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1.
2021 Control Conference Africa, CCA 2021 ; 54:151-156, 2021.
Article in English | Scopus | ID: covidwho-1945144

ABSTRACT

Congestion is a phenomenon that impacts most cities in the world. Due to car emissions, it is a significant source of pollution. Even though mobility restrictions can reduce congestion and emissions, essential activities still need cars. With lockdown measures during the global pandemic of Covid-19, measuring essential traffic data has been made possible. This paper concerns analysis and modelling of such essential traffic. It appears that congestion dynamics of essential traffic exhibits dynamics than can be represented with a linear model. This paper introduces such a model and provide a method to jointly estimate the parameters and the model input. The model is validated with data collected in Johannesburg, South Africa. Copyright © 2021 The Authors.

2.
Blood ; 138:3019, 2021.
Article in English | EMBASE | ID: covidwho-1582282

ABSTRACT

Background: Patients (pts) with malignancies are at increased risk of morbidity and mortality from COVID-19. Among these pts, some of the higher case fatality ratios (CFR) reported are among pts with myeloid malignancies, ranging from 37 to 50% (Mehta V, Cancer Discov 2020;Ferrara F, Leukemia 2020). Levine Cancer Institute (LCI) has a robust hematologic malignancy and cellular therapy program that serves many pts with myeloid malignancies, seeing nearly 100 new diagnoses of acute myeloid leukemia per year. A strategy to mitigate risks associated with COVID-19 was established at LCI in partnership with Atrium Health's (AH) Hospital at Home (HAH). HAH was a system wide platform using telemedicine and home health services to assess and monitor COVID-19 + pts at high risk of complications. To augment HAH for our medically complex cancer pts, a virtual health navigation process involving expertise from across LCI, including a specialized nurse navigation team, was developed to rapidly identify LCI pts + for SARS-CoV-2, monitor them under physician supervision, and escalate care as needed with AH HAH. Along with the navigation platform, data-driven guidelines for detecting, monitoring, and managing LCI pts + for SARS-CoV-2 were swiftly employed across the extensive LCI network. Herein we report on the outcomes for LCI pts with myeloid malignancies + for SARS-CoV-2 and outline the employed risk mitigation strategies and their potential impact on these outcomes. Methods: An automated daily list of LCI pts + for SARS-CoV-2 was provided by AH Information Services. Each pt's chart was reviewed by a nurse navigator for hematologic or oncologic diagnosis, outpatient or inpatient status, and COVID-19 symptoms. Pts without a cancer diagnosis were not assigned a navigator. If hospitalized, a pt was not assigned a navigator;following discharge, if enrolled in HAH, a navigator was assigned. In collaboration with HAH, an algorithm for directing care was utilized (Figure 1). A diagnosis-specific navigator contacted and screened the pt with an assessment tool, which scored pts for surveillance and treatment needs (Table 1). Documentation was forwarded to the primary hematologist/oncologist. Comprehensive guidelines for testing, scheduling, management of + pts, research, and process changes were created, disseminated, and actively updated through LCI's EAPathways. For outcome analysis for pts with myeloid malignancies, pt vital status was updated through data cutoff (7/3/21). Results: From inception on 3/20/20 to 12/2/20, 974 LCI patients were identified as SARS-CoV-2 + and reviewed for nurse navigation. Of the 974 pts, including pts with benign and malignant diagnoses, 488 were navigated. Among all SARS-CoV-2 + LCI pts, 145 (15%) had a hematologic malignancy, including 37 (4%) pts with myeloid malignancies. Characteristics are shown in Table 2. Of the 37 pts, 18 (49%) were navigated. 70% with myeloid malignancies were on active treatment at the time of + test. Nearly 50% of those on active treatment were navigated. 46% were hospitalized with COVID-19, with this being the main reason for no assigned navigator. 24% of hospitalized pts were eventually assigned a navigator. Only 3 pts had undergone allogeneic stem cell transplantation (allo-SCT) with a median time from transplant to detection of SARS-CoV-2 of 9 months (range, 7-23). 2 out of 3 cases post allo-SCT were asymptomatic. No pt died from COVID-19 following allo-SCT. Among the navigated pts with myeloid malignancies, there was no death related to COVID-19. 4 pts, all of whom were hospitalized, died from COVID-19 (N=2, myelodysplastic syndrome with 1 on azacitidine;N=2, myeloproliferative neoplasm, both on hydrea). A CFR of 11% was demonstrated for LCI pts with myeloid malignancies. Conclusions: A multidisciplinary response strategy liaising between AH HAH and LCI followed, assessed, and assisted cancer pts + for SARS-CoV-2. With our embedded nurse navigation team's specialized attention along with enhanced physician oversight and close collaboration with AH HAH, opportunities f r care escalation or adjustments in cancer-focused care were promptly identified. In this setting, among the high-risk population of pts with myeloid malignancies, a lower CFR than has been reported was observed. A virtual navigation platform with HAH capabilities is a feasible, safe, and effective way to monitor and care for this high-risk population. [Formula presented] Disclosures: Moyo: Seattle Genetics: Consultancy. Chai: Cardinal Health: Membership on an entity's Board of Directors or advisory committees. Avalos: JUNO: Membership on an entity's Board of Directors or advisory committees. Grunwald: Amgen: Consultancy;Agios: Consultancy;Astellas: Consultancy;Daiichi Sankyo: Consultancy;Stemline: Consultancy;Bristol Myers Squibb: Consultancy;PRIME: Other;Trovagene: Consultancy;Blueprint Medicines: Consultancy;AbbVie: Consultancy;Med Learning Group: Other;Pfizer: Consultancy;Sierra Oncology: Consultancy;Janssen: Research Funding;Incyte: Consultancy, Research Funding;Gilead: Consultancy;MDEdge: Other;PER: Other;Cardinal Health: Consultancy;Karius: Consultancy. Copelan: Amgen: Consultancy.

