Semi-infectious particles contribute substantially to influenza virus within-host dynamics when infection is dominated by spatial structure

Influenza is an ribonucleic acid virus with a genome that comprises eight segments. Experiments show that the vast majority of virions fail to express one or more gene segments and thus cannot cause a productive infection on their own. These particles, called semi-infectious particles (SIPs), can induce virion production through complementation when multiple SIPs are present in an infected cell. Previous within-host influenza models did not explicitly consider SIPs and largely ignore the potential effects of coinfection during virus infection. Here, we constructed and analyzed two distinct models explicitly keeping track of SIPs and coinfection: one without spatial structure and the other implicitly considering spatial structure. While the model without spatial structure fails to reproduce key aspects of within-host influenza virus dynamics, we found that the model implicitly considering the spatial structure of the infection process makes predictions that are consistent with biological observations, highlighting the crucial role that spatial structure plays during an influenza infection. This model predicts two phases of viral growth prior to the viral peak: a first phase driven by fully infectious particles at the initiation of infection followed by a second phase largely driven by coinfections of fully infectious particles and SIPs. Fitting this model to two sets of data, we show that SIPs can contribute substantially to viral load during infection. Overall, the model provides a new interpretation of the in vivo exponential viral growth observed in experiments and a mechanistic explanation for why the production of large numbers of SIPs does not strongly impede viral growth. Being simple and predictive, our model framework serves as a useful tool to understand coinfection dynamics in spatially structured acute viral infections.

The impact of pandemics on labour organization: insights from an Italian company archive during the Spanish Flu

In this paper, we discuss the classical modelling approach of pandemics as a negative labour shock. We perform an archival analysis of one of the largest Italian banks (Credito Italiano) during the First World War - Spanish Flu period (1914-1920). In particular, we scrutinise the circulars that the central management of the bank sent out to the local branches, with the aim to assess whether the Spanish Flu has been perceived by contemporaries as an event seriously affecting personnel management. Though restricted to a single case-study, archival evidence does not support the existence of a remarkable negative labour supply shock affecting personnel management because of the Spanish Flu pandemic. Other war-related events probably increased the system's resilience.

Recent development of microfluidics-based platforms for respiratory virus detection

With the global outbreak of SARS-CoV-2, the inadequacies of current detection technology for respiratory viruses have been recognized. Rapid, portable, accurate, and sensitive assays are needed to expedite diagnosis and early intervention. Conventional methods for detection of respiratory viruses include cell culture-based assays, serological tests, nucleic acid detection (e.g., RT-PCR), and direct immunoassays. However, these traditional methods are often time-consuming, labor-intensive, and require laboratory facilities, which cannot meet the testing needs, especially during pandemics of respiratory diseases, such as COVID-19. Microfluidics-based techniques can overcome these demerits and provide simple, rapid, accurate, and cost-effective analysis of intact virus, viral antigen/antibody, and viral nucleic acids. This review aims to summarize the recent development of microfluidics-based techniques for detection of respiratory viruses. Recent advances in different types of microfluidic devices for respiratory virus diagnostics are highlighted, including paper-based microfluidics, continuous-flow microfluidics, and droplet-based microfluidics. Finally, the future development of microfluidic technologies for respiratory virus diagnostics is discussed.

SARS-CoV-2 versus Influenza A Virus: Characteristics and Co-Treatments

For three years, the novel coronavirus disease 2019 (COVID-19) pandemic, caused by infection of the SARS-CoV-2 virus, has completely changed our lifestyles and prepared us to live with this novel pneumonia for years to come. Given that pre-existing flu is caused by the influenza A virus, we have begun unprecedently co-coping with two different respiratory diseases at the same time. Hence, we draw a comparison between SARS-CoV-2 and influenza A virus based on the general characteristics, especially the main variants’ history and the distribution of the two viruses. SARS-CoV-2 appeared to mutate more frequently and independently of locations than the influenza A virus. Furthermore, we reviewed present clinical trials on combined management against COVID-19 and influenza in order to explore better solutions against both at the same time.

The Staphylococcus aureus protein IsdA increases SARS CoV-2 replication by modulating JAK-STAT signaling

The Severe Acute Respiratory Syndrome Coronavirus 2 (CoV-2) pandemic has affected millions globally. A significant complication of CoV-2 infection is secondary bacterial co-infection, as seen in approximately 25% of severe cases. The most common organism isolated during co-infection is Staphylococcus aureus. Here, we describe the development of an in vitro co-infection model where both viral and bacterial replication kinetics may be examined. We demonstrate CoV-2 infection does not alter bacterial interactions with host epithelial cells. In contrast, S. aureus enhances CoV-2 replication by 10- to 15-fold. We identify this pro-viral activity is due to the S. aureus iron-regulated surface determinant A (IsdA) protein and demonstrate IsdA modifies host transcription. We find that IsdA alters Janus Kinase - Signal Transducer and Activator of Transcription (JAK-STAT) signaling, by affecting JAK2-STAT3 levels, ultimately leading to increased viral replication. These findings provide key insight into the molecular interactions between host cells, CoV-2 and S. aureus during co-infection.

Lung tissue-resident memory T cells: the gatekeeper to respiratory viral (re)-infection

The discovery of lung tissue-resident memory T (TRM) cells and the elucidation of their function in antiviral immunity have inspired considerable efforts to leverage the power of TRM cells, in defense to the infections and reinfections by respiratory viruses. Here, we have reviewed lung TRM cell identification, molecular regulation, and function after influenza and SARS-CoV-2 infections. Furthermore, we have discussed emerging data on TRM responses induced by systemic and mucosal vaccination strategies. We hope that our current outstanding of TRM cells in this review could provide insights toward the development of vaccines capable of inducing highly efficacious mucosal TRM responses for protection against respiratory viral infections.

