The estimated population of unauthorized immigrants in the U.S. stands at around 11 million people. Although the number has stabilized, the United States has seen a spike in migrant encounters in the last few years, with over two million cases registered by the U.S. Border Patrol in 2023. This is a slight decrease from the previous year, when there were over 2.2 million cases registered. Due to its proximity and shared border, Mexico remains the leading country of origin for most undocumented immigrants in the U.S., with California and Texas being home to the majority.

Immigration and political division

Despite the majority of the population having immigrant roots, the topic of immigration in the U.S. remains one of the country’s longest-standing political debates. Support among Republicans for restrictive immigration has grown alongside Democratic support for open immigration. This growing divide has deepened the polarization between the two major political parties, stifling constructive dialogue and impeding meaningful reform efforts and as a result, has led to dissatisfaction from all sides. In addition to general immigration policy, feelings toward illegal immigration in the U.S. also vary widely. For some, it's seen as a significant threat to national security, cultural identity, and economic stability. This perspective often aligns with support for stringent measures like Trump's proposed border wall and increased enforcement efforts. On the other hand, there are those who are more sympathetic toward undocumented immigrants, as demonstrated by support for the Deferred Action for Childhood Arrivals (DACA) program.

Canada’s appeal as an immigration destination has been increasing over the past two decades, with a total of 464,265 people immigrating to the country in 2024. This figure is an increase from 2000-2001, when approximately 252,527 immigrants came to Canada. Immigration to the Great White North Between July 1, 2022 and June 30, 2023, there were an estimated 199,297 immigrants to Ontario, making it the most popular immigration destination out of any province. While the number of immigrants has been increasing over the years, in 2024 over half of surveyed Canadians believed that there were too many immigrants in the country. However, in 2017, the Canadian government announced its aim to significantly increase the number of permanent residents to Canada in order to combat an aging workforce and the decline of working-age adults. Profiles of immigrants to Canada The gender of immigrants to Canada in 2023 was just about an even split, with 234,279 male immigrants and 234,538 female immigrants. In addition, most foreign-born individuals in Canada came from India, followed by China and the Philippines. The United States was the fifth most common origin country for foreign-born residents in Canada.

BACKGROUND:

The diamondback moth (DBM), Plutella xylostella (Lepidoptera: Plutellidae), is a notorious pest of cruciferous plants. In temperate areas, annual populations of DBM originate from adult migrants. However, the source populations and migration trajectories of immigrants remain unclear. Here, we investigated migration trajectories of DBM in China with genome-wide single nucleotide polymorphisms (SNPs) genotyped using double-digest RAD (ddRAD) sequencing. We first analyzed patterns of spatial and temporal genetic structure among southern source and northern recipient populations, then inferred migration trajectories into northern regions using discriminant analysis of principal components (DAPC), assignment tests and spatial kinship patterns.

RESULTS:

Temporal genetic differentiation among populations was low, indicating sources of recipient populations and migration trajectories are stable. Spatial genetic structure indicated three genetic clusters in the southern source populations. Assignment tests linked northern populations to the Sichuan cluster, and central-eastern populations to the South and Yunnan clusters, indicating that Sichuan populations are sources of northern immigrants and South and Yunnan populations are sources of central-eastern populations. First-order (full-sib) and second-order (half-sib) kin pairs were always found within populations, but about 35-40% of third-order (cousin) pairs were found in different populations. Closely related individuals in different populations were in about 35-40% of cases found at distances of 900 to 1500 km, while some were separated by over 2000 km.

CONCLUSION:

This study unravels seasonal migration patterns in the DBM. We demonstrate how careful sampling and population genomic analyses can be combined to help understand cryptic migration patterns in insects.

