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1.
Fertility and Sterility ; 116(3 SUPPL):e72, 2021.
Article in English | EMBASE | ID: covidwho-1880543

ABSTRACT

OBJECTIVE: The COVID-19 pandemic exacerbated existing and initiated new psychosocial, interpersonal, and environmental stressors. For menstruating people, these stressors may contribute to cycle irregularity and make family building an even more challenging journey. This study investigates the relationship between perceived stress and menstrual cycle and symptom changes during the COVID-19 pandemic. MATERIALS AND METHODS: A survey was administered to users of Ovia Health's Fertility mobile application in the United States from March 2020 to April 2021. Items captured changes in menstruation pattern and symptomology and included the Perceived Stress Scale 4-item version (PSS-4).1 A paired t-test was used to assess differences between groups. A p-value of < 0.05 was considered statistically significant. RESULTS: Out of a total of 12,302 respondents, 36% reported experiencing some menstrual cycle and/or symptom changes. Most commonly reported changes included cycle starting early or late (87%), stronger symptoms during menstruation (e.g. low back pain, cramping, discharge changes) (29%), and heavier bleeding during periods (27%). Respondents reporting menstrual cycle or symptom changes tended to score slightly higher on average on the PSS-4 compared to those who did not report any changes (8.5 v. 8.3, respectively, p < 0.05). PSS-4 scores in this sample were notably higher in all respondents, regardless of cycle/symptom irregularity, compared to pre-pandemic benchmarking in similar populations.2-3 CONCLUSIONS: These results demonstrate that this sample's reported stress levels during the pandemic were noticeably higher than pre-pandemic benchmarks, and that these stress levels may contribute to changes in reproductive physiological processes such as menstruation. These changes may be especially frustrating and impactful for individuals trying to conceive and those struggling with infertility. IMPACT STATEMENT: Reproductive medicine specialists should be aware of the relationship between stress fostered by the COVID-19 pandemic and menstrual pattern disruption, especially for patients trying to conceive with irregular menstrual patterns or those struggling with infertility. Providers should work together with their patients to formulate strategies to mitigate the impact of stress on menstrual cycle changes in order to optimize conception and fertility treatment outcomes.

2.
Fertility and Sterility ; 116(3 SUPPL):e298, 2021.
Article in English | EMBASE | ID: covidwho-1880542

ABSTRACT

OBJECTIVE: Over the course of the first 12 months of the COVID-19 pandemic in the United States and around the globe, reproductive and obstetric research began to reveal the potentially detrimental impacts of COVID-19 on pregnant people and fetuses, and more importantly how society and healthcare facilities can protect these vulnerable individuals. However, for millions of people planning to start or grow their families during 2020, these effects and steps to minimize risk to both parent and child were still largely unknown. This investigation captures changes in attitudes and behavior surrounding conception efforts during the height of the COVID-19 pandemic. MATERIALS AND METHODS: A survey was administered to users of Ovia Health's Fertility mobile application in the United States from March 2020 to April 2021 to assess conception effort behavior and geographic location. A Chi-squared test was performed to determine if geographical region impacted conception efforts. A p-value of < 0.05 was considered statistically significant. RESULTS: A total of 20,046 respondents qualified for inclusion in analyses. Of the 16,527 respondents actively trying to get pregnant or attempted pregnancy in the last six months, one in ten reported altering their conception plans during the last year. Most respondents decided to temporarily pause TTC efforts specifically due to the pandemic (70%), and 6% delayed conception attempts indefinitely until the conclusion of the pandemic. Main contributors to these decisions included the potential impact of COVID-19 on pregnant people or fetuses (39%), lack of support people during pregnancy and labor (25%), and concern about finances or job security (23%). Rates of temporary TTC pause were comparable across the United States, ranging from a high of 31% in the Northeast and a low of 21% in the Southeast (p > 0.05). Rates of prolonged TTC abandonment were lower and also comparable across regions, ranging from 9% in the Pacific to 4% in the Southeast (p > 0.05). People of any age were equally likely to temporarily pause or abandon conception efforts indefinitely (p > 0.05). CONCLUSIONS: Instability, isolation, and insufficient information fostered by the COVID-19 pandemic contributed to individuals' decisions to either temporarily pause or abandon their conception attempts indefinitely. Changes in TTC behavior were comparable across all U.S. geographic regions and ages, demonstrating the pandemic's indiscriminate impact on family building behavior in this sample. As individuals revisit or resume their family building journeys, especially those whose fertility opportunities may be narrowing, reproductive medicine specialists should support patients who altered or continue to alter their conception plans during the pandemic. IMPACT STATEMENT: Reproductive medicine specialists and ancillary clinical team members should be aware of the impact COVID-19 had on family building behavior and prepare to support patients as they revisit their family building plans, particularly those who may struggle with infertility and whose fertility opportunities are becoming increasingly limited.

