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The COVID-19 (corona virus disease 2019) has caused serious impacts worldwide. Many scholars have done a lot of research on the prevention and control of the epidemic. The diagnosis of COVID-19 by cough is non-contact, low-cost, and easy-access, however, such research is still relatively scarce in China. Mel frequency cepstral coefficients (MFCC) feature can only represent the static sound feature, while the first-order differential MFCC feature can also reflect the dynamic feature of sound. In order to better prevent and treat COVID-19, the paper proposes a dynamic-static dual input deep neural network algorithm for diagnosing COVID-19 by cough. Based on Coswara dataset, cough audio is clipped, MFCC and first-order differential MFCC features are extracted, and a dynamic and static feature dual-input neural network model is trained. The model adopts a statistic pooling layer so that different length of MFCC features can be input. The experiment results show the proposed algorithm can significantly improve the recognition accuracy, recall rate, specificity, and F1-score compared with the existing models. © 2023 Chinese Institute of Electronics. All rights reserved.
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Aiming at the severe form of new coronavirus epidemic prevention and control, a target detection algorithm is proposed to detect whether masks are worn in public places. The Ghostnet and SElayer modules with fewer design parameters replace the BottleneckCSP part in the original Yolov5s network, which reduces the computational complexity of the model and improves the detection accuracy. The bounding box regression loss function DIOU is optimized, the DGIOU loss function is used for bounding box regression, and the center coordinate distance between the two bounding boxes is considered to achieve a better convergence effect. In the feature pyramid, the depthwise separable convolution DW is used to replace the ordinary convolution, which further reduces the amount of parameters and reduces the loss of feature information caused by multiple convolutions. The experimental results show that compared with the yolov5s algorithm, the proposed method improves the mAP by 4.6% and the detection rate by 10.7 frame/s in the mask wearing detection. Compared with other mainstream algorithms, the improved yolov5s algorithm has better generalization ability and practicability. © 2022 ACM.
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Owing to the continuous variant of the COVID-19 virus, the present epidemic may persist for a long time, and each breakout displays strongly region/time-dependent characteristics. Predicting each specific burst is the basic task for the corresponding strategies. However, the refinement of prevention and control measures usually means the limitation of the existing records of the evolution of the spread, which leads to a special difficulty in making predictions. Taking into account the interdependence of people' s travel behaviors and the epidemic spreading, we propose a modified logistic model to mimic the COVID-19 epidemic spreading, in order to predict the evolutionary behaviors for a specific bursting in a megacity with limited epidemic related records. It continuously reproduced the COVID-19 infected records in Shanghai, China in the period from March 1 to June 28, 2022. From December 7, 2022 when Mainland China adopted new detailed prevention and control measures, the COVID-19 epidemic broke out nationwide, and the infected people themselves took "ibuprofen” widely to relieve the symptoms of fever. A reasonable assumption is that the total number of searches for the word "ibuprofen” is a good representation of the number of infected people. By using the number of searching for the word "ibuprofen” provided on Baidu, a famous searching platform in Mainland China, we estimate the parameters in the modified logistic model and predict subsequently the epidemic spreading behavior in Shanghai, China starting from December 1, 2022. This situation lasted for 72 days. The number of the infected people increased exponentially in the period from the beginning to the 24th day, reached a summit on the 31st day, and decreased exponentially in the period from the 38th day to the end. Within the two weeks centered at the summit, the increasing and decreasing speeds are both significantly small, but the increased number of infected people each day was significantly large. The characteristic for this prediction matches very well with that for the number of metro passengers in Shanghai. It is suggested that the relevant departments should establish a monitoring system composed of some communities, hospitals, etc. according to the sampling principle in statistics to provide reliable prediction records for researchers. © 2023 Chinese Physical Society.
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We use unique data on the travel history of confirmed patients at a daily frequency across 31 provinces in China to study how spatial interactions influence the geographic spread of pandemic COVID-19. We develop and simultaneously estimate a structural model of dynamic disease transmission network formation and spatial interaction. This allows us to understand what externalities the disease risk associated with a single place may create for the entire country. We find a positive and significant spatial interaction effect that strongly influences the duration and severity of pandemic COVID-19. And there exists heterogeneity in this interaction effect: the spatial spillover effect from the source province is significantly higher than from other provinces. Further counterfactual policy analysis shows that targeting the key province can improve the effectiveness of policy interventions for containing the geographic spread of pandemic COVID-19, and the effect of such targeted policy decreases with an increase in the time of delay.
