Co-existence and co-infection of influenza A viruses and coronaviruses: Public health challenges

COVID-19 vaccination and concerns regarding vaccine hesitancy after the termination of the zero-COVID policy in China: A nationwide cross-sectional study

COVID-19 vaccine hesitancy remains prevalent globally. However, national data on this issue in the general population after the termination of the zero-COVID policy in China are limited. In March 2023, we conducted a nationwide cross-sectional survey among Chinese adults using a self-administered questionnaire. Descriptive statistics and multivariate logistic regressions were employed. Among 4,966 participants, 43.8% reported COVID-19 vaccine hesitancy following the end of the zero-COVID policy in China. Higher rates of vaccine hesitancy were associated with being married (married: OR 1.36, 95%CI 1.17-1.57; other marital status: OR 1.86, 95%CI 1.36-2.55), working in healthcare (OR 1.64, 95%CI 1.38-1.96), having both minors and older adults in the household (OR 1.45, 95%CI 1.20-1.75), having no minors and older adults in the household (OR 1.44, 95%CI 1.17-1.77), having chronic diseases (OR 1.42, 95%CI 1.23-1.64), experiencing adverse events post-vaccination (OR 1.39, 95%CI 1.19-1.61), and uncertainty about previous COVID-19 infection (OR 1.45, 95%CI 1.13-1.86). Conversely, participants who had received the influenza vaccine in the past three years (OR 0.62, 95%CI 0.54-0.72), had previously taken the COVID-19 vaccine (OR 0.44, 95%CI 0.32-0.59), and had higher confidence in vaccines (OR 0.63, 95%CI 0.60-0.67) were less likely to exhibit hesitancy. Our findings indicate a significant level of vaccine hesitancy, underscoring the urgent need for tailored public health strategies to address vaccine hesitancy and improve uptake post-zero-COVID policy in China. A comprehensive understanding of public concerns and related factors is essential for developing effective vaccine communication strategies.

A multimodal integration pipeline for accurate diagnosis, pathogen identification, and prognosis prediction of pulmonary infections

Pulmonary infections pose formidable challenges in clinical settings with high mortality rates across all age groups worldwide. Accurate diagnosis and early intervention are crucial to improve patient outcomes. Artificial intelligence (AI) has the capability to mine imaging features specific to different pathogens and fuse multimodal features to reach a synergistic diagnosis, enabling more precise investigation and individualized clinical management. In this study, we successfully developed a multimodal integration (MMI) pipeline to differentiate among bacterial, fungal, and viral pneumonia and pulmonary tuberculosis based on a real-world dataset of 24,107 patients. The area under the curve (AUC) of the MMI system comprising clinical text and computed tomography (CT) image scans yielded 0.910 (95% confidence interval [CI]: 0.904-0.916) and 0.887 (95% CI: 0.867-0.909) in the internal and external testing datasets respectively, which were comparable to those of experienced physicians. Furthermore, the MMI system was utilized to rapidly differentiate between viral subtypes with a mean AUC of 0.822 (95% CI: 0.805-0.837) and bacterial subtypes with a mean AUC of 0.803 (95% CI: 0.775-0.830). Here, the MMI system harbors the potential to guide tailored medication recommendations, thus mitigating the risk of antibiotic misuse. Additionally, the integration of multimodal factors in the AI-driven system also provided an evident advantage in predicting risks of developing critical illness, contributing to more informed clinical decision-making. To revolutionize medical care, embracing multimodal AI tools in pulmonary infections will pave the way to further facilitate early intervention and precise management in the foreseeable future.

Emerging contaminants: A One Health perspective

Environmental pollution is escalating due to rapid global development that often prioritizes human needs over planetary health. Despite global efforts to mitigate legacy pollutants, the continuous introduction of new substances remains a major threat to both people and the planet. In response, global initiatives are focusing on risk assessment and regulation of emerging contaminants, as demonstrated by the ongoing efforts to establish the UN's Intergovernmental Science-Policy Panel on Chemicals, Waste, and Pollution Prevention. This review identifies the sources and impacts of emerging contaminants on planetary health, emphasizing the importance of adopting a One Health approach. Strategies for monitoring and addressing these pollutants are discussed, underscoring the need for robust and socially equitable environmental policies at both regional and international levels. Urgent actions are needed to transition toward sustainable pollution management practices to safeguard our planet for future generations.

