Digital Disease Surveillance for Emerging Infectious Diseases: An Early Warning System Using the Internet and Social Media Data for COVID-19 Forecasting in Canada.

BACKGROUND: Emerging Infectious Diseases (EID) are a significant threat to population health globally. We aimed to examine the relationship between internet search engine queries and social media data on COVID-19 and determine if they can predict COVID-19 cases in Canada. METHODS: We analyzed Google Trends (GT) and Twitter data from 1/1/2020 to 3/31/2020 in Canada and used various signal-processing techniques to remove noise from the data. Data on COVID-19 cases was obtained from the COVID-19 Canada Open Data Working Group. We conducted time-lagged cross-correlation analyses and developed the long short-term memory model for forecasting daily COVID-19 cases. RESULTS: Among symptom keywords, "cough," "runny nose," and "anosmia" were strong signals with high cross-correlation coefficients >0.8 ( rCough = 0.825, t - 9; rRunnyNose = 0.816, t - 11; rAnosmia = 0.812, t - 3 ), showing that searching for "cough," "runny nose," and "anosmia" on GT correlated with the incidence of COVID-19 and peaked 9, 11, and 3 days earlier than the incidence peak, respectively. For symptoms- and COVID-related Tweet counts, the cross-correlations of Tweet signals and daily cases were rTweetSymptoms = 0.868, t - 11 and tTweetCOVID = 0.840, t - 10, respectively. The LSTM forecasting model achieved the best performance (MSE = 124.78, R2 = 0.88, adjusted R2 = 0.87) using GT signals with cross-correlation coefficients >0.75. Combining GT and Tweet signals did not improve the model performance. CONCLUSION: Internet search engine queries and social media data can be used as early warning signals for creating a real-time surveillance system for COVID-19 forecasting, but challenges remain in modelling.

Automated Travel History Extraction From Clinical Notes for Informing the Detection of Emergent Infectious Disease Events: Algorithm Development and Validation.

BACKGROUND: Patient travel history can be crucial in evaluating evolving infectious disease events. Such information can be challenging to acquire in electronic health records, as it is often available only in unstructured text. OBJECTIVE: This study aims to assess the feasibility of annotating and automatically extracting travel history mentions from unstructured clinical documents in the Department of Veterans Affairs across disparate health care facilities and among millions of patients. Information about travel exposure augments existing surveillance applications for increased preparedness in responding quickly to public health threats. METHODS: Clinical documents related to arboviral disease were annotated following selection using a semiautomated bootstrapping process. Using annotated instances as training data, models were developed to extract from unstructured clinical text any mention of affirmed travel locations outside of the continental United States. Automated text processing models were evaluated, involving machine learning and neural language models for extraction accuracy. RESULTS: Among 4584 annotated instances, 2659 (58%) contained an affirmed mention of travel history, while 347 (7.6%) were negated. Interannotator agreement resulted in a document-level Cohen kappa of 0.776. Automated text processing accuracy (F1 85.6, 95% CI 82.5-87.9) and computational burden were acceptable such that the system can provide a rapid screen for public health events. CONCLUSIONS: Automated extraction of patient travel history from clinical documents is feasible for enhanced passive surveillance public health systems. Without such a system, it would usually be necessary to manually review charts to identify recent travel or lack of travel, use an electronic health record that enforces travel history documentation, or ignore this potential source of information altogether. The development of this tool was initially motivated by emergent arboviral diseases. More recently, this system was used in the early phases of response to COVID-19 in the United States, although its utility was limited to a relatively brief window due to the rapid domestic spread of the virus. Such systems may aid future efforts to prevent and contain the spread of infectious diseases.

Managing Viral Emerging Infectious Diseases via current Molecular Diagnostics in the Emergency Department: the Tricky Cases.