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Non-Drug Intervention (NDI) is one of the important means to prevent and control the outbreak of coronavirus disease 2019 (COVID-19), and the implementation of this series of measures plays a key role in the development of the epidemic. The purpose of this paper is to study the impact of different mitigation measures on the situation of the COVID 19, and effectively respond to the prevention and control situation in the "post-epidemic era". The present work is based on the Susceptible-Exposed-Infectious-Remove-Susceptible (SEIRS) Model, and adapted the agent-based model (ABM) to construct the epidemic prevention and control model framework to simulate the COVID-19 epidemic from three aspects: social distance, personal protection, and bed resources. The experiment results show that the above NDI are effective mitigation measures for epidemic prevention and control, and can play a positive role in the recurrence of COVID-19, but a single measure cannot prevent the recurrence of infection peaks and curb the spread of the epidemic;When social distance and personal protection rules are out of control, bed resources will become an important guarantee for epidemic prevention and control. Although the spread of the epidemic cannot be curbed, it can slow down the recurrence of the peak of the epidemic;When people abide by social distance and personal protection rules, the pressure on bed resources will be eased. At the same time, under the interaction of the three measures, not only the death toll can be reduced, but the spread of the epidemic can also be effectively curbed. © 2022 ACM.
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Based on SIR model, combined with the mode of COVID-19 epidemic spread in Wuhan, the SIR model of COVID-19 epidemic spread is constructed, which mainly includes three aspects: simulation of the average number of infected people in COVID-19, simulation of cross-infection in COVID-19 and simulation of contact infection in COVID-19. Using the results of these three simulations, we can predict the spread of COVID-19 epidemic in the region, and find out the methods to prevent and control the outbreak or spread of the epidemic. © 2023 SPIE.
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Many zoonotic diseases are found in wild animals and present a serious risk to human health, in particularly the virus carried by birds flying freely around the world is hard to control. There are three main bird migration routes which cover the most areas of China. It is important to investigate and fully understand the types of avian transmitted diseases in key areas on the bird migration routines and its impacts on both birds and human health. However, no literature is available in how about the risk of virus carried by migrating birds, and how to predict and reduce this risk of virus spreading to human being so far. In this paper, we first reviewed the main pathogen types carried by birds, including coronaviruses, influenza viruses, parasites, Newcastle disease virus (NDV), etc., and then discussed the spread risk of avian viruses to human being and animals in key areas of biosafety prevention. We also analyzed and discussed the risk of cross-spread of diseases among different bird species in nature reserves located on bird migration routes which provide sufficient food sources for migratory birds and attract numerous birds. Diseases transmitted by wild birds pose a serious threat to poultry farms, where high density of poultry may become avian influenza virus (AIV) reservoirs, cause a risk of avian influenza outbreaks. Airports are mostly built in suburban areas or remote areas with good ecological environment. There are important transit places for bird migration and densely populated areas, which have serious risk of disease transmission. Finally, this paper puts forward the following prevention suggestions from three aspects. First, establish and improve the monitoring and prediction mechanism of migratory birds, and use laser technology to prevent contact between wild birds and poultry. Second, examine and identify virus types carried by birds in their habitats and carry out vaccination. Third, protect the ecological environment of bird habitat, and keep wild birds in their natural habitat, so as to reduce the contact between wild birds and human and poultry, and thus reduce the risk of virus transmission.
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The ongoing COVID-19 epidemic has had a great impact on social activities and the economy. The usage technical analysis tools to provide a more accurate and efficient reference for epidemic control measures is of great significance. This paper analyzes the characteristics and deficiencies of the existing technical methods, such as regression model, simulation calculation, differential equation and so on. By analyzing past outbreak cases and comparing the epidemic prevention measures of different cities, we discuss the importance of early and timely prevention in controlling the epidemic, and the importance of analyzing and formulating plans in advance. We then make the key observation that the spread of the virus is related to the topology of the urban network. This paper further proposes an epidemic analysis model of the optimized PageRank model, and gives a ranking algorithm for virus transmission risk levels based on road nodes, forming a visual risk warning level map, and applies the algorithm to the epidemic analysis of Yuegezhuang area in Beijing. Finally, more in-depth research directions and suggestions for prevention and control measures are put forward. © 2023 SPIE.
