Annual mid-year data on internal migration moves for England and Wales, by local authority, region, age and sex.

"Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.This dataset includes demographic data of 22 countries from 1960 to 2018, including Sri Lanka, Bangladesh, Pakistan, India, Maldives, etc. Data fields include: country, year, population ratio, male ratio, female ratio, population density (km). Source: ( 1 ) United Nations Population Division. World Population Prospects: 2019 Revision. ( 2 ) Census reports and other statistical publications from national statistical offices, ( 3 ) Eurostat: Demographic Statistics, ( 4 ) United Nations Statistical Division. Population and Vital Statistics Reprot ( various years ), ( 5 ) U.S. Census Bureau: International Database, and ( 6 ) Secretariat of the Pacific Community: Statistics and Demography Programme. Periodicity: Annual Statistical Concept and Methodology: Population estimates are usually based on national population censuses. Estimates for the years before and after the census are interpolations or extrapolations based on demographic models. Errors and undercounting occur even in high-income countries. In developing countries errors may be substantial because of limits in the transport, communications, and other resources required to conduct and analyze a full census. The quality and reliability of official demographic data are also affected by public trust in the government, government commitment to full and accurate enumeration, confidentiality and protection against misuse of census data, and census agencies' independence from political influence. Moreover, comparability of population indicators is limited by differences in the concepts, definitions, collection procedures, and estimation methods used by national statistical agencies and other organizations that collect the data. The currentness of a census and the availability of complementary data from surveys or registration systems are objective ways to judge demographic data quality. Some European countries' registration systems offer complete information on population in the absence of a census. The United Nations Statistics Division monitors the completeness of vital registration systems. Some developing countries have made progress over the last 60 years, but others still have deficiencies in civil registration systems. International migration is the only other factor besides birth and death rates that directly determines a country's population growth. Estimating migration is difficult. At any time many people are located outside their home country as tourists, workers, or refugees or for other reasons. Standards for the duration and purpose of international moves that qualify as migration vary, and estimates require information on flows into and out of countries that is difficult to collect. Population projections, starting from a base year are projected forward using assumptions of mortality, fertility, and migration by age and sex through 2050, based on the UN Population Division's World Population Prospects database medium variant."

The largest number of immigrants in Germany were from Ukraine, as of 2023. The top three origin countries were rounded up by Romania and Turkey. Immigrants are defined as having left a country, which may be their home country, to permanently reside in another. Upon arriving, immigrants do not hold the citizenship of the country they move to. Immigration in the EU All three aforementioned countries are members of the European Union, which means their citizens have freedom of movement between EU member states. In practice, this means that citizens of any EU member country may relocate between them to live and work there. Unrestricted by visas or residence permits, the search for university courses, jobs, retirement options, and places to live seems to be defined by an enormous amount of choice. However, even in this freedom of movement scheme, immigration may be hampered by bureaucratic hurdles or financial challenges. Prosperity with a question mark While Germany continues to be an attractive destination for foreigners both in and outside the European Union, as well as asylum applicants, it remains to be seen how current events might influence these patterns, whether the number of immigrants arriving from certain countries will shift. Europe’s largest economy is suffering. Climbing inflation levels in the last few months, as well as remaining difficulties from the ongoing coronavirus (COVID-19) pandemic are affecting global economic development. Ultimately, future immigrants may face the fact of moving from one struggling economy to another.

This dataset contains information from the Office for National Statistics internal migration data for Wales, showing the origin and destination of each migration flow by sex and broad age group between each of the local authorities in Wales and also the UK countries. Data for flows to and from Scotland and Northern Ireland (and hence the UK as whole) prior to 2011-2012 are not available on this origin-destination basis, although from 2011-2012, the whole of the UK is covered. Data are available split by sex for 2011-2012 onwards only, prior to that data are only available for persons. Note that data for Wales as a whole will not be the sum of individual local authority data as moves between local authorities within Wales will not contribute to the flows into or out of Wales.

This dataset presents the migration rate in small regions of Australia based on the 2016 Census and aggregated following the 2016 edition of the Australian Statistical Geography Standard (ASGS). The data has been provided by The National Centre for Social and Economic Modelling (NATSEM). The migration rate is the proportion of people in the area who were not born in Australia, that is, who have migrated to Australia in the past. All indicators were extracted from the ABS Tablebuilder system using the usual residence profile. For usual residence data, the ABS moves people back to where they live, rather than using the location the data were collected (place of enumeration). Usual residence data is preferred for individual level data because it removes the effect of respondents travelling or holidaying. For more information please view the NATSEM Technical Report. Please note: AURIN has spatially enabled the original data provided directly from NATSEM. Where data values are NULL, the data is either unpublished or not applicable mathematically. In the calculation, Inadequately Described, At sea, Not Stated and Overseas Visitor were excluded from both the numerator and denominator as there is no information on these respondents. Methodology between the 2016 NATSEM and 2011 OECD data release may have changed, please refer to the technical report for parity status and specific changes.

