Journal of Education and Health Promotion

Predicting intubation risk among COVID‑19 hospitalized patients using artificial neural networks

. Raoof Nopour; . Mostafa Shanbezadeh; . Hadi Kazemi-Arpanahi

Volume 13, Issue 1 , January 2023, , Pages 1-8

Abstract

  BACKGROUND: Accurately predicting the intubation risk in COVID‑19 patients at the admissiontime is critical to optimal use of limited hospital resources, providing customized and ...  Read More BACKGROUND: Accurately predicting the intubation risk in COVID‑19 patients at the admissiontime is critical to optimal use of limited hospital resources, providing customized and evidence‑basedtreatments, and improving the quality of delivered medical care services. This study aimed to designa statistical algorithm to select the best features influencing intubation prediction in coronavirusdisease 2019 (COVID‑19) hospitalized patients. Then, using selected features, multiple artificialneural network (ANN) configurations were developed to predict intubation risk.MATERIAL AND METHODS: In this retrospective single‑center study, a dataset containing 482COVID‑19 patients who were hospitalized between February 9, 2020 and July 20, 2021 was used. First,the Phi correlation coefficient method was performed for selecting the most important features affectingCOVID‑19 patients’ intubation. Then, the different configurations of ANN were developed. Finally,the performance of ANN configurations was assessed using several evaluation metrics, and the beststructure was determined for predicting intubation requirements among hospitalized COVID‑19 patients.RESULTS: The ANN models were developed based on 18 validated features. The results indicatedthat the best performance belongs to the 18‑20‑1 ANN configuration with positive predictive value(PPV) = 0.907, negative predictive value (NPV) = 0.941, sensitivity = 0.898, specificity = 0.951, andarea under curve (AUC) = 0.906.CONCLUSIONS: The results demonstrate the effectiveness of the ANN models for timely and reliableprediction of intubation risk in COVID‑19 hospitalized patients. Our models can inform clinicians andthose involved in policymaking and decision making for prioritizing restricted mechanical ventilationand other related resources for critically COVID‑19 patients.

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COVID‑19 vaccine hesitancy among medical students: A systematic review

. Kirthika Venkatesan; . Sukrita Menon; . Nisha Nigil Haroon

Volume 12, Issue 6 , July 2022, , Pages 1-8

Abstract

  BACKGROUND: Vaccine hesitancy leads to an increase in morbidity, mortality, and health‑care burden. Reasons for vaccine hesitancy include anti‑vax group statements, misinformation ...  Read More BACKGROUND: Vaccine hesitancy leads to an increase in morbidity, mortality, and health‑care burden. Reasons for vaccine hesitancy include anti‑vax group statements, misinformation about vaccine side effects, speed of vaccine development, and general disbelief in the existence of viruses like COVID‑19. Medical students are future physicians and are key influencers in the uptake of vaccines. Hence, investigating vaccine hesitancy in this population can help to overcome any barrier in vaccine acceptance.METHODS: In this paper, we review five articles on COVID‑19 vaccine hesitancy in medical students and consider potential future research. All published papers relevant to the topic were obtained through extensive search using major databases. Inclusion criteria included studies that specifically investigated COVID‑19 vaccine hesitancy in medical students published between 2020 and 2021. Exclusion criteria included studies that investigated vaccine hesitancy in health‑care professionals, allied health, and viruses apart from COVID‑19. A total of 10 studies were found from our search.RESULTS: Based on our exclusion criteria, only five studies were included in our review. The sample size ranged from 168 to 2133 medical students. The percentage of vaccine hesitancy in medical students ranged from 10.6 to 65.1%. Reasons for vaccine hesitancy included concern about serious side effects, vaccine efficacy, misinformation and insufficient information, disbelief in public health experts, financial costs, and belief that they had acquired immunity.CONCLUSION: These results suggest that vaccine hesitancy is an important cause of the incidence and prevalence of COVID‑19 cases. Identifying the barriers of vaccine hesitancy in prospective physicians can help increase vaccination uptake in the general public. Further research is necessary to identify the root cause of these barriers.

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COVID‑19: Distance learning to empower educators and health assistants in rural areas

. Maria do Carmo Barros de Melo; . Priscila Menezes Ferri; . Monica Maria Almeida de Vasconcelos; . Zilma Silveira Nogueira Reis; . Solange Cervinho Bicalho Godoy; . Vitória Andrade Palmeira; . Gabriel Rocha; . Rosalia Morais Torres; . Unaí Tupinambás

Volume 12, Issue 5 , June 2022, , Pages 1-7

Abstract

  BACKGROUND: Educators and health assistants can act as key players in controlling the pandemic.In general, they are respected by the community, especially in rural areas, and can help ...  Read More BACKGROUND: Educators and health assistants can act as key players in controlling the pandemic.In general, they are respected by the community, especially in rural areas, and can help guide andraise the population’s awareness of preventive measures. The objective of this paper is to evaluatethe results in knowledge progress of an e‑learning course offered to educators and health assistantsby a public university and to analyze the profile and satisfaction of the participants.MATERIALS AND METHODS: A single group pre‑ and post‑test design based on a questionnaire,interventional, study was conducted in the period from April 20th to June 20th. All participants of thecourse answered sociodemographic and satisfaction questionnaire and a pre‑ and post‑test. Datawere descriptively arranged and regarding the distribution and comparison of means and frequency,paired t‑test for group comparisons. P < 0.05 was statistically significant. Data were collected fromthe Moodle® teaching platform, without identifying the participants.RESULTS: A total of 674 participants were enrolled in the five groups, and 583 concluded thecourse (86.5%). The reasons for those who did not access the entire course (n = 47) were: Lack oftime, difficulty in accessing the internet, and lack of experience with distance learning courses. On theevaluation of the course platform, from the tutors in general and the degree of satisfaction in severalquestions, participants marked maximum grades. The comparison between pre‑ and post‑proficiencyscores showed increased proficiency of the enrolled groups (P < 0.0001).CONCLUSIONS: The course contributed to the training of health assistants and educators, preparingthem to act in a participatory way in the prevention and control of the pandemic. The course waswell evaluated and there was a progression of knowledge by the participants.

