Emerging infectious diseases and pandemic potential: status quo and reducing risk of global spread

Improving risk analysis of the environmental drivers of the spillover, emergence/re-emergence and spread of Crimean-Congo haemorrhagic fever virus, Marburg virus and Middle East respiratory syndrome coronavirus in the East Africa Region

INTRODUCTION

Emerging and/or re-emerging infectious diseases (EIDs) in the East Africa region are associated with climate change-induced environmental drivers. There is a need for a comprehensive understanding of these environmental drivers and to adopt an integrated risk analysis (IRA) framework for addressing a combination of the biological, environmental and socioeconomic factors that increase population vulnerabilities to EID risks to inform biological risk mitigation and cross-sectoral decision-making. The aim of this integrative review was to identify knowledge gaps and contribute to a holistic understanding about the environmental drivers of Crimean-Congo haemorrhagic fever virus (CCHFV), Marburg virus (MARV) and Middle East respiratory syndrome coronavirus (MERS-CoV) infections in the East Africa Region to improve IRA processes at the environment-animal-human exposure interface.

METHODS

An integrative review search was carried out to identify relevant studies and reports from 2000 to 2024. Searches were conducted in bibliographic databases and global institutional websites. Inclusion criteria were studies and reports (in English) addressing environmental drivers of CCHFV, MARV and MERS-CoV infections across countries in the East Africa region, existing risk frameworks/methodological tools and/or One Health policy recommendations for risk analysis of environmentally driven biological threats.

RESULTS

Of the total number of studies retrieved from database searches (n=18 075) and website searches (n=44), 242 studies and reports combined were included in the review with the majority covering the environmental drivers (n=137), the risk frameworks/methodological tools (n=73) and the policy recommendations (n=32). We identified 10 categories of environmental drivers, four thematic groups of risk frameworks and three categories of policy recommendations. Overall, many of the included records on the risk frameworks/methodological tools expounded on the adoption of ecological niche modelling (ENM) for environmental monitoring of potential transmission pathways of EIDs and other biological threats.

CONCLUSION

This integrative review recommends the adoption of specialised risk mapping approaches such as ENM for environmental monitoring of EIDs under IRA processes. Findings from the review were used for the conceptualisation of an IRA framework for addressing environmentally driven EIDs.

Appraisal of World Health Organization guidelines for priority infectious diseases with potential to cause public health emergencies

OBJECTIVES

To map and assess the quality of guidelines developed by or in partnership with the WHO on infectious diseases with a high risk of causing public health emergencies.

STUDY DESIGN

Cross-sectional audit study.

METHODS

A search of the WHO website and MAGICapp was conducted to identify guidelines on treatment, management, diagnosis, prevention, and surveillance of the WHO's priority list of diseases. When these sources yielded no results, the AI search engine Perplexity was used to expand the search for locally developed WHO partner guidelines. Eligible guidelines were evaluated by three to four appraisers using the Appraisal of Guidelines for Research and Evaluation (AGREE II).

RESULTS

Of the thirty-three guidelines assessed, 73 % were developed by the WHO and 27 % were in partnership with external organisations. Guidelines scored highest in clarity of presentation (73.71 %) but were weakest in editorial independence (26.63 %) and rigour of development (30.05 %). Thirteen guidelines (40 %) were suitable for practical use, with high scores in scope, rigour, and clarity. Fourteen (42 %) were recommended for clinical use with modifications due to insufficient rigour, stakeholder involvement, or editorial independence, whilst six (18 %) were not recommended because of significant methodological flaws. Furthermore, WHO's sole-produced guidelines had higher quality than those developed with external collaborators, except for one partnership. Moreover, no WHO guidelines were found for Crimean-Congo haemorrhagic fever, Lassa fever, Rift Valley fever, Nipah and henipaviral diseases, and SARS.

CONCLUSIONS

The rigour of development and editorial independence of WHO-supported guidelines require improvement, particularly for diseases where comprehensive guidelines are lacking.

Artificial intelligence in respiratory pandemics-ready for disease X? A scoping review

OBJECTIVES

This study aims to identify repeated previous shortcomings in medical imaging data collection, curation, and AI-based analysis during the early phase of respiratory pandemics. Based on the results, it seeks to highlight essential steps for improving future pandemic preparedness.

MATERIALS AND METHODS

We searched PubMed/MEDLINE, Scopus, and Cochrane Reviews for articles published from January 1, 2000, to December 31, 2021, using the terms "imaging" or "radiology" or "radiography" or "CT" or "x-ray" combined with "SARS," "MERS," "H1N1," or "COVID-19." WHO and CDC Databases were searched for case definitions.

RESULTS

Over the last 20 years, the world faced several international health emergencies caused by respiratory diseases such as SARS, MERS, H1N1, and COVID-19. During the same period, major technological advances enabled the analysis of vast amounts of imaging data and the continual development of artificial intelligence algorithms to support radiological diagnosis and prognosis. Timely availability of data proved critical, but so far, data collection attempts were initialized only as individual responses to each outbreak, leading to long delays and hampering unified guidelines and data-driven technology to support the management of pandemic outbreaks. Our findings highlight the multifaceted role of imaging in the early stages of SARS, MERS, H1N1, and COVID-19, and outline possible actions for advancing future pandemic preparedness.

CONCLUSIONS

Advancing international cooperation and action on these topics is essential to create a functional, effective, and rapid counteraction system to future respiratory pandemics exploiting state of the art imaging and artificial intelligence.

KEY POINTS

Question What has been the role of radiological data for diagnosis and prognosis in early respiratory pandemics and what challenges were present? Findings International cooperation is essential to developing an effective rapid response system for future respiratory pandemics using advanced imaging and artificial intelligence. Clinical relevance Strengthening global collaboration and leveraging cutting-edge imaging and artificial intelligence are crucial for developing rapid and effective response systems. This approach is essential for improving patient outcomes and managing future respiratory pandemics more effectively.

Epidemic and Pandemic Preparedness and Response in a Multi-Hazard Context: COVID-19 Pandemic as a Point of Reference

Infectious diseases manifesting in the form of epidemics or pandemics do not only cause devastating impacts on public health systems but also disrupt the functioning of the socio-economic structure. Further, risks associated with pandemics and epidemics become exacerbated with coincident compound hazards. This study aims to develop a framework that captures key elements and components of epidemic and pandemic preparedness and response systems, focusing on a multi-hazard context. A systematic literature review was used to collect data through peer-reviewed journal articles using three electronic databases, and 17 experts were involved in the validation. Epidemiological surveillance and early detection, risk and vulnerability assessments, preparedness, prediction and decision making, alerts and early warning, preventive strategies, control and mitigation, response, and elimination were identified as key elements associated with epidemic and pandemic preparedness and response systems in a multi-hazard context. All elements appear integrated within three interventional phases: upstream, interface, and downstream. A holistic approach focusing on all interventional phases is required for preparedness and response to pandemics and epidemics to counter their cascading and systemic effects. Further, a paradigm shift in the preparedness for multi-hazards during an epidemic or pandemic is essential due to the multiple challenges posed by concurrent hazards.

