Asymptomatic Infected Individuals Research Articles

Distinct serum exosomal miRNA profiles detected in acute and asymptomatic dengue infections: A community-based study in Baiyun District, Guangzhou

BackgroundIn recent years, research on exosomal miRNAs has provided new insights into exploring the mechanism of viral infection and disease prevention. This study aimed to investigate the serum exosomal miRNA expression profile of dengue-infected individuals through a community survey of dengue virus (DENV) infection. MethodsA seroprevalence study of 1253 healthy persons was first conducted to ascertain the DENV infection status in Baiyun District, Guangzhou. A total of 18 serum samples, including 6 healthy controls (HC), 6 asymptomatic DENV infections (AsymptDI), and 6 confirmed dengue fever patients (AcuteDI), were collected for exosome isolation and then sRNA sequencing. Through bioinformatics analysis, we discovered distinct serum exosomal miRNA profiles among the different groups and identified differentially expressed miRNAs (DEMs). These findings were further validated by qRT-PCR. ResultsThe community survey of DENV infection indicated that the DENV IgG antibody positivity rate among the population was 11.97 % in the study area, with asymptomatic infected individuals accounting for 93.06 % of the anti-DENV IgG positives. The age and Guangzhou household registration were associated with DENV IgG antibody positivity by logistic regression analysis. Distinct miRNA profiles were observed between healthy individuals and DENV infections. A total of 1854 miRNAs were identified in 18 serum exosome samples from the initial analysis of the sequencing data. Comparative analysis revealed 23 DEMs comprising 5 upregulated and 18 downregulated miRNAs in the DENV-infected group (mergedDI). In comparison to AcuteDI, 18 upregulated miRNAs were identified in AsymptDI. Moreover, functional enrichment of the predicted target genes of DEMs indicated that these miRNAs were involved in biological processes and pathways related to cell adhesion, focal adhesion, endocytosis, and ECM-receptor interaction. Eight DEMs were validated by qRT-PCR. ConclusionThe Baiyun District of Guangzhou exhibits a notable proportion of asymptomatic DENV infections as suggested in other research, highlighting the need for enhanced monitoring and screening of asymptomatic persons and the elderly. Differential miRNA expression among healthy, symptomatic and asymptomatic DENV-infected individuals suggests their potential as biomarkers for distinguishing DENV infection and offers new avenues of investigating the mechanisms underlying DENV asymptomatic infections.

Analyzing the dynamic patterns of COVID-19 through nonstandard finite difference scheme

This paper presents a novel approach to analyzing the dynamics of COVID-19 using nonstandard finite difference (NSFD) schemes. Our model incorporates both asymptomatic and symptomatic infected individuals, allowing for a more comprehensive understanding of the epidemic's spread. We introduce an unconditionally stable NSFD system that eliminates the need for traditional Runge–Kutta methods, ensuring dynamical consistency and numerical accuracy. Through rigorous numerical analysis, we evaluate the performance of different NSFD strategies and validate our analytical findings. Our work demonstrates the benefits of using NSFD schemes for modeling infectious diseases, offering advantages in terms of stability and efficiency. We further illustrate the dynamic behavior of COVID-19 under various conditions using numerical simulations. The results from these simulations demonstrate the effectiveness of the proposed approach in capturing the epidemic's complex dynamics.

GLOBAL SENSITIVITY ANALYSIS AND OPTIMAL CONTROL OF TYPHOID FEVER TRANSMISSION DYNAMICS

This paper presents a mathematical model aimed at studying the global behaviour and optimal control strategies for Typhoid fever. The primary objective of this study is to identify the most effective control strategy that minimizes the spread of the disease. To achieve this, we calculate the effective and basic reproduction numbers and utilize them to investigate the existence and stability of the equilibria. Furthermore, we investigate the global impact of each model parameter on the variables using Latin Hypercube Sampling and Partial Rank Correlation Coefficient. The necessary conditions of the optimal control problem are analyzed using Pontryagin’s maximum principle, and the numerical values of the model parameters are estimated using the maximum likelihood estimator. The results indicate that the optimal use of vaccination for susceptible individuals, as well as the screening and treatment of asymptomatic infected individuals, have a significant impact on reducing the spread of the disease in endemic regions.