The Data Mechanisms of Diagnosis and Intelligence

Diagnosis is a measurement, and so is intelligence. We present a novel visual method to analyze diagnoses. The concept of country health was introduced in a trial to compare the efficiency of two treatments: box plot and pull anti. We found that the pull anti performs better in both accuracy and extent. The box plot is a diagnosis of abnormality using simple up–down symmetry; however, when abnormalities occur in the probability, the symmetry of the structure may be negatively affected. The pull anti checks the asymmetry of the left and right and therefore results in a better analysis. Furthermore, we designed another trial to test the sampling bias and found that an insensible disturbance might lead to statistical self-significance. We thus suggest that extended observations towards certainty are necessary to obtain better diagnoses or intelligence.

SARS-CoV-2 infection of sustentacular cells disrupts olfactory signaling pathways

Loss of olfactory function has been commonly reported in SARS-CoV-2 infections. Recovery from anosmia is not well understood. Previous studies showed that sustentacular cells, and occasionally olfactory sensory neurons (OSNs) in the olfactory epithelium (OE), are infected in SARS-CoV-2-infected patients and experimental animals. Here, we show that SARS-CoV-2 infection of sustentacular cells induces inflammation characterized by infiltration of myeloid cells to the olfactory epithelium and variably increased expression of proinflammatory cytokines. We observed widespread damage to, and loss of cilia on, OSNs, accompanied by downregulation of olfactory receptors and signal transduction molecules involved in olfaction. A consequence of OSN dysfunction was a reduction in the number of neurons in the olfactory bulb expressing tyrosine hydroxylase, consistent with reduced synaptic input. Resolution of the infection, inflammation, and olfactory dysfunction occurred over 3-4 weeks following infection in most but not all animals. We also observed similar patterns of OE infection and anosmia/hyposmia in mice infected with other human coronaviruses such as SARS-CoV and MERS-CoV. Together, these results define the downstream effects of sustentacular cell infection and provide insight into olfactory dysfunction in COVID-19-associated anosmia.

A Traceable Vaccine Supply Management System

Everyone should be vaccinated, but the eligibility and safety of the vaccine are always overlooked by most people. The outbreak of COVID-19 has led many countries to intensify the development and production of the COVID-19 vaccine. and some countries have even required universal vaccination against this epidemic. However, such popularization of vaccination has also exposed various flaws in vaccine management that existed in the past, and vaccinators have become more concerned about the effectiveness of their vaccinations. In this paper, we propose a blockchain-based traceable vaccine management system. First, the system uses smart contracts to store the records generated during the whole process, from vaccine production to vaccination. Second, the proposed scheme uses the Edwards-curve digital signature algorithm (EdDSA) to guarantee the security and integrity of these data. Third, the system participants can access the corresponding data according to their authority to ensure the transparency of the whole system operation process. Finally, this paper will also conduct a security analysis of the whole system to ensure that the system can resist potential attacks by criminals.

Influenza Virus Infection during Pregnancy as a Trigger of Acute and Chronic Complications

Influenza A virus (IAV) infection during pregnancy disrupts maternal and fetal health through biological mechanisms, which are to date poorly characterised. During pregnancy, the viral clearance mechanisms from the lung are sub-optimal and involve hyperactive innate and adaptive immune responses that generate wide-spread inflammation. Pregnancy-related adaptations of the immune and the cardiovascular systems appear to result in delayed recovery post-viral infection, which in turn promotes a prolonged inflammatory phenotype, increasing disease severity, and causing maternal and fetal health problems. This has immediate and long-term consequences for the mother and fetus, with complications including acute cardiopulmonary distress syndrome in the mother that lead to perinatal complications such as intrauterine growth restriction (IUGR), and birth defects; cleft lip, cleft palate, neural tube defects and congenital heart defects. In addition, an increased risk of long-term neurological disorders including schizophrenia in the offspring is reported. In this review we discuss the pathophysiology of IAV infection during pregnancy and its striking similarity to other well-established complications of pregnancy such as preeclampsia. We discuss general features of vascular disease with a focus on vascular inflammation and define the "Vascular Storm" that is triggered by influenza infection during pregnancy, as a pivotal disease mechanism for short and long term cardiovascular complications.

Vulnerability and COVID-19 infection rates: A changing relationship during the first year of the pandemic

In the first year of the COVID-19 pandemic, Spain was one of the worst-hit countries, although not all areas and social groups were affected equally. This study focuses on Malaga, a cosmopolitan tourist destination located on the southern Mediterranean coast that has the sixth largest population in Spain. Specifically, it examines the relationship between multidimensional vulnerability and COVID-19 infection rates across the city's census tracts for the period February 2020 to February 2021. The analysis uses high frequency (daily) data on the accumulated incidence of the disease at 14 days and shows that COVID-19 did not spread symmetrically across the census tracts of Malaga but had a greater impact on the most vulnerable neighbourhoods. However, the pattern of this relationship was not uniform in the period examined, with specific contextual factors driving the higher infection rates across time. Our findings show that pandemic containment regulations cannot overlook vulnerability considerations and universal restrictions to reduce the spread of disease should be supplemented by targeted regulations for specific areas.

Emerging antiviral therapies and drugs for the treatment of influenza

INTRODUCTION

Both vaccines and antiviral drugs represent the mainstay for preventing and treating influenza. However, approved M2 ion channel inhibitors, neuraminidase inhibitors, polymerase inhibitors, and various vaccines cannot meet therapeutic needs because of viral resistance. Thus, the discovery of new targets for the virus or host and the development of more effective inhibitors are essential to protect humans from the influenza virus.

AREAS COVERED

This review summarizes the latest progress in vaccines and antiviral drug research to prevent and treat influenza, providing the foothold for developing novel antiviral inhibitors.

EXPERT OPINION

Vaccines embody the most effective approach to preventing influenza virus infection, and recombinant protein vaccines show promising prospects in developing next-generation vaccines. Compounds targeting the viral components of RNA polymerase, hemagglutinin and nucleoprotein, and the modification of trusted neuraminidase inhibitors are future research directions for anti-influenza virus drugs. In addition, some host factors affect the replication of virus in vivo, which can be used to develop antiviral drugs.