Associations between frailty, depression and risk of hospitalisation for infection: A large prospective cohort study

BACKGROUND

There is a considerable lack of epidemiological evidence on whether frailty, and frailty comorbid depression could increase the risk of infections in older adults. This study aimed to examine the prospective association between frailty, depression, and risk of infections.

METHODS

A total of 308,892 eligible participants were included. Linked hospital admission records (HES) were used to identify a primary or secondary diagnosis of depression, and infection. Frailty was assessed by Fried frailty phenotype indicators. Cox proportional hazard model was conducted to examine the associated risk between frailty, depression, comorbid frailty and depression and risk of incident infections. Results were stratified by age and gender.

RESULTS

During the follow-up, 74,749 (24.19 %) incident any infection cases were identified, the incidence density of any infection was 17.29/1000 person years. Frailty alone (HR = 1.38, 95 % CI: 1.33-1.43), depression alone (HR = 1.90, 95 % CI: 1.86-1.94), and comorbid frailty and depression (HR = 1.91, 95 % CI: 1.82-1.99) were associated with greater risks of any infections relative to participants with neither frailty nor depression. The associations between frailty alone, depression alone, comorbid frailty and depression, and any infections/most infection subtypes were significant for all age strata in both male and female.

LIMITATIONS

Frailty phenotype was assessed through the adapted Fried criteria, based on a mix of self-reported and objective measurements.

CONCLUSION

Frailty, depression, and comorbid frailty and depression were significantly associated with increased risk of incident infections.

Effectiveness of Rehabilitation Interventions in Individuals With Emerging Virtual Respiratory Tract Infectious Disease: A Systematic Review and Meta-Analysis

OBJECTIVE

Assessing rehabilitation effectiveness for persistent symptoms post-infection with emerging viral respiratory diseases.

DATA SOURCES

Systematic review of seven databases (MEDLINE, EMBASE, Cochrane Library, PEDro, MedRxiv, CNKI, Wanfang) until 30 December 2023.

REVIEW METHODS

Evaluated 101 studies (9593 participants) on respiratory function, exercise capacity, and quality of life. Methodological quality was assessed using the Cochrane Collaboration's Risk of Bias tool for randomized controlled trials (RCTs), the Newcastle-Ottawa Scale (NOS) for observational studies and non-RCTs, and the NIH Quality Assessment Tools for before-after studies.

RESULTS

The most common rehabilitation program combined breathing exercises with aerobic exercise or strength training. Rehabilitation interventions significantly enhanced respiratory function, as evidenced by improvements on the Borg Scale (MD, -1.85; 95% CI, -3.00 to -0.70, low certainty), the mMRC Dyspnea Scale (MD, -0.45; 95% CI, -0.72 to -0.18, low certainty), and the Multidimensional Dyspnoea-12 Scale (MD, -4.64; 95% CI, -6.54 to -2.74, moderate certainty). Exercise capacity also improved, demonstrated by results from the Six-Minute Walk Test (MD, 38.18; 95% CI, 25.33-51.03, moderate certainty) and the Sit-to-Stand Test (MD, 3.04; 95% CI, 1.07-5.01, low certainty).

CONCLUSION

Rehabilitation interventions are promising for survivors of viral respiratory diseases, yet gaps in research remain. Future investigations should focus on personalizing rehabilitation efforts, utilizing remote technology-assisted programs, improving research quality, and identifying specific subgroups for customized rehabilitation strategies to achieve the best outcomes for survivors.

Multidisciplinary approaches to combat emerging viruses: diagnostics, therapeutic gene and vaccine delivery, and nanotherapeutics

Emerging viruses, such as filoviruses (Ebola, Marburg), SARS and MERS coronaviruses, and Zika, pose significant threats to global public health, particularly for individuals with co-morbidities. To address these challenges, this review article explores multidisciplinary strategies for combatting emerging viruses. We emphasize the importance of developing accurate diagnostics, innovative therapeutic gene and vaccine delivery systems, and long-acting nanotherapeutics. These approaches are designed to enhance the safety and efficacy of treatments against these deadly pathogens. We discuss the collaborative efforts of virologists, geneticists, formulation scientists, clinicians, immunologists, and medicinal chemists in advancing these therapeutic modalities.

Nowcasting methods to improve the performance of respiratory sentinel surveillance: lessons from the COVID-19 pandemic

Respiratory diseases, including influenza and coronaviruses, pose recurrent global threats. This study delves into the respiratory surveillance systems, focusing on the effectiveness of SARI sentinel surveillance for total and severe cases incidence estimation. Leveraging data from the COVID-19 pandemic in Chile, we examined 2020-2023 data (a 159-week period) comparing census surveillance results of confirmed cases and hospitalizations, with sentinel surveillance. Our analyses revealed a consistent underestimation of total cases and an overestimation of severe cases of sentinel surveillance. To address these limitations, we introduce a nowcasting model, improving the precision and accuracy of incidence estimates. Furthermore, the integration of genomic surveillance data significantly enhances model predictions. While our findings are primarily focused on COVID-19, they have implications for respiratory virus surveillance and early detection of respiratory epidemics. The nowcasting model offers real-time insights into an outbreak for public health decision-making, using the same surveillance data that is routinely collected. This approach enhances preparedness for emerging respiratory diseases by the development of practical solutions with applications in public health.

The Tokyo 2020 and Beijing 2022 Olympic Games held during the COVID-19 pandemic: planning, outcomes, and lessons learnt

The COVID-19 pandemic profoundly affected all mass gatherings for sporting and religious events, causing cancellation, postponement, or downsizing. On March 24, 2020, the Japanese Government, the Tokyo Organising Committee of the Olympic and Paralympic Games, and the International Olympic Committee decided to postpone the Tokyo 2020 Olympic and Paralympic Games until the summer of 2021. With the emergence of SARS-CoV-2, the potential creation of a superspreading event that would overwhelm the Tokyo health system was perceived as a risk. Even with a delayed start date, an extensive scale of resources, planning, risk assessment, communication, and SARS-CoV-2 testing were required for the Games to be held during the COVID-19 pandemic. The effectiveness of various mitigation and control measures, including the availability of vaccines and the expansion of effective testing options, allowed event organisers and the Japanese Government to successfully host the rescheduled 2020 Tokyo Olympic Games from July 23 to Aug 8, 2021 with robust safety plans in place. In February and March, 2022, Beijing hosted the 2022 Winter Olympic Games as scheduled, built on the lessons learnt from the Tokyo Games, and developed specific COVID-19 countermeasure plans in the context of China's national framework for the plan called Zero COVID. Results from the testing programmes at both the Tokyo and Beijing Games show that the measures put in place were effective at preventing the spread of COVID-19 within the Games, and ensured that neither event became a COVID-19-spreading event. The extensive experience from the Tokyo and Beijing Olympic Games highlights that it is possible to organise mass gatherings during a pandemic, provided that appropriate risk assessment, risk mitigation, and risk communication arrangements are in place, leaving legacies for future mass gatherings, public health, epidemic preparedness, and wider pandemic response.

