Pub Date : 2022-01-01DOI: 10.1515/openhe-2022-0009
K. Maheshkumar, Vijayakumar. Venugopal, S. Geethanjali, S. Poonguzhali, S. Silambanan, R. Padmavathi, Sankaralingam Thirupathy Venkateswaran
Abstract Background: In December 2019, a new corona-virus (COVID-19) infection broke out in the Chinese province of Wuhan. With the rampant spread of virus around the world, COVID-19 was declared as a global pandemic in the following year. Many complementary and alternate therapies (CAM) were used experimentally alongside conventional treatments for effective management of COVID-19. Aim: This paper presents a protocol for the systematic review and meta-analysis of the studies with various CAM therapies for the management of COVID-19 pneumonia. Methods: Electronic databases such as PubMed, Embase, Scopus, and the Cochrane Central Register of Controlled Trials (CENTRAL) could be used for searching the relevant trials and studies with keywords related to COVID-19 and CAM therapies. Two independent reviewers would screen a list of all the trials and extract the relevant variables. Additionally, we would also evaluate the risk of bias of the selected studies. Review Manager software (RevMan; version 5.3.5) and R statistical software (version 3.6.1) would be used for the data analysis. Results: Risk ratio (RR) would be estimated for dichotomous outcomes, and the mean differences (MD) would be measured for continuous outcomes. Heterogeneity with the help of I2 statistic would be used for the assessment of inconsistency across studies with the level of significance at P< 0.10. We would also assess publication bias using funnel plots and Egger’s test for the selected studies. Conclusion: The protocol for systematic review and meta-analysis would investigate the beneficial and possible adverse effects of various CAM therapies in the prevention and management of COVID-19 associated pneumonia.
背景:2019年12月，中国武汉市发生新型冠状病毒(COVID-19)感染。随着新冠疫情在世界范围内的蔓延，第二年被宣布为全球大流行。许多补充和替代疗法(CAM)与常规治疗一起实验性地用于有效管理COVID-19。目的:本文提出了一种系统评价和荟萃分析各种CAM治疗COVID-19肺炎的研究方案。方法:通过PubMed、Embase、Scopus、Cochrane Central Register of Controlled Trials (Central)等电子数据库检索与COVID-19和CAM治疗相关的相关试验和研究。两名独立的审稿人将筛选所有试验的列表并提取相关变量。此外，我们还将评估所选研究的偏倚风险。Review Manager软件(RevMan;5.3.5版本)和R统计软件(3.6.1版本)进行数据分析。结果:二分结局的风险比(RR)将被估计，连续结局的平均差异(MD)将被测量。使用I2统计量的异质性来评估研究间的不一致性，显著性水平为P< 0.10。我们还会对选定的研究使用漏斗图和Egger检验来评估发表偏倚。结论:系统评价和荟萃分析方案将探讨各种CAM疗法在预防和管理COVID-19相关性肺炎中的有益和可能的不良影响。
{"title":"Complementary and alternate therapies (CAM) in the management of novel Corona virus (COVID-19): protocol for systematic review and meta-analysis","authors":"K. Maheshkumar, Vijayakumar. Venugopal, S. Geethanjali, S. Poonguzhali, S. Silambanan, R. Padmavathi, Sankaralingam Thirupathy Venkateswaran","doi":"10.1515/openhe-2022-0009","DOIUrl":"https://doi.org/10.1515/openhe-2022-0009","url":null,"abstract":"Abstract Background: In December 2019, a new corona-virus (COVID-19) infection broke out in the Chinese province of Wuhan. With the rampant spread of virus around the world, COVID-19 was declared as a global pandemic in the following year. Many complementary and alternate therapies (CAM) were used experimentally alongside conventional treatments for effective management of COVID-19. Aim: This paper presents a protocol for the systematic review and meta-analysis of the studies with various CAM therapies for the management of COVID-19 pneumonia. Methods: Electronic databases such as PubMed, Embase, Scopus, and the Cochrane Central Register of Controlled Trials (CENTRAL) could be used for searching the relevant trials and studies with keywords related to COVID-19 and CAM therapies. Two independent reviewers would screen a list of all the trials and extract the relevant variables. Additionally, we would also evaluate the risk of bias of the selected studies. Review Manager software (RevMan; version 5.3.5) and R statistical software (version 3.6.1) would be used for the data analysis. Results: Risk ratio (RR) would be estimated for dichotomous outcomes, and the mean differences (MD) would be measured for continuous outcomes. Heterogeneity with the help of I2 statistic would be used for the assessment of inconsistency across studies with the level of significance at P< 0.10. We would also assess publication bias using funnel plots and Egger’s test for the selected studies. Conclusion: The protocol for systematic review and meta-analysis would investigate the beneficial and possible adverse effects of various CAM therapies in the prevention and management of COVID-19 associated pneumonia.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88710631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1515/openhe-2022-0008
Mehrukh Zehravi, Mudasir Maqbool, I. Ara