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As cruise ships call at many ports and passengers come from all over the world, it is very easy to carry viruses on cruise ships. Under the control of the epidemic situation on board, the solid waste generated by them should be scientifically treated to prevent the spread of infectious diseases such as COVID-19 pneumonia. Therefore, Reasonable selection of waste disposal ports and formulation of unloading plans are directly related to the resumption of cruise operations. This study considers the cost and risk of waste disposal, uses robust optimization to deal with waste volume, increases the scenarios of port service interruption due to epidemics and other reasons, and proposes a variety of emergency strategies. Finally, the relevant strategies are selected according to the decision-maker's preference for cost and risk;By solving the relevant examples, the optimal choice of the cruise ship waste disposal port under the epidemic situation is given, which verifies the validity and feasibility of the model. The research helps to improve the management of cruise waste during the post-epidemic period, and has practical value and guiding significance for the normal operation and development of the global cruise market. © 2023 SPIE.
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Objectives: To analyze the budget impact (BI) of Covid-19 vaccines from a mixed U.S commercial and Medicare payer perspective after depletion of the Federally-Purchased Supply (FPS). Method(s): BI analyses were conducted in a hypothetical one-million member health plan with a mixed commercial (55%) and Medicare (45%) population over a one-year time horizon based on the current (January 2023) Covid-19 vaccine recommendations from the Centers for Disease Control and Prevention (CDC). The two scenarios in the model include 1) the health plan does not pay for Covid-19 vaccines, and 2) after the depletion of FPS, the health plan must cover all costs for Covid-19 vaccines. Model inputs include the market shares of available Covid-19 vaccines in the US as of December 2022, Covid-19 vaccine utilization trends stratified into age groups (<12, 12-17, 18-24, 25-49, 50-64, >=65 years old) between commercial and Medicare populations, and predicted Covid-19 vaccine costs. Model inputs were based on the CDC publicly available data, real world evidence, published literature, and expert opinions. Sensitivity analyses (SA) were conducted to test uncertainties arising from the input values in the model. Result(s): The number of members receiving one primary dose, completed Covid-19 vaccine series, one booster dose and two booster doses was estimated at 9,253, 49,720, 594,933 and 29,387, respectively. The incremental Covid-19 vaccine cost per member per month over one year after depletion of the FPS was $5.92 for the commercial population, $8.93 for the Medicare population, and $7.27 for the total population in the health plan. In the SA, the largest effect was observed for the scenario which varied the percentage of population >=65 years old receiving one booster dose. Conclusion(s): The model results indicate that there will be a high budget impact from a mixed U.S commercial and Medicare perspective after depletion of the FPS of Covid-19 vaccines.Copyright © 2023
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BackgroundRheumatoid arthritis (RA) and spondyloarthritis, including either Psoriatic Arthritis (PsA) and Ankylosing Spondylitis (AS), are some of the most diagnosed autoimmune rheumatic diseases (AIRDs) in rheumatologists' routine clinical practice [1]. Understanding patients' health and functional status is crucial to provide personalized management strategies to optimize disease control and enhance the quality of life.ObjectivesWe aimed to compare disease burden in patients with RA, PsA or AS by assessing Patient-Reported Outcome Measurement Information System (PROMIS) Physical Health, Global Mental Health, Physical Function and Fatigue 4a together with VAS Pain.MethodsData were obtained in the international COVID vaccination in autoimmune rheumatic diseases study second e-survey (COVAD study). Demographics, AIRD diagnosis, disease activity, PROMIS Global Physical health, PROMIS Global Mental Health, PROMIS Physical Function SF10 and PROMIS Fatigue 4a score were extracted from the COVAD study database. For this study, we only included patients with self-reported RA or spondyloarthritis (either PsA or AS) undergoing active treatment with conventional synthetic disease-modifying drugs (DMARDs) and/or biologic DMARDs, who answered all the survey questions. Active disease was defined as the patient's perception of their disease as active in the four weeks before their first COVID-19 vaccine shot. Analysis of Variance with Bartlett's and Tukey's test was used to compare continuous variables between groups.ResultsFrom January to June 2022, n.1907 patients with