Trajectory of COVID-19 response and management strategy in China: scientific rationale driven strategy adjustments

The pneumonia caused by novel coronavirus SARS-CoV-2 infection in early December 2019, which was later named coronavirus disease 2019 (COVID-19) by the World Health Organization (WHO), rapidly spread across the world. China has made extraordinary efforts to this unprecedented pandemic, put its response and control at a very high level of infectious disease management (Category B but with measures for Category A), given top priority to the people and their lives, and balanced the pandemic control and socio-economic development. After more than three years' fighting against this disease, China downgraded the management of COVID-19 to Category B infectious disease on January 8, 2023 and the WHO declared the end of public health emergency on May 5, 2023. However, the ending of pandemic does not mean that the disease is no longer a health threat. Experiences against COVID-19 from China and the whole world should be learned to prepare well for the future public health emergencies. This article gives a systematic review of the trajectory of COVID-19 development in China, summarizes the critical policy arrangements and provides evidence for the adjustment during policy making process, so as to share experiences with international community and contribute to the global health for all humanity.

Surveillance and response strategies for zoonotic diseases: a comprehensive review

Out of all emerging infectious diseases, approximately 75% are of zoonotic origin, with their source often traced back to animals. The emergence of zoonoses is driven by a complex interplay between anthropogenic, genetic, ecological, socioeconomic, and climatic factors. This intricate web of influences poses significant challenges for the prediction and prevention of zoonotic outbreaks. Effective coordination and collaboration among the animal, human, and environmental health sectors are essential for proactively addressing major zoonotic diseases. Despite advancements in surveillance and diagnostic practices, the emergence of zoonoses continues to be a pressing global concern. Therefore, prioritizing zoonotic disease surveillance is of paramount importance as part of a comprehensive disease prevention and containment strategy. Furthermore, evaluating existing surveillance systems provides insights into the challenges faced, which can be mitigated through implementation of One Health principles involving relevant stakeholders. To initiate multisectoral partnerships, it is crucial to identify the priorities and core themes of surveillance systems with equitable inputs from various sectors. Strengthening surveillance, promoting data sharing, enhancing laboratory testing capabilities, and fostering joint outbreak responses in both the human and animal health sectors will establish the necessary infrastructure to effectively prevent, predict, detect, and respond to emerging health threats, thereby reinforcing global health security. This review assesses existing surveillance approaches by offering an overview of global agencies engaged in monitoring zoonoses and outlines the essential components required at the human-animal-environment interface for designing comprehensive surveillance networks. Additionally, it discusses the key steps necessary for executing effective zoonotic disease surveillance through a One Health approach, while highlighting the key challenges encountered in establishing such a robust surveillance system.

An overview of avian influenza surveillance strategies and modes

The global epidemic of avian influenza has imposed a substantial disease burden, inciting substantial societal panic and economic losses. The high variability and associated uncertainty of the influenza virus present significant challenges in its prevention and control. As a pivotal strategy for the mitigation of avian influenza, the surveillance network has shown considerable growth at both global and regional levels. This includes the expansion of surveillance coverage, continuous refinement of monitoring content and scope, and rapid enhancement of monitoring quality. Although the ultimate goal of avian influenza surveillance remains uniform, strategies and models vary, reflecting regional or national differences in surveillance system frameworks and their implementation. This review collates and examines the features and experiences of global, regional, and national avian influenza surveillance efforts. Furthermore, it delves into the surveillance system modalities in light of the "One Health" concept, which includes the establishment and enhancement of interdisciplinary and cross-sectoral coordination and cooperation among medical, veterinary, and public health institutions, and the sharing of surveillance information for timely alerts.

Intranasal mRNA-LNP vaccination protects hamsters from SARS-CoV-2 infection

Intranasal vaccination represents a promising approach for preventing disease caused by respiratory pathogens by eliciting a mucosal immune response in the respiratory tract that may act as an early barrier to infection and transmission. This study investigated immunogenicity and protective efficacy of intranasally administered messenger RNA (mRNA)-lipid nanoparticle (LNP) encapsulated vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Syrian golden hamsters. Intranasal mRNA-LNP vaccination systemically induced spike-specific binding [immunoglobulin G (IgG) and IgA] and neutralizing antibodies. Intranasally vaccinated hamsters also had decreased viral loads in the respiratory tract, reduced lung pathology, and prevented weight loss after SARS-CoV-2 challenge. Together, this study demonstrates successful immunogenicity and protection against respiratory viral infection by an intranasally administered mRNA-LNP vaccine.

A fully integrated duplex RT-LAMP device for the detection of viral infections

Respiratory viruses can cause epidemics or pandemics, which are worldwide outbreaks of disease. The severity of these events varies depending on the virus, its characteristics, along with environmental factors. The frequency of epidemics and pandemics caused by respiratory viruses is difficult to predict, but the potential severity of such events underlines the importance of continued monitoring, research, and preparation for emerging infectious diseases. To help improve pandemic preparedness, we created a fully integrated duplex reverse transcription loop-mediated isothermal amplification (RT-LAMP) device targeting two respiratory viruses, influenza A/X-31 virus and bovine coronavirus, as a replacement for SARS-CoV-2. This device can be adapted to any other respiratory virus. In this study, we showed and evaluated a prototype of a microfluidic system, and showed that duplex RT-LAMP can detect and distinguish between the two viruses, with LoDs of 2,000 copies/ml for bovine coronavirus and 200 copies/ml for influenza A/X-31 virus.

The interfaces between One Health and Global Health: A scoping review

One Health (OH) and Global Health (GH) are interconnected perspectives that may contribute to subsidizing GH policies. This scoping review aims to map the volume, nature, and characteristics of studies focused on the interface of OH and GH concepts. We used PubMed (MEDLINE), Embase, Scopus, and The Virtual Health Library (BVS) as the literature data sources for the review. The search strategy used the descriptors "one health", "one health concept", "one medicine", "global health", "international health", and "planetary health" in title and abstracts. We included original research presented as articles in scientific journals, book chapters or conference papers written in English, Spanish, or Portuguese, exploring the intersections between OH and GH concepts, not necessarily as their primary objectives, and published up to December 31, 2021. A total of 1.060 references were identified in the databases after removing duplicates, 139 publications selected for full-text evaluation and 45 publications were included for analysis. All included publications were published between 2011 and 2021, with the highest concentration in 2014 (22.2%). First authors were most frequently from the United States (35.6%), followed by the United Kingdom (15.6%). Overall, seven key themes were identified zoonosis, emerging infectious diseases, antimicrobial resistance, food safety, policy, human resources, and Sustainable Development Goals (SDG). The majority of the included publications employed OH concepts based on the United States Centre for Disease Control and Prevention, and the American Veterinary Medical Association definitions. We observed a common understanding of OH as an area of knowledge involving multiple disciplines and professionals and recognizing that both humans' and animals' health and the environment are interdependent. Although most authors demonstrated that health issues transcend national boundaries, a formal definition for GH was frequently not clearly identified. OH and GH interfaces are essential for accomplishing the 2030 Agenda and its SDG.

