In 2019, California had the highest population of unauthorized immigrants, at around **** million. The overall figure for the United States was estimated to be around ***** million unauthorized immigrants.

In January 2022, it was estimated that about 1.85 million male illegal immigrants living in the United States were aged between 35 and 44 years old. In that same year, it was estimated that 1.52 million female illegal immigrants living in the U.S. were between 35 and 44 years old.

As of January 2022, it was estimated that about 4.81 million illegal immigrants from Mexico were living in the United States. It was also estimated that 750,000 illegal immigrants from Guatemala were living in the United States.

Abstract

The Human Sciences Research Council (HSRC) carried out the Migration and Remittances Survey in South Africa for the World Bank in collaboration with the African Development Bank. The primary mandate of the HSRC in this project was to come up with a migration database that includes both immigrants and emigrants. The specific activities included: · A household survey with a view of producing a detailed demographic/economic database of immigrants, emigrants and non migrants · The collation and preparation of a data set based on the survey · The production of basic primary statistics for the analysis of migration and remittance behaviour in South Africa.

Like many other African countries, South Africa lacks reliable census or other data on migrants (immigrants and emigrants), and on flows of resources that accompanies movement of people. This is so because a large proportion of African immigrants are in the country undocumented. A special effort was therefore made to design a household survey that would cover sufficient numbers and proportions of immigrants, and still conform to the principles of probability sampling. The approach that was followed gives a representative picture of migration in 2 provinces, Limpopo and Gauteng, which should be reflective of migration behaviour and its impacts in South Africa.

Geographic coverage

Two provinces: Gauteng and Limpopo

Limpopo is the main corridor for migration from African countries to the north of South Africa while Gauteng is the main port of entry as it has the largest airport in Africa. Gauteng is a destination for internal and international migrants because it has three large metropolitan cities with a great economic potential and reputation for offering employment, accommodations and access to many different opportunities within a distance of 56 km. These two provinces therefore were expected to accommodate most African migrants in South Africa, co-existing with a large host population.

Analysis unit

• Household
• Individual

Universe

The target group consists of households in all communities. The survey will be conducted among metro and non-metro households. Non-metro households include those in: - small towns, - secondary cities, - peri-urban settlements and - deep rural areas. From each selected household, one adult respondent will be selected to participate in the study.

Kind of data

Sample survey data [ssd]

Sampling procedure

Migration data for South Africa are available for 2007 only at the level of local governments or municipalities from the 2007 Census; for smaller areas called "sub places" (SPs) only as recently as the 2001 census, and for the desired EAs only back so far as the Census of 1996. In sum, there was no single source that provided recent data on the five types of migrants of principal interest at the level of the Enumeration Area, which was the area for which data were needed to draw the sample since it was going to be necessary to identify migrant and non-migrant households in the sample areas in order to oversample those with migrants for interview.

In an attempt to overcome the data limitations referred to above, it was necessary to adopt a novel approach to the design of the sample for the World Bank's household migration survey in South Africa, to identify EAs with a high probability of finding immigrants and those with a low probability. This required the combined use of the three sources of data described above. The starting point was the CS 2007 survey, which provided data on migration at a local government level, classifying each local government cluster in terms of migration level, taking into account the types of migrants identified. The researchers then spatially zoomed in from these clusters to the so-called sub-places (SPs) from the 2001 Census to classifying SP clusters by migration level. Finally, the 1996 Census data were used to zoom in even further down to the EA level, using the 1996 census data on migration levels of various typed, to identify the final level of clusters for the survey, namely the spatially small EAs (each typically containing about 200 households, and hence amenable to the listing operation in the field).

A higher score or weight was attached to the 2007 Community Survey municipality-level (MN) data than to the Census 2001 sub-place (SP) data, which in turn was given a greater weight than the 1996 enumerator area (EA) data. The latter was derived exclusively from the Census 1996 EA data, but has then been reallocated to the 2001 EAs proportional to geographical size. Although these weights are purely arbitrary since it was composed from different sources, they give an indication of the relevant importance attached to the different migrant categories. These weighted migrant proportions (secondary strata), therefore constituted the second level of clusters for sampling purposes.

In addition, a system of weighting or scoring the different persons by migrant type was applied to ensure that the likelihood of finding migrants would be optimised. As part of this procedure, recent migrants (who had migrated in the preceding five years) received a higher score than lifetime migrants (who had not migrated during the preceding five years). Similarly, a higher score was attached to international immigrants (both recent and lifetime, who had come to SA from abroad) than to internal migrants (who had only moved within SA's borders). A greater weight also applied to inter-provincial (internal) than to intra-provincial migrants (who only moved within the same South African province).

How the three data sources were combined to provide overall scores for EA can be briefly described. First, in each of the two provinces, all local government units were given migration scores according to the numbers or relative proportions of the population classified in the various categories of migrants (with non-migrants given a score of 1.0. Migrants were assigned higher scores according to their priority, with international migrants given higher scores than internal migrants and recent migrants higher scores than lifetime migrants. Then within the local governments, sub-places were assigned scores assigned on the basis of inter vs. intra-provincial migrants using the 2001 census data. Each SP area in a local government was thus assigned a value which was the product of its local government score (the same for all SPs in the local government) and its own SP score. The third and final stage was to develop relative migration scores for all the EAs from the 1996 census by similarly weighting the proportions of migrants (and non-migrants, assigned always 1.0) of each type. The the final migration score for an EA is the product of its own EA score from 1996, the SP score of which it is a part (assigned to all the EAs within the SP), and the local government score from the 2007 survey.

