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1.
3rd International Conference on Recent Trends in Advanced Computing - Artificial Intelligence and Technologies, ICRTAC-AIT 2020 ; 806:353-362, 2022.
Article in English | Scopus | ID: covidwho-1626827

ABSTRACT

With the rise of the novel coronavirus pandemic, there has emerged an eminent need for social distancing to flatten the curve of the infected. The world needs to breathe in some time to develop vaccines to fight COVID-19, and time can only be bought through the currency of social distancing. We venture to find a better way to allude coronavirus in disaster struck areas by making use of near sound frequency data transmission (NSDT) along with peer-to-peer (P2P) networking, which would immediately recognize a person at risk in our proximity, hence providing an optimal solution for following social distancing norms and also carry out disaster mitigation. P2P networking and data communication through NSDT technology along with the usage of Aarogya Setu App API is explored to obtain and transmit crucial data and two use case mitigation scenarios were proposed in this work. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

2.
European Journal of Public Health ; 31:2, 2021.
Article in English | Web of Science | ID: covidwho-1609794
3.
Journal of Cystic Fibrosis ; 20:S66, 2021.
Article in English | EMBASE | ID: covidwho-1368827

ABSTRACT

Objectives: The aim of this study was to examine the impact of COVID-19 pandemic on 1) the psychological health of children with cystic fibrosis (CWCF) and their parents and 2) education of CWCF. Methods: A cross-sectional online survey was conducted via SmartSurvey UK for a period of six-to-eight weeks in September/October 2020. The survey was hosted and advertised by CF Ireland via social media platforms (Twitter, Facebook, Instagram, and WhatsApp). Results: 123 parents of CWCF responded. Increasing prevalence of issues related to mental health of CWCF was noted with increasing age. The psychological issues in children during the pandemic were mainly stress (33.3%) and anxiety (25.6%). Communicating with loved ones (18.8%) followed by gardening (11.5%) and watching TV (10.4%) were preferred by most parents and children to manage stress. Parents of children >5 years were 2.7 times more willing to send their children to creche/playgroup/school as compared to those with children aged <5 years (Odds Ratio: 2.663;p value = 0.030). One in ten (11%) parents of CWCF aged <5 years showed signs of depression or distress. Many parents of CWCF?>5 years did not feel peaceful (31.8%) and felt tired (52.4%). Overall, more fathers felt happy (52.6%), peaceful (47.4%) and energetic (57.9, p value = 0.023), and more mothers felt tired (57%). Looking at comparisons by parental age, parents <45 years were more nervous (45.7% vs 20.5%;p value = 0.008) and tired compared to older parents (63.7% vs 41.0%;p value = 0.019). Overall, working parents were relatively happier (53.4% vs 47.4% p value = 0.514), and more energetic (41.4% vs 29.8%;p value = 0.196) compared to parents who were not working. Conclusion: The pandemic has an important effect on mental health through fear and isolation. Increased anxiety and levels of stress were the key mental issues faced by CWCF. Parents of children aged over 5 years were more willing to send their children to school. Younger parents were more likely to feel nervous and tired.

4.
Journal of Cystic Fibrosis ; 20:S66, 2021.
Article in English | EMBASE | ID: covidwho-1361555

ABSTRACT

Objectives: The aim of this study is to examine cocooning rates of persons with cystic fibrosis (PWCF) during the COVID-19 pandemic working from home and employer attitudes. Methods: A cross-sectional survey jointly developed by University College Dublin and Cystic Fibrosis Ireland (CFI) research teams was made available to complete using SmartSurvey UK. The survey was advertised widely by CFI via social media (Twitter, Instagram, Facebook), the CFI website and through CFI PWCF WhatsApp groups. Results: Approximately half (50.8%) of PWCF cocooned. Most participants spent their day while cocooning performing exercises, doing household chores, and watching TV. Most of the participants ordered groceries/medications online, whereas smaller numbers had them delivered by family or friends. Amongst the participants who worked (46.2%), 87.2% (n = 48) worked from home during the pandemic. More PWCF aged <35 years (9.6%) worked onsite as compared those 35 years or over (1.9%). 95% employers were sympathetic for the participants who cocooned while working from home. However, approximately one-third of the employers were considered unsympathetic to PWCF who were not working due to cocooning. Employers were equally sympathetic to females and males and to younger and older PWCF. Majority of participants had access to excellent quality of internet service during pandemic, but this differed by urban/rural divide. Conclusion: Some PWCF faced challenges in relation to work while cocooning due to the pandemic risk. While Ireland provided pandemic unemployment payment assistance to those who lost jobs, this did not fully compensate most people. The urban/rural difference noted reflects national broadband rollout delays. Delivery of essentials at home and working from home can be effective ways to mitigate risks and therefore more provisions should be made in this regard for PWCF.