Amebiasis as a sexually transmitted infection: A re-emerging health problem in developed countries.

Amebiasis, which is caused by Entamoeba histolytica (E. histolytica), is the second leading cause of parasite-related death worldwide. It manifests from asymptomatic carriers to severe clinical conditions, like colitis and liver abscesses. Amebiasis is commonly seen in developing countries, where water and food are easily contaminated by feces because of the poor sanitation. However, a recently challenge in many developed countries is the increase in domestic cases of invasive amebiasis as a sexually transmitted infection (STI amebiasis). In contrast to food-/ waterborne transmission of E. histolytica in developing countries, transmission of STI amebiasis occurs directly through human-to-human sexual contact (e.g., men who have sex with men and people who engage in oral-anal sex); in this setting, asymptomatic infected individuals are the main reservoir of E. histolytica. The Development of screening methods for the early diagnosis of asymptomatic E. histolytica infection is the key to epidemiologic control. Moreover, delay in diagnosis of severe cases (e.g., fulminant amebiasis) leads to death even in developed countries. It is also important to increase clinical awareness of domestically transmitted STI amebiasis in the clinical settings. This review considers the changing epidemiology and clinical manifestations of STI amebiasis, and finally discusses the future strategies for the better practice.

Demand assessment of the number of inpatient beds in China based on the COVID-19 dynamical model

COVID-19 is a worldwide pandemic that poses a great threat to people’s health and has a huge impact on economic and social life. The epidemic is currently at a low level, but is still prevalent worldwide. Therefore, it is still important to study the prevention and control of the spread of the COVID-19 epidemic. We collected the numbers of COVID-19 infections in China during the past three years, and obtained the regional distribution of outbreaks through analysis. To assess the capacity of medical resources in these regions in response to the outbreaks of COVID-19, we developed a model of COVID-19 transmission dynamics including mild and severe cases. The simulation showed that 11 regions, Beijing, Shanghai, Heilongjiang, Yunnan, Xinjiang, Inner Mongolia, Liaoning, Jilin, Hainan, Guangdong and Fujian, all have a serious shortage of medical beds in reserve. When facing the next new outbreak, these areas will have insufficient medical resources. We simulated the effects of drug effectiveness and the proportion of asymptomatic infected individuals on the spread of the epidemic, and obtained that an accurate determination of the proportion of asymptomatic patients in the population is crucial to the impact on healthcare resources, while improving the effectiveness of drugs can significantly reduce the burden on healthcare resources. Regions should invest more in healthcare and increase more medical resources, including medical beds. Government should accelerate the development of effective COVID-19 drugs to effectively control the scale of the outbreak. The proportion of asymptomatic patients in the population has a significant impact on the allocation of healthcare resources. The monitoring of antibody levels in the population should be strengthened to better control the spread of the epidemic.

Vector-borne Trypanosoma brucei parasites develop in artificial human skin and persist as skin tissue forms

Transmission of Trypanosoma brucei by tsetse flies involves the deposition of the cell cycle-arrested metacyclic life cycle stage into mammalian skin at the site of the fly’s bite. We introduce an advanced human skin equivalent and use tsetse flies to naturally infect the skin with trypanosomes. We detail the chronological order of the parasites’ development in the skin by single-cell RNA sequencing and find a rapid activation of metacyclic trypanosomes and differentiation to proliferative parasites. Here we show that after the establishment of a proliferative population, the parasites enter a reversible quiescent state characterized by slow replication and a strongly reduced metabolism. We term these quiescent trypanosomes skin tissue forms, a parasite population that may play an important role in maintaining the infection over long time periods and in asymptomatic infected individuals.

Limited efficacy of forward contact tracing in epidemics.