Abstract

In 1985 the population and health observatory was established at Mlomp, in the region of Ziguinchor, in southern Senegal (see map). The objective was to complement the two rural population observatories then existing in the country, Bandafassi, in the south-east, and Niakhar, in the centre-west, with a third observatory in a region - the south-west of the country (Casamance) - whose history, ethnic composition and economic situation were quite different from those of the regions where the first two observatories were located. It was expected that measuring the demographic levels and trends on those three sites would provide better coverage of the demographic and epidemiological diversity of the country.

Following a population census in 1984-1985, demographic events and causes of death have been monitored yearly. During the initial census, all women were interviewed concerning the birth and survival of their children. Since 1985, yearly censuses, usually conducted in January-February, have been recording demographic data, including all births, deaths, and migrations. The completeness and accuracy of dates of birth and death are cross-checked against those of registers of the local maternity ward (_95% of all births) and dispensary (all deaths are recorded, including those occurring outside the area), respectively. The study area comprises 11 villages with approximately 8000 inhabitants, mostly Diola. Mlomp is located in the Department of Oussouye, Region of Ziguinchor (Casamance), 500 km south of Dakar.

On 1 January 2000 the Mlomp area included a population of 7,591 residents living in 11 villages. The population density was 108 people per square kilometre. The population belongs to the Diola ethnic group, and the religion is predominantly animist, with a large minority of Christians and a few Muslims. Though low, the educational level - in 2000, 55% of women aged 15-49 had been to school (for at least one year) - is definitely higher than at Bandafassi. The population also benefits from much better health infrastructure and programmes. Since 1961, the area under study has been equipped with a private health centre run by French Catholic nurses and, since 1968, a village maternity centre where most women give birth. The vast majority of the children are totally immunized and involved in a growth-monitoring programme (Pison et al.,1993; Pison et al., 2001).

Geographic coverage

The Mlomp DSS site, about 500 km from the capital, Dakar, in Senegal, lies between latitudes 12°36' and 12°32'N and longitudes 16°33' and 16°37'E, at an altitude ranging from 0 to 20 m above sea level. It is in the region of Ziguinchor, Département of Oussouye (Casamance), in southwest Senegal. It is locates 50 km west of the city of Ziguinchor and 25 kms north of the border with Guinea Bissau. It covers about half the Arrondissement of Loudia-Ouolof. The Mlomp DSS site is about 11 km × 7 km and has an area of 70 km2. Villages are households grouped in a circle with a 3-km diameter and surrounded by lands that are flooded during the rainy season and cultivated for rice. There is still no electricity.

Analysis unit

Individual

Universe

At the census, a person was considered a member of the compound if the head of the compound declared it to be so. This definition was broad and resulted in a de jure population under study. Thereafter, a criterion was used to decide whether and when a person was to be excluded or included in the population.

A person was considered to exit from the study population through either death or emigration. Part of the population of Mlomp engages in seasonal migration, with seasonal migrants sometimes remaining 1 or 2 years outside the area before returning. A person who is absent for two successive yearly rounds, without returning in between, is regarded as having emigrated and no longer resident in the study population at the date of the second round. This definition results in the inclusion of some vital events that occur outside the study area. Some births, for example, occur to women classified in the study population but physically absent at the time of delivery, and these births are registered and included in the calculation of rates, although information on them is less accurate. Special exit criteria apply to babies born outside the study area: they are considered emigrants on the same date as their mother.

A new person enters the study population either through birth to a woman of the study population or through immigration. Information on immigrants is collected when the list of compounds of a village is checked ("Are there new compounds or new families who settled since the last visit?") or when the list of members of a compound is checked ("Are there new persons in the compound since the last visit?"). Some immigrants are villagers who left the area several years before and were excluded from the study population. Information is collected to determine in which compound they were previously registered, to match the new and old information.

Information is routinely collected on movements from one compound to another within the study area. Some categories of the population, such as older widows or orphans, frequently move for short periods of time and live in between several compounds, and they may be considered members of these compounds or of none. As a consequence, their movements are not always declared.