Identification of Asymptomatic COVID-19 Patients on Chest CT Images Using Transformer-Based or Convolutional Neural Network-Based Deep Learning Models

Novel coronavirus disease 2019 (COVID-19) has rapidly spread throughout the world; however, it is difficult for clinicians to make early diagnoses. This study is to evaluate the feasibility of using deep learning (DL) models to identify asymptomatic COVID-19 patients based on chest CT images. In this retrospective study, six DL models (Xception, NASNet, ResNet, EfficientNet, ViT, and Swin), based on convolutional neural networks (CNNs) or transformer architectures, were trained to identify asymptomatic patients with COVID-19 on chest CT images. Data from Yangzhou were randomly split into a training set (n = 2140) and an internal-validation set (n = 360). Data from Suzhou was the external-test set (n = 200). Model performance was assessed by the metrics accuracy, recall, and specificity and was compared with the assessments of two radiologists. A total of 2700 chest CT images were collected in this study. In the validation dataset, the Swin model achieved the highest accuracy of 0.994, followed by the EfficientNet model (0.954). The recall and the precision of the Swin model were 0.989 and 1.000, respectively. In the test dataset, the Swin model was still the best and achieved the highest accuracy (0.980). All the DL models performed remarkably better than the two experts. Last, the time on the test set diagnosis spent by two experts-42 min, 17 s (junior); and 29 min, 43 s (senior)-was significantly higher than those of the DL models (all below 2 min). This study evaluated the feasibility of multiple DL models in distinguishing asymptomatic patients with COVID-19 from healthy subjects on chest CT images. It found that a transformer-based model, the Swin model, performed best.

Antibiotic Adjuvants: A Versatile Approach to Combat Antibiotic Resistance

The problem of antibiotic resistance is on the rise, with multidrug-resistant strains emerging even to the last resort antibiotics. The drug discovery process is often stalled by stringent cut-offs required for effective drug design. In such a scenario, it is prudent to delve into the varying mechanisms of resistance to existing antibiotics and target them to improve antibiotic efficacy. Nonantibiotic compounds called antibiotic adjuvants which target bacterial resistance can be used in combination with obsolete drugs for an improved therapeutic regime. The field of "antibiotic adjuvants" has gained significant traction in recent years where mechanisms other than β-lactamase inhibition have been explored. This review discusses the multitude of acquired and inherent resistance mechanisms employed by bacteria to resist antibiotic action. The major focus of this review is how to target these resistance mechanisms by the use of antibiotic adjuvants. Different types of direct acting and indirect resistance breakers are discussed including enzyme inhibitors, efflux pump inhibitors, inhibitors of teichoic acid synthesis, and other cellular processes. The multifaceted class of membrane-targeting compounds with poly pharmacological effects and the potential of host immune-modulating compounds have also been reviewed. We conclude with providing insights about the existing challenges preventing clinical translation of different classes of adjuvants, especially membrane-perturbing compounds, and a framework about the possible directions which can be pursued to fill this gap. Antibiotic-adjuvant combinatorial therapy indeed has immense potential to be used as an upcoming orthogonal strategy to conventional antibiotic discovery.

Public health emergency preparedness for infectious disease emergencies: a scoping review of recent evidence

BACKGROUND

The COVID-19 pandemic continues to demonstrate the risks and profound health impacts that result from infectious disease emergencies. Emergency preparedness has been defined as the knowledge, capacity and organizational systems that governments, response and recovery organizations, communities and individuals develop to anticipate, respond to, or recover from emergencies. This scoping review explored recent literature on priority areas and indicators for public health emergency preparedness (PHEP) with a focus on infectious disease emergencies.

METHODS

Using scoping review methodology, a comprehensive search was conducted for indexed and grey literature with a focus on records published from 2017 to 2020 onward, respectively. Records were included if they: (a) described PHEP, (b) focused on an infectious emergency, and (c) were published in an Organization for Economic Co-operation and Development country. An evidence-based all-hazards Resilience Framework for PHEP consisting of 11 elements was used as a reference point to identify additional areas of preparedness that have emerged in recent publications. The findings were analyzed deductively and summarized thematically.

RESULTS

The included publications largely aligned with the 11 elements of the all-hazards Resilience Framework for PHEP. In particular, the elements related to collaborative networks, community engagement, risk analysis and communication were frequently observed across the publications included in this review. Ten emergent themes were identified that expand on the Resilience Framework for PHEP specific to infectious diseases. Planning to mitigate inequities was a key finding of this review, it was the most frequently identified emergent theme. Additional emergent themes were: research and evidence-informed decision making, building vaccination capacity, building laboratory and diagnostic system capacity, building infection prevention and control capacity, financial investment in infrastructure, health system capacity, climate and environmental health, public health legislation and phases of preparedness.

CONCLUSION

The themes from this review contribute to the evolving understanding of critical public health emergency preparedness actions. The themes expand on the 11 elements outlined in the Resilience Framework for PHEP, specifically relevant to pandemics and infectious disease emergencies. Further research will be important to validate these findings, and expand understanding of how refinements to PHEP frameworks and indicators can support public health practice.

The Threat of Impending Pandemics: A Proactive Approach

The incessant occurrence of devastating health-related events, either on a large scale, such as pandemics, or in a local community in the form of sporadic outbreaks due to infectious agents, warrants a rapid, target-oriented, well-organized response team to combat the demonic consequences. While the world has been recovering from the clutches of the recent disastrous COVID-19 pandemic, the struggles against novel emerging and re-emerging pathogens such as monkeypox (mpox), newer evolving strains of influenza, Ebola, Zika, and the yellow fever virus continue to date. Therefore, a multisectoral, intercontinental, collaborative, interdisciplinary, and highly dedicated approach should always be implemented to achieve optimal health and avert future threats.

Syndromic surveillance system during mass gathering of Panchkroshi Yatra festival, Ujjain, Madhya Pradesh, India

Background

The health implications surrounding a mass gathering pose significant challenges to public health officials. The use of syndromic surveillance provides an ideal method for achieving the public health goals and objectives at such events. In the absence of published reports of systematic documentation of public health preparedness in mass gatherings in the local context, we describe the public health preparedness and demonstrate the operational feasibility of a tablet-based participatory syndromic surveillance among pilgrims during the annual ritual circumambulation- Panchkroshi Yatra.

Methods

A real-time surveillance system was established from 2017-2019 to capture all the health consultations done at the designated points (medical camps) in the Panchkroshi yatra area of the city Ujjain in Madhya Pradesh. We also surveyed a subset of pilgrims in 2017 to gauge satisfaction with the public health measures such as sanitation, water, safety, food, and cleanliness.

Results

In 2019, injuries were reported in the highest proportion (16.7%; 794/4744); most numbers of fever cases (10.6%; 598/5600) were reported in 2018, while 2017 saw the highest number of patient presentations of abdominal pain (7.73%; 498/6435).

