Social inequality is the phenomenon that differentiates between people in the context of the same society, placing some individuals in structurally more advantageous conditions than others. It manifests itself in all aspects: political, economic among others. The main causes of inequality are investment lack in social areas, health and education. Among the consequences of inequality, we highlight: increased violence, poverty, delay in economic progress; hunger, destruction and infant mortality; young marginalization people, and finally; rising unemployment. Among the main inequality types, we highlight: people with and without disabilities, regions, races; income and sex. To measure this inequality, we highlight HDI, Theil and MPI. A person with a disability is any person who presents a loss or abnormality that generates an inability to perform one or more activities, and these characteristics hinder their social inclusion, access to the labor market, transportation, education, financing and training; urban and environmental barriers, and finally; ignorance of employers. Situations like these provide disabilities people with lower wages when employed, worse purchasing power, less social participation providing greater exclusion and disadvantaged situations when compared to those without disabilities. For this work we used exploratory analysis techniques considering data sets from the 2010 IBGE Census and UNDP.
{"title":"INEQUALITY AND DISABILITY: IN STATISTICAL TERMS, WHAT ELSE DO WE NEED TO KNOW?","authors":"P. Oliveira","doi":"10.28951/rbb.v39i3.528","DOIUrl":"https://doi.org/10.28951/rbb.v39i3.528","url":null,"abstract":"Social inequality is the phenomenon that differentiates between people in the context of the same society, placing some individuals in structurally more advantageous conditions than others. It manifests itself in all aspects: political, economic among others. The main causes of inequality are investment lack in social areas, health and education. Among the consequences of inequality, we highlight: increased violence, poverty, delay in economic progress; hunger, destruction and infant mortality; young marginalization people, and finally; rising unemployment. Among the main inequality types, we highlight: people with and without disabilities, regions, races; income and sex. To measure this inequality, we highlight HDI, Theil and MPI. A person with a disability is any person who presents a loss or abnormality that generates an inability to perform one or more activities, and these characteristics hinder their social inclusion, access to the labor market, transportation, education, financing and training; urban and environmental barriers, and finally; ignorance of employers. Situations like these provide disabilities people with lower wages when employed, worse purchasing power, less social participation providing greater exclusion and disadvantaged situations when compared to those without disabilities. For this work we used exploratory analysis techniques considering data sets from the 2010 IBGE Census and UNDP.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85868131","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}
In this paper, a system of nonlinear equations for the maximum likelihood estimators as wel as the exact forms of the Fisher information matrix for Crovelli's bivariate gamma distribution and bivariate gamma beta distribution of the second kind are determined. An application of the results to the rainfall data from the city of Passo Fundo are provided.
{"title":"FISHER INFORMATION MATRIX FOR CROVELLI'S AND GAMMA BETA II BIVARIATE DISTRIBUTIONS","authors":"A. P. C. M. Silva, Adélia Conceição Diniz","doi":"10.28951/rbb.v39i2.476","DOIUrl":"https://doi.org/10.28951/rbb.v39i2.476","url":null,"abstract":"In this paper, a system of nonlinear equations for the maximum likelihood estimators as wel as the exact forms of the Fisher information matrix for Crovelli's bivariate gamma distribution and bivariate gamma beta distribution of the second kind are determined. An application of the results to the rainfall data from the city of Passo Fundo are provided.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77621165","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}
We present a short review of the asymmetric distributions alpha-stable, skew normal, skew Student’s t and skew Laplace. We compare the performance for these distributions, in general, are used to model asymmetric data, using AIC and BIC. These criterias were able to selecting the best model for each data set. We also apply these models to gene expression data and we verify these distributions are qualified to model these observations.
