Cooperate with community health centers to eliminate HCV in low prevalence region of South China

Background: Shenzhen, a city of immigrants in South China, has a low HCV incidence rate of 19.47 per 100,000. To eliminate HCV in this low prevalence region, it may be efficiency to collaborate with the communities to screen HCV in high risk population. There are 849 Community Health Centers up to now in Shenzhen. The study aimed to evaluate the model of HCV elimination in high-risk population with Community Health Centers. Method(s): The Shenzhen Medical Association assigned hepatologists to educate Primary Care Physicians (PCPs) of 13 Community Health Centers in Bao'an District from 2021.6-2022.6. The PCPs need to take HCV knowledge tests before and after the training. Only when all the questions are answered correctly can the test be passed. Then they recommend the high risk population, e.g., PWID, pricking wound, iatrogenic exposure, to do the HCV antibody test and transfer the patients with HCV-Ab (+) to the hepatologist of Shenzhen Bao'an People's Hospital. Result(s): 151 PCPs participated in HCV knowledge education, the pass rate improved from 15.2% to 53.8% after the training. The high risk population screening number in Community Health Centers improved from 192 (a year before) to 300, even affected by the lockdown of COVID-19. The HCV antibody positive rate in high risk population is 4% (12/300), higher than the hospital population (0.8%, Shenzhen Bao'an People's Hospital), the blood donor (0.3%, Shenzhen Blood Center). The HCV-Ab positive patients in communities transferred to Shenzhen Bao'an People's Hospital, where the rate of DAA treatment is improved from 36.6% (a year before) to 64.1%. Conclusion(s): It is an efficient way to achieve HCV elimination earlier to screening in high risk population through PCPs in low prevalence region. Expanding this model to other Community Health Centers in Shenzhen may accelerate HCV elimination. (Figure Presented).

Person Detection Based Adaptive Video Synthesis: A Fusion Framework for Ultra HD Panorama and Green Screen Videos

The past two years have witnessed the increasing prevalence of metaverse, while the COVID-19 pandemic has accelerated the formation of a non-contact culture. Under this circumstance, virtual reality once again attracts the public attention. Panorama video, as one of the most important forms of virtual reality, provides users with excellent immersion experience. This paper has proposed a fusion framework for Ultra HD panorama videos and green screen videos. In this framework, panorama videos are set as the virtual background layer on which the user-defined real foreground layer of portrait obtained by green screen matting is superimposed. During video fusion process, the portrait size is adaptively determined by parameters provided by a person detection algorithm running on panorama videos. Therefore, a more natural video synthesis result can be achieved, and presented on a head-mounted display or a flat screen device to provide an indistinguishable visual experience to the users. © 2022 IEEE.

Smartphone Built-in Features: Do They Help Our Diabetic Patients?

Objective: To evaluate the pre-set features of smartphones and the inclusion of ADCES7 guidelines for Diabetes self-care during the COVID-19 era. Method(s): The pre-loaded applications of the iPhone 13 and Samsung S22 Ultra were tested with the ADCES7 parameters: 1) Healthy eating, 2) Being Active, 3) Monitoring, 4) Taking Medication, 5) Problem Solving, 6 )Healthy coping, 7) Reducing Risks. We evaluated the smartphones for the following subcategorties of the ADCES7 parameters: 1a) Nutrition, 1b) Calorie-counting;2a) Step-counting, 2b) Calorie-burning, 3a): Blood pressure, 3b) Blood glucose, 3c) HbA1c, 3d) Weight, 3e) Push notification, 4a) Med Log, 5a) Contact healthcare team, 5b) Contact family;6a) Mental health outreach, 7a) Goal-Setting, 7b) Graph analysis. We added additional categories 8) Insulin pumps and 9) Language. Result(s): 1. Nutrition facts= Apple(Yes), Samsung(No);2. Calorie counting= Apple(Yes), Samsung(Yes);3. Step counting= Apple(Yes), Samsung(Yes);4. Calorie Burning= Apple(No), Samsung(Yes);5. Monitoring BP= Apple(No). Samsung(Yes);6. Monitoring Blood Glucose= Apple(No), Samsung(Yes);7. Monitoring HbA1c= Apple(No), Samsung(Yes);8. Weight Monitoring= Apple(Yes), Samsung(Yes);9. Push Notifications and Med Reminders= Apple(Yes), Samsung(Yes);10. Goal setting= Apple(No), Samsung(Yes);11. Med Log= Apple(No), Samsung(Yes);12. Facetime, Samsung Video Call= Apple(Yes), Samsung(Yes);13. Healthy Coping= Apple(No), Samsung(No);14. Goal Setting for Steps= Apple(No), Samsung(Yes);15. Graph Analysis= Apple(Yes), Samsung(Yes);16. Insulin pumps= Apple(No), Samsung(No);17. Foreign languages= Apple(46), Samsung(187) Samsung provides more ADCES7 parameters and more language options than Apple. Conclusion(s): The smartphones have internal resources for patients to self-manage their Diabetes Mellitus. As MDs, we can continue to partner with our patients for diabetes management during COVID-19 and beyond.

