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1.
Canadian Journal of Nonprofit and Social Economy Research ; 13(2):1-16, 2022.
Article in English | Web of Science | ID: covidwho-2205624

ABSTRACT

This article examines the experiences of the nonprofit, homeless-serving sector during the first wave of the COVID-19 pandemic. Qualitative interviews were conducted with staff and volunteers from frontline organizations in the two largest communities in Nova Scotia, Canada. Participants reported much strain on their organizations' human resources, but also the ability to adjust service delivery mechanisms quickly in order to continue offering supports. Most reported greater in-kind contributions from businesses and community members as well as more funding from the federal government in particular, albeit with administrative burdens and defined timelines. Nonprofits played a leadership role in developing responses to serve the needs of those experiencing home-lessness, including developing comfort centres, installing portable toilets in downtown locations, and moving those without housing into hotels. They also advocated to government for state-level responses to those without housing, including calls to invest in new units and enhance funding for frontline service providers. At the same time, nonprofits reported working across sectors, noting better communication and relationships with state actors as well as other nonprofit organizations as a result of their COVID-19 response.

2.
Emerging infectious diseases ; 29(2), 2023.
Article in English | EMBASE | ID: covidwho-2198462

ABSTRACT

Genomic data provides useful information for public health practice, particularly when combined with epidemiologic data. However, sampling bias is a concern because inferences from nonrandom data can be misleading. In March 2021, the Washington State Department of Health, USA, partnered with submitting and sequencing laboratories to establish sentinel surveillance for SARS-CoV-2 genomic data. We analyzed available genomic and epidemiologic data during presentinel and sentinel periods to assess representativeness and timeliness of availability. Genomic data during the presentinel period was largely unrepresentative of all COVID-19 cases. Data available during the sentinel period improved representativeness for age, death from COVID-19, outbreak association, long-term care facility-affiliated status, and geographic coverage;timeliness of data availability and captured viral diversity also improved. Hospitalized cases were underrepresented, indicating a need to increase inpatient sampling. Our analysis emphasizes the need to understand and quantify sampling bias in phylogenetic studies and continue evaluation and improvement of public health surveillance systems.

3.
Open Forum Infectious Diseases ; 9(Supplement 2):S895-S896, 2022.
Article in English | EMBASE | ID: covidwho-2190026

ABSTRACT

Background. Families with children may be at higher risk for influenza infection. Community transmission can suffer from underreporting as testing is often not performed. We studied the epidemiology of influenza in households with school-aged children using home-based sample collection. Methods. We conducted a remote household study surveilling respiratory viruses from November 2019-June 2021, in King County, Washington (WA), USA. Households with school-aged children were enrolled, mailed home specimen collection kits, and asked to self-assess for weekly acute respiratory illness (ARI) using remote survey platforms. Participants with ARI symptoms were prompted to complete serial illness surveys and self-collect/parent collect mid-turbinate nasal swabs. Samples were sent to a University of Washington study laboratory for RT-PCR influenza testing. Influenza rates were compared to WA Department of Health (DOH) reporting. Results. A total of 1861 ARI events were reported among 992 adults and 869 children in 470 households;75 influenza cases were detected (36 influenza A and 39 influenza B). The study participant median age was 32 years (0-84), 10 years (1-49) for influenza A, and 11 years (3-49) for influenza B cases. Overall 13% of households had an influenza case, of which 13 (22%) reported >1 case. A total of 81% of participants reported receipt of one dose of the 2019-2020 influenza vaccine, including 91% of influenza A and 90% of influenza B cases, and 84% received the 2020-2021 influenza vaccine. Like WA DOH, we observed a wave of influenza B cases followed by influenza A in 2019-2020. During influenza season 2020-2021, WA DOH reported 9 positive influenza tests and none observed in our study. Commonly, influenza case-patients reported were fever, cough, rhinorrhea, and fatigue. GI symptoms were more common in children than adults. Of the cases, 92% of influenza A and 78% of influenza B occurred in children. Conclusion. Influenza illness in 2019-2020 was initially influenza B, and subsequently replaced by influenza A. Most cases were in children and adolescents, despite at least one dose of influenza vaccine. Symptoms were widely distributed and similar between influenza A and B. Influenza incidence in our cohort declined to zero with the rise of SARS-CoV-2 cases and widespread mitigation efforts. (Figure Presented).