INTRODUCTION: Emerging infectious diseases' diagnosis has been a major problem in most hospitals and other senior care facilities, especially for the current Coronavirus Disease 2019 (COVID-19). The various clinical manifestations, and the several radiology and laboratory data combined with the misleading test results for identifying the virus, are responsible for certain misdiagnoses, especially for suspected cases that visit the emergency department and require urgent management and further treatment. AREAS COVERED: The major challenges for emerging infectious diseases' molecular diagnosis are being described here on a great scale, and, finally, strategies for a precise and on-the-spot molecular diagnosis are thoroughly discussed. Related literature was searched using the PubMed, Science Direct, and EMBASE databases published until May 2022 on the general information for viral infections and relevant false test results. EXPERT OPINION: Emerging diseases' molecular diagnosis via current common diagnostic assays seems to be extremely tricky, and front-line physicians and other senior care facilities should be able to recognize some falsely diagnosed cases or even prevent their existence. Further biotechnologic revolution concerning viral molecular diagnostics will be evident in the near future, thus new methods' limitations should be highlighted to physicians from the very beginning of their performances and wide utilization.

Emerging tropical neurological infections.

A large majority of neurological infections remain undiagnosed worldwide. Emerging and re-emerging infections are likely to be responsible for a significant proportion of these. Over the last two decades, several new organisms producing neurological infection and the neurotropic potential of many other known pathogens have been identified. Large outbreaks caused by re-emerging pathogens such as Chikungunya virus, Zika virus and Ebola virus have led to better delineation of their neurological manifestations. Recognition of the pandemic potential of emerging pathogens and an improved understanding of their host-vector-environment interactions would help us be better prepared to meet these emerging threats.

A Global lmmunological Observatory to meet a time of pandemics.

SARS-CoV-2 presents an unprecedented international challenge, but it will not be the last such threat. Here, we argue that the world needs to be much better prepared to rapidly detect, define and defeat future pandemics. We propose that a Global Immunological Observatory and associated developments in systems immunology, therapeutics and vaccine design should be at the heart of this enterprise.

CRISPR Tackles Emerging Viral Pathogens.

Understanding the dynamic relationship between viral pathogens and cellular host factors is critical to furthering our knowledge of viral replication, disease mechanisms and development of anti-viral therapeutics. CRISPR genome editing technology has enhanced this understanding, by allowing identification of pro-viral and anti-viral cellular host factors for a wide range of viruses, most recently the cause of the COVID-19 pandemic, SARS-CoV-2. This review will discuss how CRISPR knockout and CRISPR activation genome-wide screening methods are a robust tool to investigate the viral life cycle and how other class 2 CRISPR systems are being repurposed for diagnostics.

Emerging and endemic zoonotic diseases: surveillance and diagnostics.

In this paper, the authors: (a) list methods used to diagnose zoonotic diseases in humans and animals; (b) identify between-species differences in diagnostic approaches, providing commentary on the benefits that might arise from simultaneous interpretation of data from human and animal health surveillance systems; and (c) reiterate the importance of using species-specific, validated diagnostic tests for surveillance and disease outbreak investigations. Emerging and endemic zoonotic diseases are likely to provide a continued threat to global health in the short- to medium-term future. A good deal of knowledge about the drivers of infectious disease emergence has been developed based on numerous examples from the recent past. Sharing of diagnostic resources across human and animal health sectors, sharing of human and animal health surveillance data, development of skills in the interpretation of that data and awareness of issues related to the validation and interpretation of diagnostic test data are necessary prerequisites for an effective endemic disease surveillance system. A good understanding of the epidemiological patterns of endemic disease will allow human and animal health professionals be able to more quickly detect the presence of emerging disease threats.

Après avoir répertorié les méthodes utilisées pour diagnostiquer les maladies zoonotiques chez l'homme comme chez les animaux, les auteurs définissent les différentes approches diagnostiques suivant les espèces considérées et commentent les avantages qui pourraient découler d'une interprétation simultanée des données par les systèmes de surveillance en santé animale et en santé publique ; il réitèrent ensuite l'importance de recourir à des tests diagnostiques validés et spécifiques de l'espèce considérée dans le cadre de la surveillance et des enquêtes suite à l'apparition d'un foyer. Les maladies zoonotiques émergentes et endémiques représentent potentiellement une menace continue pour la santé mondiale à court et à moyen terme. Les facteurs favorisant l'émergence des maladies infectieuses sont désormais beaucoup mieux connus grâce aux enseignements tirés de nombreux exemples récents. Le partage des ressources diagnostiques entre les secteurs de la santé humaine et animale, les échanges des données de la surveillance sanitaire réunies par les deux secteurs, le renforcement des compétences en matière d'interprétation des données et la sensibilisation aux problématiques de la validation et de l'interprétation des données générées par les tests de diagnostic sont des conditions préalables à la mise en place d'un système efficace de surveillance des maladies endémiques. Une bonne compréhension des profils épidémiologiques des maladies endémiques permettra aux professionnels de la santé humaine et animale de détecter plus rapidement la présence de menaces émergentes.

