Background: Climate change has increased the frequency, intensity, duration, and spatial extent of some extreme weather events, for instance heat waves. Societies today are experiencing an ongoing change in the population structure yielding an increasing proportion elderly due to increased longevity, resulting in higher prevalence of chronic and degenerative diseases. Literature suggests that the elderly and certain susceptible subgroups with chronic disease are among the most vulnerable to heat waves and elevated temperatures. Aim: The main aims of this thesis were to expand the scientific knowledge on the short-term effects of extreme heat on mortality for the general population and certain susceptible groups in society, to investigate the development of this relationship over time and to attribute mortality to observed climate change. Methods: Daily numbers of deaths and daily meteorological observations during three different periods were collected for present day Stockholm County, Sweden. The analyses of the relationship between mortality and temperature extremes were analysed using a time series approach. The regression models assumed the daily counts of mortality to follow an overdispersed Poisson distribution and adjustments were made for time-trends as well as confounding factors. Results: The literature review of recent studies identified a strong relationship between heat and heat waves and increasing death rates among the elderly, particularly for respiratory and cardiovascular mortality. A statistically significant increase in total daily mortality during heat extremes in all decades investigated, as well as over the entire period, during the period 1901-2009 with a declining trend over time for the relative risk associated with heat extremes, was reported in paper II. For the period 1901-2009 cold extremes significantly increased mortality, with a more disperse pattern over individual decades and no declining trend over time. Paper III attributed increased mortality due to climate change between 1900-1929 and 1980-2009. This increase was mainly due to a large number of excess heat extremes in the latter time period. Furthermore certain subgroups of the population above 50, were in paper IV found to have significantly increased mortality during heat waves as compared to non-heat wave days. Conclusions: Although the relative risk of dying during extreme temperature events appears to have fallen in Stockholm, Sweden, such events still pose a threat to public health. The elderly population and certain susceptible subgroups of the population experience higher relative risks of dying on heat waves days as compared to normal summer days. Some of the groups most susceptible during heat waves were identified. In order to minimize future impacts of heat waves on public health, identifying susceptible subgroups in an ageing society as well as develop strategies to reduce the impact of future temperature extremes on public health will be important.

No description available.

Albania was noteworthy, not just for the isolationist policy of its government, or its domestic rigid policies applied to Europe's poorest country, but because of its high life expectancy at birth. At the end of the eighties, life expectancy at birth passed the boundary of seventy, although the country's GDP per capita was $2500 in 1990, the lowest in Europe (Madison 1995).This puzzled scholars, who either doubted the success of Albania, or because of the lack of firm information, speculated with different explanations (Watson, 1995). This research was initiated by this controversy in trying to first, estimate the scale of Albania's success in improving life expectancy and document the mortality transition in Albania during the period 1950-1990. It also looks at the social, economic and political factors behind the success of improving life expectancy at birth from 51 to 71 years in a relatively short period of 40 years. The research attempts to explain why the Albanian pattern of mortality, with very high infant and child mortality and very low adult mortality, is so different from that of other East European countries, which had the same social and economic backgrounds. The analysis concludes that the life style factors are the most likely factors in explaining the controversial mortality pattern of Albania. The research uses a new set of complete data, obtained from formerly-closed Albanian State Archives, which were made available only after 1994. It is the first time that the cause specific data are used to analyse the mortality transition in Albania. The research starts with a description of country's cultural and historical background. It continues with the political, social and economic transition during the communist rule 1945-1990, which are of particular importance in understanding the demographic regime in general, and the mortality transition in particular (Caldwell, 1986). The research continues with a detailed analysis of the availability and quality of mortality data. The analysis of mortality trends and patterns during this period confirms the success of Albania in achieving high life expectancy at birth by the end of eighties. It also shows that this was achieved by very low adult mortality, and relatively high infant and child mortality. The later analysis shows that this finding is related to the cause specific pattern of mortality, as well as regional differences within the country. The research ends with an international comparison of mortality trends and patterns in Albania, in the context of whether the Albanian success was part of the experience of countries that had "a good health at low cost" (Caldwell, 1986), or if the Albanian way is another route to low mortality.

This thesis explores the feasibility of the application of statistical regression theory to the curve fitting of mortality data. Equations derived from Makeham's first law were used. These include:1x = ksxgcXlog lx=a+hx+bcx color pX = A + BcxThe 1941 CSO and 1958 CSO mortality tables were used for initial study.Extending this work, pure raw mortality data in conjunction with a modified version of the last equation above was employed. Results were quite interesting.

The following study analyzes birthweight-specific neonatal health using a combination of a mixture model and logistic regression: the extended Parametric Mixture of Logistic Regression. The data are collected from the Obstetric database at Muhimbili National Hospital in Dar es Salaam, Tanzania and the years 2009 -2013 are used in the analysis. Due to rounding in the birthweight data a novel method to adjust for rounding when estimating a mixture model is applied. The influence of rounding on the estimates is then investigated. A three-component model is selected. The variables used in the analysis of neonatal health are early neonatal mortality, if the mother has HIV, anaemia, is a private patient and if the neonate is born after 36 completed weeks of gestation. It can be concluded that the mortality rates are high especially for low birthweights (2000 or less) in the estimated first and second components. However, due to wide confidence bounds it is hard to draw conclusions from the data.

No description available.