{"title":"USING ASYMMETRIC DISTRIBUTIONS FOR MODELING GENE EXPRESSION DATA","authors":"Walkiria Maria de Oliveira Macerau, L. Milan","doi":"10.28951/rbb.v39i2.466","DOIUrl":"https://doi.org/10.28951/rbb.v39i2.466","url":null,"abstract":"We present a short review of the asymmetric distributions alpha-stable, skew normal, skew Student’s t and skew Laplace. We compare the performance for these distributions, in general, are used to model asymmetric data, using AIC and BIC. These criterias were able to selecting the best model for each data set. We also apply these models to gene expression data and we verify these distributions are qualified to model these observations.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81848220","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}
B. V. C. Guimarães, S. Donato, I. Aspiazú, A. M. Azevedo, A. Carvalho
This study aimed to determine the size and shape of experimental plots that provide maximum precision using relative information method. This trial was conducted at the Federal Institute of Bahia. Plant height, cladode length, cladode width, cladode thickness, cladode area, cladode area index, number of cladodes, cladode total area and yield were measured in the third production cycle, 930 days after planting. The plants, defined as basic units, were arranged in 39 plot sizes so that the crop would fill the whole experimental area. Then, plot shapes with higher relative information and equal plot size in basic units were selected. The experimental plot with eight basic units in size ensures higher efficiency in the experimental evaluation. This combination between size and shape, besides meeting all evaluation requirements of the characteristics normally assessed in studies with forage cactus pear, has the maximum control of soil heterogeneity, thereby decreasing experimental error and significantly increasing precision.
{"title":"PLOT SIZE AND SHAPE FOR FIELD TRIALS WITH FORAGE CACTUS PEAR","authors":"B. V. C. Guimarães, S. Donato, I. Aspiazú, A. M. Azevedo, A. Carvalho","doi":"10.28951/RBB.V39I2.473","DOIUrl":"https://doi.org/10.28951/RBB.V39I2.473","url":null,"abstract":"This study aimed to determine the size and shape of experimental plots that provide maximum precision using relative information method. This trial was conducted at the Federal Institute of Bahia. Plant height, cladode length, cladode width, cladode thickness, cladode area, cladode area index, number of cladodes, cladode total area and yield were measured in the third production cycle, 930 days after planting. The plants, defined as basic units, were arranged in 39 plot sizes so that the crop would fill the whole experimental area. Then, plot shapes with higher relative information and equal plot size in basic units were selected. The experimental plot with eight basic units in size ensures higher efficiency in the experimental evaluation. This combination between size and shape, besides meeting all evaluation requirements of the characteristics normally assessed in studies with forage cactus pear, has the maximum control of soil heterogeneity, thereby decreasing experimental error and significantly increasing precision.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87243191","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}
Talita Evelin Nabarrete Tristão de Moraes, I. Previdelli, Giovani L. Silva
Breast cancer is one of the most common diseases among women worldwide with about 25% of new cases each year. In Brazil, 59,700 new cases of breast cancer were expected in 2019, according to the Brazilian National Cancer Institute (INCA). Survival analysis has been an useful tool for the identifying the risk and prognostic factors for cancer patients. This work aims to characterize the prognostic value of demographic, clinical and pathological variables in relation to the survival time of 2,092 patients diagnosed with breast cancer in Parana State, Brazil, from 2004 to 2016. In this sense, we propose a Bayesian analysis of survival data with long-term survivors by using Weibull regression models through integrated nested Laplace approximations (INLA). The results point to a proportion of long-term survivors around 57:6% in the population under study. In regard to potential risk factors, we namely concluded that 40-50 year age group has superior survival than younger and older age groups, white women have higher breast cancer risk than other races, and marital status decreases that risk. Caution on the general use of these results is nevertheless advised, since we have analyzed population-based breast cancer data without proper monitoring by a healthprofessional.
