A high percentage of highway crashes in the United States occur at intersections. These crashes result in property damage, lost productivity, injury, and even death. Identifying intersections associated with high crash rate is very important to minimize future crashes. The purpose of this study is to develop efficient means to evaluate intersections, which may require safety improvements. The area covered by the analysis in this thesis includes Orange and Seminole Counties and the City of Orlando. The aforementioned counties and city thus represent Central Florida. Each County/City provided data that consisted of signalized intersection drawings that were either in the form of electronic or hard copies, the county's extensive crash database and a list of intersections that underwent modifications during the study period. A total of 786 intersections were used in the analysis and the crash database was made up of 4271 crashes. From the signalized intersection drawings obtained from the county's traffic engineering department, a geometry database was created to classify all intersections by the number of through lanes, number of left turning lanes, Average Annual Daily Traffic and Posted Speed limits on the Major road of the intersection. In this research, crashes and their type, e.g., rear-end, left-turn and angle as well as total crashes were investigated. Numerous models were developed first using the Poisson regression and then using the Negative Binomial approach as the data showed overdispersion. The modeling process aimed to relate geometric and traffic factors to the frequency of crashes at intersections. Expected value analysis tables were also developed to determine if an intersection had an abnormally high number of crashes. These tables can be used in assisting Traffic Engineers in identifying serious safety problems at intersections. The general models illustrated that rear-end crashes were associated with high natural logarithm of AADT on the major road and the number of lanes (major intersections, e.g. 6x4/6x6), whereas AADT on the major road did not affect left-turn crashes. Intersections with the configuration 4x2/6x2 (2 through lanes at the minor roadway) or T intersections as another category experienced an increase in left-turn crashes. Angle crashes were most frequent at one-way intersections especially in the case of 4x4 intersections. Individual models that included interaction terms with one variable at a time concluded that AADT on the major road positively influenced rear-end crashes more compared to angle and left-turn crashes. As the speed increases on the minor road, the left turn crashes are affected more when compared to angle and rear-end crashes, therefore it can be concluded that left-turn crashes are most influenced by the speed limit on the minor road compared to angle crashes and then followed by rear-end crashes. As the total number of left turn lanes increased at the intersection, thereby increasing the size of the intersection, the number of rear-end crashes increased. An overall model that contained natural logarithm of AADT on major road, total number of left turn lanes at the intersection, number of through lanes on the minor road and configuration of the intersection, as independent variables, along with interaction terms, further concluded and supported the individual models that the number of crashes (rear-end, left-turn and angle) increased as the AADT on the major road increased and the number of crashes decreased as the total number of left turn lanes at the intersection increased. Also, crashes increased as the number of through lanes on the minor road increased. The variables' interaction effects with dummies representing rear-end and left-turn crashes in the final model showed that as the AADT on the major road increased, the number of rear-end crashes increased compared to left-turn and angle crashes and also that as the total number of left turn lanes at the intersection increased, the number of left-turn crashes decreased when compared to rear-end and angle crashes. Also the number of rear-end crashes increased at major four leg intersections e.g. 6x4, 6x6 etc. This thesis demonstrated the superiority of Negative Binomial regression in modeling the frequency of crashes at signalized intersections.

