Outbreak Of Novel Coronavirus Disease Research Articles

Religious Leaders and COVID-19 Guidelines Enforcement in Rural Communities of Nigeria

The global response to the outbreak of novel Coronavirus Disease 2019 (COVID-19) in Wuhan, China, and its rapid spread to over 200 countries/territories has been intense. Following the discovery of its index case on 27 February 2020 in Lagos, Nigeria, various measures were adopted at the federal, state and local levels to contain its spread. The enforcement of COVID-19 Guidelines/Protocols commenced on 30 March 2020 in the affected states and the Federal Capital Territory (FCT). Thus, it is acknowledged that religious institutions and their leaders are crucial stakeholders in implementing these guidelines. This study used a qualitative research design to examine how religious leaders in Ijebu North-East Local Government Area responded to the enforcement of COVID-19 guidelines during total and relaxed lockdowns. It reveals that prominent Imāms at their respective mosques during the total lockdown suspended daily Salāwāt, Fridays congregational prayers (As-Salāt al-Jumu‘at), daily Ramadān Tafsīrul-Qur’ān, Iftārus-Sawm, Tarāwīh and Tahajjud, and celebration of ‘Īd-el-Fitri, ‘Īd-el-Adhā and Mawlud-en-Nabiyy. They offered their host communities spiritual and socio-welfare support in addition to disseminating information on COVID-19 prevention methods. During the relaxed lockdown, the NCDC’s COVID-19 Guidelines for Re-Opening Places of Worship were strictly followed. Inadequate resources, the lack of belief in the existence of COVID-19, un-Islamic traits of some wealthy Muslims, and a sense of distrust among some followers were identified challenges. The study concludes by suggesting how mosque leaders can proactively assist governments in eradicating coronavirus and related diseases.

Effect of a health education program about COVID-19 on the knowledge, attitude, and practices of paramedical students in Egypt: an interventional study.

In December 2019, an outbreak of novel coronavirus disease 2019, caused by severe acute respiratory syndrome coronavirus 2, has been reported in China. This study aims to assess the knowledge, attitude, and practices (KAP) of Benha Health Technical Institute (BHTI) students and to evaluate the impact of a health education program about COVID-19 on their KAP. This is an interventional study that recruited 398 students from BHTI and was conducted in 3 phases. Firstly, an assessment of students' KAP was done using a structured questionnaire concerning COVID-19. Secondly, an education program about COVID-19 was conducted. Lastly, the reassessment of KAP was carried out using the same questionnaire after one month. The median knowledge, attitude, and practice scores among the studied students in the pre-interventional stage were 12, 15, and 26 which had significantly increased to 15, 16, and 28 respectively after the intervention. The knowledge score of the participants was significantly affected by students' age and grade of education; the attitude score was affected by age, gender, and grade of education, while the practice score was only affected by participants' age. The educational program significantly increased the KAP of BHTI students.

COVID-19 consequences to pregnant women

The outbreak of novel coronavirus disease (COVID-19) was observed in Wuhan, China, and had been exposed for the first time in 31st of December 2019. There is a rapid increase in the progression of this disease. This virus is similar in genetics to SARS-COV however different in structure. The clinical illustrations of COVID-19 include lower and upper respiratory tract infection and acute respiratory syndrome with life-threatening pneumonia. This virus causes disease in newborn babies to elders including all age groups. Respiratory infection occurs in pregnant women while most commonly affected by COVID-19. The coronavirus pandemic significantly increased worry, stress, and anxiety, which negatively affects the pregnant women emotionally. Worrying about their own and their unborn child's health, decreased expectations for prenatal care, being unable to get trustworthy information, and having less daily routines and social connections are all issues that negatively affected the pregnant women. The COVID-19 virus alters the immune response at the point where the mother and fetus meet, having an impact on both the mother and the newborn. It is critical to check suspected pregnant women during delivery due to the lack of accurate knowledge of influence on pregnancy by COVID-19. In confirmed cases, both the mother as well as the baby child should be closely monitored. This review highlights the fear, stress, anxiety, and Obstetrical issues in pregnant women during SARS and COVID-19 outbreak.

