Infected People Research Articles

Investigations of transmission dynamics of Nipah virus in Bangladesh

This study has focused on the transmission dynamics of the Nipah Virus (NiV) and its controlling system. In this respect, we have developed a virus transmission model based on several compartments and discussed the model's basic reproduction number and stability analysis at disease-free equilibrium (DFE) and endemic equilibrium (EE) points. It is observed that the model is locally and globally asymptotically stable at DFE and EE for the basic reproduction number R0<1 and R0>1, respectively. We have also solved the model equations numerically using the Runge-Kutta (RK-45) method to investigate the effect of disease parameters. In the calculation, some parameter values are taken from several references. Lastly, the calculated results show that the infection rate of the exposed individuals highly influences the disease compartments. Furthermore, drug resistance is observed to be less effective than the treatment rate. In addition, it is found that the number of infected people is reducing with the increasing treatment rate.

Research on Symptomatic Treatment Decision Support System Based on Natural Language Process (NLP) for Medication Guidance.

This study is to test the technologies related to natural language processing (NLP) and text analysis to solve the problem of symptom analysis and symptomatic treatment for healthcare workers and patients after large-scale outbreaks of infectious diseases. Using the keyword extraction tool based on NLP technology combined with text analysis, the symptom description of the infected population obtained from the questionnaire survey was analyzed, and the efficacy of the symptomatic treatment drug was analyzed, and finally a pre-experimental system of online symptomatic treatment support drug selection system was produced. Through natural language processing (NLP) and text analysis of the symptoms of infected people, we found that high-frequency symptoms were mainly reflected in: nasal congestion, sore throat, fever and other high-frequency keywords, and through the analysis of alternative drug libraries, we also found that the drugs were mainly concentrated in: cold medicines, antipyretic drugs,and traditional Chinese medicines. In the early stage of infectious disease outbreak, it is difficult to use the existing drug library to make a prompt system under the premise of insufficient data collection, and a relatively complete symptomatic treatment support medication system can be formed after accumulating certain samples.

Association Between the Level of Knowledge, Awareness and Attitude on Post-COVID-19 Syndrome Amongst Medical Students in Four Malaysian Universities

Introduction: COVID-19 is a respiratory illness that is caused by a coronavirus. Infected people will have a chance to develop post-COVID-19 syndrome. The aim of this study is to identify the association of gender, marital status, age and university on knowledge, awareness and attitude of post-COVID-19 syndrome among medical students in four universities in Malaysia. Methods: A cross-sectional study was conducted from October 2021 to July 2022 at four universities in Malaysia which are Universiti Putra Malaysia (UPM), Universiti Islam Antarabangsa Malaysia (UIAM), Universiti Sains Malaysia (USM) and Universiti Sains Islam Malaysia (USIM). A self-administered questionnaire was administered to 355 respondents consisted of four sections, assessing socio-demographic data and knowledge, awareness and attitudes of post-COVID-19 syndrome. Results: 54.4% of the respondents had high knowledge, 53.8% had high awareness, and 55.21% had a high attitude towards post-COVID-19 syndrome. In this study, there is a significant association between knowledge on post-COVID-19 syndrome and the age among respondents. Knowledge and awareness, knowledge, and attitude as well as awareness and attitude on post-COVID-19 syndrome was also found to have significant association among respondents. Conclusion: The older age of the respondents have good knowledge towards post-COVID-19 syndrome.

Optimization of cabin seating arrangement strategies based on the Wells-Riley risk theory.

Civil aviation transport is an important source of global respiratory disease spread due to the closely-spaced environment. In order to reduce the probability of infection of passengers, an improved Wells-Riley model for cabin passenger risk assessment have been given in this work, the cabin ventilation and passenger nose and mouth orientation were considered. The model's effectiveness has been verified with published data. Finally, how the load factor and use of an empty seat scheme are associated with the number of infected people was assessed. The results demonstrated that the number of infected people positively correlates with the passenger load factor, and the most suitable load factor can be determined by controlling the final number of infected people with the condition of the epidemic situation in the departure city. Additionally, infection risk was found to be lower among passengers in window seats than in those in aisle seats and middle seats, and keeping empty seats in the middle or aisle could reduce the cabin average probability of infection by up to 37.47%. Using the model developed here, airlines can determine the optimal load factor threshold and seating arrangement strategy to improve economic benefits and reduce the probability of passenger infection.

