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The following results are related to COVID-19. Are you interested to view more results? Visit OpenAIRE - Explore.

  • COVID-19
  • Open Access
  • Research data
  • ZivaHub

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Smith, Philip; Bekker, Linda-Gail; Little, Francesca;

    These data were drawn from a cluster randomised controlled study investigating the effect of infection mitigation on the household transmission of SARS-CoV-2.  This study was conducted in Cape Town, Philippi Klipfontein district from September 2020 until August 2021.  The primary outcomes are SARS-Cov-2 PCR results and serology.  These data contain the SARS-CoV-2 serology results for households by intervention and control group.These data are stored in STATA .dta format.  Data Ethics: This study was approved by the human research ethics committee (HREC) at the University of Cape Town (HREC reference: 284/2020).  Data use resctrictions: there are no restrictions on data access. This data is only for academic and non-commercial research purposes and cannot be shared or used for commercial gain without written permission from the principal investigator. 

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZivaHub - Open Data ...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZivaHub - Open Data UCT
    Dataset . 2022
    License: CC BY
    ZivaHub
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZivaHub - Open Data ...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZivaHub - Open Data UCT
      Dataset . 2022
      License: CC BY
      ZivaHub
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Smith, Philip; Bekker, Linda-Gail; Little, Francesca;

    These data were drawn from a cluster randomised controlled study investigating the effect of infection mitigation on the household transmission of SARS-CoV-2.  This TRACE study was conducted in Cape Town, Philippi Klipfontein district from September 2020 until August 2021. The primary outcomes are SARS-Cov-2 PCR results and serology. These data are stored in STATA .dta format.  Data Ethics: This study was approved by the human research ethics committee (HREC) at the University of Cape Town (HREC reference: 284/2020).  Data use resctrictions: there are no restrictions on data access. This data is only for academic and non-commercial research purposes and cannot be shared or used for commercial gain without written permission from the principal investigator. 

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZivaHub - Open Data ...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZivaHub - Open Data UCT
    Dataset . 2022
    License: CC BY
    ZivaHub
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZivaHub - Open Data ...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZivaHub - Open Data UCT
      Dataset . 2022
      License: CC BY
      ZivaHub
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Kautondokwa, Popyeni; Ophoff, Jacques; Ruhwanya, Zainab;

    This dataset contains PLS and Bootstrapping Data. The COVID-19 pandemic has forced individuals to adopt online applications and technologies, as well as remote working patterns. However, with changes in technology and working patterns, new vulnerabilities are likely to arise. Cybersecurity threats have rapidly evolved to exploit uncertainty during the pandemic, and users need to apply careful judgment and vigilance to avoid becoming the victim of a cyber-attack. This paper explores the factors that motivate security behaviour, considering the current environmental uncertainty. An adapted model, primarily based on the Protection Motivation Theory (PMT), is proposed and evaluated using data collected from an online survey of 222 respondents from a Higher Education institution. Data analysis was performed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The results confirm the applicability of PMT in the security context. Respondents’ behavioural intention, perceived threat vulnerability, response cost, response efficacy, security habits, and subjective norm predicted self-reported security behaviour. In contrast, environmental uncertainty, attitude towards policy compliance, self-efficacy and perceived threat severity did not significantly impact behavioural intention. The results show that respondents were able to cope with environmental uncertainty and maintain security behaviour.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZivaHub - Open Data ...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZivaHub - Open Data UCT
    Dataset . 2022
    License: CC BY
    ZivaHub
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZivaHub - Open Data ...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZivaHub - Open Data UCT
      Dataset . 2022
      License: CC BY
      ZivaHub
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Peckham, Hannah; De Gruijter, Nina; Radziszewska, Ania; Ciurtin, Coziana; +5 Authors

