Longevity risk and the econometric analysis of mortality trends and volatility

Working paper - Australian School of Business Research Paper No. 2009ACTL08Longevity risk and the modeling of trends and volatility for mortality improvement has attracted increased attention driven by ageing populations around the world and the expected financial implications. The original Lee-Carter model that was used for longevity risk assessment included a single improvement factor with differential impacts by age. Financial models that allow for risk pricing and risk management have attracted increasing attention along with multiple factor models. This paper investigates trends, including common trends through co-integration, and the factors driving the volatility of mortality using principal components analysis for a number of developed countries including Australia, England, Japan, Norway and USA. The results demonstrate the need for multiple factors for modeling mortality rates across all these countries. The basic structure of the Lee-Carter model can not adequately model the random variation and the full risk structure of mortality changes. Trends by country are found to be stochastic. Common trends and co-integrating relationships are found across ages highlighting the benefits from modeling mortality rates as a system in a Vector-Autoregressive (VAR) model and capturing long run equilibrium relationships in a Vector Error-Correction Model (VECM) framework.Longevity risk and the modeling of trends and volatility for mortality improvement has attracted increased attention driven by ageing populations around the world and the expected financial implications. The original Lee-Carter model that was used for longevity risk assessment included a single improvement factor with differential impacts by age. Financial models that allow for risk pricing and risk management have attracted increasing attention along with multiple factor models. This paper investigates trends, including common trends through co-integration, and the factors driving the volatility of mortality using principal components analysis for a number of developed countries including Australia, England, Japan, Norway and USA. The results demonstrate the need for multiple factors for modeling mortality rates across all these countries. The basic structure of the Lee-Carter model can not adequately model the random variation and the full risk structure of mortality changes. Trends by country are found to be stochastic. Common trends and co-integrating relationships are found across ages highlighting the benefi ts from modeling mortality rates as a system in a Vector-Autoregressive (VAR) model and capturing long run equilibrium relationships in a Vector Error-Correction Model (VECM) framework

Modeling mortality with a bayesian vector autoregression

Paper presented at Strathmore International Math Research Conference on July 23 - 27, 2012Mortality risk models have been developed to capture trends and common factors driving mortality improvement. Multiple factor models take many forms and are often developed and fitted to older ages. In order to capture trends from young ages it is necessary to take into account the richer age structure of mortality improvement from young ages to middle and then into older ages. The Heligman and Pollard (1980) model is a parametric model which captures the main features of period mortality tables and has parameters that are interpreted according to age range and effect on rates. Although time series techniques have been applied to model parameters in various parametric mortality models, there has been limited analysis of parameter risk using Bayesian techniques. This paper uses a Bayesian Vector Autoregressive (BVAR) model for the parameters of the Heligman-Pollard model and fits the model to Australian data. As VARmodels allow for dependence between the parameters of the Heligman-Pollard model they are flexible and better reflect trends in the data, giving better forecasts of the parameters. Forecasts can readily incorporate parameter uncertainty using the models. Bayesian Vector Autoregressive (BVAR) models are shown to significantly improve the forecast accuracy of VAR models for mortality rates based on Australian data. The Bayesian model allows for parameter uncertainty, shown to be a significant component of total risk.Mortality risk models have been developed to capture trends and common factors driving mortality improvement. Multiple factor models take many forms and are often developed and fitted to older ages. In order to capture trends from young ages it is necessary to take into account the richer age structure of mortality improvement from young ages to middle and then into older ages. The Heligman and Pollard (1980) model is a parametric model which captures the main features of period mortality tables and has parameters that are interpreted according to age range and effect on rates. Although time series techniques have been applied to model parameters in various parametric mortality models, there has been limited analysis of parameter risk using Bayesian techniques. This paper uses a Bayesian Vector Autoregressive (BVAR) model for the parameters of the Heligman-Pollard model and fits the model to Australian data. As VARmodels allow for dependence between the parameters of the Heligman-Pollard model they are flexible and better reflect trends in the data, giving better forecasts of the parameters. Forecasts can readily incorporate parameter uncertainty using the models. Bayesian Vector Autoregressive (BVAR) models are shown to significantly improve the forecast accuracy of VAR models for mortality rates based on Australian data. The Bayesian model allows for parameter uncertainty, shown to be a significant component of total risk

Understanding the relationship between prevalence of microfilariae and antigenaemia using a model of lymphatic filariasis infection.

