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COVID-19 Resilience Networks for Pandemic Preparedness and Response Coordination

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A special issue of Healthcare (ISSN 2227-9032). This special issue belongs to the section "Coronaviruses (CoV) and COVID-19 Pandemic".

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 17322

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Prof. Dr. Liaquat Hossain

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1. Nebraska Healthcare Collaborative Chair of Population Health Data Science Chairperson, Department of Cyber Systems, College of Business and Technology, The University of Nebraska at Kearney, Kearney, NE 68849, USA
2. Education Committee, Center for Intelligent Health Care, University of Nebraska Medical Center, Omaha, NE 68198-5506, USA
3. Visiting Professor, Department of Informatics, School of Economics and Management, Lund University, SE-22363 Lund, Sweden
Interests: complex systems; social networks; evolutionary systems; information flow; self organisation; bio-security; epidemics and public health interventions
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Dear Colleagues,

COVID-19 pandemic preparedness and response coordination can be seen as a multi-organizational effort, where shared goals—warning, containment and recovery—are heavily interdependent. For an extreme event such as the COVID-19 pandemic, the most efficient response is one where professionals from multiple organizations coordinate their respective knowledge, skills and abilities to overcome both the problems at the individual organizational level as well as problems affecting the community as a whole. This type of coordination, while ideal, presents a major challenge. The recent COVID-19 pandemic illustrates that coordination is often insufficient among responding government agencies, volunteers, businesses and humanitarian organizations. Effective coordination of the pandemic preparedness response effort depends on the transfer, use and quality of shared information about risks, vulnerabilities and hazards among coordinating agencies. This RAPID NSF proposal brings together complementary large-scale abstract modeling, including topological network modeling, algorithmic approaches to large-scale spatial and temporal data, agent-based simulations and organizational and community sense-making to create new, improved information-sharing environments for COVID-19 resilience networks toward threats. The Special Issue has three key aims:

To quantify and evaluate the existing networks of communication for COVID-19;
To design new COVID-19 resilience networks to ensure that multi-jurisdictional pandemic preparedness and responses are resilient to emerging threats of this coronavirus;
Results from this study can be leveraged to create communication networks that can organize multi-jurisdictional organizations during future disasters and public health crises.

This work will improve our understanding of human practices (i.e., social distancing, awareness, public policies, education, institutions) and build a quantitative, empirical research outcome to inform and guide pandemic preparedness and response practices for the current COVID-19 and future threats. The models created in your proposed project will help foster resilience and improve multi-jurisdictional decision-making during disease outbreaks of coronavirus and post-crisis analysis.

Prof. Dr. Liaquat Hossain
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

COVID-19
resilience networks
communication networks

Published Papers (9 papers)

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Research

11 pages, 267 KiB

Open AccessArticle

Self-Reflection, Emotional Self Disclosure, and Posttraumatic Growth in Nursing Students: A Cross-Sectional Study in South Korea

by KyoungSook Lee and SeongAh Ahn

Healthcare 2023, 11(19), 2616; https://doi.org/10.3390/healthcare11192616 - 23 Sep 2023

Viewed by 1152

Abstract

During the Coronavirus disease 2019 pandemic, several studies were conducted on mental health among various populations; however, only a few studies have focused on post-traumatic growth (PTG) in nursing students. By understanding the PTG involved in coping with emotionally challenging situations, educators, and institutions can prepare nursing students to navigate the demands of their profession and ultimately provide more empathetic and effective patient care. This study aimed to explore whether self-reflection and emotional self-disclosure are associated with PTG. A total of 195 nursing students completed the self-report questionnaire. This study used standardized instruments, including the self-reflection scale, emotional self-disclosure, and the Posttraumatic Growth Inventory (PTGI). Data were analyzed using descriptive statistics, a t-test, Pearson’s correlation coefficient, and hierarchical regression analysis using the SPSS/WIN 25.0 program. The factors influencing PTG included self-reflection (β = 0.36; p < 0.001), emotional self-disclosure (β = 0.24; p < 0.001), grade (β = −0.18; p = 0.008), and religion (β = −0.15; p = 0.013). The explanatory power of these four factors was 31.4%, and self-reflection was found to have the greatest influence on PTG. The results indicated the need for self-reflection and emotional self-disclosure promotion programs to improve PTG, especially for senior and non-religious students. Full article