Variant influenza: connecting the missing dots

BACKGROUND

In June 2009, the World Health Organization declared a new pandemic, the 2009 swine influenza pandemic (swine flu). The symptoms of the swine flu pandemic causing strain were comparable to most of the symptoms noted by seasonal influenza.

AREA COVERED

Zoonotic viruses that caused the swine flu pandemic and its preventive measures.

EXPERT OPINION

As per Centers for Disease Control and Prevention (CDC), the clinical manifestations in humans produced by the 2009 H1N1 'swine flu' virus were equivalent to the manifestations caused by related flu strains. The H1N1 vaccination was the most successful prophylactic measure since it prevented the virus from spreading and reduced the intensity and consequences of the pandemic. Despite the availability of therapeutics, the ongoing evolution and appearance of new strains have made it difficult to develop effective vaccines and therapies. Currently, the CDC recommends yearly flu immunization for those aged 6 months and above. The lessons learned from the A/2009/H1N1 pandemic in 2009 indicated that readiness of mankind toward new illnesses caused by mutant viral subtypes that leap from animals to people must be maintained.

Evolution and Control of COVID-19 Epidemic in Hong Kong

Hong Kong SAR has adopted universal masking, social distancing, testing of all symptomatic and high-risk groups for isolation of confirmed cases in healthcare facilities, and quarantine of contacts as epidemiological control measures without city lockdown or border closure. These measures successfully suppressed the community transmission of pre-Omicron SARS-CoV-2 variants or lineages during the first to the fourth wave. No nosocomial SARS-CoV-2 infection was documented among healthcare workers in the first 300 days. The strategy of COVID-19 containment was adopted to provide additional time to achieve population immunity by vaccination. The near-zero COVID-19 situation for about 8 months in 2021 did not enable adequate immunization of the eligible population. A combination of factors was identified, especially population complacency associated with the low local COVID-19 activity, together with vaccine hesitancy. The importation of the highly transmissible Omicron variant kickstarted the fifth wave of COVID-19, which could no longer be controlled by our initial measures. The explosive fifth wave, which was partially contributed by vertical airborne transmission in high-rise residential buildings, resulted in over one million cases of infection. In this review, we summarize the epidemiology of COVID-19 and the infection control and public health measures against the importation and dissemination of SARS-CoV-2 until day 1000.

Influenza A virus reassortment in mammals gives rise to genetically distinct within-host subpopulations

Influenza A virus (IAV) genetic exchange through reassortment has the potential to accelerate viral evolution and has played a critical role in the generation of multiple pandemic strains. For reassortment to occur, distinct viruses must co-infect the same cell. The spatio-temporal dynamics of viral dissemination within an infected host therefore define opportunity for reassortment. Here, we used wild type and synonymously barcoded variant viruses of a pandemic H1N1 strain to examine the within-host viral dynamics that govern reassortment in guinea pigs, ferrets and swine. The first two species are well-established models of human influenza, while swine are a natural host and a frequent conduit for cross-species transmission and reassortment. Our results show reassortment to be pervasive in all three hosts but less frequent in swine than in ferrets and guinea pigs. In ferrets, tissue-specific differences in the opportunity for reassortment are also evident, with more reassortants detected in the nasal tract than the lower respiratory tract. While temporal trends in viral diversity are limited, spatial patterns are clear, with heterogeneity in the viral genotypes detected at distinct anatomical sites revealing extensive compartmentalization of reassortment and replication. Our data indicate that the dynamics of viral replication in mammals allow diversification through reassortment but that the spatial compartmentalization of variants likely shapes their evolution and onward transmission.

Influenza A Virus Exacerbates Group A Streptococcus Infection and Thwarts Anti-Bacterial Inflammatory Responses in Murine Macrophages

Seasonal influenza epidemics pose a considerable hazard for global health. In the past decades, accumulating evidence revealed that influenza A virus (IAV) renders the host vulnerable to bacterial superinfections which in turn are a major cause for morbidity and mortality. However, whether the impact of influenza on anti-bacterial innate immunity is restricted to the vicinity of the lung or systemically extends to remote sites is underexplored. We therefore sought to investigate intranasal infection of adult C57BL/6J mice with IAV H1N1 in combination with bacteremia elicited by intravenous application of Group A Streptococcus (GAS). Co-infection in vivo was supplemented in vitro by challenging murine bone marrow derived macrophages and exploring gene expression and cytokine secretion. Our results show that viral infection of mice caused mild disease and induced the depletion of CCL2 in the periphery. Influenza preceding GAS infection promoted the occurrence of paw edemas and was accompanied by exacerbated disease scores. In vitro co-infection of macrophages led to significantly elevated expression of TLR2 and CD80 compared to bacterial mono-infection, whereas CD163 and CD206 were downregulated. The GAS-inducible upregulation of inflammatory genes, such as Nos2, as well as the secretion of TNFα and IL-1β were notably reduced or even abrogated following co-infection. Our results indicate that IAV primes an innate immune layout that is inadequately equipped for bacterial clearance.

Investigating the trade-off between self-quarantine and forced quarantine provisions to control an epidemic: An evolutionary approach

During a pandemic event like the present COVID-19, self-quarantine, mask-wearing, hygiene maintenance, isolation, forced quarantine, and social distancing are the most effective nonpharmaceutical measures to control the epidemic when the vaccination and proper treatments are absent. In this study, we proposed an epidemiological model based on the SEIR dynamics along with the two interventions defined as self-quarantine and forced quarantine by human behavior dynamics. We consider a disease spreading through a population where some people can choose the self-quarantine option of paying some costs and be safer than the remaining ones. The remaining ones act normally and send to forced quarantine by the government if they get infected and symptomatic. The government pays the forced quarantine costs for individuals, and the government has a budget limit to treat the infected ones. Each intervention derived from the so-called behavior model has a dynamical equation that accounts for a proper balance between the costs for each case, the total budget, and the risk of infection. We show that the infection peak cannot be reduced if the authority does not enforce a proactive (quantified by a higher sensitivity parameter) intervention. While comparing the impact of both self- and forced quarantine provisions, our results demonstrate that the latter is more influential to reduce the disease prevalence and the social efficiency deficit (a gap between social optimum payoff and equilibrium payoff).