A telehealth-based training model for an ambulatory care pharmacy skills course

Description: Increasingly, pharmacy services are provided using telehealth-based modalities. This paper describes a pharmacy skills course that utilised telehealth principles to train students on the technical and communications skills necessary for the ambulatory care setting. Zoom breakout rooms, electronic health records, YouTube video vignettes, and teaching assistants portraying patients/physicians simulated a telehealth-based ambulatory care setting. Evaluation: Five quizzes and six written assignments were utilised to measure student's knowledge and skills. At the end of the course, students were evaluated through a three-station objective structured clinical exam (OSCE). Students also completed a pre/post attitudes survey. Result(s): Overall, students performed well on various assessments including quizzes and written assignments. The majority of the students performed well on the OSCE. Significant improvement was noted on all items in the attitudes survey. Conclusion(s): This study suggests that a telehealth training model can be effective in teaching pharmacy students both the technical and communication skills necessary for practice in the ambulatory care setting. Copyright © 2021 FIP.

Research progress of therapeutic antibodies against COVID-19

Antibody-based biological products have gradually become a new strategy for the treatment of infectious diseases. In the past few years, especially after the outbreak of the COVID-19 in 2019, researches on therapeutic SARS-CoV-2 antibodies have greatly developed. Researchers around the world have developed a series of antibody treatment programs with extremely high efficiency to fight against COVID-19. From the early days of the pandemic, therapeutic antibodies were only used for emergency treatment of clinically severe patients, now they can be used for both pre-exposure prophylaxis and post-infection treatment. We summarize the research progress of therapeutic antibodies for SARS-CoV-2, including convalescent plasma, animal antiserum, marketed mAbs, non-targeted therapeutic mAbs, and bispecific antibodies, etc. The limitations and future application prospects of the SARS-CoV-2 therapeutic mAbs are also discussed. Copyright © 2022, Chinese Journal of New Drugs Co. Ltd. All right reserved.

Covid-19 Diagnosis via Voice Using Online Sequential Extreme Learning Machine

With the worldwide spreading of Coronavirus disease 2019 (Covid-19) pandemic, besides the traditional diagnosing approach, Artificial Intelligence provides additional support for the pre-diagnosis of Covid-19 by using data such as patients' images, and sounds, etc. Being able to recognize Covid-19 positive patients quickly and correctly is the key to preventing the expansion of the disease. However, the existing Covid-19 diagnosis models still face challenges due to the complex network structure and additional medical examination. It takes much time to return a diagnosis result. In this paper, a diagnostic model is proposed as an early work for Covid-19 diagnosis using sound samples. The features of sound signals are expressed by Mel Frequency Cepstral Coefficients, which are input into the Online Sequential Extreme Learning Machine for normal/abnormal detection. Data from an open-source database were used to train the proposed model, the experiments show that using vowel pronunciations the model can achieve an accuracy of 96.4% on average, with about 10 times faster for testing than the Support Vector Machine. © 2022 IEEE.

COVID-19 and SARS-CoV-2 Detection in the Conjunctiva: Meta Analysis

Purpose : 10% of COVID patients have eye symptoms1 . Conjunctivitis is the most reported ocular symptom, being reported in 88.8% of all pts with eye symptoms1 . Literature search for SARS-CoV-2 presence in the conjunctiva of COVID patients with conjunctivitis. Methods : Review of articles dated 2020-2021 for conjunctival swabs in COVID-19 positive conjunctivitis patients using search terms: “COVID conjunctival swabs,” “COVID conjunctivitis,” and “COVID and eyes”. Search was done on Google Scholar and PubMed. Cases were excluded if patients did not have conjunctivitis or if a positive conjunctival swab was found in a patient with no clinical or lab-confirmed COVID diagnosis. Results : 27 articles published February 2020-December 2021 were found with 223 conjunctivitis patients. We found that conjunctival swabs tested for SARS-CoV-2 using RT-PCR returned positive 54.4% of the time in COVID-19 patients with conjunctivitis. We also found that 18 patients with no conjunctivitis tested positive on conjunctival swabs. Conclusions : Further research is needed to study the pathophysiology of SARS-CoV-2 in the eyes and its presence on the ocular surface. As we begin our third year of the pandemic, we expect more case reports and clinical studies on COVID conjunctivitis.

