Spread Of Virus Research Articles

Hand gesture-based automatic door security system using squeeze and excitation residual networks

Viruses can be transmitted due to various aspects; one spreads through airborne droplets or the touch of multiple objects. This can occur in any area, including the entrance to the house or access to a room or deposit box. The spread of viruses that cause diseases like Covid-19 has caused many human casualties, and there is still the possibility of similar conditions appearing in the future. Several things need to be done to reduce the chances of spreading disease due to viruses, including developing contactless security support methods. This paper proposes a security system using hand gesture recognition using squeeze and excitation residual networks (SE-ResNet). This research offers a hand gesture recognition system for an automatic door system using SE-ResNet and the residual network (ResNet).

A hybrid deep learning optimization for predicting the spread of a new emerging infectious disease

<span lang="EN-US">In this study, a novel approach geared toward predicting the estimated number of coronavirus disease (COVID-19) cases was developed. Combining long short-term memory (LSTM) neural networks with particle swarm optimization (PSO) along with grey wolf optimization (GWO) employ hybrid optimization algorithm techniques. This investigation utilizes COVID-19 original data from the Ministry of Health of Indonesia, period 2020-2021. The developed LSTM-PSO-GWO hybrid optimization algorithm can improve the performance and accuracy of predicting the spread of the COVID-19 virus in Indonesia. In initiating LSTM initial weights with weaknesses, using the hybrid optimization algorithm helps overcome these problems and improve model performance. The results of this study suggest that the LSTM-PSO-GWO model can be utilized as an effective and reliable predictive tool to gauge the COVID-19 virus’s spread in Indonesia. </span>

Ventilator-Associated Pneumonia, Ventilator-Associated Events, and Nosocomial Respiratory Viral Infections on the Leeside of the Pandemic.

The COVID-19 pandemic has had an unprecedented impact on population health and hospital operations. Over 7 million patients have been hospitalized for COVID-19 thus far in the United States alone. Mortality rates for hospitalized patients during the first wave of the pandemic were > 30%, but as we enter the fifth year of the pandemic hospitalizations have fallen and mortality rates for hospitalized patients with COVID-19 have plummeted to 5% or less. These gains reflect lessons learned about how to optimize respiratory support for different kinds of patients, targeted use of therapeutics for patients with different manifestations of COVID-19 including immunosuppressants and antivirals as appropriate, and high levels of population immunity acquired through vaccines and natural infections. At the same time, the pandemic has helped highlight some longstanding sources of harm for hospitalized patients including hospital-acquired pneumonia, ventilator-associated events (VAEs), and hospital-acquired respiratory viral infections. We are, thankfully, on the leeside of the pandemic at present; but the large increases in ventilator-associated pneumonia (VAP), VAEs, bacterial superinfections, and nosocomial respiratory viral infections associated with the pandemic beg the question of how best to prevent these complications moving forward. This paper reviews the burden of hospitalization for COVID-19, the intersection between COVID-19 and both VAP and VAEs, the frequency and impact of hospital-acquired respiratory viral infections, new recommendations on how best to prevent VAP and VAEs, and current insights into effective strategies to prevent nosocomial spread of respiratory viruses.

Macrophage- and CD4+ T cell-derived SIV differ in glycosylation, infectivity and neutralization sensitivity.