Abstract PCOS (Polycystic Ovary Syndrome) is an endocrine condition that affects women of reproductive age: it can have catastrophic consequences, as it is accompanied by anovulation, androgen excess, infertility, insulin resistance, depression, and amenorrhea. Women who have a hereditary tendency are more likely to be affected. Other environmental variables such as a sedentary lifestyle, bad eating habits, inactivity, and obesity have frequently been implicated in the development of this illness. Each year, more women are diagnosed with PCOS as a result of an increasingly unhealthy lifestyle. When PCOS is detected early and treated correctly, the accompanying reproductive, metabolic, and cardiovascular problems can be effectively managed or predicted. PCOS is becoming a growing source of worry, as it primarily affects women of reproductive age. PCOS is also prevalent in many teenage girls during puberty. Despite being one of the most frequent reproductive health issues among women, doctors face a tremendous obstacle in providing appropriate medical therapy. PCOS is known to cause anxiety and despair, particularly when exacerbated by excessive facial hair growth, obesity, and infertility, anxiety and despair. Thus, PCOS can have a negative effect on an individual’s quality of life if it is not treated promptly. The best first-line treatment for PCOS is a lifestyle intervention that includes a healthy diet with caloric restriction, exercise to aid in weight loss and to avoid future weight gain, and support for behaviour modification. Future studies should focus on the gaps in our understanding of PCOS. Patients will receive the best care if those physicians are followed. To date, there has been no effective treatment for PCOS, and most patients receive only symptomatic treatment with hormones and insulin sensitizers, which leads to long-term medication dependency.
{"title":"Healthy Lifestyle and Dietary Approaches to Treating Polycystic Ovary Syndrome: A Review","authors":"Mehrukh Zehravi, Mudasir Maqbool, I. Ara","doi":"10.1515/openhe-2022-0008","DOIUrl":"https://doi.org/10.1515/openhe-2022-0008","url":null,"abstract":"Abstract PCOS (Polycystic Ovary Syndrome) is an endocrine condition that affects women of reproductive age: it can have catastrophic consequences, as it is accompanied by anovulation, androgen excess, infertility, insulin resistance, depression, and amenorrhea. Women who have a hereditary tendency are more likely to be affected. Other environmental variables such as a sedentary lifestyle, bad eating habits, inactivity, and obesity have frequently been implicated in the development of this illness. Each year, more women are diagnosed with PCOS as a result of an increasingly unhealthy lifestyle. When PCOS is detected early and treated correctly, the accompanying reproductive, metabolic, and cardiovascular problems can be effectively managed or predicted. PCOS is becoming a growing source of worry, as it primarily affects women of reproductive age. PCOS is also prevalent in many teenage girls during puberty. Despite being one of the most frequent reproductive health issues among women, doctors face a tremendous obstacle in providing appropriate medical therapy. PCOS is known to cause anxiety and despair, particularly when exacerbated by excessive facial hair growth, obesity, and infertility, anxiety and despair. Thus, PCOS can have a negative effect on an individual’s quality of life if it is not treated promptly. The best first-line treatment for PCOS is a lifestyle intervention that includes a healthy diet with caloric restriction, exercise to aid in weight loss and to avoid future weight gain, and support for behaviour modification. Future studies should focus on the gaps in our understanding of PCOS. Patients will receive the best care if those physicians are followed. To date, there has been no effective treatment for PCOS, and most patients receive only symptomatic treatment with hormones and insulin sensitizers, which leads to long-term medication dependency.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74965604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1515/openhe-2022-0027
Emmanuel S Adebayo, Abiodun Omowunmi Essiet, M. Plesons, Katherine Kat Watson, V. Chandra-Mouli
Abstract Despite the international, regional and national commitments to sexuality education and the evidence of its effectiveness, progress on national implementation of sexuality education has been slow for a variety of reasons. The obstacles to comprehensive sexuality education are well documented and commonly experienced, yet the knowledge base of successful strategies to deal with resistance remain limited. This study evaluated Nigeria’s experience in creating an enabling environment for and addressing backlash to the Family Life and HIV Education (FLHE) programme; the findings reveal that FLHE supporters used both proactive and reactive strategies, whilst also making concessions and compromises to ensure the acceptance of the programme in various states of the country. These practical examples from Nigeria may inspire other countries in the planning, implementation and scale-up phases of their own CSE programmes, especially in settings where socio-cultural barriers pose challenges.
