The Vaccine Adverse Event Reporting System (VAERS) received thousands of reports of adverse events that occurred after vaccine administrations from the post-marketing vaccine safety surveillance. However, the causality between vaccines and reported adverse events cannot be taken for granted. In this report several data mining methods were applied to VAERS database that is coded in MedDRA terms to discover possible associations between vaccines and adverse events. Efforts were devoted to identify events that are reported more frequently after administering one vaccine than other vaccines using the following data mining techniques: relative ratio (RR), statistical significance (LogP), proportional reporting ratio (PRR), and screened PRR (SPRR). The vaccine-event combinations that ranked top in each method varied substantially among the methods. RR and PRR gave excessive weight to small counts of vaccine-event pairs, but SPRR was able to correct this weakness. There are only 33 vaccine-event pairs that were shared among the top 1,000 ranked in each method. Evaluating the properties of these data mining methods and exploring other methods will help improve vaccine safety surveillance. / text

Thesis advisor: Ina V.S. Mullis / Equity in educational outcomes, particularly reading, is an important policy issue in countries around the world. This dissertation used data from PIRLS 2006 to explore an approach to measuring equity in reading achievement internationally at the fourth grade. Relative risk ratios were selected as a measurement approach and were used to create a composite measure, the Relative Risk-Percentage (RRP) Equity Index, to compare equity in reading achievement across countries. This index was used to present the likelihood of scoring below the PIRLS 2006 Low International Benchmark for student groups that were traditionally at risk for low reading achievement compared to other students. The `at risk' student groups that were the focus of this study included those with low parental education, who spoke a language other than the language of instruction, who attended urban or rural schools, and who were boys. To complement the RRP Equity Index results, the relative likelihood of students scoring within the lower 20 percent of their country's reading achievement distribution was also presented. The results of these analyses showed that students with these characteristics were more likely than other fourth grade students to have low reading achievement in a number of the PIRLS 2006 countries. Overall, having parents with less than secondary education and not speaking the language of the test before starting school were associated with inequity in reading achievement in the largest number of PIRLS 2006 countries. As an example of how individual countries could further explore potential reasons for inequities in reading achievement highlighted by the RRP Equity Index, logistic regression models were built for Germany, Iran, and Romania. These models explored the extent to which statistically controlling for differences in resources could diminish the effect of being in an `at risk' group on reading achievement. In all three countries examined, resources explained a substantial proportion of the risk for low reading achievement. Though the logistic regression model results were country-specific, lacking books in the home was strongly associated with lower reading achievement in all three countries. / Thesis (PhD) — Boston College, 2009. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Research, Measurement, and Evaluation.

The Swedish Association of Local Authorities and Regions (SALAR) and the Swedish National Board of Health and Welfare (NBHW) have published a yearly report called “Open Comparisons of Quality and Efficiency in Swedish Health Care –Regional Comparisons” since the year 2006 to compare medical outcomes, patient experience, availability and costs among hospitals and counties. In this paper, inspired by the region profiles attached to the report, we describe several possible measurement methods for comparing dichotomous data: Risk Difference (RD), Relative Risk (RR), Relative Risk Reduction (RRR) and Odds Ratio (OR), mainly by using a geometric approach as a basis for further discussion. A standard scores method is also presented as a means for more efficient comparisons.

Orientador: Tereza Cristina Cardoso da Silva / Coorientadora: Katia Denise Saraiva Bresciani / Banca: Ana Carolina Borsanelli / Banca: Andréa Fontes Garcia / Resumo: Leishmaniose visceral é uma doença infecciosa, de potencial zoonótico, negligenciada e um sério problema de saúde pública em muitas partes do mundo. Dada à importância epidemiológica, a pesquisa teve como objetivo identificar soroprevalência, distribuição espacial e os fatores de risco relacionados à ocorrência de casos de leishmaniose visceral canina (LVC) no município de Piacatu. Foram analisados dados de inquérito censitário canino, com coleta de amostras de 833 animais, com posterior mapeamento dos casos positivos e aplicação de questionário epidemiológico casa a casa em locais de ocorrência de LVC. Baseado nos dados da análise soro- epidemiológica e espacial observou-se que ocorreram associações significativas entre fatores de risco e prevalência de LVC. Medidas de controle da LV necessitam ser intensificadas e direcionadas ao controle de vetores com identificação de flebótomos infectados, manejo ambiental e avaliação do real potencial de transmissão de gatos e animais considerados sorologicamente negativos. / Abstract: Visceral leishmaniasis is an infectious disease of zoonotic potential, neglected and a serious public health problem in many parts of the world. Given the epidemiological importance, the research aimed to identify seroprevalence, spatial distribution and risk factors related to the occurrence of cases of canine visceral leismaniasis (LVC) in the city of Piacatu. Data from a canine census survey were analyzed, with samples collected from 833 animals, with subsequent mapping of the positive cases and application of an epidemiological questionnaire at places with LVC occurrence. Based on data from the seroepidemiological and spatial analysis it was observed that there were significant associations between risk factors and prevalence of LVC. Control measures of LV need to be intensified and directed to the control of vectors with identification of infected sandflies, environmental management and evaluation of the real transmission potential of cats and animals considered serologically negative. / Mestre