Los autores proceden aquí a: a) relacionar los métodos empleados para diagnosticar enfermedades zoonóticas en personas y animales; b) señalar las diferencias que existen entre los distintos planteamientos de diagnóstico según la especie de que se trate, comentando asimismo las ventajas que podrían derivarse de la interpretación simultánea de los datos de los sistemas de vigilancia sanitaria y de los de vigilancia zoosanitaria; y c) reiterar la importancia que reviste el uso de pruebas de diagnóstico no solo validadas, sino también adaptadas específicamente a cada especie, para las labores de vigilancia y estudio de brotes. Lo más probable es que a corto y medio plazo las enfermedades zoonóticas, ya sean emergentes o endémicas, sigan constituyendo una amenaza para la salud mundial. Gracias a numerosos ejemplos del pasado reciente se ha ido constituyendo un buen conocimiento de los factores que propician la aparición de enfermedades infecciosas. Para disponer de un eficaz sistema de vigilancia de enfermedades endémicas hay una serie de requisitos previos indispensables: utilización compartida de los recursos de diagnóstico entre los sectores de la salud humana y la sanidad animal; intercambio de los datos de vigilancia sanitaria y de vigilancia zoosanitaria; adquisición de competencias para interpretar esos datos; y buen conocimiento de las cuestiones ligadas a la validación de pruebas de diagnóstico y a la interpretación de los datos que arrojan. Si los profesionales de la salud humana y la sanidad animal conocen debidamente los patrones epidemiológicos de las enfermedades endémicas, estarán en condiciones de detectar con más celeridad la presencia de enfermedades emergentes que constituyan una amenaza.

Early Warning Diagnostics for Emerging Infectious Diseases in Developing into Late-Stage Pandemics.

The spread of infectious diseases due to travel and trade can be seen throughout history, whether from early settlers or traveling businessmen. Increased globalization has allowed infectious diseases to quickly spread to different parts of the world and cause widespread infection. Posthoc analysis of more recent outbreaks-SARS, MERS, swine flu, and COVID-19-has demonstrated that the causative viruses were circulating through populations for days or weeks before they were first detected, allowing disease to spread before quarantines, contact tracing, and travel restrictions could be implemented. Earlier detection of future novel pathogens could decrease the time before countermeasures are enacted. In this Account, we examined a variety of novel technologies from the past 10 years that may allow for earlier detection of infectious diseases. We have arranged these technologies chronologically from pre-human predictive technologies to population-level screening tools. The earliest detection methods utilize artificial intelligence to analyze factors such as climate variation and zoonotic spillover as well as specific species and geographies to identify where the infection risk is high. Artificial intelligence can also be used to monitor health records, social media, and various publicly available data to identify disease outbreaks faster than traditional epidemiology. Secondary to predictive measures is monitoring infection in specific sentinel animal species, where domestic animals or wildlife are indicators of potential disease hotspots. These hotspots inform public health officials about geographic areas where infection risk in humans is high. Further along the timeline, once the disease has begun to infect humans, wastewater epidemiology can be used for unbiased sampling of large populations. This method has already been shown to precede spikes in COVID-19 diagnoses by 1 to 2 weeks. As total infections increase in humans, bioaerosol sampling in high-traffic areas can be used for disease monitoring, such as within an airport. Finally, as disease spreads more quickly between humans, rapid diagnostic technologies such as lateral flow assays and nucleic acid amplification become very important. Minimally invasive point-of-care methods can allow for quick adoption and use within a population. These individual diagnostic methods then transfer to higher-throughput methods for more intensive population screening as an infection spreads. There are many promising early warning technologies being developed. However, no single technology listed herein will prevent every future outbreak. A combination of technologies from across our infection timeline would offer the most benefit in preventing future widespread disease outbreaks and pandemics.

Nowcasting epidemics of novel pathogens: lessons from COVID-19.