{"title":"A BAYESIAN WEIBULL ANALYSIS OF BREAST CANCER DATA WITH LONG-TERM SURVIVORS IN PARANA STATE, BRAZIL","authors":"Talita Evelin Nabarrete Tristão de Moraes, I. Previdelli, Giovani L. Silva","doi":"10.28951/rbb.v39i2.469","DOIUrl":"https://doi.org/10.28951/rbb.v39i2.469","url":null,"abstract":"\u0000 \u0000 \u0000Breast cancer is one of the most common diseases among women worldwide with about 25% of new cases each year. In Brazil, 59,700 new cases of breast cancer were expected in 2019, according to the Brazilian National Cancer Institute (INCA). Survival analysis has been an useful tool for the identifying the risk and prognostic factors for cancer patients. This work aims to characterize the prognostic value of demographic, clinical and pathological variables in relation to the survival time of 2,092 patients diagnosed with breast cancer in Parana State, Brazil, from 2004 to 2016. In this sense, we propose a Bayesian analysis of survival data with long-term survivors by using Weibull regression models through integrated nested Laplace approximations (INLA). The results point to a proportion of long-term survivors around 57:6% in the population under study. In regard to potential risk factors, we namely concluded that 40-50 year age group has superior survival than younger and older age groups, white women have higher breast cancer risk than other races, and marital status decreases that risk. Caution on the general use of these results is nevertheless advised, since we have analyzed population-based breast cancer data without proper monitoring by a healthprofessional. \u0000 \u0000 \u0000","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75863356","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}
R. Michels, M. G. Canteri, M. A. D. Aguiar e Silva, Janksyn Bertozzi, T. C. Dal Bosco
The lack of error of experimental planning in agricultural field studies can result in rework, causing the waste of financial resources. The determination of the optimal size of the experimental plot for carrying out the treatments can minimize these problems. The objective of this paper was to estimate the optimal plot size for measuring reflectance in soybeans, without treatment, using the modified maximum curvature method and the maximum distance method. Reflectance readings were taken in the soybean crop with the aid of the GreenSeeker® equipment, in basic experimental units of 0.45 m², in an area of 7 lines and 8 meters in length. The data were collected in three phenological stages of soy (R4, R5.5 and R6), obtaining 63 simulations of experimental area in each stage. Based on the results, it is recommended to use plots of 7.20 m², with grouping of 4 lines of 4 m in length.
{"title":"ESTIMATION OF THE OPTIMUM SIZE OF PLOTS FOR SOYBEAN RADIOMETER EXPERIMENTS","authors":"R. Michels, M. G. Canteri, M. A. D. Aguiar e Silva, Janksyn Bertozzi, T. C. Dal Bosco","doi":"10.28951/rbb.v39i2.477","DOIUrl":"https://doi.org/10.28951/rbb.v39i2.477","url":null,"abstract":"The lack of error of experimental planning in agricultural field studies can result in rework, causing the waste of financial resources. The determination of the optimal size of the experimental plot for carrying out the treatments can minimize these problems. The objective of this paper was to estimate the optimal plot size for measuring reflectance in soybeans, without treatment, using the modified maximum curvature method and the maximum distance method. Reflectance readings were taken in the soybean crop with the aid of the GreenSeeker® equipment, in basic experimental units of 0.45 m², in an area of 7 lines and 8 meters in length. The data were collected in three phenological stages of soy (R4, R5.5 and R6), obtaining 63 simulations of experimental area in each stage. Based on the results, it is recommended to use plots of 7.20 m², with grouping of 4 lines of 4 m in length.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84275167","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}
The time series methodology is an important tool when using data over time. The time series can be composed of the components trend (Tt), seasonality (St) and the random error (at). The aim of this study was to evaluate the tests used to analyze the trend component, which were: Pettitt, Run, Mann-Kendall, Cox-Stuart and the unit root tests (Dickey-Fuller, Dickey-Fuller Augmented and Zivot and Andrews), given that there is a discrepancy between the test results found in the literature. The four series analyzed were the maximum temperature in the Lavras city, MG, Brazil, the unemployment rate in the Metropolitan Region of S~ao Paulo (RMSP), the Broad Consumer Price Index (IPCA) and the nominal Gross Domestic Product (GDP) of Brazil. It was found that the unit root tests showed similar results in relation to the presence of the stochastic trend for all series. Furthermore, the turning point of the Pettitt test diverged from all the structural breaks found through the Zivot and Andrews test, except for the GDP series. Therefore, it was found that the trend tests diverged, obtaining similar results only in relation to the unemployment series.