4.
Open Forum Infectious Diseases ; 9(Supplement 2):S756, 2022.
Article in English | EMBASE | ID: covidwho-2189926

ABSTRACT

Background. Characterizing SARS-CoV-2 outbreaks on university campuses is critical for informed public health measures and understanding transmission dynamics. Figure 1. Dropbox and Kiosk Samples Collected September 10, 2021 to April 23, 2022. Methods. Faculty, staff, and students at a major public university in Seattle, WA, USA were enrolled in a COVID-19 testing study. Individuals could test using observed self-swabs at on-campus kiosks or unobserved self-swabs using a kit and returning it to a dropbox on campus. Sample collection volume for observed self-swabs was limited by staffing and space. All samples were returned to the laboratory and tested for SARS-CoV-2 by qRT-PCR. Results. From September 10, 2021 to April 23, 2022, 38,400 individuals were enrolled in the study. Of these individuals, 5,089 used dropboxes only, 14,421 used kiosks only, and 5,820 used both. A total of 21,653 dropbox swabs and 75,493 observed self-swabs were collected. Median age was similar between individuals using dropboxes and observed self-swabs (20 vs. 22 years). A greater proportion of dropbox users were students compared to faculty and staff (students made up 83% of dropbox only population, 75% of kiosk only, and 86% of both, chi2 p-value< 0.0001). Symptom data was reported for 65,349 swabs. Dropbox users were less likely to have symptoms compared to observed self-swab users (24% of swabs vs. 54%, chi2 p-value< 0.0001). SARS-CoV-2 positivity was slightly lower for dropboxes compared to kiosks (4% vs. 5%;p=0.001). Dropboxes were highly utilized during periods of increased testing demand, including after academic breaks and variant emergence (Figure 1). Of the total tests distributed for use, a greater proportion of dropbox kits were unable to be resulted (6%) compared to observed self-swab kits (0.02%). Conclusion. Dropboxes provided a flexible, high-volume collection method at times of increased testing demand. Individuals who used dropboxes were less likely to report symptoms and slightly less likely to test positive, suggesting a role for dropbox utilization in high-risk asymptomatic individuals during periods of high community transmission on a university campus.

5.
Open Forum Infectious Diseases ; 9(Supplement 2):S750, 2022.
Article in English | EMBASE | ID: covidwho-2189915

ABSTRACT

Background. Non-pharmaceutical interventions (NPIs), such as masking and social distancing, can reduce SARS-CoV-2 transmission. Longitudinal behavioral data in individuals with acute respiratory illness (ARI) during the COVID-19 pandemic are limited. We describe changes in adherence to NPIs and the impact of ARIs on work or school in families before and during the COVID-19 pandemic. Methods. From November 2019 to June 2021, households with school-aged children in King County, WA, were remotely monitored on a weekly basis for symptoms of respiratory illness. Participants with ARI (cough or >=2 qualifying symptoms) were asked about illness-related behavior changes (e.g. masking, isolation, hand hygiene, surface cleaning, public transit use) and impacts on school/work 7 days after initial symptom report. Using generalized estimating equations for household clusters, we compared the frequency of behavior changes and school/work impact during 3 time periods: the pre-/early COVID-19 pandemic period (11/14/19-3/22/20), prevaccine period (3/23/20-12/10/20), and post-COVID-19 vaccine period (12/11/ 20-6/19/21). Results. Of 1861 participants in 470 households, 695 (37%, from 70% of households) reported 1157 ARIs. Over the 3 time periods, the percent of ill participants who reported staying home (34 vs 34 vs 54%, respectively, P< .001), avoiding contact with others (25 vs 28 vs 45%, P< .001), and masking (3 vs 23 vs 38%, P< .001) increased (Fig 1A). Other illness-related behaviors, including washing hands and disinfecting surfaces, were unchanged over time. The percent of ill participants who worked from home (7 vs 9 vs 3%, P= .02) and missed work due to ARI (13 vs 8 vs 8%, P= .03) decreased over time (Fig 1B). Figure 1A. Participant reported illness-related health behaviors in the past week-Seattle, WA, 2019-2021. Figure 1B. Participant reported illness-related school or work impact in the past week due to illness - Seattle, WA, 2019-2021 Time periods were defined as: Period 1: 11/14/19 - 3/22/20 (pre-/early COVID-19 pandemic), Period 2: 3/23/20 - 12/10/20 (post-Washington State Stay at Home order), and Period 3: 12/11/20 - 6/19/21 (United States Food and Drug Administration Emergency Use Authorization for the Pfizer-BioNTech COVID-19 vaccine for those 16 years and older). Illness was defined per Acute Respiratory Illness (ARI) case definition: cough or two qualifying symptoms (fever, sore throat, runny nose, muscle or body aches, headache, difficulty breathing, fatigue, nausea or vomiting;for participants < 18 years of age, ear pain or drainage, rash, and diarrhea were also qualifying symptoms). Conclusion. As theCOVID-19 pandemic progressed, households with school-aged children engaged in isolation, social distancing, and masking more frequently in response to ARI. The impact of ARIs on work decreased during the pandemic.