BACKGROUND: Lymphatic filariasis is a debilitating neglected tropical disease that affects impoverished communities. Rapid diagnostic tests of antigenaemia are a practical alternative to parasitological tests of microfilaraemia for mapping and surveillance. However the relationship between these two methods of measuring burden has previously been difficult to interpret. METHODS: A statistical model of the distribution of worm burden and microfilariae (mf) and resulting antigenaemic and mf prevalence was developed and fitted to surveys of two contrasting sentinel sites undergoing interventions. The fitted model was then used to explore the relationship in various pre- and post-intervention scenarios. RESULTS: The model had good quantitative agreement with the data and provided estimates of the reduction in mf output due to treatment. When extrapolating the results to a range of prevalences there was good qualitative agreement with published data. CONCLUSIONS: The observed relationship between antigenamic and mf prevalence is a natural consequence of the relationship between prevalence and intensity of adult worms and mf production. The method described here allows the estimation of key epidemiological parameters and consequently gives insight into the efficacy of an intervention programme

Modelling strategies to break transmission of lymphatic filariasis : aggregation, adherence and vector competence greatly alter elimination

Background: With ambitious targets to eliminate lymphatic filariasis over the coming years, there is a need to identify optimal strategies to achieve them in areas with different baseline prevalence and stages of control. Modelling can assist in identifying what data should be collected and what strategies are best for which scenarios. Methods: We develop a new individual-based, stochastic mathematical model of the transmission of lymphatic filariasis. We validate the model by fitting to a first time point and predicting future timepoints from surveillance data in Kenya and Sri Lanka, which have different vectors and different stages of the control programme. We then simulate different treatment scenarios in low, medium and high transmission settings, comparing once yearly mass drug administration (MDA) with more frequent MDA and higher coverage. We investigate the potential impact that vector control, systematic non-compliance and different levels of aggregation have on the dynamics of transmission and control. Results: In all settings, increasing coverage from 65 to 80 % has a similar impact on control to treating twice a year at 65 % coverage, for fewer drug treatments being distributed. Vector control has a large impact, even at moderate levels. The extent of aggregation of parasite loads amongst a small portion of the population, which has been estimated to be highly variable in different settings, can undermine the success of a programme, particularly if high risk sub-communities are not accessing interventions. Conclusion: Even moderate levels of vector control have a large impact both on the reduction in prevalence and the maintenance of gains made during MDA, even when parasite loads are highly aggregated, and use of vector control is at moderate levels. For the same prevalence, differences in aggregation and adherence can result in very different dynamics. The novel analysis of a small amount of surveillance data and resulting simulations highlight the need for more individual level data to be analysed to effectively tailor programmes in the drive for elimination

Understanding the relationship between prevalence of microfilariae and antigenaemia using a model of lymphatic filariasis infection

Background: Lymphatic filariasis is a debilitating neglected tropical disease that affects impoverished communities. Rapid diagnostic tests of antigenaemia are a practical alternative to parasitological tests of microfilaraemia for mapping and surveillance. However the relationship between these two methods of measuring burden has previously been difficult to interpret. Methods: A statistical model of the distribution of worm burden and microfilariae (mf) and resulting antigenaemic and mf prevalence was developed and fitted to surveys of two contrasting sentinel sites undergoing interventions. The fitted model was then used to explore the relationship in various pre- and post-intervention scenarios. Results: The model had good quantitative agreement with the data and provided estimates of the reduction in mf output due to treatment. When extrapolating the results to a range of prevalences there was good qualitative agreement with published data. Conclusions: The observed relationship between antigenamic and mf prevalence is a natural consequence of the relationship between prevalence and intensity of adult worms and mf production. The method described here allows the estimation of key epidemiological parameters and consequently gives insight into the efficacy of an intervention programme

