Evidence map›Paper›PMID 41980994›Full record

ArticleScientific reports2026

An interpretable piecewise model for human mortality: the Christopher-Samba model.

Christopher Lalromawia, Samba Siva Rao Pasupuleti

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Christopher LalromawiaDepartment of Statistics, Pachhunga University College, Mizoram University (A Central University), Aizawl, India.
Samba Siva Rao PasupuletiDepartment of Statistics, Pachhunga University College, Mizoram University (A Central University), Aizawl, India. srao113@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modelling mortality schedules has a long history in demographic research, with many models developed over time. This study proposes a new mortality model—the Christopher–Samba (C–S) model—that captures mortality patterns across the entire age spectrum. The proposed piecewise model integrates two components: The first part is an exponential function describing mortality up to age 5, while the second part focuses on mortality above age 5. The parameters of the second component, a reparametrized version of the classical logistic model, reflect the ages at which the annual probability of death reaches 1% and 10%, representing the benchmark ages for the onset of increased mortality and severe mortality, respectively. These thresholds naturally vary across populations. Mortality data from the Human Mortality Database were used to demonstrate the application of the proposed C–S model. The C–S model fits well across countries with diverse mortality schedules. Fitted parameters reveal substantial variation in the ages at which the annual probability of death reaches 1% and 10%, underscoring population differences in mortality dynamics. In summary, with its simplicity, strong fit, and meaningful parameter interpretations, the proposed C–S model is a valuable addition to mortality modelling literature.

Indexed as

Models, StatisticalMortalityAdolescentAgedChildChild, PreschoolFemaleHumansInfantAgeing patternsAge-specific mortalityChristopher–Samba (C–S) modelHuman mortality database (HMD)Mortality graduationOnset of increased mortalitySevere mortality age

Identifiers

PMID41980994
PMCPMC13079803

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.