(This article belongs to the Special Issue COVID-19 Resilience Networks for Pandemic Preparedness and Response Coordination)

16 pages, 248 KiB

Open AccessArticle

Physicians’ Trust in Relevant Institutions during the COVID-19 Pandemic: A Binary Logistic Model

by Tudor-Ștefan Rotaru, Aida Puia, Ștefan Cojocaru, Ovidiu Alexinschi, Cristina Gavrilovici and Liviu Oprea

Healthcare 2023, 11(12), 1736; https://doi.org/10.3390/healthcare11121736 - 13 Jun 2023

Cited by 1 | Viewed by 1151

Abstract

Little research has been done on professionals’ perceptions of institutions and governments during epidemics. We aim to create a profile of physicians who feel they can raise public health issues with relevant institutions during a pandemic. A total of 1285 Romanian physicians completed an online survey as part of a larger study. We used binary logistic regression to profile physicians who felt they were able to raise public health issues with relevant institutions. Five predictors could differentiate between respondents who tended to agree with the trust statement and those who tended to disagree: feeling safe at work during the pandemic, considering the financial incentive worth the risk, receiving training on the use of protective equipment, having the same values as colleagues, and enjoying work as much as before the pandemic. Physicians who trusted the system to raise public health issues with the appropriate institutions were more likely to feel that they shared the same values as their colleagues, to say they were trained to use protective equipment during the pandemic, to feel that they were safe at work during the pandemic, to enjoy their work as much as before the pandemic, and to feel that the financial bonus justified the risk. Full article

(This article belongs to the Special Issue COVID-19 Resilience Networks for Pandemic Preparedness and Response Coordination)

12 pages, 2927 KiB

Open AccessArticle

How Dexamethasone Used in Anti-COVID-19 Therapy Influenced Antihypertensive Treatment in Patients with SARS-CoV-2

by Andrei Puiu Cârstea, Adrian Mită, Mircea-Cătălin Fortofoiu, Irina Paula Doica, Doina Cârstea, Cristina Maria Beznă, Cristina Elena Negroiu, Ileana-Diana Diaconu, Andreea-Roberta Georgescu, Adina Maria Kamal, Beatrice Mahler, Adriana-Gabriela Grigorie and Gabriel Adrian Dobrinescu

Healthcare 2023, 11(10), 1399; https://doi.org/10.3390/healthcare11101399 - 11 May 2023

Cited by 1 | Viewed by 1168

Abstract

Background: During the SARS-CoV-2 pandemic period, in the treatment approved by the WHO, along with antivirals, antibiotics, nonsteroidal anti-inflammatory drugs and anticoagulants, dexamethasone was always used. This study started from the professional concern related to the vasopressor effect of cortisone on blood pressure (BP). Methods: The study group was achieved by selecting, from a total of 356 patients hospitalized in the clinic, the patients with known hypertensive status at admission for SARS-CoV-2. Dexamethasone was part of the anti-COVID-19 treatment, with an administration of 4–6–8 mg/day, depending on bodyweight, for 10 days. All patients with hypertension received antihypertensive treatment in adjusted doses according to the recorded BP values. Results: Monitoring of BP in hospitalized patients was performed daily, in the morning and evening. If on the 2nd day of treatment, 84% of the patients partially responded to the treatment with a moderate decrease in BP, on the 3rd therapy day, the situation clearly improved: more than 75% of the patients had values of BP that can be classified as high-normal (38.23%) and normal (40.03%). Conclusions: Dexamethasone for treatment of SARS-CoV-2 infection did not have a notable influence on increasing BP, because the doses were low–moderate and prescribed for a short time. Full article

(This article belongs to the Special Issue COVID-19 Resilience Networks for Pandemic Preparedness and Response Coordination)