Conclusion

Public health and safety measures were satisfactory except for the need for setting up urinals along the fixed route of the circumambulation. A systematic data collection of selected symptoms among yatris and their surveillance through tablet could be established during the panchkroshi yatra, which can complement the existing surveillance for detecting early warning signals. We recommend the implementation of such tablet-based surveillance during such mass gathering events.

Modern vaccine strategies for emerging zoonotic viruses

INTRODUCTION

The significant increase in the emergence of notable zoonotic viruses in the previous decades has become a serious concern to global public health. Ninety-nine percent of infectious diseases have originated from zoonotic viruses with immense potential for dissemination, infecting the susceptible population completely lacking herd immunity.

AREAS COVERED

Zoonotic viruses appear in the last two decades as a major health threat either newly evolved or previously present with elevated prevalence in the last few years are selected to explain their current prophylactic measures. In this review, modern generation vaccines including viral vector vaccines, mRNA vaccines, DNA vaccines, synthetic vaccines, virus-like particles, and plant-based vaccines are discussed with their benefits and challenges. Moreover, the traditional vaccines and their efficacy are also compared with the latest vaccines.

EXPERT OPINION

The emergence and reemergence of viruses that constantly mutate themselves have greatly increased the chance of transmission and immune escape mechanisms in humans. Therefore, the only possible solution to prevent viral infection is the use of vaccines with improved safety profile and efficacy, which becomes the basis of modern generation vaccines.

A call to prioritise prevention: Action is needed to reduce the risk of zoonotic disease emergence

Anthropogenic changes to the environment are facilitating the spread of animal pathogens into human populations. A global focus on detecting and containing emerging infectious diseases has deflected from the need for upstream prevention measures to reduce the risk of pathogen emergence. The drivers of infectious disease emergence have predominantly been considered as environmental and conservation issues and not as risks to human health. There is an opportunity for the UK to take a leadership position on this complex issue. This will require the establishment and maintenance of effective governance and policy mandates. Novel ways of policymaking are needed urgently to achieve three key aims: coordination and collaboration across sectors and government departments, the inclusion of diverse expertise, and the prioritisation of measures directed at prevention.

Nanomaterials to combat SARS-CoV-2: Strategies to prevent, diagnose and treat COVID-19

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the associated coronavirus disease 2019 (COVID-19), which severely affect the respiratory system and several organs and tissues, and may lead to death, have shown how science can respond when challenged by a global emergency, offering as a response a myriad of rapid technological developments. Development of vaccines at lightning speed is one of them. SARS-CoV-2 outbreaks have stressed healthcare systems, questioning patients care by using standard non-adapted therapies and diagnostic tools. In this scenario, nanotechnology has offered new tools, techniques and opportunities for prevention, for rapid, accurate and sensitive diagnosis and treatment of COVID-19. In this review, we focus on the nanotechnological applications and nano-based materials (i.e., personal protective equipment) to combat SARS-CoV-2 transmission, infection, organ damage and for the development of new tools for virosurveillance, diagnose and immune protection by mRNA and other nano-based vaccines. All the nano-based developed tools have allowed a historical, unprecedented, real time epidemiological surveillance and diagnosis of SARS-CoV-2 infection, at community and international levels. The nano-based technology has help to predict and detect how this Sarbecovirus is mutating and the severity of the associated COVID-19 disease, thereby assisting the administration and public health services to make decisions and measures for preparedness against the emerging variants of SARS-CoV-2 and severe or lethal COVID-19.

Partnerships in pandemics: tracing power relations in community engaged scholarship in food systems during COVID-19

The COVID-19 pandemic dramatically disrupted food and educational systems, laying bare institutional inadequacies and structural inequalities. While there has been ample discussion on impacts to the food system and higher education institutions separately, there has been little written through the perspective of people who navigate both. Farmers, researchers, graduate students, chefs, and many stakeholders contribute to community engaged scholarship (CES) in food systems, facing novel obstacles and opportunities with the spread of the pandemic. In this article, I utilize institutional ethnography to center the experiences of the people who participated in or led CES projects during the spring and summer of 2020. The goal of this study is to understand how discourse and texts in the academic institution constrain the reality of CES partnerships and identify areas for change. My findings show that tenure and promotion guidelines and funding opportunities constrain CES partnerships, reducing opportunities for relationship building and discouraging innovative models of participation. Quantified evaluation metrics on grant rubrics and tenure and promotion guidelines privilege individual academic researchers growing large programs, writing lucrative grants for the university, and publishing profusely. However, community-led and decentralized projects were able to adapt to community priorities and sustain research projects during the pandemic. COVID-19 created obstacles to community engagement and allowed for creative approaches to community participation. By restructuring academic evaluation and funding processes to support problem-solving models of CES led by community partners, CES projects can support both academic and community priorities in times of disruption and relative stability.

Impact of Status quo and Resistance to Innovation on the Failure of Detection and Prevention Strategies of Drugs Control Committee in Malaysia

The detection and prevention strategies for drug control have gained significant attention from the drug control committees globally and need the researchers’ attention to improve these strategies worldwide. Hence, this research investigates the impact of the status quo (SQ) and resistance to the innovative nature of the drug control committee on the failure of detection and prevention strategies (FDPS) in Malaysia. This article also analyzes the mediating role of poor team performance (PTP) among the SQ and resistance to the innovative nature of the drug control committee and the FDPS in Malaysia. This study has employed the primary data collection ways such as questionnaires to gather the data from selected respondents. The researchers also applied the SPSS-AMOS to check the association among variables and testing of hypotheses. The results revealed that the SQ and resistance to the innovative nature of the drug control committee have a positive association with the FDPS in Malaysia. The findings have also exposed that PTP significantly mediates between the SQ and resistance to the innovative nature of the drug control committee and the FDPS in Malaysia. This study guides the policymakers that they should develop the policies that eliminate the SQ nature and motivate the committee to adopt innovations that enhance the team performance and success of detection and prevention strategies in Malaysia.

Computational Study of SARS-CoV-2 RNA Dependent RNA Polymerase Allosteric Site Inhibition

The COVID-19 pandemic has caused millions of fatalities since 2019. Despite the availability of vaccines for this disease, new strains are causing rapid ailment and are a continuous threat to vaccine efficacy. Here, molecular docking and simulations identify strong inhibitors of the allosteric site of the SARS-CoV-2 virus RNA dependent RNA polymerase (RdRp). More than one hundred different flavonoids were docked with the SARS-CoV-2 RdRp allosteric site through computational screening. The three top hits were Naringoside, Myricetin and Aureusidin 4,6-diglucoside. Simulation analyses confirmed that they are in constant contact during the simulation time course and have strong association with the enzyme's allosteric site. Absorption, distribution, metabolism, excretion and toxicity (ADMET) data provided medicinal information of these top three hits. They had good human intestinal absorption (HIA) concentrations and were non-toxic. Due to high mutation rates in the active sites of the viral enzyme, these new allosteric site inhibitors offer opportunities to drug SARS-CoV-2 RdRp. These results provide new information for the design of novel allosteric inhibitors against SARS-CoV-2 RdRp.