This thesis presents (a) results of a field evaluation of the Traffic Speed Deflectometer (TSD) in the United States (b) deflection thresholds to classify the pavement structural condition obtained from the TSD for a small subset of the Pennsylvania secondary road network. The results of the field evaluation included: (1) repeatability of the TSD, (2) ability of the TSD to identify pavement sections with varying structural conditions, and (3) consistency between the structural number (SNeff) calculated from the TSD and SNeff calculated by the Pennsylvania Department of Transportation (PennDOT). The results showed consistent error standard deviation in the TSD measurements and that the TSD was able to identify pavement sections that varied in structural condition. Comparison of the SNeff calculated with TSD measurements, using an empirically developed equation by Rohde, with the SNeff calculated by PennDOT’s Pavement Management System based on construction history showed similar trends, although the TSD-calculated SNeff was higher. In order to develop deflection thresholds, a model that related the pavement surface condition to pavement surface age and structural condition was developed. Structural condition thresholds were then selected so that the pavement surface condition predicted from the model for a 10-year-old pavement surface fell within one of the three condition categories (Good, Fair, and Poor), to identify pavements in good, fair and poor condition. With Overall Pavement Index(OPI) characterizing the surface condition and Deflection Slope Index(DSI) characterizing the structural condition, the DSI threshold that separates structurally good from structurally fair pavements was determined as follows: (1) the OPI threshold that separates pavements with good surface condition from those with fair surface condition was obtained from the Pennsylvania Pavement Management System (PMS) and (2) the DSI thresholds were calculated using the determined OPI value and the model equation. / Master of Science / This thesis presents (a) some of the results of a field evaluation of the Traffic Speed Deflectometer (TSD) in the United States (b) deflection thresholds to classify the pavement structural condition obtained from the TSD for a small subset of the Pennsylvania secondary road network. The results of the field evaluation included: (1) repeatability of the TSD: which is the variation in repeated TSD measurements on the same section of the road, (2) ability of the TSD to identify pavement sections with varying structural conditions, and (3) consistency between the structural number (SNeff) calculated from the TSD and SNeff calculated by the Pennsylvania Department of Transportation (PennDOT). The pavement structural number is an abstract number expressing the structural strength of the pavement. The results showed that the TSD measurements were repeatable and that the TSD was able to identify pavement sections that varied in structural condition. Comparison of the SNeff calculated with TSD measurements, using an empirically developed equation by Rohde, with the SNeff calculated by PennDOT Pavement Management System based on construction history showed similar trends, although the TSD-calculated SNeff was higher. In order to develop deflection thresholds to categorize pavements in different condition: good, fair and poor, a model that related the pavement surface condition to pavement surface age and structural condition was developed. Structural condition thresholds were then selected so that the pavement surface condition predicted from the model for a 10-year-old pavement surface fell within one of the three condition categories (Good, Fair, and Poor), to identify pavements in good, fair and poor condition. With Overall Pavement Index(OPI) characterizing the surface condition and Deflection Slope Index(DSI) characterizing the structural condition, the DSI threshold that separates structurally good from structurally fair pavements was determined as follows: (1) the OPI threshold that separates pavements with good surface condition from those with fair surface condition was obtained from the Pennsylvania Pavement Management System (PMS) and (2) the DSI thresholds were calculated using the determined OPI value and the model equation.

Malaria is one of the leading causes of mortality and morbidity globally. Land use/land cover (LULC) change have been found to affect the transmission and distribution of malaria in other regions, but no study has attempted to examine such relationships in Nepal. Therefore, this study was conducted in Nepal to assess LULC change between 2000 and 2010, to study the spatial and temporal trend of malaria incidence rate (MIR) between 1999 and 2015, and to understand the relationship between LULC and malaria. The land cover types used for this study are forest, water bodies, agriculture, grassland, shrubland, barren areas, built-up areas and paddy areas. Change detection techniques were used to study LULC change. The temporal trend of MIR in 58 districts, and the relationship between MIR and LULC were evaluated using Poisson and negative binomial regression. Forest, water bodies, snow cover, and built-up area increased in Nepal by 28.5%, 2.96%, 55.12% and 21.19% respectively while the rest of the LULC variables decreased. MIR decreased significantly in 21 districts; however, four districts namely Pyuthan, Kaski, Rupandehi and Siraha had a significantly increasing trend of MIR. During 2001, 2002, and 2003, MIR was positively related to water bodies and paddy areas. Similarly, MIR of 2010 was negatively related to grassland. However, there was no relationship between LULC and MIR in 2000, 2011, 2012 and 2013. It may be because MIR is decreasing significantly in the country and thus the influence of LULC change is also decreasing. / MS

It has been proved from several studies that the genetic influence has been the most significant factor for having preeclampsia (PE). Still there are many uncertainties about origin and magnitude of the genetic effects as no specific inheritance patterns have been established. In this study, heritage risk of PE is in both the woman’s family and her partner’s family to her risk of PE is examined, along women and men own history with same and different partners. Moreover it is also examined whether timing of onset of PE is also has any impact on familial clustering of PE. Here, we used the population based Danish birth and multi generation registers to identify a cohort of women who have given birth during 1978 to 2008; which consisted of 1,79,69,28 singleton deliveries. This information is linked with pedigree information from the Danish Family Relation Database to define both maternal and paternal relationships. Risk ratios were estimated comparing women with and without various PE histories. It is found that the recurrence risk of a woman suffering from PE is 12.4 with 95% confidence limits (11.9, 12.8). Woman's recurrence risk diminishes only slightly when she changes partner means that particularly maternal genetic factors play the largest role, compared to male partner whose recurrence risk almost diminishes if he changes his female partner. Women and men from families with PE contribute to risk of PE in pregnancies they are involved in. The woman’s family history is still more important compared to man family history of PE; except for increased rick in pregnancies fathered by men who were born to preeclamptic mothers.  The recurrence risk of a women suffering from PE, if she already has suffered from this condition before 34 weeks is found to be very high (RR=25.4 with 95% confidence limits (21.8, 29.1)) with same male partner. It is found that early-onset PE and later-onset varieties have a clear genetic component but the intensity of early onset is stronger than late onset varieties. There are both maternal and paternal genetic contributions to early-onset PE, with the maternal ones seeming to be stronger.