The human immunodeficiency virus (HIV) envelope protein (Env) mediates viral entry into host cells and is the primary target for the humoral immune response. Env is extensively glycosylated, and these glycans shield underlying epitopes from neutralizing antibodies. The glycosylation of Env is influenced by the type of host cell in which the virus is produced. Thus, HIV is distinctly glycosylated by CD4+ T cells, the major target cells, and macrophages. However, the specific differences in glycosylation between viruses produced in these cell types have not been explored at the molecular level. Moreover, it remains unclear whether the production of HIV in CD4+ T cells or macrophages affects the efficiency of viral spread and resistance to neutralization. To address these questions, we employed the simian immunodeficiency virus (SIV) model. Glycan analysis implied higher relative levels of oligomannose-type N-glycans in SIV from CD4+ T cells (T-SIV) compared to SIV from macrophages (M-SIV), and the complex-type N-glycans profiles seem to differ between the two viruses. Notably, M-SIV demonstrated greater infectivity than T-SIV, even when accounting for Env incorporation, suggesting that host cell-dependent factors influence infectivity. Further, M-SIV was more efficiently disseminated by HIV binding cellular lectins. We also evaluated the influence of cell type-dependent differences on SIV's vulnerability to carbohydrate binding agents (CBAs) and neutralizing antibodies. T-SIV demonstrated greater susceptibility to mannose-specific CBAs, possibly due to its elevated expression of oligomannose-type N-glycans. In contrast, M-SIV exhibited higher susceptibility to neutralizing sera in comparison to T-SIV. These findings underscore the importance of host cell-dependent attributes of SIV, such as glycosylation, in shaping both infectivity and the potential effectiveness of intervention strategies.

Community-Centric Approach: Bhabinkamtibmas Strategies in Mitigating Covid-19 Transmission Within The Cultural Landscape Of Hukurila

The escalation of Covid-19 in Indonesia, including Maluku, underscores varying levels of public awareness concerning health protocols, notably non-compliance with mask-wearing, public gatherings, and other breaches of Covid-19 regulations. This article delves into the pivotal role of Bhabinkamtibmas, an integral part of the police force, in addressing these community issues. The research aims to elucidate Bhabinkamtibmas' strategies in curtailing the virus's spread in the indigenous community of Negeri Hukurila, employing a community-centric approach with qualitative methods like in-depth interviews, observations, and document studies. Research findings highlight Bhabinkamtibmas' active participation in health education, mask distribution, and vaccination programs. They are also integral to the 3T strategy, establishing health centres, innovating health protocols in restaurants, fortifying places of worship, conducting vaccinations, implementing colour zoning, and forming Covid-19 data task forces. Bhabinkamtibmas goes beyond education, fostering security and discipline in the community's adherence to health protocols during the pandemic. Collaborating with Babinsa, they actively curb virus spread through socializing health protocols, participating in evacuations, and overseeing quarantine measures. Despite distinct roles, Bhabinkamtibmas and Babinsa maintain synergy, underscoring the need for community involvement and cross-institutional collaboration for optimal Covid-19 management.

Vibration assisted electron tunnelling in COVID-19 infection using quantum state diffusion.

The spread of the COVID-19 virus has become a global health crisis, and finding effective treatments and preventions is a top priority. The field of quantum biology primarily focuses on energy or charge transfer, with a particular emphasis on photosynthesis. However, there is evidence to suggest that cellular receptors such as olfactory or neural receptors may also use vibration-assisted electron tunnelling to enhance their functions. Quantum tunnelling has also been observed in enzyme activity, which is relevant to the invasion of host cells by the SARS-CoV-2 virus. Additionally, COVID-19 appears to disrupt receptors such as olfactory receptors. These findings suggest that quantum effects could provide new insights into the mechanisms of biological systems and disease, including potential treatments for COVID-19. We have applied the open quantum system approach using Quantum State Diffusion to solve the non-linear stochastic Schrödinger equation (SSE) for COVID-19 virus infection. Our model includes the mechanism when the spike protein of the virus binds with an ACE2 receptor is considered as dimer. These two entities form a system and then coupled with the cell membrane, which is modelled as a set of harmonic oscillators (bath). By simulating the SSE, we find that there is vibration-assisted electron tunnelling happening in certain biological parameters and coupling regimes. Furthermore, our model contributes to the ongoing research to understand the fundamental nature of virus dynamics. It proposes that vibration-assisted electron tunneling could be a molecular phenomenon that augments the lock-and-key process for olfaction. This insight may enhance our understanding of the underlying mechanisms governing virus-receptor interactions and could potentially lead to the development of novel therapeutic strategies.

