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Thailand and Vietnam have done relatively well in terms of containing the COVID-19 pandemic. While hundreds of thousands of cases and thousands of deaths have been registered in Indonesia and the Philippines, Vietnam's number of cases was only 2550 (and only 35 deaths) and Thailand 26, 679 (85 deaths) by 15 March 2021. Nevertheless, it is also important to investigate to what extent weaker sections of society have been affected by the pandemic. As is widely known, the pandemic and lockdowns have led to dramatic socioeconomic upheavals. In this chapter attention is paid to relatively under-researched groups: farmers, fishers and their households. How have they fared amidst economic disruptions? Whereas the media has focused on the impact of lockdowns on urban areas, this chapter highlights livelihood challenges as experienced in rural areas based on 240 semi-structured interviews with farmers and fishers in southern Thailand and northern Vietnam conducted between July 2020 and February 2021. Results show that domestic trade in farm products and both domestic and international trade in seafood were battered by demand slumps, lockdowns and the collapse of the Thai tourism industry. Factors that co-determine the intensity of impacts are socioeconomic status, the crops farmers grow, the size of fishing vessels and numbers of boat crews, jobs and opportunities of relatives and age. This chapter contributes to debates on the nature of poverty reduction given concerns that the pandemic is currently undoing years of progress in middle-income countries and offers options for further empirical and policy-oriented research. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
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The era of the fourth industrial revolution and the Covid-19 pandemic gives rise to the incredible growth of the IoT (Internet of Things) field. The trend of an immense amount of devices connected to specific networks brings up various problems, but most noticeable, control and management issues. In this paper, we propose a structural and efficient solution to solve this problem in a large-scale IoT system - along with two implementations of the proposed solution. The paper's main contribution is to present an overview of the architecture for an IoT system inspired by numerous IoT-based implementations. The design is expected to be dynamic, transparent, and easily deployed for newcomers. Furthermore, with the different implementations in health care and agriculture mentioned later, we want to demonstrate the flexibility and adaptability of the design to various fields. © 2022 IEEE.
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One of the most contentious areas of research in Medical Image Preprocessing is 3D CT-scan. With the rapid spread of COVID-19, the function of CT-scan in properly and swiftly diagnosing the disease has become critical. It has a positive impact on infection prevention. There are many tasks to diagnose the illness through CT-scan images, include COVID-19. In this paper, we propose a method that using a Stacking Deep Neural Network to detect the Covid 19 through the series of 3D CT-scans images. In our method, we experiment with two backbones are DenseNet 121 and ResNet 101. This method achieves a competitive performance on some evaluation metrics. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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BACKGROUND: One strategy to aid patients in managing their diabetes is group visits (GVs) that include group education and individual medical visits with a provider. Though in-person GVs have been shown to benefit patients, few studies have evaluated virtual diabetes GVs. METHODS: In this single-arm trial, adult patients with A1c ≥ 8% from six community health centers were recruited to participate in monthly virtual GVs for 6 months. Patients completed surveys about diabetes self-care, support, distress, and the group visit concept before and after they participated in GVs. Health center staff trained to lead the GVs completed surveys pre and post virtual GVs. Linear mixed effects models were used to adjust cohort-based association and model the survey data over time for the time trend effect. RESULTS: Forty-five patients enrolled in the study and thirty-eight patients completed the baseline survey. The average age was 55 (range of 36-83) and 65% of enrollees were female. 63% were black/African American, 32% were white/Caucasian, and 8% were Hispanic/Latino. Thirty-four patients attended one or more GVs and twenty-one patients completed the post GV survey. Overall satisfaction with the virtual GVs was high with 18/20 (90%) of participants being very satisfied and 20/21 (95%) saying they would attend GVs in the future. Most participants agreed that GVs helped improve diabetes self-management skills (78%), motivated them to achieve health goals (89%), and introduced them to others living with diabetes (78%). Barriers to participation were the timing of the GVs and access to a computer, tablet, phone, and internet. Patients had an increase in their diabetes knowledge (mean (SD): 3.2/ 5 (0.9) to 3.6/5 (0.7), p= 0.02) and diabetes support (3.5/5 (0.64) to 4.1/5 (0.7), p <0.001) as well as decreased diabetes distress (2.9/6 (1.5) to 1.2/6 (0.5), p=0.03) from baseline to 6 months. Thirty-five staff enrolled in the study and seventeen completed a post GV survey. Most staff agreed that GVs provided patients with social support and more frequent contact with medical providers. Staff largely agreed that virtual GVs increased opportunity for teamwork and collaboration (94%), care coordination (82%), and understanding of patients (94%). However, only 5/17 (29%) and 3/17 (18%) staff members agreed that virtual GVs increased provider productivity or led to higher reimbursement, respectively. Staff cited other priorities at the health center, difficulty recruiting patients, and concerns about access to technology as the biggest barriers to implementing virtual GVs. CONCLUSIONS: Virtual GVs show promise as evidenced by high patient satisfaction and improvements in support, distress, and diabetes knowledge in patients. Staff also perceived virtual GV benefits to patients, staff, and health centers despite concerns about logistics such as productivity, reimbursement, and the health center's ability to continue visits virtually.