Optimal control of a rumor propagation model in online social network by considering influential nodes

Social networking platforms give people an opportunity to get in contact with each other irrespective of boundaries. Through these platforms, any individual can easily follow the ideas of other individuals like friends, relatives, politicians, actors, etc, and get in contact with them. In this paper, we examine rumor propagation with two types of infected people: highly influential people and ordinary people. Some ordinary people, blindly follow the messages shared by highly influential people. By using this concept we analyze the rumor-spreading model in networks (homogeneous and heterogeneous). We applied control strategies in homogeneous networks and observed that government policies to control rumor propagation can reduce its spread. Immunization in heterogeneous networks by giving proper information and education to people about facts can also reduce the spread and help people make the right decision when they come across a rumor.

Factors associated with the use of medicines and self-medication during the COVID-19 pandemic in 12 Latin American countries

IntroductionThe coronavirus disease 2019 (COVID-19) pandemic has triggered a rise in the global phenomenon of self-medication. The use of medicines with unsubstantiated claims of benefit for the prevention and/or treatment of infected people has been widely adopted. ObjectiveTo determine the factors associated with the use of medicines and self-medication by Latin American populations during the COVID-19 pandemic. MethodsThis analytical cross-sectional study was conducted via an analysis of secondary data collected from 8777 responses from 12 Latin American countries obtained from a survey on the use of medicines and self-medication during the pandemic. ResultsRespondents who reported using Paracetamol, Ibuprofen, or antibiotics (ABx) disclosed this as self-medication in 26.9%, 16.6%, and 9.7% of cases respectively. In our multivariate analysis, significant associations were found between: self-medication by individual choice and the use of Hydroxychloroquine, ABx, or non-steroidal anti-inflammatory drugs (NSAIDs) (p = 0.026, = 0.003, and <0.001 respectively); self-medication on the recommendation of a family member, with ABx, Paracetamol, Ibuprofen, or other NSAIDs (p <0.001, <0.001, <0.001, and <0.001 respectively); and self-medication on the recommendation of another person, with Chloroquine, Hydroxychloroquine, Azithromycin, Penicillin, other ABx, Warfarin, Ivermectin, Paracetamol, Ibuprofen, or other NSAIDs (p <0.001, <0.001, <0.001, = 0.001, <0.001, <0.001, = 0.004, <0.001, <0.001, and <0.001 respectively). ConclusionThere was a significantly high prevalence of self-medication in our Latin American study population, including the use of medicines not recommended for COVID-19 treatment and/or prevention. The implementation of public health measures aimed at combating the worrying COVID-19 infodemic is essential to prevent this ongoing issue and its associated negative impacts on both current public health and future medication efficacy. This is especially important in the case of ABx due to the threat of a future antimicrobial resistance pandemic.

Wearable Devices to Diagnose and Monitor the Progression of COVID-19 Through Heart Rate Variability Measurement: Systematic Review and Meta-Analysis.

Recent studies have linked low heart rate variability (HRV) with COVID-19, indicating that this parameter can be a marker of the onset of the disease and its severity and a predictor of mortality in infected people. Given the large number of wearable devices that capture physiological signals of the human body easily and noninvasively, several studies have used this equipment to measure the HRV of individuals and related these measures to COVID-19. The objective of this study was to assess the utility of HRV measurements obtained from wearable devices as predictive indicators of COVID-19, as well as the onset and worsening of symptoms in affected individuals. A systematic review was conducted searching the following databases up to the end of January 2023: Embase, PubMed, Web of Science, Scopus, and IEEE Xplore. Studies had to include (1) measures of HRV in patients with COVID-19 and (2) measurements involving the use of wearable devices. We also conducted a meta-analysis of these measures to reduce possible biases and increase the statistical power of the primary research. The main finding was the association between low HRV and the onset and worsening of COVID-19 symptoms. In some cases, it was possible to predict the onset of COVID-19 before a positive clinical test. The meta-analysis of studies reported that a reduction in HRV parameters is associated with COVID-19. Individuals with COVID-19 presented a reduction in the SD of the normal-to-normal interbeat intervals and root mean square of the successive differences compared with healthy individuals. The decrease in the SD of the normal-to-normal interbeat intervals was 3.25 ms (95% CI -5.34 to -1.16 ms), and the decrease in the root mean square of the successive differences was 1.24 ms (95% CI -3.71 to 1.23 ms). Wearable devices that measure changes in HRV, such as smartwatches, rings, and bracelets, provide information that allows for the identification of COVID-19 during the presymptomatic period as well as its worsening through an indirect and noninvasive self-diagnosis.

