title: Source code for "Parallel computing efficiency of SWAN"

authors: Rautenbach, Christo

subjects: SWAN

abstract: Source code for  the paper "Rautenbach, C., Mullarney, J. C., and Bryan, K. R.: Parallel computing efficiency of SWAN, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2020-314, in review, 2020."

text: Source code for "Parallel computing efficiency of SWAN" Source code for  the paper "Rautenbach, C., Mullarney, J. C., and Bryan, K. R.: Parallel computing efficiency of SWAN, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2020-314, in review, 2020."

year: 2020

title: Data generation for composite-based structural equation modeling methods

authors: Schlittgen, Rainer

abstract: Examining the efficacy of composite-based structural equation modeling (SEM) features prominently in research. However, studies analyzing the efficacy of corresponding estimators usually rely on factor model data. Thereby, they assess and analyze their performance on erroneous grounds (i.e., factor model data instead of composite model data). A potential reason for this malpractice lies in the lack of available composite model-based data generation procedures for prespecified model parameters in the structural model and the measurements models. Addressing this gap in research, we derive model formulations and present a composite model-based data generation approach. The findings will assist researchers in their composite-based SEM simulation studies.

text: Data generation for composite-based structural equation modeling methods Examining the efficacy of composite-based structural equation modeling (SEM) features prominently in research. However, studies analyzing the efficacy of corresponding estimators usually rely on factor model data. Thereby, they assess and analyze their performance on erroneous grounds (i.e., factor model data instead of composite model data). A potential reason for this malpractice lies in the lack of available composite model-based data generation procedures for prespecified model parameters in the structural model and the measurements models. Addressing this gap in research, we derive model formulations and present a composite model-based data generation approach. The findings will assist researchers in their composite-based SEM simulation studies.

year: 2020

title: Inequities in Covid-19 Omicron infections and hospitalisations for Māori and Pacific people in Te Manawa Taki Midland region, New Zealand

authors: Whitehead, Jesse

abstract: Covid-19 impacts population health equity. While mRNA vaccines protect against serious illness and death, little New Zealand (NZ) data exists about the impact of Omicron - and effectiveness of vaccination - on different population groups. We aim to examine the impact of  Omicron  on Māori, Pacific and Other ethnicities and how this interacts with age and vaccination status in the Te Manawa Taki Midland region of NZ. Daily Covid-19 infection and hospitalisation rates (01/02/2022 - 29/06/2022) were calculated for Māori, Pacific and Other ethnicities for six age bands. A multivariate logistic regression model quantified the effects of ethnicity, age, and vaccination on hospitalisation rates. Per-capita Omicron cases were highest and occurred earliest among Pacific (9 per 1,000) and Māori (5 per 1,000) people and were highest among 12-24 year-olds (7 per 1,000). Hospitalisation was significantly more likely for Māori (OR=2.03), Pacific people (OR=1.75), over 75-year olds (OR=39.22), and unvaccinated people (OR=4.64). Length of hospitalisation is strongly related to age. Covid-19 vaccination reduces hospitalisations for older individuals and Māori and Pacific populations. Omicron inequitably impacted Māori and Pacific people through higher per-capita infection and hospitalisation rates. Older people are more likely to be hospitalised and for longer.

text: Inequities in Covid-19 Omicron infections and hospitalisations for Māori and Pacific people in Te Manawa Taki Midland region, New Zealand Covid-19 impacts population health equity. While mRNA vaccines protect against serious illness and death, little New Zealand (NZ) data exists about the impact of Omicron - and effectiveness of vaccination - on different population groups. We aim to examine the impact of  Omicron  on Māori, Pacific and Other ethnicities and how this interacts with age and vaccination status in the Te Manawa Taki Midland region of NZ. Daily Covid-19 infection and hospitalisation rates (01/02/2022 - 29/06/2022) were calculated for Māori, Pacific and Other ethnicities for six age bands. A multivariate logistic regression model quantified the effects of ethnicity, age, and vaccination on hospitalisation rates. Per-capita Omicron cases were highest and occurred earliest among Pacific (9 per 1,000) and Māori (5 per 1,000) people and were highest among 12-24 year-olds (7 per 1,000). Hospitalisation was significantly more likely for Māori (OR=2.03), Pacific people (OR=1.75), over 75-year olds (OR=39.22), and unvaccinated people (OR=4.64). Length of hospitalisation is strongly related to age. Covid-19 vaccination reduces hospitalisations for older individuals and Māori and Pacific populations. Omicron inequitably impacted Māori and Pacific people through higher per-capita infection and hospitalisation rates. Older people are more likely to be hospitalised and for longer.

year: 2023-04-24