    An online search of government websites and published literature was performed for regional data reports on COVID-19 cases that included sex as a variable from 1st January 2020 up until 1st June 2020 (Search terms: COVID-19/case/sex/country/data/death/ICU/ITU). In order to ensure unbiased representation from as many regions as possible, a cross check was done using the list of countries reporting data on ‘Worldometer’, and an attempt was made to include as many regions reporting sex data as possible. Reports were translated using Google translate if they were not in English.Data selection, extraction and synthesisReports were included if they contained sex as a variable in data describing case number, intensive treatment unit (ITU) admission, or mortality. Data were entered directly by individual researchers into an online structured data extraction table. For some sources, counts of male confirmed cases or male deaths were not provided, but percentages of male cases or male deaths were provided instead. To include these sources and avoid biases that might be introduced by their exclusion, we calculated counts of male confirmed cases and male deaths from the reported percentages with rounding to the nearest integer. We acknowledge that this approach assumes that the reported percentages are reflective of the true percentages. For some sources, data included confirmed cases and deaths of unknown sex. For these sources, the reported totals were used where the proportion of unknown sex was small. This approach was preferred to excluding cases of unknown sex in order to avoid bias. The estimates represent the proportion of known male infections and odds ratios for mortality associated with known male sex, and will differ slightly from what the true values would be if the sex had been reported for all cases. Data were available at the level of country or regional summary data representing distinct individuals for each report, but not at the level of covariates for all individuals within a study. Consequently, covariates such as lifestyle, comorbidities, testing method and case type (hospital vs. community) could not be controlled for.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZivaHub - Open Data ...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZivaHub
    Dataset . 2020
    License: CC 0
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZivaHub - Open Data ...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZivaHub
      Dataset . 2020
      License: CC 0
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Besada, Donela; Docrat, Sumaiyah; DAVIAUD, Emmanuelle; solanki, geetesh; +3 Authors

    This model assesses the potential economic burden of alcohol-related injuries in South Africa. In addition to provider costs for each injury, the model calculates number of outpatient visits, general ward inpatient days and ICU days needed per event.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZivaHub - Open Data ...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZivaHub - Open Data UCT
    Dataset . 2020
    License: CC BY
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZivaHub - Open Data ...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZivaHub - Open Data UCT
      Dataset . 2020
      License: CC BY
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Cleary, Susan; Tchuem, Cynthia Tamandjou; Geetesh Solanki; Docrat, Sumaiyah; +2 Authors

    MODEL STRATEGIESThis model assesses costs and outcomes for admitted severe and critical Covid-19 patients from time of admission to discharge or death.Two competing strategies are modelled:1. The "status quo" summarizes costs and outcomes for patients assuming usual care (no dexamethasone).2. The "dexamethasone" comparator summarizes costs and outcomes for patients assuming usual care with dexamethasone at 6mg/day over 10 days. MODEL OUTCOMESCost: mean cost (general ward and ICU) per admitted patient from the health care provider's perspective.Health outcomes: mean DALYs and deaths per admitted patient. Other: mean ICU days and inpatient days per admitted patient.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZivaHub - Open Data ...arrow_drop_down
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    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZivaHub - Open Data ...arrow_drop_down
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      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Cleary, Susan; Wilkinson, Tommy; Tchuem, Cynthia Tamandjou; Docrat, Sumaiyah; +4 Authors

    As the COVID-19 pandemic progresses, the demands on the health care system will intensify and will result in critical shortages of resources (hospital beds, intensive care unit (ICU) beds, ventilators, medical workforce), particularly in the public sector. Given the expected downturn in an already weak economy coupled with the increased demand for government resources for economic relief and other measures, the ability of government to commit additional funding to an already under-funded public health sector is limited. Within this context, it is imperative that available public resources are used fairly, optimally and efficiently - we simply cannot afford to waste any resources. This rapid economic evaluation intends to inform Covid-19 health system decision-making. In this report, we respond to the question: What is the cost-effectiveness of ICU care versus treatment in general ward in supporting severe Covid-19 cases? Given the emergent nature of Covid-19 and the huge uncertainty in key parameters, a simple excel-based model is provided. This simplicity is designed to facilitate understanding. In addition, the framework allows for parameters to be varied and ultimately updated as sufficient local data become available.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZivaHub - Open Data ...arrow_drop_down
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    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZivaHub - Open Data ...arrow_drop_down
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      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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    Authors: Ryan, Peter G; Maclean, Kyle; Weideman, Eleanor;