The application of SIR model in COVID-19

The SIR model was used to better comprehend and analyse the transmission dynamics of COVID-19. This mathematical framework splits the population into three compartments: suspectable, infectious, and recovered, allowing disease spread to be simulated across time. After making some essential assumptions of SIR model, the project illustrates the rate of suspectable, infected, recovered individuals over time by constructing several differential equations using specific parameters. Also, SIR model gives insights into expected disease trajectories, the impact of therapies, and other pertinent discoveries by including critical factors and assumptions. Researchers successfully anticipate disease trajectories using this simulation, indicating the usefulness of actions in preventing viral propagation. Researchers have found that the incubation period of COVID-19 has vital impact on the epidemic curve, which results in a slower growth in the number of infected people overtime and a delay in the upward slope of the infectious in the epidemic curve. The SIR models examination of epidemic curves has assisted in identifying the peak of infections, estimating the duration of outbreaks, and assessing the efficiency of public health measures in various context. Further study, continued data collecting, and integration with real-world data will improve the accuracy and usefulness of the SIR model, enabling evidence-based ways to combating COVID-19s issues.

A Mathematical Model for the COVID-19 Pandemic in Tokyo through Changing Point Calculus

The great social and economic impact that the COVID-19 pandemic has had on a global level has encouraged the development of new mathematical models that make it possible to better manage this and future pandemics. Here, we propose an extension of the classical epidemiological compartmental model SIR, the SEIAMD model (Susceptible–Exposed–Identified–Asymptomatic–iMmunized–Deceased), which considers the appearance of new virus variants, the use of vaccines, the existence of nonidentified asymptomatic individuals, and the loss of immunity acquired by infection or vaccination. Using an optimization model coded in Python that allows us to determine the change points that represent different behaviors of infected people, the SEIAMD model calculates, from official data, the different effective contact rates that were observed during the first seven waves of the COVID-19 pandemic in Tokyo due to the application of Non-Pharmaceutical Interventions (NPIs) and social habits. The closeness of the results obtained with our model and the real data, as well as the accuracy of predictions and observations, confirm the suitability of our model for studying the evolution of the COVID-19 pandemic in Tokyo.

Correlation Of (D- Dimer), (LDH) And (C RP) Levels With COVID-19 Infection

100 samples were taken from people infected with Covid 19 virus, where the infection was diagnosed by taking nasal samples using special sterile cotton swabs, then the infection was confirmed using a PCR machine. After confirming the infection, 52 samples were taken from males (52%) and 48 samples from females (48%) of different ages, in general, the results showed that 78% of the infected people had an increase in CRP and 46% of the infected people had an increase in D. dimer above the normal level While 36% had an increased LDH. Then the levels of LDH, D. dimer and CRP were measured using the Vitec device, the results showed that the patients aged over 50 years in both sexes were more affected by the infection than the patients aged less than 50 years, as they showed that the percentage of infection severity was in the elderly more and that the percentage of infection was more High levels of LDH, D. dimer and CRP in males were more than females and this may be affected by sex hormones

Long COVID Explained: The Ultimate Guide For Kids!

COVID-19 is caused by SARS-CoV-2, a virus that affects the upper and lower respiratory tracts. Most kids who get COVID-19 do not get sick at all, or only feel sick for a short time. But sometimes children who have had COVID-19 can feel unwell for several weeks or months after the infection. They continue to feel exhausted, have shortness of breath, and have trouble doing daily tasks. This is called long COVID, and doctors are trying to understand it and find ways to protect people. In this article, we will explain what can happen when kids get COVID-19, what long COVID is, and what might cause long COVID to happen in a number of infected people.