Heat Inactivation of Influenza Viruses—Analysis of Published Data and Estimations for Required Decimal Reduction Times for Different Temperatures and Media

(1) Background: Influenza is a viral infection that has claimed many millions of lives over the past 100 years, and there is always a risk that a new influenza virus will emerge and cause another pandemic. One way to reduce such a potential new influenza virus will be heat inactivation. The question in this study is how much the heat sensitivities of previous influenza viruses differ. If they are very similar, it is expected that a new influenza virus can be inactivated with the same heat parameters as previous influenza viruses. (2) Methods: Through a literature search, published heat inactivation results are compiled and analyzed using Arrhenius models and regression equations for decimal reduction times for different temperatures and media determined. (3) Results: There are about 50 studies on heat inactivation of human and avian influenza viruses so far, showing large differences in heat sensitivity of influenza viruses in different media. However, within a single medium the differences between viruses are rather small. (4) Conclusions: At a temperature of 60 °C, previous influenza viruses can be reduced by 4 or more orders of magnitude within approximately 30 min in almost all media, and this is likely to be true for a potential new influenza virus. Further studies, especially on human influenza viruses, would be desirable.

Detection of multiple waves for COVID-19 and its optimal control through media awareness and vaccination: study based on some Indian states

COVID-19 is a highly infectious disease, and in very recent times, it has shown a massive impact throughout the globe. Several countries faced the COVID-19 infection waves multiple times. These later waves are more aggressive than the first wave and drastically impact social and economic factors. We developed a mechanistic model with imperfect lockdown effect, reinfection, transmission variability between symptomatic & asymptomatic, and media awareness to focus on the early detection of multiple waves and their control measures. Using daily COVID-19 cases data from six states of India, we estimated several important model parameters. Moreover, we estimated the home quarantine, community, and basic reproduction numbers. We developed an algorithm to carry out global sensitivity analysis (Sobol) of the parameters that influence the number of COVID-19 waves ( W C ) and the average number of COVID-19 cases in a wave ( A W ). We have identified some critical controlling parameters that mainly influenced W C and A W . Our study also revealed the best COVID-19 control strategy/strategies among vaccination, media awareness, and their combination using an optimal cost-effective study. The detailed analysis suggests that the severity of asymptomatic transmission is around 10% to 29% of that of symptomatic transmission in all six locations. About 1% to 4% of the total population under lockdown may contribute to new COVID-19 infection in all six locations. Optimal cost-effective analysis based on interventions, namely only vaccination (VA), only media awareness (ME), and a combination of vaccination & media (VA+ME), are projected for the period March 14, 2020, to August 31, 2021, for all the six locations. We have found that a large percentage of the population (26% to 45%) must be vaccinated from February 13 to August 31, 2021, to avert an optimal number of COVID-19 cases in these six locations.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11071-022-07887-5.

Tissue resident memory T cells- A new benchmark for the induction of vaccine-induced mucosal immunity

Historically, the gold-standard benchmark for vaccine immunogenicity has been the induction of neutralizing antibodies detectable in the serum of peripheral blood. However, in recent years there has been a new appreciation for the mucosa as an important site for vaccine induced immunity. As a point of first contact, the mucosal tissue represents a major site of immune based detection and restriction of pathogen entry and dissemination. Tissue resident memory T cells (Trm) are one of the critical cell types involved in this early detection and restriction of mucosal pathogens. Following tissue-specific infection or vaccination, Trm lodge themselves within tissues and can perform rapid sensing and alarm functions to control local re-infections, in an effort that has been defined as important for restriction of a number of respiratory pathogens including influenza and respiratory syncytial virus. Despite this characterized importance, only minor attention has been paid to the importance of Trm as a benchmark for vaccine immunogenicity. The purpose of this review is to highlight the functions of Trm with particular emphasis on respiratory infections, and to suggest the inclusion of Trm elicitation as a benchmark for vaccine immunogenicity in animal models, and where possible, human samples.

Pandemic influenza and gender imbalance: Mortality selection before births

This study uses data from the 1918-1920 influenza pandemic in Japan along with newly digitized and complete census records on births and infant deaths to analyze mortality selection in utero. I find that fetal exposure to the influenza pandemic during the first trimester of the pregnancy decreases the proportion of males at birth. The results from mechanism analysis suggest that this decline in male births is associated with the deterioration of fetal and infant health. This result supports a wide range of existing literature on the long-run adverse effects of pandemic influenza.

Antiviral Peptides as Anti-Influenza Agents

Influenza viruses represent a leading cause of high morbidity and mortality worldwide. Approaches for fighting flu are seasonal vaccines and some antiviral drugs. The development of the seasonal flu vaccine requires a great deal of effort, as careful studies are needed to select the strains to be included in each year's vaccine. Antiviral drugs available against Influenza virus infections have certain limitations due to the increased resistance rate and negative side effects. The highly mutative nature of these viruses leads to the emergence of new antigenic variants, against which the urgent development of new approaches for antiviral therapy is needed. Among these approaches, one of the emerging new fields of "peptide-based therapies" against Influenza viruses is being explored and looks promising. This review describes the recent findings on the antiviral activity, mechanism of action and therapeutic capability of antiviral peptides that bind HA, NA, PB1, and M2 as a means of countering Influenza virus infection.

Comparison of COVID-19 and seasonal influenza under different intensities of non-pharmaceutical interventions and vaccine effectiveness

Background

The COVID-19 pandemic has lasted more than 2 years, and the global epidemic prevention and control situation remains challenging. Scientific decision-making is of great significance to people's production and life as well as the effectiveness of epidemic prevention and control. Therefore, it is all the more important to explore its patterns and put forward countermeasures for the pandemic of respiratory infections.