3.
Fertility and Sterility ; 116(3 SUPPL):e295, 2021.
Article in English | EMBASE | ID: covidwho-1880541

ABSTRACT

OBJECTIVE: The strain on the healthcare system and attempts to limit virus transmission during the COVID-19 pandemic reduced patients' access to healthcare services, particularly those seeking specialized or elective health services such as infertility treatment. Mandatory fertility clinic closures prolonged conception efforts and further complicated the already arduous family building journey. This study investigates the incidence of assisted reproductive technology (ART) delay or abandonment during the COVID-19 pandemic and assesses whether these rates varied by U.S. geographic region. MATERIALS AND METHODS: A survey was administered to users of Ovia Health's Fertility mobile application in the United States from March 2020 to April 2021. A Chi-squared test was performed to assess differences in ART delay or cancellation and geographical region. A p-value of < 0.05 was considered statistically significant. RESULTS: A total of 20,047 respondents qualified for inclusion in this analysis. Of the 16,527 respondents currently or formerly trying to conceive within the last six months, 16% reported utilizing intrauterine insemination (IUI), in vitro fertilization (IVF), or another form of ART. Though the majority of treatments proceeded as planned, almost one in five (17%) were delayed or cancelled between March 2020 and April 2021. Main contributors to the decision to delay or cancel ART efforts were temporary fertility clinic closures (28%), concern about the impact of COVID-19 on pregnant people or fetuses (28%), attempting to avoid healthcare facilities (22%), lack of availability of support people during pregnancy and labor (17%), and concerns about finances or job security (16%). ART delay or cancellation did not differ by geographic region (p > 0.05). CONCLUSIONS: Our results demonstrate how the closure of fertility clinics during the COVID-19 pandemic and concern about COVID-19's detrimental impact during pregnancy pushed people seeking these services to delay indefinitely or altogether abandon their family building efforts. These trends were similar across the United States, regardless of geographical region. As ART treatments and care plans resume, reproductive medicine specialists should reinforce safety mitigation strategies to reduce the risk of COVID-19 transmission, foster COVID-19 vaccination discussions, and empower and restore patients' confidence with the latest COVID-19 research findings. IMPACT STATEMENT: Clinical service models resuming ART services should center around addressing patients' main concerns for delaying or abandoning ART efforts, especially focused on empowering patients whose family building journeys were interrupted by fertility center closures during the COVID-19 pandemic.