Evaluation of the ABL NGS assay for HIV-1 drug resistance testing

HIV evolution and variability around the world requires special monitoring of the viral strains in infected people. High-throughput HIV sequencing and drug resistance testing techniques have become routinely available over the last few years.We conducted a study to assess the new CE-marked ABL NGS HIV genotyping assay on an Illumina® platform, to compare the results (the detection of resistance associated mutations (RAMs) detected in the three main targets: reverse transcriptase, protease, and integrase) with those produced by three Sanger-based assays, and to compare the assays’ respective costs.For the 10 samples and a 20 % sensitivity threshold for the NGS technology, the percent agreement between the four assays ranged from 99.5 % to 100 %. We detected 4 more and 10 more RAMs of interest when we lowered the NGS assay's threshold to 10 % and 3 %, respectively. At a threshold of 3 %, the antiretroviral sensitivity interpretation algorithm (for protease inhibitors) was modified for only two patients. The NGS assay's unit cost fell rapidly as the number of samples per run increased.Compared with Sanger sequencing, the ABL NGS HIV genotyping assay is just as robust and somewhat more expensive but opens up interesting multiplexing perspectives for virology laboratories.

Dynamic behaviors and non-instantaneous impulsive vaccination of an SAIQR model on complex networks

We establish an SAIQR epidemic network model, in which asymptomatic infected people (A) are as contagious as infected people (I). The basic reproductive number R0 is calculated, and the globally asymptotically stable of the disease-free equilibrium, the globally attractive and globally asymptotically stable of the endemic equilibrium are obtained. For the control of epidemic transmission, we take into account the non-instantaneous impulsive vaccination in the model, calculate the basic reproduction number R0⁎ of the model, and demonstrate that the disease-free T-periodic solution is globally attractive and the model is permanent. Finally, we choose scale-free network to simulate numerically and validate the results of this paper.

PULMONARY REHABILITATION IN POST COVID SEQUELAE IN INDIA

An outbreak of pneumonia was reported in Wuhan, Hubei Province, China in December 2019 and quickly spread to all Chinese provinces. 1, 2 The coronavirus disease (COVID-19) pandemic spread through 190 countries within 20 weeks from Wuhan, China, affecting 334,000 populations. This caused more than 14,500 deaths by mid-March 2020. The number of infected people has risen to 1,210,956 in the month of April 6, 2020, with 67,594 associated expirations. 4 India recorded its first COVID-19 infection case on January 30, 2020 in a student from China's capital, Wuhan. In 2020, India reported 360 positive COVID-19 cases from 23 states across the country. 4 in India, the number of asymptomatic cases was higher. On April 4, 2019, a novel coronavirus pathogen was proved to be a novel betacoronavirus. 2 Sub-micron sized viruses, narrated as "organisms at the edge of life", are liable for some of the worst human pandemics in history, like influenza (1918), smallpox (1978), and COVID-19, as of September 17, 2020. 2 The SARS-CoV-2 virus is causative for COVID-19. Nearly 29 million people have been affected by this virus, which caused 936,521 deaths worldwide (WHO, 2020). 2 Corona viruses are single-stranded positive-strand RNA viruses that are known to contain some of the largest viral genomes, up to around 32 kbp in length. Following an augmentation in the number of coronavirus genome sequences available and following efforts to investigate the diversity in the wild, the family Corona viridae now contains four genera. The structure of the coronavirus as given in figure 1 Those species that belong to the genera Alpha corona virus and Beta corona virus can infect mammalian hosts, while those of Gamma corona virus and the recently defined Delta corona virus mainly infect avian species. 3 The highly pathogenic human coronaviruses, Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV), belong to lineage B (sub-genus Sarbecovirus) and lineage C (sub-genus Merbecovirus) of Betacoronavirus. 3

TB-ISATEST: a Diagnostic LAMP Assay for Differentiation of &lt;i&gt;Mycobacterium tuberculosis&lt;/i&gt;