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Using logistic regression to develop a diagnostic model for COVID‑19: A single‑center study

. Raoof Nopour; . Mostafa Shanbehzadeh; . Hadi Kazemi‑Arpanahi

Volume 12, Issue 5 , June 2022, , Pages 1-6

Abstract

  BACKGROUND: The main manifestations of coronavirus disease‑2019 (COVID‑19) are similarto the many other respiratory diseases. In addition, the existence of numerous uncertainties ...  Read More BACKGROUND: The main manifestations of coronavirus disease‑2019 (COVID‑19) are similarto the many other respiratory diseases. In addition, the existence of numerous uncertainties inthe prognosis of this condition has multiplied the need to establish a valid and accurate predictionmodel. This study aimed to develop a diagnostic model based on logistic regression to enhance thediagnostic accuracy of COVID‑19.MATERIALS AND METHODS: A standardized diagnostic model was developed on data of 400patients who were referred to Ayatollah Talleghani Hospital, Abadan, Iran, for the COVID‑19diagnosis. We used the Chi‑square correlation coefficient for feature selection, and logistic regressionin SPSS V25 software to model the relationship between each of the clinical features. Potentiallydiagnostic determinants extracted from the patient’s history, physical examination, and laboratoryand imaging testing were entered in a logistic regression analysis. The discriminative ability of themodel was expressed as sensitivity, specificity, accuracy, and area under the curve, respectively.RESULTS: After determining the correlation of each diagnostic regressor with COVID‑19 usingthe Chi‑square method, the 15 important regressors were obtained at the level of P < 0.05. Theexperimental results demonstrated that the binary logistic regression model yielded specificity,sensitivity, and accuracy of 97.3%, 98.8%, and 98.2%, respectively.CONCLUSION: The destructive effects of the COVID‑19 outbreak and the shortage of healthcareresources in fighting against this pandemic require increasing attention to using the Clinical DecisionSupport Systems equipped with supervised learning classification algorithms such as logisticregression.

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COVID‑19 vaccine hesitancy and influence of professional medical guidance

. Govind Nair; . Kirthika Venkatesan; . Arjun Nair; . Irene N. Firoz; . Nisha Nigil Haroon

Volume 12, Issue 4 , April 2022, , Pages 1-9

Abstract

  BACKGROUND: Vaccine hesitancy presents a major challenge during the COVID‑19 pandemic. It is crucial to address the factors contributing to vaccine hesitancy necessary to control ...  Read More BACKGROUND: Vaccine hesitancy presents a major challenge during the COVID‑19 pandemic. It is crucial to address the factors contributing to vaccine hesitancy necessary to control the associated morbidity and mortality. This study aimed to investigate the impact of professional medical guidance on the likelihood of receiving the COVID‑19 vaccine in immigrants of USA and Canada.MATERIALS AND METHODS: A total of 92 immigrants in the USA and Canada who predominantly spoke Malayalam were recruited using social media platforms. An online survey was administered investigating participants’ confidence in receiving the COVID‑19 vaccine. Following, a short webinar was conducted by a medical professional explaining the efficacy and safety of the vaccine. A postwebinar survey was immediately given assessing the confidence and likelihood of receiving the vaccine. SPSS was used to generate descriptive statistics and Pearson Chi‑square analysis where appropriate.RESULTS: Results revealed that participants who attended the webinar reported greater confidence in receiving the COVID‑19 vaccine. There was a statistically significant difference between pre‑ and postwebinar confidence scores for the COVID‑19 vaccine, 2 (12, n = 80) = 43.34, P < 0.01.CONCLUSION: Results from the current study demonstrate the successful delivery of professional medical guidance to the general public through online small‑group sessions to help address the misconceptions surrounding the COVID‑19 vaccine and combat vaccine hesitancy among vulnerable populations. Future studies should focus on interventions addressing vaccine hesitancy in larger and diverse populations and analyze other barriers to vaccination.

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Coronavirus disease‑2019: Challenges, opportunities, and benefits in India

. Riwanka Khlem; . Sujatha R. Kannappan; . Papori Pathak Choudhury

Volume 12, Issue 3 , March 2022, , Pages 1-9

Abstract

  BACKGROUND: The human coronavirus was first identified in 1965, belongs to the same family of Viruses as SARS, MERS‑Co. The current virus that affected worldwide came into existence in ...  Read More BACKGROUND: The human coronavirus was first identified in 1965, belongs to the same family of Viruses as SARS, MERS‑Co. The current virus that affected worldwide came into existence in late 2019, recently found in Wuhan, China, and caused a global pandemic called coronavirus disease‑2019 (COVID‑19). This disease became a quick global pandemic due to the rapid transmission of the virus from one human to another. In the history of humankind, people were inside the four walls for more than a month. The COVID‑19 pandemic has posed significant problems in a variety of fields. The current pandemic created many changes that are seen as challenges worldwide. However, it created opportunities and benefits for many, extend a helping hand towards the people in need, in the society, community, and the nation. This paper focuses on challenges, opportunities, and benefits during the (COVID‑19) pandemic in India.MATERIALS AND METHODS: Online search engines like PubMed and Google Scholar were used to conduct the research. The review article’s dates were not restricted in any way. A total of 48 articles were chosen. The data was tabulated based on the kind of study and the outcomes. There are just a few papers available that demonstrate the necessity for more study.RESULTS: COVID‑19 caused unforeseen changes in the health care industry, unequal distribution of health care, and consequences on mental health, according to the review studies. Teleconsultation, Internet use, and E‑learning have all become more accessible. A period of transitory economic collapse and an increase in the number of migrants left many despondent. Improvement in family bonding, use of a face mask, and hygiene measures to adapt to the current scenario. There was also an impact on water sources, waste management systems, and environmental resource conservation.CONCLUSION: Difficult conditions can provide both problems and opportunities and advantages to the people during a pandemic outbreak.

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Persian mobile health applications for COVID‑19: A use case‑based study

. Rasool Nouri; . Raheleh Salari; . Sharareh R. Niakan Kalhori; . Seyed Mohammad Ayyoubzadeh; . Marsa Gholamzadeh

Volume 12, Issue 3 , March 2022, , Pages 1-5

Abstract

  BACKGROUND: Since the beginning of the COVID‑19 outbreak, a significant number of mobile health apps have been created around the world and in Iran to help consequence reduction ...  Read More BACKGROUND: Since the beginning of the COVID‑19 outbreak, a significant number of mobile health apps have been created around the world and in Iran to help consequence reduction of this emerging pandemic.OBJECTIVES: This study aimed to review the characteristics of Persian Android and iOS apps related to COVID‑19 and determine their use‑cases based on a reference model.METHODS: This was a cross‑sectional descriptive study conducted in three main steps. First, a systematic search was conducted via Iranian mobile apps’ markets using the keywords related to COVID‑19 in January 2021. Then, the retrieved apps were analyzed according to their characteristics. Finally, the use‑cases of the given apps were determined and categorized based on a reference model.RESULTS: Based on our inclusion criteria, 122 apps were selected and evaluated. Most of these apps (87.7%) was free. Small proportions (5%) of reviewed apps have been developed with participation of clinical expert and half of the apps mentioned the references they used. Furthermore, about half of the apps (50.8%) were provided contact information of the developers. The studied apps were classified into four use‑case major categories, including educational (98%), fulfilling a contextual need (18%), communicating, and/or sharing the information (0.83%), and health‑related management (2%).CONCLUSION: The results showed that the Persian mobile apps for COVID‑19 are not in a satisfying situation. Furthermore, although these apps are significant in quantity but in terms of use‑cases, they are not widespread.