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16 pages, 3403 KiB

Open AccessArticle

Exploring the Role of Infodemics in People’s Incompliance with Preventive Measures during the COVID-19 in Conflict Settings (Mixed Method Study)

by Ahmed Asa’ad Al-Aghbari, Ola El Hajj Hassan, Maureen Dar Iang, Albrecht Jahn, Olaf Horstick and Fekri Dureab

Healthcare 2023, 11(7), 952; https://doi.org/10.3390/healthcare11070952 - 26 Mar 2023

Cited by 4 | Viewed by 1855

Abstract

The evolving availability of health information on social media, regardless of its credibility, raises several questions about its impact on our health decisions and social behaviors, especially during health crises and in conflict settings where compliance with preventive measures and health guidelines is already a challenge due to socioeconomic factors. For these reasons, we assessed compliance with preventive measures and investigated the role of infodemic in people’s non-compliance with COVID-19 containment measures in Yemen. To this purpose and to triangulate our data collection, we executed a mixed method approach in which raw aggregated data were taken and analyzed from multiple sources (COVID-19 Government Response Tracker and Google COVID-19 Community Mobility Reports), then complemented and verified with In-depth interviews. Our results showed that the population in Yemen had relatively complied with the governmental containment measures at the beginning of the pandemic. However, containment measures were not supported by daily COVID-19 reports due to low transparency, which, together with misinformation and lack of access to reliable sources, has caused the population not to believe in COVID-19 and even practice social pressure on those who showed some compliance with the WHO guidelines. Those results indicate the importance of adopting an infodemic management approach in response to future outbreaks, particularly in conflict settings. Full article

(This article belongs to the Special Issue COVID-19 Resilience Networks for Pandemic Preparedness and Response Coordination)

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24 pages, 5051 KiB

Open AccessArticle

Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier

by Kashif Shaheed, Piotr Szczuko, Qaisar Abbas, Ayyaz Hussain and Mubarak Albathan

Healthcare 2023, 11(6), 837; https://doi.org/10.3390/healthcare11060837 - 13 Mar 2023

Cited by 9 | Viewed by 4197

Abstract

In recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia. First, a pre-processing method based on a Gaussian filter and logarithmic operator is applied to input chest X-ray (CXR) images to improve the poor-quality images by enhancing the contrast, reducing the noise, and smoothing the image. Second, robust features are extracted from each enhanced chest X-ray image using a Convolutional Neural Network (CNNs) transformer and an optimal collection of grey-level co-occurrence matrices (GLCM) that contain features such as contrast, correlation, entropy, and energy. Finally, based on extracted features from input images, a random forest machine learning classifier is used to classify images into three classes, such as COVID-19, pneumonia, or normal. The predicted output from the model is combined with Gradient-weighted Class Activation Mapping (Grad-CAM) visualisation for diagnosis. (3) Results: Our work is evaluated using public datasets with three different train–test splits (70–30%, 80–20%, and 90–10%) and achieved an average accuracy, F1 score, recall, and precision of 97%, 96%, 96%, and 96%, respectively. A comparative study shows that our proposed method outperforms existing and similar work. The proposed approach can be utilised to screen COVID-19-infected patients effectively. (4) Conclusions: A comparative study with the existing methods is also performed. For performance evaluation, metrics such as accuracy, sensitivity, and F1-measure are calculated. The performance of the proposed method is better than that of the existing methodologies, and it can thus be used for the effective diagnosis of the disease. Full article

(This article belongs to the Special Issue COVID-19 Resilience Networks for Pandemic Preparedness and Response Coordination)

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13 pages, 850 KiB

Open AccessArticle

Clinical Consequences for Individuals Treated with Tocilizumab for Serious COVID-19 Infection

by Al Shaimaa Ibrahim Rabie, Hager Salah, Amira S. A. Said, Ahmed Hassan Shaaban, Lamya Mohamed Abdou, Doaa Mahmoud Khalil, Zelal Kharaba, Hala Afifi, Mahmoud R. Sofy, Eman M. I. Youssef, Eman S. M. Bayoumy and Raghda R. S. Hussein