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BACKGROUND: Diabetes group visits (GVs) or shared medical appointments have been shown to improve clinical outcomes, but few have reported results from virtual diabetes GVs. No studies have evaluated virtual GVs among community health center patients across a region of the U.S. METHODS: Six health center sites across five states conducted six monthly virtual GVs with up to 12 adult patients with type 2 diabetes and suboptimal glycemic control (glycosylated hemoglobin (A1C) ≥8%). Virtual group visits consisted of six monthly 60 to 90 minute-long diabetes education sessions led by health center staff via a videoconferencing platform. GV patients enrolled at the site also had an appointment with their primary care physician within two weeks of each monthly virtual group visit. Primary outcome was change in patients' A1C from baseline to 6- months. Secondary outcomes were changes in patients' blood pressure, low density lipoproteins (LDL) and weight. Patients also completed surveys at baseline and 6-months describing their diabetes self-care behaviors and satisfaction with the virtual GVs. Generalized linear mixed models and linear mixed models were used to test the effects of GVs, time points and their interaction. RESULTS: Forty eight patients were enrolled (mean age 55 ± 12 years, 67% female, 63% black/African American, 32% white/Caucasian, and 8% Hispanic/Latino, 88% had public health insurance, mean baseline A1C of 9.84% ± 1.78%, 35% with A1c <9%). 34 patients completed one or more virtual GVs;14 patients attended no virtual group visits. At 6-months, average A1C was 8.96 ±1.82;A1C decreased by -0.56% ± 0.31 compared to baseline which was borderline significant (p=0.08). At 6-months, 58% of patients had an A1C < 9% which was borderline significantly decreased (p=0.055) compared to baseline. For patients with an A1C at baseline >9%, there was a significant decrease in A1C at 6 months (-1.06 ±0.45, p=0.03). There was no significant difference in blood pressure, LDL or weight from baseline to 6- months or association of number of visits attended and change in A1C. There were no significant changes in foot self-exams, blood sugar testing, nor exercise, but patients did report more days of healthy eating in the past week at 6-months compared to baseline (4.5 ±2.3 vs. 3.2 +2.7 days, p=0.02). Overall satisfaction with the virtual GVs was high with 90%of participants being very satisfied and 95% saying they would attend GVs in the future. CONCLUSIONS: Virtual GVs show high patient satisfaction and promise for improving A1C among patients with poor glycemic control who receive care in community health centers. Future studies are needed with a larger patient sample size and a control comparison group to determine which patients and health centers are best suited for virtual GVs.
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Mask mandate has been applied in many countries in the last two years as a simple but effective way to limit the Covid-19 transmission. Besides the guidance from authorities regarding mask use in public, numerous vision-based approaches have been developed to aid with the monitoring of face mask wearing. Despite promising results have been obtained, several challenges in vision-based masked face detection still remain, primarily due to the insufficient of a quality dataset covering adequate variations in lighting conditions, object scales, mask types, or occlusion levels. In this paper, we investigate the effectiveness of a lightweight masked face detection system under different lighting conditions and the possibility of enhancing its performance with the employment of an image enhancement algorithm and an illumination awareness classifier. A dataset of human subjects with and without face masks in different lighting conditions is first introduced. An illumination awareness classifier is then trained on the collected dataset, the labeling of which is processed automatically based on the difference in detection accuracy when an image enhancement algorithm is taken into account. Experimental results have shown that the combination of the masked face detection system with the illumination awareness and an image enhancement algorithm can boost the system performance to up to 8.6%, 7.4%, and 8.5% in terms of Accuracy, F1-score, and AP-M, respectively. © 2022 IEEE.
