Binary Classification of COVID-19 CT Images Using CNN

COVID-19 pandemic has hit the world with such a force that the world's leading economies are finding it challenging to come out of it. Countries with the best medical facilities are even cannot handle the increasing number of cases and fatalities. This disease causes significant damage to the lungs and respiratory system of humans, leading to their death. Computed tomography (CT) images of the respiratory system are analyzed in the proposed work to classify the infected people with non-infected people. Deep learning binary classification algorithms have been applied, which have shown an accuracy of 86.9% on 746 CT images of chest having COVID-19 related symptoms.

How community medical facilities can promote resilient community constructions under the background of pandemics

Nowadays, urban and community resilience have become the core issues of urban theoretical research and construction practices. While there are many studies on climate change, natural hazards and environmental pollution, relatively less attention has been paid to public and human health. However, the current COVID-19 pandemic, which is a major global public health crisis, is posing severe challenges to the resilience of cities and communities in the context of high-mobility, high-density and high-intensity, as well as expands the connotation of community resilience to public health. To compensate for the lack of current research, this study examined the characteristics of community medical facilities in response to pandemics at urban, community and individual multi-spatial scales based on a thorough review of current research and relevant practice. It also emphasized the significant role played by community medical facilities in improving resilient community constructions in the face of large-scale public health emergencies. These characteristics were fully utilized to explore ways to build and govern the ‘resilience' of communities in the future, help people to survive better as well as develop in complex and changeable external environments.

Country-specific optimization strategy for testing through contact tracing can help maintain a low reproduction number ($$R_{0}$$) during unlock

In response to the COVID19 pandemic, many countries have implemented lockdowns in multiple phases to ensure social distancing and quarantining of the infected subjects. Subsequent unlocks to reopen the economies started next waves of infection and imposed an extra burden on quarantine to keep the reproduction number ($$R_{0}$$ R 0 ) < 1. However, most countries could not effectively contain the infection spread, suggesting identification of the potential sources weakening the effect of lockdowns could help design better informed lockdown-unlock cycles in the future. Here, through building quantitative epidemic models and analyzing the metadata of 50 countries from across the continents we first found that the estimated value of $$R_{0}$$ R 0 , adjusted w.r.t the distribution of medical facilities and virus clades correlates strongly with the testing rates in a country. Since the testing capacity of a country is limited by its medical resources, we investigated if a cost–benefit trade-off can be designed connecting testing rate and extent of unlocking. We present a strategy to optimize this trade-off in a country specific manner by providing a quantitative estimate of testing and quarantine rates required to allow different extents of unlocks while aiming to maintain $$R_{0} < 1$$ R 0 < 1 . We further show that a small fraction of superspreaders can dramatically increase the number of infected individuals even during strict lockdowns by strengthening the positive feedback loop driving infection spread. Harnessing the benefit of optimized country-specific testing rates would critically require minimizing the movement of these superspreaders via strict social distancing norms, such that the positive feedback driven switch-like exponential spread phase of infection can be avoided/delayed.

The use of Big Data Analytics in healthcare

The introduction of Big Data Analytics (BDA) in healthcare will allow to use new technologies both in treatment of patients and health management. The paper aims at analyzing the possibilities of using Big Data Analytics in healthcare. The research is based on a critical analysis of the literature, as well as the presentation of selected results of direct research on the use of Big Data Analytics in medical facilities. The direct research was carried out based on research questionnaire and conducted on a sample of 217 medical facilities in Poland. Literature studies have shown that the use of Big Data Analytics can bring many benefits to medical facilities, while direct research has shown that medical facilities in Poland are moving towards data-based healthcare because they use structured and unstructured data, reach for analytics in the administrative, business and clinical area. The research positively confirmed that medical facilities are working on both structural data and unstructured data. The following kinds and sources of data can be distinguished: from databases, transaction data, unstructured content of emails and documents, data from devices and sensors. However, the use of data from social media is lower as in their activity they reach for analytics, not only in the administrative and business but also in the clinical area. It clearly shows that the decisions made in medical facilities are highly data-driven. The results of the study confirm what has been analyzed in the literature that medical facilities are moving towards data-based healthcare, together with its benefits.

Attenuating pandemic supply shocks with 3D printed emergency use equipment

The fast-moving COVID-19 pandemic stressed supply chains even for some of the best prepared medical facilities. As a result, producing on-demand personal protective equipment (PPE) using additive manufacturing (AM) capabilities (3D-printing) emerged as a common strategy. While layer-by-layer processing confers several advantages to AM, it also imposes prohibitive print times, particularly for large volume parts. This leads to potential for using AM to rapidly produce smaller adaptors that modify available components for addressing critical shortages in emergencies. We applied this principle in developing a quick, simple, and low-cost adaptation of elastomeric half-mask respirators for emergency use in high-risk clinical settings. As we move toward reopening society, we must proactively build stronger bridges between engineering and medicine to respond to critical shortages in PPE ensuing from a potential second wave.