RA, female 87.62% (1671/1907), with mean age (±SD) 50.95 ±13.67, n.311 patients with PsA, female 67.20% (209/311), with a mean age of 50.42 ±12.70, and n.336 patients with AS, male 51.31% (209/311), with a mean age of 43.13 ±12.75 years, responded to the COVAD e-survey.In those with active disease, neither physical health, global mental health, physical function, fatigue, nor pain were different among groups (Table 1, Figure 1). Patients with inactive AS had higher mean global physical health scores than RA patients (13.13 ±2.93 VS RA 12.48 ±2.90, p=0.01, Table 1). Those with inactive RA or PsA showed more severe fatigue (PsA 10.58 ±2.22, RA 10.45 ±4.08 VS 9.4 ±4.13, p =0.01 for both). Patients with inactive RA also reported poorer physical function and more residual pain than those with AS (37.79 ±8.86 VS 41.13 ±7.79, p<0.001;3.87 ±2.45 VS 3.34 ±2.39, p=0.01, respectively). Similarly, residual pain was perceived as higher in patients with inactive PsA than those with AS (4.04 ±2.50 VS 3.34 ±2.39, p=0.01)ConclusionDisease burden is roughly comparable in patients with active RA, PsA or AS. Patients with inactive RA and PsA suffer higher disease burden than those with inactive AS.Reference[1]Mease PJ, Liu M, Rebello S, Kang H, Yi E, Park Y, Greenberg JD. Comparative Disease Burden in Patients with Rheumatoid Arthritis, Psoriatic Arthritis, or Axial Spondyloarthritis: Data from Two Corrona Registries. Rheumatol Ther. 2019 Dec;6(4):529-542.Table 1.Patient-Reported Outcome Measures between groups.Inactive diseaseAS (n.185)PsA (n.179)RA (n.1167)MeanSDMeanSDMeanSDPROMIS Global Physical Health13.13*2.9512.433.2712.482.90p=0.01, VS RAPROMIS Global Mental Health13.313.3612.973.3312.843.17PROMIS Fatigue 4a9.44.1310.58*4.2210.45*4.08p=0.01, bothPROMIS Physical Function SF10 Score41.137.3939.279.0137.79*8.86p<0.001, VS ASVAS Pain3.342.394.04*2.503.87*2.45p=0.01, bothActive DiseaseAS (n.35)PsA (n.38)RA (n.189)MeanSDMeanSDMeanSDPROMIS Global Physical Health11.053.1910.102.7611.243.41PROMIS Global Mental Health11.313.2610.843.6311.893.30PROMIS Fatigue 4a12.944.8712.844.4211.754.68PROMIS Physical Function SF10 Score35.829.6233.528.7634.909.80VAS Pain4.682.775.02.544.682.61Figure 1.Violin plots showing kernel densities, quartiles and median for Patient-Reported Outcome Measures for patients with RA, PsA and AS, stratified by disease activity status.[Figure omitted. See PDF]Acknowledgements:NIL.Disclosure of InterestsVincenzo Venerito: None declared, Marc Fornaro: None declared, Florenzo Iannone: None declared, Lorenzo Cavagna: None declared, Masataka Kuwana: None declared, Vishwesh Agarwal: None declared, Naveen Ravichandran: None declared, Jessica Day Grant/research support from: JD has received research funding from CSL Limited., Mrudula Joshi: None declared, Sreoshy Saha: None declared, Syahrul Sazliyana Shaharir: None declared, Wanruchada Katchamart: None declared, Phonpen Akarawatcharangura Goo: None declared, Lisa Traboco: None declared, Yi-Ming Chen: None declared, Parikshit Sen: None declared, James B. Lilleker Speakers bureau: JBL has received speaker honoraria/participated in advisory boards for Sanofi Genzyme, Roche, and Biogen. None is related to this manuscript., Consultant of: JBL has received speaker honoraria/participated in advisory boards for Sanofi Genzyme, Roche, and Biogen. None is related to this manuscript., Arvind Nune: None declared, John Pauling: None declared, Chris Wincup: None declared, Ai Lyn Tan Speakers bureau: ALT has received honoraria for advisory boards and speaking for Abbvie, Gilead, Janssen, Lilly, Novartis, Pfizer, and UCB., Nelly Ziade Speakers bureau: NZ has received speaker fees, advisory board fees, and research grants from Pfizer, Roche, Abbvie, Eli Lilly, NewBridge, Sanofi-Aventis, Boehringer Ingelheim, Janssen, and Pierre Fabre;none are related to this manuscript, Grant/research support from: NZ has received speaker fees, advisory board fees, and research grants from Pfizer, Roche, Abbvie, Eli Lilly, NewBridge, Sanofi-Aventis, Boehringer Ingelheim, Janssen, and Pierre Fabre;none are related to this manuscript, Marcin Milchert: None declared, Abraham Edgar Gracia-Ramos: None declared, Carlo Vinicio Caballero: None declared, COVAD Study: None declared, Vikas Agarwal: None declared, Rohit Aggarwal Speakers bureau: RA has a consultancy relationship with and/or has received research funding from the following companies: Bristol Myers-Squibb, Pfizer, Genentech, Octapharma, CSL Behring, Mallinckrodt, AstraZeneca, Corbus, Kezar, Abbvie, Janssen, Alexion, Argenx, Q32, EMD-Serono, Boehringer Ingelheim, and Roivant., Grant/research support from: RA has a consultancy relationship with and/or has received research funding from the following companies: Bristol Myers-Squibb, Pfizer, Genentech, Octapharma, CSL Behring, Mallinckrodt, AstraZeneca, Corbus, Kezar, Abbvie, Janssen, Alexion, Argenx, Q32, EMD-Serono, Boehringer Ingelheim, and Roivant., Latika Gupta: None declared.
