There are many existing methodologies on measuring health equity, while seldom has method aiming at health resource allocation. We collected 6 method of measuring equity in health resource allocation. This paper presents key contents of methods on measuring horizontal equity in health service allocation, yet each method has its advantages and disadvantages as well as range of application, which may help researchers or government to make wise decision when choosing appropriate method for measuring equity. Through comparative analysis, we concluded that socioeconomic factors were considered in concentration index; although the Lorenz curve and Gini-coefficient are widely used, which exist uncertainty and incompleteness; overall inequality can be decomposed by Theil index, which is of significance for the planning of urban and rural areas; preferences on a certain class can be set artificially by Atkinson index; it is easy for Chi-square to analyze aided with statistical software; specific regional differences can be calculated by index of dissimilarity.
Abstract ᅟ There are many existing methodologies on measuring health equity, while seldom has method aiming at health resource allocation. We collected 6 method of measuring equity in health resource allocation. This paper presents key contents of methods on measuring horizontal equity in health service allocation, yet each method has its advantages and disadvantages as well as range of application, which may help researchers or government to make wise decision when choosing appropriate method for measuring equity. Through comparative analysis, we concluded that socioeconomic factors were considered in concentration index; although the Lorenz curve and Gini-coefficient are widely used, which exist uncertainty and incompleteness; overall inequality can be decomposed by Theil index, which is of significance for the planning of urban and rural areas; preferences on a certain class can be set artificially by Atkinson index; it is easy for Chi-square to analyze aided with statistical software; specific regional differences can be calculated by index of dissimilarity. Classification codes I1
BACKGROUND: The study aimed to explore the factors influencing protective behavior and its association with factors during the post-COVID-19 period in China based on the risk perception emotion model and the protective action decision model (PADM). METHODS: A total of 2830 valid questionnaires were collected as data for empirical analysis via network sampling in China. Structural equation modeling (SEM) was performed to explore the relationships between the latent variables. RESULTS: SEM indicated that social emotion significantly positively affected protective behavior and intention. Protective behavioral intention had significant direct effects on protective behavior, and the direct effects were also the largest. Government trust did not have a significant effect on protective behavior but did have a significant indirect effect. Moreover, it was found that government trust had the greatest direct effect on social emotion. In addition, we found that excessive risk perception level may directly reduce people's intention and frequency of engaging in protective behavior, which was not conducive to positive, protective behavior. CONCLUSION: In the post-COVID-19 period, theoretical framework constructed in this study can be used to evaluate people's protective behavior. The government should strengthen its information-sharing and interaction with the public, enhance people's trust in the government, create a positive social mood, appropriately regulate people's risk perception, and, finally, maintain a positive attitude and intent of protection.
Green plants (Viridiplantae) include around 450,000-500,000 species(1,2) of great diversity and have important roles in terrestrial and aquatic ecosystems. Here, as part of the One Thousand Plant Transcriptomes Initiative, we sequenced the vegetative transcriptomes of 1,124 species that span the diversity of plants in a broad sense (Archaeplastida), including green plants (Viridiplantae), glaucophytes (Glaucophyta) and red algae (Rhodophyta). Our analysis provides a robust phylogenomic framework for examining the evolution of green plants. Most inferred species relationships are well supported across multiple species tree and supermatrix analyses, but discordance among plastid and nuclear gene trees at a few important nodes highlights the complexity of plant genome evolution, including polyploidy, periods of rapid speciation, and extinction. Incomplete sorting of ancestral variation, polyploidization and massive expansions of gene families punctuate the evolutionary history of green plants. Notably, we find that large expansions of gene families preceded the origins of green plants, land plants and vascular plants, whereas whole-genome duplications are inferred to have occurred repeatedly throughout the evolution of flowering plants and ferns. The increasing availability of high-quality plant genome sequences and advances in functional genomics are enabling research on genome evolution across the green tree of life. ; Alberta Ministry of Advanced Education; Alberta Innovates AITF/iCORE Strategic Chair [RES0010334]; Musea Ventures; National Key Research and Development Program of China [2016YFE0122000]; Ministry of Science and Technology of the People's Republic of ChinaMinistry of Science and Technology, China [2015BAD04B01/2015BAD04B03]; State Key Laboratory of Agricultural Genomics [2011DQ782025]; Guangdong Provincial Key Laboratory of core collection of crop genetic resources research and application [2011A091000047]; Shenzhen Municipal Government of China [CXZZ20140421112021913/JCYJ20150529150409546/JCYJ20150529150505656]; National Science FoundationNational Science Foundation (NSF) [DBI-1265383, IOS 0922742, IOS-1339156, DEB 0830009, EF-0629817, EF-1550838, DEB 0733029, DBI 1062335, 1461364]; National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [1R01DA025197]; Deutsche ForschungsgemeinschaftGerman Research Foundation (DFG) [Qu 141/5-1, Qu 141/6-1, GR 3526/7-1, GR 3526/8-1]; Natural Sciences and Engineering Research Council of CanadaNatural Sciences and Engineering Research Council of Canada ; The 1KP initiative was funded by the Alberta Ministry of Advanced Education and Alberta Innovates AITF/iCORE Strategic Chair (RES0010334) to G.K.-S.W., Musea Ventures, The National Key Research and Development Program of China (2016YFE0122000), The Ministry of Science and Technology of the People's Republic of China (2015BAD04B01/2015BAD04B03), the State Key Laboratory of Agricultural Genomics (2011DQ782025) and the Guangdong Provincial Key Laboratory of core collection of crop genetic resources research and application (2011A091000047). Sequencing activities at BGI were also supported by the Shenzhen Municipal Government of China (CXZZ20140421112021913/JCYJ20150529150409546/JCYJ20150529150505656). Computation support was provided by the China National GeneBank (CNGB), the Texas Advanced Computing Center (TACC), WestGrid and Compute Canada; considerable support, including personnel, computational resources and data hosting, was also provided by the iPlant Collaborative (CyVerse) funded by the National Science Foundation (DBI-1265383), National Science Foundation grants IOS 0922742 (to C.W.d., P.S.S., D.E.S. and J.H.L.-M.), IOS-1339156 (to M.S.B.), DEB 0830009 (to J.H.L.-M., C.W.d., S.W.G. and D.W.S.), EF-0629817 (to S.W.G. and D.W.S.), EF-1550838 (to M.S.B.), DEB 0733029 (to T.W. and J.H.L.-M.), and DBI 1062335 and 1461364 (to T.W.), a National Institutes of Health Grant 1R01DA025197 (to T.M.K., C.W.d. and J.H.L.-M.), Deutsche Forschungsgemeinschaft grants Qu 141/5-1, Qu 141/6-1, GR 3526/7-1, GR 3526/8-1 (to M.Q. and I.G.) and a Natural Sciences and Engineering Research Council of Canada Discovery grant (to S.W.G.). We thank all national, state, provincial and regional resource management authorities, including those of province Nord and province Sud of New Caledonia, for permitting collections of material for this research. ; Public domain authored by a U.S. government employee