The future of zoonotic risk prediction

In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from known zoonoses to identify which animal pathogens could someday pose a threat to global health. We synthesize the findings of an interdisciplinary workshop on zoonotic risk technologies to answer the following questions. What are the prerequisites, in terms of open data, equity and interdisciplinary collaboration, to the development and application of those tools? What effect could the technology have on global health? Who would control that technology, who would have access to it and who would benefit from it? Would it improve pandemic prevention? Could it create new challenges? This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.

Considerations for acute care staffing during a pandemic

The increase in interconnectedness of the global population has enabled a highly transmissible virus to spread rapidly around the globe in 2020. The COVID-19 (Coronavirus Disease 2019) pandemic has led to physical, social, and economic repercussions of previously unseen proportions. Although recommendations for pandemic preparedness have been published in response to previous viral disease outbreaks, these guidelines are primarily based on expert opinion and few of them focus on acute care staffing issues. In this review, we discuss how working in acute care medicine during a pandemic can affect the physical and mental health of medical and nursing staff. We provide ideas for limiting staff shortages and creating surge capacity in acute care settings, and strategies for sustainability that can help hospitals maintain adequate staffing throughout their pandemic response.

Asymmetric cross-strain protection for amphibians exposed to a fungal-metabolite prophylactic treatment

Chytridiomycosis, an infectious disease of amphibians caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd), poses an imminent conservation threat. The global spread of Bd has led to mass mortality events in many amphibian species, resulting in at least 90 species' extinctions to date. Exposure to Bd metabolites (i.e. non-infectious antigenic chemicals released by Bd) partially protects frogs during subsequent challenges with live Bd, suggesting its use as a prophylactic treatment and potential vaccine. However, we do not know whether Bd metabolite exposure protects against strains beyond the one used for treatment. To address this knowledge gap, we conducted a 3 × 2 experiment where we exposed adult Cuban treefrogs, Osteopilus septentrionalis, to one of three treatments (Bd metabolites from California-isolated strain JEL-270, Panamá-isolated strain JEL-419, or an artificial spring water control) and then challenged individuals with live Bd from either strain. We found that exposure to Bd metabolites from the California-isolated strain significantly reduced Bd loads of frogs challenged with the live Panamá-isolated strain, but no other treatments were found to confer protective effects. These findings demonstrate asymmetric cross-protection of a Bd metabolite prophylaxis and suggest that work investigating multiple, diverse strains is urgently needed.

Impact of lipid nanoparticle size on mRNA vaccine immunogenicity

Lipid nanoparticles (LNP) are effective delivery vehicles for messenger RNA (mRNA) and have shown promise for vaccine applications. Yet there are no published reports detailing how LNP biophysical properties can impact vaccine performance. In our hands, a retrospective analysis of mRNA LNP vaccine in vivo studies revealed a relationship between LNP particle size and immunogenicity in mice using LNPs of various compositions. To further investigate this, we designed a series of studies to systematically change LNP particle size without altering lipid composition and evaluated biophysical properties and immunogenicity of the resulting LNPs. While small diameter LNPs were substantially less immunogenic in mice, all particle sizes tested yielded a robust immune response in non-human primates (NHP).

Risk management for pandemics: a novel approach: "Hindsight is 20/20" English proverb

The impacts of the current COVID-19 pandemic illustrate the global-level sensitivity to such threats. As understanding of major hazards is generally based on past experience and there is a lack of good historical precedents, approaches and models currently employed to assess risks and guide responses generally lack transparency and are often associated with huge, unspecified uncertainties. Fundamental challenges arise from the strongly coupled nature of the impacts of a pandemic (i.e. not only on health, but also on the entire socio-economic infrastructure) and their long-term evolution with recovery likely to take many years or, potentially, decades. Here, we outline experience gained in risk assessment within the nuclear industry, which has experience facing similar challenges (assessing long-term impacts in a strongly coupled technical system subject to socio-economic constraints), and assess options for knowledge transfer that may help manage future pandemics and other high-impact threats.

What determines city's resilience against epidemic outbreak: evidence from China's COVID-19 experience

By employing the city-level data from China during the spring of 2020, this study investigates the relationship between city-level resilience against the outbreak of COVID-19 pandemics and its affecting factors, including the inflow risk pressure of COVID-19 virus (population inflow from the epicenter), city agglomeration characteristics (urban population density and city size), healthcare resource adequacy, among others. The results reveal that, while managing COVID-19 inflow risk pressure plays a critical role in the city's pandemic disaster resilience, city agglomeration characteristics also matters. To be exact, we find that large and high-density cities with high inter and intra-city mobility flows have more difficulties in containing the epidemic spread, but improving healthcare infrastructure adequacy and urban governance capacity can increase time efficacy of pandemic control and then improve the city's resilience against pandemic. Although our analysis is based on the performance of Chinese cities in the case of COVID-19, the research framework can be applied in understanding COVID-19 control performance of cities in other countries and the findings can be useful for improving health-related urban resilience and sustainability.

Epidemiology of Severe Acute Respiratory Infection (SARI) Cases at a sentinel site in Egypt, 2013-15

BACKGROUND

Sentinel surveillance for severe acute respiratory infection (SARI) in Egypt began in 2006 and occurs at eight sites. Avian influenza is endemic, and human cases of influenza A (H5N1) have been reported annually since 2006. This study aimed to describe the epidemiology of SARI at a major sentinel site in the country.

METHODS

Data included in the study were collected from a major SARI sentinel site in Egypt during three consecutive years (2013-15).

RESULTS

A total of 1254 SARI patients conforming to the WHO case definition were admitted to the sentinel site, representing 5.6% of admitted patients for all causes and 36.6% of acute respiratory infection patients. A total of 99.7% of the patients were tested, and 21.04% tested positive; 48.7% of cases involved influenza A viruses, while 25% involved influenza B. The predominant age group was under 5 years of age, accounting for 443 cases. The seasonality of the influenza data conformed to the Northern Hemisphere pattern.

CONCLUSIONS

The present study's results show that SARI leads to substantial morbidity in Egypt. There is a great need for high-quality data from the SARI surveillance system in Egypt, especially with endemic respiratory threats such as influenza A (H5N1) in Egypt.

A tool for rapid assessment of wildlife markets in the Asia-Pacific Region for risk of future zoonotic disease outbreaks

Decades of warnings that the trade and consumption of wildlife could result in serious zoonotic pandemics have gone largely unheeded. Now the world is ravaged by COVID-19, with tremendous loss of life, economic and societal disruption, and dire predictions of more destructive and frequent pandemics. There are now calls to tightly regulate and even enact complete wildlife trade bans, while others call for more nuanced approaches since many rural communities rely on wildlife for sustenance. Given pressures from political and societal drivers and resource limitations to enforcing bans, increased regulation is a more likely outcome rather than broad bans. But imposition of tight regulations will require monitoring and assessing trade situations for zoonotic risks. We present a tool for relevant stakeholders, including government authorities in the public health and wildlife sectors, to assess wildlife trade situations for risks of potentially serious zoonoses in order to inform policies to tightly regulate and control the trade, much of which is illegal in most countries. The tool is based on available knowledge of different wildlife taxa traded in the Asia-Pacific Region and known to carry highly virulent and transmissible viruses combined with relative risks associated with different broad categories of market types and trade chains.