Kind of data

Event history data

Frequency of data collection

One round of data collection took place annually, except in 1987 and 2008.

Sampling procedure

No samplaing is done

Sampling deviation

None

Mode of data collection

Proxy Respondent [proxy]

Research instrument

List of questionnaires: - Household book (used to register informations needed to define outmigrations) - Delivery questionnaire (used to register information of dispensaire ol mlomp) - New household questionnaire - New member questionnaire - Marriage and divorce questionnaire - Birth and marital histories questionnaire (for a new member) - Death questionnaire (used to register the date of death)

Cleaning operations

On data entry data consistency and plausibility were checked by 455 data validation rules at database level. If data validaton failure was due to a data collection error, the questionnaire was referred back to the field for revisit and correction. If the error was due to data inconsistencies that could not be directly traced to a data collection error, the record was referred to the data quality team under the supervision of the senior database scientist. This could request further field level investigation by a team of trackers or could correct the inconsistency directly at database level.

No imputations were done on the resulting micro data set, except for:

a. If an out-migration (OMG) event is followed by a homestead entry event (ENT) and the gap between OMG event and ENT event is greater than 180 days, the ENT event was changed to an in-migration event (IMG). b. If an out-migration (OMG) event is followed by a homestead entry event (ENT) and the gap between OMG event and ENT event is less than 180 days, the OMG event was changed to an homestead exit event (EXT) and the ENT event date changed to the day following the original OMG event. c. If a homestead exit event (EXT) is followed by an in-migration event (IMG) and the gap between the EXT event and the IMG event is greater than 180 days, the EXT event was changed to an out-migration event (OMG). d. If a homestead exit event (EXT) is followed by an in-migration event (IMG) and the gap between the EXT event and the IMG event is less than 180 days, the IMG event was changed to an homestead entry event (ENT) with a date equal to the day following the EXT event. e. If the last recorded event for an individual is homestead exit (EXT) and this event is more than 180 days prior to the end of the surveillance period, then the EXT event is changed to an out-migration event (OMG)

In the case of the village that was added (enumerated) in 2006, some individuals may have outmigrated from the original surveillance area and setlled in the the new village prior to the first enumeration. Where the records of such individuals have been linked, and indivdiual can legitmately have and outmigration event (OMG) forllowed by and enumeration event (ENU). In a few cases a homestead exit event (EXT) was followed by an enumeration event in these cases. In these instances the EXT events were changed to an out-migration event (OMG).

Response rate

On an average the response rate is about 99% over the years for each round.

Sampling error estimates

Not applicable

Data appraisal

CenterId Metric Table QMetric Illegal Legal Total Metric Rundate
SN012 MicroDataCleaned Starts 18756 2017-05-19 00:00
SN012 MicroDataCleaned Transitions 0 45136 45136 0 2017-05-19 00:00
SN012 MicroDataCleaned Ends 18756 2017-05-19 00:00
SN012 MicroDataCleaned SexValues 38 45098 45136 0 2017-05-19 00:00
SN012 MicroDataCleaned DoBValues 204 44932 45136 0 2017-05-19 00:00