Epidemic nowcasting broadly refers to assessing the current state by understanding key pathogenic, epidemiologic, clinical and socio-behavioral characteristics of an ongoing outbreak. Its primary objective is to provide situational awareness and inform decisions on control responses. In the event of large-scale sustained emergencies, such as the COVID-19 pandemic, scientists need to constantly update their aims and analytics with respect to the rapidly evolving emergence of new questions, data and findings in order to synthesize real-time evidence for policy decisions. In this Perspective, we share our views on the functional aims, rationale, data requirements and challenges of nowcasting at different stages of an epidemic, drawing on the ongoing COVID-19 experience. We highlight how recent advances in the computational and laboratory sciences could be harnessed to complement traditional approaches to enhance the scope, timeliness, reliability and utility of epidemic nowcasting.

Emerging Fungal Infections.

Various uncommon fungal pathogens have been increasingly identified as causes of disseminated and invasive fungal disease (IFD) worldwide. Growing recognition and clinical knowledge of these emerging fungal pathogens has occurred through improved molecular diagnostics, nucleic sequence databases, and taxonomic reclassification of medically significant fungi. However, emerging fungal diseases carry significant morbidity and mortality and, due to a paucity of published literature, the collective clinical experience with these fungi is often limited. In this review, we focus on unusual emerging fungal pathogens not extensively covered elsewhere in this issue of Infectious Diseases Clinics of North America.

Mitigating Future Respiratory Virus Pandemics: New Threats and Approaches to Consider.

Despite many recent efforts to predict and control emerging infectious disease threats to humans, we failed to anticipate the zoonotic viruses which led to pandemics in 2009 and 2020. The morbidity, mortality, and economic costs of these pandemics have been staggering. We desperately need a more targeted, cost-efficient, and sustainable strategy to detect and mitigate future zoonotic respiratory virus threats. Evidence suggests that the transition from an animal virus to a human pathogen is incremental and requires a considerable number of spillover events and considerable time before a pandemic variant emerges. This evolutionary view argues for the refocusing of public health resources on novel respiratory virus surveillance at human-animal interfaces in geographical hotspots for emerging infectious diseases. Where human-animal interface surveillance is not possible, a secondary high-yield, cost-efficient strategy is to conduct novel respiratory virus surveillance among pneumonia patients in these same hotspots. When novel pathogens are discovered, they must be quickly assessed for their human risk and, if indicated, mitigation strategies initiated. In this review, we discuss the most common respiratory virus threats, current efforts at early emerging pathogen detection, and propose and defend new molecular pathogen discovery strategies with the goal of preempting future pandemics.

Ocular manifestations of emerging viral diseases.

Emerging infectious diseases (EIDs) are an increasing threat to public health on a global scale. In recent times, the most prominent outbreaks have constituted RNA viruses, spreading via droplets (COVID-19 and Influenza A H1N1), directly between humans (Ebola and Marburg), via arthropod vectors (Dengue, Zika, West Nile, Chikungunya, Crimean Congo) and zoonotically (Lassa fever, Nipah, Rift Valley fever, Hantaviruses). However, specific approved antiviral therapies and vaccine availability are scarce, and public health measures remain critical. Patients can present with a spectrum of ocular manifestations. Emerging infectious diseases should therefore be considered in the differential diagnosis of ocular inflammatory conditions in patients inhabiting or returning from endemic territories, and more general vigilance is advisable in the context of a global pandemic. Eye specialists are in a position to facilitate swift diagnosis, improve clinical outcomes, and contribute to wider public health efforts during outbreaks. This article reviews those emerging viral diseases associated with reports of ocular manifestations and summarizes details pertinent to practicing eye specialists.

Utility of Proteomics in Emerging and Re-Emerging Infectious Diseases Caused by RNA Viruses.