{"title":"Commitment, Concessions and Compromise. Experiences of building support for and addressing resistance to sexuality education from Nigeria","authors":"Emmanuel S Adebayo, Abiodun Omowunmi Essiet, M. Plesons, Katherine Kat Watson, V. Chandra-Mouli","doi":"10.1515/openhe-2022-0027","DOIUrl":"https://doi.org/10.1515/openhe-2022-0027","url":null,"abstract":"Abstract Despite the international, regional and national commitments to sexuality education and the evidence of its effectiveness, progress on national implementation of sexuality education has been slow for a variety of reasons. The obstacles to comprehensive sexuality education are well documented and commonly experienced, yet the knowledge base of successful strategies to deal with resistance remain limited. This study evaluated Nigeria’s experience in creating an enabling environment for and addressing backlash to the Family Life and HIV Education (FLHE) programme; the findings reveal that FLHE supporters used both proactive and reactive strategies, whilst also making concessions and compromises to ensure the acceptance of the programme in various states of the country. These practical examples from Nigeria may inspire other countries in the planning, implementation and scale-up phases of their own CSE programmes, especially in settings where socio-cultural barriers pose challenges.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88312078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1515/openhe-2021-0004
Alexis Wilderman, Marcus M. Lam, Z. Yin
Abstract The connection between urban greenspace and mental health is a robust but unsettled area of research in the public health and urban planning literatures. Inconsistent findings in prior studies are mostly due to differences in greenspace measurements and interrelations with socio-demographic factors. This study examines the relationships of mental health prevalence (MHP) with health prevention, socioeconomic and race-ethnicity factors, and proximity to greenspace at the census-tract level in the City of San Diego, California, using data from the CDC 500 Cities Project and US Census Bureau. We considered three greenspace proximity measures: distances to specified vegetation types, parks, and tree cover. Spear-man’s rank correlation showed that MHP was significantly correlated to distances to greenspace (rho = 0.480), parks (rho = 0.234), and tree cover (rho = 0.342), and greenspace proximity plus crime occurrence explained 37.8% of the variance in MHP in regression analysis. Further analysis revealed that socioeconomic status, race-ethnicity, and health prevention explained more than 93% of the variance in MHP, while greenspace proximity did not enter the regression model with statistical significance. We discovered that certain socioeconomic and race-ethnicity variables, such as proportion of Hispanic population, poverty, and regular checkup, may fully represent the effects of greenspace on MHP in the City of San Diego. Regression analysis for three subsections of the city suggested that different predictors of MHP should be considered in formulating intervention measures. Our results indicate the need to improve mental health conditions through a range of interventions that address the disparities experienced by racial-ethnic minorities and those in lower-socioeconomic classes.