OPTIMAL CONTROL ANALYSIS OF HIV/AIDS DISEASE SPREAD MODEL IN INDONESIA

The Human Immunodeficiency Virus (HIV) is a contagious virus that weakens the immune system of infected individuals, making them more susceptible to various diseases. These individuals are referred to as those exposed to the AIDS disease, which unfortunately, cannot be cured. To effectively manage AIDS, prevention is crucial in slowing down the spread and growth of the HIV virus. Mathematical modeling can play a significant role in the optimal control of AIDS. In this study, the , , , , model with three different optimal controls were employed. Optimal control involves public health education campaigns, screening, and treatment. The goal is to minimize the number of individuals infected with HIV/AIDS using Pontryagin's Maximum Principle. This principle considers various factors, such as population class coefficients, cost weights, and control variables to determine the most effective approach. The simulation results indicate that counseling control in the exposed population class ( ) yields better outcomes compared to counseling control in the susceptible class and treatment control in the HIV-infected population class. This implies that focusing on educating and counseling individuals who are exposed to HIV can be more efficient in AIDS control than targeting those already infected or at risk. By applying these optimal control strategies, it may be possible to mitigate the impact of HIV/AIDS and improve public health outcomes.

Exploration of the Challenges of COVID-19 from the Perspective of Emergency Medicine Specialists

Background. Emergency physicians are at the forefront of the medical system in the face of the COVID-19 crisis. Identifying the challenges, along with the strategies and effective measures implemented by them in the face of the COVID-19 crisis, can be a roadmap for future crisis management planning. This study aims to explain the challenges faced by emergency physicians regarding COVID-19. Methods. This study is a qualitative content analysis. Data were collected using individual and semistructured interviews. Twenty-seven emergency medical specialists in Fars University of Medical Sciences, Iran, participated in the study by purposive sampling method and were interviewed using semistructured interviews. Results. Participants’ experience of COVID-19 led to the extraction of four main themes, including structural factors, threats to the health of the medical team, fluctuations of extremism and wastage in the face of COVID-19, and the country’s policymaking hierarchy. Conclusions. Emergency physicians face challenges such as structural factors, health threats, extreme fluctuations, and national policymaking. To avoid surprises and threats, they must predict acute scenarios, provide necessary equipment, address skilled manpower shortages, and adopt appropriate management policies. This includes culture-building, cross-sector coordination, planning, and efficient management to prevent virus spread.

The Role of Urban Disaster Risk Management in Major Catastrophic Events: A Case Study of Resilience in Chinese Cities During the COVID-19 Pandemic

The emergence of infectious diseases has historically influenced urban development, necessitating the evolution of urban planning toward greater disaster resilience. The COVID-19 pandemic, in particular, has revealed weaknesses in modern urban planning and governance, emphasizing the need for enhanced urban resilience and disaster risk management. For China, as urban populations continue to grow, urban resilience and disaster risk management have become focal points for urban planners and policymakers, ensuring that cities can rapidly adapt and effectively respond to various challenges. This study summarizes a series of emergency measures adopted by the Chinese government during the COVID-19 pandemic and analyzes their effectiveness. China's response, characterized by early intervention, social distancing, extensive testing, and advanced tracking technologies, effectively curtailed the virus's spread, especially in Hubei province and its capital, Wuhan. Despite these successes, the paper identifies areas where China's urban resilience could be improved, including coordination of emergency plans, information dissemination, and social cohesion, among other aspects, to better confront future challenges.

Plasmonic Imaging of Multivalent NTD-Nucleic Acid Interactions for Broad-Spectrum Antiviral Drug Analysis.