Billions of animals migrate to track seasonal pulses in resources. Optimally timing migration is a key strategy, yet the ability of animals to compensate for phenological mismatches en route is largely unknown. We studied a population of mule deer (Odocoileus hemionus) in Wyoming that lack reliable cues on their desert winter range, causing them to start migration 70 days ahead to 52 days behind the wave of spring green-up. By adjusting movement speed and stopover use, however, individual deer arrive at the summer range within an average 6-day window. Late migrants move 2.5 times faster and spend 72% less time on stopovers than early migrants, which allows them to catch the green wave. Ungulates, and potentially other migratory species, possess cognitive abilities to recognize where they are in space and time relative to key resources. Such behavioral capacity may allow migratory taxa to maintain foraging benefits amid rapidly changing phenology. Methods Animal capture and handling From 2014–2020, we captured n = 220 adult female mule deer (>1-yr-old) in the Red Desert near Rock Springs, Wyoming, USA (41° 35′N, 109° 12′W) as part of a long-term study. We recaptured deer each March and December for a total of n = 528 animal-years of data. All deer were captured via helicopter net-gunning1,2. Mule deer in this portion of the Sublette Herd migrate a variety of distances to their summer ranges in northwestern Wyoming3,4. Herein, we focused on n = 72 long-distance migrants (n = 152 animal-years) that migrated 134–293 km and spent the summer north of Pinedale, WY (42° 51′N, 109° 51′W). During captures, we used an electronic platform scale (± 0.1 kg) to measure body mass (kg) and a portable ultrasound (Ibex, E.I. Medical Imaging, Loveland, CO) to measure maximum rump fat (mm). Following previously applied methods5, we used body mass, maximum rump fat, and a body-condition score to estimate percent-scaled ingesta-free body fat (IFBFat)5,6. For captures in March, we used an ultrasound to determine pregnancy, including fetal rate (number of fetuses per deer) and fetal development via measures of the fetal eye diameter (mm). To estimate the age of each deer, we extracted the lower right incisiform canine and used cementum annuli aging technique7–9, which was conducted by the Matson’s Laboratory in Manhattan, Montana, USA. From 2014–2020, we outfitted all deer with store-on-board or iridium GPS collars that collected locations every 1–2 hrs (Advanced Telemetry Systems, Isanti, MN, USA; Lotek Wireless, Newmarket, ON, CAN; Telonics, Mesa, AZ, USA). We also included GPS collar data from a previous study on the Sublette Mule Deer Herd (2011–2013)4 to analyze movement for n = 27 additional deer (n = 66 animal-years), which were outfitted with store-on-board GPS collars that collected locations every 3 hours (Telonics, Mesa, AZ, USA). All animal capture and handling protocols were approved by the Wyoming Game and Fish Department (Chapter 33-937) and an Institutional Animal Care and Use Committee at the University of Wyoming (20131111KM00040, 20151204KM00135, 20170215KM00260, 20200302MK00411). Delineation of migratory routes and seasonal ranges We used Net Square Displacements (NSDs10) to determine the timing of spring and autumn migration, delineate migratory routes, and determine the net displacement (km) between the start of spring migration and each GPS location along the migratory route. We determined winter range use for each deer by extracting GPS locations between the end of autumn migration and the start of spring migration (or between the time of capture and start of spring migration if the end of autumn migration was unknown). We determined summer range use for each deer by extracting GPS locations between the end of spring migration and the start of autumn migration (or between the end of spring migration and time of collar failure or mortality on summer range). We used a 95% Kernel Utilization Distribution (KUD11) to delineate the winter range (41.63 ± 7.26 km2 [x̄ ± 95% CI]) and summer range (7.26 ± 1.61 km2) of each animal-year. We removed 0.10%, 0.09%, and 0.24% of all GPS locations during migration, on winter range, and on summer range, respectively, because the movement rate between consecutive locations was greater than 10.8 km/hr and indicated an inaccurate GPS fix. Green wave surfing We evaluated the ability of mule deer to track green-up of plants during spring migration by analyzing the synchronicity between movement and peak IRG. We determined IRG by extracting the first derivative of double-logistic curves that were fitted to the annual time series of NDVI12. Days from peak IRG (hereafter referred to as Days-From-Peak) were calculated as the difference in days between the date of every GPS location for a deer and the date of peak IRG at the same GPS location12,13. A theoretically perfect surfer occupies a location on the same day that peak IRG occurs (Days-From-Peak = 0)12. We calculated mean Days-From-Peak and IRG for each day and kilometer of an individual’s migration to reduce pseudoreplication and account for irregular GPS fixes12,13. We quantified an individual’s location on the green wave at the start and end of spring migration by calculating the difference in days between the mean date of peak IRG on each seasonal range and the date an individual departed their winter range or arrived at their summer range. References

Barrett, M. W., Nolan, J. W. & Roy, L. D. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10, 108–114 (1982). Krausman, P. R., Hervert J. J. & Ordway, L. L. Capturing deer and mountain sheep with a net-gun. Wildlife Society Bulletin 13, 71–73 (1985). Kauffman, M. J. et al. Wild Migrations: Atlas of Wyoming’s Ungulates (Oregon State University Press, Corvallis, OR, 2018). Sawyer, H., Middleton, A. D., Hayes, M. M., Kauffman, M. J. & Monteith, K. L. The extra mile: ungulate migration distance alters the use of seasonal range and exposure to anthropogenic risk. Ecosphere 7 (2016) doi:10.1002/ecs2.1534. Cook, R. C. et al. Revisions of rump fat and body scoring indices for deer, elk, and moose. Journal of Wildlife Management 74, 880–896 (2010). Monteith, K. L. et al. Risk-sensitive allocation in seasonal dynamics of fat and protein reserves in a long-lived mammal. Journal of Animal Ecology 82, 377–388 (2013). Rolandsen, C. M. et al. Accuracy and repeatability of moose (Alces alces) age as estimated from dental cement layers. European Journal of Wildlife Research 54, 6–14 (2008). Cooper, S. M., Sieckenius, S. S. & Silva, A. L. Dentine method: Aging white-tailed deer by tooth measurements. Wildlife Society Bulletin 37, 451–457 (2013). Boertje, R. D., Ellis, M. M. & Kellie, K. A. Accuracy of moose age determinations from canine and incisor cementum annuli. Wildlife Society Bulletin 39, 383–389 (2015). Bunnefeld, N. A model-driven approach to quantify migration patterns: individual, regional and yearly differences. Journal of Animal Ecology 80, 466–476 (2011). Worton, B. J. Kernel methods for estimating the utilization distribution in home-range studies. Ecology 70, 164–168 (1989). Aikens, E. O. et al. The greenscape shapes surfing of resource waves in a large migratory herbivore. Ecology Letters 20, 741–750 (2017). Middleton, A .D. et al. Green-wave surfing increases fat gain in a migratory ungulate. Oikos 127, 1060–1068 (2018).