Adult population as potential reservoir of NTD infections in rural villages of Kwale district, Coastal Kenya: implications for preventive chemotherapy interventions policy

<p>Abstract</p> <p>Background</p> <p>Neglected tropical diseases (NTDs) are major public health problems in developing countries where they contribute to suffering of populations living in poor settings. As part of a research project started in September 2009 in Kwale district, Coast Region, Kenya, a baseline cross-sectional survey was conducted in 5 rural villages to provide information on the status of NTDs, including urinary schistosomiasis, soil-transmitted helminthiasis (STH), and lymphatic filariasis. This paper presents the results of a parasitological investigation among adults in the study villages.</p> <p>Methods</p> <p>A total of 599 adults in the 5 study villages were tested for NTD infections in urine, stool and blood. The presence of <it>Schistosoma haematobium </it>infection was determined by the urine filtration method. The presence of STH in stool was determined by Kato-Katz method while filarial antigenaemia was determined using immunochromatographic (ICT) test.</p> <p>Results</p> <p>The study revealed high prevalence of hookworm (41.7%) and schistosomiasis (18.2%) infections among adults in the study villages. Of the 599 individuals examined, 50.1% had one or more helminthic infections. There was low level of polyparasitism with helminthic NTDs in the study population with 9.5% and 1.7% of the participants having two and three infections, respectively.</p> <p>Conclusions</p> <p>In the current study, hookworm and schistosomiasis infections were identified as important infections among adults living in areas of high endemicity for these infections. Thus, if this section of the population is left untreated it may remain an important potential reservoir and a source of re-infection for school-age children treated in school deworming programmes. Therefore, there is a need to design novel strategies for preventive chemotherapy interventions that could allow inclusion of adults in an effort to reduce force of infection in high endemic communities.</p

Youth Savings Patterns and Performance in Colombia, Ghana, Kenya, and Nepal: YouthSave Research Report 2015

If offered an opportunity to save via formal financial services, will youth in developing countries participate, save, and accumulate assets? This is one of the key questions in YouthSave, a savings initiative implemented in four developing countries, targeting youth aged 12 to 18 years, from predominantly low-income households. This report presents two-year findings from a study that tracks account uptake and saving patterns and performance in youth savings accounts in four countries: Colombia, Ghana, Kenya, and Nepal. This savings demand assessment (SDA) is ambitious in its attempt to include systematic data on as many youth savers as possible. The result is a very large dataset that enables us to report in detail who is saving, and factors associated with saving patterns and performance. The report is divided into four sections: the ten key findings; the project summary; the body, which consists of Chapters 1 through 9 and summarizes information across all four countries; and the appendices, which include country-specific details and summary tables. A summary of findings appears at the end of each chapter

Youth Savings Patterns and Performance in Colombia, Ghana, Kenya, and Nepal

Youth Savings Patterns and Performance in Colombia, Ghana, Kenya, and Nepa

Youth Savings Patterns and Performance in Colombia, Ghana, Kenya, and Nepal: Executive Summary

This summary presents an overview of findings from the YouthSave Project\u27s 2015 research report Youth Savings Patterns and Performance in Columbia, Ghana, Kenya, and Nepal. Created in partnership with the MasterCard Foundation, YouthSave investigated the potential of savings accounts as a tool for youth development and financial inclusion in developing countries by co-designing tailored, sustainable savings products with local financial institutions and assessing their performance and development outcomes with local researchers. This study tracked account uptake, saving patterns, and savings performance in youth savings accounts in Colombia, Ghana, Kenya, and Nepal