3.
Blood ; 138:1756, 2021.
Article in English | EMBASE | ID: covidwho-1582193

ABSTRACT

Background: Brexucabtagene autoleucel (brexu-cel) is the first CD19 chimeric antigen receptor T-cell (CAR T) therapy approved for use in patients (pts) with relapsed mantle cell lymphoma (MCL). The ZUMA-2 trial demonstrated that brexu-cel induces durable remissions in these pts with an ORR of 85% (59% CR), estimated 12-month PFS rate of 61%, and similar toxicity profile to other CAR T therapies (Wang et al, NEJM 2020). We conducted a multicenter, retrospective study of pts treated with commercial brexu-cel to evaluate its safety and efficacy in the non-trial setting. Methods: We reviewed records of pts with relapsed MCL across 12 US academic medical centers. Pts who underwent leukapheresis between July 2020 and June 2021 with the intent to proceed to commercial brexu-cel were included. Baseline demographic and clinical characteristics were summarized using descriptive statistics. Survival curves were generated using the Kaplan-Meier method, and univariate models were fit to identify predictors of post-CAR T outcomes. Results: Fifty-five pts underwent leukapheresis. There were 3 manufacturing failures. Baseline characteristics of the 52 pts who received brexu-cel are summarized in Table 1. Median age was 66 yrs (range: 47-79 yrs) and 82% were male. Twenty of 29 (69%) pts with known baseline MIPI were intermediate or high risk. Seven pts had a history of CNS involvement. The median number of prior therapies was 3 (range: 2-8), including prior autologous stem cell transplant (ASCT) in 21 (40%) and prior allogeneic transplant in 2 pts (1 with prior ASCT and 1 without). Fifty percent had relapsed within 24 months of their initial therapy. All pts had previously received a Bruton's tyrosine kinase inhibitor (BTKi), including 29 (56%) with disease progression on a BTKi. Forty (77%) pts received bridging therapy (17 BTKi, 10 BTKi + venetoclax, 6 chemo, 3 venetoclax, 2 XRT only, 1 steroids only, 1 lenalidomide + rituximab). The ORR was 88% (CR 69%) among patients who received brexu-cel. Two pts had PD on initial restaging and 3 died prior to first response assessment (without evidence of relapse). Seven pts have not completed restaging due to limited follow-up (< 3 months) and were not included in the response assessment. Five pts have progressed, including 2 with CR and 1 with PR on initial restaging. With a median follow-up of 4.2 months, the estimated 6-month PFS and OS rates were 82.7% and 89.0%, respectively. All 7 pts with prior CNS involvement were alive without relapse at last follow-up. The incidence of cytokine release syndrome (CRS) was 84% (10% grade ≥ 3) with a median time to max grade of 5 days (range: 0-10 days). There were no cases of grade 5 CRS. The incidence of neurotoxicity (NT) was 57% (31% grade ≥ 3) with a median time to onset of 7 days (range: 4-15 days). NT occurred in 4/7 pts with prior CNS involvement (3 grade 3, 1 grade 4). Grade 5 NT occurred in 1 pt who developed cerebral edema and died 8 days after infusion. Thirty-five pts received tocilizumab, 33 received steroids, 7 received anakinra, and 1 received siltuximab for management of CRS and/or NT. Post-CAR T infections occurred in 8 pts, including two grade 5 infectious AEs (covid19 on day +80 and septic shock on day +40 after infusion). Rates of grade ≥ 3 neutropenia and thrombocytopenia were 38% and 37%, respectively. Among pts with at least 100 days of follow-up and lab data available, 5/34 (15%) had persistent grade ≥ 3 neutropenia and 4/34 (12%) had persistent grade ≥ 3 thrombocytopenia at day +100. Five pts have died, with causes of death being disease progression (2), septic shock (1), NT (1), and covid19 (1). Univariate analysis did not reveal any significant associations between survival and baseline/pre-CAR T MIPI, tumor pathologic or cytogenetic features, prior therapies, receipt of steroids/tocilizumab, or pre-CAR T tumor bulk. Conclusions: This analysis of relapsed MCL pts treated with commercial brexu-cel reveals nearly identical response and toxicity rates compared to those reported on ZUMA-2. Longer follow-up is require to confirm durability of response, but these results corroborate the efficacy of brexu-cel in a population of older adults with high-risk disease features. While all 7 pts with prior CNS involvement are alive and in remission, strategies to mitigate the risk of NT in this setting need to be evaluated. Further studies to define the optimal timing of CAR T, bridging strategies, and salvage therapies for post-CAR T relapse in MCL are warranted. [Formula presented] Disclosures: Gerson: TG Therapeutics: Consultancy;Kite: Consultancy;Abbvie: Consultancy;Pharmacyclics: Consultancy. Sawalha: TG Therapeutics: Consultancy, Research Funding;Celgene/BMS: Research Funding;BeiGene: Research Funding;Epizyme: Consultancy. Bond: Kite/Gilead: Honoraria. Karmali: Janssen/Pharmacyclics: Consultancy;BeiGene: Consultancy, Speakers Bureau;Morphosys: Consultancy, Speakers Bureau;Takeda: Research Funding;Genentech: Consultancy;AstraZeneca: Speakers Bureau;Roche: Consultancy;Karyopharm: Consultancy;Epizyme: Consultancy;Kite, a Gilead Company: Consultancy, Research Funding, Speakers Bureau;BMS/Celgene/Juno: Consultancy, Research Funding;EUSA: Consultancy. Torka: TG Therapeutics: Membership on an entity's Board of Directors or advisory committees. Chow: ADC Therapeutics: Current holder of individual stocks in a privately-held company, Research Funding;AstraZeneca: Research Funding. Shadman: Abbvie, Genentech, AstraZeneca, Sound Biologics, Pharmacyclics, Beigene, Bristol Myers Squibb, Morphosys, TG Therapeutics, Innate Pharma, Kite Pharma, Adaptive Biotechnologies, Epizyme, Eli Lilly, Adaptimmune, Mustang Bio and Atara Biotherapeutics: Consultancy;Mustang Bio, Celgene, Bristol Myers Squibb, Pharmacyclics, Gilead, Genentech, Abbvie, TG Therapeutics, Beigene, AstraZeneca, Sunesis, Atara Biotherapeutics, GenMab: Research Funding. Ghosh: Genentech: Research Funding;Pharmacyclics LLC, an AbbVie Company: Consultancy, Honoraria, Research Funding, Speakers Bureau;Karyopharma: Consultancy, Honoraria;Seattle Genetics: Consultancy, Honoraria, Speakers Bureau;Janssen: Consultancy, Honoraria, Speakers Bureau;TG Therapeutics: Consultancy, Honoraria, Research Funding;Incyte: Consultancy, Honoraria;Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau;Genmab: Consultancy, Honoraria;Epizyme: Honoraria, Speakers Bureau;Bristol Myers Squibb: Consultancy, Honoraria, Research Funding, Speakers Bureau;AstraZeneca: Consultancy, Honoraria, Speakers Bureau;ADC Therapeutics: Consultancy, Honoraria;Adaptive Biotech: Consultancy, Honoraria;AbbVie: Honoraria, Speakers Bureau. Moyo: Seattle Genetics: Consultancy. Fenske: TG Therapeutics: Consultancy, Speakers Bureau;Servier Pharmaceuticals: Consultancy;Seattle Genetics: Speakers Bureau;Sanofi: Speakers Bureau;Pharmacyclics: Consultancy;MorphoSys: Consultancy;Kite (Gilead): Speakers Bureau;KaryoPharm: Consultancy;CSL Therapeutics: Consultancy;Bristol-Myers Squibb: Speakers Bureau;Biogen: Consultancy;Beigene: Consultancy;AstraZeneca: Speakers Bureau;ADC Therapeutics: Consultancy;Adaptive Biotechnologies: Consultancy;AbbVie: Consultancy. Grover: Genentech: Research Funding;Novartis: Consultancy;ADC: Other: Advisory Board;Kite: Other: Advisory Board;Tessa: Consultancy. Maddocks: Seattle Genetics: Divested equity in a private or publicly-traded company in the past 24 months;BMS: Divested equity in a private or publicly-traded company in the past 24 months;Pharmacyclics: Divested equity in a private or publicly-traded company in the past 24 months;Novatis: Divested equity in a private or publicly-traded company in the past 24 months;Janssen: Divested equity in a private or publicly-traded company in the past 24 months;Morphosys: Divested equity in a private or publicly-traded company in the past 24 months;ADC Therapeutics: Divested equity in a private or publicly-traded company in the past 24 months;Karyopharm: Divested equity in a private or publicly-traded company in the past 24 months;Beigene: Divested equity in a private or publicly-traded company in the past 24 months;Merck: Divested equity in a private or publicly-traded company in the past 24 months;KITE: Divested equity in a private or publicly-traded company in the past 24 months;Celgene: Divested equity in a private or publicly-traded company in the past 24 months. Jacobson: Kite, a Gilead Company: Consultancy, Honoraria, Other: Travel support;Humanigen: Consultancy, Honoraria, Other: Travel support;Celgene: Consultancy, Honoraria, Other: Travel support;Pfizer: Consultancy, Honoraria, Other: Travel support, Research Funding;Lonza: Consultancy, Honoraria, Other: Travel support;AbbVie: Consultancy, Honoraria;Precision Biosciences: Consultancy, Honoraria, Other: Travel support;Novartis Pharmaceuticals Corporation: Consultancy, Honoraria, Other: Travel support;Nkarta: Consultancy, Honoraria;Axis: Speakers Bureau;Clinical Care Options: Speakers Bureau. Cohen: Janssen, Adaptive, Aptitude Health, BeiGene, Cellectar, Adicet, Loxo/Lilly, AStra ZenecaKite/Gilead: Consultancy;Genentech, Takeda, BMS/Celgene, BioInvent, LAM, Astra Zeneca, Novartis, Loxo/Lilly: Research Funding.