Infectious diseases that spread silently through asymptomatic or pre-symptomatic infections represent a challenge for policy makers. A traditional way of achieving isolation of silent infectors from the community is through forward contact tracing, aimed at identifying individuals that might have been infected by a known infected person. In this work we investigate how efficient this measure is in preventing a disease from becoming endemic. We introduce an SIS-based compartmental model where symptomatic individuals may self-isolate and trigger a contact tracing process aimed at quarantining asymptomatic infected individuals. Imperfect adherence and delays affect both measures. We derive the epidemic threshold analytically and find that contact tracing alone can only lead to a very limited increase of the threshold. We quantify the effect of imperfect adherence and the impact of incentivizing asymptomatic and symptomatic populations to adhere to isolation. Our analytical results are confirmed by simulations on complex networks and by the numerical analysis of a much more complex model incorporating more realistic in-host disease progression.

Estimating the prevalence of COVID-19 cases through the analysis of SARS-CoV-2 RNA copies derived from wastewater samples from North Dakota

The SARS-CoV-2 virus was first detected in December 2019, which prompted many researchers to investigate how the virus spreads. SARS-CoV-2 is mainly transmitted through respiratory droplets. Symptoms of the SARS-CoV-2 virus appear after an incubation period. Moreover, the asymptomatic infected individuals unknowingly spread the virus. Detecting infected people requires daily tests and contact tracing, which are expensive. The early detection of infectious diseases, including COVID-19, can be achieved with wastewater-based epidemiology, which is timely and cost-effective. In this study, we collected wastewater samples from wastewater treatment plants in several cities in North Dakota and then extracted viral RNA copies. We used log-RNA copies in the model to predict the number of infected cases using Quantile Regression (QR) and K-Nearest Neighbor (KNN) Regression. The model's performance was evaluated by comparing the Mean Absolute Percentage Error (MAPE). The QR model performs well in cities where the population is >10000. In addition, the model predictions were compared with the basic Susceptible-Infected-Recovered (SIR) model which is the golden standard model for infectious diseases.

Lipid alternations in the plasma of COVID-19 patients with various clinical presentations.

COVID-19 is a highly infectious respiratory disease that can manifest in various clinical presentations. Although many studies have reported the lipidomic signature of COVID-19, the molecular changes in asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected individuals remain elusive. This study combined a comprehensive lipidomic analysis of 220 plasma samples from 166 subjects: 62 healthy controls, 16 asymptomatic infections, and 88 COVID-19 patients. We quantified 732 lipids separately in this cohort. We performed a difference analysis, validated with machine learning models, and also performed GO and KEGG pathway enrichment analysis using differential lipids from different control groups. We found 175 differentially expressed lipids associated with SASR-CoV-2 infection, disease severity, and viral persistence in patients with COVID-19. PC (O-20:1/20:1), PC (O-20:1/20:0), and PC (O-18:0/18:1) better distinguished asymptomatic infected individuals from normal individuals. Furthermore, some patients tested positive for SARS-CoV-2 nucleic acid by RT-PCR but did not become negative for a longer period of time (≥60 days, designated here as long-term nucleic acid test positive, LTNP), whereas other patients became negative for viral nucleic acid in a shorter period of time (≤45 days, designated as short-term nucleic acid test positive, STNP). We have found that TG (14:1/14:1/18:2) and FFA (4:0) were differentially expressed in LTNP and STNP. In summary, the integration of lipid information can help us discover novel biomarkers to identify asymptomatic individuals and further deepen our understanding of the molecular pathogenesis of COVID-19.