2022 iOS Apps and COVID-19: Can They Help Our Eye Patients?

Purpose : 85% of US adults have a smartphone with 87 million people using a health or wellness app monthly in 20201. There are 350,000 eHealth apps2. Roughly 33M adults in the US have the chief complaint of vision loss. An estimated 93M are at high risk for serious visual impairment3 . Only half have visited an eye doctor in the past 12 months, due to COVID 193. American adults over the age of 18 fall into the demographic of mobile app users. Do free apps help our eye patients during this pandemic? Methods : We used the search terms “vision test” and “eye exam” in the Apple App Store to compile a list of the top 10 free apps. We looked for how many free apps have eye charts that are “recognized” such as Snellen chart, Landolt C, LogMAR chart, Amsler grid & Visual Field. Control: Inclusion criteria: 1) free;2) English language;3) ≥50 reviews, ≥4 star rating in the Apple App store. Exclusion criteria: 1) foreign languages 2) paid apps. Results : Results: Top 10 iOS apps (from most downloads to least) in the Apple App Store seen in Table 1. For all iOS apps, Snellen vision test: 9/10;Landolt C: 1/10;LogMAR chart: 3/10;Amsler grid: 3/10;Visual field 1/10. Only 1 app connected you with a local optometrist or ophthalmologist. Only 3/10 apps had >1K reviews. iOS apps do not provide a number of downloads. Conclusions : Although many adults have not received an eye exam over the past 12 months, physicians can still connect with their patients through public education with the use of mobile apps. However, current eHealth apps can improve their content for eye patients.

COVID-19 and Air Pollution: Air Quality Impact in 13 Cities of the Jiangsu Province of China

Jiangsu province is one of the economically strong provinces in east China. With the advance of the modernization process, the problem of air pollution in this area is facing a severe challenge under the common role of human activities and regional climate change. While the rest of the world struggles to control COVID-19, China has managed to control the pandemic rapidly and effectively with strong lockdown policies. This study investigates the change in air pollution (focusing on the air quality index (AQI), six ambient air pollutants nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2), carbon monoxide (CO), particulate matter with aerodynamic diameters ≤10 μm (PM10) and ≤2.5 μm (PM2.5)) patterns for different periods in last 5 years. Different pollutants have different behavior identified in this studied which is helping for understanding the pattern of air quality. Short-term health advantages from the COVID-19 pandemic can be attributed to the reduction in air pollution and significant improvement in ambient air quality, which need the government to enact post-COVID environmental regulations. © 2022, HARD Publishing Company. All rights reserved.

A Pre-to Post-COVID-19 Change of Air Quality Patterns in Anhui Province Using Path Analysis and Regression

During the epidemic period, primary emissions across the world were significantly reduced, while the response to secondary pollution such as ozone differed from region to region. To study the impact of the strict control measures of the new COVID-19 epidemic on the air quality of Anhui in early 2020, the air quality monitoring data of Anhui, from 2019 to 2021, specifically 1 January to 30 August, was examined to analyze the characteristics of the temporal and spatial distribution. Regression and path analysis were used to extract the relationship between the variable. PM10 and O3, on average, increased by 6%, and 2%, while PM2.5, SO2 decreased by 15% and 10% in the post-COVID-19 period. All air quality pollutants decreased during the active-COVID-19 period, with a maximum decrease of 21% observed in PM10, followed by 19% of PM2.5, and a minimum decrease of 2% observed in O3 . Changes in air pollutants from 2017 to 2021 were also compared, and a decrease in all pollutants through 2020 was found. The air quality index (AQI) recorded a low decrease of 3% post-COVID-19, which shows that air quality will worsen in the future, but it decreased by 16% during the active-COVID-19 period. A path analysis model was developed to further understand the relationship between the AQI and air quality patterns. This path analysis shows a strong correlation between the AQI and PM10 and PM2.5, however, its correlation with other air pollutants is weak. Regression analysis shows a similar pattern of there being a strong relationship between AQI and PM10 (r2 = 0.97) and PM2.5 (r2 = 0.93). The government must implement policies to control the environmental issues which are causing poor air quality in post-COVID-19. © 2022, HARD Publishing Company. All rights reserved.