Heatwave studies typically estimate heat-related mortality and morbidity risks at the city level; few have addressed the heterogeneous risks by socioeconomic status (SES) and location within a city. This study aimed to examine the impacts of heatwaves on mortality outcomes in Memphis, Tennessee, a Mid-South metropolitan area top-ranked in morbidity and poverty rates, and to investigate the effects of SES and urbanicity. Mortality data were retrieved from the death records in 2008–2017, and temperature data from the Applied Climate Information System. Heatwave days were defined based on four temperature metrics. Heatwave effects on daily total-cause, cardiovascular, and respiratory mortality were evaluated using Poisson regression, accounting for temporal trends, sociodemographic factors, urbanicity, and air pollution. We found higher cardiovascular mortality risk (cumulative RR (relative risk) = 1.25, 95% CI (confidence interval): 1.01–1.55) in heatwave days defined as those with maximum daily temperature >95th percentile for more than two consecutive days. The effects of heatwaves on mortality did not differ by SES, race, or urbanicity. The findings of this study provided evidence to support future heatwave planning and studies of heatwave and health impacts at a coarser geographic resolution.

Several large-sample confidence intervals for the ratio of independent binomial proportions are compared in terms of exact coverage probability and width. A non-iterative approximate Bayesian interval is derived and its frequency properties are superior to all of the non-iterative confidence intervals considered. The approximate Bayesian interval, which is very easy to compute, has performance characteristics that are very similar to the computationally intensive score method. Two sample size determination formulas are presented, one for desired absolute precision and the other for desired relative precision.

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第17859号 / 医博第3828号 / 新制||医||1000(附属図書館) / 30679 / 京都大学大学院医学研究科医学専攻 / (主査)教授 松田 秀一, 教授 佐藤 俊哉, 教授 戸口田 淳也 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DGAM