Modeling the dynamics of COVID-19 with real data from Thailand

In recent years, COVID-19 has evolved into many variants, posing new challenges for disease control and prevention. The Omicron variant, in particular, has been found to be highly contagious. In this study, we constructed and analyzed a mathematical model of COVID-19 transmission that incorporates vaccination and three different compartments of the infected population: asymptomatic (I_{a}), symptomatic (I_{s}), and Omicron (I_{m}). The model is formulated in the Caputo sense, which allows for fractional derivatives that capture the memory effects of the disease dynamics. We proved the existence and uniqueness of the solution of the model, obtained the effective reproduction number, showed that the model exhibits both endemic and disease-free equilibrium points, and showed that backward bifurcation can occur. Furthermore, we documented the effects of asymptomatic infected individuals on the disease transmission. We validated the model using real data from Thailand and found that vaccination alone is insufficient to completely eradicate the disease. We also found that Thailand must monitor asymptomatic individuals through stringent testing to halt and subsequently eradicate the disease. Our study provides novel insights into the behavior and impact of the Omicron variant and suggests possible strategies to mitigate its spread.

Dynamic effects of asymptomatic infections on malaria transmission

Asymptomatic transmission is a way of spreading malaria from asymptomatic infected individuals to susceptible ones by mosquito bites. Asymptomatic malaria-infected individuals do not show clinical symptoms, but they can still transmit the disease. Motivated by mathematical models with asymptomatic infections, we propose a human–mosquito model for malaria transmission dynamics with asymptomatic infections and standard incidence rates. We calculate the basic reproduction number R0 of the model and then prove that the model exists a unique endemic equilibrium E∗ if and only if R0>1. By the Lyapunov function method, the global stability of equilibria of the model is obtained. It is shown that the disease-free equilibrium E0 is globally asymptotically stable (GAS) if and only if R0≤1, which implies that malaria will be extinct; and the endemic equilibrium E∗ is GAS if and only if R0>1, which suggests that malaria will persist. In addition, the effects of partial malaria-related parameters on the dynamic transmission of malaria are studied and analysed numerically. The results of numerical simulations show that asymptomatic infections can shift the epidemic dynamics of malaria and have a significant influence on the transmission of malaria.

New diagnostics for the spectrum of asymptomatic TB: from infection to subclinical disease.

TB remains a leading cause of morbidity and mortality worldwide. However, most infected immunocompetent individuals are asymptomatic and only 5-10% of these will eventually develop active TB during their lifetime (typically within 2 years after exposure). Therefore, rapid diagnosis and efficient management of asymptomatic infected individuals who are at the highest risk of progression and transmission remain major clinical and public health challenges. In recent years, there has been important scientific progress in our understanding of the spectrum of asymptomatic Mycobacterium tuberculosis (Mtb) infections that not only includes the dynamic state of latent TB infection (LTBI), but also the preclinical state of incipient and subclinical TB. The latter is possibly as prevalent as symptomatically active TB and potentially contributes to global Mtb transmission in various settings. We summarize the latest developments and current challenges of the existing testing tools for LTBI and describe promising biomarkers and diagnostics for the spectrum of asymptomatic TB. Following the negative results of a recent clinical trial for a biomarker-guided preventive therapy approach, we also suggest some treatment options for incipient TB.

Mathematical Model and Simulation of the Spread of COVID-19 with Vaccination, Implementation of Health Protocols, and Treatment

This research develops the SVEIHQR model to simulate the spread of COVID-19 with vaccination, implementation of health protocols, and treatment. The population is divided into twelve subpopulations, resulting in a mathematical model of COVID-19 in the form of a system of twelve differential equations with twelve variables. From the model, we obtain the disease-free equilibrium point, the endemic equilibrium point, and the basic reproduction number (R0). The disease-free equilibrium point is locally asymptotically stable when R0 1 and ∆5 0, where ∆5 is the fifth-order Routh-Hurwitz matrix of the characteristic polynomial of the Jacobian matrix. Additionally, an endemic equilibrium point exists when R0 1. The results of numerical simulations are consistent with the conducted analysis, and the sensitivity analysis reveals that the significant parameters influencing the spread of COVID-19 are the proportion of symptomatic infected individuals and the contact rate with asymptomatic infected individuals.