Research on stimulating mechanism and restricting factors of employees’ innovative behaviour under COVID-19

Innovation is the foundation of an enterprise’s survival and development. Employee innovation is the source of enterprise innovation. Under the COVID-19 epidemic, staff innovation is crucial to whether an enterprise can transform a crisis into an opportunity. However, the negative emotions caused by the epidemic will hinder staff innovation. The influence of the COVID-19 pandemic in China was investigated from May 2020 to October 2021 by using questionnaires. This study explores the motivating mechanism and restricting factors of employees’ innovative behaviour under sudden public crisis events. The software SPSS 22.0 is used for the descriptive statistical and correlation analyses of the collected data. Enterprise managers need to study the influencing factors of employees’ innovative behaviour under the COVID-19 epidemic to solve the problem of employees’ negative emotions. Based on the statistical analysis of 639 valid questionnaires for employees of high-tech enterprises, this study explores the motivating mechanism and influencing factors of employees’ innovative behaviour from the aspects of positive psychological quality and leaders’ interpersonal emotion management. This study also uses work autonomy as a mediating variable to verify its mediating role in the process of employees’ positive psychological quality and leaders’ interpersonal emotion management on innovation behaviour. This study tested the moderating effect of employees’ perceived corporate social responsibility on the relationship between employees’ positive psychological quality, leaders’ interpersonal emotion management and innovative behaviour. Through the statistical analysis of 639 valid questionnaires of employees in high-tech enterprises, the relevant model assumptions are verified. Therefore, under the COVID-19 pandemic, enterprises should take responsibility from the aspect of caring for employees to promote the positive effect of employees’ psychological attitudes on work results. This study provides countermeasures to ensure the smooth progress of employee innovation activities. Copyright © 2022 Wu.

IMPACT OF IMMUNOSUPPRESSIVE THERAPIES ON ANTIBODY DECAY FOLLOWING MRNA VACCINATION TO SARS-COV-2 IN A PROSPECTIVE COHORT OF PATIENTS WITH CHRONIC INFLAMMATORY DISEASES

Background: Waning levels of anti-SARS-CoV-2 Spike (S) antibodies, particularly neutralizing, are associated with the risk of breakthrough infections. The impact of immunosuppression on antibody decay kinetics is unclear. We have previously reported a strong correlation between total anti-S antibodies and neutralization titers. Here, we report the decay kinetics in anti-S IgG antibodies across various immunosuppressive medications used in patients with CID. Methods: We recruited a volunteer sample of adults with confirmed CID eligible for SARS-CoV-2 vaccination in a prospective observational cohort study at two United States CID referral centers. All study participants received two doses of mRNA vaccine to SARSCoV- 2. To assess the durability of immunogenicity, anti-S IgG were measured at 7 (visit 3), 90 (visit 5), and 120 (visit 6) days after the 2nd dose of mRNA vaccine. The impact of various medications was assessed in repeated measures mixed model with the patient as a random effect, adjusting for gender and age, and using the group of patients on sulfasalazine, NSAIDs, or on no medications as a reference, using STATA. The half-life of anti-S IgG for a 50 percent reduction in titers at visit 3 was calculated for each medication class. Results: A total of 316 CID patients were recruited of which 148 (46.8%) had inflammatory bowel disease (IBD). Durability was assessed in 495 samples obtained in 293 patients. The arithmetic mean of anti-S IgG antibodies for each medication class at visits 3, 5, and 6 is shown in Figure 1. Overall, a 2-fold reduction in titers was observed from 7 to 90 days and 90 to 120 days (Table 1). The strongest decline was observed among patients on B cell depleting/ modulating therapies followed by those on combinations of biologics and/or small molecules and antimetabolites (methotrexate, leflunomide, thiopurines, mycophenolate mofetil, and teriflunomide). There was modest decline seen with TNFi (half-life 430.5 days, -2.15, 95% CI - 4.31 to - 1.07, p = 0.03). There was also a modest, but not significant, decline seen with Janus Kinase inhibitor (JAKi). No decline was seen with anti-IL-23 or anti-integrin medication classes. Conclusions: Antibody decay in patients with CID is not observed in patients on anti-integrins or anti-IL-23 while it is seen among patients on TNFi, JAKi, antimetabolites, and combinations of biologics and/or small molecules. Our data and those from other cohorts may be used to prioritize medication classes for boosting immunogenicity with additional doses of vaccination against SARS-CoV-2. Collection of antibody titers after booster doses is currently ongoing.(Table Presented) (Figure Presented) Figure 1: Durability of anti-spike IgG antibodies after vaccination against SARS-CoV-2 in patients with Chronic Inflammatory Disease

