scholarly journals Mortality Forecasts. Comments on How to Improve Existing Models – An Epidemiologist’s Perspective

2019 ◽  
pp. 79-83
Author(s):  
Kaare Christensen
Keyword(s):  
Mortality Forecasts

scholarly journals Forecasting Imminent Deaths

2021 ◽  
Author(s):  
Silvia Rizzi ◽  
James W Vaupel
Keyword(s):  
Short Term ◽  
Excess Death ◽  
Economic Changes ◽  
Behavioral Healthcare ◽  
Policy Interventions ◽  
Short Term Mortality ◽  
Short Term Forecasting ◽  
Mortality Forecasts ◽  
The Impact ◽  
Death Count

We introduce a new method for making short-term mortality forecasts of a few months, illustrating it by estimating how many deaths might have happened if some major shock had not occurred. We apply the method to assess excess mortality from March to June 2020 in Denmark and Sweden as a result of the first wave of the coronavirus pandemic, associated policy interventions and behavioral, healthcare, social and economic changes. We chose to compare Denmark and Sweden because reliable data were available and because the two countries are similar but chose different responses to covid-19: Denmark imposed a rather severe lockdown; Sweden did not. We make forecasts by age and sex to predict expected deaths if covid-19 had not struck. Subtracting these forecasts from observed deaths gives the excess death count. Excess deaths were lower in Denmark than Sweden during the first wave of the pandemic. The later/earlier ratio we propose for shortcasting is easy to understand, requires less data than more elaborate approaches, and may be useful in many countries in making both predictions about the future and the past to study the impact on mortality of coronavirus and other epidemics. In the application to Denmark and Sweden, prediction intervals are narrower and bias is less than when forecasts are based on averages of the last five years, as is often done. More generally, later/earlier ratios may prove useful in short-term forecasting of illnesses and births as well as economic and other activity that varies seasonally or periodically.

scholarly journals Assessing the use and understanding of the Portuguese Heat–Health Warning System (ÍCARO)

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
A Leite ◽  
A J Santos ◽  
S Silva ◽  
B Nunes ◽  
R Mexia ◽  
...  
Keyword(s):  
Local Level ◽  
Warning System ◽  
Action Plans ◽  
Structured Interviews ◽  
Health Warning ◽  
Key Stakeholders ◽  
Level Information ◽  
Health Action ◽  
Mortality Forecasts ◽  
Related Mortality

Abstract Background Heatwaves can lead to increased mortality. Portugal has a Heat-Health Warning System (HHWS) in place (ÍCARO system). Researchers at the Instituto Ricardo Jorge send a daily report with heat-related mortality forecasts to key stakeholders (e.g. Heat-Health Action Plans (HHAP) staff). HHAP practitioners issue warnings and implement measures to prevent heatwaves-related mortality. ICARO is amongst the recommended data sources to assess risk and issue warnings but its use and understanding is unknown. Therefore, we aimed to assess ÍCARO’s use and understanding by key HHAP practitioners. Methods We conducted semi-structured interviews with national and regional HHAP practitioners. Interviews were recorded, transcribed, and analysed using thematic content analysis. Intercoder reliability was applied to a sample of segments from 5 of 6 interviews. Results We conducted 6 interviews with 9 professionals (mean time 52 minutes). We identified 4 categories: Report’s content and presentation, Report’s reception and communication, ÍCARO and risk assessment, Other issues. Practitioners use ÍCARO and perceived it as very relevant tool. However, they mentioned several questions on its interpretation. Practitioners also felt their questions were not fully answered, given researchers’ use of statistical terms. Finally, practitioners referred the need to assess risk at the local level, information not currently provided. We also identified the need for improved communication and report’s clarity. Conclusions Our study stresses the need for an integrated collaboration between experts within HHWS and HHAP. Despite ICARO’s understanding being challenging, practitioners consider it a relevant tool. Researchers should use less statistical language and clarify ÍCARO interpretation. Practitioners’ needs should be considered when developing or revising tools. We are currently implementing some of these recommendations in an attempt to close the gap between researchers and practitioners. Key messages Portuguese Heat–Health Action Plans practitioners use heat-related mortality forecasts (ICARO) and perceived it as very relevant instrument. However there find ICARO’s interpretation challenging. Portuguese Heat/Health Action Plans Practitioners’ needs should be considered when revising or developing tools, and notes should be added to clarify statistical/technical concepts.

scholarly journals Coherent Mortality Forecasts for a Group of Populations: An Extension of the Lee-Carter Method

Demography ◽  
2005 ◽  
Vol 42 (3) ◽  
pp. 575-594 ◽  
Author(s):  
Nan Li ◽  
Ronald Demos Lee
Keyword(s):  
Mortality Forecasts

Effects of targets and aggregation on the propagation of error in mortality forecasts