Methods Specimen collection and DNA extraction DBM were sampled from potential source population locations in the annual breeding area of southern China. DBM were collected from cabbage and oilseed rape fields, and all sampling was completed before the first observations of DBM in northern China between March and May 1, 2. In order to reduce the likelihood of sampling siblings within populations, third- and fourth-instar larvae of DBM were collected from about 20 sites at each sampling location, each at least 10 m apart. Putative immigrant male adults were collected in northern China by sex pheromone trapping before the presence of first-generation larvae. Trapping of male DBM was conducted in unplanted fields with no greenhouses within 500 m, to reduce the likelihood of trapping individuals overwintering in protected conditions. The distance between traps was at least 50 m. The development of one generation of DBM takes about 30 days in early spring 3. This strategy therefore restricted sampling of genetically related individuals to within three generations between source and recipient populations, and reduced the influence of genomic admixture between immigrants from different sources. This sampling was conducted in 2017 and again in 2018, to examine annual variation in migratory trajectories and temporal variation in population genetic structure. In total, samples were collected from 16 locations in 2017 and 17 locations in 2018, and in 2018 four locations were sampled across multiple months (Fig. 1, Table 1). Twenty individuals from each population (specimens collected at different times from the same location were considered as different populations) were used for genotyping. Genomic DNA for library preparation was extracted from individual specimens using DNeasy Blood and Tissue Kit (Qiagen, Germany). SNP genotyping The ddRAD libraries were prepared following a published protocol 4 for identifying SNPs. Briefly, 120 ng of extracted genomic DNA from each sample was digested by the restriction enzymes NlaIII and AciI (New England Biolabs, USA) 5. The 50 μL digestion reaction was run for 3 hours at 37 °C, followed by DNA cleaning using 1.5× volume of AMPure XP beads (Beckman Coulter, USA) instead of a heat kill step. Next, we ligated each sample to adapters barcoded with a combinatorial index at 16 °C overnight in a 40 μL ligation reaction, labeling each population with a 6-bp index and each individual with a unique 9-bp barcode. After ligation, we pooled uniquely barcoded samples into multiplexed libraries. Fragments between 380-540 bp were selected using BluePippin and a 2% gel cassette (Sage Sciences, USA). Finally, the pooled libraries were enriched with 12 amplification cycles on a Mastercycler Nexus Thermal Cycler (Eppendorf, Germany). PCR products were cleaned with 0.8× volume of beads. We used Qubit 3.0 (Life Invitrogen, USA) and Agilent 2100 Bioanalyzer (Agilent Technology, USA) to check the concentration and size distribution of enriched libraries, respectively. Pooled libraries were sequenced on an Illumina HiSeq 2500 platform to obtain 150-bp paired-end reads, at BerryGenomics Company (Beijing, China). The Stacks v2.3 pipeline 6 was used to call SNPs, linking to the DBM genome (GenBank assembly accession: GCA_000330985.1) as reference 7. FastQC v 0.11.5 was employed to assess read quality and check for adapter contamination 8. Sequence data was demultiplexed and trimmed using process_radtags in Stacks v2.3 6, 9. Low quality reads with a Phred score below 20 were removed as well as any reads with an uncalled base. Reads were trimmed to 140 bp in length. The remaining paired-end reads were aligned to the DBM genome 7 using Bowtie v2.3.5 10. Output reads for all individuals were imported into Stacks pipeline ref_map.pl to call SNPs, requiring a minimum of three identical reads to create a stack. SNPs were called using a maximum likelihood statistical model. Finally, we obtained a catalog with all possible loci and alleles. The exported loci were present