Synthesis, molecular docking, and binding Gibbs free energy calculation of β-nitrostyrene derivatives: Potential inhibitors of SARS-CoV-2 3CL protease

The outbreak of novel coronavirus disease 2019 (COVID-19), caused by the novel coronavirus (SARS-CoV-2), has had a significant impact on human health and the economic development. SARS-CoV-2 3CL protease (3CLpro) is highly conserved and plays a key role in mediating the transcription of virus replication. It is an ideal target for the design and screening of anti-coronavirus drugs. In this work, seven β-nitrostyrene derivatives were synthesized by Henry reaction and β-dehydration reaction, and their inhibitory effects on SARS-CoV-2 3CL protease were identified by enzyme activity inhibition assay in vitro. Among them, 4-nitro-β-nitrostyrene (compound a) showed the lowest IC50 values of 0.7297 µM. To investigate the key groups that determine the activity of β-nitrostyrene derivatives and their interaction mode with the receptor, the molecular docking using the CDOCKER protocol in Discovery Studio 2016 was performed. The results showed that the hydrogen bonds between β-NO2 and receptor GLY-143 and the π-π stacking between the aryl ring of the ligand and the imidazole ring of receptor HIS-41 significantly contributed to the ligand activity. Furthermore, the ligand-receptor absolute binding Gibbs free energies were calculated using the Binding Affinity Tool (BAT.py) to verify its correlation with the activity of β-nitrostyrene 3CLpro inhibitors as a scoring function. The higher correlation(r2=0.6) indicates that the absolute binding Gibbs free energy based on molecular dynamics can be used to predict the activity of new β-nitrostyrene 3CLpro inhibitors. These results provide valuable insights for the functional group-based design, structure optimization and the discovery of high accuracy activity prediction means of anti-COVID-19 lead compounds.

Contact pattern, current immune barrier, and pathogen virulence determines the optimal strategy of further vaccination.

The current outbreak of novel coronavirus disease 2019 has caused a serious disease burden worldwide. Vaccines are an important factor to sustain the epidemic. Although with a relatively high-vaccination worldwide, the decay of vaccine efficacy and the arising of new variants lead us to the challenge of maintaining a sufficient immune barrier to protect the population. A case-contact tracking data in Hunan, China, is used to estimate the contact pattern of cases for scenarios including school, workspace, etc, rather than ordinary susceptible population. Based on the estimated vaccine coverage and efficacy, a multi-group vaccinated-exposed-presymptomatic-symptomatic-asymptomatic-removed model (VEFIAR) with 8 age groups, with each partitioned into 4 vaccination status groups is developed. The optimal dose-wise vaccinating strategy is optimized based on the currently estimated immunity barrier of coverage and efficacy, using the greedy algorithm that minimizes the cumulative cases, population size of hospitalization and fatality respectively in a certain future interval. Parameters of Delta and Omicron variants are used respectively in the optimization. The estimated contact matrices of cases showed a concentration on middle ages, and has compatible magnitudes compared to estimations from contact surveys in other studies. The VEFIAR model is numerically stable. The optimal controled vaccination strategy requires immediate vaccination on the un-vaccinated high-contact population of age 30-39 to reduce the cumulative cases, and is stable with different basic reproduction numbers ( ). As for minimizing hospitalization and fatality, the optimized strategy requires vaccination on the un-vaccinated of both aged 30-39 of high contact frequency and the vulnerable older. The objective of reducing transmission requires vaccination in age groups of the highest contact frequency, with more priority for un-vaccinated than un-fully or fully vaccinated. The objective of reducing total hospitalization and fatality requires not only to reduce transmission but also to protect the vulnerable older. The priority changes by vaccination progress. For any region, if the local contact pattern is available, then with the vaccination coverage, efficacy, and disease characteristics of relative risks in heterogeneous populations, the optimal dose-wise vaccinating process will be obtained and gives hints for decision-making.

Challenges and the potential of promoting remote medical interpreting during COVID-19.

Language barriers negatively affect patient outcomes, and linguistic assistance is essential for adequate healthcare. The adoption of face-to-face medical interpretating is believed to have been rendered more challenging by the implementation of hospital admission restrictions following the outbreak of novel coronavirus disease (COVID-19). On the other hand, remote interpretating can be implemented using merely equipment, enabling it to be introduced without being impacted by the transmission of illness, and its use may have spread globally. To comprehend how COVID-19 has impacted remote interpreting utilization and what issues have arisen, we conducted a systematic review of two databases, PubMed and Ichushi-web (Japanese medical literature) with "remote interpreting" and "COVID-19" as keywords in June, 2022. Five references were included in the review. The research supported an increase in remote interpreting during COVID-19 to limit the risk of infection. This change in the trend of medical interpreting has the potential of promoting remote medical interpreting for places lacking sufficient linguistically skilled human resources, regardless of the pandemic status. There have also been accounts of novel methods of remote medical interpretation in which neither the healthcare professional nor the interpreter was face-to-face with the patient, and difficulty was acknowledged by both the healthcare professional and the patient with remote interpreting. To fully take advantage of the possibilities of remote interpreting, additional training and support would be required. Further studies are also required to determine the best way to employ this technology.