{"title":"A pilot study exploring the relationship between urban greenspace accessibility and mental health prevalence in the City of San Diego in the context of socioeconomic and demographic factors","authors":"Alexis Wilderman, Marcus M. Lam, Z. Yin","doi":"10.1515/openhe-2021-0004","DOIUrl":"https://doi.org/10.1515/openhe-2021-0004","url":null,"abstract":"Abstract The connection between urban greenspace and mental health is a robust but unsettled area of research in the public health and urban planning literatures. Inconsistent findings in prior studies are mostly due to differences in greenspace measurements and interrelations with socio-demographic factors. This study examines the relationships of mental health prevalence (MHP) with health prevention, socioeconomic and race-ethnicity factors, and proximity to greenspace at the census-tract level in the City of San Diego, California, using data from the CDC 500 Cities Project and US Census Bureau. We considered three greenspace proximity measures: distances to specified vegetation types, parks, and tree cover. Spear-man’s rank correlation showed that MHP was significantly correlated to distances to greenspace (rho = 0.480), parks (rho = 0.234), and tree cover (rho = 0.342), and greenspace proximity plus crime occurrence explained 37.8% of the variance in MHP in regression analysis. Further analysis revealed that socioeconomic status, race-ethnicity, and health prevention explained more than 93% of the variance in MHP, while greenspace proximity did not enter the regression model with statistical significance. We discovered that certain socioeconomic and race-ethnicity variables, such as proportion of Hispanic population, poverty, and regular checkup, may fully represent the effects of greenspace on MHP in the City of San Diego. Regression analysis for three subsections of the city suggested that different predictors of MHP should be considered in formulating intervention measures. Our results indicate the need to improve mental health conditions through a range of interventions that address the disparities experienced by racial-ethnic minorities and those in lower-socioeconomic classes.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83151410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1515/openhe-2021-0003
M. Asghar, M. Din, A. Waris, Muhammad Talha Yasin, T. Zohra, M. Zia
Abstract The coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), was first reported in December, 2019, in Wuhan, China. Even the public health sector experts could not anticipate that the virus would spread rapidly to create the worst worldwide crisis in more than a century. The World Health Organization (WHO) declared COVID-19 a public health emergency on January 30, 2020, but it was not until March 11, 2020 that the WHO declared it a global pandemic. The epidemiology of SARS-CoV-2 is different from the SARS coronavirus outbreak in 2002 and the Middle East Respiratory Syndrome (MERS) in 2012; therefore, neither SARS nor MERS could be used as a suitable model for foreseeing the future of the current pandemic. The influenza pandemic of 1918 could be referred to in order to understand and control the COVID-19 pandemic. Although influenza and the SARS-CoV-2 are from different families of viruses, they are similar in that both silently attacked the world and the societal and political responses to both pandemics have been very much alike. Previously, the 1918 influenza pandemic and unpredictability of the second wave caused distress among people as the first wave of that outbreak (so-called Spanish flu) proved to be relatively mild compared to a much worse second wave, followed by smaller waves. As of April, 2021, the second wave of COVID-19 has occurred around the globe, and future waves may also be expected, if the total population of the world is not vaccinated. This article aims to highlight the key similarities and differences in both pandemics. Similarly, lessons from the previous pan-demics and various possibilities for the future course of COVID-19 are also highlighted.
{"title":"COVID-19 and the 1918 influenza pandemics: a concise overview and lessons from the past","authors":"M. Asghar, M. Din, A. Waris, Muhammad Talha Yasin, T. Zohra, M. Zia","doi":"10.1515/openhe-2021-0003","DOIUrl":"https://doi.org/10.1515/openhe-2021-0003","url":null,"abstract":"Abstract The coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), was first reported in December, 2019, in Wuhan, China. Even the public health sector experts could not anticipate that the virus would spread rapidly to create the worst worldwide crisis in more than a century. The World Health Organization (WHO) declared COVID-19 a public health emergency on January 30, 2020, but it was not until March 11, 2020 that the WHO declared it a global pandemic. The epidemiology of SARS-CoV-2 is different from the SARS coronavirus outbreak in 2002 and the Middle East Respiratory Syndrome (MERS) in 2012; therefore, neither SARS nor MERS could be used as a suitable model for foreseeing the future of the current pandemic. The influenza pandemic of 1918 could be referred to in order to understand and control the COVID-19 pandemic. Although influenza and the SARS-CoV-2 are from different families of viruses, they are similar in that both silently attacked the world and the societal and political responses to both pandemics have been very much alike. Previously, the 1918 influenza pandemic and unpredictability of the second wave caused distress among people as the first wave of that outbreak (so-called Spanish flu) proved to be relatively mild compared to a much worse second wave, followed by smaller waves. As of April, 2021, the second wave of COVID-19 has occurred around the globe, and future waves may also be expected, if the total population of the world is not vaccinated. This article aims to highlight the key similarities and differences in both pandemics. Similarly, lessons from the previous pan-demics and various possibilities for the future course of COVID-19 are also highlighted.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87669942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1515/openhe-2021-0002
A. Iyanda, Yongmei Lu
Abstract Having poor mental health can be life-threatening, and problems tied to it are prevalent in communities across the United States (US). The city of Austin is one of the ten cities in the US undergoing rapid urban gentrification; however, there is insufficient empirical evidence on the impact of this process on residents’ health. Consequently, this study explored the concept of weathering and life course perspective using data of 331 residents recruited from two regions endemic with gentrification to assess the health impacts of gentrification. We used a triangulation method including univariate, bivariate correlation, and multiple linear regression implemented through the structural equation model to examine the complex pathways to three health outcomes—measured stress, self-rated mental health, and depression symptoms. Bivariate Pearson’s correlation indicated a significant positive association between gentrification score and mental health symptoms and stress. However, the direct association between gentrification and depression disappeared in the causal/path model. In support of the weathering hypothesis, this study found that stress score was directly related to the adulthood depression score. Therefore, this research builds on the accumulating evidence of environmental stress and mental health in the US’s rapidly changing physical and sociocultural environment. Hence, implementing and guaranteeing social equity of resources will improve residents’ health and reduce the cost of health care spending at both the household level and the city government level.