in all populations, and in at least 75% of individuals per population. The exported SNPs for populations that were collected in both years were further filtered using the R package vcfR 11 and VCFtools v0.1.16 12 with the following criteria: SNPs with sequencing depth ≤ 3 and in the highest 0.1% depth were removed, as were SNPs with missingness in all samples ≥ 0.05 and those with minimum minor allele count ≤ 20. An additional data matrix was generated by retaining only SNPs separated by at least 500 bp, to reduce linkage among SNPs. Genetic diversity, population structure and assignment tests Global population differentiation was estimated using Weir and Cockerham’s FST with 99% confidence intervals (1000 bootstraps) in diveRsity version 1.9.90. Pairwise FST for all population pairs was estimated using GenePop version 4.7.2 13. Discriminant analysis of principal components (DAPC) was performed in the R package adegenet v2.1.1 14, with the optimal number of clusters determined by the Akaike information criterion (AIC). Assignment tests were performed in assignPOP v1.1.7 15. Source groups of ST (south) and SW (southwest, this group was divided into YN and SC groups in 2018) (see Table 1 and Fig. 1 for locations) were trained using the support vector machine algorithm to build predictive models. For training, we used either 25, 28, or 32 random individuals (2017 samples) or 13, 15 or 17 random individuals (2018 samples) from each group, and loci with the highest 60%, 80% or 100% FST values. Monte-Carlo cross-validation was performed by resampling each training set combination 1000 times. The ratio of assignment probability between the most-likely and second most-likely assigned groups was calculated for each individual 16. When an individual showed an assignment ratio smaller than 2 in more than 30% of the resampling analysis, it was considered unstable and removed in subsequent training. This allowed us to remove individuals from source populations that are not similar enough to other individuals in that source population, thus leaving a set of source populations each comprised of individuals distinctive from those in other populations. Immigrants from the CE (central) and NT (north) regions (see Table 1 and Fig. 1 for locations) were assigned to the trained groups using the support vector machine algorithm. Kinship analysis As a complement to assignment tests (but focusing on the individual level rather than the population level), we investigated spatial patterns of kinship within and between populations. Related individuals were identified following the method of Jasper, Schmidt, Ahmad, Sinkins and Hoffmann 17. First, Loiselle’s K was calculated for all individual pairs using SPAGeDi 18 . Kinship coefficients represent the probability that any allele scored in both individuals is identical by descent, with theoretical mean K values for each kinship category as follows: full‐siblings = 0.25, half-siblings = 0.125, full‐cousins = 0.0625, half‐cousins = 0.0313, second-cousins = 0.0156 and unrelated = 0. To allocate pairs of individuals to relatedness categories across three orders of kinship, maximum‐likelihood estimation in the program ML‐Relate 19 was used to identify first‐order (full‐sibling) and second‐order (half‐sibling) pairs. The K scores of pairs within the full‐sibling and half-sibling data sets were used to calculate standard deviations for these categories. Using the theoretical means and standard deviations of K, we randomly sampled 100,000 simulated K scores from each kinship category. In the initial pool of 40755 pairings (2017) and 89676 pairings (2018), ML‐Relate identified 33 (2017) and 36 (2018) full‐sibling and half‐sibling pairs. Assuming that the data contained twice as many first cousin (full and half) pairings as sibling (full and half) pairings, and twice as many second cousin pairings as first cousin pairings, final sampling distributions were developed as follows: 100,000 unrelated, 320 second-cousins, 80 full‐cousins, 80 half‐cousins, 40