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In the wake of the SARS-CoV-2 pandemic, inactivating bioaerosols became a pivotal issue which helps to prevent the transmittance of SARS-CoV-2. Thus, the current study was conducted to investigate a potential inactivating method using both ozone (O-3) and ultraviolet C (UVC). Individual and integrated effects of O-3 and UVC were compared. A solution containing approximately 4 similar to 7.3 x 10(6) CFU/mL of Salmonella typhimurium bacteria was used to produce bacteria droplets. These droplets were exposed to O-3 and UVC to determine the reduction rate of bacteria. The exposure times were set as 1 and 30 minutes. Ozone concentrations were 100 and 200 ppmv. UVC-LEDs were used as a UVC source. Peak wavelength of the UVC-LED was 275 nm and the irradiation dose was 0.77 mW/cm(2). In terms of O-3 and UVC-LED interaction, 194 ppmv styrene was used as a target compound to be removed. Considering the O-3 and UVC-LED interaction, the presence of O-3 could reduce the performance of the UVC-LED, and UVC-LED could also reduce significant amount of O-3. The sequence of O-3 and UVC-LED treatment was as follows: O-3 was exposed at first, then UVC-LED, and this order showed the best reduction ratio ( > 99.9%). Therefore, if O-3 and UVC-LED is used to disinfect Salmonella typhimurium bacteria contained in droplets, bacteria should be separately exposed to O-3 and UVC-LED in order to improve the inactivation efficiency.
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The COVID-19 pandemic has fueled attention towards strategic decisions on business value, crisis responses, and social aspects. Correspondingly, there is an urgent need for identifying relevant key performance indicators (KPIs) to support the decision-making process and survive from exogenous shocks. The paper focuses on the cultural sector, one of the social and economic sectors that has faced severe disruption by the pandemic. The objective of this study is to conduct a literature review on KPIs, especially for organizations in the cultural sector, with relevance to massive data and crisis response. The research results indicate the novel balanced scorecard covering the perspectives of finance, customers, web, social media, and crisis responses for crisis-ready organizations. The importance and originality of this study are that it updates the traditional balanced scorecard with KPIs in the era of digitalization to remain agile and resilient in the pandemic. © AMCIS 2021.
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COVID-19 mitigation measures (e.g., stay-at-home orders and public mask mandate) and fundamental public health interventions (e.g., case investigations and contact tracing with prompt isolation or quarantine) are primary approaches to preventing and controlling SARS-CoV-2 community transmission. State-mandated stay-at-home orders and public mask mandates coupled with case investigations with contact tracing contributed to an 82% reduction in COVID-19 incidence, 88% reduction in hospitalizations, and 100% reduction in mortality in Delaware during late April-June. The combination of state-mandated community mitigation efforts and routine public health interventions can reduce the occurrence of new COVID-19 cases, hospitalizations, and deaths.
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AIMS & OBJECTIVES: Surgical masks are broadly used as personal protective equipment in a pandemic setting, but little is known regarding decontamination interventions to allow for their reuse. This systematic review sought to evaluate and synthesize data from original research evaluating interventions to decontaminate surgical masks. METHODS: The protocol was registered on PROSPERO (CRD42020178290). We searched MEDLINE, Embase, CENTRAL, Global Health, the WHO COVID-19 database, Google Scholar, DisasterLit, and preprint servers from inception to April 8, 2020. Citation screening was conducted independently in duplicate. Outcomes of interest included mask performance (i.e. filtration efficiency, airflow resistance) and germicidal effects following decontamination. RESULTS: Of 1874 unique citations, 33 full-texts were assessed of which 7 studies were included. One study evaluated mask performance with interventions applied after mask use: dry heat (via rice cooker), autoclave, and three chemical agents (70% ethanol, 100% isopropanol, and 0.5% sodium hypochlorite). Six studies evaluated interventions applied prior to mask use to enhance antimicrobial properties and/or mask performance: nanoparticle emulsions, quaternary ammonium agent, N-halamine, salt film, and a fluorochemical repellent. Heterogeneity of interventions evaluated and outcomes assessed precluded quantitative analysis. Mask performance was best preserved with dry heat decontamination. Good germicidal effects were observed in salt-, N-halamine-, and nanoparticle-coated masks. Safety outcomes were infrequently evaluated. CONCLUSIONS: Limited evidence exists on the safety or efficacy of surgical mask decontamination interventions. Studies to date have evaluated interventions and outcomes using heterogenous and non-standardized test conditions, limiting our ability to compare between interventions or draw conclusions on the most efficacious intervention.