Numerical Approach for Solving a Fractional-Order Norovirus Epidemic Model with Vaccination and Asymptomatic Carriers

This paper explored the impact of population symmetry on the spread and control of a norovirus epidemic. The study proposed a mathematical model for the norovirus epidemic that takes into account asymptomatic infected individuals and vaccination effects using a non-singular fractional operator of Atanganaa–Baleanu Caputo (ABC). Fixed point theory, specifically Schauder and Banach’s fixed point theory, was used to investigate the existence and uniqueness of solutions for the proposed model. The study employed MATLAB software to generate simulation results and demonstrate the effectiveness of the fractional order q. A general numerical algorithm based on Adams–Bashforth and Newton’s Polynomial method was developed to approximate the solution. Furthermore, the stability of the proposed model was analyzed using Ulam–Hyers stability techniques. The basic reproductive number was calculated with the help of next-generation matrix techniques. The sensitivity analysis of the model parameters was performed to test which parameter is the most sensitive for the epidemic. The values of the parameters were estimated with the help of least square curve fitting tools. The results of the study provide valuable insights into the behavior of the proposed model and demonstrate the potential applications of fractional calculus in solving complex problems related to disease transmission.

Minimum wave speed for dengue prevalence in the symptomatic and asymptomatic infected individuals

Minimum wave speed for dengue prevalence in the symptomatic and asymptomatic infected individuals

Social dilemma analysis on vaccination game accounting for the effect of immunity waning

A new SEIRS-based ODE (Ordinary Differential Equation) model is built, where asymptomatic and symptomatic infectious compartments, hospitalized state and immune state are additionally introduced, which is dovetailed with a behavior model that defines the vaccination rate as time-variable. We also apply Social Efficiency Deficit; SED, to quantitatively identify whether or not social dilemma taking place behind the model dynamics. Numerical results prove that, depending on the fraction of asymptomatic infected individuals and the discount ratio of infected force for asymptomatic state compared with that for symptomatic one, whether or not social dilemma appearing is different, which is also substantially affected by the vaccination cost and the immunity waning rate. The behavior model tends to incur a slight social dilemma brought by wasting vaccination even in the region of disease free, identified by R0<1. Meanwhile, a relatively strong social dilemma is indicated in the parameter region where the behavior model shows less amount of vaccinated population while the social optimal state needs much more vaccinated for complete remission of disease.

A mathematical model for transmission dynamics of COVID-19 infection.

In this paper, a mathematical model of COVID-19 has been proposed to study the transmission dynamics of infection by taking into account the role of symptomatic and asymptomatic infected individuals. The model has also considered the effect of non-pharmaceutical interventions (NPIs) in controlling the spread of virus. The basic reproduction number ( ) has been computed and the analysis shows that for , the disease-free state becomes globally stable. The conditions of existence and stability for two other equilibrium states have been obtained. Transcritical bifurcation occurs when basic reproduction number is one (i.e. ). It is found that when asymptomatic cases get increased, infection will persist in the population. However, when symptomatic cases get increased as compared to asymptomatic ones, the endemic state will become unstable and infection may eradicate from the population. Increasing NPIs decrease the basic reproduction number and hence, the epidemic can be controlled. As the COVID-19 transmission is subject to environmental fluctuations, the effect of white noise has been considered in the deterministic model. The stochastic differential equation model has been solved numerically by using the Euler-Maruyama method. The stochastic model gives large fluctuations around the respective deterministic solutions. The model has been fitted by using the COVID-19 data of three waves of India. A good match is obtained between the actual data and the predicted trajectories of the model in all three waves of COVID-19. The findings of this model may assist policymakers and healthcare professionals in implementing the most effective measures to prevent the transmission of COVID-19 in different settings.