The discovery and identification of broad-spectrum antiviral drugs are of great significance for blocking the spread of pathogenic viruses and corresponding variants of concern. Herein, we proposed a plasmonic imaging-based strategy for assessing the efficacy of potential broad-spectrum antiviral drugs targeting the N-terminal domain of a nucleocapsid protein (NTD) and nucleic acid (NA) interactions. With NTD and NA conjugated gold nanoparticles as core and satellite nanoprobes, respectively, we found that the multivalent binding interactions could drive the formation of core-satellite nanostructures with enhanced scattering brightness due to the plasmonic coupling effect. The core-satellite assembly can be suppressed in the presence of antiviral drugs targeting the NTD-NA interactions, allowing the drug efficacy analysis by detecting the dose-dependent changes in the scattering brightness by plasmonic imaging. By quantifying the changes in the scattering brightness of plasmonic nanoprobes, we uncovered that the constructed multivalent weak interactions displayed a 500-fold enhancement in affinity as compared with the monovalent NTD-NA interactions. We demonstrated the plasmonic imaging-based strategy for evaluating the efficacy of a potential broad-spectrum drug, PJ34, that can target the NTD-NA interactions, with the IC50 as 24.35 and 14.64 μM for SARS-CoV-2 and SARS-CoV, respectively. Moreover, we discovered that ceftazidime holds the potential as a candidate drug to inhibit the NTD-NA interactions with an IC50 of 22.08 μM from molecular docking and plasmonic imaging-based drug analysis. Finally, we validated that the potential antiviral drug, 5-benzyloxygramine, which can induce the abnormal dimerization of nucleocapsid proteins, is effective for SARS-CoV-2, but not effective against SARS-CoV. All these demonstrations indicated that the plasmonic imaging-based strategy is robust and can be used as a powerful strategy for the discovery and identification of broad-spectrum drugs targeting the evolutionarily conserved viral proteins.

High-throughput sequencing for plant virology diagnostics and its potential in plant health certification

High-throughput sequencing (HTS) technologies have revolutionized plant virology through simultaneous detection of mixed viral infections. HTS advances have uncovered and improved understanding of virus biology, ecology, and evolution which is vital for viral disease management. Plant viruses continue to threaten global agricultural productivity and strict quarantine measures are essential to prevent the introduction and spread of virulent viruses around the world. The gradual decrease in HTS operational costs, including improved computational systems and automation through robotics, has facilitated the adoption of this tool for plant diagnostics, including its use in surveillance and quarantine programs. However, the speed of technology advancements and distinct HTS chemistries, laboratory procedures, data management, and bioinformatic analyses have proven challenging. In addition, the lack of viral species reference sequences, compared with the estimated number of distinct viral taxa, makes classification and identification of novel viruses difficult. There is a need for standardized HTS testing, especially within plant health programs. In this review, we consider the application of HTS in plant virology, explore the technical challenges faced and the opportunities for HTS in plant health certification. We propose standards for overcoming current barriers and for ensuring reliable and reproducible results. These efforts will impact global plant health by reducing the risk of introduction and the spread of damaging novel viruses.

Dissemination of influenza B virus to the lower respiratory tract of mice is restricted by the interferon response.

Our study investigated how influenza B virus (IBV) spreads from the nose to the lungs of mice and the impact this has on disease and protection from re-infection. We found that when applied to the nose only, IBV does not spread very efficiently to the lungs in a process controlled by the interferon response. Priming immunity at the nose only resulted in less protection from re-infection than priming immunity at both the nose and lungs. These insights can guide the development of potential therapies targeting the interferon response as well as of intranasal vaccines against IBV.