Migration in Europe in 2024 marks a return to normality after the extreme disruptions experienced in 2022. While in 2022 ******* saw the largest negative net migration balance, with almost * million of its citizens fleeing the eastern European country in the aftermath of Russia's invasion, in 2024 it is in fact the country with the largest positive net migration balance. Over **** million Ukrainians have returned to their home country from abroad, leading Poland, Romania, and Hungary to have large net migration deficits, as they were key recipient countries for Ukrainians in 2022. The other countries which experienced large positive net migration balances in 2023 are all in Western Europe, as the UK, the Netherlands, France, Italy, and Spain all remain popular destinations for migrants.

In financial year 2023, it was estimated that 64.32 thousand more Chinese migrated to Australia than emigrated. This marked a significant increase in Chinese net migration compared to 14.72 thousand people in the previous financial year.

The Chinese community in Australia

Chinese migration to Australia dates back to the Australian gold rush of the 1850s and 60s, however, exclusionary migration policies up until the 1970’s restricted migration from China for some time. Since then, immigration from China has increased steadily and Chinese migrants now represent Australia’s third largest migrant group after the UK and India. The 2016 Australian census showed that Mandarin was the second most common language spoken at home in Australia, and Cantonese came in fourth. The Australian Chinese community also includes a significant proportion of the international students from China choosing to study in Australia.

Chinese investment in Australia

Although foreign investment in Australia still comes primarily from its traditional trade partners, the United States and the United Kingdom, Chinese investment has been increasing in recent years. The bulk of Chinese investment in Australia goes toward commercial real estate and agribusiness. In New South Wales alone, real estate investment from China totaled almost 1.25 billion Australian dollars, which accounted for around a half of all Chinese real estate investment in the country. By comparison, in 2019 the import value of Australian food products to China displayed yet another year on year increase, totaling more than two billion U.S. dollars.

This dataset presents the migration rate in small regions of Australia based on the 2016 Census and aggregated following the 2016 edition of the Australian Statistical Geography Standard (ASGS). The data has been provided by The National Centre for Social and Economic Modelling (NATSEM). The migration rate is the proportion of people in the area who were not born in Australia, that is, who have migrated to Australia in the past. All indicators were extracted from the ABS Tablebuilder system using the usual residence profile. For usual residence data, the ABS moves people back to where they live, rather than using the location the data were collected (place of enumeration). Usual residence data is preferred for individual level data because it removes the effect of respondents travelling or holidaying. For more information please view the NATSEM Technical Report. Please note: AURIN has spatially enabled the original data provided directly from NATSEM.

As of 2023, 27.3 percent of California's population were born in a country other than the United States. New Jersey, New York, Florida, and Nevada rounded out the top five states with the largest population of foreign born residents in that year. For the country as a whole, 14.3 percent of residents were foreign born.

This dataset presents the estimates of the internal migration statistics of Australia by Greater Capital City Statistical Area (GCCSA) following the 2011 Australian Statistical Geography Standard (ASGS). The dataset spans from the 2006-07 financial year up to the 2015-16 financial year.

Regional internal migration is the movement of people from one region to another within Australia (both interstate and intrastate). For example, it incorporates moves from a GCCSA to any other GCCSA within the country. Net regional internal migration is the net gain or loss of population through this movement.

The ABS has developed a new series of annual regional internal migration estimates (RIME) based on the 2011 edition of the Australian Statistical Geography Standard (ASGS). The Medicare and Defence data used for estimating interstate migration is now also used to estimate internal migration below the state/territory level. A similar method was used to prepare RIME at the LGA level, based on 2011 boundaries.