5.
Journal of Cystic Fibrosis ; 20:S65, 2021.
Article in English | EMBASE | ID: covidwho-1361554

ABSTRACT

Objectives: The aim of this study is to examine the impact of the COVID-19 lockdown on hospital services and specialist care of adults with cystic fibrosis (PWCF) in Ireland. Methods: A cross-sectional survey was undertaken. The consent and questionnaire were hosted on SmartSurveyUK. The survey was advertised widely by Cystic Fibrosis Ireland to the CF community via CF website, Twitter, Instagram, Facebook and through WhatsApp groups during September/October 2020. Results: 118 PWCF responded and 56 (47.5%) indicated a deferral of hospital visits for CF care. The period of delay ranged from 1 to 6 months, with 57.4% to three months and 42.6% to over 6 months. Key reasons for deferral amongst those who deferred (n = 56) were fear of infection from coronavirus (69.8%) and hospital unit closed (11.5%). Amongst PWCF who deferred, deferrals impacted rehabilitation therapies (n = 25%), medical care at hospital (n = 65.6%), surgery (n = 6.3%), and appointment with GP (n = 34.4%). More respondents aged 35 and over had to cancel/postpone diagnostic tests compared to those <35 years (64% vs 36%: NS). Non-significantly greater proportions of females postponed therapy and tests. Online consultation was new for more than half of the participants (51.7%) and the majority (88.8%) found it useful. Little over half of the participants (53%) had access to prescription via email and majority of those who used (98.4%) found it useful. Conclusion: The COVID-19 pandemic has impacted many PWCF in terms of access to tests and specialist care. Time will tell how this will impact on future hospital admissions and survival. Online consultation and emailed prescriptions were both positively received by many. Prescription renewal via email is certainly a consideration to be continued post-pandemic.

6.
Studies in Systems, Decision and Control ; 322:95-110, 2021.
Article in English | Scopus | ID: covidwho-1144276

ABSTRACT

COVID19 pandemic is playing havoc all around the world. Though the world is fighting this invisible enemy it has succumbed to the devastating potential of the Coronavirus. Largest of world economies and developed nations have been exposed and their health infrastructure has collapsed during this testing time. It is assessed and predicted that the novel coronavirus which is responsible for COVID19 pandemic, may turn into an endemic (just like HIV) and will never go away. It will become part and parcel of our life and humans have to learn to live with it even if the vaccine is developed. The government’s world over is concerned with containment and eradication of this virus at the earliest and massive efforts are on at all front to contain it’s spread. As of now (3rd week of May 2020), more than 4.4 million cases of the disease have been recorded worldwide and more than 300,000 have died. The world has also seen technological innovation during this time and mechanisms to tackle COVID19 patients. Innovations in carrying out quick testing using Rapid testing kits, Artificial Intelligence (AI) powered thermal scanning for temperature monitoring in the crowd, AI-enabled contact tracing, Mobile Apps, low-cost ventilators, and many other such similar solutions. All these pertain to checking for COVID19 symptoms and taking actions thereafter, but what about the stress, pain, and shock of a person who has been put under quarantine in a facility meant for the purpose or the person who is Corona positive? In this chapter, the authors have discussed briefly the pandemic and tried to provide a solution for the mental wellbeing of such people who are under quarantine and are isolated but heavily stressed or showing stress symptoms, by creating a VisualBOT which could understand the facial expression of the person and judge his mood, for providing suitable counseling and help. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

7.
Studies in Computational Intelligence ; 912:83-98, 2021.
Article in English | Scopus | ID: covidwho-829036

ABSTRACT

Medical data can be mined for effective decision making in spread of disease analysis. Globally, Coronavirus (COVID-19) has recently caused highly rated cause of mortality which is a serious threat as the number of coronavirus cases are increasing worldwide. Currently, the techniques of machine learning and predictive analytics has proven importance in data analysis. Predictive analytics techniques can give effective solutions for healthcare related problems and predict the significant information automatically using machine learning models to get knowledge about Covid-19 spread and its trends also. In a nutshell, this chapter aims to discuss upon the latest happenings in the technology front to tackle coronavirus and predict the spread of coronavirus in various cities of Saudi Arabia from purely a dataset perspective, outlines methodologies such as Naïve Bayes and Support vector machine approaches. Also, the chapter briefly covers the performance of the prediction models and provide the prediction results in order to better understand the confirmed, recovered and the mortality cases from COVID-19 infection in KSA regions. It also discusses and highlights the necessity for a Sustainable Healthcare Approach in tackling future pandemics and diseases. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

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