Brief Description of the Project

CARONTE aims at addressing fundamental open questions on the structure and functioning of competing death causes and their joint impact on overall mortality levels and forecasts, through the creation of innovative bridges between demography and statistics. A key lesson learned from the recent pandemic is that cause–specific mortality patterns do not propagate in isolation, but co–evolve via intricate systems of interrelated patterns that are rooted in the temporally–varying and demographically–multifaceted dependence structures underlying such causes. For example, a cause–specific death rate may decline as a result of improved treatment of a given disease or simply because other causes have grown meanwhile. Unveiling the endogenous and exogenous determinants that explain the interplay between different causes of death and their effects on overall longevity, can unlock unprecedented knowledge to learn, experiment and control current and future mortality dynamics. Despite the availability of recent studies suggesting that a full understanding of modern mortality trends necessarily requires a finer–scale analysis of cause–specific mortality, the complexity underlying the functional, compositional and discrete nature of multivariate cause–specific mortality processes still hinders progress in the field.

Motivated by the above gap, project CARONTE bridges demography and recent advancements in functional data analysis, compositional data analysis, graphical models and discrete choice models, to develop a unique statistical modeling framework which can learn the complex systems of graphical dependencies behind causes of death and unveil their combined effects on overall mortality. This will allow to:

  • Explain the dynamic co–evolution of causes of death patterns, while understanding how variations in the incidence of one cause, or groups of causes, affect current and future dynamics of the other causes.
  • Explain trends in overall mortality, along with their differences across countries and cohorts, in terms of causes of death co–evolution.
  • Study and forecasting the impact of potential mortality shocks (e.g., covid–19) and health policies on the composition, dependence and dynamics of causes of death patterns.
These outputs will push forward the research frontier by creating cutting–edge statistical models and demographic theories that may be used to assist local and national institutions in allocating resources for health care and retirement schemes, by also taking into account how specific policies addressing a certain cause of death can affect, directly or indirectly, other causes of death.

To address these goals, CARONTE will analyze several databases through an interdisciplinary approach which combines the leading expertise in demography, public health and statistics of the three Universities which are part of the project, namely Bocconi University (PI: Daniele Durante), University of Padova (co–PI: Stefano Mazzuco) and University of Rome Tor Vergata (co–PI: Marco Stefanucci). Hence, the Post–Docs hired will conduct research in a vibrant environment which promotes top research, while facilitating effective interdisciplinary collaborations and cross–fertilization across data–related fields. The PI and co–PIs of CARONTE have fruitfully collaborated in the past years within the PRIN–MIUR 2017 Grant: “Unfolding the SEcrets of LongEvity: Current Trends and future prospects" [SELECT] [Start: 08/2019 — End: 08/2023]. As witnessed by the success of SELECT in terms of scientific publications, junior recruiting and organization of national/international workshops, CARONTE can be expected to yield similarly–successful outcomes.

Team Members

[PI] Daniele Durante, AP of Statistics, Bocconi University.

[co–PI] Stefano Mazzuco, Professor of Demography, University of Padova.

[co–PI] Marco Stefanucci, AP of Statistics, University of Rome Tor Vergata

Research Progress

Publications in peer–reviewed journals and works in progress.
[10] Diaconu, V., Zarrulli, V., Mazzuco, S. (2024+). The role of causes of death in shaping dispersion around the mode in high-income countries. [work in progress].
[9] Aliverti, E., Mazzuco, S., Scarpa, B. (2024+). Evolution of sub-national longevity and causes of death composition using data on Italian provinces. [work in progress].
[8] Mazzuco, S., Stefanucci, M. (2024+). Reflections on alternative approaches in causes of death data: cause-specific hazard rates or compositions by cause?. [work in progress].
[7] Romanò, G., Aliverti, E., Durante, D. (2024+). Dynamic clustering of country-specific log-mortality rates via random partition models on B-splines expansions. [work in progress].
[6] Pozza, F., Durante, D., Szabo, B. (2024+). Skew-symmetric approximations of posterior distributions. [in review].
[5] Depaoli, E.G., Stefanucci, M., Mazzuco, S. (2024). Functional concurrent regression with compositional covariates and its application to the time-varying effect of causes of death on human longevity. The Annals of Applied Statistics, 18(2), 1668–1685.
[4] Pavone, F., Legramanti, S., Durante, D. (2024). Learning and forecasting of age-specific period mortality via B-spline processes with locally-adaptive dynamic coefficients. The Annals of Applied Statistics, 18(3), 1965–1987.
[3] Nigri, A., Levantesi, S., Scognamiglio, S. (2024). Disaggregating death rates of age-groups using deep learning algorithms. Journal of Official Statistics, 4 (2), 262–282.
[2] Bondi, L., Pagano, M., Bonetti, M. (2024). The sparsity index in Poisson size-biased sampling: Algorithms for the optimal unbiased estimation from small samples. Statistics & Probability Letters, 214, 110217.
[1] Bonetti, M., Basellini, U., Nigri, A. (2024). The average uneven mortality index: Building on the ‘e-dagger’ measure of lifespan inequality. Demographic Research, 50, 1281–1300.
Presentations at national and international conferences.
[5–8] Workshop PRIN CARONTE, Padova, Italy, 7/2024 [Diaconu, Romanò, Nigri, Stefanucci]
[3–4] European Population Conference (EPC) 2024, Edinburgh, UK, 6/2024 [Mazzuco, Stefanucci]
[2] 52esimo convegno della Società Italiana di Statistica (SIS), Bari, Italy, 6/2024 [Stefanucci]
[1] International Symposium on Non Parametric Statistics (ISNPS) 2024, Braga, Portugal, 6/2024 [Stefanucci]
Meetings and workshops organized.
[1] CARONTE workshop on advances in causes of death modelling. July 8 – 9, 2024 [University of Padova]
[2] CARONTE kick–off meeting. March 22, 2024 [online]