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In order to analyze the impact of COVID-19 prevention and control measures on the hotspots of residential burglary, the data of crimes that occurred during the First Level Response period of Major Public Health Emergencies in Beijing in 2020 and the same period in 2019 were collected, and the changes of hotspots during the two periods were compared by using kernel density estimation and predictive accuracy index. Consequently, the environmental features such as street network, point of interest (POI) diversity, crime locations, and repeat victimization in significantly varied hotspot areas were investigated. The results show that: 1) After the outbreak of the pandemic, the occurrence of residential burglary in the core urban areas of Beijing dropped significantly, and daily occurrence of crimes during the First Level Response period in 2020 decreased by 66.8% compared with the same days in 2019. 2) The eight major hotspots that existed in 2019 apparently declined during the corresponding days in 2020, five of them basically disappeared, and three hotspots weakened. 3) The declined hotspots were generally clustered around traffic hubs, areas with high diversity of POIs, clustered crimes, and repeat victimizations. 4) Home isolation and social restriction strategies implemented during the First Level Response period reduced the opportunities of offenders, and the real-name inspection adopted in public places increased the exposure risk of offenders, which are the main reasons for the hotspots decline during the pandemic. This work has some implications for crime prevention and police resources optimization during the pandemic. © 2023, Editorial office of PROGRESS IN GEOGRAPHY. All rights reserved.
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Objective:To explore the differences in laboratory indicators test results of coronavirus disease 2019 (COVID-19) and influenza A and to establish a differential diagnosis model for the two diseases, and to clarify the clinical significance of the model for distinguishing the two diseases. Methods :A total of 56 common COVID-19 patients and 54 influenza A patients were enrolled , and 24 common COVID-19 patients and 30 influenza A patients were used for model validation. The average values of the laboratory indicators of the patients 5 d after admission were calculated,and the elastic network model and the stepwise Logistic regression model were used to screen the indicators for identifying COVID-19 and influenza A. Elastic network models were used for the first round of selection,in which the optimal cutoff of lambda was chosen by performing 10-fold cross validations. With different random seeds,the elastic net models were fit for 200 times to select the high-frequency indexes ( frequency>90% ). A Logistic regression model with AIC as the selection criterions was used in the second round of screening uses;a nomogram was used to represent the final model;an independent data were used as an external validation set,and the area under the curve (AUC) of the validation set were calculate to evaluate the predictive the performance of the model. Results:After the first round of screening, 16 laboratory indicators were selected as the high-frequency indicators. After the second round of screening,albumin/ globulin (A/G),total bilirubin (TBIL) and erythrocyte volume (HCT) were identified as the final indicators. The model had good predictive performance , and the AUC of the verification set was 0. 844 (95% CI:0. 747-0. 941). Conclusion:A differential diagnosis model for COVID-19 and influenza A based on laboratory indicators is successfully established,and it will help clinical and timely diagnosis of both diseases.Copyright © 2022 Jilin University Press. All rights reserved.
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Background: This study aims to evaluate the mental health status of children, adolescents and their parents during the first year of COVID-19 pandemic in Belgium. Method(s): Analysis compared results before and during the second national lockdown, which started on November 2nd 2020. A cross-sectional online survey was conducted between May 2020 and April 2021. Result(s): Two hundred and eighteen adults and 273 children fully completed the survey. Almost one in five children (17.9%) presented moderate-to-severe scores of depression. Adolescents presented a higher level of depression than children (p = 0.007). The rate of moderate-to-severe depression scores (10.8% to 21%, p = 0.007) and internalized symptoms increased during the second lockdown (p < 0.001). Parents' depression (p < 0.001) and anxiety (p = 0.027) levels also increased during the second lockdown. Logistic regression showed that the use of psychotropic medication in parents and parents' depression scores were risk factors for children to have worse depression scores. Conclusion(s): The second lockdown appears to worsen the effects of the pandemic on children's and parents' mental health. There is a need to implement specific interventions targeting both children/adolescents and their parents to support them during lockdown periods and improve mental health outcomes.Copyright © 2022, The Author(s).