4.
Fertility and Sterility ; 116(3 SUPPL):e207, 2021.
Article in English | EMBASE | ID: covidwho-1880369

ABSTRACT

OBJECTIVE: The purpose of this study is to determine the positive predictive value (PPV) of diagnosis for endometriosis by the Nezhat Endometriosis Advisor (NEA) mobile application to serve as a screening tool MATERIALS AND METHODS: A retrospective cohort study was conducted at a university-affiliated private practice. Inclusion criteria were women with no previous surgical diagnosis of endometriosis who also completed an endometriosis assessment using the application. Patients with symptoms desiring definitive diagnosis and treatment of endometriosis then underwent laparoscopic surgery once surgeries were once again allowed. The diagnosis of endometriosis was confirmed visually by a surgeon specialized in treating endometriosis and also through biopsy sent to pathology. The primary outcome measured was the PPVof NEA mobile application questionnaire to the surgical diagnoses of endometriosis. RESULTS: A total of 100 patients met the inclusion criteria for this study. 95% of the patients whose score on the app was 90% or above, had a surgical pathology confirmed diagnosis of endometriosis (PPV 95%). CONCLUSIONS: NEA mobile application questionnaire has a high PPVof 95% for diagnosing endometriosis and can help identify a patient population that may require surgical treatment for pelvic pain or unexplained infertility. This will be helpful as it may lead to earlier diagnosis and management of endometriosis. Patients can reduce risk exposure of COVID-19 by avoiding multiple medical office visits. The COVID-19 pandemic has also decreased the availability of healthcare for many, and they may suffer for a long time with pain or infertility before a diagnosis is made. The mobile application is a possible alternative method to assess risk of endometriosis while avoiding risk of COVID-19 exposure. Patients can be medically treated based on symptoms and application results until surgery can be performed. With further research, the application has the potential to be the diagnostic measure of endometriosis. More research is needed to determine the continued accuracy of the application in different patient population and demographics IMPACT STATEMENT: Endometriosis is ectopic uterine lining growing outside the uterus which causes pain and infertility. Currently, definitive diagnosis is with pelvic laparoscopic surgery, as no screening test is widely available or accepted. The Coronavirus Disease 2019 (COVID-19) pandemic due to the infectious pathogen Severe Acute Respiratory Syndrome Coronavirus 2 has altered ambulatory and inpatient health care. For several months commencing March 2020, non-emergent surgeries came to an abrupt hault due to the COVID- 19 pandemic. Many patients who were scheduled to have diagnostic laparoscopies for suspected endometriosis were not able to have their surgeries performed. As an alternative NEA was utilized to determine the likelihood of endometriosis based on self-answered questionnaires about experienced symptoms. The mobile app is free and available for patients worldwide. Patients with a high probability of endometriosis can be treated medically until surgery resume.

5.
Journal of Managed Care and Specialty Pharmacy ; 27(4-A SUPPL):S128, 2021.
Article in English | EMBASE | ID: covidwho-1880081

ABSTRACT

BACKGROUND: Digital therapeutics (DTx) have grown in recent years in terms of market size and influence. Despite increasing interest, managed care organizations face barriers around DTx management. Disparate DTx coverage has led to unequal uptake and discrepancies around utilization management (UM) strategies. Thus, an unmet need exists for elucidating DTx coverage criteria and the evidence that shapes policy development. OBJECTIVE: To understand current DTx payer coverage policy patterns and anticipated future trends. METHODS: DTx medical policy research was conducted August to September 2020 using Canary Insights (Lakewood, CO). Following this surveillance, an online survey was fielded to payers from Xcenda's Managed Care Network. Respondents familiar with DTx were asked about DTx coverage, UM, policy criteria, and COVID-19 implications for DTx management. RESULTS: Fifty respondents (54% represent health plans, 26% pharmacy benefit managers, 20% integrated delivery network) completed the survey, and 88% evaluated ≥ 1 DTx in the past 12 to 18 months. Respondents reported that mobile apps (48%) and medication adherence platforms (40%) were the most reviewed and were expected to have the greatest increase in coverage demand over the next 12 to 18 months. Respondents indicated diabetes as the highest priority (66%) with the greatest impact in addressing unmet needs (52%). For UM, DTx coverage fell under medical benefit (41%) or was product dependent (43%). In evaluating DTx, clinical effectiveness (94%), safety (82%), and FDA-approved or cleared use (78%) were indicated as absolutely needed while clinical benefit (98%), peer-reviewed publications (94%), and return on investment (88%) were most useful for coverage decisions. The most cited rationale for either covering or denying DTx was evaluation of existing efficacy and safety data vs a lack of outcomes and cost data. For reauthorization, most respondents indicated documentation of positive clinical response (80%) and total cost of care reduction (71%) as requirements for re-authorization, while citing lack of long-term clinical data (73%) as the largest barrier for establishing re-authorization criteria, and 52% of respondents were interested in subscription-based or alternative pricing models for re-authorization. Respondents indicated that the COVID-19 pandemic has not impacted DTx coverage (58%), with no changes expected in the next 12 to 18 months (46%). CONCLUSIONS: Inconsistencies in DTx payer evaluation, coverage, and UM highlight the unmet need for establishing a standardized format for DTx appraisal.