6.
Open Forum Infectious Diseases ; 9(Supplement 2):S633-S634, 2022.
Article in English | EMBASE | ID: covidwho-2189864

ABSTRACT

Background. The need for community surveillance of respiratory viruses in high-risk settings such as homeless shelters has been underscored by the COVID-19 pandemic. Here, we show that sampling high-touch surfaces is a low-cost, minimally intensive means of community respiratory virus surveillance. Methods. Environmental samples were collected weekly from adult and family homeless shelters in King County, WA from November 2019 - April 2020. At times when residents were present, a 10cm2 area of selected high-touch surfaces were swabbed and bioaerosol samples were collected in high-traffic areas. Surfaces included entrance and restroom doorknobs, counters, and surfaces unique to each shelter. Study staff collected mid-turbinate swabs from shelter resident participants aged > 3 months with symptoms of acute respiratory illness (ARI). All samples were tested by RT-PCR for 27 viruses. From January 1, 2020 onward, samples were also tested for SARS-CoV-2. Results. A total of 788 environmental swabs, 1509 nasal swabs, and 98 bioaerosol samples from 6 adult and 3 family shelters were tested. Adenovirus (109 positive swabs, 13.8% of tested swabs), rhinovirus (107, 13.6%) and human bocavirus (62, 7.9%) were the most frequently detected viruses in surface swabs. Rhinovirus (160, 10.6%), human coronaviruses (79, 5.24%) and influenza B (43, 2.85%) were the most detected in nasal swabs. All viruses detected in nasal swabs were found in surface swabs. Of 9 surfaces, exterior bathroom doorknobs were the physical location with the highest number of pathogens detected. SARS-CoV-2 was first detected in surface swabs on 3/20/20, and in nasal swabs on 3/10/20. Bioaerosol samples detected virus in a low percentage of samples relative to surface and nasal swabs. Table 1 Count and period prevalence of environmental viral detection by shelter type, November 18, 2019 - April 10, 2020. (Figure Presented) Conclusion. Respiratory viruses detected through environmental sampling in homeless shelters were similar to the viruses detected from ARI episodes in study participants. Environmental surface sampling presents a plausible, minimally invasive method of surveillance for both endemic and emerging respiratory pathogens, as evidenced by the detection of SARS-CoV-2 during the early stages of the pandemic. Further research could focus on sampling public locations for broader community surveillance and culturing viruses found on these surfaces.