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Objective: To evaluate the influence of coronavirus disease 2019 (COVID-19) prevention and control measures on the transmission and epidemic of influenza in Chongqing, so as to provide references for formulating targeted influenza prevention and control strategies. Methods: The influenza surveillance data, during the year 2018 to 2020, were collected through the "China Influenza Surveillance Information System", and the seasonal characteristics of influenza epidemic were analyzed. The percentage of influenza like cases (ILI%) and influenza virus positive rate between 2020 and 2018-2019 were compared, so as to evaluate the impact of COVID-19 prevention and control measures on influenza epidemic characteristics. Results: The annual proportions of ILI cases in Chongqing were respectively 3.53%, 2.23% and 1.2% from 2018 to 2020, while the positive rates of influenza virus were respectively 13.97%, 23.81% and 2.65%. The distribution trend of ILI% from 2018 to 2019 fluctuated were similar, but it continued to drop and remain at a low level since February 2020. The positive rate of influenza virus showed an epidemic peak from December to March in 2018-2019, also peaked from November 2019 to January 2020, but decreased to 0 in March. ILI% was positively correlated with the positive rate of influenza virus (r=0.404 8, P < 0.05). In 2020, compared with the same period of 2018-2019, the growth rate of ILI% was -66.09% and -46.32%, respectively. The positive rate of influenza virus in 2020 decreased by 81.03% and 88.87% compared with the same period of 2018-2019, respectively. The growth rates of influenza virus positive rate in January 2020 were decreased with a small rate of about 39.87%, and with a significantly decline of more than 93.65% from February. No influenza epidemic was found after March. Conclusions: Since COVID-19 prevention and control measures were implemented in January 2020 in Chongqing, the ILI% and the positive rate of influenza virus in sentinel hospitals decreased significantly. In the season of high incidence of respiratory infectious diseases, personal protection and other measures can effectively reduce influenza virus infection.
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PurposeThis study aims to focus on the preparation and characterization of the silver nanowire (AgNWs), as well as their application as antimicrobial and antivirus activities either with incorporation on the waterborne coating formulation or on their own.Design/methodology/approachPrepared AgNWs are characterized by different analytical instruments, such as ultraviolet-visible spectroscope, scanning electron microscope and X-ray diffraction spectrometer. All the paint formulation's physical and mechanical qualities were tested using American Society for Testing and Materials, a worldwide standard test procedure. The biological activities of the prepared AgNWs and the waterborne coating based on AgNWs were investigated. And, their effects on pathogenic bacteria, antioxidants, antiviral activity and cytotoxicity were also investigated.FindingsThe obtained results of the physical and mechanical characteristics of the paint formulation demonstrated the formulations' greatest performance, as well as giving good scrub resistance and film durability. In the antimicrobial activity, the paint did not have any activity against bacterial pathogen, whereas the AgNWs and AgNWs with paint have similar activity against bacterial pathogen with inhibition zone range from 10 to 14 mm. The development of antioxidant and cytotoxicity activity of the paint incorporated with AgNWs were also observed. The cytopathic effects of herpes simplex virus type 1 (HSV-1) were reduced in all three investigated modes of action when compared to the positive control group (HSV-1-infected cells), suggesting that these compounds have promising antiviral activity against a wide range of viruses, including DNA and RNA viruses.Originality/valueThe new waterborne coating based on nanoparticles has the potential to be promising in the manufacturing and development of paints, allowing them to function to prevent the spread of microbial infection, which is exactly what the world requires at this time.