Healthcare 2023, 11(4), 607; https://doi.org/10.3390/healthcare11040607 - 17 Feb 2023

Cited by 7 | Viewed by 2208

Abstract

There seem to currently be no therapeutic medications found for the severe coronavirus infection in 2019 (COVID-19). In light of this, it has been hypothesized that the immunomodulatory treatment known as tocilizumab can lessen the inflammatory response that occurs in the respiratory system, speed up the process of clinical benefit, lower the risk of death, and avert the need for ventilators. This randomized controlled trial (RCT) studied patients with a proven infection of SARS-CoV-2 and hyperinflammatory reactions. The inclusion criteria included fever (body temperature > 38 °C), pulmonary infiltrates, or supplemental oxygen. The patients received either conventional treatment with one dose of either tocilizumab (8 mg per kilogram of body weight) or conventional treatment only. The subjects were randomized to receive either treatment with a 1:1 ratio. A time-to-event test was conducted to determine the time to intubation or death. There was an insignificant difference between the investigated groups regarding the time to death, time to mechanical ventilation, and percentage of deaths. The conventional group’s median (IQR) hospital length of stay was 4 (3–6) days, whereas the tocilizumab therapy group was 7 (4.75–10) days. There was a substantial difference in the mechanical ventilation rates in both groups, which were 17 (34%) and 28 (56%), respectively. In hospitalized patients with severe illness and COVID-19, tocilizumab was ineffective in preventing intubation or death. Trials must be larger, however, in order to exclude the potential benefits or harms. Full article

(This article belongs to the Special Issue COVID-19 Resilience Networks for Pandemic Preparedness and Response Coordination)

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13 pages, 863 KiB

Open AccessArticle

Multipath Routing in Wireless Body Area Sensor Network for Healthcare Monitoring

by Shuja Akbar, Muhammad Mohsin Mehdi, M. Hasan Jamal, Imran Raza, Syed Asad Hussain, Jose Breñosa, Julio César Martínez Espinosa, Alina Eugenia Pascual Barrera and Imran Ashraf

Healthcare 2022, 10(11), 2297; https://doi.org/10.3390/healthcare10112297 - 17 Nov 2022

Cited by 3 | Viewed by 1659

Abstract

Mobility and low energy consumption are considered the main requirements for wireless body area sensor networks (WBASN) used in healthcare monitoring systems (HMS). In HMS, battery-powered sensor nodes with limited energy are used to obtain vital statistics about the body. Hence, energy-efficient schemes are desired to maintain long-term and steady connectivity of the sensor nodes. A sheer amount of energy is consumed in activities such as idle listening, excessive transmission and reception of control messages, packet collisions and retransmission of packets, and poor path selection, that may lead to more energy consumption. A combination of adaptive scheduling with an energy-efficient protocol can help select an appropriate path at a suitable time to minimize the control overhead, energy consumption, packet collision, and excessive idle listening. This paper proposes a region-based energy-efficient multipath routing (REMR) approach that divides the entire sensor network into clusters with preferably multiple candidates to represent each cluster. The cluster representatives (CRs) route packets through various clusters. For routing, the energy requirement of each route is considered, and the path with minimum energy requirements is selected. Similarly, end-to-end delay, higher throughput, and packet-delivery ratio are considered for packet routing. Full article

(This article belongs to the Special Issue COVID-19 Resilience Networks for Pandemic Preparedness and Response Coordination)

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16 pages, 2213 KiB

Open AccessArticle

Factors Influenced the Endoscopic Services Volume during the COVID-19 Pandemic at National Tertiary Referral Hospital in Indonesia: Dr. Cipto Mangunkusumo Hospital

by Chyntia Olivia Maurine Jasirwan, Amal C. Sjaaf, Anhari Achadi, Prastuti Soewondo, Roswin Rosnim Djaafar and Rino A. Gani

Healthcare 2022, 10(11), 2280; https://doi.org/10.3390/healthcare10112280 - 14 Nov 2022