Neste estudo, baseado na análise de séries temporais para um período de 8 anos, correlacionou-se os casos de dengue com as variáveis climáticas das cidades da Baixada Santista (sudeste brasileiro) e de Cingapura (sudeste asiático). O estudo foi feito com o uso de um modelo de regressão de Poisson (MRP), que considera os casos de dengue como a variável dependente e as variáveis climáticas: precipitação, temperatura (máxima e mínima) e umidade relativa (máxima e mínima) como as variáveis independentes. Também foi utilizada a Análise de Componentes Principais (ACP) para escolher as variáveis que influenciam no aumento do número de casos de dengue nas cidades estudadas. A CP1 (componente principal 1) foi representada pelas temperaturas (máxima e mínima) e a precipitação e a CP2 (componente principal 2) pela umidade relativa (máxima e mínima). Calculou-se o acréscimo dos novos casos de dengue e o risco relativo de ocorrência da doença por influência de cada uma das variáveis climáticas. Na Baixada Santista, os maiores valores de precipitação e temperatura ocorrem nos meses de dezembro e janeiro (verão) e o aumento dos casos de dengue ocorre nos meses de março a maio (outono). Para Cingapura, a diminuição da precipitação e o aumento da temperatura ocorrem nos meses de março a maio (pré-monção de sudoeste), e, portanto, observa-se o aumento dos casos de dengue nos meses de junho a outubro (monção de sudoeste). Os resultados foram: em Cingapura, para 2oC a 10oC de variação na temperatura (máxima e mínima), houve um aumento médio dos casos de dengue de 22,2% a 184,6% (máxima) e de 26,1% a 230,3% (mínima). O risco relativo médio foi de 1,2% a 2,9% e de 1,3% a 3,3%, respectivamente. Para precipitação, a variação de 5mm a 55mm, houve o aumento dos casos de dengue de 5,6% a 83,2%, sendo e o risco relativo médio foi de 1,06% a 1,83%. A umidade relativa após a análise de correlação foi descartada no uso do modelo de regressão de Poisson por apresentar uma correlação muito baixa. Para a Baixada Santista, a variação da temperatura de 2oC a 10oC apresentou um acréscimo médio nos casos de dengue de 19,6% a 154,4% (máxima) e de 18,2% a 145,4% (mínima). O risco relativo médio foi de 1,20% a 2,54% e de 1,18% a 2,45%, respectivamente. A variação da precipitação de 5mm a 55mm apresentou um aumento dos casos de dengue de 3,92% a 53,10%. A umidade relativa mínima variando de 2% a 10%, o acréscimo dos casos de dengue foi 7,7% a 49,4%, sendo que o risco relativo foi de 1,08% a 1,49%. Assim, após várias análises, a temperatura mínima foi um dos preditores para ocorrência do aumento dos casos de dengue em Cingapura, sendo que há uma influência bem particular da precipitação, na qual, atua significativamente no período seco (pré-monção de sudoeste). Enquanto que na Baixada Santista as influências mais significativas foram da temperatura (máxima e mínima) e precipitação, que desenvolvem conjuntamente um bom cenário de atuação do vetor no período do outono / In this study, based on time series analysis for a period of eight years, correlated dengue cases with climatic variables in the cities of Santos (southeastern Brazil) and Singapore (Southeast Asia). The study was done using a Poisson regression model (PRM), which considers the cases of dengue as the dependent variable and climatic variables: precipitation, temperature (maximum and minimum) and relative humidity (maximum and minimum) as the independent variables. Also we used the Principal Component Analysis (PCA) to select the variables that influence the increase in the number of dengue cases in the cities studied. The PC1 (principal component 1) was represented by the temperatures (maximum and minimum) and precipitation and the PC2 (principal component 2) the relative humidity (maximum and minimum). We calculated the addition of new dengue cases and relative risk of disease influenced by each variable climate. In Baixada Santista, the highest values of precipitation and temperature occur in the months of December and January (summer) and the increase in dengue cases occur in the months from March to May (autumn). For Singapore, the decrease in precipitation and temperature increase occurring in the months March to May (southwest inter-monsoon) and hence there is an increase of dengue cases in the months from June to October (southwest monsoon). The results were in Singapore for 2oC to 10oC change in temperature (maximum and minimum), there was an average increase of dengue cases from 22.2% to 184.6% (maximum) and 26.1% at 230 3% (minimum). The average relative risk was 1.2% to 2.9% and 1.3% to 3.3%, respectively. For precipitation, the range of 5mm to 55mm, there was an increase of dengue cases from 5.6% to 83.2%, with and average relative risk was 1.06% to 1.83%. The relative humidity after the correlation analysis was discarded in the use of Poisson regression model for presenting a very low correlation. For Baixada Santista, the variation of temperature of 2oC to 10oC showed an average increase in the dengue cases from 19.6% to 154.4% (maximum) and 18.2% to 145.4% (minimum). The average relative risk is 1.20% to 2.54% and 1.18% to 2.45%, respectively. The variation in the precipitation of 5mm to 55mm showed an increase in dengue cases from 3.92% to 53.10%. The minimum relative humidity ranging from 2% to 10%, the increase of dengue cases was 7.7% to 49.4%, and the relative risk was 1.08% to 1.49%. Thus, after several analyzes, the minimum temperature was one of the predictors for the occurrence of the increase of dengue cases in Singapore, and there is a very particular influence of the precipitation, in which it acts significantly in the dry season (southwest inter-monsoon). While in Baixada Santista were the most significant influences of temperature (maximum and minimum) and precipitation, which jointly develop a good field of action of the vector in the autumn