Spatial variations in COVID-19 risk perception and coping mechanism in Pakistan

The outbreak of novel coronavirus disease (COVID-19) was declared a pandemic by the World Health Organization, which instigated governments to impose lockdowns across their countries. Amidst the lockdown in Pakistan, this study comprised measures of the COVID-19 risk perception, coping mechanism, and spatial variations. The data from 40 selected indicators was collected using an online questionnaire and grouped into domains (4 risk perception and 3 coping mechanisms domains). The results revealed the spatial variations and the levels of risk perception and coping mechanisms within the study area. Relative to each other, overall risk perception was highest in Northern Areas (Gilgit-Baltistan and Azad Jammu and Kashmir) and Islamabad, and lowest in Balochistan province. Very little spatial variation was observed in terms of coping mechanisms. Age, gender, and marital status influenced the risk perception associated with COVID-19. The findings suggest spatial variation in risk perception, implying the need for localized and modified COVID-19 risk communication and risk reduction strategies.

Electricity consumption variation versus economic structure during COVID-19 on metropolitan statistical areas in the US

The outbreak of novel coronavirus disease (COVID-19) has resulted in changes in productivity and daily life patterns, and as a result electricity consumption (EC) has also shifted. In this paper, we construct estimates of EC changes at the metropolitan level across the continental U.S., including total EC and residential EC during the initial two months of the pandemic. The total and residential data on the state level were broken down into the county level, and then metropolitan level EC estimates were aggregated from the counties included in each metropolitan statistical area (MSA). This work shows that the reduction in total EC is related to the shares of certain industries in an MSA, whereas regardless of the incidence level or economic structure, the residential sector shows a trend of increasing EC across the continental U.S. Since the MSAs account for 86% of the total population and 87% of the total EC of the continental U.S., the analytical result in this paper can provide important guidelines for future social-economic crises.

In Silico Testing of Some Protected Galactopyranose as SARS-CoV-2 Main Protease Inhibitors

An outbreak of novel Coronavirus disease (COVID-19 or 2019-nCoV) due to the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has already demonstrated a fatal death toll all over the world. To cure this viral infection, a number of compounds of different categories have been investigated in silico. Some of the compounds showed better binding energy with COVID-19-related proteins. However, until now there is no appropriate drug except a vaccine. It was found that many antifungal drugs are used for COVID-19 patients in hospitals. Many monosaccharide esters have been reported to have antifungal potential. Thus, in the present study, some protected galactopyranose esters are chosen for molecular docking with SARS-CoV-2 main proteases (PDB id: 7BQY and 6LU7). A docking study revealed that galactopyranose esters 5-8 have very good docking scores (-8.4 to -6.5 kcal/mol) compared to the standard drugs azithromycin, remdesivir, and hydroxychloroquine. To explain such good scores interaction between amino acid residues of proteins and compounds in their docked complexes are calculated and duly discussed in this study.

Biological and Exploitable Crossroads for the Immune Response in Cancer and COVID-19

The outbreak of novel coronavirus disease 2019 (COVID-19) has exacted a disproportionate toll on cancer patients. The effects of anticancer treatments and cancer patients’ characteristics shared significant responsibilities for this dismal outcome; however, the underlying immunopathological mechanisms are far from being completely understood. Indeed, despite their different etiologies, SARS-CoV-2 infection and cancer unexpectedly share relevant immunobiological connections. In the pathogenesis and natural history of both conditions, there emerges the centrality of the immune response, orchestrating the timed appearance, functional and dysfunctional roles of multiple effectors in acute and chronic phases. A significant number (more than 600) of observational and interventional studies have explored the interconnections between COVID-19 and cancer, focusing on aspects as diverse as psychological implications and prognostic factors, with more than 4000 manuscripts published so far. In this review, we reported and discussed the dynamic behavior of the main cytokines and immune system signaling pathways involved in acute vs. early, and chronic vs. advanced stages of SARS-CoV-2 infection and cancer. We highlighted the biological similarities and active connections within these dynamic disease scenarios, exploring and speculating on possible therapeutic crossroads from one setting to the other.