Background: Staphylococcus aureus (SA) infections are common and important within the hospital environment. The case fatality rate of invasive Staphylococcus aureus (SA) infections is between 20-40%. Whether the infection is due to methicillin resistant SA (MRSA) or methicillin sensitive SA (MSSA) may determine outcomes. Literature to date is inconclusive regarding whether antimicrobial resistance in SA affects patient outcomes. Host factors, infection-host interactions, and treatment-related factors may also influence case fatality. Objectives: The purpose of this study was to determine if patients with MRSA invasive infections were more likely to die than those with MSSA invasive infections, and what factors were associated with death. Methods: A retrospective matched case control study was designed, comparing cases of MRSA with controls of MSSA invasive disease from hospitals participating in the Canadian Nosocomial Infection Surveillance Program (CNISP). Two analyses were run: the first, to identify the variables associated with MRSA vs. MSSA infections, and the second, to determine the variables associated with death in invasive Staphylococcal aureus (S. aureus) infections. Backward logistic regression analysis was used for the MRSA vs. MSSA analysis and a hierarchical logistic regression model for assessment of risk factors for death. Results: In the logistic regression MRSA model the variables: recent prior use of antibiotics, Charlson Comorbidity Index score > 2 and not having received appropriate empiric antibiotics were associated with MRSA vs. MSSA infections. The hierarchical model identified older age, higher CCI scores, immunosuppression, bloodstream infection, septic shock, neurological dysfunction and not receiving appropriate empiric antibiotic as associated with death. MRSA infection was not more likely to be associated with increased mortality than MSSA infection. Those with a resistant infection (MRSA) however, were less likely to receive appropriate empiric antibiotic treatment. Conclusions: Appropriate empiric antibiotics are the most important and only modifiable risk factor identified. Elderly patients who are on immunosuppressive drugs and have chronic comorbid conditions need to be monitored and screened more often since they are more at risk for death than others.

For life insurance and annuity products whose payoffs depend on the future mortality rates, there is a risk that realized mortality rates will be different from the anticipated rates accounted for in their pricing and reserving calculations. This is termed as mortality risk. Since mortality risk is difficult to diversify and has significant financial impacts on insurance policies and pension plans, it is now a well-accepted fact that stochastic approaches shall be adopted to model the mortality risk and to evaluate the mortality-linked securities. The objective of this thesis is to propose the use of a time-changed Markov process to describe stochastic mortality dynamics for pricing and risk management purposes. Analytical and empirical properties of this dynamics have been investigated using a matrix-analytic methodology. Applications of the proposed model in the evaluation of fair values for mortality linked securities have also been explored. To be more specific, we consider a finite-state Markov process with one absorbing state. This Markov process is related to an underlying aging mechanism and the survival time is viewed as the time until absorption. The resulting distribution for the survival time is a so-called phase-type distribution. This approach is different from the traditional curve fitting mortality models in the sense that the survival probabilities are now linked with an underlying Markov aging process. Markov mathematical and phase-type distribution theories therefore provide us a flexible and tractable framework to model the mortality dynamics. And the time-changed Markov process allows us to incorporate the uncertainties embedded in the future mortality evolution. The proposed model has been applied to price the EIB/BNP Longevity Bonds and other mortality derivatives under the independent assumption of interest rate and mortality rate. A calibrating method for the model is suggested so that it can utilize both the market price information involving the relevant mortality risk and the latest mortality projection. The proposed model has also been fitted to various type of population mortality data for empirical study. The fitting results show that our model can interpret the stylized mortality patterns very well.

Background: Staphylococcus aureus (SA) infections are common and important within the hospital environment. The case fatality rate of invasive Staphylococcus aureus (SA) infections is between 20-40%. Whether the infection is due to methicillin resistant SA (MRSA) or methicillin sensitive SA (MSSA) may determine outcomes. Literature to date is inconclusive regarding whether antimicrobial resistance in SA affects patient outcomes. Host factors, infection-host interactions, and treatment-related factors may also influence case fatality. Objectives: The purpose of this study was to determine if patients with MRSA invasive infections were more likely to die than those with MSSA invasive infections, and what factors were associated with death. Methods: A retrospective matched case control study was designed, comparing cases of MRSA with controls of MSSA invasive disease from hospitals participating in the Canadian Nosocomial Infection Surveillance Program (CNISP). Two analyses were run: the first, to identify the variables associated with MRSA vs. MSSA infections, and the second, to determine the variables associated with death in invasive Staphylococcal aureus (S. aureus) infections. Backward logistic regression analysis was used for the MRSA vs. MSSA analysis and a hierarchical logistic regression model for assessment of risk factors for death. Results: In the logistic regression MRSA model the variables: recent prior use of antibiotics, Charlson Comorbidity Index score > 2 and not having received appropriate empiric antibiotics were associated with MRSA vs. MSSA infections. The hierarchical model identified older age, higher CCI scores, immunosuppression, bloodstream infection, septic shock, neurological dysfunction and not receiving appropriate empiric antibiotic as associated with death. MRSA infection was not more likely to be associated with increased mortality than MSSA infection. Those with a resistant infection (MRSA) however, were less likely to receive appropriate empiric antibiotic treatment. Conclusions: Appropriate empiric antibiotics are the most important and only modifiable risk factor identified. Elderly patients who are on immunosuppressive drugs and have chronic comorbid conditions need to be monitored and screened more often since they are more at risk for death than others.

No description available.