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Influence of knowledge on Brazilian student’s perception of life and clinical classes during COVID‑19

. Fernanda de Souza e Silva Ramos; . Laryssa de Castro Oliveira; . Diego Felipe Mardegan Gonçalves; . Rafael Santos Rocha; . Eduardo Bresciani; . Ticiane Cestari Fagundes

Volume 12, Issue 2 , February 2022, , Pages 1-6

Abstract

  BACKGROUND: The current pandemic associated with SARS‑CoV‑2 has negatively influenced several activities, including teaching in Operative Dentistry. The aim of this study was ...  Read More BACKGROUND: The current pandemic associated with SARS‑CoV‑2 has negatively influenced several activities, including teaching in Operative Dentistry. The aim of this study was to evaluate the influence of knowledge in Operative Dentistry on undergraduate students’ perception related to personal life and return to clinical practices classes during pandemic.MATERIALS AND METHODS: The present research was a cross‑sectional, observational, and qualitative survey. The 16‑item based questionnaire was sent to undergraduate students in 2020, which were divided into two groups, according to the Operative Dentistry knowledge: G1‑not started clinical practice; G2‑already started or completed clinical practice. Questions were focused on the impact of the pandemic in relation to their personal lives and return to clinical practice classes. Chi‑square association test was performed using the SigmaPlot 12.0 software (P ≤ 0.05).RESULTS: The response rate was 55.5% for G1 and 44.4% for G2. Regarding the questions related to personal life, G1 demonstrated higher percentages of fear of contracting the virus during theoretical classes. Same observations were found when students answered about their fear of contracting coronavirus during the clinical practice classes. However, G2 presented the highest agreement responses for the preparedness feeling to return to theoretical classroom, clinical practice classes, and the possibility of applying online learning.CONCLUSIONS: In general, students’ knowledge had little influence on perception of personal life. However, students who have more knowledge in operative dentistry presented more security about returning to clinical classes.

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The COVID‑19 pandemic impact on clinical load of plastic and reconstructive surgery in a tertiary care hospital of north India: A retrospective comparative analysis

. Mohd Altaf Mir; . Debarati Chattopadhyay; . Nishank Manohar; . Madhubari Vathulya; . Vishal Mago; . Akshay Kapoor; . Neeraj Rao

Volume 12, Issue 1 , January 2022, , Pages 1-5

Abstract

  BACKGROUND: The objective of the study was to analyze and determine statistically significantimpact of the COVID‑19 on clinical load of plastic and reconstructive surgery practices.MATERIALS ...  Read More BACKGROUND: The objective of the study was to analyze and determine statistically significantimpact of the COVID‑19 on clinical load of plastic and reconstructive surgery practices.MATERIALS AND METHODS: The retrospective analysis and comparison of the number of patientsvisiting to outpatient clinic, number of patients admitted, number of patients operated in the plasticand reconstructive surgery department during the COVID‑19 pandemic months of January 2020–June 2020 with the same months of preceding non‑COVID‑19 year was done. The data obtainedwere tabulated in Microsoft Excel spread sheet and the statistical analysis done using MedCalcstatistical software.RESULTS: The mean ± standard deviation of patients attended in outpatient department (OPD),admitted in inpatient department (IPD), emergency surgeries performed, and elective surgeriesperformed during ‑COVID‑19 versus COVID‑19 pandemic period is (651.167 ± 310.42 vs.212.5 ± 307.591), (83.5 ± 16.263 vs. 34.333 ± 53.74), (5.167 ± 4.243 vs. 3.333 ± 4.95),and (74.333 ± 28.284 vs. 40.833 ± 60.811), respectively. The difference in means is highly significantstatistically in the number of patients attended in OPD, admitted in IPD, and elective surgeriesperformed during pre‑COVID versus COVID period; however, the difference in the means is notstatistically significant in the number of emergency surgeries performed during pre‑COVID versusCOVID period.CONCLUSION: The COVID‑19 pandemic has significantly reduced the number of patients attended inOPD, admitted in IPD, and elective surgeries performed in the department of plastic surgery. However,there is a reduction in number of emergency surgeries but statistically insignificant. The strategy isto use telemedicine portal e‑Sanjeevani services for OPD, encourage admission of patients withreverse transcription polymerase chain reaction negative for COVID‑19, and perform reconstructiveand esthetic plastic surgery operative procedures using COVID‑19 appropriate precautions.

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Developing an artificial neural network for detecting COVID‑19 disease

. Mostafa Shanbehzadeh; . Raoof Nopour; . Hadi Kazemi-Arpanahi

Volume 12, Issue 1 , January 2022, , Pages 1-10

Abstract

  BACKGROUND: From December 2019, atypical pneumonia termed COVID‑19 has been increasingexponentially across the world. It poses a great threat and challenge to world health and the ...  Read More BACKGROUND: From December 2019, atypical pneumonia termed COVID‑19 has been increasingexponentially across the world. It poses a great threat and challenge to world health and the economy.Medical specialists face uncertainty in making decisions based on their judgment for COVID‑19.Thus, this study aimed to establish an intelligent model based on artificial neural networks (ANNs)for diagnosing COVID‑19.MATERIALS AND METHODS: Using a single‑center registry, we studied the records of 250 confirmedCOVID‑19 and 150 negative cases from February 9, 2020, to October 20, 2020. The correlationcoefficient technique was used to determine the most significant variables of the ANN model. Thevariables at P < 0.05 were used for model construction. We applied the back‑propagation techniquefor training a neural network on the dataset. After comparing different neural network configurations,the best configuration of ANN was acquired, then its strength has been evaluated.RESULTS: After the feature selection process, a total of 18 variables were determined as the mostrelevant predictors for developing the ANN models. The results indicated that two nested loops’architecture of 9‑10‑15‑2 (10 and 15 neurons used in layer 1 and layer 2, respectively) with the areaunder the curve of 0.982, the sensitivity of 96.4%, specificity of 90.6%, and accuracy of 94% wasintroduced as the best configuration model for COVID‑19 diagnosis.CONCLUSION: The proposed ANN‑based clinical decision support system could be considered as asuitable computational technique for the frontline practitioner in early detection, effective intervention,and possibly a reduction of mortality in patients with COVID‑19.

