Comparer des méthodes

	Mobile-Phone Mobility Estimation	Forced Migration Needs Assessment
Domaine	Migration Studies	Migration Studies
Famille	Process / pipeline	Process / pipeline
Année d'origine	2014	2015
Auteur d'origine	Pierre Deville, Catherine Linard, Andrew J. Tatem, et al.	Inter-Agency Standing Committee (MIRA framework)
Type	Computational pipeline for population and migration inference from mobile data	Rapid multi-sector field assessment protocol for displacement crises
Source fondatrice	Deville, P., Linard, C., Martin, S., Gilbert, M., Stevens, F. R., Gaughan, A. E., Blondel, V. D., & Tatem, A. J. (2014). Dynamic Population Mapping Using Mobile Phone Data. PNAS, 111(45), 15888-15893.	Inter-Agency Standing Committee (2015). Multi-Sector Initial Rapid Assessment (MIRA) Guidance. Geneva: IASC.
Alias	CDR Mobility Estimation, Call-Detail-Record Migration Inference, Mobile Big Data Population Mapping, Phone-Based Displacement Tracking	Displacement Needs Assessment, Multi-Sector Rapid Needs Assessment, MIRA-Style Assessment, Humanitarian Needs Assessment
Apparentées	3	3
Résumé	Mobile-phone mobility estimation uses the digital traces left by ordinary phone use — call detail records, or CDRs — to map where people are, how their numbers shift over time, and how they move between places. Deville and colleagues' 2014 study in PNAS demonstrated that the locations of cell towers handling each call, aggregated across millions of subscribers, can produce dynamic population maps that track seasonal and daily changes far more finely than a decennial census ever could. Because a CDR records which tower served a user and when, the method can infer each person's habitual home location, count how many people 'live' in each area, and detect when those homes shift — the signature of internal migration or displacement. The approach turns a byproduct of telecom billing into a near-real-time demographic sensor, especially valuable where censuses are infrequent and crises move people faster than official statistics can follow. Crucially, the estimates are calibrated and validated against census or survey ground truth, so the phone-derived figures are anchored to known totals rather than taken at face value. The result is a powerful, if ethically fraught, way to observe human mobility at scale.	A forced-migration needs assessment is the structured, rapid process humanitarian actors use to understand what a displaced population urgently needs in the chaotic first days and weeks of a refugee or displacement crisis. Its reference standard is the Inter-Agency Standing Committee's Multi-Sector Initial Rapid Assessment (MIRA) framework, codified in 2015, which coordinates many agencies behind a single, comparable picture of needs rather than a scatter of overlapping, sector-specific surveys. The method is deliberately a pipeline: it begins with a secondary-data review that mines everything already known — pre-crisis baselines and early situation reports — to define what is still unknown; it then collects rapid primary data across sectors such as food, water, shelter, health, and protection through key-informant interviews, direct site observation, and reports from the affected people themselves; it converts these into standardized severity scores; and it ranks needs to prioritize the response. Because conditions are fluid and access is constrained, the assessment trades statistical precision for speed, coordination, and decision-relevance, producing a shared analytical basis for an inter-agency humanitarian appeal and response plan.