Landscape of human organoids: Ideal model in clinics and research

In the last decade, organoid research has entered a golden era, signifying a pivotal shift in the biomedical landscape. The year 2023 marked a milestone with the publication of thousands of papers in this arena, reflecting exponential growth. However, amid this burgeoning expansion, a comprehensive and accurate overview of the field has been conspicuously absent. Our review is intended to bridge this gap, providing a panoramic view of the rapidly evolving organoid landscape. We meticulously analyze the organoid field from eight distinctive vantage points, harnessing our rich experience in academic research, industrial application, and clinical practice. We present a deep exploration of the advances in organoid technology, underpinned by our long-standing involvement in this arena. Our narrative traverses the historical genesis of organoids and their transformative impact across various biomedical sectors, including oncology, toxicology, and drug development. We delve into the synergy between organoids and avant-garde technologies such as synthetic biology and single-cell omics and discuss their pivotal role in tailoring personalized medicine, enhancing high-throughput drug screening, and constructing physiologically pertinent disease models. Our comprehensive analysis and reflective discourse provide a deep dive into the existing landscape and emerging trends in organoid technology. We spotlight technological innovations, methodological evolution, and the broadening spectrum of applications, emphasizing the revolutionary influence of organoids in personalized medicine, oncology, drug discovery, and other fields. Looking ahead, we cautiously anticipate future developments in the field of organoid research, especially its potential implications for personalized patient care, new avenues of drug discovery, and clinical research. We trust that our comprehensive review will be an asset for researchers, clinicians, and patients with keen interest in personalized medical strategies. We offer a broad view of the present and prospective capabilities of organoid technology, encompassing a wide range of current and future applications. In summary, in this review we attempt a comprehensive exploration of the organoid field. We offer reflections, summaries, and projections that might be useful for current researchers and clinicians, and we hope to contribute to shaping the evolving trajectory of this dynamic and rapidly advancing field.

Respiratory Viral Coinfections: Insights into Epidemiology, Immune Response, Pathology, and Clinical Outcomes

Respiratory viral coinfections are a global public health threat that poses an economic burden on individuals, families, and healthcare infrastructure. Viruses may coinfect and interact synergistically or antagonistically, or their coinfection may not affect their replication rate. These interactions are specific to different virus combinations, which underlines the importance of understanding the mechanisms behind these differential viral interactions and the need for novel diagnostic methods to accurately identify multiple viruses causing a disease in a patient to avoid misdiagnosis. This review examines epidemiological patterns, pathology manifestations, and the immune response modulation of different respiratory viral combinations that occur during coinfections using different experimental models to better understand the dynamics respiratory viral coinfection takes in driving disease outcomes and severity, which is crucial to guide the development of prevention and treatment strategies.

Influenza and COVID-19 co-infection and vaccine effectiveness against severe cases: a mathematical modeling study

Background

Influenza A virus have a distinctive ability to exacerbate SARS-CoV-2 infection proven by in vitro studies. Furthermore, clinical evidence suggests that co-infection with COVID-19 and influenza not only increases mortality but also prolongs the hospitalization of patients. COVID-19 is in a small-scale recurrent epidemic, increasing the likelihood of co-epidemic with seasonal influenza. The impact of co-infection with influenza virus and SARS-CoV-2 on the population remains unstudied.

Method

Here, we developed an age-specific compartmental model to simulate the co-circulation of COVID-19 and influenza and estimate the number of co-infected patients under different scenarios of prevalent virus type and vaccine coverage. To decrease the risk of the population developing severity, we investigated the minimum coverage required for the COVID-19 vaccine in conjunction with the influenza vaccine, particularly during co-epidemic seasons.

Result

Compared to the single epidemic, the transmission of the SARS-CoV-2 exhibits a lower trend and a delayed peak when co-epidemic with influenza. Number of co-infection cases is higher when SARS-CoV-2 co-epidemic with Influenza A virus than that with Influenza B virus. The number of co-infected cases increases as SARS-CoV-2 becomes more transmissible. As the proportion of individuals vaccinated with the COVID-19 vaccine and influenza vaccines increases, the peak number of co-infected severe illnesses and the number of severe illness cases decreases and the peak time is delayed, especially for those >60 years old.