Methods

Modeling of epidemiological characteristics was conducted based on COVID-19 and influenza characteristics using improved transmission dynamics models to simulate the number of COVID-19 and influenza infections in different scenarios in a hypothetical city of 100,000 people. By comparing the infections of COVID-19 and influenza in different scenarios, the impact of the effectiveness of vaccination and non-pharmaceutical interventions (NPIs) on disease trends can be calculated. We have divided the NPIs into three levels according to the degree of restriction on social activities (including entertainment venues, conventions, offices, restaurants, public transport, etc.), with social controls becoming progressively stricter from level 1 to level 3.

Results

In the simulated scenario where susceptible individuals were vaccinated with three doses of COVID-19 coronaVac vaccine, the peak number of severe cases was 26.57% lower than that in the unvaccinated scenario, and the peak number of infection cases was reduced by 10.16%. In the scenario with level three NPIs, the peak number of severe cases was reduced by 7.79% and 15.43%, and the peak number of infection cases was reduced by 12.67% and 28.28%, respectively, compared with the scenarios with NPIs intensity of level 2 and level 1. For the influenza, the peak number of severe cases in the scenario where the entire population were vaccinated was 89.85%, lower than that in the unvaccinated scenario, and the peak number of infections dropped by 79.89%.

Conclusion

The effectiveness of COVID-19 coronaVac vaccine for preventing severe outcomes is better than preventing infection; for the prevention and control of influenza, we recommend influenza vaccination as a priority over strict NPIs in the long term.

Incidence and risk factors for stroke in patients with COVID-19 in the Philippines: An analysis of 10,881 cases

BACKGROUND

While most large studies on the possible association of COVID-19 and stroke were done in high-income countries, only a few studies consisting of small sample populations have been done in low- to middle-income countries like the Philippines.

OBJECTIVES

To determine the risk factors of stroke among hospitalized COVID19 patients in the Philippines; to determine the possible association between these risk factors and stroke among the same cohort; and to determine if there is an association between mortality and stroke in this same group.

METHODOLOGY

We obtained relevant clinical and neurological, including stroke data from the Philippine CORONA study, an observational study involving 10,881 patients with COVID-19 admitted in 37 referral hospitals from all over the Philippines.

RESULTS

The incidence of stroke among patients with COVID-19 was 3.4% (n = 367). There were more deaths among patients with stroke and COVID-19 than those without stroke and COVID-19 (42.2% vs 14.7%, p < 0.01). In addition, more patients with stroke were admitted in the ICU (43.3% vs 15.0%, p < 0.01) regardless of cause. Smoking (OR: 1.5, 95% CI: 1.3 to 1.7, p < 0.0001), hypertension (OR:1.75, 95% CI:1.53 to 1.97, p < 0.0001), presence of heart failure (OR: 1.4, 95% CI: 1.07 to 1.86, p = 0.01), presence of any neurologic co-morbidities (OR: 1.4, 95% CI:1.11 to 1.46, p = 0.004), and history of stroke (OR:2.3, 95% CI:1.82 to 2.97, p < 0.0001) had direct significant correlation with stroke; while being a health care worker (OR: 0.5, 95% CI: 0.33 to 0.70, p < 0.0004) had an inverse significant association with stroke.

CONCLUSION

COVID-19 stroke patients in the Philippines have a higher mortality and ICU admission rates than patients with COVID-19 alone or COVID-19 stroke patients from developed countries. Our cohort has similar cardiovascular and metabolic risk factors to western patients with stroke, highlighting that COVID-19 may only have a small contribution to stroke incidence.

The enigma of the 1889 Russian flu pandemic: A coronavirus?

The "Russian flu", which raged from 1889 to 1894, is considered as the first pandemic of the industrial era for which statistics have been collected. This planetary event started in Turkestan and hit the Russian Empire, before reaching all European countries, the United States of America, and the whole world. Contemporaries were surprised by its high contagiousness as evidenced by attack rates averaging 60% in urban populations, its rapid spread in successive waves circling the globe in a few months by rail and sea, and the tendency of the disease to relapse. Despite its low case-fatality rate (0.10%-0.28%), it is estimated to have caused one million deaths worldwide. On serological grounds, it is generally accepted that the causative agent of Russian influenza was Myxovirus influenzae, the virus identified for all influenza pandemics since the "Spanish flu" of 1918. In light of the Covid-19 pandemic, which has underscored the extraordinary epidemic potential of coronaviruses, this assumption has recently been questioned. Coronaviruses come from wild reservoirs (bats, rodents, birds, …). They induce respiratory symptoms mimicking influenza, possibly leading to respiratory distress with pneumonia. In addition to the Covid-19 pandemic, recent deadly and limited epidemics, such as SARS in 2002 and MERS in 2012, have occurred. Russian influenza presented as an influenza-like syndrome with clinical peculiarities (multivisceral and neurological involvement, skin rash, early iterative relapses), evoking some particularities of Covid-19. Four other coronaviruses circulating in the human population for decades (HCoV-229E, HCoV-NL63, HCoV-OC43, HCoV-HKU1) have been found to be responsible for 15 to 30% of seasonal colds. All of these viruses are of animal origin. Recently, phylogenetic studies have revealed the genetic proximity between a bovine coronavirus BCoV and the human virus HCoV-OC43, indicating that the latter emerged around 1890, at the time of the Russian flu, when an epizootic was raging among cattle throughout Europe. Could the current human virus be the attenuated remnant that appeared after the Russian flu in 1894? Was there a coronavirus pandemic before Covid-19 ?