Risk of Global External Cereals Supply under the Background of the COVID-19 Pandemic: Based on the Perspective of Trade Network

International food trade is an integral part of the food system, and the COVID-19 pandemic has exposed the fragility of external food supplies. Based on the perspective of cereals trade networks (CTN), the pandemic risk is combined with the trade intensity between countries, and an assessment model of cereals external supply risk is constructed that includes external dependence index (EDI), import concentration, and risk of COVID-19 from import countries index (RICI). The results show that: (1) the global main CTN have typical scale-free characteristics, and seven communities are detected under the influence of the core countries; (2) about 60%, 50%, and 70% of countries face risks of medium and above (high and very high) external dependence, concentration of imports, and COVID-19 in the country of origin, respectively. Under the influence of the pandemic, the risk of global external cereal supply index (RECSI) has increased by 65%, and the USA-CAN communities show the highest risk index; (3) the countries with a very high risk are mainly the Pacific island countries and the Latin American and African countries. In addition, Japan, Mexico, South Korea, and 80% of the net food-importing developing countries are at high or very high RECSI levels. Approximately 50% of countries belong to the compound risk type, and many export countries belong to the RICI risk type; (4) global external food supply is subjected to multiple potential threats such as trade interruption, "price crisis", and "payment dilemma". The geographical proximity of community members and the geographical proximity of the pandemic risk is superimposed, increasing the regional risk of external food supply; and (5) this study confirms that the food-exporting countries should avoid the adoption of food export restriction measures and can prevent potential external supply risks from the dimensions of maintaining global food liquidity and promoting diversification of import sources. We believe that our assessment model of cereals external supply risk comprises a useful method for investigations regarding the international CTN or global food crisis under the background of the pandemic.

Implementing epidemic intelligence in the WHO African region for early detection and response to acute public health events

Epidemic intelligence activities are undertaken by the WHO Regional Office for Africa to support member states in early detection and response to outbreaks to prevent the international spread of diseases. We reviewed epidemic intelligence activities conducted by the organisation from 2017 to 2020, processes used, key results and how lessons learned can be used to strengthen preparedness, early detection and rapid response to outbreaks that may constitute a public health event of international concern. A total of 415 outbreaks were detected and notified to WHO, using both indicator-based and event-based surveillance. Media monitoring contributed to the initial detection of a quarter of all events reported. The most frequent outbreaks detected were vaccine-preventable diseases, followed by food-and-water-borne diseases, vector-borne diseases and viral haemorrhagic fevers. Rapid risk assessments generated evidence and provided the basis for WHO to trigger operational processes to provide rapid support to member states to respond to outbreaks with a potential for international spread. This is crucial in assisting member states in their obligations under the International Health Regulations (IHR) (2005). Member states in the region require scaled-up support, particularly in preventing recurrent outbreaks of infectious diseases and enhancing their event-based surveillance capacities with automated tools and processes.

Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade

Introduction: Drug design and discovery of new antivirals will always be extremely important in medicinal chemistry, taking into account known and new viral diseases that are yet to come. Although machine learning (ML) have shown to improve predictions on the biological potential of chemicals and accelerate the discovery of drugs over the past decade, new methods and their combinations have improved their performance and established promising perspectives regarding ML in the search for new antivirals.Areas covered: The authors consider some interesting areas that deal with different ML techniques applied to antivirals. Recent innovative studies on ML and antivirals were selected and analyzed in detail. Also, the authors provide a brief look at the past to the present to detect advances and bottlenecks in the area.Expert opinion: From classical ML techniques, it was possible to boost the searches for antivirals. However, from the emergence of new algorithms and the improvement in old approaches, promising results will be achieved every day, as we have observed in the case of SARS-CoV-2. Recent experience has shown that it is possible to use ML to discover new antiviral candidates from virtual screening and drug repurposing.

Rapid Molecular Diagnostic Sensor Based on Ball-Lensed Optical Fibers

Given the fatal health conditions caused by emerging infectious pathogens, such as severe acute respiratory syndrome coronavirus 2, their rapid diagnosis is required for preventing secondary infections and guiding correct treatments. Although various molecular diagnostic methods based on nucleic acid amplification have been suggested as gold standards for identifying different species, these methods are not suitable for the rapid diagnosis of pathogens owing to their long result acquisition times and complexity. In this study, we developed a rapid bio-optical sensor that uses a ball-lensed optical fiber (BLOF) probe and an automatic analysis platform to precisely diagnose infectious pathogens. The BLOF probe is easy to align and has a high optical sensing sensitivity (1.5-fold) and a large detection range (1.2-fold) for an automatic optical sensing system. Automatic signal processing of up to 250 copies/reaction of DNA of Q-fever-causing Coxiella burnetii was achieved within 8 min. The clinical utility of this system was demonstrated with 18 clinical specimens (9 Q-fever and 9 other febrile disease samples) by measuring the resonant wavelength shift of positive or negative samples for Coxiella burnetii DNA. The results from the system revealed the stable and automatic optical signal measurement of DNA with 100% accuracy. We envision that this BLOF probe-based sensor would be a practical tool for the rapid, simple, and sensitive diagnosis of emerging infectious pathogens.

K-SEIR-Sim: A simple customized software for simulating the spread of infectious diseases

Infectious disease is a great enemy of humankind. The ravages of COVID-19 are leading to profound crises across the world. There is an urgent requirement for analyzing the current pandemic situation, predicting trends over time, and assessing the effectiveness of containment measures. Thus, numerous statistical models, primarily based on the susceptible-exposed-infected-recovered or removed (SEIR) model, have been established. However, these models are highly technical, which are difficult for the public and governing bodies to understand and use. To address this issue, we developed a simple operating software based on our improved K-SEIR model termed as the kernelkernel SEIR simulator (K-SEIR-Sim). This software includes natural propagation parameters, containment measure parameters, and certain characteristic parameters that can deduce the effects of natural propagation and containment measures. Further, the applicability of the proposed software was demonstrated using the example of the COVID-19 outbreak in the United States and the city of Wuhan, China. Operating results verified the potency of the proposed software in evaluating the epidemic situation and human intervention during COVID-19. Importantly, the software can perform real-time, backward-looking, and forward-looking analysis by functioning in data-driven and model-driven ways. All of them have considerable practical values in their applications according to the actual needs of personal use. Conclusively, K-SEIR-Sim is the first simple customized operating software that is highly valuable for the global fight against COVID-19 and other infectious diseases.

Knowing and combating the enemy: a brief review on SARS-CoV-2 and computational approaches applied to the discovery of drug candidates

Since the emergence of the new severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) at the end of December 2019 in China, and with the urge of the coronavirus disease 2019 (COVID-19) pandemic, there have been huge efforts of many research teams and governmental institutions worldwide to mitigate the current scenario. Reaching more than 1,377,000 deaths in the world and still with a growing number of infections, SARS-CoV-2 remains a critical issue for global health and economic systems, with an urgency for available therapeutic options. In this scenario, as drug repurposing and discovery remains a challenge, computer-aided drug design (CADD) approaches, including machine learning (ML) techniques, can be useful tools to the design and discovery of novel potential antiviral inhibitors against SARS-CoV-2. In this work, we describe and review the current knowledge on this virus and the pandemic, the latest strategies and computational approaches applied to search for treatment options, as well as the challenges to overcome COVID-19.