Ontario was the province with the most immigrants in 2024, with 197,657 immigrants. Nunavut, Canada’s northernmost territory, had 56 immigrants arrive in the same period. Immigration to Canada Over the past 20 years, the number of immigrants to Canada has held steady and is just about evenly split between men and women. Asian countries dominate the list of leading countries of birth for foreign-born residents of Canada, although the United Kingdom, the United States, and Italy all make the list as well. Unemployment among immigrants In 2023, the unemployment rate for immigrants in Canada was highest among those who had been in the country for five years or less. The unemployment rate decreased the longer someone had been in Canada, and unemployment was lowest among those who had been in the country for more than ten years, coming more into line with the average unemployment rate for the whole of Canada.

1. Climate change is reported to have caused widespread changes to species' populations and ecological communities. Warming has been associated with population declines in long-distance migrants and habitat specialists, and increases in southerly distributed species. However, the specific climatic drivers behind these changes remain undescribed. 2. We analysed annual fluctuations in the abundance of 59 breeding bird species in England over 45 years to test the effect of monthly temperature and precipitation means upon population trends. 3. Strong positive correlations between population growth and both winter and breeding season temperature were identified for resident and short-distance migrants. Lagged correlations between population growth and summer temperature and precipitation identified for the first time a widespread negative impact of hot, dry summer weather. Resident populations appeared to increase following wet autumns. Populations of long-distance migrants were negatively affected by May temperature, consistent with a potential negative effect of phenological mismatch upon breeding success. There was evidence for some nonlinear relationships between monthly weather variables and population growth. 4. Habitat specialists and cold-associated species showed consistently more negative effects of higher temperatures than habitat generalists and southerly distributed species associated with warm temperatures. Results suggest that previously reported changes in community composition represent the accumulated effects of spring and summer warming. 5. Long-term population trends were more significantly correlated with species' sensitivity to temperature than precipitation, suggesting that warming has had a greater impact on population trends than changes in precipitation. Months where there had been the greatest warming were the most influential drivers of long-term change. There was also evidence that species with the greatest sensitivity to extremes of precipitation have tended to decline. 6. Our results provide novel insights about the impact of climate change on bird communities. Significant lagged effects highlight the potential for altered species' interactions to drive observed climate change impacts, although some community changes may have been driven by more immediate responses to warming. In England, resident and short-distance migrant populations have increased in response to climate change, but potentially at the expense of long-distance migrants, habitat specialists and cold-associated species.

The United States hosted, by far, the highest number of immigrants in the world in 2020. That year, there were over 50 million people born outside of the States residing in the country. Germany and Saudi Arabia followed behind at around 16 and 13 million, respectively. There are varying reasons for people to emigrate from their country of origin, from poverty and unemployment to war and persecution. American Migration People migrate to the United States for a variety of reasons, from job and educational opportunities to family reunification. Overall, in 2021, most people that became legal residents of the United States did so for family reunification purposes, totaling 385,396 people that year. An additional 193,338 people became legal residents through employment opportunities. In terms of naturalized citizenship, 113,269 people from Mexico became naturalized American citizens in 2021, followed by people from India, the Philippines, Cuba, and China. German Migration Behind the United States, Germany also has a significant migrant population. Migration to Germany increased during the mid-2010's, in light of the Syrian Civil War and refugee crisis, and during the 2020’s, in light of conflict in Afghanistan and Ukraine. Moreover, as German society continues to age, there are less workers in the labor market. In a low-migration scenario, Germany will have 37.2 million skilled workers by 2040, compared to 39.1 million by 2040 in a high-migration scenario. In both scenarios, this is still a decrease from 43.5 skilled workers in 2020.

In the past four centuries, the population of the United States has grown from a recorded 350 people around the Jamestown colony of Virginia in 1610, to an estimated 331 million people in 2020. The pre-colonization populations of the indigenous peoples of the Americas have proven difficult for historians to estimate, as their numbers decreased rapidly following the introduction of European diseases (namely smallpox, plague and influenza). Native Americans were also omitted from most censuses conducted before the twentieth century, therefore the actual population of what we now know as the United States would have been much higher than the official census data from before 1800, but it is unclear by how much. Population growth in the colonies throughout the eighteenth century has primarily been attributed to migration from the British Isles and the Transatlantic slave trade; however it is also difficult to assert the ethnic-makeup of the population in these years as accurate migration records were not kept until after the 1820s, at which point the importation of slaves had also been illegalized. Nineteenth century In the year 1800, it is estimated that the population across the present-day United States was around six million people, with the population in the 16 admitted states numbering at 5.3 million. Migration to the United States began to happen on a large scale in the mid-nineteenth century, with the first major waves coming from Ireland, Britain and Germany. In some aspects, this wave of mass migration balanced out the demographic impacts of the American Civil War, which was the deadliest war in U.S. history with approximately 620 thousand fatalities between 1861 and 1865. The civil war also resulted in the emancipation of around four million slaves across the south; many of whose ancestors would take part in the Great Northern Migration in the early 1900s, which saw around six million black Americans migrate away from the south in one of the largest demographic shifts in U.S. history. By the end of the nineteenth century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. Twentieth and twenty-first century The U.S. population has grown steadily throughout the past 120 years, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. In the past century, the U.S. established itself as a global superpower, with the world's largest economy (by nominal GDP) and most powerful military. Involvement in foreign wars has resulted in over 620,000 further U.S. fatalities since the Civil War, and migration fell drastically during the World Wars and Great Depression; however the population continuously grew in these years as the total fertility rate remained above two births per woman, and life expectancy increased (except during the Spanish Flu pandemic of 1918).