Epidemiology of COVID-19 in Kish Island from February to August 2020

Background: In March 2020, the world health organization declared the outbreak of novel coronavirus disease 2019 (COVID-19) as a pandemic. COVID-19 is a highly contagious disease. Kish is a touristic island that is located in the south of Iran. The aim of the present study was to investigate the epidemiology of COVID-19 on Kish island. Methods: In the present cross-sectional study, the residents of Kish Island, Iran, who were checked with COVID-19 polymerase chain reaction (PCR) test from February to August 2020 were included. The PCR test was obtained from symptomatic individuals or those people who had exposure to suspected COVID-19 cases. Data were collected from their medical records and analyzed based on their PCR test results. Results: A total of 4859 individuals were checked with COVID-19 PCR test. The result was positive in 1251 (25.75%) cases and negative in 3608 (74.25%). The mean age was 37.32 years. The majority of the individuals were men. Most of the participants were office employees. The number of housewives was approximately double in COVID-19 positive patients compared with the patients with negative results. About 40% of the individuals with positive results had a history of exposure to suspected COVID-19 cases. The prevalence of exposure to suspected COVID-19 cases and recent travel was significantly higher among positive cases (P<0.001). There was a significant correlation between the delay between the onset of the symptoms and performing PCR. Longer delays were seen among the deceased patients. Conclusion: It seems that more precise policies should be taken to avoid contact with symptomatic patients and people who had a history of travel to the island.

COVID-19 Classification Using Medical Image Synthesis by Generative Adversarial Networks

The outbreak of novel coronavirus disease 2019, also called COVID-19, in Wuhan, China, began in December 2019. Since its outbreak, infectious disease has rapidly spread across the globe. The testing methods adopted by the medical practitioners gave false negatives, which is a big challenge. Medical imaging using deep learning can be adopted to speed up the testing process and avoid false negatives. This work proposes a novel approach, COVID-19 GAN, to perform coronavirus disease classification using medical image synthesis by a generative adversarial network. Detecting coronavirus infections from the chest X-ray images is very crucial for its early diagnosis and effective treatment. To boost the performance of the deep learning model and improve the accuracy of classification, synthetic data augmentation is performed using generative adversarial networks. Here, the available COVID-19 positive chest X-ray images are fed into the styleGAN2 model. The styleGAN model is trained, and the data necessary for training the deep learning model for coronavirus classification is generated. The generated COVID-19 positive chest X-ray images and the normal chest X-ray images are fed into the deep learning model for training. An accuracy of 99.78% is achieved in classifying chest X-ray images using CNN binary classifier model.

The disaster resilience trajectory of the first batch front-line nurses at fighting the Novel Coronavirus Disease 2019 in Wuhan: A qualitative study

AimIt is widely accepted that resilience is an essential solution to the challenges caused by disasters or crisis. The resilient individual can actively cope with challenges and maintain a good performance in facing of disastrous events. After the outbreak of Novel Coronavirus Disease 2019 (COVID-19) in Wuhan, China, numerous researchers have engaged in studying the experiences of front-line nurses in Wuhan from different perspectives. However, little is known on how the first batch front-line nurses developed their resilience trajectories during the disastrous events. The purpose of the present study is to explore the disaster resilience trajectory of the first batch front-line nurses at the early-stage of COVID-19 outbreak in Wuhan, Hubei province. MethodQualitative research method was employed using purposive sampling. Nurses from Sichuan who had anti-epidemic experiences in Wuhan were selected to be conducted in-depth phone interviews. The interviews were transcribed verbatim, and data was analysed by adopting Colaizzi phenomenological approach. ResultsThree theme categories emerged through the data analysis: (1) Challenges and difficulties; (2) Overcoming difficulties; (3) and Personal growth. ConclusionNurses have accumulated relevant experiences in dealing with sudden public health events after the rescue task, which can provide psychological and material supports for coping with similar situation in the future. Additionally, multiple support systems were critical elements for front-line nurses to recover from the disaster. Through uncovering front-line nurses’ disaster resilience trajectories, it is significant for health care organizations and managers to establish more comprehensive system in handling with public health emergency events.