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BACKGROUND: The lockdown would become the primary strategy for facing covid-19 as it quickly mutates which might cause repeated pandemics;however, it negatively affects individuals' quality of life (QOL). The schizophrenia caregivers experience considerable stress. The research on the impact of the COVID-19 lockdown on QOL of schizophrenia caregivers is essential, especially for those who reside in rural areas. AIM: This study aimed to investigate the impact of lockdown-related COVID-19 on QOL among primary caregivers of schizophrenia patients living in a rural area. METHOD(S): This study recruited 204 primary caregivers (15-79 years). This study used the World Health Organization Quality of Life instrument (WHOQOL-BREF) to asses QOL's primary caregiver. Evaluate the possible change in caregivers' QOL before and during the COVID-19 lockdown using paired t-test for repeated measures. RESULT(S): The mean age of the caregivers was 46.61 years (SD = 12.79), ranging from 15 to 79 years, with a preponderance of male (54.5%), aged 38-47 years old (29.7%), married (81.2%), employed (57.4%), and had senior high school level of education (34.7%). Majority were parents (26.2%) of the ill relative, and took care of the patients more than 5 years (52.5%). There was a statistical difference (p < 0.05) in caregivers' QOL between before and during the COVID-19 lockdown, including in physical health, psychological, social relationships, and environment domain. CONCLUSION(S): Implementing a lockdown policy related to COVID-19 has negatively impacted the caregivers' QOL. The degradation of caregivers' QOL showed from before to during COVID-19 lockdown. Further study needs to explore the QOL of other mental illness caregivers regarding COVID-19 lockdown. This finding becomes a reference for a government to modify some policy-related lockdowns to minimize their negative impact.Copyright © 2023 Utomo Utomo, Eko Mulyadi, Endang Fauziyah.
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COVID-19 epidemic is not over. The correct wearing of masks can effectively prevent the spread of the virus. Aiming at a series of problems of existing mask-wearing detection algorithms, such as only detecting whether to wear or not, being unable to detect whether to wear correctly, difficulty in detecting small targets in dense scenes, and low detection accuracy, It is suggested to use a better algorithm based on YOLOv5s. It improves the generalization and transmission performance of the model by changing the ACON activation function. Then Bifpn is used to replace PAN to effectively integrate the target features of different sizes extracted by the network. Finally, To enable the network to pay attention to a wide area, CA is introduced to the backbone. This embeds the location information into the channel attention. © 2023 SPIE.
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As a result of the rural exodus over the last decades, unused vacancies in rural areas are at risk of falling into disrepair. Given the current trends of flexible workplaces and people returning to rural areas, their repurposing as coworking spaces (CWSs) by entrepreneurs poses a potential for sustainable future-oriented workplace solutions. However, there is little to no guidance on the structural configuration and business models of CWSs in rural areas available for these entrepreneurs. We apply a structured empirical research approach to create a comprehensive and specialized taxonomy, including a literature review and eleven interviews with operators of rural CWSs in Germany. The resulting taxonomy of business models of CWSs in rural areas based on an extension of the business model canvas contributes to the knowledge base on rural CWSs. We evaluate its usability through a case study and an entrepreneurial operator of a rural CWS, underlining its entrepreneurial and practice-oriented purpose. The study addresses several urgent topics, such as the future of work and new work (places), which enable and accelerate the development of CWSs outside agglomerations consequential to the COVID-19 pandemic. It also promotes social and sustainable entrepreneurship and the revitalizing, enhancing, and increasing of digital accessibility of rural regions.