We assessed how estimates of need-expected inpatient hospital use differ depending on whether need-expected use was estimated for a population of all Canadians, Canadian health regions, or a subpopulation of higher income Canadians, who likely had minimal healthcare access problems. Data came from the 2009/2010 Canadian Community Health Survey, a national cross-sectional survey. Using zero-inflated negative binomial regression, we modeled inpatient hospital use separately based on the three aforementioned choices of population. We adjusted for demographic, health behaviour, health status, socioeconomic, and health care supply factors. We then estimated need-expected inpatient hospital use and compared the estimates across individuals and by income and province. The three choices of population that we used in this study had similar results. Our estimates of the average need-expected use by province or income group were not sensitive to the choice of population used to estimate need-expected use.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Air pollution may be due to various economic activities, as well as natural phenomena. Regardless of the generating factor, it influences the environment and quality of life of human beings. In addition to damage the fauna and flora, air pollution can affect people's health. In Brazil, the researchers are concentrated in the state of São Paulo, with few studies in other regions of the country. This study was realized in the city of Canoas/RS and aimed to analyze the association of pollutants (PM10, O3, CO, SO2) with the number of hospitalizations, in 2014, for respiratory diseases in under 14 and over 60 years. Negative Binomial regression was used due to the presence in over dispersed in the data. The relative risks were estimated (RR) for lags (Lag) up to seven days, and the relative percentage risk (RR%) to the increase of 10 mg/m³ of PM10 and increase of difference interquartile of other pollutants. It was observed that occurred in county of Canoas, 3080 hospitalizations by respiratory diseases, in greater numbers in the elderly, which is the main cause of death in the city. With the results of this study, it was possible to verify the association of PM10 (Lag 0, Lag 1 and Lag 3), O3 (Lag 0) and SO2 (Lag 5) with hospitalizations by respiratory diseases in children and adolescents, and CO (Lag 0, Lag 4, Lag 6 and Lag 7) and O3 (Lag 3), with the number of hospitalizations for respiratory diseases in the elderly. These results confirm strong evidence that air pollution is an important risk factor for the onset and worsening of respiratory problems in county of Canoas, stressing the need for effective action to reduce emissions. / A poluição atmosférica pode ser decorrente de diversas atividades econômicas, como também de fenômenos naturais. Independentemente do fator gerador, ela exerce influência no meio ambiente e na qualidade de vida dos seres humanos. Além de prejudicar a fauna e a flora, a poluição atmosférica é capaz de afetar a saúde das pessoas. No Brasil, as pesquisas analisando os efeitos da poluição do ar na saúde se concentram no estado de São Paulo, sendo poucos os estudos desenvolvidos em outras regiões do país. Esta pesquisa foi realizada no município de Canoas/RS e teve o objetivo de analisar a associação de poluentes (MP10, O3, CO, SO2) com o número de internações, em 2014, por doenças respiratórias em menores de 14 anos e maiores de 60 anos. Foi utilizada a regressão Binomial Negativa devido à presença de sobredispersão nos dados. Foram estimados os riscos relativos (RR) para defasagens (Lag) de até sete dias, bem como o risco relativo percentual (RR%) para o incremento de 10 μg/m³ de PM10 e do incremento da diferença interquartílica dos demais poluentes. Foi observado que ocorreram, no município de Canoas, 3080 internações por doenças respiratórias, em maior número nos idosos, sendo esta a principal causa de óbito na cidade, no período analisado. Com os resultados deste estudo, foi possível verificar a associação do PM10 (Lag 0, Lag 1 e Lag 3), do O3 (Lag 0) e do SO2 (Lag 5) com internações por doenças respiratórias em crianças e adolescentes, e do CO (Lag 0, Lag 4, Lag 6 e Lag 7) e do O3 (Lag 3), com o número de internações por doenças respiratórias em idosos. Tais resultados confirmam fortes indícios de que a poluição do ar é fator de risco importante para o surgimento e agravo de problemas respiratórios no município de Canoas, alertando para a necessidade de ações efetivas para a redução da emissão de poluentes.

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Analysis of Variance (ANOVA) is the easiest and most widely used model nowadays in statistics. ANOVA however requires a set of assumptions for the model to be a valid choice and for the inferences to be accurate. Among many, ANOVA assumes the data in question is normally distributed and homogenous. However, data from most disciplines does not meet the assumption of normality and/or equal variance. Regrettably, researchers do not always check whether the assumptions are met, and if these assumptions are violated, inferences might well be wrong. We conducted a simulation study to compare the performance of standard ANOVA to Poisson and Negative Binomial models when applied to counts data. We considered different combination of sample sizes and underlying distributions. In this simulation study, we first assed Type I error for each model involved. We then compared power as well as the quality of the estimated parameters across the models.