This data is Australian Bureau of Statistics (ABS) data (catalogue number: 3412.0) used with permission from the ABS.

For more information please visit the ABS Explanatory Notes.

Please note: RIME are not directly comparable with estimated resident populations (ERPs) because of the different methods and source data used to prepare each series. The combination of natural increase and net migration (internal and overseas) therefore may not correspond with change in ERP. AURIN has spatially enabled the original data.

Abstract

In 2016, UNHCR became aware of a group of stateless persons living in or near Nairobi, Kenya. Most of them were Shona, descendants of missionaries who arrived from Zimbabwe and Zambia in the 1960s and remained in Kenya. The total number of Shona living in Kenya is estimated to be between 3,000 and 3,500 people.

On their first arrival, the Shona were issued certificates of registration, but a change in the Registration of Persons Act of 1978 did not make provision for people of non-Kenyan descent, consequently denying the Shona citizenship. Zimbabwe and Zambia did not consider them nationals either, rendering them stateless. Besides the Shona, there are other groups of stateless persons of different origins and ethnicities, with the total number of stateless persons in Kenya estimated at 18,500.

UNHCR and the Government of Kenya are taking steps to address statelessness in the country, among them is the registration of selected groups for nationalization. In April 2019, the Government of Kenya pledged to recognize qualifying members of the Shona community as Kenyan citizens. However, the lack of detailed information on the stateless population in Kenya hinders advocacy for the regularization of their nationality status. Together with the Kenyan Government through the Department of Immigration Services (DIS) and the Kenya National Bureau of Statistics (KNBS), UNHCR Kenya conducted registration and socioeconomic survey for the Shona community from May to July 2019. While the primary objective of the registration was to document migration, residence and family history with the aim of preparing their registration as citizens, this survey was conducted to provide a baseline on the socio-economic situation of the stateless Shona population for comparison with non-stateless populations of Kenya.

Geographic coverage

Githurai, Nairobi, Kiambaa and Kinoo

Analysis unit

Household and individual

Universe

All Shona living in Nairobi and Kiambu counties, Kenya

Kind of data

Census/enumeration data [cen]

Sampling procedure

The objective of the socio-economic survey was to cover the entire Shona population living in areas of the Nairobi and Kiambu counties. This included Shona living in Githurai, Kiambaa, Kinoo and other urban areas in and around Nairobi. Data collection for the socioeconomic survey took place concurrently with a registration verification. The registration verification was to collect information on the Shona's migration history, residence in Kenya and legal documentation to prepare their registration as citizens. The registration activity including questions on basic demographics also covered some enumeration areas outside the ones of the socio-economic survey, such as institutional households in Hurlingham belonging to a religious order who maintain significantly different living conditions than the average population. The total number of households for which socio-economic data was collected for is 350 with 1,692 individuals living in them. A listing of Shona households using key informant lists and respondent-driven referral to identify further households was conducted by KNBS and UNHCR before the start of enumeration for the registration verification and socio-economic survey.

Sampling deviation

None

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The following sections are included: household roster, education, employment, household characteristics, consumption and expenditure.

Cleaning operations

The dataset presented here has undergone light checking, cleaning and restructuring (data may still contain errors) as well as anonymization (includes removal of direct identifiers and sensitive variables, recoding and local suppression).

Response rate

Overall reponse rate was 99 percent, mainly due to refusal to participate.

Abstract

The Bandafassi HDSS is located in south-eastern Senegal, near the borders with Mali and Guinea. The area is 700 km from the national capital, Dakar. The population under surveillance is rural and in 2012 comprised 13 378 inhabitants living in 42 villages. Established in 1970, originally for genetic studies, and initially covering only villages inhabited by one subgroup of the population of the area (the Mandinka), the project was transformed a few years later into a HDSS and then extended to the two other subgroups living in the area: Fula villages in 1975, and Bedik villages in 1980. Data gathered include births, marriages, migrations and deaths (including their causes). One specific feature of the Bandafassi HDSS is the availability of genealogies.

Villages are quite small - 270 inhabitants in average - divided in hamlet pour a part. The population density is 19 inhabitants per km².

The population is divided in three living ethnical groups in distinct villages. In 2000, the ethnical groups are : 1 - Bedik (25 % of population). 2 - Malinke (17 %), 3 - Peul (58 %).

The housing unit is the square (or concession) which hosts members of an extended patrilineal family. It contains 17 people in average.Peul and Bedik squares are less populated (15 and 18 people in average) than Malinke squares (27 people in average). Polygamy is intense (160 maried women for 100 maried men). Women maried to the same men usually inhabit in the same square. Each wife has her own hu, sharing the same square courtyard.