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Objectives: This study aims to evaluate the impact of the stay-at-home orders, especially closing and reopening bars and other drinking establishments, on binge drinking patterns in US populations in Metropolitan Statistical Areas (MSAs). Method(s): Data on binge drinking and heavy binge drinking for this study was extracted from the 2018-2021 Behavioral Risk Factor Surveillance System (BRFSS). Data on regulations were collected by National Academy for State Health Policy. We used two staggered differences-in-differences strategies to account for monthly variations in bar regulations. We implemented a strategy that used never treated states as controls via the Stata package CSDID and a strategy that directly imputed counterfactuals for treated states via the Stata package FECT. The outcomes were measured by the number of binge drinkers or heavy binge drinkers per 1000 population. The treatment effect was estimated while controlling for age, income level, race, chronic conditions, gender, MSA fixed effects, and month fixed effects. Stay-at-home orders were coded as 1 in the first full month of implementation and were assumed to impact the entire state equally. Bars were assumed to reopen if the indoor service has been reactivated at any capacity. Result(s): For heavy binge drinking, the average treatment effect on the treated group was 4.86 per 1000 population (p=0.027) using FECT package and 6.74 per 1000 population (p = 0.025) using CSDID package. No significant effect was found for binge drinking. Conclusion(s): We provide suggestive evidence that stay-at-home orders may have increased heavy binge drinking in metropolitan areas. We estimated this led to a 3.38% (FECT) or 4.68% (CSDID) increase in heavy binge drinking during the pandemic. Future work will assess the characteristics of areas that saw the greatest increase in heavy binge drinking, and explore why heavy binge drinkers were more vulnerable than binge drinkers during the Covid.Copyright © 2023
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Background: This study seeks to evaluate the prevalence of and the association between receiving medical care abroad and the level of trust that citizens from the Western Balkans-Albania, Bosnia and Herzegovina, Kosovo and Montenegro-have in their healthcare systems. Method(s): The study is cross-sectional and was carried out during three months (July 25-October 30, 2021) through a self-reported questionnaire administered through the Google Forms platform. The study included approximately two-thousand citizens (N=2,356) aged eighteen (18) to seventy (70). Result(s): More than one-third (37.2%) of respondents stated that they or a relative had received healthcare services abroad during the last twelve (12) months. Citizens of Montenegro had the highest prevalence of receiving healthcare services abroad at 43.8%, followed by those from Bosnia and Herzegovina at 39%. No statistically significant difference was found in the level of trust in the healthcare system in the country between those who received healthcare services abroad (4.41+/-2.88) (out of 10) and those who did not (4.48+/-2.81) (t=-0.587, p=0.557). Conclusion(s): We ultimately conclude that more than one-third of the participants in our study have traveled abroad for healthcare purposes, with females, those living in urban areas, and those who have previously had a negative healthcare experience in their home country all being more likely to rely on health tourism.Copyright © 2023 Maljichi et al.
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COVID-19 is caused by the novel coronavirus SARS-CoV-2. First started in Wuhan, COVID-19 has spread everywhere, including Indonesia. COVID-19 can cause severe pneumonia, severe acute respiratory distress syndrome (ARDS) symptoms, and multiple organ failure. According to the WHO, COVID-19 generally has an incubation period of 5-6 days, ranging from 1 to 14 days. However, in Jakarta, the cases have decreased significantly since the implementation of PPKM (Restrictions of Activity), running since early July 2021. The government claimed that the PPKM rule has significantly impacted COVID-19 cases, decreasing every day, especially in Jawa-Bali Region. In addition, the Vaccination rate in Indonesia also played a significant part in decreasing COVID-19 cases, with Jakarta currently standing with 9 million people fully vaccinated per December 2021. To monitor the development of COVID-19 in Jakarta and provide information to the public about health facilities, especially hospitals in Jakarta, in this study, the distribution area of COVID-19 cases will be mapped with CHIME using ArcGIS Online tools. The analysis results obtained based on the mapping results that most cases were in the Cengkareng area, and the area with the most hospitals werein East Jakarta. © 2022 IEEE.
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BACKGROUND: Hepatopancreatobiliary (HPB) cancer incidence and mortality are increasing worldwide. An initial diagnostic predictor is needed for recommending further diagnostic modalities, referral, and curative or palliative decisions. There were no studies conducted in area with limited accessibility setting of the COVID-19 pandemic, coupled with limited human resources and facilities. AIM: We aimed to investigate the advantages of total bilirubin for predicting malignant obstructive jaundice, a combination of the pandemic era and limited resources settings. METHOD(S): Data from all cholestasis jaundice patients at M. Djamil Hospital in Pandemic COVID-19 period from July 2020 to May 2022 were retrospectively collected. The data included demographics, bilirubin fraction results, and final diagnosis. Bivariate analysis for obtain demographic risk factor, and Receiver Operating Characteristics (ROC) analysis for getting bilirubin value. RESULT(S): Of a total 132 patients included, 35.6% were malignant obstructive jaundice, and Pancreatic adeno ca was the most malignant etiology (34.4%). Bivariate analysis showed a significant correlation between age and malignant etiology (p = 0,024). Direct and total Bilirubin reach the same level of Area Under Curve (AUC). Total bilirubin at the cutoff point level of 10.7 mg/dl had the most optimal results on all elements of ROC output, AUC 0.88, sensitivity 76.6%, specificity 90.1%, +LR 8.14, and-LR 0.26. CONCLUSION(S): The bilirubin fraction is a good initial indicator for differentiating benign and malignant etiology (AUC 0.8-0.9) in pandemic era and resource-limited areas to improve diagnostic effectiveness and reduce referral duration.Copyright © 2023 Avit Suchitra, M. Iqbal Rivai, Juni Mitra, Irwan Abdul Rachman, Rini Suswita, Rizqy Tansa.