Since the Second World War, Latin America has replaced Europe as the most common point of origin for migrants, with Hispanic populations growing rapidly across the south and border states. Because of this, the proportion of non-Hispanic whites, which has been the most dominant ethnicity in the U.S. since records began, has dropped more rapidly in recent decades. Ethnic minorities also have a much higher birth rate than non-Hispanic whites, further contributing to this decline, and the share of non-Hispanic whites is expected to fall below fifty percent of the U.S. population by the mid-2000s. In 2020, the United States has the third-largest population in the world (after China and India), and the population is expected to reach four hundred million in the 2050s.

Geographic coverage

Nationally representative sample

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame

The 2002 population and housing census provided a frame for sample selection. The frame contains a list of all administrative units up to the lowest level called, 'Local Council 1', or LC1. This is usually, but not always consistent with a village in terms of area. The Enumeration Area (EA) may comprise of one village/LC1, or more than one village/LC1. The demarcation of EAs is based on total population within a given area and in many instances, may vary by locality. In addition the sampling frame also indicates the EA to which a particular LC belongs. The 2002 Uganda Sampling Frame has a total of 33,283 EAs.

Study population

The study population comprised of the entire population of Uganda. Based on the distribution of households in table 1 above, the sample was determined based on information from Uganda National Household survey 2005/06 conducted by the Uganda Bureau of Statistics. The proportion of internal migrants reported in the past 5 years has been used to estimate the required sample. Given the limited nature of the number of international migrants, the proportion of internal migrants is considered adequate to provide sufficient estimates of the indicators of interest.

Sample allocation by region

The above sample was proportionately allocated across the four statistical regions on the basis of the population in each of the regions. There was oversampling for urban population approximately by 5 times. To ease implementation, the regional sample was further disaggregated down to Enumeration Area level.

Selection of Enumeration Areas

The task was to undertake a nationally-representative survey of 2,000 households (urban and rural combined) in 2009 that would provide information on migration, remittances and their effects on development. The frame was be divided into two strata namely rural and urban. A two-stage stratified sample design was adopted. The first stage representing the primary sampling unit comprised of the selection of EAs from each of the strata while at the second and ultimate stage households were selected. EAs were selected from the list of Enumeration Areas developed after the 2002 Population and Housing Census and updated to include new districts.

The selection of EAs was proportionally done based on the number of households in the respective stratum according to the 2006 Uganda household survey. All the EAs in each domain were sorted by county, sub-county and parish. A random number was generated and an appropriate random start and sampling interval was systematically selected from the ordered list with probability proportionate to number of households. This was done separately for urban and rural areas, hence stratified sampling. The proportion of EAs sampled in urban areas is about 5 times that in rural.

Selection of households

At the second stage, a complete listing of households in each EA was done to classify the households into three groups: non migrants, internal migrants and international migrants. The number of households per EA varied from around 20 to about 1000. Most of the time, all households were listed even in the large EAs since it was difficult to establish lines of demarcation to segment the EA.

A total of 10 households were selected randomly from each of the 200 EAs. The goal was to select 4 households with an international migrant (emigrant), 3 with one or more internal migrants, and 3 with no migrant. This sampling was done from the three strata or listings of households according to migration status. Separate sampling was done from each stratum using systematic sampling. In case of a refusal or other reason for non-response, another household was selected from the same stratum to reach the desired quota. In case the number of households listed in any of the three strata was smaller than the numbers desired (4, 3, 3), then all those listed in that stratum were automatically sampled and the short fall selected from the next stratum.

For example, if there were, say, 150 households in an EA, with 3 with international migrants, 27 with internal migrants, and 120 with no migrants, the numbers selected would be, respectively, 3, 3 and 3. But to make up 10, priority would be given to the migrant stratum to add one more, randomly selected, from that stratum. As another example, suppose there were 0 international migrant households; then 7 would be selected from the internal migrant stratum and still only 3 from the list of non-migrant households.

The choice of 10 households per EA was based on experience from the various economic surveys conducted by UBOS, where 10 households provide adequate representation at EA level for most of the economic and social indicators.