{"title":"Structural equation modeling of mental health in gentrifying neighborhoods in Austin, Texas","authors":"A. Iyanda, Yongmei Lu","doi":"10.1515/openhe-2021-0002","DOIUrl":"https://doi.org/10.1515/openhe-2021-0002","url":null,"abstract":"Abstract Having poor mental health can be life-threatening, and problems tied to it are prevalent in communities across the United States (US). The city of Austin is one of the ten cities in the US undergoing rapid urban gentrification; however, there is insufficient empirical evidence on the impact of this process on residents’ health. Consequently, this study explored the concept of weathering and life course perspective using data of 331 residents recruited from two regions endemic with gentrification to assess the health impacts of gentrification. We used a triangulation method including univariate, bivariate correlation, and multiple linear regression implemented through the structural equation model to examine the complex pathways to three health outcomes—measured stress, self-rated mental health, and depression symptoms. Bivariate Pearson’s correlation indicated a significant positive association between gentrification score and mental health symptoms and stress. However, the direct association between gentrification and depression disappeared in the causal/path model. In support of the weathering hypothesis, this study found that stress score was directly related to the adulthood depression score. Therefore, this research builds on the accumulating evidence of environmental stress and mental health in the US’s rapidly changing physical and sociocultural environment. Hence, implementing and guaranteeing social equity of resources will improve residents’ health and reduce the cost of health care spending at both the household level and the city government level.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80903670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Balenghien, N. Alexander, Auður Lilja Arnþórsdóttir, Marina G. Bisia, A. Blackwell, R. Bødker, Maria Bourquia, S. Boutsini, S. Carpenter, C. Colenutt, Lorna Culverwell, Aleksandar Cvetkovikj, L. Dascălu, N. De Regge, S. Dhollander, A. Elbers, M. England, S. Filatov, C. Garros, M. Goffredo, N. Haddad, T. Høye, D. Hristescu, K. Khallaayoune, A. Kočišová, M. Larska, J. Lucientes, B. Mathieu, M. Miranda, A. Murchie, C. Nițescu, Z. Ozoliņa, I. P. da Fonseca, D. Petrić, D. Pudar, D. Ramilo, J. Richardson, Zanda Segliņa, S. Sghaier, J. Stefanovska, D. Stougiou, S. Sviland, Simona Tchakarova, W. Van Bortel, M. Castello, E. Veronesi, V. Versteirt, W. Wint
This is the third in a planned series of data papers presenting modelled vector distributions produced during the ECDC and EFSA funded VectorNet project. The data package presented here includes those Culicoides vectors species first modelled in 2015 as part of the VectorNet gap analysis work namely C. imicola, C. obsoletus, C. scoticus, C. dewulfi, C. chiopterus, C. pulicaris, C. lupicaris, C. punctatus, and C. newsteadi. The known distributions of these species within the Project area (Europe, the Mediterranean Basin, North Africa, and Eurasia) are currently incomplete to a greater or lesser degree. The models are designed to fill the gaps with predicted distributions, to provide a) first indication of vector species distributions across the project geographical extent, and b) assistance in targeting surveys to collect distribution data for those areas with no field validated information. The models are based on input data from light trap surveillance of adult Culicoides across continental Europe and surrounding regions (71.8°N –33.5°S, – 11.2°W – 62°E), concentrated in Western countries, supplemented by transect samples in eastern and northern Europe. Data from central EU are relatively sparse. Funding statement: This work was carried out with support from the VectorNet framework contract OC/EFSA/AHAW/2013/02-FWC1 funded by the European Centre for Disease prevention and Control (ECDC) and the European Food Safety Agency (EFSA) and the PALE-Blu H2020 Project ID: 727393.