6.
J Am Med Inform Assoc ; 2022 Jun 06.
Article in English | MEDLINE | ID: covidwho-1878796

ABSTRACT

During the coronavirus disease-2019 (COVID-19) pandemic, the Centers for Disease Control and Prevention (CDC) supplemented traditional COVID-19 case and death reporting with COVID-19 aggregate case and death surveillance (ACS) to track daily cumulative numbers. Later, as public health jurisdictions (PHJs) revised the historical COVID-19 case and death data due to data reconciliation and updates, CDC devised a manual process to update these records in the ACS dataset for improving the accuracy of COVID-19 case and death data. Automatic data transfer via an application programming interface (API), an intermediary that enables software applications to communicate, reduces the time and effort in transferring data from PHJs to CDC. However, APIs must meet specific content requirements for use by CDC. As of March 2022, CDC has integrated APIs from 3 jurisdictions for COVID-19 ACS. Expanded use of APIs may provide efficiencies for COVID-19 and other emergency response planning efforts as evidenced by this proof-of-concept. In this article, we share the utility of APIs in COVID-19 ACS.

7.
International Journal of Automation Technology ; 16(3):286-295, 2022.
Article in English | Scopus | ID: covidwho-1879729

ABSTRACT

Manufacturing functions are often performed by groups of engineers who cooperate and gather at work sites. However, since the beginning of the COVID-19 pandemic, the movement and activities of groups of people have been restricted, especially in indoor spaces. This reduction in travel by engineers also implies a reduction in associated costs. Telepresence technology, which is studied in the field of virtual re-ality, can be used as a way to reduce travel. Telep-resence allows users to engage with a site from a remote location as if they were present. Thus, engineers would be able to participate in a working group with-out the necessity of physically traveling to the site to cooperate with local manufacturing people. A variety of telepresence systems have been proposed;however, relatively few methods have been widely implemented compared with video chat applications that have re-cently become an established infrastructure in many companies. This is most likely because most proposed systems use robots, head-mounted displays, or dedi-cated multi-functional applications that require engineers to learn how to use them. One way to use a video chat application to understand a remote space is to have a remote participant move a camera used in a video chat application. In contrast, many VR social networking services use a viewing method with which users can change their viewing direction on the computer screen. In this study, we demonstrate that a system that allows users to rotate their viewing perspec-tive on a laptop computer screen can provide an easier understanding of a virtual space than a system that re-quires a remote person to move a webcam. Based on these results, we propose a system that allows users to view a remote location on a laptop computer screen via a video chat application and an off-the-shelf spherical camera, and evaluate its usefulness. © Fuji Technology Press Ltd.

8.
8th IEEE International Conference on Problems of Infocommunications, Science and Technology, PIC S and T 2021 ; : 595-598, 2021.
Article in English | Scopus | ID: covidwho-1878969

ABSTRACT

Deep cytogenetic examination of chromosomes properties is very specialized test that can be performed only in some scientific laboratories. Many problems occurred with sending the cytohistological micro preparations to laboratories of other countries because of COVID-19 pandemic. The only one way was available-to use telecommunication systems and send digital images of micro preparations to laboratories for their analysis in the limited time. Due to technical features of digital images of microslides, their informative value can vary significantly. Subjective and qualitative estimations of the parameters of microobjects are also a significant factor, which leads to decreasing the accuracy of laboratory diagnostics and complicating the repeatability of the results in scientific research. The aim of this article is to investigate the chromosome image parameters that carry the fullest informative value out of the images. © 2021 IEEE.