Viewed by 1427

Abstract

The impact of the COVID-19 pandemic caused a decrease in healthcare services, the intervention of non-surgical procedures, and endoscopy. This study examined the volume of endoscopy at Dr. Cipto Mangukusumo Hospital, the highest referral hospital in Indonesia. A cross-sectional mixed method was used to assess the relationship between endoscopy volume, age, gender, number of COVID-19 cases, type of patient’s case, the origin of treatment, and the kind of endoscopic procedure before and during the pandemic. The secondary data were collected through the hospital’s Electronic Health Record (EHR) System and “Kawal COVID-19” Websites, while the primary data were collected through observation, document reviews, and in-depth online interviews with doctors at endoscopic units. This study period was divided into six intervals of three months, respectively, from January 2020 to September 2021, and 5030 endoscopic procedures were collected. The data were analyzed both quantitatively through the SPSS statistics and qualitatively. The quantitative data presented as descriptive and bivariate results in an Independent T-Test and a Chi-Square test. The results showed there was a significant difference (p = 0.004) in the volume of endoscopes before (the highest volume) and during the pandemic (the lowest volume during April–June 2020 period). The mean age of the patients was higher before the pandemic. There was a significant difference between patient admissions from outpatient and emergency procedures before and during the pandemic. There are changes in the flow of outpatient to do endoscopies which were different from the flow of emergency patients during the pandemic, which focused on the long waiting list for inward entry queues, the mandatory COVID-19 PCR swab, and the criteria of emergency cases for fast-track procedures, the reduced bed capacity, and the expired date of laboratory examinations. The decreased volume was also caused by the limitation of patient intervention by the doctors. However, the duration of the action procedure was accelerated without reducing its quality. Furthermore, there was a high wave of Delta Variant cases from May to July 2021. In addition, the factors of age, type of patient’s case, origin, and treatment showed significant differences before and during the COVID-19 pandemic. Finally, changes in the flow of services also influenced various impacts on endoscopy and service costs. Therefore, further study is required to calculate the unit costs. Full article

(This article belongs to the Special Issue COVID-19 Resilience Networks for Pandemic Preparedness and Response Coordination)

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11 pages, 884 KiB

Open AccessArticle

Translation, Adaptation and Validation of the Pandemic Fatigue Scale (PFS) in the Greek Language

by Evanthia Asimakopoulou, Panagiotis Paoullis, Antonio Shegani, Alexandros Argyriadis, Agathi Argyriadi, Evridiki Patelarou and Athina Patelarou

Healthcare 2022, 10(11), 2118; https://doi.org/10.3390/healthcare10112118 - 22 Oct 2022

Cited by 2 | Viewed by 1366

Abstract

The growing fatigue of citizens due to the COVID-19 pandemic has already been addressed and its results are visible and threatens citizen compliance. The aim of this study was to translate and validate the Pandemic Fatigue Scale (PFS) in the Greek language. A cross-sectional study was conducted between October 2021 to March 2022. The translation and cultural adaptation process was developed according to the research protocols among the university student population in Cyprus and tested the psychometric properties of PFS. Three hundred thirty-four subjects participated in the study through a web survey, which included general information and the study process. The internal consistency for the total PFS showed good reliability (six items, a = 0.88). A weak statistically significant positive correlation was found between the PFS and the Greek versions of Generalised Anxiety Disorder Assessment—GAD-7 (r = 0.1.96; p < 0.001) and the PFS and Patient Health Questionnaire—PHQ-9 (r = 0.173; p = 0.002) demonstrating good concurrent validity. Recovering from the pandemic, it is necessary to build systems to detect and respond to future healthcare crises. The results suggest that the psychometric properties of the Greek PFS are satisfactory. The measure of pandemic fatigue allows for identifying fatigue groups for targeted interventions and testing how pandemic fatigue might be reduced in such situations. Full article

(This article belongs to the Special Issue COVID-19 Resilience Networks for Pandemic Preparedness and Response Coordination)

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