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BACKGROUND: Vaccines are one of the best interventions developed for eradicating COVID-19. In Albania, COVID-19 vaccination uses different types of vaccines: Pfizer, AstraZeneca, CoronaVac, and Sputnik V. Like any other vaccine, these have side effects too. AIM: This study was carried out to identify the perception of the side effects of vaccines. METHOD(S): A quantitative study using a cross-sectional survey was conducted between April and September 2021 to collect data on the effects of the COVID-19 vaccine among individuals in Shkodra region. Data were collected online through a self-administered survey created on Google Forms which had been randomly delivered to individuals (aged >=18 years) using social media sites (Email and WhatsApp). All data collected were analyzed with Microsoft Office Excel 2010, using the exact Fisher's test and x2 test. RESULT(S): This study included 292 citizens, out of which 200 were female and 92 were male;62% were from urban areas and 38% from rural areas of Shkodra region. The random sample of the citizens who took part in this study is 44.5% (18-30 years old). A massive percentage of the participants, 66.4%, had received the second dose of the vaccine. Our study shows that 55.8% of these citizens have had side effects after the first vaccination dose, and only 43.8% have had side effects after the second dose. About 80.6% of the participants were well informed about the type of vaccine they got. CONCLUSION(S): Side effects from vaccines were reported. Injection site pain and fatigue were the most common first dose side effects (55.8%). The same side effects were reported for the second dose. The side effects were presented during the first 12 h after the vaccination in most cases. Side effects were more prevalent in people >50 years old. Older people have a higher probability to have more side effects from the COVID vaccine. There is no statistically significant relationship between gender and the presence of the side effect from the COVID vaccine. People living in urban areas have a higher probability to have side effect from COVID vaccine comparing with people living in rural areas. People being vaccinated with Pfizer vaccine have a higher probability to admit the presence of side effects.Copyright: © 2022 Zamira Shabani, Arketa Guli, Julian Kraja, Arlinda Ramaj, Nertila Podgorica.
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We examine the impact of the COVID-19 pandemic on food access in US households located in low-income low-food access (LILA) zip codes and those in other areas. We explored changes in utilization of key food sources and in reported challenges, worries, and strategies related to obtaining food. Living in a LILA zip code was associated with a higher prevalence of using food programs, experiencing challenges finding help for food, worrying that food was unsafe, and worrying about losing access to food programs. Examining food acquisition during the pandemic may inform ways to reduce barriers to food access.Copyright © 2023 Taylor & Francis Group, LLC.
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The novel coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2).Mortality attributable to COVID-19 remains considerably high, with case fatality rates as high as 8-11%. Early medical intervention in patients who are seriously and critically ill with COVID-19 reduces fatal outcomes. Thus, there is an urgent need to identify biomarkers that could help clinicians determine which patients with SARS-CoV-2 infection are at a higher risk of developing the most adverse outcomes, which include intensive care unit (ICU) admission, invasive ventilation, and death. In COVID-19 patients experiencing the most severe form of the disease, tests of liver function are frequently abnormal and liver enzymes are found to be elevated. For this reason, we examine the most promising liver biomarkers for COVID-19 prognosis in an effort to help clinicians predict the risk of ARDS, ICU admission, and death at hospital admission. In patients meeting hospitalization criteria for COVID-19, serum albumin < 36 g/L is an independent risk factor for ICU admission, with an AUC of 0.989, whereas lactate dehydrogenase (LDH) values > 365 U/L accurately predict death with an AUC of 0.943.The clinical scores COVID-GRAM and SOFA that include measures of liver function such as albumin, LDH, and total bilirubin are also good predictors of pneumonia development, ICU admission, and death, with AUC values ranging from 0.88 to 0.978.Thus, serum albumin and LDH, together with clinical risk scores such as COVID-GRAM and SOFA, are the most accurate biomarkers in the prognosis of COVID-19.Copyright © 2021 Sociedad Medica del Hospital General de Mexico. Published by Permanyer.