{"title":"VectorNet Data Series 3: Culicoides Abundance Distribution Models for Europe and Surrounding Regions","authors":"T. Balenghien, N. Alexander, Auður Lilja Arnþórsdóttir, Marina G. Bisia, A. Blackwell, R. Bødker, Maria Bourquia, S. Boutsini, S. Carpenter, C. Colenutt, Lorna Culverwell, Aleksandar Cvetkovikj, L. Dascălu, N. De Regge, S. Dhollander, A. Elbers, M. England, S. Filatov, C. Garros, M. Goffredo, N. Haddad, T. Høye, D. Hristescu, K. Khallaayoune, A. Kočišová, M. Larska, J. Lucientes, B. Mathieu, M. Miranda, A. Murchie, C. Nițescu, Z. Ozoliņa, I. P. da Fonseca, D. Petrić, D. Pudar, D. Ramilo, J. Richardson, Zanda Segliņa, S. Sghaier, J. Stefanovska, D. Stougiou, S. Sviland, Simona Tchakarova, W. Van Bortel, M. Castello, E. Veronesi, V. Versteirt, W. Wint","doi":"10.5334/OHD.33","DOIUrl":"https://doi.org/10.5334/OHD.33","url":null,"abstract":"This is the third in a planned series of data papers presenting modelled vector distributions produced during the ECDC and EFSA funded VectorNet project. The data package presented here includes those Culicoides vectors species first modelled in 2015 as part of the VectorNet gap analysis work namely C. imicola, C. obsoletus, C. scoticus, C. dewulfi, C. chiopterus, C. pulicaris, C. lupicaris, C. punctatus, and C. newsteadi. The known distributions of these species within the Project area (Europe, the Mediterranean Basin, North Africa, and Eurasia) are currently incomplete to a greater or lesser degree. The models are designed to fill the gaps with predicted distributions, to provide a) first indication of vector species distributions across the project geographical extent, and b) assistance in targeting surveys to collect distribution data for those areas with no field validated information. The models are based on input data from light trap surveillance of adult Culicoides across continental Europe and surrounding regions (71.8°N –33.5°S, – 11.2°W – 62°E), concentrated in Western countries, supplemented by transect samples in eastern and northern Europe. Data from central EU are relatively sparse. Funding statement: This work was carried out with support from the VectorNet framework contract OC/EFSA/AHAW/2013/02-FWC1 funded by the European Centre for Disease prevention and Control (ECDC) and the European Food Safety Agency (EFSA) and the PALE-Blu H2020 Project ID: 727393.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46975624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Gorris, L. Cat, M. Matlock, O. Ogunseitan, K. Treseder, J. Randerson, C. Zender
We compiled a coccidioidomycosis (Valley fever) case database for three states in the southwestern United States (US). Currently, county-level, monthly case counts are available from 2000–2015 for Arizona, California, and Nevada. We collected these data from each respective state public health agency. The Valley fever case database is available on GitHub, at https://github.com/valleyfever/valleyfevercasedata . This database may be used to examine relationships between the number of Valley fever cases and hypothesized explanatory variables such as environmental conditions, social determinants, human behavior, occupational activities, public policies, or other risk factors. We aim to provide regular updates to this database and include more states as data become available. Funding statement: M. E. Gorris received support from a Department of Defense (DoD), National Defense Science & Engineering Graduate Fellowship (32 CFR 168a). M. E. Gorris, L. A. Cat, and M. Matlock thank the UC Irvine Data Science Initiative for their funding and support. L. A. Cat acknowledges funding and support from the UC-Mexico Initiative. M. Matlock is also supported by Water UCI and the UCI Graduate Division. K. K. Treseder is supported by US NSF (EAR-1411942 and DEB-1457160) and the US Department of Energy, Office of Science, Office of Biological and Environmental Research (BER), under Award Numbers DE-PS02-09ER09-25 and DE-SC001641. J. T. Randerson received support from the Gordon and Betty Moore Foundation (GBMF#3269), NASA Soil Moisture and Interdisciplinary Science Program, and the U.S. Dept. of Energy Office of Science RUBISCO Science Focus Area. C. S. Zender acknowledges support from the Borrego Valley Endowment Fund and DOE ACME DE-SC0012998.