Consumption, white plague, tuberculosis… Only relatively recently, this disease has ceased to be an absolutely death sentence for infected people, but problems of the spread and diagnosis of the disease are still relevant. This paper presents results of the development of a new loop isothermal amplification (LAMP) assay, named TB-ISATEST, which targeting the species-specific gene rv2341 for the differentiation of Mycobacterium tuberculosis from non-tuberculosis mycobacteria. The assay is applicable for quantitative analysis of genomic DNA and allows detecting tenfold difference in concentration. The results of amplification optimization using a unique two-stage protocol based on the method of orthogonal Taguchi matrices are presented for the first time. A theoretical interpretation of the high amplification efficiency values observed in the LAMP reaction is proposed. Limit of detection of the developed assay is 40 copies of genomic DNA per reaction and amplification requires 15 min. In terms of the combination of characteristics, the TB-ISATEST assay surpasses all the known ways for identifying M. tuberculosis by the LAMP method.

Monitoring the reproductive number of COVID-19 in France: Comparative estimates from three datasets.

The effective reproduction number (Rt) quantifies the average number of secondary cases caused by one person with an infectious disease. Near-real-time monitoring of Rt during an outbreak is a major indicator used to monitor changes in disease transmission and assess the effectiveness of interventions. The estimation of Rt usually requires the identification of infected cases in the population, which can prove challenging with the available data, especially when asymptomatic people or with mild symptoms are not usually screened. The purpose of this study was to perform sensitivity analysis of Rt estimates for COVID-19 surveillance in France based on three data sources with different sensitivities and specificities for identifying infected cases. We applied a statistical method developed by Cori et al. to estimate Rt using (1) confirmed cases identified from positive virological tests in the population, (2) suspected cases recorded by a national network of emergency departments, and (3) COVID-19 hospital admissions recorded by a national administrative system to manage hospital organization. Rt estimates in France from May 27, 2020, to August 12, 2022, showed similar temporal trends regardless of the dataset. Estimates based on the daily number of confirmed cases provided an earlier signal than the two other sources, with an average lag of 3 and 6 days for estimates based on emergency department visits and hospital admissions, respectively. The COVID-19 experience confirmed that monitoring temporal changes in Rt was a key indicator to help the public health authorities control the outbreak in real time. However, gaining access to data on all infected people in the population in order to estimate Rt is not straightforward in practice. As this analysis has shown, the opportunity to use more readily available data to estimate Rt trends, provided that it is highly correlated with the spread of infection, provides a practical solution for monitoring the COVID-19 pandemic and indeed any other epidemic.

Teachers’ Perceptions on their Readiness to Teach HIV/AIDS Education in Schools

South Africa is the highest HIV prevalence country in the world with young people (15-24 years) making up the largest proportion of HIV infected people. Kwazulu-Natal is the worst affected province nationally. Poor teacher training and the stigma around HIV/AIDS are contributing factors. Therefore an effective school-based HIV/AIDS education intervention program should encompass effective teacher training and curriculum development. A cross-sectional study was conducted among teachers to identify the factors that support or hinder their role in HIV/AIDS education. A self-administered questionnaire was used for interviewing teachers from stratified randomly-selected 2 primary and 2 secondary schools in the province of KwaZulu-Natal’s Pietermaritzburg region. Teachers from 2 out of the 4 selected schools were trained under an HIV/AIDS education intervention program funded by Community Care Project while those from the other 2 selected schools were not trained. This was meant to compare (using tables and graphs) the teachers’ perceptions, ability, skills, and their participation in HIV/AIDS education between the trained and untrained teachers. While about 56% of the untrained teachers never taught about HIV, it was only 5% of the trained teachers who never taught about HIV. While 97% (95% CI 93.85–100) of the trained teachers use interactive teaching methods, it was only 41% (95% CI 28.21-53.99) on the untrained teachers. Higher number of untrained teachers (70%) reported facing difficulty while talking about HIV issues compared to the trained teachers (9%). So trained teachers were more likely to participate, less likely to face difficulties, and more likely to use interactive teaching methods in HIV/AIDS classes compared to the untrained teachers. Inadequate time allocation to HIV/AIDS classes was found to be a barrier to HIV/AIDS education. This suggests the need to provide teachers with more support in terms of training and logistics.