4.
Journal of Engineering Design and Technology ; ahead-of-print(ahead-of-print):23, 2021.
Article in English | Web of Science | ID: covidwho-1371783

ABSTRACT

Purpose The purpose of this study was to investigate the perceptions of construction professionals relative to factors that affect the delivery of optimum health and safety (H&S) on construction projects during the COVID-19 pandemic. Design/methodology/approach The study adopted a quantitative design which entailed the distribution of a web-based questionnaire among construction professionals, namely, architects, construction/project managers, engineers, H&S managers and quantity surveyors working for contractors and construction consultants in Zimbabwe. The data were analysed with descriptive and inferential statistics. Factor analysis was used to reveal interrelated significant sets of factors affecting the delivery of optimum H&S. Findings Factor analysis revealed nine components/factors: change and innovation-related, monitoring and enforcement-related, production-related, access to information and health service-related, on-site facilities and welfare-related, risk assessment and mitigation-related, job security and funding-related, cost-related and COVID-19 risk perception-related factors as the significant factors affecting the delivery of optimum H&S during the COVID-19 pandemic in Zimbabwe. Research limitations/implications The results highlighted the need for social dialogue among construction stakeholders to support initiatives that will enhance the delivery of H&S on construction projects. Construction stakeholders may find the results useful in highlighting the areas that need improvement to protect workers' H&S during the pandemic. However, the small sample limits the generalisability of the results to construction sectors in other regions. Originality/value The study investigated factors affecting the delivery of optimum H&S during the COVID-19 to inform interventions to enhance H&S.