我们编制了美国西南部三个州的球孢子菌病(谷热)病例数据库。目前，从2000年到2015年，亚利桑那州、加利福尼亚州和内华达州的县级每月病例计数是可用的。我们从每个州的公共卫生机构收集了这些数据。谷热病例数据库可以在GitHub上找到，网址是https://github.com/valleyfever/valleyfevercasedata。该数据库可用于检查谷热病例数与假设的解释变量(如环境条件、社会决定因素、人类行为、职业活动、公共政策或其他风险因素)之间的关系。我们的目标是为这个数据库提供定期更新，并在数据可用时包括更多的州。资助声明:m.e. Gorris获得了国防部(DoD)国防科学与工程研究生奖学金(32 CFR 168a)的支持。M. E. Gorris, L. A. Cat和M. Matlock感谢加州大学欧文分校数据科学计划的资助和支持。L. A. Cat感谢加州大学墨西哥分校倡议的资助和支持。马特洛克也得到了水UCI和UCI研究生部的支持。K. K. Treseder项目由美国国家科学基金会(EAR-1411942和DEB-1457160)和美国能源部、科学办公室、生物与环境研究办公室(BER)资助，项目编号为DE-PS02-09ER09-25和DE-SC001641。J. T. Randerson得到了Gordon and Betty Moore基金会(gbmf# 3269)、NASA土壤水分和跨学科科学计划以及美国能源部科学办公室RUBISCO科学重点领域的支持。C. S. Zender感谢Borrego Valley捐赠基金和DOE ACME DE-SC0012998的支持。
{"title":"Coccidioidomycosis (Valley Fever) Case Data for the Southwestern United States","authors":"M. Gorris, L. Cat, M. Matlock, O. Ogunseitan, K. Treseder, J. Randerson, C. Zender","doi":"10.5334/ohd.31","DOIUrl":"https://doi.org/10.5334/ohd.31","url":null,"abstract":"We compiled a coccidioidomycosis (Valley fever) case database for three states in the southwestern United States (US). Currently, county-level, monthly case counts are available from 2000–2015 for Arizona, California, and Nevada. We collected these data from each respective state public health agency. The Valley fever case database is available on GitHub, at https://github.com/valleyfever/valleyfevercasedata . This database may be used to examine relationships between the number of Valley fever cases and hypothesized explanatory variables such as environmental conditions, social determinants, human behavior, occupational activities, public policies, or other risk factors. We aim to provide regular updates to this database and include more states as data become available. Funding statement: M. E. Gorris received support from a Department of Defense (DoD), National Defense Science & Engineering Graduate Fellowship (32 CFR 168a). M. E. Gorris, L. A. Cat, and M. Matlock thank the UC Irvine Data Science Initiative for their funding and support. L. A. Cat acknowledges funding and support from the UC-Mexico Initiative. M. Matlock is also supported by Water UCI and the UCI Graduate Division. K. K. Treseder is supported by US NSF (EAR-1411942 and DEB-1457160) and the US Department of Energy, Office of Science, Office of Biological and Environmental Research (BER), under Award Numbers DE-PS02-09ER09-25 and DE-SC001641. J. T. Randerson received support from the Gordon and Betty Moore Foundation (GBMF#3269), NASA Soil Moisture and Interdisciplinary Science Program, and the U.S. Dept. of Energy Office of Science RUBISCO Science Focus Area. C. S. Zender acknowledges support from the Borrego Valley Endowment Fund and DOE ACME DE-SC0012998.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43773041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.1515/openhe-2020-0001
Simon Brown, D. Cooke, L. Blackwell
Abstract Practical domestic monitoring of the menstrual cycle requires measurements of urinary metabolites of reproductive hormones: oestrone glucuronide (E1G) and pregnanediol glucuronide (PdG). Data reported in the literature are expressed as (i) concentration, without or with either creatinine- or specific gravity correction, or (ii) excretion rates. This variation in such a fundamental issue prompts consideration of the relationships between the four measures. Because the menstrual cycle kinetics of E1G and PdG are complex, we consider measurements of urinary creatinine, urea, galactose, xylose and inulin which tend to be more stable. We show that uncorrected concentration measurements of these urinary analytes can be positively correlated, negatively correlated or uncorrelated with the serum concentration. Based on measurements of urinary creatinine concentrations, urinary specific gravity and creatinine excretion rates, we conclude that urinary analyte concentration are likely to be more reliable when creatinine-corrected rather than corrected using specific gravity, but that both are less reliable than measurements of the excretion rate. This has implications for the quantitation of any urinary analyte, but especially for the monitoring of the menstrual cycle in which changes in E1G and PdG from one day to the next can be physiologically significant for a woman monitoring her fertility.