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Introduction: Combination of daratumumab (Dara) and lenalidomide (Len) may enhance the function of teclistamab (Tec), potentially resulting in improved antimyeloma activity in a broader population. We present initial safety and efficacy data of Tec-Dara- Len combination in patients with multiple myeloma (MM) in a phase 1b study (MajesTEC-2;NCT04722146). Method(s): Eligible patients who received 1-3 prior lines of therapy (LOT), including a proteasome inhibitor and immune-modulatory drug, were given weekly doses of Tec (0.72-or- 1.5 mg/kg with step-up dosing) + Dara 1800 mg + Len 25 mg. Responses per International Myeloma Working Group criteria, adverse events (Aes) per CTCAE v5.0, and for cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) per ASTCT guidelines, were assessed. Result(s): 32 patients received Tec-Dara- Len (0.72 mg/kg, n = 13;1.5 mg/kg, n = 19). At data cut-off (11 July 2022), median follow-up (range) was 5.78 months (1.0-10.4) and median treatment duration was 4.98 months (0.10-10.35). Median age was 62 years (38-75);87.5% were male. Median prior LOT was 2 (1-3), 18.8% were refractory to Dara and 28.1% refractory to Len. CRS was most frequent AE (81.3% [n = 26], all grade 1/2), 95% occurred during cycle1. Median time to onset was 2 days (1-8), median duration was 2 days (1-22). No ICANS were reported. Frequent Aes (>=25.0% across both dose levels) were neutropenia (75.0% [n = 24];grade 3/4: 68.8% [n = 22]), fatigue (43.8% [n = 14];grade 3/4: 6.3% [n = 2]), diarrhoea (37.5% [n = 12];all grade 1/2), insomnia (31.3% [n = 10];grade 3/4: 3.1% [n = 1]), cough (28.1% [n = 9];all grade 1/2), hypophosphatemia (25.0% [n = 8];all grade 1/2), and pyrexia (25% [n = 8];grade 3/4: 6.3% [n = 2]). Febrile neutropenia frequency was 12.5% (n = 4). Infections occurred in 24 patients (75.0%;grade 3/4: 28.1% [n = 9]). Most common were upper respiratory infection (21.9% [n = 7]), COVID-19 (21.9% [n = 7]), and pneumonia (21.9% [n = 7]). Three (9.4%) had COVID-19 pneumonia. One (3.1%) discontinued due to COVID-19 infection and this patient subsequently died of this infection. Overall response rate (ORR, median follow-up) was 13/13 (8.61 months) at 0.72 mg/kg and 13/16 evaluable patients (less mature at 4.17 months) at 1.5 mg/kg. 12 patients attained very good/better partial response at 0.72 mg/kg dose, and response was not mature for 1.5 mg/kg group. Median time to first response was 1.0 month (0.7-2.0). Preliminary pharmacokinetic concentrations of Tec-Dara- Len were similar as seen with Tec monotherapy. Tec-Dara- Len- treatment led to proinflammatory cytokine production and T-cell activation. Conclusion(s): The combination of Tec-Dara- Len has no new safety signals beyond those seen with Tec or Dara-Len individually. Promising ORR supports the potential for this combination to have enhanced early disease control through the addition of Tec. These data warrant further investigation.
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After careful screening to exclude coronavirus symptoms we invite some patients into the practice to be examined. With longstanding patients I hope that this will be just a brief interruption to our normal relationship, but when I haven't previously met the patient it poses a significant challenge to building a rapport. In the past week the number of new patients reporting coronavirus symptoms has fallen, as has the death rate at our local hospital.
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Shortly after the novel coronavirus (now known as SARSCoV- 2) was recognized, data began to accumulate on the virus's effects on children. Initial data showed that children were more likely to be mildly affected, compared to adults, with lower risks of hospitalization and death. However, in April of 2020, reports appeared of a severe disease in children occurring about two-six weeks after infection with SARS-CoV-2. The features were similar to those seen in a rare vasculitis condition called Kawasaki disease. On May 14, 2020, the Centers for Disease Control and Prevention (CDC) issued a national health advisory regarding this new condition, which was called multisystem inflammatory syndrome in children (MIS-C). The current case definition for MIS-C includes six criteria: (1) serious illness leading to hospitalization or resulting in death;(2) age less than 21 years;(3) measured fever over 38 degrees Celsius or report of subjective fever;(4) laboratory evidence of inflammation;(5) new onset involvement in at least two of the following (cardiac involvement, mucocutaneous involvement, shock, gastrointestinal involvement, and hematologic involvement);and (6) laboratory-confirmed SARS-CoV-2 infection or an epidemiologic link to a person with COVID-19. According to CDC, as of January 3, 2023, there have been 9,333 patients in the United States meeting the case definition of MIS-C, with 76 deaths. The median age of patients was nine years, with half of those affected between the ages of five and 13 years. More than half of the reported patients on whom race-ethnicity information was available were in children who are Hispanic/Latino or Black, non-Hispanic. Over 60% of reported patients were male. Most affected children had previously been healthy. A better understanding of the pathogenesis of this serious illness is needed to provide better treatment options for children with MIS-C. Prevention of MIS-C is focused on the prevention of SARS-CoV-2 infection through staying up to date with COVID-19 vaccination, masking, and other prevention strategies.