In Silico Identification of New Anti-SARS-CoV-2 Agents from Bioactive Phytocompounds Targeting the Viral Spike Glycoprotein and Human TLR4

Background: The recent outbreak of novel coronavirus disease (COVID-19) pandemic caused by SARS-CoV-2 has posed a tremendous threat to mankind. The unavailability of a specific drug or vaccine has been the major concern to date. Spike (S) glycoprotein of SARS-CoV-2 plays the most crucial role in viral infection and immunopathogenesis, and hence this protein appears to be an efficacious target for drug discovery. Objective: The objective of this study was to identify potent bioactive phytocompound that can target viral spike (S) glycoprotein and human TLR4 to reduce immunopathological manifestations of COVID- 19. Method: A series of thirty (30) bioactive phytocompounds, previously documented for antiviral activity, were theoretically screened for their binding efficacy against key proteins related to the pathogenesis of SARS-CoV-2, namely viral spike (S) glycoprotein, and human TLR4. MD simulation was employed to verify the postulations of molecular docking study, and further ADME analysis was performed to predict the most effective one. Results: Studies hypothesized that two new phytochemicals, viz. cajaninstilbene acid (-8.83 kcal/mol) and papaverine (-5.81 kcal/mol), might be the potent inhibitors of spike glycoprotein with stout binding affinity and favourable ADME attributes. MD simulation further ratified the stability of the docked complexes between the phytochemicals and S protein through strong hydrogen bonding. Our in silico data also indicated that cajaninstilbene acid and papaverine might block human TLR4, which could be useful in mitigating SARS-CoV-2-induced lethal proinflammatory responses. Conclusion: Experimental data collectively predict cajaninstilbene acid as the potential blocker of S protein which may be used as an anti-viral against COVID-19 in the future. However, further experimental validations alongside toxicological detailing are needed for claiming the candidature of these molecules as future anti-corona therapeutics.

Psychological impact of COVID-19 on female health professionals

Background: The World Health Organization in January 2020 declared an outbreak of novel coronavirus disease, COVID-19, an international public health emergency. The suddenness of this calamity with no end in sight caused a great deal of stress, anxiety, and depression throughout the world. Aim: The aim of this study was to assess the psychological impact during the developing COVID-19 situation among female health professionals. Methods: This was an observation-based cross-sectional study conducted for a total of 3-month duration between August and October 2020. A structured questionnaire to assess the psychological impact was sent via the (email) electronic mail system, and responses were obtained from 343 female doctors. Results: The mean ± standard deviation values for age were found to be 39 ± 8 years. Insomnia, stress, and anxiety were seen in a majority of the respondents. Conclusions: The present study has shown severe psychological impact associated with the pandemic on female health-care workers and highlights the major factors associated.

The Role of the Mask in Preventing and Controlling the Coronavirus Disease 2019 Pandemic

Following the outbreak of novel coronavirus disease 2019 (COVID-19), there have been debates among scientific communities, officials, and the public about the role of the mask in controlling and preventing this disease. Nonetheless, there are some ambiguities regarding various aspects of the mask which are still important to be addressed, including the type of the mask to be used, the situation in which the mask should be used, the correct way to use the mask, and the effectiveness of the mask in preventing the disease. Accordingly, addressing these ambiguities could change policy trends and public beliefs about the use of mask and help control the disease. To this end, this study discusses the role of the mask in preventing and controlling the COVID-19 pandemic.

Stacking Ensemble-Based Intelligent Machine Learning Model for Predicting Post-COVID-19 Complications.

The recent outbreak of novel coronavirus disease (COVID-19) has resulted in healthcare crises across the globe. Moreover, the persistent and prolonged complications of post-COVID-19 or long COVID are also putting extreme pressure on hospital authorities due to the constrained healthcare resources. Out of many long-lasting post-COVID-19 complications, heart disease has been realized as the most common among COVID-19 survivors. The motivation behind this research is the limited availability of the post-COVID-19 dataset. In the current research, data related to post-COVID complications are collected by personally contacting the previously infected COVID-19 patients. The dataset is preprocessed to deal with missing values followed by oversampling to generate numerous instances, and model training. A binary classifier based on a stacking ensemble is modeled with deep neural networks for the prediction of heart diseases, post-COVID-19 infection. The proposed model is validated against other baseline techniques, such as decision trees, random forest, support vector machines, and artificial neural networks. Results show that the proposed technique outperforms other baseline techniques and achieves the highest accuracy of 93.23%. Moreover, the results of specificity (95.74%), precision (95.24%), and recall (92.05%) also prove the utility of the adopted approach in comparison to other techniques for the prediction of heart diseases.