1990 ◽  
Vol 2 (3) ◽  
pp. 209-227 ◽  
Author(s):  
Juha M. Alho ◽  
Bruce D. Spencer
Keyword(s):  
Mortality Forecasts

scholarly journals Identifying Structural Breaks in Stochastic Mortality Models

2015 ◽  
Vol 1 (2) ◽  
Author(s):  
Colin O’Hare ◽  
Youwei Li
Keyword(s):  
Life Expectancy ◽  
Structural Breaks ◽  
Structural Break ◽  
Mortality Rates ◽  
Insurance Companies ◽  
Mortality Data ◽  
Stochastic Mortality ◽  
Stochastic Mortality Models ◽  
Mortality Models ◽  
Mortality Forecasts

In recent years, the issue of life expectancy has become of utmost importance to pension providers, insurance companies, and government bodies in the developed world. Significant and consistent improvements in mortality rates and hence life expectancy have led to unprecedented increases in the cost of providing for older ages. This has resulted in an explosion of stochastic mortality models forecasting trends in mortality data to anticipate future life expectancy and hence quantify the costs of providing for future aging populations. Many stochastic models of mortality rates identify linear trends in mortality rates by time, age, and cohort and forecast these trends into the future by using standard statistical methods. These approaches rely on the assumption that structural breaks in the trend do not exist or do not have a significant impact on the mortality forecasts. Recent literature has started to question this assumption. In this paper, we carry out a comprehensive investigation of the presence or of structural breaks in a selection of leading mortality models. We find that structural breaks are present in the majority of cases. In particular, we find that allowing for structural break, where present, improves the forecast result significantly.

scholarly journals Mortality from COVID in Colombia and Peru: Analyses of Mortality Data and Statistical Forecasts

2020 ◽  
Author(s):  
Patrick E Brown ◽  
Zoë R Greenwald ◽  
Luis Ernesto Salinas ◽  
Gabriel Aguirre Martens ◽  
Leslie Newcombe ◽  
...  
Keyword(s):  
Mortality Data ◽  
Surge Capacity ◽  
Actual Mortality ◽  
All Cause Mortality ◽  
Extreme Variability ◽  
Mortality Forecasts ◽  
Second Peak ◽  
Ongoing Monitoring ◽  
Country Specific ◽  
Overall Mortality

AbstractNational predictions of the course of COVID mortality can be used to plan for effective healthcare responses as well as to support COVID policymaking. We developed the Global COVID Assessment of Mortality (GCAM), a statistical model with continually improving precision that combines actual mortality counts with Bayesian inference, to predict COVID trends, currently until December 1, 2020. In Colombia, the GCAM analysis found the peak of COVID mortality around August 12 and an expected total of COVID deaths of 24,000-31,000, or 48%-92% over the total through August 21. In Peru, a first mortality peak occurred around May 24, and given the current trajectory, a second peak is predicted around September 6. Peru can expect 29,000-43,000 COVID deaths, representing an increase of 7%-55% over COVID deaths through August 21. GCAM projections are also used to estimate medical surge capacity needs. To gauge the reliability of COVID mortality forecasts, we compared all-cause mortality from January through June 2020 with average all-cause mortality in previous years in Colombia and Peru, and found that the excesses were consistent with GCAM forecast, most notably a doubling of overall mortality from May 25-June 7th of weeks in Peru. The GCAM results predict that as a percentage of all adult deaths in previous years, Colombia can expect about 13% excess from COVID deaths, whereas Peru can expect 34% excess. Comparisons of GCAM analyses of several other countries with Colombia and Peru demonstrate the extreme variability that characterizes COVID mortality around the world, emphasizing the need for country-specific analyses and ongoing monitoring as more mortality data become available.

scholarly journals Coherent Mortality Model in A State-Space Approach

2021 ◽  
Vol 50 (4) ◽  
pp. 1101-1111
Author(s):  
Siti Rohani Mohd Nor ◽  
Fadhilah Yusof ◽  
Siti Mariam Norrulashikin
Keyword(s):  
State Space ◽  
Prediction Interval ◽  
Forecast Accuracy ◽  
Age Effect ◽  
Joint Estimation ◽  
Mortality Model ◽  
Proposed Model ◽  
Mortality Forecasts ◽  
Population Mortality ◽  
Life Annuities

Mortality improvements that have recently become apparent in most developing countries have significantly shaped queries on forecast divergent between populations in recent years. Therefore, to ensure a more coherent way of forecasting, previous researchers have proposed multi-population mortality model in the form of independent estimation procedures. However, similar to single-population mortality model, such independent approaches might lead to inaccurate prediction interval. As a result of this inaccurate mortality forecasts, the life expectancies and the life annuities that the mortality model aims to generate is underestimated. In this study, we propose another new extension of the multi-population mortality model in a joint estimation approach by recasting the model into a state-space framework. A combination of augmented Li-Lee and O’Hare-Li methods are employed, before we transform the proposed model into a state-space formulation. In addition, this study incorporates the quadratic age effect parameter to the proposed model to better capture the younger ages mortality. We apply the method to gender and age-specific data for Malaysia. The results show that our latter framework brings a significant contribution to the multi-population mortality model due to the incorporation of joint-estimate and quadratic age effect parameters into the model’s structure. Consequently, the proposed model improves the mortality forecast accuracy.

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