Differential Recognition of Computationally Optimized H3 Hemagglutinin Influenza Vaccine Candidates by Human Antibodies

Among circulating influenza viruses in humans, H3N2 viruses typically evolve faster than other subtypes and have caused disease in millions of people since emerging in 1968. Computationally optimized broadly reactive antigen (COBRA) technology is one strategy to broaden vaccine-elicited antibody responses among influenza subtypes. In this study, we determined the structural integrity of an H3N2 COBRA hemagglutinin (HA), TJ5, and we probed the antigenic profile of several H3N2 COBRA HAs by assessing recognition of these immunogens by human B cells from seasonally vaccinated human subjects. Of three recently described COBRA H3 HA antigens (TJ5, NG2, and J4), we determined that TJ5 and J4 HA proteins recognize pre-existing B cells more effectively than NG2 HA and a wild-type Hong Kong/4801/2014 protein. We also isolated a panel of 12 H3 HA-specific human monoclonal antibodies (MAbs) and identified that most MAbs recognize both wild-type and COBRA HA proteins and have functional activity against a broad panel of H3N2 viruses. Most MAbs target the receptor-binding site, and one MAb targets the HA stem. MAb TJ5-5 recognizes TJ5 and J4 COBRA HA proteins but has poor recognition of NG2 HA, similar to the global B-cell analysis. We determined a 3.4 Å structure via cryo-electron microscopy of Fab TJ5-5 complexed with the H3 COBRA TJ5, which revealed residues important to the differential binding. Overall, these studies determined that COBRA H3 HA proteins have correct antigenic and structural features, and the proteins are recognized by B cells and MAbs isolated from seasonally vaccinated humans. IMPORTANCE Vaccine development for circulating influenza viruses, particularly for the H3N2 subtype, remains challenging due to consistent antigenic drift. Computationally optimized broadly reactive antigen (COBRA) technology has proven effective for broadening influenza hemagglutinin (HA)-elicited antibody responses compared to wild-type immunogens. Here, we determined the structural features and antigenic profiles of H3 COBRA HA proteins. Two H3 COBRA HA proteins, TJ5 and J4, are better recognized by pre-existing B cells and monoclonal antibodies from the 2017 to 2018 vaccine season compared to COBRA NG2 and a wild-type A/Hong Kong/2014 HA protein. We determined a cryo-electron microscopy (cryo-EM) structure of one MAb that poorly recognizes NG2, MAb TJ5-5, in complex with the TJ5 COBRA HA protein and identified residues critical to MAb recognition. As NG2 is more effective than TJ5 for the recent Hong Kong/2019 virus, these data provide insights into the diminished effectiveness of influenza vaccines across vaccine seasons.

A Historical Review of Military Medical Strategies for Fighting Infectious Diseases: From Battlefields to Global Health

The environmental conditions generated by war and characterized by poverty, undernutrition, stress, difficult access to safe water and food as well as lack of environmental and personal hygiene favor the spread of many infectious diseases. Epidemic typhus, plague, malaria, cholera, typhoid fever, hepatitis, tetanus, and smallpox have nearly constantly accompanied wars, frequently deeply conditioning the outcome of battles/wars more than weapons and military strategy. At the end of the nineteenth century, with the birth of bacteriology, military medical researchers in Germany, the United Kingdom, and France were active in discovering the etiological agents of some diseases and in developing preventive vaccines. Emil von Behring, Ronald Ross and Charles Laveran, who were or served as military physicians, won the first, the second, and the seventh Nobel Prize for Physiology or Medicine for discovering passive anti-diphtheria/tetanus immunotherapy and for identifying mosquito Anopheline as a malaria vector and plasmodium as its etiological agent, respectively. Meanwhile, Major Walter Reed in the United States of America discovered the mosquito vector of yellow fever, thus paving the way for its prevention by vector control. In this work, the military relevance of some vaccine-preventable and non-vaccine-preventable infectious diseases, as well as of biological weapons, and the military contributions to their control will be described. Currently, the civil-military medical collaboration is getting closer and becoming interdependent, from research and development for the prevention of infectious diseases to disasters and emergencies management, as recently demonstrated in Ebola and Zika outbreaks and the COVID-19 pandemic, even with the high biocontainment aeromedical evacuation, in a sort of global health diplomacy.

Miniaturized Raman Instruments for SERS-Based Point-of-Care Testing on Respiratory Viruses

As surface-enhanced Raman scattering (SERS) has been used to diagnose several respiratory viruses (e.g., influenza A virus subtypes such as H1N1 and the new coronavirus SARS-CoV-2), SERS is gaining popularity as a method for diagnosing viruses at the point-of-care. Although the prior and quick diagnosis of respiratory viruses is critical in the outbreak of infectious disease, ELISA, PCR, and RT-PCR have been used to detect respiratory viruses for pandemic control that are limited for point-of-care testing. SERS provides quantitative data with high specificity and sensitivity in a real-time, label-free, and multiplex manner recognizing molecular fingerprints. Recently, the design of Raman spectroscopy system was simplified from a complicated design to a small and easily accessible form that enables point-of-care testing. We review the optical design (e.g., laser wavelength/power and detectors) of commercialized and customized handheld Raman instruments. As respiratory viruses have prominent risk on the pandemic, we review the applications of handheld Raman devices for detecting respiratory viruses. By instrumentation and commercialization advancements, the advent of the portable SERS device creates a fast, accurate, practical, and cost-effective analytical method for virus detection, and would continue to attract more attention in point-of-care testing.

‘Live with the Virus’ Narrative and Pandemic Amnesia in the Governance of COVID-19

Political leaders have commonly used the phrase ‘learn to live with the virus’ to explain to citizens how they should respond to the COVID-19 pandemic. I consider how the ‘live with the virus’ narrative perpetrates pandemic amnesia by refusing what is known about pandemic-related inequities and the strategies that can be used to overcome these effects. Advice to ‘live with the virus’ helps to further austerity public policy and therefore individualises the social and health burdens of post pandemic life. ‘Live with the virus’ asks citizens to look only to their own futures, which are political strategies that might work for privileged individuals who have the capacity to protect their health, but less well for those with limited personal resources. I draw on Esposito’s framing of affirmative biopolitics and scholarship on how excluded communities have built for themselves health-sustaining commons in responses to pandemic threats to health. I argue that creating opportunities for a ‘COVID-19 commons’ that can enlarge capacity for citizenly deliberation on how they have been governed and other pandemic related matters is vital for the development of more ethical and equitable post-pandemic politics.