在使用随时间变化的数据时，时间序列方法是一个重要的工具。时间序列可以由趋势分量(Tt)、季节性分量(St)和随机误差分量(at)组成。本研究的目的是评估用于分析趋势成分的测试，这些测试是:Pettitt, Run, Mann-Kendall, Cox-Stuart和单位根测试(Dickey-Fuller, Dickey-Fuller Augmented和Zivot and Andrews)，因为在文献中发现的测试结果存在差异。所分析的四个序列分别是巴西MG州拉夫拉斯市的最高气温、圣保罗大都市区的失业率(RMSP)、广义消费者价格指数(IPCA)和巴西名义国内生产总值(GDP)。发现单位根检验在所有序列的随机趋势存在方面显示出相似的结果。此外，除了GDP序列外，Pettitt检验的拐点偏离了Zivot和Andrews检验发现的所有结构性断裂。因此，发现趋势检验是不一致的，只有在失业系列中才得到类似的结果。
{"title":"STUDY OF TESTS FOR TREND IN TIME SERIES","authors":"D. Paiva, T. Sáfadi","doi":"10.28951/rbb.v39i2.471","DOIUrl":"https://doi.org/10.28951/rbb.v39i2.471","url":null,"abstract":"The time series methodology is an important tool when using data over time. The time series can be composed of the components trend (Tt), seasonality (St) and the random error (at). The aim of this study was to evaluate the tests used to analyze the trend component, which were: Pettitt, Run, Mann-Kendall, Cox-Stuart and the unit root tests (Dickey-Fuller, Dickey-Fuller Augmented and Zivot and Andrews), given that there is a discrepancy between the test results found in the literature. The four series analyzed were the maximum temperature in the Lavras city, MG, Brazil, the unemployment rate in the Metropolitan Region of S~ao Paulo (RMSP), the Broad Consumer Price Index (IPCA) and the nominal Gross Domestic Product (GDP) of Brazil. It was found that the unit root tests showed similar results in relation to the presence of the stochastic trend for all series. Furthermore, the turning point of the Pettitt test diverged from all the structural breaks found through the Zivot and Andrews test, except for the GDP series. Therefore, it was found that the trend tests diverged, obtaining similar results only in relation to the unemployment series.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88810360","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}
L. Lucena, Álefe Chagas de Lima Costa, Antonio Dennys Melo de Oliveira, M. L. D. M. V. Leite
Forage plants are considered one of the main factors for the development of livestock worldwide, for presenting high potential for phytomass production, drought tolerance, high energy value, large water reserve and easy propagation. Forage cactus stands out for its tolerance to water deficit. Aimed to evaluate the initial performance of the morphometric characteristics of Giant Sweet clone (N. cochenillifera) submitted to water and saline stresses using response surface analysis. Design used was completely randomized in a 4x4 factorial scheme, composed of four levels of water replacement, based on crop evapotranspiration (ETc): (25%.ETc, 50%.ETc, 75%.ETc and 100%.ETc) and four levels of water salinity (0, 2, 4 and 8 dS/m), with four repetitions totalling 64 experimental units. The following morphometric characteristics were evaluated: plant height, length, width, thickness, number of cladodes and area of cladodes. Eight evaluations were realized during the experimental period. Response surface analysis was used to evaluate the morphometric characteristics of the cladodes. Best water levels were between 55%.ETc and 65%.ETc and saline levels between 3.5 and 5 dS/m, maximizing the morphometric characteristics of Giant Sweet clone.
{"title":"INITIAL DEVELOPMENT OF CLADODE GIANT SWEET CLONE AS A FUNCTION OF WATER AND SALINE STRESS","authors":"L. Lucena, Álefe Chagas de Lima Costa, Antonio Dennys Melo de Oliveira, M. L. D. M. V. Leite","doi":"10.28951/rbb.v39i2.468","DOIUrl":"https://doi.org/10.28951/rbb.v39i2.468","url":null,"abstract":"Forage plants are considered one of the main factors for the development of livestock worldwide, for presenting high potential for phytomass production, drought tolerance, high energy value, large water reserve and easy propagation. Forage cactus stands out for its tolerance to water deficit. Aimed to evaluate the initial performance of the morphometric characteristics of Giant Sweet clone (N. cochenillifera) submitted to water and saline stresses using response surface analysis. Design used was completely randomized in a 4x4 factorial scheme, composed of four levels of water replacement, based on crop evapotranspiration (ETc): (25%.ETc, 50%.ETc, 75%.ETc and 100%.ETc) and four levels of water salinity (0, 2, 4 and 8 dS/m), with four repetitions totalling 64 experimental units. The following morphometric characteristics were evaluated: plant height, length, width, thickness, number of cladodes and area of cladodes. Eight evaluations were realized during the experimental period. Response surface analysis was used to evaluate the morphometric characteristics of the cladodes. Best water levels were between 55%.ETc and 65%.ETc and saline levels between 3.5 and 5 dS/m, maximizing the morphometric characteristics of Giant Sweet clone.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81374546","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}
Angélica Maria Tortola Ribeiro, Paulo Ribeiro Lins Júnior, W. H. Bonat
In the analysis of multivariate spatial random elds, it is essential to dene a covariance structure that adequately models the relationship between the variables under study. We propose a covariance structure with exponential correlation function for bivariate random elds, the SEC model. We compare the SEC model fits with the bivariate separable exponential model and the bivariate exponential model with constraints, which are particular cases of the full bivariate Matern model, presented in the literature. A simulation study assess characteristics of the proposed model. The model is tted to a weather data set from Brazil, bearing in mind the importance of analyzing climate data to predict adverse environmental conditions. Predictive measures are used to compare the models under study. The satisfactory results compared to the models considered and the simpler structure makes the SEC model an alternative for the analysis of bivariate spatial elds.