7.
Open Forum Infectious Diseases ; 9(Supplement 2):S585, 2022.
Article in English | EMBASE | ID: covidwho-2189840

ABSTRACT

Background. Human parainfluenza viruses (HPIV) cause respiratory illness in individuals of all ages. However, HPIV epidemiology data in people experiencing homelessness (PEH) are limited. Methods. We analyzed cross-sectional data from a clinical trial and SARS-CoV-2 surveillance study in 23 homeless shelters in King County, Washington from October 2019-May 2021. Questionnaires and nasal swab specimens were obtained from eligible participants at enrollment. Between October 2019-March 31, 2020, participants included those aged > 3 months with acute respiratory illness. Monthly shelter surveillance was also conducted where participants were recruited regardless of symptoms. With the community spread of SARS-CoV-2, the study design transitioned from a clinical trial to a SARS-CoV-2 surveillance study which expanded enrollment eligibility to include participants with or without symptoms from April 1, 2020, onward. Participants were not followed longitudinally but were permitted to enroll multiple times during the study period. Specimens were tested for HPIV 1-4 and other respiratory viruses using RT-PCR. Results. Among 14,464 specimens, 32 were HPIV-positive from 29 participants (median age 9 years, range 0.3-64 years;45% female;28% Black;10% with chronic conditions) of which 59% were children. Family shelters had the highest percentage of HPIV infections (Table). HPIV was detected every month before the community spread of SARS-CoV-2. All HPIV-positive samples in May 2021 came from a single family shelter (Figure). Only 67% of HPIV-positive participants had symptoms with runny nose, cough and sore throat the most commonly reported. HPIV codetection with other respiratory viruses occurred in 19% of HPIV-positive specimens;Rhinovirus co-detection (16%) was the most common. Human Parainfluenza Encounters by Shelter Type Before and After April 1, 2020 Human Parainfluenza Positive Samples by Shelter Type Among Unique Participants Conclusion. HPIV affected PEH of all ages with most cases in shelters with children. Coinciding with community-wide SARS-CoV-2 mitigation efforts, the number of HPIV infections were reduced. However, a cluster of HPIV infections still occurred within one family shelter. Shelter-specific public health measures including nonpharmaceutical interventions used during the COVID-19 pandemic may reduce HPIV infections among residents.

8.
Technology Pedagogy and Education ; 2022.
Article in English | Web of Science | ID: covidwho-2186859

ABSTRACT

This qualitative research involved the development of 12 weeks of twice-weekly virtual maker professional learning (PL) sessions for K-12 and post-secondary educators at the beginning of the COVID-19 pandemic. The sessions were developed by four researchers from a maker lab in Ontario, Canada that moved entirely online in March 2020. The research question driving the study was: what are best practices related to virtual maker professional learning? Findings and implications related to this question include: a) technical issues should be anticipated and addressed in advance of each session;b) simple, hands-on activities are most effective for online maker professional learning;c) collaboration are pivotal to a rich online maker professional learning experience;d) using free, virtual tools is imperative for equitable access and learning;and e) adaptability is key when working with a diversity of learners/teachers from varied subjects and divisions.

9.
Nature Reviews. Microbiology. ; 18:18, 2023.
Article in English | MEDLINE | ID: covidwho-2185916

ABSTRACT

In late 2020, after circulating for almost a year in the human population, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exhibited a major step change in its adaptation to humans. These highly mutated forms of SARS-CoV-2 had enhanced rates of transmission relative to previous variants and were termed 'variants of concern' (VOCs). Designated Alpha, Beta, Gamma, Delta and Omicron, the VOCs emerged independently from one another, and in turn each rapidly became dominant, regionally or globally, outcompeting previous variants. The success of each VOC relative to the previously dominant variant was enabled by altered intrinsic functional properties of the virus and, to various degrees, changes to virus antigenicity conferring the ability to evade a primed immune response. The increased virus fitness associated with VOCs is the result of a complex interplay of virus biology in the context of changing human immunity due to both vaccination and prior infection. In this Review, we summarize the literature on the relative transmissibility and antigenicity of SARS-CoV-2 variants, the role of mutations at the furin spike cleavage site and of non-spike proteins, the potential importance of recombination to virus success, and SARS-CoV-2 evolution in the context of T cells, innate immunity and population immunity. SARS-CoV-2 shows a complicated relationship among virus antigenicity, transmission and virulence, which has unpredictable implications for the future trajectory and disease burden of COVID-19.

10.
Alzheimer's & Dementia ; 18 Suppl 2:e068017, 2022.
Article in English | MEDLINE | ID: covidwho-2172409

ABSTRACT

BACKGROUND: The COVID-19 pandemic has limited in-lab cognitive testing. While at-home alternatives exist (testing over the phone), differences in test design and delivery complicate direct comparison of most in-lab and at-home tests. Here we describe the design, infrastructure, and implementation of the California Cognitive Assessment Battery (CCAB), a cognitive test battery and administration system. Using automated remote administration over cellular networks, identical computerized cognitive tests can be administered at-home or in the lab.