Smart resilience through IoT‐enabled natural disaster management: A COVID‐19 response in São Paulo state

AbstractNatural disaster management approach establishes stages of prevention, preparation, response, and recovery. With the Internet of Things (IoT), Bigdata, Business Intelligence, and other Information Communication Technologies, data can be gathered to support decisions in stages of the response to natural disaster events. In biological natural disasters, the ICTs can also support efforts to promote social distancing, public health, and economic monitoring to face the threads. São Paulo state used IoT in scenarios to face COVID‐19, such as monitoring vehicular interurban mobility, social distancing, and economic activity. Frameworks, strategies, data views, and use cases are presented to support the decision‐making process to face this biological natural disaster. The data‐driven approach supports several purposes, including the communication of social distancing indices, economic recovery, the progression of contagion, and deaths. It also played a pivotal role in fostering transparency initiatives for society and supporting the crisis committee by facilitating situational analyses, and this approach became standard practice for pandemic response. Studies and innovative visualisation perspectives have produced positive outcomes, guiding the decision‐making process through data analysis. Noteworthy use cases were interurban traffic fence monitoring; mapping of virus spreading; tracking the economic impact concerning recovery plans; and, evaluating the effectiveness of public policies.

Numerical modeling of reaction–diffusion e-epidemic dynamics

The objective of this paper is to understand the dynamics of virus spread in a computer network by e-epidemic reaction–diffusion model and applying an implicit finite difference (FD) scheme for a numerical solution. The SIR models are used in studies of epidemiology to predict the behavior of the propagation of biological viruses within the population. We divide the population of computer nodes into three parts i.e. susceptible (may catch the virus), infected 1 (infected but not completely), and infected 2 (completely infected). By using Taylor’s series expansion the consistency of the implicit scheme is proved. The unconditional stability of the implicit FD model is proved by using the Von Numan stability analysis. The qualitative analysis of the underlying model is also analyzed such as positivity and boundedness of the model. The numerical stability and bifurcation of is also analyzed. Likewise, identical modeling techniques are adopted to analyze the spread of the virus in digital networks. Because the computer virus behaves in the identical way as the biological virus behaves, this paper emphasizes the significance of diffusion in decreasing the gap between reality and theory, offering a more precise depiction of the spread of the virus within the digital network.

Molecular characterization of cotton leaf curl Multan beta-satellite occurance on chili plants in Multan, Pakistan

The prevalence of cotton leaf curl disease (CLCuD) has significantly hampered chili (Capsicum spp.) production, presenting a formidable challenge in Pakistan. During a chili field survey in 2018, distinct symptoms, including stunted growth, yellowing, and severe leaf curling, were observed on several plants. Subsequently, a comprehensive sampling effort was undertaken, collecting a total of 39 symptomatic samples from diverse locations across Multan, Punjab. The DNA extraction from these samples was conducted at the plant virology laboratory at Bahauddin Zakariya University, Multan, marking a crucial step in the investigation of this debilitating disease and its impact on chili production in the region. Molecular analysis with PCR using Av/Ac Core, Beta 01/02, and CLCuMuBF11/R33 primers confirmed begomovirus infection in chili plants. Positive amplification demonstrated a 71.79% infection rate, with 579 bp, 1.4 kb, and 481 bp amplicons for Av/Ac Core, Beta 01/02, and CLCuMuBF11/R33, respectively. Sequencing identified cotton leaf curl Multan beta-satellite (MT668934) infecting the chili plant. Effectively managing these begomoviruses is crucial to curbing their multiplication and protecting vital crops like chili. Addressing the distributions of beta-satellites in agricultural fields, particularly chili, is imperative to prevent further viral spread.

Simultaneous detection of influenza A, B and respiratory syncytial virus in wastewater samples by one-step multiplex RT-ddPCR assay