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Domestic violence against women is a major social problem in Bangladesh. This paper examines the determinants of domestic violence in Bangladesh during the COVID-19 pandemic. The project was carried out in selected areas of Khulna district of the country and followed survey research design. A total of 312 ever married female respondents who experienced domestic violence at any stage of their life were surveyed. The respondents were selected through simple random sampling as a semi-structured questionnaire/ interview schedules was used as the primary tool for data collection. The data were collected in two stages between the months of May-October, 2021 through face-to-face interviews. Results from the chi-square analysis show that, respondents' residence, educational status, age at first marriage, duration of marriage life, husband's income, husband's occupation, and a demand for dowry were all associated with domestic violence against women (p <.01). The study concludes that creation of awareness and empowerment of women through income generating activities particularly in the rural areas of Bangladesh is necessary to reduce the prevalence of domestic violence.Copyright © Nova Science Publishers, Inc.
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Introduction: Lung cancer is the leading cause of cancer-related death in the US with an estimated 236,740 new cases and 130,180 deaths expected in 2022. While early detection with low-dose computed tomography reduces lung cancer mortality by at least 20%, there has been a low uptake of lung cancer screening (LCS) use in the US. The COVID-19 pandemic caused significant disruption in cancer screening. Yet, little is known about how COVID-19 impacted already low use of LCS. This study aims to estimate LCS use before (2019) and during (2020 and 2021) the COVID-19 pandemic among LCS-eligible population in the US. Method(s): We used population-based, nationally representative, cross-section data from the 2019 (n=4,484), 2020 (n=1,239) and 2021 (n=1,673) Behavioral Risk Factor Surveillance System, Lung Cancer Screening module. The outcome was self-reported LCS use among eligible adults in the past 12 months. For 2019 and 2020, the eligibility was defined based on US Preventive Services Task Force (USPSTF) initial criteria-adults aged 55 to 80 years old, who were current and former smokers (had quit within the past 15 years) with at least 30 pack years of smoking history. For 2021, we used the USPSTF updated criteria- adults aged 50 to 80 years, current and former smokers (who had quit within the past 15 years) with at least 20 pack years of smoking history. We applied sampling weights to account for the complex survey design to generate population estimates and conducted weighted descriptive statistics and logistic regression models. Result(s): Overall, there were an estimated 1,559,137 LCS-eligible respondents from 16 US states in 2019 (AZ, ID, KY, ME, MN, MS, MT, NC, ND, PA, RI, SC, UT, VT, WV, WI), 200,301 LCS-eligible respondents from five states in 2020 (DE, ME, NJ, ND, SD), and 668,359 LCS-eligible respondents from four states in 2021 (ME, MI, NJ, RI). Among 2,427,797 LCS-eligible adults, 254,890;38,875;and 122,240 individuals reported receiving LCS in 2019, 2020 and 2021, respectively. Overall, 16.4% (95% CI 14.4-18.5), 19.4% (95% CI 15.3-24.3), and 18.3% (95% CI 15.6-21.3) received LCS during 2019, 2020, and 2021, respectively. In all years, the proportion of LCS use was higher among adults aged 65-74, insured, those with fair and poor health, lung disease and history of cancer (other than lung cancer). In 2020, a higher proportion of adults living in urban areas reported receiving LCS compared to those living in rural areas (20.36% vs. 12.7%, p=0.01). Compared to non-Hispanic White adults, the odds of receiving LCS was lower among Hispanic adults and higher among Non-Hispanic American Indian/Alaskan Native adults in 2020 and 2021, respectively. Conclusion(s): LCS uptake remains low in the US. An estimated 2,011,792 adults at high-risk for developing lung cancer did not receive LCS during 2019, 2020 and 2021. Efforts should be focused to increase LCS awareness and uptake across the US to reduce lung cancer burden.