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A cross sectional study to assess the expressed COVID‑19 preventive practices among the health care workers and public visiting tertiary care hospital, AIIMS, Jodhpur

. Mukesh C. Sharma; . V. A. Raghu; . Manish K. Balai

Volume 12, Issue 1 , January 2022, , Pages 1-6

Abstract

  BACKGROUND: The corona virus disease‑2019 (COVID‑19) infection is a current public healthcrisis, and it is challenging to the world health‑care system. As there is no treatment, ...  Read More BACKGROUND: The corona virus disease‑2019 (COVID‑19) infection is a current public healthcrisis, and it is challenging to the world health‑care system. As there is no treatment, preventionis the crucial importance to break the chain of transmission of infection and prevent fatality amongthe high‑risk populations. The aim of the study was to assess the Expressed COVID‑19 preventivepractices among health‑care workers (HCWs) and the public visiting tertiary care hospital, AIIMS,Jodhpur.METHODOLOGY: A cross‑sectional study was conducted among 406 HCWs and 238 public, recruitedby convenient sampling technique. A validated and pretested self‑structured practice questionnaireused to collect the data regarding COVID‑19 preventive practice. The data were collected throughonline Google Forms and interview techniques and analyzed by software SPSS 26 version.RESULTS: Majority of 87.7% HCWs and 76.5% public always followed practice of hand wash withsoap and water and sanitize for 20 s. Majority of 79.6% HCWs and 49.2% public maintain socialdistance in public place. Gender (χ2 = 18.806 P ≤ 0.001) and education (χ2 = 43.270 P ≤ 0.001)among HCWs and in public demographic variable income (χ2 = 21.102 P = 0.002), religion (χ2 = 13.302P = 0.006) and source of information (χ2 = 17.030 P = 0.026) was significantly associated with levelof COVID‑19 preventive practice.CONCLUSION: The study showed moderate level of COVID‑19 preventive practice among HCWsand public. Based on this result, an effective IEC intervention programs can be designed to educatepublic and HCWs and follow a safe COVID‑19 preventive practice.

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Homemade food, alcohol, and body weight: Change in eating habits in young individuals at the time of COVID‑19 Lockdown

. Elisa Mazza; . Yvelise Ferro; . Roberta Pujia; . Samantha Maurotti; . Tiziana Montalcini; . Arturo Pujia

Volume 11, Issue 10 , November 2021, , Pages 1-8

Abstract

  BACKGROUND: The 2019 coronavirus disease (COVID‑19) lockdown has caused significantchanges in everyday life. This study evaluated the effect of the COVID‑19 quarantine on dietary ...  Read More BACKGROUND: The 2019 coronavirus disease (COVID‑19) lockdown has caused significantchanges in everyday life. This study evaluated the effect of the COVID‑19 quarantine on dietary andalcohol consumption habits and body weight of Italian university students.MATERIALS AND METHODS: An online cross‑sectional survey was carried out among universitystudents than 18 years in July 2020. The online self‑administered questionnaire included demographicand anthropometric data (reported weight and height), weight, and dietary habits changes during ofthe COVID‑19 lockdown.RESULTS: A total of 520 respondents have been included in the study. A total of 393 (~76%) werefemale, 3.8% was obese, and the mean age was 23 ± 4 years. Numerous students reported a changein their eating habits during the lockdown with an increase in consumption of chocolate (40%),ice cream, and desserts (34%), but most of all an increase of homemade bread and pasta (60%),pizza (47%), and homemade sweets (55%). The students also reported an increase of vegetables,fresh fruit, legumes, eggs, and coffee, but also of processed meat, fried foods, cheeses, butter,and sweet beverage, and a reduction in alcohol intake. The weight gain was observed in 43.8%,and males have greater weight gain than females (57% vs. 46%, respectively; P = 0.04). A greaterincrease in body weight was observed in obese as compared to those with normal weight (77% vs.44%, respectively; P < 0.001).CONCLUSIONS: Our data highlighted the need for dietary guidelines to prevent weight gain duringthe period of self‑isolation, especially targeting those with overweight and obesity.

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Epidemiology and factors associated with COVID‑19 outbreak‑related deaths in patients admitted to medical centers of Mazandaran University of Medical Sciences

. Hamidreza Khankeh; . Mehrdad Farrokhi; . Hassan Talebi Ghadicolaei; . Sadegh Ahmadi Mazhin; . Juliet Roudini; . Yazdan Mohsenzadeh; . Zoya Hadinejad

Volume 11, Issue 10 , November 2021, , Pages 1-6

Abstract

  BACKGROUND: The first case of COVID‑19 was reported in Iran on February 19, 2020, in Qom. SinceMazandaran is one of the high‑risk provinces with many patients and deaths, this study ...  Read More BACKGROUND: The first case of COVID‑19 was reported in Iran on February 19, 2020, in Qom. SinceMazandaran is one of the high‑risk provinces with many patients and deaths, this study was conductedto investigate the epidemiological characteristics of COVID‑19‑related deaths in Mazandaran.MATERIALS AND METHODS: In this descriptive study, demographic information and clinicalfindings in patients who died following COVID‑19 in the medical centers of Mazandaran University ofMedical Sciences from February 8, 2020, to October 10, 2020, were extracted. Data were analyzedby using SPSS 21. Logistic regression was used to compare the data. P < 0.05 was considered asthe significance level.RESULTS: Out of a total of 34,039 patients admitted during the 8 months, 2907 patients died. Ofthese, 1529 (52%) were male, and the rest were female. In terms of age, 10 cases in the age groupof fewer than 15 years, 229 cases in the age group of 15–44 years, 864 patients in the age group of45–64 years, and 1793 people in the age group of 65 years and over died. 2206 people (more than75%) by personal visit referred to medical centers. The mortality rate was more than 8 cases per 100hospitalized patients. Men were 16% more likely to die from COVID‑19 than women.DISCUSSION AND CONCLUSION: Older adults over 65 have the highest incidence and death ratedue to this disease. The incidence rate was higher in women, and the death rate was higher in men,which differs from the national pattern.