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Severe acute respiratory syndrome coronavirus (SARS-CoV-2), the causative agent of the current COVID-19 pandemic, has evolved to have a wide range of hosts, including non-human primates, wild and domestic animals. Determining the susceptibility of different animal species to SARS-CoV-2 infection and the role of animals in the epidemiology of the disease will be critical to designing appropriate human and veterinary public health responses to this pandemic. A better understanding of the susceptibility of animal species to SARS-CoV-2 may help clarify transmission mechanisms and identify potential reservoirs and sources of infection that are important for both animal and human health. The current pandemic produced by SARS CoV-2 and its variants represents an example of the unique concept of health (One Health) in which humans and animals are components of the same epidemiological chain. In this paper, only the natural infections found in different animals species will be reviewed, according to literature data, regarding the species of affected animals, the transmission patterns (human-animal, animal-human), clinical aspects, diagnosis confirmation and a brief presentation of the prevention possibilities through vaccination.
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Introduction: Croatian National Cancer Registry of Croatian Institute for Public Health reported that in year 2020 lung cancer was the second most common cancer site diagnosed in men with 16% and the third most common in women with 10% incidence among all cancer sites. Unfortunatelly lung cancer has the highest mortality in both men and women. Haematological malignancies had 7% share in all malignancies in both male and female cances cases. In 2020 190 newly diagnosed cases of lymphatic leukemia in men and 128 cases in women were reporeted, meaning 1.5 and 1.2% of all malignancies, respectively. Chronic lymphatic leukemia (CLL) is an advanced age disease and incidence increases with age. Impaired immunity, T and B cell dysfunction in CLL, chromosomal aberations, long-term immunosuppressive therapy and genetic factors can all cause secondary malignancies. Co- occurence of solid tumors and CLL is very rare. Although patiens with CLL have an increased risk of developing second primary malignancies including lung carcinoma, the data about their clinical outcomes are lacking. Parekh et al. retrospectively analyzed patients with simultaneous CLL and lung carcinoma over a 20-year period, and they found that ~2% of patients with CLL actually developed lung carcinoma. The authors claimed that up to 38% of patients will also develop a third neoplasm more likely of the skin (melanoma and basal cell carcinoma), larynx (laryngeal carcinoma) or colon. Currently there are no specific guidelines for concurrent CLL and non-small cell lung carcinoma (NSCLC) treatment. Usually, when the tumors are diagnosed simultaneously, treatment is based to target the most aggressive malignancy, as the clinical outcomes depend on the response of the tumor with the poorest prognosis. For this reason, a multidisciplinary approach is mandatory. Case report: A patient with history of coronary heart disease, myocardial infarction and paroxysmal atrial fibrillation was diagnosed in 2019 (at the age of 71) with B chronic lymphocytic leukemia with bulky tumor (inguinal lymph nodes 8x5 cm), stage B according to Binet, intermediate risk. He was treated with 6 cycles of chemoimmunotherapy (rituximab/cyclofosfamid/fludarabine). In 10/2019 remission was confirmed, but MSCT described tumor in the posterior segment of upper right lung lobe measuring 20x17 mm and bilateral metastases up to 11 mm. Bronchoscopy and biopsy were performed, and EGFR neg, ALK neg, ROS 1 neg, PD-L1>50% adenocarcinoma was confirmed. He was referred to Clinical Hospital Center Osijek where monotherapy with pembrolizumab in a standard dose of 200 mg intravenously was started in 01/2020. Partial remission was confirmed in October 2020. Immunotherapy was discontinued due to development of pneumonitis, dysphagia and severe weight loss (20kg), but without radiologically confirmed disease progression. At that time he was referred to our hospital for further treatment. Gastroscopy has shown erosive gastritis with active duodenal ulcus, Forrest III. Supportive therapy and proton pump inhibitor were introduced. After complete regression of pneumonitis, improvement of general condition and resolution of dysphagia, no signs of lung cancer progression were found and pembrolizumab was reintroduced in 12/2021. Hypothyroidism was diagnosed in 01/2021 and levothyroxine replacement ther apy was started. In 03/2021 he underwent surgical removal of basal