scholarly journals A BAYESIAN JOINT MODEL FOR POPULATION AND PORTFOLIO-SPECIFIC MORTALITY

2017 ◽  
Vol 47 (3) ◽  
pp. 681-713 ◽  
Author(s):  
Frank van Berkum ◽  
Katrien Antonio ◽  
Michel Vellekoop
Keyword(s):  
Parameter Uncertainty ◽  
Mortality Rates ◽  
Insurance Companies ◽  
Posterior Distributions ◽  
Short Term ◽  
Specific Mortality ◽  
Extensive Information ◽  
Specific Factors ◽  
Population Mortality ◽  
Bayesian Joint Model

AbstractInsurance companies and pension funds must value liabilities using mortality rates that are appropriate for their portfolio. These can only be estimated in a reliable way from a sufficiently large historical dataset for such portfolios, which is often not available. We overcome this problem by introducing a model to estimate portfolio-specific mortality simultaneously with population mortality. By using a Bayesian framework, we automatically generate the appropriate weighting for the limited statistical information in a given portfolio and the more extensive information that is available for the whole population. This allows us to separate parameter uncertainty from uncertainty due to the randomness in individual deaths for a given realization of mortality rates. When we apply our method to a dataset of assured lives in England and Wales, we find that different prior specifications for the portfolio-specific factors lead to significantly different posterior distributions for hazard rates. However, in short-term predictive distributions for future numbers of deaths, individual mortality risk turns out to be more important than parameter uncertainty in the portfolio-specific factors, both for large and for small portfolios.

scholarly journals Risk of death among people with rare autoimmune diseases compared to the general population in England during the 2020 COVID-19 pandemic

Rheumatology ◽  
2020 ◽  
Author(s):  
Emily Peach ◽  
Megan Rutter ◽  
Peter Lanyon ◽  
Matthew J Grainge ◽  
Richard Hubbard ◽  
...  
Keyword(s):  
General Population ◽  
Healthcare Services ◽  
Mortality Rates ◽  
Published Data ◽  
Risk Of Death ◽  
Increased Risk ◽  
Specific Mortality ◽  
Population Mortality ◽  
The Uk ◽  
Recorded Diagnosis

Abstract Objectives To quantify the risk of death among people with rare autoimmune rheumatic diseases (RAIRD) during the UK 2020 COVID-19 pandemic compared with the general population, and compared with their pre-COVID risk. Methods We conducted a cohort study in Hospital Episode Statistics for England 2003 onwards, and linked data from the NHS Personal Demographics Service. We used ONS published data for general population mortality rates. Results We included 168 691 people with a recorded diagnosis of RAIRD alive on 01/03/2020. Their median age was 61.7 (IQR 41.5–75.4) years, and 118 379 (70.2%) were female. Our case ascertainment methods had a positive predictive value of 85%. 1,815 (1.1%) participants died during March and April 2020. The age-standardised mortality rate (ASMR) among people with RAIRD (3669.3, 95% CI 3500.4–3838.1 per 100 000 person-years) was 1.44 (95% CI 1.42–1.45) times higher than the average ASMR during the same months of the previous 5 years, whereas in the general population of England it was 1.38 times higher. Age-specific mortality rates in people with RAIRD compared with the pre-COVID rates were higher from the age of 35 upwards, whereas in the general population the increased risk began from age 55 upwards. Women had a greater increase in mortality rates during COVID-19 compared with men. Conclusion The risk of all-cause death is more prominently raised during COVID-19 among people with RAIRD than among the general population. We urgently need to quantify how much risk is due to COVID-19 infection and how much is due to disruption to healthcare services.

scholarly journals Monitoring progress with national and subnational health goals by integrating verbal autopsy and medically certified cause of death data

2021 ◽  
Vol 6 (5) ◽  
pp. e005387
Author(s):  
Tim Adair ◽  
Sonja Firth ◽  
Tint Pa Pa Phyo ◽  
Khin Sandar Bo ◽  
Alan D Lopez
Keyword(s):  
Cause Of Death ◽  
Verbal Autopsy ◽  
Integration Method ◽  
Mortality Rates ◽  
Vital Statistics ◽  
Death Registration ◽  
Chronic Respiratory Diseases ◽  
Health Goals ◽  
Specific Mortality ◽  
Four Causes

IntroductionThe measurement of progress towards many Sustainable Development Goals (SDG) and other health goals requires accurate and timely all-cause and cause of death (COD) data. However, existing guidance to countries to calculate these indicators is inadequate for populations with incomplete death registration and poor-quality COD data. We introduce a replicable method to estimate national and subnational cause-specific mortality rates (and hence many such indicators) where death registration is incomplete by integrating data from Medical Certificates of Cause of Death (MCCOD) for hospital deaths with routine verbal autopsy (VA) for community deaths.MethodsThe integration method calculates population-level cause-specific mortality fractions (CSMFs) from the CSMFs of MCCODs and VAs weighted by estimated deaths in hospitals and the community. Estimated deaths are calculated by applying the empirical completeness method to incomplete death registration/reporting. The resultant cause-specific mortality rates are used to estimate SDG Indicator 23: mortality between ages 30 and 70 years from cardiovascular diseases, cancers, chronic respiratory diseases and diabetes. We demonstrate the method using nationally representative data in Myanmar, comprising over 42 000 VAs and 7600 MCCODs.ResultsIn Myanmar in 2019, 89% of deaths were estimated to occur in the community. VAs comprised an estimated 70% of community deaths. Both the proportion of deaths in the community and CSMFs for the four causes increased with older age. We estimated that the probability of dying from any of the four causes between 30 and 70 years was 0.265 for men and 0.216 for women. This indicator is 50% higher if based on CSMFs from the integration of data sources than on MCCOD data from hospitals.ConclusionThis integration method facilitates country authorities to use their data to monitor progress with national and subnational health goals, rather than rely on estimates made by external organisations. The method is particularly relevant given the increasing application of routine VA in country Civil Registration and Vital Statistics systems.