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Performance analysis of data mining algorithms for diagnosing COVID‑19

. Raoof Nopour; . Hadi Kazemi‑Arpanahi; . Mostafa Shanbehzadeh; . Akbar Azizifar

Volume 11, Issue 10 , November 2021, , Pages 1-8

Abstract

  BACKGROUND: An outbreak of atypical pneumonia termed COVID‑19 has widely spread all overthe world since the beginning of 2020. In this regard, designing a prediction system for the ...  Read More BACKGROUND: An outbreak of atypical pneumonia termed COVID‑19 has widely spread all overthe world since the beginning of 2020. In this regard, designing a prediction system for the earlydetection of COVID‑19 is a critical issue in mitigating virus spread. In this study, we have appliedselected machine learning techniques to select the best predictive models based on their performance.MATERIALS AND METHODS: The data of 435 suspicious cases with COVID‑19 which were recordedfrom the Imam Khomeini Hospital database between May 9, 2020 and December 20, 2020, havebeen taken into consideration. The Chi‑square method was used to determine the most importantfeatures in diagnosing the COVID‑19; eight selected data mining algorithms including multilayerperceptron (MLP), J‑48, Bayesian Net (Bayes Net), logistic regression, K‑star, random forest,Ada‑boost, and sequential minimal optimization (SMO) were applied in data mining. Finally, the mostappropriate diagnostic model for COVID‑19 was obtained based on comparing the performance ofthe selected algorithms.RESULTS: As the result of using the Chi‑square method, 21 variables were identified as themost important diagnostic criteria in COVID‑19. The results of evaluating the eight selected datamining algorithms showed that the J‑48 with true‑positive rate = 0.85, false‑positive rate = 0.173,precision = 0.85, recall = 0.85, F‑score = 0.85, Matthews Correlation Coefficient = 0.68, and areaunder the receiver operator characteristics = 0.68, respectively, had the higher performance thanthe other algorithms.CONCLUSION: The results of evaluating the performance criteria showed that the J‑48 can beconsidered as a suitable computational prediction model for diagnosing COVID‑19 disease.

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COVID‑19 vaccine acceptability, determinants of potential vaccination, and hesitancy in public: A call for effective health communication

. Rajesh Kumar; . Mukesh Bairwa; . Kalpana Beniwal; . Ravi Kant

Volume 11, Issue 9 , October 2021, , Pages 1-10

Abstract

  BACKGROUND: Coronavirus disease rapidly spreads across the entire world in < 2 months andgravely jeopardizes the regular human routine. The medical fraternity recommends a vaccine ...  Read More BACKGROUND: Coronavirus disease rapidly spreads across the entire world in < 2 months andgravely jeopardizes the regular human routine. The medical fraternity recommends a vaccine as oneof the best solutions to save the universe. However, to be effective, the population should reflect anencouraging attitude to accept it. The study aimed to measure vaccine acceptability and reason forhesitancy among the public.MATERIALS AND METHODS: Eight hundred and forty one adults visiting a tertiary care hospitalresponded to a pretested validated questionnaire on vaccine acceptability and hesitancy. The Chi‑squaretest and independent t‑test, followed by multinomial logistic regression, were used to analyze the findings.RESULTS: Overall, 53.4% (n = 445) of participants interested to take vaccine, 27.2% (n = 229)were not sure, and the remaining 19.4% (n = 163) did not intent to vaccinate. Gender (P = 0.013),information on the vaccine (P = 0.022), chances to get coronavirus disease in the next 6months (P < 0.001), awareness on India COVID‑19 vaccine (P < 0.001), Indian manufacturingcompany of vaccine (P < 0.001), family history of the laboratory‑confirmed case (P < 0.001), andhealth status (P = 0.011) found a significant association with intention to vaccination (a response“yes” vs. “no” and “not sure”). Reasons for vaccine hesitancy included specific antivaccine attitudesand beliefs, a concern of fear and phobia, lack of information, and safety issues on the vaccine.CONCLUSIONS: This institute‑specific survey revealed that approximately every 4 in 8 people werenot sure to take the vaccine, and one in five people refused to be vaccinated. The study recommendsusing target‑based health education to understand and address vaccine‑specific concerns to enhancevaccine coverage, and boost confidence among the population.

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A content analysis of social media on outbreak of infodemic amidst COVID‑19 pandemic

. Anusha Divvi; . Shivashankar Kengadaran; . Lakshmi Subhashini Katuri; . M. Kavitha; . Arunkumar Sundaragopal; . Vani Anusha; . Sivabalakumaran Kengadaran; . Hemachandran Sekar

Volume 11, Issue 9 , October 2021, , Pages 1-5

Abstract

  BACKGROUND: With so much content on social media platforms about COVID‑19, determiningwhich information is reliable can be a daunting task. Hence, this study is aimed to analyze variousposts ...  Read More BACKGROUND: With so much content on social media platforms about COVID‑19, determiningwhich information is reliable can be a daunting task. Hence, this study is aimed to analyze variousposts with regard to COVID‑19 on various social media platforms for their reliability and also examinedvarious factors that influence information reliability.MATERIALS AND METHODS: A cross‑sectional study was conducted, with 934 samples relatedto coronavirus pandemic published on Twitter, Instagram, and Facebook using systematic randomsampling. We adopted the criteria given by Paul Bradshaw and modified to assess the characteristicsof the samples. Training and calibration of the investigators were carried out for 3 consecutive daysbefore beginning the study. The data were analyzed using the Chi‑square test and multinomial logisticregression to estimate the odds ratios.RESULTS: Out of 934 samples studied, only 570 (61%) were found to be reliable of which243 (42.6%) were from Twitter, 117 (20.6%) from Instagram, and 210 (36.8%) from Facebook.We found that the reliability of the information on social media platforms is significantly influencedby network (odds: 1.32; 95% confidence interval [CI]: 1.16–1.52; P = 0.036), content (odds: 1.83;95% CI: 1.69–1.92; P = 0.009), contextual update (odds: 1.41; 95% CI: 1.24–1.53) and age of theaccount (odds: 1.92; 95% CI: 1.64–2.09; P = 0.002).CONCLUSION: Our study shows that the reliability of the social media posts significantly dependson the network, contextual update, and age of the account. Hence, cross verifying the informationfrom a reliable source is the need of the hour to prevent panic and mental distress.