9.
Orthop Traumatol Surg Res ; : 103342, 2022 Jun 02.
Article in English | MEDLINE | ID: covidwho-1878337

ABSTRACT

BACKGROUND: Rehabilitation after surgery is a crucial process that governs the final functional outcome. The self-rehabilitation smartphone application Doct'up (Healing SAS, Lyon, France) is designed for patients who have had anterior cruciate ligament (ACL) reconstruction surgery. In France in the spring of 2020, the lockdown mandated due to the COVID-19 pandemic prevented patients from seeing their physiotherapists for 2 months. The objective of this study was to compare the clinical outcomes in two groups of patients who underwent ACL reconstruction surgery: in one group, surgery performed before the lockdown was followed by standard in-person physiotherapy while, in the other, surgery was done just before the lockdown and rehabilitation was performed by the patients themselves using the phone application. HYPOTHESIS: Using a self-rehabilitation smartphone app limits the negative effects of not receiving physiotherapist rehabilitation after ACL reconstruction. MATERIAL AND METHODS: We performed a case-control study involving the retrospective analysis of prospectively collected data from two groups of patients who had undergone ACL reconstruction surgery. Patients in the App group had surgery just before the 2-month COVID-19-related lockdown that started in France on March 17, 2020,and used only the smartphone app for rehabilitation. The standard-care group was composed of matched controls who had surgery 1 year before the cases and received rehabilitation therapy during in-person physiotherapist visits. The ACL reconstruction technique was the same in the two groups. The primary outcome measure was extension lag 6 weeks after surgery. The secondary outcome measures were extension lag 3 weeks and 6 months after surgery, quadriceps muscle activation, knee extension locking 3 and 6 weeks after surgery, and the 6-month rate of surgical revision for cyclops syndrome. RESULTS: We included 32 cases managed using only self-rehabilitation guided by the phone app, and we identified 101 matched controls managed using standard care. We found no significant between-group difference in extension lag after 6 weeks: 9.4% (28/32) vs. 4.6% (87/101), p=0.39. After 3 weeks, the App group had a higher proportions of patients with quadriceps activation (94% [30/32] vs. 73% [74/101], p=0.015) and extension control using canes (78.1% [25/32] vs. 40.6% [41/101], p=0.0002). None of the other measured outcomes differed significantly between the two groups (extension lag after 3 weeks: 12.5% [4/32] vs. 13.8% 14/101]; extension lag after 6 months: 3.2% [1/32] vs. 1% [1/101]; quadriceps activation after 6 weeks: 97% [31/32] vs. 99% [100/101]; extension locking with canes after 6 weeks: 96.9% [31/32] vs. 93.1% [94/101]; extension locking without canes after 3 weeks: 53.2% [17/32] vs. 47.5% [48/101]; extension locking without canes after 6 weeks: 93.7% [30/32] vs. 82.2% [83/101]; and surgery for cyclops syndrome (3.1% [1/32] vs. 1% [1/101]). DISCUSSION: The use of a self-rehabilitation phone app after ACL reconstruction during a COVID-19 lockdown limited the adverse effects of not receiving in-person physiotherapy. The 6-month outcomes were similar to those seen with standard rehabilitation. The study results demonstrate the usefulness of self-rehabilitation after ACL reconstruction surgery. Self-rehabilitation guided by a phone app could be used as a complement to the protocols generally applied by physiotherapists. LEVEL OF EVIDENCE: IV, single-centre retrospective case-control study.

10.
Smart Innovation, Systems and Technologies ; 294:113-129, 2022.
Article in English | Scopus | ID: covidwho-1877789

ABSTRACT

Recent developments in Internet of Things (IoT) have significantly changed modern lifestyles through linkages of smart objects and smart applications that can be controlled anytime anywhere in the world. It is expected that as of 2021, more than 35 billion devices are connected with each other under the broad IoT umbrella. The autonomous nature of IoT brings an opportunity for virtual representation and unique identification of devices, applications, and services. Lower costs, lower levels of energy consumption, higher levels of outputs, smart and user-friendly precincts, and others are some factors behind rising popularity of IoT, which is also becoming more effective in providing higher levels of security and reducing errors and abuses. In this paper, we describe a model of smart dustbin designed and configured by the authors, and explain how the smart dustbin model can be applied efficiently to achieve smart environmental goals. This example of smart dustbin application can be adopted by cities and communities to maximize public health and hygiene objectives in smarter ways, and to curb negative impacts of public health crises situations such as the ongoing COVID-19 pandemic and other infectious diseases that may bring any type of pandemic in the future. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