scholarly journals Investigating the Broken-Heart Effect: a Model for Short-Term Dependence between the Remaining Lifetimes of Joint Lives

2012 ◽  
Vol 7 (2) ◽  
pp. 236-257 ◽  
Author(s):  
Jaap Spreeuw ◽  
Iqbal Owadally
Keyword(s):  
Mortality Rates ◽  
Short Term ◽  
Numerical Work ◽  
Data Set ◽  
Multiple State ◽  
Multiple State Model ◽  
Insurance Data ◽  
Over Time ◽  
Assurance Contracts

AbstractWe analyze the mortality of couples by fitting a multiple state model to a large insurance data set. We find evidence that mortality rates increase after the death of a partner and, in addition, that this phenomenon diminishes over time. This is popularly known as a “broken-heart” effect and we find that it affects widowers more than widows. Remaining lifetimes of joint lives therefore exhibit short-term dependence. We carry out numerical work involving the pricing and valuation of typical contingent assurance contracts and of a joint life and survivor annuity. If insurers ignore dependence, or mis-specify it as long-term dependence, then significant mis-pricing and inappropriate provisioning can result. Detailed numerical results are presented.

Slowing of age-specific mortality rates in Drosophila melanogaster

1993 ◽  
Vol 28 (6) ◽  
pp. 585-599 ◽  
Author(s):  
H.Henry Fukui ◽  
Liang Xiu ◽  
James W. Curtsinger
Keyword(s):  
Drosophila Melanogaster ◽  
Mortality Rates ◽  
Specific Mortality

scholarly journals Reserves of Motor-Vehicle Insurance in Finland

1962 ◽  
Vol 2 (1) ◽  
pp. 161-173 ◽  
Author(s):  
Teivo Pentikäinen
Keyword(s):  
Motor Vehicle ◽  
Insurance Companies ◽  
Accurate Calculation ◽  
Short Term ◽  
The Subject ◽  
Image Position ◽  
Premium Income ◽  
The Cost ◽  
Motor Vehicle Insurance ◽  
Cluster Points

The Ministry of Social Affairs, which acts i.a. as the supervising office in Finland, has given instructions regarding the normal reserves of insurance companies. A summary of these and some comments are given here as far as they concern motor-vehicle insurance. The instructions as far as they concern the subject referred to in the following in the items 2-6, 9 and 10, were compiled by a committee, presided over by Mr. I. Ketola, M. Sc, which availed itself of the experience of several Finnish insurance companies.In order to give a review of the system as a whole many items, which are mathematically trivial and well-known, are briefly explained.The conventional principle of “pro rata parte temporis” is followed, which leads to the well-known reserve where P is the premium income of the company. This provides that the days when the premiums fall due are approximately equally distributed over the year (which can be checked from the premium sums of the different months in the book-keeping) or at least have no cluster points in the second half of the year and that the cost of the collecting of premiums is not less than 0.2 P. A more accurate calculation takes into account i.a. temporary short term policies etc.In casu-reserve. All unpaid claims (except those mentioned later) due to accidents which occured before the end of the account year, are listed and rated one by one. Doubtful cases, e.g. where the cause of the accident is still under litigation, are calculated in accordance with the “worst” alternative.

scholarly journals Efficacy of cognitive-behavioural psychotherapy in the treatment of chronic fatigue in patients with multiple sclerosis – a literature review

2021 ◽  
Vol 21 (1) ◽  
pp. 36-40
Author(s):  
Justyna Wiśniowska ◽  
◽  
Kamilla Puławska ◽  
Keyword(s):  
Multiple Sclerosis ◽  
Chronic Fatigue ◽  
Research Groups ◽  
Long Term Effects ◽  
Short Term ◽  
Behavioural Model ◽  
Cognitive Behavioural ◽  
The Central Nervous System ◽  
Specific Factors

Fatigue is one of the most common symptoms seen in patients with multiple sclerosis. Cognitive-behavioural psychotherapy can be a non-pharmacological approach for these patients. Van Kessel and Moss-Morris developed a cognitive-behavioural model to explain multiple sclerosis-related fatigue (2006). According to this model, inflammatory and demyelinating factors present in the central nervous system trigger fatigue, while cognitive interpretation, anxiety, or depressive symptoms and resting lifestyle are maintaining factors. Based on the cognitive-behavioural model of fatigue in multiple sclerosis, a protocol encompassing 8 treatment sessions was developed. For over 10 years, studies have been conducted to verify the effectiveness of cognitive-behavioural psychotherapy in the treatment of fatigue in patients with multiple sclerosis. The so far obtained results show that cognitive-behavioural psychotherapy has a moderate short-term effect on reducing fatigue, while the effect size in the long-term is small. The obtained results were undoubtedly influenced by several factors: the heterogeneity of the procedures used, the size of the research groups, and the large number of disease-related intermediary variables. Further research should be conducted to identify specific factors responsible for the effectiveness of cognitive-behavioural psychotherapy in the treatment of fatigue and to assess the long-term effects of therapy.

Sign in / Sign up

Export Citation Format

Share Document