cell carcinoma of skin on the right temporal region with lobe reconstruction. From 02/2021, when pembrolizumab was reintroduced, regression in tumor size was continously confirmed with complete recovery of general condition. He was hospitalized for COVID 19 infection in 09/2021, and due to complications pembrolizumab was discontinued till 11/2021. Lung cancer immunotherapy proceeded till 11/2022, when Multidisciplinary team decided to finish pembrolizumab because of CLL relapse. CLL was in remission till August 2022 when due to B symptoms, lymphcytosis, anemia and generalized lymphadenopathy, hematological workup including biopsy of cervical lymph node was performed and CLL/SLL relapse was confirmed. Initially chlorambucil was introduced, but disease was refractory. Based on cytogenetic test results (IGHV unmutated, negative TP53) and due to cardiovascular comorbidity (contraindication for BTK inhibitors) venetoclax and rituximab were started in 01/2023. After just 1 cycle of treatment normal blood count as well as regression of B symptoms and peripheral lymphadenopathy occured, indicating the probability of complete disease remission. In our patient with metastatic lung adenocarcinoma excellent disease control is achieved during 41 month of treatment in first line setting. Furthermore, relapsed/refractory CLL/SLL is currently in confirmed remission. Conclusion(s): Successful treatment of patients with multiple primary malignancies is based on multidisciplinarity, early recognition and management of side effects, treatment of comorbidities with the aim of prolonging life, controlling symptoms of disease and preserving quality of life.
ABSTRACT
A chronic respiratory disease known as pneumonia can be devastating if it is not identified and treated in a timely manner. For successful treatment and better patient outcomes, pneumonia must be identified early and properly classified. Deep learning has recently demonstrated considerable promise in the area of medical imaging and has successfully applied for a few image-based diagnosis tasks, including the identification and classification of pneumonia. Pneumonia is a respiratory illness that produces pleural effusion (a condition in which fluids flood the lungs). COVID-19 is becoming the major cause of the global rise in pneumonia cases. Early detection of this disease provides curative therapy and increases the likelihood of survival. CXR (Chest X-ray) imaging is a common method of detecting and diagnosing pneumonia. Examining chest X-rays is a difficult undertaking that often results in variances and inaccuracies. In this study, we created an automatic pneumonia diagnosis method, also known as a CAD (Computer-Aided Diagnosis), which may significantly reduce the time and cost of collecting CXR imaging data. This paper uses deep learning which has the potential to revolutionize in the area of medical imaging and has shown promising results in the detection and classification of pneumonia. Further research and development in this area is needed to improve the accuracy and reliability of these models and make them more accessible to healthcare providers. These models can provide fast and accurate results, with high sensitivity and specificity in identifying pneumonia in chest X-rays. © 2023 IEEE.
ABSTRACT
Using a multilevel modelling approach, this study investigates the impact of urban inequalities on changes to rail ridership across Chicago's "L” stations during the pandemic, the mass vaccination rollout, and the full reopening of the city. Initially believed to have an equal impact, COVID-19 disproportionally impacted the ability of lower socioeconomic status (SES) neighbourhoods' to adhere to non-pharmaceutical interventions: working-from-home and social distancing. We find that "L” stations in predominately Black or African American and Hispanic or Latino neighbourhoods with high industrial land-use recorded the smallest behavioural change. The maintenance of higher public transport use at these stations is likely to have exacerbated existing health inequalities, worsening disparities in users' risk of exposure, infection rates, and mortality rates. This study also finds that the vaccination rollout and city reopening did not significantly increase the number of users at stations in higher vaccinated, higher private vehicle ownership neighbourhoods, even after a year into the pandemic. A better understanding of the spatial and socioeconomic determinants of changes in ridership behaviour is crucial for policymakers in adjusting service routes and frequencies that will sustain reliant neighbourhoods' access to essential services, and to encourage trips at stations which are the most impacted to revert the trend of declining public transport use.