Analysis unit

Individual

Universe

At the census, a person was considered a member of the compound if the head of the compound declared it to be so. This definition was broad and resulted in a de jure population under study. Thereafter, a criterion was used to decide whether and when a person was to be excluded or included in the population.

A person was considered to exit from the study population through either death or emigration. Part of the population of Mlomp engages in seasonal migration, with seasonal migrants sometimes remaining 1 or 2 years outside the area before returning. A person who is absent for two successive yearly rounds, without returning in between, is regarded as having emigrated and no longer resident in the study population at the date of the second round. This definition results in the inclusion of some vital events that occur outside the study area. Some births, for example, occur to women classified in the study population but physically absent at the time of delivery, and these births are registered and included in the calculation of rates, although information on them is less accurate. Special exit criteria apply to babies born outside the study area: they are considered emigrants on the same date as their mother.

A new person enters the study population either through birth to a woman of the study population or through immigration. Information on immigrants is collected when the list of compounds of a village is checked ("Are there new compounds or new families who settled since the last visit?") or when the list of members of a compound is checked ("Are there new persons in the compound since the last visit?"). Some immigrants are villagers who left the area several years before and were excluded from the study population. Information is collected to determine in which compound they were previously registered, to match the new and old information.

Information is routinely collected on movements from one compound to another within the study area. Some categories of the population, such as older widows or orphans, frequently move for short periods of time and live in between several compounds, and they may be considered members of these compounds or of none. As a consequence, their movements are not always declared.

Kind of data

Event history data

Frequency of data collection

One round of data collection took place annual except in 1970 and 2015.

Sampling procedure

No samplaing is done

Sampling deviation

None

Mode of data collection

Proxy Respondent [proxy]

Research instrument

List of questionnaires: - Household book (used to register informations needed to define outmigrations) - Delivery questionnaire (used to register information of dispensaire ol mlomp) - New household questionnaire - New member questionnaire - Marriage and divorce questionnaire - Birth and marital histories questionnaire (for a new member) - Death questionnaire (used to register the date of death)

Cleaning operations

On data entry data consistency and plausibility were checked by 455 data validation rules at database level. If data validaton failure was due to a data collection error, the questionnaire was referred back to the field for revisit and correction. If the error was due to data inconsistencies that could not be directly traced to a data collection error, the record was referred to the data quality team under the supervision of the senior database scientist. This could request further field level investigation by a team of trackers or could correct the inconsistency directly at database level.

No imputations were done on the resulting micro data set, except for:

a. If an out-migration (OMG) event is followed by a homestead entry event (ENT) and the gap between OMG event and ENT event is greater than 180 days, the ENT event was changed to an in-migration event (IMG). b. If an out-migration (OMG) event is followed by a homestead entry event (ENT) and the gap between OMG event and ENT event is less than 180 days, the OMG event was changed to an homestead exit event (EXT) and the ENT event date changed to the day following the original OMG event. c. If a homestead exit event (EXT) is followed by an in-migration event (IMG) and the gap between the EXT event and the IMG event is greater than 180 days, the EXT event was changed to an out-migration event (OMG). d. If a homestead exit event (EXT) is followed by an in-migration event (IMG) and the gap between the EXT event and the IMG event is less than 180 days, the IMG event was changed to an homestead entry event (ENT) with a date equal to the day following the EXT event. e. If the last recorded event for an individual is homestead exit (EXT) and this event is more than 180 days prior to the end of the surveillance period, then the EXT event is changed to an out-migration event (OMG)

In the case of the village that was added (enumerated) in 2006, some individuals may have outmigrated from the original surveillance area and setlled in the the new village prior to the first enumeration. Where the records of such individuals have been linked, and indivdiual can legitmately have and outmigration event (OMG) forllowed by and enumeration event (ENU). In a few cases a homestead exit event (EXT) was followed by an enumeration event in these cases. In these instances the EXT events were changed to an out-migration event (OMG).

Response rate

On an average the response rate is about 99% over the years for each round.