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Performance evaluation of selected machine learning algorithms for COVID‑19 prediction using routine clinical data: With versus Without CT scan features

. Mostafa Shanbehzadeh; . Hadi Kazemi-Arpanahi; . Azam Orooji; . Sara Mobarak; . Saeed Jelvay

Volume 11, Issue 7 , August 2021, , Pages 1-11

Abstract

  BACKGROUND: Given coronavirus disease (COVID‑19’s) unknown nature, diagnosis, and treatmentis very complex up to the present time. Thus, it is essential to have a framework ...  Read More BACKGROUND: Given coronavirus disease (COVID‑19’s) unknown nature, diagnosis, and treatmentis very complex up to the present time. Thus, it is essential to have a framework for an early predictionof the disease. In this regard, machines learning (ML) could be crucial to extract concealed patternsfrom mining of huge raw datasets then it establishes high‑quality predictive models. At this juncture,we aimed to apply different ML techniques to develop clinical predictive models and select the bestperformance of them.MATERIALS AND METHODS: The dataset of Ayatollah Talleghani hospital, COVID‑19 focal centeraffiliated to Abadan University of Medical Sciences have been taken into consideration. The datasetused in this study consists of 501 case records with two classes (COVID‑19 and non COVID‑19) and32 columns for the diagnostic features. ML algorithms such as Naïve Bayesian, Bayesian Net, randomforest (RF), multilayer perceptron, K‑star, C4.5, and support vector machine were developed. Then,the recital of selected ML models was assessed by the comparison of some performance indices suchas accuracy, sensitivity, specificity, precision, F‑score, and receiver operating characteristic (ROC).RESULTS: The experimental results indicate that RF algorithm with the accuracy of 92.42%, specificityof 75.70%, precision of 92.30%, sensitivity of 92.40%, F‑measure of 92.00%, and ROC of 97.15%has the best capability for COVID‑19 diagnosis and screening.CONCLUSION: The empirical results reveal that RF model yielded higher performance as comparedto other six classification models. It is promising to the implementation of RF model in the health‑caresettings to increase the accuracy and speed of disease diagnosis for primary prevention, screening,surveillance, and early treatment.

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Systematic review on telemedicine platforms in lockdown periods: Lessons learned from the COVID‑19 pandemic

. Mostafa Shanbehzadeh; . Hadi Kazemi-Arpanahi; . Sasan Ghorbani Kalkhajeh; . Gholam Basati

Volume 11, Issue 5 , June 2021, , Pages 1-10

Abstract

  With the onset of the coronavirus disease 2019 (COVID‑19) outbreak, the transformation of the caredelivery model from conventional in-person (face to face) to largely virtual or remote ...  Read More With the onset of the coronavirus disease 2019 (COVID‑19) outbreak, the transformation of the caredelivery model from conventional in-person (face to face) to largely virtual or remote care has beenaccelerated to appropriately allocate resources and constrain the spread of the virus. In this regard,telemedicine is a breakthrough technology to battle against the COVID‑19 emergency. Therefore, wesought to identify the telemedicine applications in the COVID‑19 pandemic (tele‑COVID) accordingto interaction modes, transmission modalities, and disease categories. This systematic reviewwas conducted through searching five databases including PubMed, Scopus, ProQuest, Web ofScience, and Science Direct. Inclusion criteria were studies clearly outlining any use of telemedicineinteractive mode during the COVID‑19 pandemic, written in English language and published inpeer-reviewed journals in 2020. Finally, 43 articles met the inclusion out of the 1118 search results.Telemedicine provides a diversity of interaction modes and modalities affordable by patients andphysicians including short message service, E-mail and web portals, secure telephone calls or VOIP,video calls, interactive mobile health applications (m-Health), remote patient monitoring, and videoconferencing. Transmission of video data using synchronized video calls via common social mediahad the highest and exchange of data using store-forward service via secure messaging technologyand prerecorded multimedia had the lowest popularity for virtual disease management during theCOVID‑19 outbreak. Selection of telemedicine communication services and interaction modes withregard to its use‑case, disease category, and application plays a significant role in the success ofremote disease management infrastructures in this scenario and their implication for a better futurehealthcare system.

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Study of clinical features of patients with COVID‑19 hospitalized in an educational hospital in Iran

. Abbas Homauni; . Ladan Ghadami; . Hamed Abdollahi; . Alireza Namazi Shabestari; . Behzad Asanjarani

Volume 11, Issue 4 , May 2021, , Pages 1-5

Abstract

  BACKGROUND: The outbreak of new pathogens or the resurgence of pathogens that have alreadyspread is a serious challenge to public health. Coronavirus is a pathogen that seems to invade ...  Read More BACKGROUND: The outbreak of new pathogens or the resurgence of pathogens that have alreadyspread is a serious challenge to public health. Coronavirus is a pathogen that seems to invade thehuman respiratory system in the first place. Coronaviruses form a large family and are so calledbecause of the presence of crown like cristae on their surface.MATERIALS AND METHODS: This is a cross‑sectional, descriptive study conducted to assess thestatus of patients with COVID‑19 who were hospitalized in an educational hospital. For this purpose,142 patients hospitalized in this hospital were followed up 2 weeks after discharge and were inquired aboutthe symptoms they had upon admission to the hospital, the number of hospitalization days, the history ofunderlying disease, and so on. Descriptive data analysis was done with the SPSS software version 22.RESULTS: The findings of this research showed that overweight or obese people (about 66%)is more likely to contract the disease. It also seems that older people (37.3% older than 60 yearsold) and those with a history of diseases (69.6%) such as diabetes, high blood pressure, or heartdisease are more prone to COVID‑19. The most common symptoms of COVID‑19 patients includedfever (64.5%), shortness of breath (67.4%), and dry cough (50.4%).CONCLUSION: it seems that high risk group (obese people, old people, and people with a history ofdisease) is more likely to be infect with coronavirus so they should more careful than others. Anotherimportant issue is that policy‑makers must play an active role in public awareness of dangers ofCOVID‑19 and ways to prevent it.