The listing operation

The survey targeted household with in-migrants or former members who have migrated away, whether to another part of the country (urban or rural) or to another country. Since the census frame does not uniquely identify who is a migrant or non migrant, and owing to the lack of an up to date list of all households in Uganda from which to draw the sample, the survey team adopted a listing exercise as stop gap measure.

The exercise involved conducting a fresh listing of all households in each of the selected EAs. During the exercise, households with migrants were identified and the migrants clearly categorized as internal-within Uganda- or international where household members had moved to another country all together. The total number of listed household numbers was 24,618. Thereafter, a sample of 10 households was selected using systematic sampling procedure.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire consisted of seven sections namely: A Cover Sheet requiring household identification particulars including district name and code, county name and code, parish name and code, EA name, stratum, household number, names of the household head and first spouse, number of household members and a description of the location of the household.

In addition, the page captured details of the interview including the interviewer name, date, duration and the outcome of the interview. It also provided for the team leaders remarks and signature.

Section 1: Household roster

This section captured the socio-demographic characteristics of all household members.

Section 2: Households housing conditions

In this section, information was sought on the type of dwelling, occupancy status, the physical characteristics of the dwelling, and access to basic utilities including water, electricity and sanitation.

Section 3 Household Assets and Expenditure

The section collected information on the assets and expenditures of the household. This information was used to determine the welfare status of the household.

Section 4: Household Use of Financial Services:

In this section, information relating to use of financial services by household members was collected.

Section 5: Internal and International Migration And Remittances From Former Household Members

This section captured information on migration, both internal and international as well as remittances received by the household from former household member migrants.

Section 6: Internal and International Migration and Remittances From Former Household Members

Like section 5 above, section 6 sought information on migration, both internal and international as well as remittances received by the household from non household member migrants.

Section 7: Return Migrants

Here information on Return migrants was captured. A return migrant was defined as an adult member (over 18 years old) currently living in the household, who had lived in another country or another place in Uganda for at least 3 months in the 5 years preceding the survey. The information sought in this section related to the last migration episode for each return migrant.

Cleaning operations

Data Editing: Data editing was initially done by six editors from among the enumerators.

Response rate

Three categories of non response were encountered in the survey. These include: · Household not Visisted: In this category, the survey teams were unable to visit the households due to one reason or another. This happened in Karamoja, where 2 EAs could not be visited due to insecurity; Kalangala, an island EA where residents were reported to have vacated the EA on the advice of the National Environmental Management Authority (NEMA) in a bid to conserve the environment, four years prior to the visit by the survey team and in Kampala, where an EA could not be located. This led to a loss of 40 responses. · Incomplete Information: Here households were located but enumerators were not able to conduct or complete the interviews due to various reasons. Such reasons include respondents' hostility, interruption by an unforeseen event such as death of the respondent's close relative. The total number of responses lost in this category is 79. Overall, there were 1872 valid responses received representing a response rate of 94%. Of these, 49% reported having migrants.

Temporary residents who are in Canada on a study permit in the observed calendar year. Datasets include study permit holders by year in which permit(s) became effective or with a valid permit in a calendar year or on December 31st. Please note that in these datasets, the figures have been suppressed or rounded to prevent the identification of individuals when the datasets are compiled and compared with other publicly available statistics. Values between 0 and 5 are shown as “--“ and all other values are rounded to the nearest multiple of 5. This may result to the sum of the figures not equating to the totals indicated.

This table provides quarterly estimates of the number of non-permanent residents by type for Canada, provinces and territories.