Emerging and re-emerging infectious diseases due to RNA viruses cause major negative consequences for the quality of life, public health, and overall economic development. Most of the RNA viruses causing illnesses in humans are of zoonotic origin. Zoonotic viruses can directly be transferred from animals to humans through adaptation, followed by human-to-human transmission, such as in human immunodeficiency virus (HIV), severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and, more recently, SARS coronavirus 2 (SARS-CoV-2), or they can be transferred through insects or vectors, as in the case of Crimean-Congo hemorrhagic fever virus (CCHFV), Zika virus (ZIKV), and dengue virus (DENV). At the present, there are no vaccines or antiviral compounds against most of these viruses. Because proteins possess a vast array of functions in all known biological systems, proteomics-based strategies can provide important insights into the investigation of disease pathogenesis and the identification of promising antiviral drug targets during an epidemic or pandemic. Mass spectrometry technology has provided the capacity required for the precise identification and the sensitive and high-throughput analysis of proteins on a large scale and has contributed greatly to unravelling key protein-protein interactions, discovering signaling networks, and understanding disease mechanisms. In this Review, we present an account of quantitative proteomics and its application in some prominent recent examples of emerging and re-emerging RNA virus diseases like HIV-1, CCHFV, ZIKV, and DENV, with more detail with respect to coronaviruses (MERS-CoV and SARS-CoV) as well as the recent SARS-CoV-2 pandemic.

Potential role of viral metagenomics as a surveillance tool for the early detection of emerging novel pathogens.

Since the early times, human beings have always been faced with deadly microbial infections, both bacterial and viral. Pathogens such as viruses are always evolving owing to the processes of antigenic shift and drift. Such viral evolution results in the emergence of new types and serovars that prove deadly for humans-like influenza pandemics, severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). The pandemic of novel coronavirus SARS-CoV-2 is the recent example. It has resulted in a great loss of human lives and a serious burden on economy across the globe. To counter such situations, a system should exist for the early detection of emerging viral pathogens. This will help prevent possible outbreaks and save human lives. Most of such deadly novel viruses and viral outbreaks are known to be originated from animal hosts. Regular monitoring of potential hot spots of such emerging microbes, such as zoos and animal markets, through metagenomics could help assess the presence of new viruses and pathogens. In this review, we focus on the potential of viral metagenomics and propose a surveillance system based on it for the early detection and hence prevention of such emerging viral infections.

Laboratory diagnosis of emerging human coronavirus infections - the state of the art.

The three unprecedented outbreaks of emerging human coronavirus (HCoV) infections at the beginning of the twenty-first century have highlighted the necessity for readily available, accurate and fast diagnostic testing methods. The laboratory diagnostic methods for human coronavirus infections have evolved substantially, with the development of novel assays as well as the availability of updated tests for emerging ones. Newer laboratory methods are fast, highly sensitive and specific, and are gradually replacing the conventional gold standards. This presentation reviews the current laboratory methods available for testing coronaviruses by focusing on the coronavirus disease 2019 (COVID-19) outbreak going on in Wuhan. Viral pneumonias typically do not result in the production of purulent sputum. Thus, a nasopharyngeal swab is usually the collection method used to obtain a specimen for testing. Nasopharyngeal specimens may miss some infections; a deeper specimen may need to be obtained by bronchoscopy. Alternatively, repeated testing can be used because over time, the likelihood of the SARS-CoV-2 being present in the nasopharynx increases. Several integrated, random-access, point-of-care molecular devices are currently under development for fast and accurate diagnosis of SARS-CoV-2 infections. These assays are simple, fast and safe and can be used in the local hospitals and clinics bearing the burden of identifying and treating patients.

Data sharing during COVID-19 pandemic: what to take away.

INTRODUCTION: In light of the viral outbreak of SARS-CoV-2 that monopolized the focus of the scientific community and general public alike for the past 6 months, one of the greatest contributors in the battle against this pandemic was the international sharing of information. Whether regarding the viral genome, incubation periods, method of transmission, symptoms, dangerous behaviors, age groups at risk, all information was valuable, all data was shared as soon as possible. AREAS COVERED: Considering that the most severely impacted group of patients are already suffering from other conditions, accessing the impact that metabolic associated fatty liver disease (MAFLD), obesity, and diabetes has on patients by sharing information between different healthcare facilities is of vital importance. However, the value behind open information sharing would remain significant even without a viral outbreak and should there be a more efficient infrastructure in place, the global exchange of data can become more practical and less arduous. EXPERT OPINION: Since the sharing of data by individual researchers is often motivated by personal benefits, this observed international collaboration is conditional at best, and the widespread misinformation during this pandemic could be an indication of a certain lack of consensus within the scientific community itself.