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BACKGROUND: In pandemics such as COVID-19, shortages of personal protective equipment are common. One solution may be to decontaminate equipment such as facemasks for reuse. AIM: To collect and synthesize existing information on decontamination of N95 filtering facepiece respirators (FFRs) using microwave and heat-based treatments, with special attention to impacts on mask function (aerosol penetration, airflow resistance), fit, and physical traits. METHODS: A systematic review (PROSPERO CRD42020177036) of literature available from Medline, Embase, Global Health, and other sources was conducted. Records were screened independently by two reviewers, and data was extracted from studies that reported on effects of microwave- or heat-based decontamination on N95 FFR performance, fit, physical traits, and/or reductions in microbial load. FINDINGS: Thirteen studies were included that used dry/moist microwave irradiation, heat, or autoclaving. All treatment types reduced pathogen load by a log10 reduction factor of at least three when applied for sufficient duration (>30 s microwave, >60 min dry heat), with most studies assessing viral pathogens. Mask function (aerosol penetration <5% and airflow resistance <25 mmH2O) was preserved after all treatments except autoclaving. Fit was maintained for most N95 models, though all treatment types caused observable physical damage to at least one model. CONCLUSIONS: Microwave irradiation and heat may be safe and effective viral decontamination options for N95 FFR reuse during critical shortages. The evidence does not support autoclaving or high-heat (>90°C) approaches. Physical degradation may be an issue for certain mask models, and more real-world evidence on fit is needed.
Subject(s)
Coronavirus Infections/prevention & control , Decontamination/standards , Equipment Reuse/standards , Guidelines as Topic , Hot Temperature , Respiratory Protective Devices/virology , Ultraviolet Rays , HumansABSTRACT
In less than three months after its emergence in China, the Covid-19 pandemic has spread to at least 180 countries. In the absence of previous experience with this new disease, public health authorities have implemented many experiments in a short period and, in a mostly uninformed way, various combinations of interventions at different scales. These include a ban on large gatherings, closure of borders - individual and collective containment, monitoring of population movements, social tracing, social distancing, etc. However, as the pandemic is progressing, data are collected from various sources. On the one hand, authorities allow to make informed adjustments to the current and planned interventions and reveal them. On the other hand, an urgent need for tools and methodologies that enable fast analysis, understanding, comparison, and forecasting of the effectiveness of the responses against COVID-19 across different communities and contexts. In this perspective, computational modeling appears as invaluable leverage as it allows us to explore in silico a range of intervention strategies before the potential phase of field implementation. © 2020 IEEE.
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BACKGROUND: The high demand for personal protective equipment during the novel coronavirus outbreak has prompted the need to develop strategies to conserve supply. Little is known regarding decontamination interventions to allow for surgical mask reuse. AIM: To identify and synthesize data from original research evaluating interventions to decontaminate surgical masks for the purpose of reuse. METHODS: MEDLINE, Embase, CENTRAL, Global Health, the WHO COVID-19 database, Google Scholar, DisasterLit, preprint servers, and prominent journals from inception to April 8th, 2020, were searched for prospective original research on decontamination interventions for surgical masks. Citation screening was conducted independently in duplicate. Study characteristics, interventions, and outcomes were extracted from included studies by two independent reviewers. Outcomes of interest included impact of decontamination interventions on surgical mask performance and germicidal effects. FINDINGS: Seven studies met eligibility criteria: one evaluated the effects of heat and chemical interventions applied after mask use on mask performance, and six evaluated interventions applied prior to mask use to enhance antimicrobial properties and/or mask performance. Mask performance and germicidal effects were evaluated with heterogeneous test conditions. Safety outcomes were infrequently evaluated. Mask performance was best preserved with dry heat decontamination. Good germicidal effects were observed in salt-, N-halamine-, and nanoparticle-coated masks. CONCLUSION: There is limited evidence on the safety or efficacy of surgical mask decontamination. Given the heterogeneous methods used in studies to date, we are unable to draw conclusions on the most efficacious and safe intervention for decontaminating surgical masks.