    The lockdowns instigated to slow the spread of the COVID-19 pandemic offered a unique opportunity to assess how restrictions on human activity affect street litter. We recorded daily litter arrival rates for 50 days in two South African cities from the time of strictest lockdown through two successive easings in regulations. The strict lockdown had no marked impact on litter composition, which was dominated by convenience foods and beverages (29% by number, 34% by mass) and tobacco products (33% by number, 3% by mass). The ban on the sale of tobacco products during the lockdown did not greatly reduce the number of cigarette butts and associated packaging. Vehicle parts accounted for <1% of litter items (2% by mass) whereas household waste spilled from bins prior to or during collection accounted for 3% of litter items (14% by mass). Street litter loads decreased roughly by a factor of three during the strict lockdown. The increase in litter was gradual, suggesting a reduction in compliance with regulations as the lockdown continued. Our results show a clear link between human activity levels and littering.

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    ZivaHub - Open Data UCT
    Dataset . 2020
    License: CC BY
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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      ZivaHub - Open Data UCT
      Dataset . 2020
      License: CC BY
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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    Authors: Cleary, Susan; Tamandjou Tchuem, Cynthia; solanki, geetesh; Wilkinson, Tommy;

    MODEL STRATEGIESThis model assesses costs and outcomes for admitted severe and critical Covid-19 patients from time of admission to discharge or deathFour competing strategies are modelled:1. The "status quo" summarizes costs and outcomes for patients assuming no dexamethasone or remdesivir2. The "dexamethasone" comparator summarizes costs and outcomes for patients assuming dexamethasone at 6mg/day3. The "remdesivir" comparator summarizes costs and outcomes for patients assuming remdesivir at 100mg/day4. The "remdesivr plus dexamethasone" comparator summarizes costs and outcomes for patients assuming remdesivir at 100mg/day plus dexamethasone at 6mg/dayMODEL OUTCOMESCost: mean cost (general ward, ICU, dexamethasone and remdesivir as appropriate) per admitted patient from the health care provider's perspectiveHealth outcomes: mean DALYs and deaths per admitted patient Other outcomes: mean ICU days and inpatient days per admitted patientBudget impact: mean costs (or savings) associated with intervention implementation

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    ZivaHub - Open Data UCT
    Dataset . 2020
    License: CC BY
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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      ZivaHub - Open Data UCT
      Dataset . 2020
      License: CC BY
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Smith, Philip; Bekker, Linda-Gail; Little, Francesca;

    These data were drawn from a cluster randomised controlled study investigating the effect of infection mitigation on the household transmission of SARS-CoV-2.  This study was conducted in Cape Town, Philippi Klipfontein district from September 2020 until August 2021.  The primary outcomes are SARS-Cov-2 PCR results and serology.  These data contain the SARS-CoV-2 serology results for households by intervention and control group.These data are stored in STATA .dta format.  Data Ethics: This study was approved by the human research ethics committee (HREC) at the University of Cape Town (HREC reference: 284/2020).  Data use resctrictions: there are no restrictions on data access. This data is only for academic and non-commercial research purposes and cannot be shared or used for commercial gain without written permission from the principal investigator. 

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    ZivaHub - Open Data UCT
    Dataset . 2022
    License: CC BY
    ZivaHub
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZivaHub - Open Data UCT
      Dataset . 2022
      License: CC BY
      ZivaHub
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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    Authors: Smith, Philip; Bekker, Linda-Gail; Little, Francesca;

    These data were drawn from a cluster randomised controlled study investigating the effect of infection mitigation on the household transmission of SARS-CoV-2.  This TRACE study was conducted in Cape Town, Philippi Klipfontein district from September 2020 until August 2021. The primary outcomes are SARS-Cov-2 PCR results and serology. These data are stored in STATA .dta format.  Data Ethics: This study was approved by the human research ethics committee (HREC) at the University of Cape Town (HREC reference: 284/2020).  Data use resctrictions: there are no restrictions on data access. This data is only for academic and non-commercial research purposes and cannot be shared or used for commercial gain without written permission from the principal investigator. 