BackgroundAfter the occurrence of the COVID-19 pandemic, detection of other disseminated respiratory viruses using highly sensitive molecular methods was declared essential for monitoring the spread of health-threatening viruses in communities. The development of multiplex molecular assays are essential for the simultaneous detection of such viruses even at low concentrations. In the present study, a highly sensitive and specific multiplex one-step droplet digital PCR (RT-ddPCR) assay was developed for the simultaneous detection and absolute quantification of influenza A (IAV), influenza B (IBV), respiratory syncytial virus (RSV), and beta-2-microglobulin transcript as an endogenous internal control (IC B2M).ResultsThe assay was first evaluated for analytical sensitivity and specificity, linearity, reproducibility, and recovery rates with excellent performance characteristics and then applied to 37 wastewater samples previously evaluated with commercially available and in-house quantitative real-time reverse transcription PCR (RT-qPCR) assays. IAV was detected in 16/37 (43%), IBV in 19/37 (51%), and RSV in 10/37 (27%) of the wastewater samples. Direct comparison of the developed assay with real-time RT-qPCR assays showed statistically significant high agreement in the detection of IAV (kappa Cohen’s correlation coefficient: 0.834, p = 0.001) and RSV (kappa: 0.773, p = 0.001) viruses between the two assays, while the results for the detection of IBV (kappa: 0.355, p = 0.27) showed good agreement without statistical significance.ConclusionsOverall, the developed one-step multiplex ddPCR assay is cost-effective, highly sensitive and specific, and can simultaneously detect three common respiratory viruses in the complex matrix of wastewater samples even at low concentrations. Due to its high sensitivity and resistance to PCR inhibitors, the developed assay could be further used as an early warning system for wastewater monitoring.

Assessing the reduction of viral infectivity in HPV16/18-positive women after one, two, and three doses of Gardasil-9 (RIFT): Study protocol.

Human Papillomavirus (HPV) prophylactic vaccination has proven effective in preventing new infections, but it does not treat existing HPV infections or associated diseases. Hence, there is still an important reservoir of HPV in adults, as vaccination programs are mainly focused on young women. The primary objective of this non-randomized, open-label trial is to evaluate if a 3-dose regimen of Gardasil-9 in HPV16/18-positive women could reduce the infective capacity of their body fluids. We aim to assess if vaccine-induced antibodies could neutralize virions present in the mucosa, thus preventing the release of infective particles and HPV transmission to sexual partners. As our main endpoint, the E1^E4-HaCaT model will be used to assess the infectivity rate of cervical, anal and oral samples, obtained from women before and after vaccination. HPV DNA positivity, virion production, seroconversion, and the presence of antibodies in the exudates, will be evaluated to attribute infectivity reduction to vaccination. Our study will recruit two different cohorts (RIFT-HPV1 and RIFT-HPV2) of non-vaccinated adult women. RIFT-HPV1 will include subjects with an HPV16/18 positive cervical test and no apparent cervical lesions or cervical lesions eligible for conservative treatment. RIFT-HPV2 will include subjects with an HPV16/18 positive anal test and no apparent anal lesions or anal lesions eligible for conservative treatment, as well as women with an HPV16/18 positive cervical test and HPV-associated vulvar lesions. Subjects complying with inclusion criteria for both cohorts will be recruited to the main cohort, RIFT-HPV1. Three doses of Gardasil-9 will be administered intramuscularly at visit 1 (0 months), visit 2 (2 months) and visit 3 (6 months). Even though prophylactic HPV vaccines would not eliminate a pre-existing infection, our results will determine if HPV vaccination could be considered as a new complementary strategy to prevent HPV-associated diseases by reducing viral spread. Trial registration: https://clinicaltrials.gov/ct2/show/NCT05334706.

Dengue Virus and Zika Virus Seroprevalence in the South Pacific Populations of the Cook Islands and Vanuatu