11.
21st International Conference on Image Analysis and Processing, ICIAP 2022 ; 13231 LNCS:173-184, 2022.
Article in English | Scopus | ID: covidwho-1877764

ABSTRACT

Thanks to the rapid increase in computational capability during the latest years, traditional and more explainable methods have been gradually replaced by more complex deep-learning-based approaches, which have in fact reached new state-of-the-art results for a variety of tasks. However, for certain kinds of applications performance alone is not enough. A prime example is represented by the medical field, in which building trust between the physicians and the AI models is fundamental. Providing an explainable or trustful model, however, is not a trivial task, considering the black-box nature of deep-learning based methods. While some existing methods, such as gradient or saliency maps, try to provide insights about the functioning of deep neural networks, they often provide limited information with regards to clinical needs. We propose a two-step diagnostic approach for the detection of Covid-19 infection from Chest X-Ray images. Our approach is designed to mimic the diagnosis process of human radiologists: it detects objective radiological findings in the lungs, which are then employed for making a final Covid-19 diagnosis. We believe that this kind of structural explainability can be preferable in this context. The proposed approach achieves promising performance in Covid-19 detection, compatible with expert human radiologists. Moreover, despite this work being focused Covid-19, we believe that this approach could be employed for many different CXR-based diagnosis. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

12.
Computer Applications in Engineering Education ; 2022.
Article in English | Scopus | ID: covidwho-1877564

ABSTRACT

Games for learning help students and professionals to incorporate new knowledge through a playful experience. With the popularization of virtual education (partially due to COVID-19), there is a need for new tools that complement virtual educational environments. To deal with this need, we present Scrum Game, a mobile application game that aims to support the Scrum software methodology teaching and training. Scrum Game offers 42 activities grouped in levels with specific learning goals. This paper reports on a controlled experiment that evaluates Scrum Game in a course with more than 160 students. We assessed Scrum Game's effectiveness in terms of (i) user performance (i.e., students' marks and number of levels/activities completed) and (ii) user experience (i.e., usability). We found that students who used Scrum Game outperformed those who did not use it. We also found that students think that Scrum Game exhibits an enjoyable user experience. © 2022 Wiley Periodicals LLC.

13.
34th International Conference on Computer Applications in Industry and Engineering, CAINE 2021 ; 79:91-98, 2021.
Article in English | Scopus | ID: covidwho-1876866

ABSTRACT

In this paper, we study the Convolutional Neural Network (CNN) applications in medical image processing during the battle against Coronavirus Disease 2019 (COVID-19). Specifically, three CNN implementations are examined: CNN-LSTM, COVID-Net, and DeTraC. These three methods have been shown to offer promising implications for the future of CNN technology in the medical field. This survey explores how these technologies have improved upon their predecessors. Qualitative and quantitative analyses have strongly suggested that these methods perform significantly better than the commensurate technologies. After analyzing these CNN implementations, it is reasonable to conclude that this technology has a place in the future of the medical field, which can be used by professionals to gain insight into new diseases and to help in diagnosing infections using medical imaging. © 2021, EasyChair. All rights reserved.

