background: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the etiological agent of coronavirus disease-2019 (COVID-19), is a novel Betacoronavirus that was first reported in Wuhan, China in December of 2019. The virus has since caused a worldwide pandemic that highlights the need to quickly identify potential prophylactic or therapeutic treatments that can reduce the signs, symptoms, and/or spread of disease when dealing with a novel infectious agent. To combat this problem, we constructed a computational pipeline that uniquely combines existing tools to predict drugs and biologics that could be repurposed to combat an emerging pathogen. Methods: Our workflow analyzes RNA-sequencing data to determine differentially expressed genes, enriched Gene Ontology (GO) terms, and dysregulated pathways in infected cells, which can then be used to identify US Food and Drug Administration (FDA)-approved drugs that target human proteins within these pathways. We used this pipeline to perform a meta-analysis of RNA-seq data from cells infected with three Betacoronavirus species including severe acute respiratory syndrome coronavirus (SARS-CoV; SARS), Middle East respiratory syndrome coronavirus (MERS-CoV; MERS), and SARS-CoV-2, as well as respiratory syncytial virus and influenza A virus to identify therapeutics that could be used to treat COVID-19.  Results: This analysis identified twelve existing drugs, most of which already have FDA-approval, that are predicted to counter the effects of SARS-CoV-2 infection. These results were cross-referenced with interventional clinical trials and other studies in the literature to identify drugs on our list that had previously been identified or used as treatments for COIVD-19 including canakinumab, anakinra, tocilizumab, sarilumab, and baricitinib. Conclusions: While the results reported here are specific to Betacoronaviruses, such as SARS-CoV-2, our bioinformatics pipeline can be used to quickly identify candidate therapeutics for future emerging infectious diseases.

Surveillance of the major pathogenic arboviruses of public health concern in Gabon, Central Africa: increased risk of West Nile virus and dengue virus infections

BACKGROUND

Increasing arbovirus infections have been a global burden in recent decades. Many countries have experienced the periodic emergence of arbovirus diseases. However, information on the prevalence of arboviruses is largely unknown or infrequently updated because of the lack of surveillance studies, especially in Africa.

METHODS

A surveillance study was conducted in Gabon, Central Africa, on arboviruses, which are a major public health concern in Africa, including: West Nile virus (WNV), dengue virus (DENV), Zika virus (ZIKV), yellow fever virus (YFV), chikungunya virus (CHIKV), and Rift Valley fever virus (RVFV). Serological and molecular assays were performed to investigate past infection history and the current status of infection, using serum samples collected from healthy individuals and febrile patients, respectively.

RESULTS

The overall seroprevalence during 2014-2017 was estimated to be 25.3% for WNV, 20.4% for DENV, 40.3% for ZIKV, 60.7% for YFV, 61.2% for CHIKV, and 14.3% for RVFV. No significant differences were found in the seroprevalence of any of the viruses between the male and female populations. However, a focus on the mean age in each arbovirus-seropositive individual showed a significantly younger age in WNV- and DENV-seropositive individuals than in CHIKV-seropositive individuals, indicating that WNV and DENV caused a relatively recent epidemic in the region, whereas CHIKV had actively circulated before. Of note, this indication was supported by the detection of both WNV and DENV genomes in serum samples collected from febrile patients after 2016.

CONCLUSIONS

This study revealed the recent re-emergence of WNV and DENV in Gabon as well as the latest seroprevalence state of the major arboviruses, which indicated the different potential risks of virus infections and virus-specific circulation patterns. This information will be helpful for public health organizations and will enable a rapid response towards these arbovirus infections, thereby preventing future spread in the country.

The intersection of land use and human behavior as risk factors for zoonotic pathogen exposure in Laikipia County, Kenya

A majority of emerging infectious diseases (EIDs) are zoonotic, mainly caused through spillover events linked to human-animal interactions. We conducted a survey-based human behavioral study in Laikipia County, Kenya, which is characterized by a dynamic human-wildlife-livestock interface. Questionnaires that assessed human-animal interactions, sanitation, and illnesses experienced within the past year were distributed to 327 participants among five communities in Laikipia. This study aimed to 1) describe variation in reported high-risk behaviors by community type and 2) assess the relationship between specific behaviors and self-reported illnesses. Behavioral trends were assessed in R via Fisher’s exact tests. A generalized linear mixed model with Lasso penalization (GLMMLasso) was used to assess correlations between behaviors and participants’ self-reported illness within the past year, with reported behaviors as independent variables and reported priority symptoms as the outcome. Reported behaviors varied significantly among the study communities. Participants from one community (Pastoralist-1) were significantly more likely to report eating a sick animal in the past year (p< 0.001), collecting an animal found dead to sell in the past year (p<0.0001), and not having a designated location for human waste (p<0.0001) when compared to participants from other communities. The GLMMLasso revealed that reports of an ill person in the household in the past year was significantly associated with self-reported illness. Sixty-eight percent of participants reported that bushmeat is available within the communities. Our study demonstrates community-level variation in behaviors that may influence zoonotic pathogen exposure. We further recommend development of targeted studies that explore behavioral variations among land use systems in animal production contexts.

Many infectious diseases, such as H1N1, Ebola, and COVID-19, can be spread to humas from animals. In order to reduce the risk of disease “spillover” (disease transmission from an animal to a person), it is important to understand how interactions between humans and animals can influence spread. Certain behaviors, such as eating raw meat, hunting, or sharing drinking water with animals can put people at greater risk of contacting bacteria and viruses that can cause these diseases. Globally, communities that depend on animal production are at heightened risk due to increased contact with animals. In this study, the authors conducted human behavioral surveys among different communities in Kenya that raise livestock. Results show that reported behaviors varied greatly by community. One of the communities reported a significantly higher proportion of behaviors, such as eating raw meat or eating animals found dead. Communities that show high prevalence of these behaviors may be at greater risk for contracting diseases from animals. Understanding this variation is important for developing plans for community outreach and addressing behaviors that can influence risk of disease spread.