{"title":"Expressing the quantity of urinary analytes: a discussion of some issues arising from the monitoring of the menstrual cycle","authors":"Simon Brown, D. Cooke, L. Blackwell","doi":"10.1515/openhe-2020-0001","DOIUrl":"https://doi.org/10.1515/openhe-2020-0001","url":null,"abstract":"Abstract Practical domestic monitoring of the menstrual cycle requires measurements of urinary metabolites of reproductive hormones: oestrone glucuronide (E1G) and pregnanediol glucuronide (PdG). Data reported in the literature are expressed as (i) concentration, without or with either creatinine- or specific gravity correction, or (ii) excretion rates. This variation in such a fundamental issue prompts consideration of the relationships between the four measures. Because the menstrual cycle kinetics of E1G and PdG are complex, we consider measurements of urinary creatinine, urea, galactose, xylose and inulin which tend to be more stable. We show that uncorrected concentration measurements of these urinary analytes can be positively correlated, negatively correlated or uncorrelated with the serum concentration. Based on measurements of urinary creatinine concentrations, urinary specific gravity and creatinine excretion rates, we conclude that urinary analyte concentration are likely to be more reliable when creatinine-corrected rather than corrected using specific gravity, but that both are less reliable than measurements of the excretion rate. This has implications for the quantitation of any urinary analyte, but especially for the monitoring of the menstrual cycle in which changes in E1G and PdG from one day to the next can be physiologically significant for a woman monitoring her fertility.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88646864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.1515/openhe-2020-0003
Oliver Boxell
Abstract Prior research shows mental health stigma is context-dependent and blocks help-seeking behaviors. Any applied solutions will require basic research to understand these contextual nuances. The present paper presents two timed Likert-type rating studies in which participants scored photographs of individuals with mental health diagnoses and other control condition labels in different social contexts. In the first study (N = 99), participants rated the individuals in a professional context and in a non-professional context. The second study (N = 99) systematically manipulated the attractiveness of the individuals depicted. Professional context moderated mental health stigma, indicating that, relative to control label conditions, participants were less accepting of an individual with a mental health diagnosis label as a medical clinician than as a next-door neighbor. Attractiveness had a uniform effect across all the label conditions, which produced a compounding additive effect in which a mental health diagnosis and low attractiveness negatively impacted the ratings simultaneously. The study used timed implicit judgments to demonstrate empirically how previously unstudied social contexts can affect mental health stigma. Understanding how such contextual effects affect stigma is a prerequisite for the development of interventions to overcome the barriers stigma creates for access to treatment and prevention.
{"title":"Social context affects mental health stigma","authors":"Oliver Boxell","doi":"10.1515/openhe-2020-0003","DOIUrl":"https://doi.org/10.1515/openhe-2020-0003","url":null,"abstract":"Abstract Prior research shows mental health stigma is context-dependent and blocks help-seeking behaviors. Any applied solutions will require basic research to understand these contextual nuances. The present paper presents two timed Likert-type rating studies in which participants scored photographs of individuals with mental health diagnoses and other control condition labels in different social contexts. In the first study (N = 99), participants rated the individuals in a professional context and in a non-professional context. The second study (N = 99) systematically manipulated the attractiveness of the individuals depicted. Professional context moderated mental health stigma, indicating that, relative to control label conditions, participants were less accepting of an individual with a mental health diagnosis label as a medical clinician than as a next-door neighbor. Attractiveness had a uniform effect across all the label conditions, which produced a compounding additive effect in which a mental health diagnosis and low attractiveness negatively impacted the ratings simultaneously. The study used timed implicit judgments to demonstrate empirically how previously unstudied social contexts can affect mental health stigma. Understanding how such contextual effects affect stigma is a prerequisite for the development of interventions to overcome the barriers stigma creates for access to treatment and prevention.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76285702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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