Sampling error estimates

Not applicable

Data appraisal

CenterId Metric Table QMetric Illegal Legal Total Metric Rundate
SN011 MicroDataCleaned Starts 26293 2017-05-20 00:00
SN011 MicroDataCleaned Transitions 0 85058 85058 0 2017-05-20 00:00
SN011 MicroDataCleaned Ends 26293 2017-05-20 00:00
SN011 MicroDataCleaned SexValues 50 85008 85058 0 2017-05-20 00:00
SN011 MicroDataCleaned DoBValues 85058 2017-05-20 00:00

As recorded by the source, Moroccans ranked as the foreign nationality with more residents in Spain in 2023, closely followed by Romanians. After years of losing its foreign population, Spain’s immigration figures started to pick up in 2015, with the number of people that moved to the Mediterranean country surpassing the number of foreigners that decided to leave.

A matter of balance The net migration rate of Spain changed its course mainly due to the great inflow of foreigners that move to reside in the Mediterranean country. Spain’s immigration flow slowed down after the 2008 financial crisis, albeit the number of foreigners that opted to change their residence saw a significant growth in the last years. In 2022, Colombians ranked first as the foreign nationality that most relocated to Spain, distantly followed by Moroccans and Ukranians.

Spain does not have the highest number of immigrants in Europe In recent years, the European Union confronted a rising number of refugees arriving from the Middle East. Migration figures show that Germany accommodated approximately 15 million foreign-born citizens, ranking it as the country that most hosted immigrants in Europe in 2022. By comparison, Spain’s foreign population stood slightly over seven million, positioning the Western Mediterranean country third on the European list of foreign-born population. Unfortunately, thousands of persons have died ore gone missing trying to reach Spanish territory, as more and more irregular migrants opt to use dangerous maritime routes to arrive at Southern Europe from Africa's coasts.

The migration rate within India between 2020 and 2021 was almost ** percent. This means, between July 2020 and June 2021, about **** percent of the population in the rural areas of the country were migrants, while this was about ** percent for the population in urban areas. During the same time period, there was a much higher share of migrants among females than males in the country.

In 2024, approximately 948,000 million people migrated to the United Kingdom, while 517,000 people migrated from the UK, resulting in a net migration figure of 431,000. There have consistently been more people migrating to the United Kingdom than leaving it since 1993 when the net migration figure was negative 1,000. Although migration from the European Union has declined since the Brexit vote of 2016, migration from non-EU countries accelerated rapidly from 2021 onwards. In the year to June 2023, 968,000 people from non-EU countries migrated to the UK, compared with 129,000 from EU member states. Immigration and the 2024 election Since late 2022, immigration, along with the economy and healthcare, has consistently been seen by UK voters as one of the top issues facing the country. Despite a pledge to deter irregular migration via small boats, and controversial plans to send asylum applicants to Rwanda while their claims are being processed, Rishi Sunak's Conservative government lost the trust of the public on this issue. On the eve of the last election, 20 percent of Britons thought the Labour Party would be the best party to handle immigration, compared with 13 percent who thought the Conservatives would handle it better. Sunak and the Conservatives went on to lose this election, suffering their worst defeat in modern elections. Historical context of migration The first humans who arrived in the British Isles, were followed by acts of conquest and settlement from Romans, Anglo-Saxons, Danes, and Normans. In the early modern period, there were also significant waves of migration from people fleeing religious or political persecution, such as the French Huguenots. More recently, large numbers of people also left Britain. Between 1820 and 1957, for example, around 4.5 million people migrated from Britain to America. After World War Two, immigration from Britain's colonies and former colonies was encouraged to meet labour demands. A key group that migrated from the Caribbean between the late 1940s and early 1970s became known as the Windrush generation, named after one of the ships that brought the arrivals to Britain.

******** ranked as the country of origin of the largest immigration group arriving into Spain in 2023, as revealed by the latest data. Over ******* people migrated from the South American country to Spain that year. The second largest group was comprised by ********* with around ******* newcomers. A matter of balance The net migration rate of Spain changed its course mainly due to the great inflow of foreigners that move to reside in the Mediterranean country. Spain’s immigration flow slowed down after the 2008 financial crisis, albeit the number of foreigners that opted to change their residence saw a significant growth in the last years. In 2023, Moroccans ranked first as the foreign nationality residing Spain, followed by people from Romania and the Colombians. Spain does not have the highest number of immigrants in Europe In recent years, the European Union confronted a rising number of refugees arriving from the Middle East and Africa. Migration figures show that Germany accommodated approximately ** million foreign-born citizens, ranking it as the country that most hosted immigrants in Europe in 2023. By comparison, Spain’s foreign population stood over ***** million, positioning the Western Mediterranean country third on the European list of foreign-born population. Unfortunately, thousands of persons have died or gone missing trying to reach Spanish territory, as more and more irregular migrants opt to use dangerous maritime routes to arrive at Southern Europe from Africa's coasts.