ABSTRACT
The paper contributes to the scarce literature on the negative effect of coronavirus 2019-induced income and food price shocks on household economic access to food, focusing on Malawi during the first two pandemic waves and using a country representative sample. We find that household income reduction, as explained by income source shocks and health mitigation measures, has a wave-specific and persistent effect on ordinal categories of food security perception. Our evidence supports the implementation and monthly scaling-up of nutrition-sensitive social protection programmes and health measures at the household level to address these adverse effects. © 2022 The Author(s). Published by Oxford University Press on behalf of the Foundation for the European Review of Agricultural Economics. All rights reserved.
ABSTRACT
The paper contributes to the scarce literature on the negative effect of coronavirus 2019-induced income and food price shocks on household economic access to food, focusing on Malawi during the first two pandemic waves and using a country representative sample. We find that household income reduction, as explained by income source shocks and health mitigation measures, has a wave-specific and persistent effect on ordinal categories of food security perception. Our evidence supports the implementation and monthly scaling-up of nutrition-sensitive social protection programmes and health measures at the household level to address these adverse effects.
ABSTRACT
During the pandemic of Corona-virus Disease 2019 (COVID-19), the whole world was confronted by a particularly high death toll and infection rate. Research has shown that air pollution plays a considerable part in the spread of certain illnesses and diseases. In the case of the COVID-19 pandemic, research has shown that increased air pollution has a negative effect on people's well-being and plays a role in the quick spread of the disease. Air pollution by itself affects the respiratory system of individuals which is aggravated, in addition, by a COVID19 infection. Some efforts have been made to use emerging technologies to combat the virus and its subsequent aerosol aspects to reduce transmission. In this context, we present an IoT system for Air Quality (AQ) monitoring and prediction using deep learning for data analysis and Augmented Reality (AR) for data visualization. The proposed system shows great potential for using Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) units as a framework for leveraging knowledge from time-series data of AQ. Moreover, integrating AR visualization for the proposed IoT system enables intuitive interaction between users and IoT devices and further improves visualization of AQ data which effectively contributes to easily conducting a deeper analysis of data and makes faster decisions. © 2021 IEEE.
ABSTRACT
The Internet of Things (IoT) is characterized by heterogeneous technologies, which contribute to the provision of innovative services in various fields of application. Among these applications, we find the field of e-Health which provides a huge amount of data that served the health of patients remotely and in real time but also medical records, health monitoring and emergency response. e-Health systems require low latency and delay which is not guaranteed since data are transferred to the cloud and then back to the application, which can seriously affect performance. Also, COVID-19 pandemic has accelerated the need of remote monitoring of patients to reduce chances of infection among physicians and healthcare workers. To this end, Fog computing has emerged, where cloud computing is extended to the edge of the network to reduce latency and network congestion. This large amount of data is downloaded and stored on remote public cloud servers to which users cannot be fully trusted, especially when we are dealing with sensitive data like health data. In this scenario, meeting the confidentiality and patient privacy requirements becomes urgent for a large deployment of cloud systems. In this context, we offer a solution to secure the personal data of the e-Health system and protect the privacy of patients in an IoT–Fog–cloud environment while being based on cryptographic techniques especially CP-ABE and the blockchain paradigm. The results obtained are satisfactory, which allowed us to deduce that the solutions are protected against the most known attacks in IoT–Fog–cloud systems. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
INTRODUCTION: Imaging is essential for the initial diagnosis and monitoring of the novel coronavirus, which emerged in Wuhan, China. This study aims to assess the insight of radiographers on how the COVID-19 pandemic has affected their work routine and if protective measures are applied. METHOD: A prospective observational study was conducted among radiographers registered in the Cyprus Society of Registered Radiologic Technologists & Radiation Therapy Technologists. A questionnaire composed of 28 multiple choice questions was utilised, and the data analysis was performed using SPSS software with the statistical significance assumed as p-value < 0.05. RESULTS: Out of 350 registered radiographers, 101 responses were received. The results showed that there are statistically significant differences regarding the working hours, the feeling of stress, the work effectiveness, the average examination time, the presence of a protocol used among the different workplaces of the participants; a private radiology centre, a private hospital or a public hospital, with a p-value 0.0022, 0.015, 0.027, 0.001, 0.0001 respectively. Also, statistically significant differences were observed in the decontamination methods used for equipment (p-value 0.007), for air (p-value 0.04) and when decontamination takes place (p-value 0.00032) among the different workplaces of the participants. Nonetheless, the majority of radiographers believe that their workplace is sufficiently provided with PPE, cleaning supplies, equipment, and with cleaning personnel and are optimistic regarding the adequacy of these provisions in the next three months. CONCLUSION: This study showed that in the Republic of Cyprus, there are protocols regarding protective measures against COVID-19, and the radiographers are adequately trained on how to face an infectious disease outbreak. However, work is needed in order to develop protocols that reassure the safety of patients and medical personnel while managing the excess workload effectively. IMPLICATIONS FOR PRACTICE: This study indicates the importance of applying protective measures and protocols in the radiology departments in order to minimise the spread of the virus.