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    ZivaHub - Open Data UCT
    Dataset . 2022
    License: CC BY
    ZivaHub
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      ZivaHub - Open Data UCT
      Dataset . 2022
      License: CC BY
      ZivaHub
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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    Authors: Kautondokwa, Popyeni; Ophoff, Jacques; Ruhwanya, Zainab;

    This dataset contains PLS and Bootstrapping Data. The COVID-19 pandemic has forced individuals to adopt online applications and technologies, as well as remote working patterns. However, with changes in technology and working patterns, new vulnerabilities are likely to arise. Cybersecurity threats have rapidly evolved to exploit uncertainty during the pandemic, and users need to apply careful judgment and vigilance to avoid becoming the victim of a cyber-attack. This paper explores the factors that motivate security behaviour, considering the current environmental uncertainty. An adapted model, primarily based on the Protection Motivation Theory (PMT), is proposed and evaluated using data collected from an online survey of 222 respondents from a Higher Education institution. Data analysis was performed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The results confirm the applicability of PMT in the security context. Respondents’ behavioural intention, perceived threat vulnerability, response cost, response efficacy, security habits, and subjective norm predicted self-reported security behaviour. In contrast, environmental uncertainty, attitude towards policy compliance, self-efficacy and perceived threat severity did not significantly impact behavioural intention. The results show that respondents were able to cope with environmental uncertainty and maintain security behaviour.

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    ZivaHub - Open Data UCT
    Dataset . 2022
    License: CC BY
    ZivaHub
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      ZivaHub - Open Data UCT
      Dataset . 2022
      License: CC BY
      ZivaHub
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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    Authors: Peckham, Hannah; De Gruijter, Nina; Radziszewska, Ania; Ciurtin, Coziana; +5 Authors

    An online search of government websites and published literature was performed for regional data reports on COVID-19 cases that included sex as a variable from 1st January 2020 up until 1st June 2020 (Search terms: COVID-19/case/sex/country/data/death/ICU/ITU). In order to ensure unbiased representation from as many regions as possible, a cross check was done using the list of countries reporting data on ‘Worldometer’, and an attempt was made to include as many regions reporting sex data as possible. Reports were translated using Google translate if they were not in English.Data selection, extraction and synthesisReports were included if they contained sex as a variable in data describing case number, intensive treatment unit (ITU) admission, or mortality. Data were entered directly by individual researchers into an online structured data extraction table. For some sources, counts of male confirmed cases or male deaths were not provided, but percentages of male cases or male deaths were provided instead. To include these sources and avoid biases that might be introduced by their exclusion, we calculated counts of male confirmed cases and male deaths from the reported percentages with rounding to the nearest integer. We acknowledge that this approach assumes that the reported percentages are reflective of the true percentages. For some sources, data included confirmed cases and deaths of unknown sex. For these sources, the reported totals were used where the proportion of unknown sex was small. This approach was preferred to excluding cases of unknown sex in order to avoid bias. The estimates represent the proportion of known male infections and odds ratios for mortality associated with known male sex, and will differ slightly from what the true values would be if the sex had been reported for all cases. Data were available at the level of country or regional summary data representing distinct individuals for each report, but not at the level of covariates for all individuals within a study. Consequently, covariates such as lifestyle, comorbidities, testing method and case type (hospital vs. community) could not be controlled for.

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    ZivaHub
    Dataset . 2020
    License: CC 0
    Data sources: Datacite
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      ZivaHub
      Dataset . 2020
      License: CC 0
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Besada, Donela; Docrat, Sumaiyah; DAVIAUD, Emmanuelle; solanki, geetesh; +3 Authors

    This model assesses the potential economic burden of alcohol-related injuries in South Africa. In addition to provider costs for each injury, the model calculates number of outpatient visits, general ward inpatient days and ICU days needed per event.

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    ZivaHub - Open Data UCT
    Dataset . 2020
    License: CC BY
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZivaHub - Open Data UCT
      Dataset . 2020
      License: CC BY
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Cleary, Susan; Tchuem, Cynthia Tamandjou; Geetesh Solanki; Docrat, Sumaiyah; +2 Authors

    MODEL STRATEGIESThis model assesses costs and outcomes for admitted severe and critical Covid-19 patients from time of admission to discharge or death.Two competing strategies are modelled:1. The "status quo" summarizes costs and outcomes for patients assuming usual care (no dexamethasone).2. The "dexamethasone" comparator summarizes costs and outcomes for patients assuming usual care with dexamethasone at 6mg/day over 10 days. MODEL OUTCOMESCost: mean cost (general ward and ICU) per admitted patient from the health care provider's perspective.Health outcomes: mean DALYs and deaths per admitted patient. Other: mean ICU days and inpatient days per admitted patient.