Telehealth System for Effective Treatment in COVID-19 Pandemics

The current coronavirus disease 2019 (COVID-19) pandemic has placed tremendous pressure on the worldwide healthcare systems. The hospitals are instructing patients to quarantine and providing medical facilities to COVID-19 patients at their homes. The feedback and proper monitoring of the quarantined patients is very important for the healthcare system. This situation has forced the use of telehealth systems to offer the delivery of medical facilities over a distance. This chapter presents a wireless telehealth system to monitor the home quarantined COVID-19 patients effectively. When an abnormality is detected then an alert is sent to the concerned hospital or doctor. The presented system allows setting the thresholds and providing alerts, reminders, and notifications to the doctors. The prototype of the presented system has been successfully developed, implemented, and tested, which helps the medical staff to monitor and treat the patients remotely, especially the coronavirus patients who are home quarantined.

Diversity and Equity in Healthcare

Overcoming diversity and equity challenges in healthcare is no small feat for healthcare facilities, professionals, and the healthcare industry at large. This chapter will bring awareness to healthcare disparities that transpire because of the lack of equity which can occur when diversity is finite. It will identify and explore how diversity and equity have been omitted from medical facilities and look at the impact of the presence of diversity and equity on both consumers and medical personnel. In addition, it will uncover factors that contribute to negative outcomes at the virtual level and uncover ways to reduce inefficiencies and negative outcomes caused by the lack of diversity and equity in healthcare.

Innovation in Sustainability of Tourism After the COVID-19 Pandemic

The tourism industry includes air, sea, and land transportation; food supply chain; accommodation; entertainment; recreation; etc. services. Hence, tourism businesses are proposing changes, and post-COVID tourists will not be the same as pre-COVID ones. Innovative solutions regarding safety and hygiene measures as well as the proximity of medical facilities will be of key importance in meeting the tourist expectations and sustainability of the tourism industry. In addition, it is possible to state that the COVID-19 pandemic has affected the whole world. This situation caused the economic balances of countries to deteriorate and some sectors to be adversely affected. The most affected sector is undoubtedly the tourism industry. Innovation has gained more importance in the tourism industry in the context of sustainability of tourism with the COVID-19 pandemic process. In this context, this chapter aimed to examine how innovation can contribute to the sustainability of post-COVID tourism.

Health Monitoring System Using IoT

Health on of the key aspects of any human’s life and one needs to keep up good health to make progress in life. We see most of the people facing health issues during different times during their life and it is their first job as an individual to keep up their health. As weare already seeing the novel coronavirus has devastated the world for the past few months and continues to do so. We see many cases like people living in distant villages and towns where there are no proper medical facilities to have a health check-up once in a while, they need to travel long distances to get a basic health checkup done. Especially the old people who cannot travel much due to their age. A human's health can be carefully monitored and a reasonable outcome can be predicted to avoid unfortunate deaths or misfortunate occurrences by measuring temperature, sp02, or pulse and Strain upon the muscles. These factors are being collected by various devices, but have never been classified and carefully monitored for anomalies. So this system is the best option to counter the situation as it collects data and stores it in the webserver and also gives alerts. Keywords: Health, Sensors, Internet of things

Change in Quality of Tuberculosis (TB) Care since National Quality Assessment Program of TB Healthcare Service

Purpose: This study aims to examine the quality of tuberculosis (TB) care after the 1^st to 3^rd national quality assessment (QA) program for TB healthcare service in Korea was conducted.Methods: We analyzed Health Insurance Review & Assessment Service (HIRA) claims data of new TB patients during the period of January to June from 2018-2020. The new TB patients were defined as TB patients reported to Korea Centers for Disease Control and Prevention Agency (KCDA). The unit of analysis was the patient. Chi-square tests were used to analyze the differences in indicator value according to the types of medical facilities. The QA indicators of TB care were divided into 3 areas consisting of the following 7 quality indicators: 4 indicators of diagnosis test (the rate of acid-fast bacilli smear, the rate of acid-fast bacilli culture, the rate of Mycobacterium tuberculosis-polymerase chain reaction, drug susceptibility test), 1 compliance of treatment guideline, and 2 indicators of care management of TB patients (encounter rate, day of therapy).Results: The QA program for TB care was conducted among 8,246 patients from 534 facilities in 2020. The value of the 7 quality indicators was shown to increase as a result of the QA program. The indicators of the diagnostic test were all higher than 95%, with the exception of the drug susceptibility test which was 84.8%. Both indicators for care management of TB patients were 88.5%.Conclusion: The quality of TB care has been improving with the implementation of the QA program. In order to continue to improve the quality of TB care, it will be necessary to disclose the results of the QA program in medical facilities in the future.