11.
Hepatology ; 76(Supplement 1):S336-S337, 2022.
Article in English | EMBASE | ID: covidwho-2157779

ABSTRACT

Background: Screening for HCV is the first critical decision point for preventing morbidity and mortality from HCV cirrhosis and hepatocellular carcinoma, and will ultimately contribute to global elimination of a curable disease. This study aims to portray the changes over time in HCV screening rates and the screened population characteristics following the 2020 implementation of an EHR alert for universal screening in the outpatient setting in a large healthcare system in the US mid-Atlantic region. Method(s): Data was ed from the EHR on all outpatients from 1/1/2017 through 10/31/2021, including individual demographics and their HCV antibody screening dates. Mixed effects multivariable regression analyses were performed to compare the timeline and characteristics of those screened and un-screened for a limited period from 1/1/2020 to 10/31/2020 and centered on the EHR alert implementation. Result(s): Absolute number of screens increased by 103% after the implementation of the EHR alert. When comparing the five-month period before and after the EHR alert, the odds of being screened at an outpatient visit increased by 62% from 17 to 27 screens per 1,000 outpatient visits. Also during this time period, patients with Medicaid were more likely to be screened than private insurance (ORadj 1.10, [CI95: 1.05, 1.15]), females more likely than males (1.26, [1.20, 1.32]);Black race more than White (1.59, [1.53, 1.64]);while those with Medicare were less likely than private insurance (0.62, [0.62, 0.65]). Over the entire 58-month period, the HCV Ab positivity rate decreased from 4.2% to 1.5%. Conclusion(s): Implementation of a universal HCV screening EHR alert was followed by a large increase in absolute screens and screening rates in the outpatient setting, despite the concurrent onset of the COVID-19 pandemic. These findings support that such an alert could play a crucial role in identification and subsequent elimination of HCV. Females, Black race and Medicaid patients were screened at higher rates, suggesting possible bias toward certain groups. Targeted testing in addition to universal screening remains a need despite much higher screening rates -expectedly, the proportion screened decreased, however the absolute number of HCV positive individuals decreased over time (data not shown). Our findings suggest that an EHR alert for universal screening could play a crucial role as the first step in identification and then elimination of HCV.

12.
Trials ; 23(1):980, 2022.
Article in English | PubMed | ID: covidwho-2153657

ABSTRACT

BACKGROUND: The aim of this protocol is to describe the study protocol changes made and subsequently implemented to the Pediatric Guideline Adherence and Outcomes (PEGASUS) Argentina randomized controlled trial (RCT) for care of children with severe traumatic brain injuries (TBI) imposed by the COVID-19 pandemic. The PEGASUS study group met in spring 2020 to evaluate available literature review guidance and the study design change or pausing options due to the potential interruption of research. METHODS: As a parallel cluster RCT, pediatric patients with severe TBIs are admitted to 8 control (usual care) and 8 intervention (PEGASUS program) hospitals in Argentina, Chile, and Paraguay. PEGASUS is an intervention that aims to increase guideline adherence and best practice care for improving patient outcomes using multi-level implementation science-based approaches. Strengths and weaknesses of proposed options were assessed and resulted in a decision to revert from a stepped wedge to a parallel cluster RCT but to not delay planned implementation. DISCUSSION: The parallel cluster design was considered more robust and flexible to secular interruptions and acceptable and feasible to the local study sites in this situation. Due to the early stage of the study, the team had flexibility to redesign and implement a design more compatible with the conditions of the research landscape in 2020 while balancing analytical methods and power, logistical and implementation feasibility, and acceptability. As of fall 2022, the PEGASUS RCT has been active for nearly 2 years of implementation and data collection, scheduled to be completed in in fall 2023. The experience of navigating research during this period will influence decisions about future research design, strategies, and contingencies. TRIAL REGISTRATION: Pediatric Guideline Adherence and Outcomes-Argentina. Registered with ClinicalTrials.gov Identifier NCT03896789 on April 1, 2019.