Modeling and optimal control of the transmission dynamics of amebiasis

In this paper, the mathematical models for amebiasis are developed and presented. The first model considers the transmission dynamics of amebiasis coupled with two constant controls: treatment and sanitation. The next-generation matrix calculates the effective reproductive number, which is then used to assess model system stability. A sensitivity analysis is performed to determine the primary factors affecting disease transmission. Nonetheless, the results suggest that indirect transmission is more crucial than direct transmission in spreading disease. In addition, we extended the first model to incorporate time-dependent optimal control measures, namely community awareness, treatment, and sanitation. The aim was to reduce the number of infections emanating from interaction with carriers, infected people, and polluted environments while minimizing the expenses associated with adopting controls. The optimal control problem is solved by applying Pontryagin’s Maximum Principle and forward and backward-in-time fourth-order Runge–Kutta methods. The results indicate that an awareness program is optimal when a single control strategy is the only available option. However, when a combination of two controls is implemented, an approach combining awareness programs and treatment is shown to be optimal. Generally, the best strategy is implementing a combination of all three controls: awareness programs, sanitation, and treatment.

General practitioners’ knowledge, perception and experience on Long Covid: a cross-sectional study in Belgium and Malta

Abstract Background Over 10% of Covid-19 infected people experience persistent symptoms (Long Covid). As most Long Covid cases are in patients with a mild acute Covid-19 infection, primary health care and general practitioners (GPs) are at the forefront in their care. This study investigated GPs’ knowledge, perception and experience on Long Covid at cross-country level. Methods A cross-sectional study targeting GPs was conducted in Belgium and Malta during mid-2022. An online survey on Long Covid was disseminated. Descriptive and logistic regression analyses were performed. Results The survey was completed by 150 GPs (105 for Belgium, 45 for Malta). In both countries, most GPs reported insufficient scientific knowledge and information on Long Covid diagnosis and treatment. Accessibility to educational material was limited and an awareness-rising campaign was seen as merited, especially by Maltese GPs (OR = 6.81, 95%CI [1.49;31.12]). For diagnosing Long Covid, 54.7% reported the requirement of a positive Covid-19 test, more among Belgian than Maltese GPs (64.3% vs 45.2%, p = 0.036). To assess Long Covid, GPs applied diagnostic criteria by themselves (47.3%) in combination with persistent symptoms. 76.0% GPs reported caring for Long Covid patients, irrespective of practice type and GPs’ country, sex or age (p = 0.353; p = 0.241; p = 0.194; p = 0.058). Although most GPs (94.7%, p = 0.291) stated that Long Covid patients should follow multidisciplinary approach, only 29.8% of them reported to care for these patients by multidisciplinary cooperation and 48.3% by themselves/GP colleagues. Conclusions GPs frequently provide care to Long Covid patients and GPs’ care showed similarities at cross-country level. Although GPs perceived lack of scientific knowledge and educational material on Long Covid, similar diagnostic criteria were noted. Across Europe, uniform evidence-based guidelines, scientific support and training for GPs must be a priority to empower GPs in their Long Covid approach.

Self-awareness of hepatitis C infection in the United States: A cross-sectional study based on the National Health Nutrition and Examination Survey.

Hepatitis C virus (HCV) is a global health issue with an estimated prevalence of 2.4 to 3 million people in the US and 58 million worldwide. Previous reports from the US have shown that close to half of those with the infection are unaware of their status. Although the current therapy for HCV is very effective, the primary barrier has been the inability to diagnose a large fraction of those infected. We studied public awareness of HCV in the US using National Health Nutrition and Examination Survey data from 2013 to 2020. Our aim was to measure awareness of infection in individuals with HCV and identify possible barriers to diagnosis. In total, 206 individuals with HCV were included in the weighted analysis. The weighted awareness of infection was 60.1%, suggesting that over 0.8 million are unaware nationally. Awareness was significantly low in the Mexican American and Asian populations. Non-US citizens and non-US-born individuals also had poor awareness. The transaminases were more elevated in those unaware of the infection, suggesting their higher risk of liver fibrosis. Although the proportion of infected people aware of their illness has been rising, over 0.8 million are still unaware of their infection and their risk of liver damage. We believe policy measures focused on further intense screening and educational campaigns, particularly in high-risk groups, are vital in realizing the World Health Organization's goal of eliminating HCV as a global health threat.