Association of Pathogen Type With Outcomes of Children Encountering Community-Acquired Pediatric Septic Shock

OBJECTIVES

To determine the association of pathogen type with mortality, functional status, and health-related quality of life (HRQL) among children at hospital discharge/1 month following hospitalization for septic shock.

DESIGN

Secondary database analysis of a prospective, descriptive cohort investigation.

SETTING

Twelve academic PICUs in the United States.

PATIENTS

Critically ill children, 1 month to 18 years old, enrolled from 2013 to 2017.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Association of clinical outcomes with pathogen type was assessed for all patients and separately for surviving patients enrolled in the primary Life After Pediatric Sepsis Evaluation (LAPSE) investigation. For this secondary analysis, we predicted that age would be associated with pathogen type and outcomes, and accordingly, it was incorporated as a confounding variable in primary analyses. Among 389 children enrolled with septic shock, at 1 month/hospital discharge, we observed no statistically significant differences in relation to pathogen types for the composite outcome mortality or substantial new functional morbidity: no causative organism identified (27% [28/103]), pure viral infections (26% [24/91]), pure bacterial/fungal infections (25% [31/125]), and bacterial/fungal+viral coinfections (33% [23/70]). Similarly, we observed no statistically significant differences in relation to pathogen types for the composite outcome, mortality, or persistent serious deterioration of HRQL: no causative organism identified (43% [44/103]), pure viral infections (33% [30/91]), pure bacterial/fungal infections (46% [57/125]), and bacterial/fungal+viral coinfections (43% [30/70]). However, we did identify statistically significant associations between pathogen type and the outcome ventilator-free days ( p = 0.0083) and PICU-free days (0.0238).

CONCLUSIONS

This secondary analysis of the LAPSE database identified no statistically significant association of pathogen type with composite mortality and morbidity outcomes. However, pathogen type may be associated with PICU resources employed to treat sepsis organ dysfunction. Ultimately, pediatric septic shock was frequently associated with adverse patient-centered, clinically meaningful outcomes regardless of infectious disease pathogen type.

Highly Sensitive Flexible SERS-Based Sensing Platform for Detection of COVID-19

COVID-19 continues to spread and has been declared a global emergency. Individuals with current or past infection should be identified as soon as possible to prevent the spread of disease. Surface-enhanced Raman spectroscopy (SERS) is an analytical technique that has the potential to be used to detect viruses at the site of therapy. In this context, SERS is an exciting technique because it provides a fingerprint for any material. It has been used with many COVID-19 virus subtypes, including Deltacron and Omicron, a novel coronavirus. Moreover, flexible SERS substrates, due to their unique advantages of sensitivity and flexibility, have recently attracted growing research interest in real-world applications such as medicine. Reviewing the latest flexible SERS-substrate developments is crucial for the further development of quality detection platforms. This article discusses the ultra-responsive detection methods used by flexible SERS substrate. Multiplex assays that combine ultra-responsive detection methods with their unique biomarkers and/or biomarkers for secondary diseases triggered by the development of infection are critical, according to this study. In addition, we discuss how flexible SERS-substrate-based ultrasensitive detection methods could transform disease diagnosis, control, and surveillance in the future. This study is believed to help researchers design and manufacture flexible SERS substrates with higher performance and lower cost, and ultimately better understand practical applications.

A Tale of Three Recent Pandemics: Influenza, HIV and SARS-CoV-2

Emerging infectious diseases are one of the main threats to public health, with the potential to cause a pandemic when the infectious agent manages to spread globally. The first major pandemic to appear in the 20th century was the influenza pandemic of 1918, caused by the influenza A H1N1 strain that is characterized by a high fatality rate. Another major pandemic was caused by the human immunodeficiency virus (HIV), that started early in the 20th century and remained undetected until 1981. The ongoing HIV pandemic demonstrated a high mortality and morbidity rate, with discrepant impacts in different regions around the globe. The most recent major pandemic event, is the ongoing pandemic of COVID-19, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has caused over 5.7 million deaths since its emergence, 2 years ago. The aim of this work is to highlight the main determinants of the emergence, epidemic response and available countermeasures of these three pandemics, as we argue that such knowledge is paramount to prepare for the next pandemic. We analyse these pandemics’ historical and epidemiological contexts and the determinants of their emergence. Furthermore, we compare pharmaceutical and non-pharmaceutical interventions that have been used to slow down these three pandemics and zoom in on the technological advances that were made in the progress. Finally, we discuss the evolution of epidemiological modelling, that has become an essential tool to support public health policy making and discuss it in the context of these three pandemics. While these pandemics are caused by distinct viruses, that ignited in different time periods and in different regions of the globe, our work shows that many of the determinants of their emergence and countermeasures used to halt transmission were common. Therefore, it is important to further improve and optimize such approaches and adapt it to future threatening emerging infectious diseases.

Design, Synthesis, Molecular Docking Analysis and Biological Evaluations of 4-[(Quinolin-4-yl)amino]benzamide Derivatives as Novel Anti-Influenza Virus Agents

In this study, a series of 4-[(quinolin-4-yl)amino]benzamide derivatives as the novel anti-influenza agents were designed and synthesized. Cytotoxicity assay, cytopathic effect assay and plaque inhibition assay were performed to evaluate the anti-influenza virus A/WSN/33 (H1N1) activity of the target compounds. The target compound G07 demonstrated significant anti-influenza virus A/WSN/33 (H1N1) activity both in cytopathic effect assay (EC₅₀ = 11.38 ± 1.89 µM) and plaque inhibition assay (IC₅₀ = 0.23 ± 0.15 µM). G07 also exhibited significant anti-influenza virus activities against other three different influenza virus strains A/PR/8 (H1N1), A/HK/68 (H3N2) and influenza B virus. According to the result of ribonucleoprotein reconstitution assay, G07 could interact well with ribonucleoprotein with an inhibition rate of 80.65% at 100 µM. Furthermore, G07 exhibited significant activity target PA−PB1 subunit of RNA polymerase according to the PA−PB1 inhibitory activity prediction by the best pharmacophore Hypo1. In addition, G07 was well drug-likeness based on the results of Lipinski’s rule and ADMET prediction. All the results proved that 4-[(quinolin-4-yl)amino]benzamide derivatives could generate potential candidates in discovery of anti-influenza virus agents.