14.
JMIR Form Res ; 6(6): e38113, 2022 Jun 16.
Article in English | MEDLINE | ID: covidwho-1875306

ABSTRACT

BACKGROUND: Serial testing for SARS-CoV-2 is recommended to reduce spread of the virus; however, little is known about adherence to recommended testing schedules and reporting practices to health departments. OBJECTIVE: The Self-Testing for Our Protection from COVID-19 (STOP COVID-19) study aims to examine adherence to a risk-based COVID-19 testing strategy using rapid antigen tests and reporting of test results to health departments. METHODS: STOP COVID-19 is a 12-week digital study, facilitated using a smartphone app for testing assistance and reporting. We are recruiting 20,000 participants throughout the United States. Participants are stratified into high- and low-risk groups based on history of COVID-19 infection and vaccination status. High-risk participants are instructed to perform twice-weekly testing for COVID-19 using rapid antigen tests, while low-risk participants test only in the case of symptoms or exposure to COVID-19. All participants complete COVID-19 surveillance surveys, and rapid antigen results are recorded within the smartphone app. Primary outcomes include participant adherence to a risk-based serial testing protocol and percentage of rapid tests reported to health departments. RESULTS: As of February 2022, 3496 participants have enrolled, including 1083 high-risk participants. Out of 13,730 tests completed, participants have reported 13,480 (98.18%, 95% CI 97.9%-98.4%) results to state public health departments with full personal identifying information or anonymously. Among 622 high-risk participants who finished the study period, 35.9% showed high adherence to the study testing protocol. Participants with high adherence reported a higher percentage of test results to the state health department with full identifying information than those in the moderate- or low-adherence groups (high: 71.7%, 95% CI 70.3%-73.1%; moderate: 68.3%, 95% CI 66.0%-70.5%; low: 63.1%, 59.5%-66.6%). CONCLUSIONS: Preliminary results from the STOP COVID-19 study provide important insights into rapid antigen test reporting and usage, and can thus inform the use of rapid testing interventions for COVID-19 surveillance.

15.
JMIR Form Res ; 6(6): e37779, 2022 Jun 07.
Article in English | MEDLINE | ID: covidwho-1875304

ABSTRACT

BACKGROUND: In Myanmar, the use of a mobile app for tuberculosis (TB) screening and its operational effect on seeking TB health care have not been evaluated yet. OBJECTIVE: This study aims to report the usability of a simple mobile app to screen TB and comply with chest X-ray (CXR) examination of presumptive cases detected by the app. METHODS: A new "TB-screen" app was developed from a Google Sheet based on a previously published algorithm. The app calculates a TB risk propensity score from an individual's sociodemographic characteristics and TB clinical history and suggests whether the individual should undergo a CXR. The screening program was launched in urban slum areas soon after the COVID-19 outbreak subsided. A standard questionnaire was used to assess the app's usability rated by presumptive cases. Compliance to undergo CXR was confirmed by scanning the referral quick response (QR) code via the app. RESULTS: Raters were 453 presumptive cases detected by the app. The mean usability rating score was 4.1 out of 5. Compliance to undergo CXR examination was 71.1% (n=322). Active TB case detection among CXR compliances was 7.5% (n=24). One standard deviation (SD) increase in the app usability score was significantly associated with a 59% increase in the odds to comply with CXR (ß=.464) after adjusting for other variables (P<.001). CONCLUSIONS: This simple mobile app got a high usability score rated by 453 users. The mobile app usability score successfully predicted compliance to undergo CXR examination. Eventually, 24 (7.5%) of 322 users who were suspected of having TB by the mobile app were detected as active TB cases by CXR. The system should be upscaled for a large trial.

16.
2022 CHI Conference on Human Factors in Computing Systems, CHI 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1874720

ABSTRACT

Ridesharing services do not make data of their availability (supply, utilization, idle time, and idle distance) and surge pricing publicly available. It limits the opportunities to study the spatiotemporal trends of the availability and surge pricing of these services. Only a few research studies conducted in North America analyzed these features for only Uber and Lyft. Despite the interesting observations, the results of prior works are not generalizable or reproducible because: i) the datasets collected in previous publications are spatiotemporally sensitive, i.e., previous works do not represent the current availability and surge pricing of ridesharing services in different parts of the world;and ii) the analyses presented in previous works are limited in scope (in terms of countries and ridesharing services they studied). Hence, prior works are not generally applicable to ridesharing services operating in different countries. This paper addresses the issue of ridesharing-data unavailability by presenting Ridesharing Measurement Suite (RMS). RMS removes the barrier of entry for analyzing the availability and surge pricing of ridesharing services for ridesharing users, researchers from various scientific domains, and regulators. RMS continuously collects the data of the availability and surge pricing of ridesharing services. It exposes real-time data of these services through i) graphical user interfaces and ii) public APIs to assist various stakeholders of these services and simplify the data collection and analysis process for future ridesharing research studies. To signify the utility of RMS, we deployed RMS to collect and analyze the availability and surge pricing data of 10 ridesharing services operating in nine countries for eight weeks in pre and during pandemic periods. Using the data collected and analyzed by RMS, we identify that previous articles miscalculated the utilization of ridesharing services as they did not count in the vehicles driving in multiple categories of the same service. We observe that during COVID-19, the supply of ridesharing services decreased by 54%, utilization of available vehicles increased by 6%, and a 5 × increase in the surge frequency of services. We also find that surge occurs in a small geographical region, and its intensity reduces by 50% in about 0.5 miles away from the location of a surge. We present several other interesting observations on ridesharing services' availability and surge pricing. © 2022 ACM.