Arboviral diseases are serious threats to global health with increasing prevalence and potentially severe complications. Significant arthropod-borne viruses are the dengue viruses (DENV 1-4), the Zika virus (ZIKV), and the chikungunya virus (CHIKV). Among the areas most affected is the South Pacific Region (SPR). Here, arboviruses not only cause a high local burden of disease, but the region has also proven to contribute to their global spread. Outpatient serum samples collected between 08/2016 and 04/2017 on three islands of the island states of Vanuatu and the Cook Islands were tested for anti-DENV- and anti-ZIKV-specific antibodies (IgG) using enzyme-linked immunosorbent assays (ELISA). ELISA test results showed 89% of all test sera from the Cook Islands and 85% of the Vanuatu samples to be positive for anti-DENV-specific antibodies. Anti-ZIKV antibodies were identified in 66% and 52%, respectively, of the test populations. Statistically significant differences in standardized immunity levels were found only at the intranational level. Our results show that in both the Cook Islands and Vanuatu, residents were exposed to significant Flavivirus transmission. Compared to other seroprevalence studies, the marked difference between ZIKV immunity levels and previously published CHIKV seroprevalence rates in our study populations is surprising. We propose the timing of ZIKV and CHIKV emergence in relation to recurrent DENV outbreaks and the impact of seasonality as explanatory external factors for this observation. Our data add to the knowledge of arboviral epidemics in the SPR and contribute to a better understanding of virus spread, including external conditions with potential influence on outbreak dynamics. These data may support preventive and rapid response measures in the affected areas, travel-related risk assessment, and infection identification in locals and returning travelers.

Control dengue with Wolbachia: Insights from a two-strain vector-host model with larval competition

Due to deficient treatments and vaccines for dengue viruses, dengue control mainly depends on controlling mosquitoes. Suppressing wild mosquito population size by releasing male-only Wolbachia-carrying mosquitoes into the field has become an eco-friendly alternative for traditional mosquito control methods. By assuming an ideal continuous proportional release strategy, we formulate a two-strain vector-host model incorporating larval competition to describe the affected cross-transmission dynamics of two dengue viruses serotypes. Moreover, antibody-dependent enhancement (ADE) and temporal cross-immunity are considered in this model. Theoretical analysis including the well-posedness, the existence and local stability of dengue-free equilibria in terms of the basic reproduction numbers is conducted. Sensitivity analysis indicates that the basic reproduction numbers are most sensitive to the adult female mortality rate and mosquito bite rate. As expected, intensifying larval competition can prevent the spread of dengue viruses. Unexpectedly, increasing the release ratio can delay the peak time while increase the peak level of both primary and secondary infections. To efficiently eliminate dengue outbreaks, other control methods such as spraying larvicides/adult insecticides and avoiding mosquito bites should be employed simultaneously during the time period gained by releasing Wolbachia-carrying males.

Multiplexed detection of eight respiratory viruses based on nanozyme colorimetric microfluidic immunoassay

Pandemics caused by respiratory viruses, such as the SARS-CoV-1/2, influenza virus, and respiratory syncytial virus, have resulted in serious consequences to humans and a large number of deaths. The detection of such respiratory viruses in the early stages of infection can help control diseases by preventing the spread of viruses. However, the diversity of respiratory virus species and subtypes, their rapid antigenic mutations, and the limited viral release during the early stages of infection pose challenges to their detection. This work reports a multiplexed microfluidic immunoassay chip for simultaneous detection of eight respiratory viruses with noticeable infection population, namely, influenza A virus, influenza B virus, respiratory syncytial virus, SARS-CoV-2, human bocavirus, human metapneumovirus, adenovirus, and human parainfluenza viruses. The nanomaterial of the nanozyme (Au@Pt nanoparticles) was optimized to improve labeling efficiency and enhance the detection sensitivity significantly. Nanozyme-binding antibodies were used to detect viral proteins with a limit of detection of 0.1 pg/mL with the naked eye and a microplate reader within 40 min. Furthermore, specific antibodies were screened against the conserved proteins of each virus in the immunoassay, and the clinical sample detection showed high specificity without cross reactivity among the eight pathogens. In addition, the microfluidic chip immunoassay showed high accuracy, as compared with the RT-PCR assay for clinical sample detection, with 97.2%/94.3% positive/negative coincidence rates. This proposed approach thus provides a convenient, rapid, and sensitive method for simultaneous detection of eight respiratory viruses, which is meaningful for the early diagnosis of viral infections. Significantly, it can be widely used to detect pathogens and biomarkers by replacing only the antigen-specific antibodies.