A mathematical model for COVID-19 considering waning immunity, vaccination and control measures

In this work we define a modified SEIR model that accounts for the spread of infection during the latent period, infections from asymptomatic or pauci-symptomatic infected individuals, potential loss of acquired immunity, people’s increasing awareness of social distancing and the use of vaccination as well as non-pharmaceutical interventions like social confinement. We estimate model parameters in three different scenarios—in Italy, where there is a growing number of cases and re-emergence of the epidemic, in India, where there are significant number of cases post confinement period and in Victoria, Australia where a re-emergence has been controlled with severe social confinement program. Our result shows the benefit of long term confinement of 50% or above population and extensive testing. With respect to loss of acquired immunity, our model suggests higher impact for Italy. We also show that a reasonably effective vaccine with mass vaccination program are successful measures in significantly controlling the size of infected population. We show that for a country like India, a reduction in contact rate by 50% compared to a reduction of 10% reduces death from 0.0268 to 0.0141% of population. Similarly, for a country like Italy we show that reducing contact rate by half can reduce a potential peak infection of 15% population to less than 1.5% of population, and potential deaths from 0.48 to 0.04%. With respect to vaccination, we show that even a 75% efficient vaccine administered to 50% population can reduce the peak number of infected population by nearly 50% in Italy. Similarly, for India, a 0.056% of population would die without vaccination, while 93.75% efficient vaccine given to 30% population would bring this down to 0.036% of population, and 93.75% efficient vaccine given to 70% population would bring this down to 0.034%.

BACTERIAL INFECTION AND ANTIMICROBIAL SUSCEPTIBILITSY TEST (AST) PATTERNS AMONG CONFIRMED SARS COV-2 INDIVIDUAL IN SOUTHWESTERN NIGERIA.

Antimicrobial medications were given to patients with this illness without antimicrobial susceptibility since recent statistics on SARS-C0V-2 showed that bacterial infection increased mortality rate and lowered clearance rate of the virus. The goal of this study was to detect co-infecting pathogen(s) and analyze their antibiotic resistance profiles in confirmed SARS-CoV-2 cases in Oyo State, Nigeria. 400 symptomatic and asymptomatic infected individuals had their nasopharynx sampled, and structured questionnaires were given out to identify risk factors for SARS-CoV-2 infection. Using API 20E and VITEK 2.0 ID cards, isolates were recognized after being collected using conventional microbiological techniques. Antimicrobial susceptibility testing was done using VITEK 2.0 AST card kits and Kirby Bauer disc diffusion techniques. The Enterobacteriaceae family had a large number of the observed bacteria. The COVID-19 cases treated with azithromycin, which is more resistant to Gram positive bacteria, had a higher resistance rate (66.6%). However, bacterial isolates have significantly higher quinolone susceptibility (89.0%). Some of the microbiological isolates identified in individuals with SARS-CoV-2 infection were multidrug resistant, including Azithromycin. This discovery raises serious health concerns and requires additional investigation.

Genomic Epidemiology and Transmission Dynamics of Global Coxsackievirus B4.

The aim of this study was to determine the global genetic diversity and transmission dynamics of coxsackievirus B4 (CVB4) and to propose future directions for disease surveillance. Next-generation sequencing was performed to obtain the complete genome sequence of CVB4, and the genetic diversity and transmission dynamics of CVB4 worldwide were analyzed using bioinformatics methods such as phylogenetic analysis, evolutionary dynamics, and phylogeographic analysis. Forty complete genomes of CVB4 were identified from asymptomatic infected individuals and hand, foot, and mouth disease (HFMD) patients. Frequent recombination between CVB4 and EV-B multiple serotypes in the 3Dpol region was found and formed 12 recombinant patterns (A-L). Among these, the CVB4 isolated from asymptomatic infected persons and HFMD patients belonged to lineages H and I, respectively. Transmission dynamics analysis based on the VP1 region revealed that CVB4 epidemics in countries outside China were dominated by the D genotype, whereas the E genotype was dominant in China, and both genotypes evolved at a rate of > 6.50 × 10-3 substitutions/site/year. CVB4 spreads through the population unseen, with the risk of disease outbreaks persisting as susceptible individuals accumulate. Our findings add to publicly available CVB4 genomic sequence data and deepen our understanding of CVB4 molecular epidemiology.