13.
Journal of Managed Care and Specialty Pharmacy ; 28(10 A-Supplement):S108-S109, 2022.
Article in English | EMBASE | ID: covidwho-2092985

ABSTRACT

BACKGROUND: Digital therapeutics (DTx) represent a growing market, accelerated over the last two years by the COVID-19 pandemic. As more DTx emerge, healthcare decision makers (HCDMs) are tasked with navigating a crowded and highly variable market to ensure patients have access to treatment options that can potentially improve outcomes. There is limited evidence evaluating how DTx products are perceived from the payer perspective. OBJECTIVE(S): To assess payer perceptions on the current and future state of DTx global trends and evidence generation needs. METHOD(S): A double-blind web-based survey was fielded from April 2022 to May 2022 to HCDMs to gather insights on existing and anticipated DTx trends. RESULT(S): There were 50 HCDMs who completed the survey. Respondents predicted that DTx will expand to new disease areas outside of mental health, diabetes, and cardiology (70%) and that more prescription DTx products will be covered (56%) over the next 18 months. Considering COVID- 19, respondents were at least somewhat likely to allow virtual assistance (64%) and API transfer (68%) for benefits verification. A MaxDiff trade-off exercise showed from an evidentiary needs perspective, head-to-head comparison studies (81) followed by prospective randomized controlled trials (74) were considered the best evidence options in terms of usefulness for DTx review, and objective clinical effectiveness (81) and total cost of care offset (66) were priorities for health outcomes data. Respondents (78%) noted that evidence demonstrating long-term efficacy and specific disease-state management were absolutely needed to determine coverage for new DTx. 48% considered two years as the best definition of long-term efficacy and most (68%) were at least interested in discussions about piloting a DTx to gather real-world evidence pending more information. CONCLUSION(S): The results indicate that HCDMs expect the market to continue to expand into new therapeutic areas and that more prescription DTx will obtain coverage. Evidence of long-term efficacy demonstrated over at least two years and pilot programs may be instrumental in optimizing DTx HCDM evaluation. Stakeholder alignment across the industry will help shape the future of DTx and facilitate appropriate patient access.

14.
56th Annual Conference on Information Sciences and Systems, CISS 2022 ; : 25-30, 2022.
Article in English | Scopus | ID: covidwho-1831733

ABSTRACT

With the continuous rise of the COVID-19 cases worldwide, it is imperative to ensure that all those vulnerable countries lacking vaccine resources can receive sufficient support to contain the risks. COVAX is such an initiative operated by the WHO to supply vaccines to the most needed countries. One critical problem faced by the COVAX is how to distribute the limited amount of vaccines to these countries in the most efficient and equitable manner. This paper aims to address this challenge by first proposing a data-driven risk assessment and prediction model and then developing a decision-making framework to support the strategic vaccine distribution. The machine learning-based risk prediction model characterizes how the risk is influenced by the underlying essential factors, e.g., the vaccination level among the population in each COVAX country. This predictive model is then leveraged to design the optimal vaccine distribution strategy that simultaneously minimizes the resulting risks while maximizing the vaccination coverage in these countries targeted by COVAX. Finally, we corroborate the proposed framework using case studies with real-world data. © 2022 IEEE.

15.
Cognitive and Behavioral Practice ; 29(1):198-213, 2022.
Article in English | Web of Science | ID: covidwho-1798231

ABSTRACT

The Safe Alternatives for Teens and Youth (SAFETY) treatment was developed to decrease the risk of repeat suicidal and self-harm behavior in youth presenting with elevated suicide risk. This paper uses case illustrations to demonstrate the SAFETY treatment, building upon the companion paper describing our "incubator " treatment development model and process (Asarnow et al., 2022). As illustrated in the second case illustration, the incubator model approach was particularly useful during the COVID-19 pandemic switch to telehealth. SAFETY specifically targets suicide and self-harm risk reduction using an individually tailored principle-guided approach, grounded in a case conceptualization that identifies cognitive-behavioral processes and reactions that contribute to increased suicide attempt risk and explains the youth's suicidal/self-harm behavior within the context of his or her broader social systems. The SAFETY treatment has been tested in two treatment development trials, and results support the efficacy of SAFETY for preventing suicide attempts in adolescents presenting with recent self-harm.

