Evidence map›Paper›PMID 35277498›Full record

ArticleScientific data2022

High spatial resolution dataset of La Mobilière insurance customers.

Alice Battiston, Emanuele Massaro, Claudia R Binder, Rossano Schifanella

Abstract read
In one paragraph

Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Alice BattistonUniversity of Turin, Via Giuseppe Verdi, 8, 10124, Turin, TO, Italy. alice.battiston@unito.it.ORCID 0000-0001-6690-2574
Emanuele MassaroEuropean Commission Joint Research Center, Via E. Fermi, 2749, 21027, Ispra, VA, Italy.
Claudia R BinderHERUS Lab, EPFL, Bˆatiment GR Station 2 CH - 1015, Lausanne, Switzerland.
Rossano SchifanellaUniversity of Turin, Via Giuseppe Verdi, 8, 10124, Turin, TO, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present the La Mobilière insurance customers dataset: a 12-year-long longitudinal collection of data on policies of customers of the Swiss insurance company La Mobilière. To preserve the privacy of La Mobilière customers, we propose the data aggregated at two geographical levels, based on the place of residence of the customer: postal areas and municipalities. For each geographical area, the data provides summary statistics on: (i) the demographic characteristics of the customer base, (ii) characteristics of vehicles insurance policies and (iii) characteristics of housing and building insurance policies. To assess the validity of the data, we investigate the temporal consistency of the data and the representativeness of La Mobilière customer base along several dimensions (total population, percentage of foreigners, etc.). We also show how the insurance data can reliably model the spatial patterns of socio-economic indicators at a high geographical resolution. We believe that the reuse of this data provides an opportunity for researchers to broaden the socio-economic characterization of Swiss areas beyond the use of official data sources.

Identifiers

PMID35277498
PMCPMC8917171

What OpenQuestion holds

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Registered trials

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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.