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Background: The emergence of Coronavirus disease (COVID-19) has been declared a pandemic and made a medical emergency worldwide. Various attempts have been made, including optimizing effective treatments against the disease or developing a vaccine. Since the SARS-CoV-2 protease crystal structure has been discovered, searching for its inhibitors by in silico technique becomes possible. Objective(s): This study aims to virtually screen the potential of phytoconstituents from the Begonia genus as 3Cl pro-SARS-CoV- 2 inhibitors, based on its crucial role in viral replication, hence making these proteases "promising" for the anti-SARS-CoV-2 target. Method(s): In silico screening was carried out by molecular docking on the web-based program DockThor and validated by a retrospective method. Predictive binding affinity (Dock Score) was used for scoring the compounds. Further molecular dynamics on Desmond was performed to assess the complex stability. Result(s): Virtual screening protocol was valid with the area under curve value 0.913. Molecular docking revealed only beta-sitosterol-3-O-beta-D-glucopyranoside with a lower docking score of -9.712 kcal/mol than positive control of indinavir. The molecular dynamic study showed that the compound was stable for the first 30 ns simulations time with Root Mean Square Deviation <3 A, despite minor fluctuations observed at the end of simulation times. Root Mean Square Fluctuation of catalytic sites HIS41 and CYS145 was 0.756 A and 0.773 A, respectively. Conclusion(s): This result suggests that beta-sitosterol-3-O-beta-Dglucopyranoside might be a prospective metabolite compound that can be developed as anti-SARS-CoV-2.Copyright © 2023, Page Press Publications. All rights reserved.
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Background: Easy availability, low cost, and low radiation exposure make chest radiography an ideal modality for coronavirus disease 2019 (COVID-19) detection. Objective(s): In this study, we propose the use of an artificial intelligence (AI) algorithm to automatically detect abnormalities associated with COVID-19 on chest radiographs. We aimed to evaluate the performance of the algorithm against the interpretation of radiologists to assess its utility as a COVID-19 triage tool. Material(s) and Method(s): The study was conducted in collaboration with Kaushalya Medical Trust Foundation Hospital, Thane, Maharashtra, between July and August 2020. We used a collection of public and private datasets to train our AI models. Specificity and sensitivity measures were used to assess the performance of the AI algorithm by comparing AI and radiology predictions using the result of the reverse transcriptase-polymerase chain reaction as reference. We also compared the existing open-source AI algorithms with our method using our private dataset to ascertain the reliability of our algorithm. Result(s): We evaluated 611 scans for semantic and non-semantic features. Our algorithm showed a sensitivity of 77.7% and a specificity of 75.4%. Our AI algorithm performed better than the radiologists who showed a sensitivity of 75.9% and specificity of 75.4%. The open-source model on the same dataset showed a large disparity in performance measures with a specificity of 46.5% and sensitivity of 91.8%, thus confirming the reliability of our approach. Conclusion(s): Our AI algorithm can aid radiologists in confirming the findings of COVID-19 pneumonia on chest radiography and identifying additional abnormalities and can be used as an assistive and complementary first-line COVID-19 triage tool.Copyright © Cancer Research, Statistics, and Treatment.
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Introduction: The COVID-19 pandemic necessitated proliferation of telesimulation. This pedagogy may be useful in rural areas to increase procedural adoption and reduce healthcare disparities. Our aim was to determine the current status of surgical simulation education to retool rural practicing Urologists. Method(s): Literature search was performed with a trained librarian for PubMed, EMBASE and Web of Science. Title/ screening were performed to include all studies of surgical simulation involving rural surgical learners to identify simulation education opportunities for practicing rural Urologists. Data was then extracted: simulation event, skills focus, MERSQI score, type/number of learners, learner assessment and event evaluation. Result(s): Seven manuscripts met inclusion criteria. Most were published 2019-2020 and were cross sectional (5/7, 71%). Mean adjusted MERSQI score was 13 (range 6-15.5). A wide range of surgical skills were taught (incl. laparoscopy, cricothyroidotomy, chest tube insertion, damage control laparotomy), but no Urological surgical skills. Two articles described mobile simulation units for rural areas. A total of 232 learners were identified including 69 medical students. One fifth of rural learners were non-medical or non-physicians. Only one study involved faculty, who were general surgeons. Conclusion(s): Telesimulation education for practicing Urologists in rural areas is lacking. Current in-operating room telementoring for rural Urologists requires surgeons to travel and perform their first cases utilizing this new technique on patients. Telesimulation to teach Urological skills in rural areas of the US may increase dissemination of techniques with no patient risk and has significant potential to redress current healthcare disparities.
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The purpose of this research was to develop a device that would facilitate visually impaired people in the use of lidded bins. And reduce the risk of spreading COVID-19 and other pathogens that may be contaminated with the trash area to all users Able to develop prototype devices to be used in practice and have the opportunity to extend it for practical use in the community area Or a point where there is a risk of the spread of garbage dumping information per day of that area for use in further data analysis. © 2023 IEEE.