Por mais que a negociação do voto em troca dos mais variados benefícios tenha desembarcado no país junto da coroa portuguesa ao início do século XIX, se percebe que ela não definhou na história política brasileira. Nem a queda da monarquia e instauração da república e seus valores, a perda de poder dos coronéis de terras, a implantação de punições eleitorais mais duras aos negociantes do voto, ou mesmo a introdução do voto eletrônico para dificultar a prestação de contas do eleitor cliente ao político patrão ao final do século XX foram capazes de conter o desenvolvimento do fenômeno político denominado clientelismo. Um tipo de prática difícil de mensurar, sobretudo, porque para confirmar a troca do voto por algum benefício é necessário que o eleitor admita ter participado desse tipo de transação, ou que o candidato admita ter proposto esse tipo de situação aos eleitores. A confissão é pouco provável de ocorrer, principalmente em decorrência das punições eleitorais e jurídicas que recaem sobre ambos. Para contornar essa dificuldade se optou por tomar apenas o eleitor brasileiro como objeto de análise, e questionar se suas características demográficas, socioeconômicas ou culturais favorecem o clientelismo no Brasil? A delimitação temporal consistiu no período com início no ano de 2000 e término no ano de 2010. Se decidiu trabalhar com duas linhas de investigação: a) mensurar a oferta do clientelismo pelo político ao eleitor; b) mensurar a aprovação do eleitor para uma situação específica de clientelismo vivenciada por si ou por outros. As hipóteses adotadas de início foram: (H1) residir em município de pequeno porte populacional aumenta a probabilidade da oferta clientelista ao eleitor brasileiro; (H2) possuir pouca renda mensal aumenta o risco da oferta e da aprovação ao clientelismo no Brasil; (H3) possuir uma cultura política paroquial aumenta a probabilidade da aprovação do clientelismo pelo eleitor brasileiro. Os resultados obtidos ao final da tese desmentem a maioria das afirmações embasadas no senso comum, algumas realizadas por pesquisadores da área, e todas as hipóteses da tese. Eles demonstram que a região de residência do eleitor e sua idade foram significativas para a ocorrência da oferta clientelista, e que nenhuma das características da população de eleitores foi capaz de influenciar em sua aprovação ao clientelismo na primeira década de 2000. / Even though the negotiation of the vote in exchange of the most varied benefits has landed in the country along with the Portuguese crown at the beginning of the XIX century, it is noticed that it does not decreased in Brazilian political History. Not even the fall of the monarchy and instauration of the Republic and their values, the loss of the power of the colonels, the implementation of harsher electoral punishments to the voting dealers or even the introduction of eletronic voting to difficult the accountability of the cliente elector to the political boss at the end of the 20th century were able to contain the development of the political phenomenon called clientelism. A type of practice that is difficult to measure because to confirm the exchange of votes for some benefits is necessary that the voter admits to having participated of this type of transaction or that the candidate admits that he has proposed this type of situation to the voters. The confession is unlikely to occur mainly due to electoral and legal punishments that fall in both. To get around this difficulty, it was decided to take only Brazilian voter as the object of analysis and question whether if their demographic, socioeconomic and cultural characteristics favor clientelism in Brazil. The temporal delimitation constitutes in the period beginning in the year 2000 and finish in the year 2010. It was decided to work with two lines of research: a) measure the offer of the clientelismo by the politician to the voter; b) measure the voter approval for a specific situation experienced by itself or others. The hypotheses adopted at the beginning were: (H1) inhabit in the municipality of small population increases the probability of clientelist offer to the Brazilian voter; (H2) having a small monthly income increases the risk; (H3) have a parochial political culture increases the probability of the clientelism approval by the Brazilian voter. The results obtained at the end of the thesis disprove most of the common sense affirmations, some performed by researchers in the área and all hypotheses of the thesis. They demonstrate that the region of residence to the voter and his age were significant for the occurence of clientelistic and that none of the characteristics of the population of the voters was able to influence their approval to the clientelism in the first decade of 2000.