Establishment of a quantitative RT-PCR detection of SARS-CoV-2 virus

BackgroundThe outbreak of novel coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern. Quantitative testing of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) virus is demanded in evaluating the efficacy of antiviral drugs and vaccines and RT-PCR can be widely deployed in the clinical assay of viral loads. Here, we developed a quantitative RT-PCR method for SARS-CoV-2 virus detection in this study.MethodsRT-PCR kits targeting E (envelope) gene, N (nucleocapsid) gene and RdRP (RNA-dependent RNA polymerase) gene of SARS-CoV-2 from Roche Diagnostics were evaluated and E gene kit was employed for quantitative detection of COVID-19 virus using Cobas Z480. Viral load was calculated according to the standard curve established by series dilution of an E-gene RNA standard provided by Tib-Molbiol (a division of Roche Diagnostics). Assay performance was evaluated.ResultsThe performance of the assay is acceptable with limit of detection (LOD) below 10E1 copies/μL and lower limit of quantification (LLOQ) as 10E2 copies/μL.ConclusionA quantitative detection of the COVID-19 virus based on RT-PCR was established.

The dynamic changes of cellular immunity among frontline medical workers who supported Wuhan for fighting against the COVID-19

The outbreak of novel coronavirus disease 2019 (COVID-19) poses a great stress to frontline medical workers. Our previous study indicated that immune cells in the peripheral blood of frontline medical workers changed significantly. However, the dynamic changes of immune cells of frontline medical workers remain unclear. Here, we reported the dynamic changes of lymphocyte subsets in the peripheral blood of 51 frontline medical worker. The frontline medical workers struggling with COVID-19 from February 8 to March 31, 2020. Demographic and clinical data, including routine blood test data were extracted from the electronic health examination record and retrospectively analyzed. The lymphocyte (LYM) count and LYM ratio increased while the monocyte (MONO) ratio, neutrophil to lymphocyte ratio (NLR), monocyte to lymphocyte ratio (MLR) and neutrophil (NEUT) ratio in the peripheral blood of frontline medical workers decreased 10 days after struggling with COVID-19. Interestingly, the differences of LYM count, LYM ratio, MONO ratio, NLR, NEUT ratio were more significantly in nurse than doctor. The differences of LYM ratio, NLR and NEUT ratio were more significantly in female than male. However, the changes of LYM count, LYM ratio, MONO ratio, NLR, MLR, NEUT ratio returned to the baseline 10 months after struggling with COVID-19. Together, these data indicated that immune cells in the peripheral blood changed significantly 10 days after struggling with COVID-19, but returned to normal after 10 months. Those maybe caused by psychological stress and we recommend to pay more attention to mental health and immune response of frontline medical workers.

Construction and Application of an Intelligent Response System for COVID-19 Voice Consultation in China: A Retrospective Study

Background: The outbreak of novel coronavirus disease 2019 (COVID-19) has led to tremendous individuals visit medical institutions for healthcare services. Public gatherings and close contact in clinics and emergency departments may increase the exposure and cross-infection of COVID-19.Objectives: The purpose of this study was to develop and deploy an intelligent response system for COVID-19 voice consultation, to provide suggestions of response measures based on actual information of users, and screen COVID-19 suspected cases.Methods: Based on the requirements analysis of business, user, and function, the physical architecture, system architecture, and core algorithms are designed and implemented. The system operation process is designed according to guidance documents of the National Health Commission and the actual experience of prevention, diagnosis and treatment of COVID-19. Both qualitative (system construction) and quantitative (system application) data from the real-world healthcare service of the system were retrospectively collected and analyzed.Results: The system realizes the functions, such as remote deployment and operations, fast operation procedure adjustment, and multi-dimensional statistical report capability. The performance of the machine-learning model used to develop the system is better than others, with the lowest Character Error Rate (CER) 8.13%. As of September 24, 2020, the system has received 12,264 times incoming calls and provided a total of 11,788 COVID-19-related consultation services for the public. Approximately 85.2% of the users are from Henan Province and followed by Beijing (2.5%). Of all the incoming calls, China Mobile contributes the largest proportion (66%), while China Unicom and China Telecom are accounted for 23% and 11%. For the time that users access the system, there is a peak period in the morning (08:00–10:00) and afternoon (14:00–16:00), respectively.Conclusions: The intelligent response system has achieved appreciable practical implementation effects. Our findings reveal that the provision of inquiry services through an intelligent voice consultation system may play a role in optimizing the allocation of healthcare resources, improving the efficiency of medical services, saving medical expenses, and protecting vulnerable groups.