Conclusion

To minimize the number of severe illnesses arising from co-infection of influenza and COVID-19, in conjunction vaccinations in the population are important, especially priority for the elderly.

Multivalent next generation influenza virus vaccines protect against seasonal and pre-pandemic viruses

Each year, new influenza virus vaccine formulations are generated to keep up with continuously circulating and mutating viral variants. A next-generation influenza virus vaccine would provide long-lasting, broadly-reactive immune protection against current and future influenza virus strains for both seasonal and pre-pandemic viruses. Next generation immunogens were designed using computationally optimized broadly reactive antigen (COBRA) methodology to protect against a broad range of strains over numerous seasons. Novel HA and NA amino acid sequences were derived from multilayered consensus sequence alignment for multiple subtypes of influenza. This multivalent formulation was hypothesized to elicit broadly protective immune responses against both seasonal and pre-pandemic influenza viruses. Mice were vaccinated with multivalent mixtures of HA and NA (H1, H2, H3, H5, H7, N1, N2) proteins. Multivalent COBRA vaccinations elicited antibodies that recognized a broad panel of strains and vaccinated mice were protected against viruses representing multiple subtypes. This is a promising candidate for a universal influenza vaccine that elicits protective immune responses against seasonal and pre-pandemic strains over multiple seasons.

Delivery of nucleic acids using nanomaterials

The increasing number of approved nucleic acid therapeutics demonstrates the potential for the prevention and treatment of a broad spectrum of diseases. This trend underscores the significant impact and promise of nucleic acid-based treatments in the field of medicine. Nevertheless, employing nucleic acids as therapeutics is challenging due to their susceptibility to degradation by nucleases and their unfavorable physicochemical characteristics that hinder delivery into cells. Appropriate vectors play a pivotal role in improving nucleic acid stability and delivering nucleic acids into specific cells. The maturation of delivery systems has led to breakthroughs in the development of therapeutics based on nucleic acids such as DNA, siRNA, and mRNA. Non-viral vectors have gained prominence among the myriad of nanomaterials due to low immunogenicity, ease of manufacturing, and simplicity of cost-effective, large-scale production. Here, we provide an overview of the recent advancements in nanomaterials for nucleic acid delivery. Specifically, we give a detailed introduction to the characteristics of polymers, lipids, and polymer-lipid hybrids, and provide comprehensive descriptions of their applications in nucleic acid delivery. Also, biological barriers, administration routes, and strategies for organ-selective delivery of nucleic acids are discussed. In summary, this review offers insights into the rational design of next-generation delivery vectors for nucleic acid delivery.

Antiviral Treatment in Older Chinese Patient with SARS-CoV-2 and Influenza A Virus Co-Infection: A Case Series

Coronavirus disease 2019 (COVID-19) emergence in late 2019, and wide spread quickly in the world. In China, the COVID-19 epidemic situation entered a low level now. With the arrival of flu season, the number of patients with respiratory symptoms is increasing. We reported three cases of patients who co-infected with SARS-CoV-2 and influenza A virus (IAV), and they were all treated with nirmatrelvir-ritonavir (NMV/r) and baloxavir marboxil. Due to the overlapping clinical features between the two diseases, it is important to identified them and gave the antiviral therapy timely.

Emerging infectious diseases never end: The fight continues

Emerging infectious diseases have accompanied the development of human society while causing great harm to humans, and SARS-CoV-2 was only one in the long list of microbial threats. Many viruses have existed in their natural reservoirs for a very long time, and the spillover of viruses from natural hosts to humans via interspecies transmission serves as the main source of emerging infectious diseases. Widely existing viruses capable of utilizing human receptors to infect human cells in animals signal the possible outbreak of another viral infection in the near future. Extensive and close collaborative surveillance across nations, more effective wildlife trade legislation, and robust investment into applied and basic research will help to combat the possible pandemics of new emerging infectious diseases in the future.