Assessment of Appropriateness of Antimicrobial Therapy in Resource-Constrained Settings: Development and Piloting of a Novel Tool-AmRAT

Inappropriate antimicrobial prescribing is considered to be the leading cause of high burden of antimicrobial resistance (AMR) in resource-constrained lower- and middle-income countries. Under its global action plan, the World Health Organization has envisaged tackling the AMR threat through promotion of rational antibiotic use among prescribers. Given the lack of consensus definitions and other associated challenges, we sought to devise and validate an Antimicrobial Rationality Assessment Tool-AmRAT-for standardizing the assessment of appropriateness of antimicrobial prescribing. A consensus algorithm was developed by a multidisciplinary team consisting of intensivists, internal medicine practitioners, clinical pharmacologists, and infectious disease experts. The tool was piloted by 10 raters belonging to three groups of antimicrobial stewardship (AMS) personnel: Master of Pharmacology (M.Sc.) (n = 3, group A), Doctor of Medicine (MD) residents (n = 3, group B), and DM residents in clinical pharmacology (n = 4, group C) using retrospective patient data from 30 audit and feedback forms collected as part of an existing AMS program. Percentage agreement and the kappa (κ) coefficients were used to measure inter-rater agreements amongst themselves and with expert opinion. Sensitivity and specificity estimates were analyzed comparing their assessments against the gold standard. For the overall assessment of rationality, the mean percent agreement with experts was 76.7% for group A, 68.9% for group B, and 77.5% for group C. The kappa values indicated moderate agreement for all raters in group A (κ 0.47-0.57), and fair to moderate in group B (κ 0.22-0.46) as well as group C (κ 0.37-0.60). Sensitivity and specificity for the same were 80% and 68.6%, respectively. Though evaluated by raters with diverse educational background and variable AMS experience in this pilot study, our tool demonstrated high percent agreement and good sensitivity and specificity, assuring confidence in its utility for assessing appropriateness of antimicrobial prescriptions in resource-constrained healthcare environments.

Oxygen Therapy and Risk of Infection for Health Care Workers Caring for Patients With Viral Severe Acute Respiratory Infection: A Systematic Review and Meta-analysis

STUDY OBJECTIVE

To synthesize the evidence regarding the infection risk associated with different modalities of oxygen therapy used in treating patients with severe acute respiratory infection. Health care workers face significant risk of infection when treating patients with a viral severe acute respiratory infection. To ensure health care worker safety and limit nosocomial transmission of such infection, it is crucial to synthesize the evidence regarding the infection risk associated with different modalities of oxygen therapy used in treating patients with severe acute respiratory infection.

METHODS

MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials were searched from January 1, 2000, to April 1, 2020, for studies describing the risk of infection associated with the modalities of oxygen therapy used for patients with severe acute respiratory infection. The study selection, data extraction, and quality assessment were performed by independent reviewers. The primary outcome measure was the infection of health care workers with a severe acute respiratory infection. Random-effect models were used to synthesize the extracted data.

RESULTS

Of 22,123 citations, 50 studies were eligible for qualitative synthesis and 16 for meta-analysis. Globally, the quality of the included studies provided a very low certainty of evidence. Being exposed or performing an intubation (odds ratio 6.48; 95% confidence interval 2.90 to 14.44), bag-valve-mask ventilation (odds ratio 2.70; 95% confidence interval 1.31 to 5.36), and noninvasive ventilation (odds ratio 3.96; 95% confidence interval 2.12 to 7.40) were associated with an increased risk of infection. All modalities of oxygen therapy generate air dispersion.

CONCLUSION

Most modalities of oxygen therapy are associated with an increased risk of infection and none have been demonstrated as safe. The lowest flow of oxygen should be used to maintain an adequate oxygen saturation for patients with severe acute respiratory infection, and manipulation of oxygen delivery equipment should be minimized.

Preparing for Emerging Zoonotic Viruses

The risk of emergence and spread of novel human pathogens originating from an animal reservoir has increased in the past decades. However, the unpredictable nature of disease emergence makes surveillance and preparedness challenging. Knowledge of general risk factors for emergence and spread, combined with local level data is needed to develop a risk-based methodology for early detection. This involves the implementation of the One Health approach, integrating human, animal and environmental health sectors, as well as social sciences, bioinformatics and more. Recent technical advances, such as metagenomic sequencing, will aid the rapid detection of novel pathogens on the human-animal interface.

Using critical information to strengthen pandemic preparedness: the role of national public health agencies

COVID-19 has demonstrated that most countries' public health systems and capacities are insufficiently prepared to prevent a localised infectious disease outbreak from spreading. Strengthening national preparedness requires National Public Health Institutes (NPHIs), or their equivalent, to overcome practical challenges affecting timely access to, and use of, data that is critical to preparedness. Our situational analysis in collaboration with NPHIs in three countries-Ethiopia, Nigeria and Pakistan-characterises these challenges. Our findings indicate that NPHIs' role necessitates collection and analysis of data from multiple sources that do not routinely share data with public health authorities. Since initiating requests for access to new data sources can be a lengthy process, it is essential that NPHIs are routinely monitoring a broad set of priority indicators that are selected to reflect the country-specific context. NPHIs must also have the authority to be able to request rapid sharing of data from public and private sector organisations during health emergencies and to access additional human and financial resources during disease outbreaks. Finally, timely, transparent and informative communication of synthesised data from NPHIs will facilitate sustained data sharing with NPHIs from external organisations. These actions identified by our analysis will support the availability of robust information systems that allow relevant data to be collected, shared and analysed by NPHIs sufficiently rapidly to inform a timely local response to infectious disease outbreaks in the future.

Initial impacts of global risk mitigation measures taken during the combatting of the COVID-19 pandemic

This paper presents an analysis of risk mitigation measures taken by countries around the world facing the current COVID-19 outbreak. In light of the current pandemic the authors collated and clustered (using harmonised terminology) the risk mitigation measures taken around the globe in the combat to contain, and since March 11, 2020, to limit the spread of the SARS-CoV-2 virus known to cause the Coronavirus disease 2019 (COVID-19). This overview gathers lessons learnt, providing an update on the current knowledge for authorities, sectors and first responders on the effectiveness of said measures, and may allow enhanced prevention, preparedness and response for future outbreaks. Various measures such as mobility restrictions, physical distancing, hygienic measures, socio-economic restrictions, communication and international support mechanisms have been clustered and are reviewed in terms of the nature of the actions taken and their qualitative early-perceived impact. At the time of writing, it is still too premature to express the quantitative effectiveness of each risk mitigation cluster, but it seems that the best mitigation results are reported when applying a combination of voluntary and enforceable measures.