In every year of the observed period, the sum of internal and international immigrants exceeded that of emigrants in Russia. In 2023, the emigrant count saw a decrease from the previous year. In aggregate terms, migration flows steadily decreased from 1990 to 2009. After 2010, the figures for in- and outflows started to recover. Why do Russians emigrate? A year after the Russia-Ukraine war began, more than one in ten Russians expressed their willingness to emigrate. The desire to provide children with a decent future was the leading reason for emigration, as cited by 45 percent of respondents who were willing to leave the country. The allegedly worsening economic situation in Russia and high-quality medicine abroad also ranked high. Among those who emigrated in 2022, the majority chose the Commonwealth of Independent States (CIS) countries or countries near the CIS region. Incentives to migrate to Russia One of the countries with the largest gross domestic product (GDP) worldwide, Russia remains a popular immigration destination. In 2023, nearly 171,000 people came to Russia from Tajikistan. Further 54,160 and 50,930 arrived from Kyrgyzstan and Ukraine, respectively. Russia’s visa-free regime with most post-Soviet states eases the entry into the country. For example, citizens of Armenia, Belarus, Kazakhstan, and Kyrgyzstan have the right to employment in Russia without obtaining a work permit. Citizens of Azerbaijan, Moldova, Tajikistan, Ukraine, and Uzbekistan can enter Russia visa-free and obtain a work patent upon arrival.

So far in 2025, The German Federal Office for Migration and Refugees recorded around 16,594 asylum applications. This was a decrease compared to the year before.

In 2023, California had the highest Hispanic population in the United States, with over 15.76 million people claiming Hispanic heritage. Texas, Florida, New York, and Illinois rounded out the top five states for Hispanic residents in that year. History of Hispanic people Hispanic people are those whose heritage stems from a former Spanish colony. The Spanish Empire colonized most of Central and Latin America in the 15th century, which began when Christopher Columbus arrived in the Americas in 1492. The Spanish Empire expanded its territory throughout Central America and South America, but the colonization of the United States did not include the Northeastern part of the United States. Despite the number of Hispanic people living in the United States having increased, the median income of Hispanic households has fluctuated slightly since 1990. Hispanic population in the United States Hispanic people are the second-largest ethnic group in the United States, making Spanish the second most common language spoken in the country. In 2021, about one-fifth of Hispanic households in the United States made between 50,000 to 74,999 U.S. dollars. The unemployment rate of Hispanic Americans has fluctuated significantly since 1990, but has been on the decline since 2010, with the exception of 2020 and 2021, due to the impact of the coronavirus (COVID-19) pandemic.

Germany has long been involved with international asylum applications, especially in recent years. The most applications came from Syrian asylum seekers. These was followed by applications from Afghanistan and Turkey. Germany as a refuge choice Statistics on the number of asylum applicants in Germany are recorded by the BAMF, or the Federal Office for Migration and Refugees (Bundesamt für Migration und Flüchtlinge). The coronavirus (COVID-19) pandemic has decreased refugee numbers in Europe, with travel bans across modes of transport and borders being closed. As the restrictions begin to lift, migration is beginning again. 2023 saw the highest number of applications for asylum since 2016. However, in 2024, numbers have decreased significanly again. Support for refugees remains a present issue, fraught with tension, legal complications and surrounded by constant debate with many believing that not enough is done to support them. Asylum decisions Not all asylum applications in Germany get accepted, due to various circumstances. Besides rejection, decisions regarding asylum may involve granting a legal status as a refugee, a grant of subsidiary protection or determining a deportation ban.

California was the state with the highest resident population in the United States in 2024, with 39.43 million people. Wyoming had the lowest population with about 590,000 residents. Living the American Dream Ever since the opening of the West in the United States, California has represented the American Dream for both Americans and immigrants to the U.S. The warm weather, appeal of Hollywood and Silicon Valley, as well as cities that stick in the imagination such as San Francisco and Los Angeles, help to encourage people to move to California. Californian demographics California is an extremely diverse state, as no one ethnicity is in the majority. Additionally, it has the highest percentage of foreign-born residents in the United States. By 2040, the population of California is expected to increase by almost 10 million residents, which goes to show that its appeal, both in reality and the imagination, is going nowhere fast.

In the fiscal year of 2022, 969,380 people became naturalized citizens in the United States. This is an increase from the previous year, when 813,861 people became naturalized citizens. 2020 saw a significant drop, a figure that was likely due to the impact of the coronavirus (COVID-19) pandemic.

There were 1,057,188 international students studying in the United States in the 2022/23 academic year. This is an increase from the previous year, when 948,519 international students were studying in the United States.