Based on all the above principles the set of weights or scores was developed.

In sum, we multiplied the proportion of populations of each migrant type, or their incidence, by the appropriate final corresponding EA scores for persons of each type in the EA (based on multiplying the three weights together), to obtain the overall score for each EA. This takes into account the distribution of persons in the EA according to migration status in 1996, the SP score of the EA in 2001, and the local government score (in which the EA is located) from 2007. Finally, all EAs in each province were then classified into quartiles, prior to sampling from the quartiles.

From the EAs so classified, the sampling took the form of selecting EAs, i.e., primary sampling units (PSUs, which in this case are also Ultimate Sampling Units, since this is a single stage sample), according to their classification into quartiles. The proportions selected from each quartile are based on the range of EA-level scores which are assumed to reflect weighted probabilities of finding desired migrants in each EA. To enhance the likelihood of finding migrants, much higher proportions of EAs were selected into the sample from the quartiles with the higher scores compared to the lower scores (disproportionate sampling). The decision on the most appropriate categorisations was informed by the observed migration levels in the two provinces of the study area during 2007, 2001 and 1996, analysed at the lowest spatial level for which migration data was available in each case.

Because of the differences in their characteristics it was decided that the provinces of Gauteng and Limpopo should each be regarded as an explicit stratum for sampling purposes. These two provinces therefore represented the primary explicit strata. It was decided to select an equal number of EAs from these two primary strata.

The migration-level categories referred to above were treated as secondary explicit strata to ensure optimal coverage of each in the sample. The distribution of migration levels was then used to draw EAs in such a way that greater preference could be given to areas with higher proportions of migrants in general, but especially immigrants (note the relative scores assigned to each type of person above). The proportion of EAs selected into the sample from the quartiles draws upon the relative mean weighted migrant scores (referred to as proportions) found below the table, but this is a coincidence and not necessary, as any disproportionate sampling of EAs from the quartiles could be done, since it would be rectified in the weighting at the end for the analysis.

The resultant proportions of migrants then led to the following proportional allocation of sampled EAs (Quartile 1: 5 per cent (instead of 25% as in an equal distribution), Quartile 2: 15 per cent (instead

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According to a survey conducted in 2024, ** percent of Americans believed that there should be a way for undocumented immigrants to stay in the United States legally if certain requirements are met. Hispanic Americans were most likely to share this belief, at ** percent. In contrast, only ** percent of White Americans believed that undocumented immigrants should have a way to stay in the country legally.

In 2025, the European country registering the largest number of migrants' arrivals was Italy. As of June 2025, 27,000 immigrants reached the Italian peninsula by sea. Spain had the second-largest number of arrivals by sea, 16,400 immigrants, both from the Wester Mediterranean route and the Wester African Atlantic route.

As of December 2024, Lombardy was the region in Italy hosting the largest share of immigrants, followed by Emilia-Romagna, Lazio, and Piedmont. Lombardy is the region with the highest number of inhabitants in the country. The north Italian region has ten million residents, around one sixth of the total national population, and was housing 18,200 immigrants. The Mediterranean route to Europe  In 2020, 955 migrants died or went missing in the Italian Central Mediterranean Sea in the attempt to reach Europe. In 2024, 66,317 people arrived at the Italian shores, 91,300 individuals less compared to 2023. Death and missing cases still represent a serious hazard for the people who want to reach Italy from North Africa. Racism on the rise in Italy Race-related violence is strictly correlated with immigration. According to 2020 data, the cases of racial physical violence increased, in particular between 2016 and 2018. Over these three years, the cases of body violence ranged from 24 to 127 attacks. Similarly, insults, threats, and harassment became more widespread. Between 2017 and 2019, the cases grew from 88 to 206, while only in the first three months of 2020 there were 53 episodes of racist insults, threats, and harassment.

In 2024, the net migration rate in France reached *******. In recent years Europe and France have seen more people arrive than depart. The net migration rate is the difference between the number of immigrants (people coming into an area) and the number of emigrants (people leaving an area) throughout the year. France's highest net migration rate was reached in 2018 when it amounted to *******. Armed conflicts and economic migration are some of the reasons for immigration in Europe. The refugee crisis Studies have shown that there were ******* immigrant arrivals in France in 2022, which has risen since 2014. The migrant crisis, which began in 2015 in Europe, had an impact on the migration entry flows not only in France but in all European countries. The number of illegal border crossings to the EU over the Eastern Mediterranean route reached a record number of ******* crossings in 2015. Immigration in France Since the middle of the 19th century, France has attracted immigrants, first from European countries (like Poland, Spain, and Italy), and then from the former French colonies. In 2023, there were approximately *** million people foreign-born in France. Most of them were living in the Ile-de-France region, which contains Paris, and in Provence-Alpes-Côte d’Azur in the Southeastern part of the country. In 2022, the majority of immigrants arriving in France were from Africa and Europe.

Significantly more men were apprehended by the United States Border Patrol than women in the the fiscal year of 2020. Nationwide, ******* men were apprehended by Border Patrol in that year, compared to ****** women who were apprehended.

In the twelve months to December 2024, approximately 948,000 people migrated to the United Kingdom, while 517,000 emigrated away from the country, resulting in a net migration figure of 431,000.