Compare methods
Review your selected methods side by side; rows that differ are highlighted.
| Refugee Camp Census× | Mobile-Phone Mobility Estimation× | |
|---|---|---|
| Field | Migration Studies | Migration Studies |
| Family | Process / pipeline | Process / pipeline |
| Year of origin≠ | 2003 | 2014 |
| Originator≠ | United Nations High Commissioner for Refugees (UNHCR) | Pierre Deville, Catherine Linard, Andrew J. Tatem, et al. |
| Type≠ | Registration-and-enumeration pipeline for displaced populations | Computational pipeline for population and migration inference from mobile data |
| Seminal source≠ | United Nations High Commissioner for Refugees (2003). Handbook for Registration: Procedures and Standards for Registration, Population Data Management and Documentation. Geneva: UNHCR. link ↗ | 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. DOI ↗ |
| Aliases | Refugee Registration and Enumeration, Displacement Camp Census, Biometric Refugee Registration, UNHCR Population Data Management | CDR Mobility Estimation, Call-Detail-Record Migration Inference, Mobile Big Data Population Mapping, Phone-Based Displacement Tracking |
| Related | 3 | 3 |
| Summary≠ | A refugee camp census is the systematic registration and enumeration of displaced people in camps and other displacement settings, producing the verified population figures on which protection and assistance depend. UNHCR's 2003 Handbook for Registration codified the standards for this work, setting out how to list households, register individuals, manage population data, and issue documentation in emergencies and protracted situations alike. The exercise is far more than a headcount: it records who each person is, where they came from, their family relationships, and protection-relevant vulnerabilities, while increasingly using biometrics to prevent duplicate or fraudulent registration. The handbook frames registration in stages, distinguishing initial level-1 group or estimate data from detailed level-2 individual case records, so that a usable population figure can be produced quickly and then refined. Accurate figures determine food rations, shelter, water, and services, and underpin durable-solution planning, so errors translate directly into people going unserved or resources being misallocated. The method is thus a specialized census discipline adapted to chaotic, high-stakes, and rights-sensitive conditions. | 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. |
| ScholarGateDataset ↗ |
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