The Spanish Flu

The Spanish flu occurred at the end of the First World War, in disastrous epidemiological conditions on populations exhausted by four years of war. At that time, there were no vaccines, no antibiotics, no oxygen and no resuscitation. It was even thought that the infectious agent was a bacterium. Humanity was poorly equipped to fight against a pandemic that caused 50-100 million deaths. The first palpable signs of the outbreak were the rapidly spreading multiple epidemics among young recruits in the American military training camps in March 1918. The flu then spread to the civilian populations and circled the globe twice, sparing no country, even the most remote islands, in tropical as well as polar climates, evolving in successive waves up until April 1919. The first was mild (lethality 0.21%), the second was lethal (lethality 2-4%), and during the third wave, lethality declined (1%), after which the flu became seasonal, with low lethality (0.1%). Between 20 and 40 years of age, patients often died within a few days of pneumonia, with respiratory distress leading to cyanosis, frequently associated with bacterial superinfection. The influenza virus, Myxovirus influenzae, was first discovered in 1931 by Richard Shope in pigs, and then in 1933 by Wilson Smith, Patrick Laidlaw and Christopher Andrews in humans during a seasonal influenza epidemic in London. In 1943, it was first observed under the electron microscope. Hemagglutinin and neuraminidase, the two main virulence factors, were discovered in the 1940s by George Hirst and Alfred Gottschalk. An RNA virus composed of 13,500 nucleotides in eight segments, it was initially sequenced in the 1980s, when Jeffrey Taubenberger determined the complete nucleotide sequence of the 1918 virus from lung tissue samples from patients who died of influenza. The 1918 H1N1 virus was found to have originated in birds. In 2005, it was successfully resuscitated in cell culture. It is 40,000 times more virulent in primates than the seasonal H1N1 virus. The lethality of the second wave could have been due to mutations in the hemagglutinin H1 gene, which would have resulted in a stronger affinity for α,2-6 galactose sialic acids, the virus' receptors on human epithelial cells. That said, the origin of the Spanish flu virus remains controversial. It probably emerged and circulated in the population before March 1918 in America, although European origin has also been evoked. The high mortality in the 20-40 age group remains an enigma. Some experts point to reduced immune response in patients previously exposed to related viral hemagglutinins during the 1889 pandemic. In any event, even though it concerns a markedly different virus, the history of the Spanish flu sheds light on the difficulties of management during today's pandemic.

Archival influenza virus genomes from Europe reveal genomic variability during the 1918 pandemic

The 1918 influenza pandemic was the deadliest respiratory pandemic of the 20th century and determined the genomic make-up of subsequent human influenza A viruses (IAV). Here, we analyze both the first 1918 IAV genomes from Europe and the first from samples prior to the autumn peak. 1918 IAV genomic diversity is consistent with a combination of local transmission and long-distance dispersal events. Comparison of genomes before and during the pandemic peak shows variation at two sites in the nucleoprotein gene associated with resistance to host antiviral response, pointing at a possible adaptation of 1918 IAV to humans. Finally, local molecular clock modeling suggests a pure pandemic descent of seasonal H1N1 IAV as an alternative to the hypothesis of origination through an intrasubtype reassortment.

For archival pathogens, like pH1N1 Influenza A virus the causative agent of 1918/19 pandemic, only few whole genome sequences exist. Here, Patrono et al. provide one complete and two partial genomes from Germany and find variation in two sites in the nucleoprotein gene in pandemic samples compared to pre-pandemic samples, that are associated with resistance to host antiviral response, pointing at a possible viral adaptation to humans.

The Continued Threat of Influenza A Viruses

Influenza A virus (IAV) is a major cause of respiratory infections worldwide, with the most severe cases occurring in the very young and in elderly individuals [...]

COVID-19: Forecasting confirmed cases and deaths with a simple time series model

Forecasting the outcome of outbreaks as early and as accurately as possible is crucial for decision-making and policy implementations. A significant challenge faced by forecasters is that not all outbreaks and epidemics turn into pandemics, making the prediction of their severity difficult. At the same time, the decisions made to enforce lockdowns and other mitigating interventions versus their socioeconomic consequences are not only hard to make, but also highly uncertain. The majority of modeling approaches to outbreaks, epidemics, and pandemics take an epidemiological approach that considers biological and disease processes. In this paper, we accept the limitations of forecasting to predict the long-term trajectory of an outbreak, and instead, we propose a statistical, time series approach to modelling and predicting the short-term behavior of COVID-19. Our model assumes a multiplicative trend, aiming to capture the continuation of the two variables we predict (global confirmed cases and deaths) as well as their uncertainty. We present the timeline of producing and evaluating 10-day-ahead forecasts over a period of four months. Our simple model offers competitive forecast accuracy and estimates of uncertainty that are useful and practically relevant.

Preventive Measures against Pandemics from the Beginning of Civilization to Nowadays—How Everything Has Remained the Same over the Millennia

As of 27 March 2022, the β-coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 487 million individuals worldwide, causing more than 6.14 million deaths. SARS-CoV-2 spreads through close contact, causing the coronavirus disease 2019 (COVID-19); thus, emergency lockdowns have been implemented worldwide to avoid its spread. COVID-19 is not the first infectious disease that humankind has had to face during its history. Indeed, humans have recurrently been threatened by several emerging pathogens that killed a substantial fraction of the population. Historical sources document that as early as between the 10th and the 6th centuries BCE, the authorities prescribed physical–social isolation, physical distancing, and quarantine of the infected subjects until the end of the disease, measures that strongly resemble containment measures taken nowadays. In this review, we show a historical and literary overview of different epidemic diseases and how the recommendations in the pre-vaccine era were, and still are, effective in containing the contagion.