17.
2022 CHI Conference on Human Factors in Computing Systems, CHI 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1874708

ABSTRACT

Instructors regularly learn and customize various feature-rich software applications to meet their unique classroom needs. Although instructors often prefer social help from colleagues to navigate this complex and time-consuming learning process, it can be difficult for them to locate relevant task-specific customizations, a challenge only exacerbated by the transition to online teaching due to COVID-19. To mitigate this, we explored how instructors could use an example-based customization sharing platform to discover, try, and appropriate their colleagues' customizations within a learning management system (LMS). Our field deployment study revealed diverse ways that ten instructors from different backgrounds used customization sharing features to streamline their workflows, improve their LMS feature awareness, and explore new possibilities for designing their courses to match student expectations. Our findings provide new knowledge about customization sharing practices, highlighting the complex interplay of expertise, software learnability, domain-specific workflows, and social perceptions. © 2022 ACM.

18.
2022 CHI Conference on Human Factors in Computing Systems, CHI 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1874707

ABSTRACT

Deaf and Hard-of-Hearing (DHH) users face accessibility challenges during in-person and remote meetings. While emerging use of applications incorporating automatic speech recognition (ASR) is promising, more user-interface and user-experience research is needed. While co-design methods could elucidate designs for such applications, COVID-19 has interrupted in-person research. This study describes a novel methodology for conducting online co-design workshops with 18 DHH and hearing participant pairs to investigate ASR-supported mobile and videoconferencing technologies along two design dimensions: Correcting errors in ASR output and implementing notification systems for influencing speaker behaviors. Our methodological findings include an analysis of communication modalities and strategies participants used, use of an online collaborative whiteboarding tool, and how participants reconciled differences in ideas. Finally, we present guidelines for researchers interested in online DHH co-design methodologies, enabling greater geographically diversity among study participants even beyond the current pandemic. © 2022 ACM.

19.
7th International Conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2022 ; : 24-27, 2022.
Article in English | Scopus | ID: covidwho-1874359

ABSTRACT

The COVID-19 pandemic has led to many lifestyle changes, one of them being the mandatory use of face masks in public settings. Given the importance of masks, there are various types for people to use, such as cloth and N95. A proper mask must be used to protect oneself and others from the spread of the coronavirus. This paper proposes CoViMask, a face mask type detector that detects the type of mask that a person is wearing, and is trained using a custom-made dataset. Accuracy, precision and recall are used to evaluate the proposed method. The paper also mentions the application areas. The results obtained prove that CoViMask is efficient in mask type detection and may aid in controlling the spread of covid. © 2022 IEEE.

20.
5th International Conference of Women in Data Science at Prince Sultan University, WiDS-PSU 2022 ; : 143-145, 2022.
Article in English | Scopus | ID: covidwho-1874358

ABSTRACT

The COVID-19 pandemic has greatly affected humanity by destabilizing the world economy through strain on hospital systems and deaths. Medical personnel is working around the clock to establish vaccines. On the other hand, technology contributes to the fight against the virus by tracking COVID-19 infections. Many digital contact tracking smartphone applications have been created to address this epidemic successfully. However, the applications lack transparency, raising worries about their privacy. Contact tracing has been employed to stop the spread of the disease. When battling the coronavirus epidemic, computerized contact tracking has quickly emerged as an essential tool. Therefore, the research conducted in this paper focuses on the challenges of tracking applications to analyze the perspective view of privacy issues. Besides, the paper proposes policies for data privacy to aid in making the tracking applications more effective and successful. © 2022 IEEE.

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