16.
2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1759018

ABSTRACT

How best to apply vaccines to a population is an open problem. It is trivial to derive intuitive strategies, but until tested, their efficacy i s n ot k nown. T his p roblem i s particularly challenging when considering the dynamics of social contact networks and their changes over time. A system for automatically discovering tested vaccination strategies with evolutionary computation has been improved upon to include additional graph metrics and to generate vaccination strategies for dynamic graphs, something that is expected of real social networks within communities. The system’s ability to generate effective strategies was demonstrated along with a comparison of the strategies developed when fit t o a s tatic g raph v ersus a d ynamic g raph. I t w as observed that the additional computational resources required to generate strategies on a dynamic graph may not be necessary as strategies developed for static graphs performed similarly well;however, the authors are careful to acknowledge that results may differ significantly w hen a djusting t he s ystems m any parameters. © IEEE 2021.

17.
2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1759016

ABSTRACT

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, led to a global health crisis, with more than 157 million cases confirmed infected by May 2021. Effective medication is desperately needed. Predicting drug-target interaction (DTI) is an important step to discover novel uses of chemical structures. Here, we develop a pipeline to predict novel DTIs based on the proteins of the coronavirus. Different datasets (human/SARSCoV-2 Protein-Protein interaction (PPI), Drug-Drug similarity (DD sim), and DTIs) are used and combined. After mapping all datasets onto a heterogeneous graph, path-related features are extracted. We then applied various machine learning (ML) algorithms to model our dataset and predict novel DTIs among unlabeled pairs. Possible drugs identified by the models with a high frequency are reported. In addition, evidence of the efficiency of the predicted medicines by the models against COVID-19 are presented. The proposed model can then be generalized to contain other features that provide a context to predict medicine for different diseases. © 2021 IEEE.

18.
Journal of Clinical Ethics ; 32(4):358-360, 2021.
Article in English | MEDLINE | ID: covidwho-1589835

ABSTRACT

Crisis standards of care have been widely developed by healthcare systems and states in the United States during the COVID-19 pandemic, and in some rare cases have actually been used to allocate medical resources. All publicly available U.S. crisis standards of care with a mechanism for allocating scarce resources make use of the Sequential Organ Failure Assessment (SOFA) score in hopes of assigning scarce resources to those patients who are more likely to survive. We reflect on the growing body of evidence suggesting that the SOFA score has limited accuracy in predicting mortality among patients hospitalized with COVID-19 and that the SOFA score systematically disfavors Black patients. Use of the SOFA score for allocating scarce resources may therefore result in Black patients with equal likelihood of survival being deprived of life-saving medical resources. There is also a risk of injustice for patients with non-COVID-19 diagnoses, for whom the SOFA score may be a more accurate prognostic score, but who might nevertheless be unfairly (de)prioritized when assessed alongside COVID-19 patients using the same scoring system. For these reasons we recommend that the SOFA score not be used for triage purposes during the COVID pandemic, and that a national effort be made to develop and empirically test crisis standards of care in advance of the next public health emergency.

19.
IEEE Symposium Series on Computational Intelligence (IEEE SSCI) ; : 2975-2984, 2020.
Article in English | Web of Science | ID: covidwho-1431477

ABSTRACT

A new AI system is being developed to optimize vaccination strategies based on the structure and shape of a community's social contact network. The technology is minimally constrained and not hound by preconceived notions or human biases. With this come novel outside the box strategies;however, the system is only capable of optimizing what it is instructed to optimize, and does not consider any ethical or political concerns. With the growing concern for systematic discrimination as a result of artificial intelligence, we acknowledge a number of relevant issues that may arise as a consequence of our new technology and categorize them into three classes. We also introduce four normative ethical approaches that are used as a framework for decision-making. Despite the focus on vaccination strategies, our goal is to improve the discussions surrounding public concern and trust over artificial intelligence and demonstrate that artificial intelligence practitioners are addressing these concerns.

20.
Psychosomatic Medicine ; 83(7):A53-A53, 2021.
Article in English | Web of Science | ID: covidwho-1405763
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