Neste estudo, baseado na análise de séries temporais para um período de 8 anos, correlacionou-se os casos de dengue com as variáveis climáticas das cidades da Baixada Santista (sudeste brasileiro) e de Cingapura (sudeste asiático). O estudo foi feito com o uso de um modelo de regressão de Poisson (MRP), que considera os casos de dengue como a variável dependente e as variáveis climáticas: precipitação, temperatura (máxima e mínima) e umidade relativa (máxima e mínima) como as variáveis independentes. Também foi utilizada a Análise de Componentes Principais (ACP) para escolher as variáveis que influenciam no aumento do número de casos de dengue nas cidades estudadas. A CP1 (componente principal 1) foi representada pelas temperaturas (máxima e mínima) e a precipitação e a CP2 (componente principal 2) pela umidade relativa (máxima e mínima). Calculou-se o acréscimo dos novos casos de dengue e o risco relativo de ocorrência da doença por influência de cada uma das variáveis climáticas. Na Baixada Santista, os maiores valores de precipitação e temperatura ocorrem nos meses de dezembro e janeiro (verão) e o aumento dos casos de dengue ocorre nos meses de março a maio (outono). Para Cingapura, a diminuição da precipitação e o aumento da temperatura ocorrem nos meses de março a maio (pré-monção de sudoeste), e, portanto, observa-se o aumento dos casos de dengue nos meses de junho a outubro (monção de sudoeste). Os resultados foram: em Cingapura, para 2oC a 10oC de variação na temperatura (máxima e mínima), houve um aumento médio dos casos de dengue de 22,2% a 184,6% (máxima) e de 26,1% a 230,3% (mínima). O risco relativo médio foi de 1,2% a 2,9% e de 1,3% a 3,3%, respectivamente. Para precipitação, a variação de 5mm a 55mm, houve o aumento dos casos de dengue de 5,6% a 83,2%, sendo e o risco relativo médio foi de 1,06% a 1,83%. A umidade relativa após a análise de correlação foi descartada no uso do modelo de regressão de Poisson por apresentar uma correlação muito baixa. Para a Baixada Santista, a variação da temperatura de 2oC a 10oC apresentou um acréscimo médio nos casos de dengue de 19,6% a 154,4% (máxima) e de 18,2% a 145,4% (mínima). O risco relativo médio foi de 1,20% a 2,54% e de 1,18% a 2,45%, respectivamente. A variação da precipitação de 5mm a 55mm apresentou um aumento dos casos de dengue de 3,92% a 53,10%. A umidade relativa mínima variando de 2% a 10%, o acréscimo dos casos de dengue foi 7,7% a 49,4%, sendo que o risco relativo foi de 1,08% a 1,49%. Assim, após várias análises, a temperatura mínima foi um dos preditores para ocorrência do aumento dos casos de dengue em Cingapura, sendo que há uma influência bem particular da precipitação, na qual, atua significativamente no período seco (pré-monção de sudoeste). Enquanto que na Baixada Santista as influências mais significativas foram da temperatura (máxima e mínima) e precipitação, que desenvolvem conjuntamente um bom cenário de atuação do vetor no período do outono / In this study, based on time series analysis for a period of eight years, correlated dengue cases with climatic variables in the cities of Santos (southeastern Brazil) and Singapore (Southeast Asia). The study was done using a Poisson regression model (PRM), which considers the cases of dengue as the dependent variable and climatic variables: precipitation, temperature (maximum and minimum) and relative humidity (maximum and minimum) as the independent variables. Also we used the Principal Component Analysis (PCA) to select the variables that influence the increase in the number of dengue cases in the cities studied. The PC1 (principal component 1) was represented by the temperatures (maximum and minimum) and precipitation and the PC2 (principal component 2) the relative humidity (maximum and minimum). We calculated the addition of new dengue cases and relative risk of disease influenced by each variable climate. In Baixada Santista, the highest values of precipitation and temperature occur in the months of December and January (summer) and the increase in dengue cases occur in the months from March to May (autumn). For Singapore, the decrease in precipitation and temperature increase occurring in the months March to May (southwest inter-monsoon) and hence there is an increase of dengue cases in the months from June to October (southwest monsoon). The results were in Singapore for 2oC to 10oC change in temperature (maximum and minimum), there was an average increase of dengue cases from 22.2% to 184.6% (maximum) and 26.1% at 230 3% (minimum). The average relative risk was 1.2% to 2.9% and 1.3% to 3.3%, respectively. For precipitation, the range of 5mm to 55mm, there was an increase of dengue cases from 5.6% to 83.2%, with and average relative risk was 1.06% to 1.83%. The relative humidity after the correlation analysis was discarded in the use of Poisson regression model for presenting a very low correlation. For Baixada Santista, the variation of temperature of 2oC to 10oC showed an average increase in the dengue cases from 19.6% to 154.4% (maximum) and 18.2% to 145.4% (minimum). The average relative risk is 1.20% to 2.54% and 1.18% to 2.45%, respectively. The variation in the precipitation of 5mm to 55mm showed an increase in dengue cases from 3.92% to 53.10%. The minimum relative humidity ranging from 2% to 10%, the increase of dengue cases was 7.7% to 49.4%, and the relative risk was 1.08% to 1.49%. Thus, after several analyzes, the minimum temperature was one of the predictors for the occurrence of the increase of dengue cases in Singapore, and there is a very particular influence of the precipitation, in which it acts significantly in the dry season (southwest inter-monsoon). While in Baixada Santista were the most significant influences of temperature (maximum and minimum) and precipitation, which jointly develop a good field of action of the vector in the autumn