Collaborative Truck-Drone Routing for Contactless Parcel Delivery During the Epidemic

The COVID-19 pandemic calls for contactless deliveries. To prevent the further spread of the disease and ensure the timely delivery of supplies, this paper investigates a collaborative truck-drone routing problem for contactless parcel delivery (CRP-T&D), which allows multiple trucks and multiple drones to deliver parcels cooperatively in epidemic areas. We formulate a mixed-integer programming model that minimizes the delivery time, with the consideration of the energy consumption model of drones. To solve CRP-T&D, we develop an improved variable neighborhood descent (IVND) that combines the Metropolis acceptance criterion of Simulated Annealing (SA) and the tabu list of Tabu Search (TS). Meanwhile, the integration of K-means clustering and Nearest neighbor strategy is applied to generate the initial solution. To evaluate the performance of IVND, experiments are conducted by comparing IVND with VND, SA, TS, variants of VND, and large neighborhood search (LNS) on instances with different scales. Several critical factors are tested to verify the robustness of IVND. Moreover, the experimental results on a practical instance further demonstrate the superior performance of IVND. IEEE

The impact of Google Trends index and encompassing tests on forecast combinations in tourism

Purpose: Given that the use of Google Trends data is helpful to improve forecasting performance, this study aims to investigate whether the precision of forecast combination can benefit from the use of Google Trends Web search index along with the encompassing set. Design/methodology/approach: Grey prediction models generate single-model forecasts, while Google Trends index serves as an explanatory variable for multivariate models. Then, three combination sets, including sets of univariate models (CUGM), all constituents (CAGM) and constituents that survive the forecast encompassing tests (CSET), are generated. Finally, commonly used combination methods combine the individual forecasts for each combination set. Findings: The tourism volumes of four frequently searched-for cities in Taiwan are used to evaluate the accuracy of three combination sets. The encompassing tests show that multivariate grey models play a role to be reckoned with in forecast combinations. Furthermore, the empirical results indicate the usefulness of Google Trends index and encompassing tests for linear combination methods because linear combination methods coupled with CSET outperformed that coupled with CAGM and CUGM. Practical implications: With Google Trends Web search index, the tourism sector may benefit from the use of linear combinations of constituents that survive encompassing tests to formulate business strategies for tourist destinations. A good forecasting practice by estimating ex ante forecasts post-COVID-19 can be further provided by scenario forecasting. Originality/value: To improve the accuracy of combination forecasting, this research verifies the correlation between Google Trends index and combined forecasts in tourism along with encompassing tests. © 2020, Emerald Publishing Limited.

CLINICAL CHARACTERISTICS OF SEVERE AND CRITICAL CORONAVIRUS DISEASE AND ASSESSMENT OF RISK FACTORS FOR PROGRESSION: A RETROSPECTIVE COHORT STUDY

Purpose: To examine the clinical characteristics of patients with severe and critical coronavirus disease and analyze the risk factors for progression to critical disease and adverse outcomes. Methods: Seventy-four clinical markers were analyzed. Patients were followed up until the clinical endpoint (survival or death). Subgroup analyses of severe/critical patients and survivors/deaths examined the risk factors for disease progression and patient outcomes. Results: Median patient age was 65.5 (54.0-73.0) years;64.5% were male. Thirty-two (51.6%) patients had comorbid hypertension;60 (96.8%), fever;and 5 (8.1%), diarrhea. Median lymphocyte count was significantly lower than the reference range (P<0.05);inflammatory marker levels exceeded normal ranges. The probability of comorbid diabetes was higher in the critical group than in the severe group (35.5% vs. 9.7%;P=0.031). There were 50 survivors and 12 deaths. The critical group's mortality rate was 38.7%. Intra-subgroup comparisons of severe/critical and survivor/death groups indicated patients with multiple comorbidities and elevated total white blood cell count had higher risks of progressing to critical disease (odds ratio [OR] [95% confidence interval (CI)], 2.3 [1.2-4.7], P=0.016;1.2 [1.0-1.4], P=0.017). A high SOFA score, lactic acid elevation, and a D-dimer level >2 ug/mL were risk factors for poor prognosis (OR [95% CI], 2.2 [1.0-4.8], P=0.047;3.9 [1.4-11.0], P=0.008;10.0 [1.2-84.2], P=0.033). Conclusion: Patients with multiple comorbidities and elevated total white blood cell count should be monitored closely. A high SOFA score, elevated lactate levels, and a D-dimer level of >2 ug/mL should also be considered as risk factors. © 2022 A. CARBONE Editore. All rights reserved.