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    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2020
    License: CC BY
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    ZivaHub
    Dataset . 2020
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    ZivaHub
    Dataset . 2020
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      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2020
      License: CC BY
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      ZivaHub
      Dataset . 2020
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      ZivaHub
      Dataset . 2020
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    Authors: Cleary, Susan; Wilkinson, Tommy; Tchuem, Cynthia Tamandjou; Docrat, Sumaiyah; +4 Authors

    As the COVID-19 pandemic progresses, the demands on the health care system will intensify and will result in critical shortages of resources (hospital beds, intensive care unit (ICU) beds, ventilators, medical workforce), particularly in the public sector. Given the expected downturn in an already weak economy coupled with the increased demand for government resources for economic relief and other measures, the ability of government to commit additional funding to an already under-funded public health sector is limited. Within this context, it is imperative that available public resources are used fairly, optimally and efficiently - we simply cannot afford to waste any resources. This rapid economic evaluation intends to inform Covid-19 health system decision-making. In this report, we respond to the question: What is the cost-effectiveness of ICU care versus treatment in general ward in supporting severe Covid-19 cases? Given the emergent nature of Covid-19 and the huge uncertainty in key parameters, a simple excel-based model is provided. This simplicity is designed to facilitate understanding. In addition, the framework allows for parameters to be varied and ultimately updated as sufficient local data become available.

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    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2020
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      ZivaHub
      Dataset . 2020
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      ZivaHub
      Dataset . 2020
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    Authors: Ryan, Peter G; Maclean, Kyle; Weideman, Eleanor;

    The lockdowns instigated to slow the spread of the COVID-19 pandemic offered a unique opportunity to assess how restrictions on human activity affect street litter. We recorded daily litter arrival rates for 50 days in two South African cities from the time of strictest lockdown through two successive easings in regulations. The strict lockdown had no marked impact on litter composition, which was dominated by convenience foods and beverages (29% by number, 34% by mass) and tobacco products (33% by number, 3% by mass). The ban on the sale of tobacco products during the lockdown did not greatly reduce the number of cigarette butts and associated packaging. Vehicle parts accounted for <1% of litter items (2% by mass) whereas household waste spilled from bins prior to or during collection accounted for 3% of litter items (14% by mass). Street litter loads decreased roughly by a factor of three during the strict lockdown. The increase in litter was gradual, suggesting a reduction in compliance with regulations as the lockdown continued. Our results show a clear link between human activity levels and littering.

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    ZivaHub - Open Data UCT
    Dataset . 2020
    License: CC BY
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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      ZivaHub - Open Data UCT
      Dataset . 2020
      License: CC BY
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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    Authors: Cleary, Susan; Tamandjou Tchuem, Cynthia; solanki, geetesh; Wilkinson, Tommy;

    MODEL STRATEGIESThis model assesses costs and outcomes for admitted severe and critical Covid-19 patients from time of admission to discharge or deathFour competing strategies are modelled:1. The "status quo" summarizes costs and outcomes for patients assuming no dexamethasone or remdesivir2. The "dexamethasone" comparator summarizes costs and outcomes for patients assuming dexamethasone at 6mg/day3. The "remdesivir" comparator summarizes costs and outcomes for patients assuming remdesivir at 100mg/day4. The "remdesivr plus dexamethasone" comparator summarizes costs and outcomes for patients assuming remdesivir at 100mg/day plus dexamethasone at 6mg/dayMODEL OUTCOMESCost: mean cost (general ward, ICU, dexamethasone and remdesivir as appropriate) per admitted patient from the health care provider's perspectiveHealth outcomes: mean DALYs and deaths per admitted patient Other outcomes: mean ICU days and inpatient days per admitted patientBudget impact: mean costs (or savings) associated with intervention implementation

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    ZivaHub - Open Data UCT
    Dataset . 2020
    License: CC BY
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    ZivaHub
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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      ZivaHub - Open Data UCT
      Dataset . 2020
      License: CC BY
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      ZivaHub
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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