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Notifiable diseases interoperable framework toward improving Iran public health surveillance system: Lessons learned from COVID‑19 pandemic

. Mostafa Shanbehzadeh; . Hadi Kazemi-Arpanahi; . Ali Asghar Valipour; . Atefeh Zahedi

Volume 11, Issue 4 , May 2021, , Pages 1-11

Abstract

  BACKGROUND: Direct transmission of notifiable disease information in a real‑time and reliable wayto public health decision‑makers is imperative for early identification of epidemiological ...  Read More BACKGROUND: Direct transmission of notifiable disease information in a real‑time and reliable wayto public health decision‑makers is imperative for early identification of epidemiological trends as wellas proper response to potential pandemic like ongoing coronavirus disease 2019 crisis. Thus, thisresearch aimed to develop of semantic‑sharing and collaborative‑modeling to meet the informationexchange requirements of Iran’s notifiable diseases surveillance system.MATERIALS AND METHODS: First, the Iran’s Notifiable diseases Minimum Data Set (INMDS)was determined according to a literature review coupled with agreements of experts. Then theINMDS was mapped to international terminologies and classification systems, and the Health Levelseven‑Clinical Document Architecture (HL7‑CDA) standard was leveraged to define the exchangeableand machine‑readable data formats.RESULTS: A core dataset consisting of 15 classes and 96 data fields was defined. Dataelements and response values were mapped to Systematized Nomenclature of Medicine‑ClinicalTerms (SNOMED‑CT) reference terminology. Then HL7‑CDA standard for interoperable dataexchange were defined.CONCLUSION: The notifiable disease surveillance requires an integrative participation ofmultidisciplinary team. In this field, data interoperability is more essential due to the heterogeneousnature of health information systems. Developing of INMDS based on HL7‑CDA along withSNOMED‑CT codes offers an inclusive and interoperable dataset that can help make notifiablediseases data more comparable and reportable across studies and organizations. The proposeddata model will be further modifications in the future according probable changes in Iran’s notifiablediseases list.

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Evaluation of clinical outcomes of neonates born to mothers with coronavirus (COVID‑19) in Shahid Beheshti Hospitals

. Maryam Sadat Hosseini; . Afsaneh Hosseini; . Elnaz Ghaffari; . Mitra Radfar; . Fariba Shirvani; . Shahrzad Tabatabai; . Dariush Abtahi; . Mahsa Mirhadi; . Maziyar Mortazavi; . Shideh Ariana

Volume 11, Issue 4 , May 2021, , Pages 1-9

Abstract

  BACKGROUND: The coronavirus, which is caused by acute respiratory syndrome, appeared inWuhan, China, in December 2019 and gradually spread around the world until almost all countriesbecame ...  Read More BACKGROUND: The coronavirus, which is caused by acute respiratory syndrome, appeared inWuhan, China, in December 2019 and gradually spread around the world until almost all countriesbecame infected with the coronavirus. In Iran, the outbreak of coronavirus began on February 21,2020, with the report of infection of two people in the city of Qom. The aim of this study is to evaluatethe clinical findings of neonates born to pregnant women with corona disease.MATERIALS AND METHODS: During this case study (February 21 to November 30, 2020), out of88 pregnant mothers who referred to the hospitals of Shahid Beheshti University of Medical Sciences,44 live neonates were born from 42 pregnant women with COVID‑19, who were evaluated for clinicalsigns by studying their files and reported as a case series, due to limited samples, No statisticalanalysis of the study was performed.RESULTS: In studies of clinical records of hospitalized mothers and infants, among the polymerasechain reactions (PCRs) provided for all infants, one PCR was reported positive 2 days after birth,whereas this infant 10 min after birth, immediately after routine procedures, due to positive mother’sPCR was isolated from the operating room. However, all of the infant’s clinical symptoms were normalduring the 3‑day hospital stay for routine postpartum care. Twenty‑eight days after birth, the babywas reevaluated for clinical, laboratory, and chest X‑ray symptoms, all of which were normal. ThePCR of other neonates was negative, and five intubated neonates, two twin, and two single died, andthe other neonates were discharged. In evaluating the clinical records of mothers of these infants,the mean age is 30 years, and the average gestational age is 35 weeks, 32 cases of caesareansection, and 10 cases of normal delivery.CONCLUSION: We describe epidemiological data, demographics, signs and symptoms onadmission, laboratory results, comorbidities, infection COVID‑19 in the mothers and neonates,chest radiography and computed tomography findings, treatment received for COVID‑19, andclinical maternal, fetal, and neonatal outcomes. Due to the fact that the study population issmall consist of 42 mothers with COVID‑19 infection, among all PCR samples from infantsborn to COVID‑19 positive mothers, the PCR result of one case was positive, and the rest ofwas negative. Therefore, vertical transmission of COVID‑19 through the placenta to the fetuscannot be confirmed or denied, nor can the COVID‑19 confirmed or denied the baby’s postnatalcomplication during pregnancy.

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Approaches and perspectives for online learning during the COVID‑19 pandemic and future chaos

. Shagufta Nesar; . Kiran Rafiq; . Muhammad Rizwan; . Syed Mehmood Hasan

Volume 11, Issue 4 , May 2021, , Pages 1-6

Abstract

  BACKGROUND: Online learning (OLL) methodology has been incorporated in higher educationextensively on the mount over the last few decades and with the onset of COVID‑19 situation, ...  Read More BACKGROUND: Online learning (OLL) methodology has been incorporated in higher educationextensively on the mount over the last few decades and with the onset of COVID‑19 situation, thevirtual method in academia became essential. After observing worldly destructions and death dueto coronavirus, the WHO declared a high alert emergency, and since Pakistan started to followlockdown since March 2020 to prevent high penetration and consequently, the online teaching methodwas adapted to keep the learning atmosphere alive. The study is aimed to identify the influencingfactors and compliance for the implementation of the OLL system in COVID‑19 and, in the future,nonpandemic state as well.MATERIALS AND METHODS: The present study is designed to observe the adaptability and hurdlesamong pharmacy students, and for the purpose of the study, a questionnaire on the Likert scale wasdeveloped and asked to respond from pharmacy undergraduate and postgraduate students aftertaking consensus, which further analyzed through IBM SPSS Statistics Version 26.RESULTS: The outcomes of the study were analyzed with a high level of conformity; however, thegender‑based reservations were observed, and moreover, merits of OLL were observed with highjeopardy.CONCLUSION: The adaptation of OLL, though proved as the only troubleshooter in an uncontrollablesituation and enabled universities, professors, and students for patience, resilience, and hopefully,will serve as swift safeguard for future challenges of epidemic and pandemic disasters. Accordingto the evolution theory, brain adaptability and plasticity of human organisms grow the capacity toadjust itself with an advanced characteristic.