5.
Journal of Clinical Oncology ; 39(15 SUPPL), 2021.
Article in English | EMBASE | ID: covidwho-1339177

ABSTRACT

Background: Reports suggested cancer patients were at greater risk for increased morbidity and mortality from COVID-19. A process to mitigate these risks was established at Levine Cancer Institute (LCI) in partnership with Atrium Health's (AH) Hospital at Home (HAH) initiative. This virtual health navigation process employed expertise from the departments of Hematologic Oncology and Blood Disorders, Oncology, and Supportive Oncology, including a specialized nurse navigation team, to rapidly identify COVID-19 positive LCI patients, monitor them under physician supervision, and escalate care as needed with AH HAH program. Methods: AH Information Services created an automated list of LCI COVID-19 positive patients with a daily database. Each patient was reviewed by a nurse navigator. Review included hematologic or oncologic diagnosis, outpatient or inpatient status, and any COVID-19 symptoms. Once a malignant diagnosis was confirmed, a diagnosis-specific navigator contacted and screened the patient with a COVID assessment tool. Documentation was forwarded to the primary oncologist/hematologist. The tool scored patients for surveillance and treatment needs. A score of 0-2 prompted phone assessment every 48-72 hours, and score of 3-5 required every 24-48 hour calls with physician involvement when appropriate. If score of ≥6, care was escalated to LCI nurse/physician for admission to AH acute care HAH or conventional inpatient admission. Results: From inception on 3/20/2020 to data review date of 12/2/2020, 974 LCI patients were identified as COVID-19 positive and reviewed for nurse navigation (Table). Of the 974, 488 were navigated. Given limited resources, patients with benign conditions were not assigned a navigator, though a similar process was created for sickle cell disease. Of the 974, 75 are now deceased. Only 25 are deceased among the 488 navigated. Conclusions: The COVID-19 pandemic presented unprecedented circumstances to our patients and their clinicians. LCI expeditiously put policies and procedures in place to mitigate the intersection of COVID-19 and cancer. The multidisciplinary response strategy liaising between AH HAH and LCI followed, assessed, and assisted LCI COVID19 positive patients. With our embedded nurse navigation team's specialized attention along with enhanced physician oversight and close collaboration with AH HAH, opportunities for care escalation or adjustments in cancerfocused care were promptly identified. Analysis is ongoing to elucidate the lower mortality rate observed among navigated patients.

7.
Non-conventional | WHO COVID, Grey literature | ID: grc-743629

ABSTRACT

In developing countries, metropolitan cities, due to their economic activities, attract an increasing amount of commuters on a daily basis. This has led to major freeways and roads experiencing high levels of congestion and consequently high pollution levels. In 2020, due to a global pandemic of an outbreak of Corona Virus (COVID-19), the national government declared a national shutdown with only essential traffic being allowed to operate. Given the scenario of the national lock-down this allows for the statistical analysis of the impact of essential traffic on the overall transportation system. Consequently the aim of the paper was to assess the congestion and CO2 emission impact of essential traffic for the City of Johannesburg. Using an exploratory approach, we monitored and collected traffic congestion data from the Tomtom traffic index for the metropolitan city of Johannesburg, South Africa. We develop a relationship between congestion and pollution to visualise the daily variations in pollution and congestion levels. We demonstrate this by comparing variations in congestion levels in two epochs, viz the period without movement restrictions and the period whereby movement is restricted. The results reveal essential traffic on the congestion index to be below 22 percent for both weekends and weekdays. A scenario common only during weekends in 2019. Whilst for the emission index, CO2 levels are approximately less than 45 percent throughout the week. The paper concludes the investment into mining and analysing traffic data has a significantly role for future mobility planning in both the developed and developing world and, more generally, improving the quality of commuting trips in the city.

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