{"title":"COMPARISON OF EXPONENTIAL COVARIANCE FUNCTIONS FOR BIVARIATE GEOSTATISTICAL DATA","authors":"Angélica Maria Tortola Ribeiro, Paulo Ribeiro Lins Júnior, W. H. Bonat","doi":"10.28951/RBB.V39I1.558","DOIUrl":"https://doi.org/10.28951/RBB.V39I1.558","url":null,"abstract":"In the analysis of multivariate spatial random elds, it is essential to dene a covariance structure that adequately models the relationship between the variables under study. We propose a covariance structure with exponential correlation function for bivariate random elds, the SEC model. We compare the SEC model fits with the bivariate separable exponential model and the bivariate exponential model with constraints, which are particular cases of the full bivariate Matern model, presented in the literature. A simulation study assess characteristics of the proposed model. The model is tted to a weather data set from Brazil, bearing in mind the importance of analyzing climate data to predict adverse environmental conditions. Predictive measures are used to compare the models under study. The satisfactory results compared to the models considered and the simpler structure makes the SEC model an alternative for the analysis of bivariate spatial elds.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83186320","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}
In December of 2019, a new coronavirus was discovered in the city of Wuhan, China. The World Health Organization officially named this coronavirus as COVID-19. Since its discovery, the virus has spread rapidly around the world and is currently one of the main health problems, causing an enormous social and economic burden. Due to this, there is a great interest in mathematical models capable of projecting the evolution of the disease in countries, states and/or cities. This interest is mainly due to the fact that the projections may help the government agents in making decisions in relation to the prevention of the disease. By using this argument, the health department of the city (HDC) of Campo Grande asked the UFMS for the development of a mathematical study to project the evolution of the disease in the city. In this paper, we describe a modeling procedure used to fit a piecewise growth model for the accumulated number of cases recorded in the city. From the fitted model, we estimate the date in which the pandemic peak is reached and project the number of patients who will need treatment in intensive care units. Weekly, was sent to HDC a technical report describing the main results.
{"title":"A PIECEWISE GROWTH MODEL FOR MODELING THE ACCUMULATED NUMBER OF COVID-19 CASES IN THE CITY OF CAMPO GRANDE","authors":"E. Saraiva, L. Sauer, B. Pereira, C. Pereira","doi":"10.28951/RBB.V39I1.542","DOIUrl":"https://doi.org/10.28951/RBB.V39I1.542","url":null,"abstract":"In December of 2019, a new coronavirus was discovered in the city of Wuhan, China. The World Health Organization officially named this coronavirus as COVID-19. Since its discovery, the virus has spread rapidly around the world and is currently one of the main health problems, causing an enormous social and economic burden. Due to this, there is a great interest in mathematical models capable of projecting the evolution of the disease in countries, states and/or cities. This interest is mainly due to the fact that the projections may help the government agents in making decisions in relation to the prevention of the disease. By using this argument, the health department of the city (HDC) of Campo Grande asked the UFMS for the development of a mathematical study to project the evolution of the disease in the city. In this paper, we describe a modeling procedure used to fit a piecewise growth model for the accumulated number of cases recorded in the city. From the fitted model, we estimate the date in which the pandemic peak is reached and project the number of patients who will need treatment in intensive care units. Weekly, was sent to HDC a technical report describing the main results.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87275920","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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