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The effect of coronavirus (COVID‑19) pandemic on medical sciences education in Iran

. Habibolah Rezaei; . Aliakbar Haghdoost; . Hamid Akbari Javar; . Reza Dehnavieh; . Shahintaj Aramesh; . Nasrin Dehgani; . Mohamad Tahmasbi Sisakht

Volume 11, Issue 4 , May 2021, , Pages 1-8

Abstract

  BACKGROUND: COVID‑19 has a great impact on medical sciences education. Some researcheshave been conducted on the effects of the COVID‑19 pandemic on medical sciences educationin ...  Read More BACKGROUND: COVID‑19 has a great impact on medical sciences education. Some researcheshave been conducted on the effects of the COVID‑19 pandemic on medical sciences educationin the world. The aim of this study was to identify the effects of this disease on medical scienceseducation in Iran.MATERIALS AND METHODS: This futures study research was carried out using the future wheelmethod in Iran’s University of Medical Sciences in the spring of 2020. A semi‑structured interviewwas also conducted on the vice chancellors of medical sciences universities, faculty presidents,faculty vice chancellors, faculty members, medical education specialists, and university students,who were purposefully identified. The interview continued until achieving data saturation. Analysisof the interviews was performed by MAXQDA version 10 software.RESULTS: The effects were presented at three levels including primary effects, secondary effects,and third effects. In addition, 16 primary effects, 51 secondary effects, and 24 tertiary effects wererecognized. One primary effect of the coronavirus (COVID‑19) pandemic on medical scienceseducation in Iran was fear, stress, and anxiety among students and faculty members as well asstaffs to get the disease. In addition, rumor was circulated concerning the infection of some people,thus, there was a need for holding courses regarding stress management and rumor management.One secondary effect of the coronavirus (COVID‑19) pandemic on medical sciences education inIran was allocation of a number of educational hospitals to the referral hospitals of COVID‑19. Onetertiary effect of the coronavirus (COVID‑19) pandemic on medical sciences education in Iran wasincreasing the number of virtual courses.CONCLUSIONS: The most important effect of this disease on medical sciences education is thepostponement of practical and apprenticeship classes, and consequently the increased length of theacademic term that leads to delay in the students’ graduation, which can reduce the workforce. Onthe one hand, this disease causes death of a number of students, educational and medical staffs,and faculty members, as well as reduces the workforce. Also, lengthening the recruitment of facultymembers will add to this challenge. In this regard, there is a need to plan to compensate for theshortage of required human resources.

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Social media effects among freshman medical students during COVID‑19 lock‑down: An online mixed research

. Ankit Gupta; . Arunita Jagzape; . Mahendra Kumar

Volume 11, Issue 2 , February 2021, , Pages 1-6

Abstract

  BACKGROUND: Lockdown was imposed as a preventive measure for coronavirus diseasepandemic. Social media was the most common tool available for the masses, including the 1styear medical ...  Read More BACKGROUND: Lockdown was imposed as a preventive measure for coronavirus diseasepandemic. Social media was the most common tool available for the masses, including the 1styear medical students during the lockdown. The objectives of the present study were to determinethe extent of use of social media and the effects on mind‑body and social distancing.MATERIALS AND METHODS: It was mixed research conducted on 1st‑year medical studentsusing convenience sampling. The quantitative aspect of E‑survey was administered through Googleforms sent via E‑mail, and structured telephonic interview was conducted as a qualitative aspect onrandomly selected 10 students based on predecided interview questions. This study was reportedas per the Checklist for Reporting Results of Internet E‑Surveys. The analysis was performed usingpercentages and paired t‑test with significance at P < 0.05, Chi‑square test with Yate’s correction.Qualitative responses were analyzed using coding and categorization.RESULTS: The response rate was 88%. Time spent on social media for >4 h increased from 1.1% to47.72% during lockdown. Forty three (48.86%) of the students reported increased mood fluctuations.The relation between mood fluctuations and time spent on social media of >4 h was significant𝜒2 = 6.41 with P < 0.05. Average hours of sleep after using social media before lockdown increasedsignificantly from 6.68 h to 8.10 h during lockdown using paired t‑test, where “t” was 6.84. Therewas a positive impact on communication with friends and family.CONCLUSION: Due to the increased extent of use of social media during lockdown, negativemind‑body effects have surfaced but emerged as boon in terms of communication .

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Corona health‑care warriors in India: knowledge, attitude, and practices during COVID‑19 outbreak

. Rajesh Kumar; . Vanya Singh; . Aroop Mohanty; . Yogesh Bahurupi; . Puneet Kumar Gupta

Volume 11, Issue 2 , February 2021, , Pages 1-8

Abstract

  BACKGROUND: COVID‑19 has become a global health emergency after its first case in Wuhan city,China. An increasing number of cases and deaths are challenging the health‑care system ...  Read More BACKGROUND: COVID‑19 has become a global health emergency after its first case in Wuhan city,China. An increasing number of cases and deaths are challenging the health‑care system globally.This study aims to assess knowledge, attitude, and practice toward COVID‑19 disease among healthpersonnel in rapid outbreak in India.MATERIALS AND METHODS: A cross‑sectional survey was conducted using Google Forms throughGoogle platform on-line. A total of 713 health personal allied health‑care staff, working in different publicand private health‑care facilities, was conducted in the mid of April 2020. A structured knowledge, attitude,and practice questionnaire used to assess health personnel’s knowledge, attitude, and practice towardCOVID‑19. All instruments were validated and pretested before use. Chi‑square test, followed by binarylogistic and multivariate regression, was applied to determine factors associated with knowledge scores.RESULTS: Seven hundred and thirteen health personnel participated, and 703 (98.6%) participantsresponded were analyzed for final results. 95.9% of the health personnel were aware about routeof transmission and clinical symptoms (95.3%) of COVID‑19. 63.7% believed that virus outbreakwould be controlled globally and followed standard precautions (81.8%), including wearing the mask.Further, majority (98.3%) of the participants avoided social contact by not going to crowded placesand not calling people to their homes (82.2%) during the advisory of the government. In binarylogistic regression analyses, the adequate knowledge score found significantly associated withMBBS/bachelor’s degree (odds ratio [OR]: 2.309, confidence interval [CI]: 1.232–4.324, P < 0.009)and master’s degree (OR: 2.944, CI: 1.485–5.835, P < 0.002), working with government health‑carefacility (OR: 3.662, CI: 1.624–8.285, P < 0.002), and holding a post of a physician (OR: 7.735, CI:2.210–27.091, P < 0.001) during outbreak.CONCLUSIONS: The level of education is associated with adequate knowledge scores among thehealth personnel. Type of health‑care facility and post held in a health‑care facility are significantpredictors of adequacy of knowledge.

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