Using Mathematical Model to Analyze COVID-19 Spreading

Since the first case of Coronavirus Disease 2019 (COVID-19) was discovered in Wuhan, Hubei, China, on December 31, 2019, the disease has spread globally at an unimaginable speed. COVID-19 has taken a huge toll on the society and the economy, and everyone is looking forward to its end. In this work, we established a mathematical model of COVID-19 epidemic development. First, we obtained a differential equation to describe the spreading of COVID-19: , in which is the total number of patients who are infected by COVID-19 at time . There are three parameters in this equation: the spreading coefficient , which is the average number of people infected by an unquarantined patient in a unit time;the average quarantine ratio , which is the number of quarantined patients divided by the total number of patients;and the incubation period , which is the time lapse between infection and exhibition of symptoms. In addition, we have written a Python program according to our equation, and have further used our program to analyze the COVID-19 epidemic development in various places around the world, including China, Western Europe, Latin America and Caribbean, Southern Asia, and the entire world. Through numerical fitting, we have obtained the values of the spreading coefficient and the isolation ratio for these places around the world, and predicted the development of the epidemic using these parameters we obtained. In order to ensure data consistency, we have used the data from COVID-19 case reports from Johns Hopkins University. We found that using the parameters we obtained, our calculated curves of fit the actually reported values very well, and we were able to accurately predict the values of in the near future. Lastly, we calculated the value (the number of infected persons per patient at the beginning of the epidemic) to be 2.94 1/45.88, which is consistent with the current estimated value of . In summary, our results serve as a reliable guideline to understand the spreading of COVID-19 and to predict the future outcome of this epidemic, and can be provided as a reference for the government to formulate policies. © 2021 ACM.

A Characteristic Analysis and Countermeasure Study of the Hedging of Listed Companies in China Stock Markets

Due to COVID-19, the risk of price volatility in commodity and equity markets increases. The research and application of hedging is the most effective way to reduce the market risk. Hedging is a risk management strategy employed to offset losses in investments by taking an opposite position in a related asset. We use K-means and hierarchical clustering methods to cluster companies and futures products respectively, and analyze the relationship between the number of hedging firms, regional distribution, nature of firms, capital distribution, company size, profitability, number of local Futures Commission Merchants (FCMs), regional location, and listing time. The study shows that listed companies with large scale and good profitability invest more money in hedging, while state-owned enterprises' participation in hedging is more likely to be affected by the company size and the number of local futures commission merchants, and private enterprises are more likely to be affected by the company profitability and the regional location. Listed companies are more willing to choose long-listed and mature futures products for hedging. We also provide policy advice based on our conclusion. So far, there is no study on the characteristics of hedging. This paper fills the gap. The results provide a basis and guidance for people's investment and risk management. Using clustering analysis in hedging study is another innovation of this paper.

Neural network to predict probabilistically possible mutations in hemagglutinins from Eurasia H1 influenza A virus

The current COVID-19 pandemic continues with its new variants, whose mutations are unpredictable. Thus, how to predict mutations in viruses has profound meanings for vaccine and drug development as well as prevention measures. Currently the documented mutations in SARS-CoV-2 are not abundant yet, especially for making phylogenetic tree, it would be useful and easy to use the virus data with abundant mutations such as influenza A virus to build predictive model. In this study, a neural network with feedforward backpropagation algorithm is employed to predict the probabilistically possible mutation positions and mutated amino acids in hemagglutinins from Eurasia H1 influenza A virus. The study demonstrates an encouraging result and suggests the possibility to continue working along this research line. © 2021 SPIE.