Advances and perspectives in the development of vaccines against highly pathogenic bunyaviruses

Increased human activities around the globe and the rapid development of once rural regions have increased the probability of contact between humans and wild animals. A majority of bunyaviruses are of zoonotic origin, and outbreaks may result in the substantial loss of lives, economy contraction, and social instability. Many bunyaviruses require manipulation in the highest levels of biocontainment, such as Biosafety Level 4 (BSL-4) laboratories, and the scarcity of this resource has limited the development speed of vaccines for these pathogens. Meanwhile, new technologies have been created, and used to innovate vaccines, like the mRNA vaccine platform and bioinformatics-based antigen design. Here, we summarize current vaccine developments for three different bunyaviruses requiring work in the highest levels of biocontainment: Crimean-Congo Hemorrhagic Fever Virus (CCHFV), Rift Valley Fever Virus (RVFV), and Hantaan virus (HTNV), and provide perspectives and potential future directions that can be further explored to advance specific vaccines for humans and livestock.

A seesaw effect between COVID-19 and influenza during 2020-2023 in WHO regions

BACKGROUND

Seasonal influenza activity showed a sharp decline in activity at the beginning of the Corona Virus Disease 2019 (COVID-19) emergence. Whether there is an epidemiological correlation between the dynamic of two respiratory infectious diseases and their future trends needs to be explored.

OBJECTIVE

To assess the correlation between COVID-19 and influenza activity and estimate their upcoming epidemiological trends.

METHODS

We retrospectively described the dynamics of COVID-19 and influenza in six World Health Organization (WHO) regions from January 2020-March 2023, and used the long short-term memory (LSTM) machine learning model to learn potential patterns of previously observed activity to predict trends for the next sixteen weeks. Finally, the past and future correlation in epidemiology between two respiratory infectious diseases was assessed by the Spearman correlation coefficients.

RESULTS

With the emergence of original strain and other severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, influenza activity kept below 10% for more than one year in the six WHO regions. Subsequently, it gradually rose as the Delta activity dropped, but still peaked below Delta. During the Omicron pandemic and the upcoming period, the two increased as each other's activity decreased, becoming interactively dominant more than once and lasting 3-4 months. Correlation analysis showed that COVID-19 and influenza activity presented a predominantly negative correlation with coefficients above -0.3 in WHO regions, especially during the Omicron pandemic and the estimated upcoming period. They had a transient positive correlation in the European Region of WHO (EURO), and the Western Pacific Region of WHO (WPRO) when multiple dominant strains were mixed pandemic.

CONCLUSIONS

Influenza activity and former seasonal epidemiological patterns are shaken by the COVID-19 pandemic. Their activities are moderately and above inversely correlated, oppressing and competing with each other, showing a seesaw effect. In the post-pandemic era of COVID-19, the seesaw trends may be more prominent, prompting the possibility of using one another as early warning signals for future estimates and conducting optimized annual vaccine campaigns.

CLINICALTRIAL

Quantifying the rebound of influenza epidemics after the adjustment of zero-COVID policy in China

The coexistence of coronavirus disease 2019 (COVID-19) and seasonal influenza epidemics has become a potential threat to human health, particularly in China in the oncoming season. However, with the relaxation of nonpharmaceutical interventions (NPIs) during the COVID-19 pandemic, the rebound extent of the influenza activities is still poorly understood. In this study, we constructed a susceptible-vaccinated-infectious-recovered-susceptible (SVIRS) model to simulate influenza transmission and calibrated it using influenza surveillance data from 2018 to 2022. We projected the influenza transmission over the next 3 years using the SVIRS model. We observed that, in epidemiological year 2021-2022, the reproduction numbers of influenza in southern and northern China were reduced by 64.0 and 34.5%, respectively, compared with those before the pandemic. The percentage of people susceptible to influenza virus increased by 138.6 and 57.3% in southern and northern China by October 1, 2022, respectively. After relaxing NPIs, the potential accumulation of susceptibility to influenza infection may lead to a large-scale influenza outbreak in the year 2022-2023, the scale of which may be affected by the intensity of the NPIs. And later relaxation of NPIs in the year 2023 would not lead to much larger rebound of influenza activities in the year 2023-2024. To control the influenza epidemic to the prepandemic level after relaxing NPIs, the influenza vaccination rates in southern and northern China should increase to 53.8 and 33.8%, respectively. Vaccination for influenza should be advocated to reduce the potential reemergence of the influenza epidemic in the next few years.