US counties by net international migration, July to June
Miami-Dade County had the highest net international migration, July to June of 3135 counties in 2019, at 36,756. Riverside County had the lowest, at -1,216. The median was 6 and the figure for the United States was 568,639. Source: the U.S. Census Bureau.
Top 40 counties, 2019
Full ranking
| Rank | Counties | 2019 | Change on 2018 |
|---|---|---|---|
| 1 | Miami-Dade County Estimated | 36,756 | -8.9% |
| 2 | Harris County Estimated | 24,967 | -2.4% |
| 3 | King County Estimated | 15,419 | -12.7% |
| 4 | Broward County Estimated | 13,198 | -16.8% |
| 5 | Dallas County Estimated | 9,889 | -0.6% |
| 6 | Middlesex County Estimated | 9,400 | -3.4% |
| 7 | Los Angeles County Estimated | 8,911 | -54.4% |
| 8 | Santa Clara County Estimated | 8,703 | -34.3% |
| 9 | Queens County Estimated | 8,604 | -17.7% |
| 10 | Fairfax County Estimated | 8,234 | +54.7% |
| 11 | Bronx County Estimated | 8,199 | -28.4% |
| 12 | Suffolk County Estimated | 7,928 | -8.9% |
| 13 | Maricopa County Estimated | 7,754 | +32.7% |
| 14 | Orange County Estimated | 7,680 | -57.6% |
| 15 | Cook County Estimated | 7,659 | -38.1% |
| 16 | Palm Beach County Estimated | 7,544 | -15.9% |
| 17 | Kings County Estimated | 7,228 | -18.9% |
| 18 | New York County Estimated | 6,313 | -20.2% |
| 19 | Montgomery County Estimated | 6,099 | +3% |
| 20 | Hudson County Estimated | 5,861 | +1.8% |
| 21 | Hillsborough County Estimated | 5,781 | -43.5% |
| 22 | Alameda County Estimated | 5,545 | -33.6% |
| 23 | Clark County Estimated | 5,543 | +3,145.6% |
| 24 | Mecklenburg County Estimated | 5,375 | +8.1% |
| 25 | Franklin County Estimated | 5,304 | +29.1% |
| 26 | Prince George's County Estimated | 4,617 | +2.8% |
| 27 | Tarrant County Estimated | 4,597 | -14.9% |
| 28 | Fort Bend County Estimated | 4,569 | -0.7% |
| 29 | Collin County Estimated | 4,398 | -2.2% |
| 30 | Philadelphia County Estimated | 4,368 | -52.5% |
| 31 | Travis County Estimated | 4,331 | -0.7% |
| 32 | DeKalb County Estimated | 3,975 | +0.8% |
| 33 | Marion County Estimated | 3,899 | -24.9% |
| 34 | Essex County Estimated | 3,781 | -9% |
| 35 | Essex County Estimated | 3,669 | -19.7% |
| 36 | Wake County Estimated | 3,654 | +5.4% |
| 37 | Hennepin County Estimated | 3,626 | -6% |
| 38 | Middlesex County Estimated | 3,511 | +0.2% |
| 39 | Fulton County Estimated | 3,149 | -1.1% |
| 40 | Norfolk County Estimated | 2,871 | +3.7% |
| 41 | Orange County Estimated | 2,765 | -53.6% |
| 42 | San Diego County Estimated | 2,756 | -40.7% |
| 43 | District of Columbia Estimated | 2,751 | -10% |
| 44 | Oakland County Estimated | 2,702 | -27.1% |
| 45 | San Francisco County Estimated | 2,684 | -35.5% |
| 46 | Gwinnett County Estimated | 2,665 | -18.1% |
| 47 | Snohomish County Estimated | 2,330 | -7.3% |
| 48 | Lee County Estimated | 2,324 | -29.5% |
| 49 | Duval County Estimated | 2,289 | -25.9% |
| 50 | Bergen County Estimated | 2,264 | +8.2% |
| 51 | Union County Estimated | 2,188 | -9.7% |
| 52 | Prince William County Estimated | 2,183 | +47.9% |
| 53 | Bexar County Estimated | 2,176 | -24.1% |
| 54 | San Mateo County Estimated | 2,142 | -34.9% |
| 54 | Worcester County Estimated | 2,142 | -45.1% |
| 56 | Collier County Estimated | 2,041 | -9.6% |
| 57 | St. Louis County Estimated | 2,038 | +0.4% |
| 58 | Pima County Estimated | 2,008 | +44.4% |
| 59 | Passaic County Estimated | 1,995 | -20.1% |
| 60 | Sacramento County Estimated | 1,959 | -42% |
| 61 | Baltimore County Estimated | 1,941 | +6% |
| 62 | Cobb County Estimated | 1,937 | -3.4% |
| 63 | Westchester County Estimated | 1,882 | -24.3% |
| 64 | Contra Costa County Estimated | 1,877 | -40.2% |
| 65 | Jefferson Parish Estimated | 1,872 | +36.1% |
| 66 | Greenville County Estimated | 1,860 | -0.3% |
| 67 | Salt Lake County Estimated | 1,845 | -52.4% |
| 68 | Arlington County Estimated | 1,811 | +46% |
| 69 | Ramsey County Estimated | 1,797 | -3% |
| 70 | Cuyahoga County Estimated | 1,779 | -34.5% |
| 71 | Honolulu County Estimated | 1,745 | -43.4% |
| 72 | Loudoun County Estimated | 1,738 | +46.5% |
| 73 | Wayne County Estimated | 1,732 | -41.5% |
| 74 | Hamilton County Estimated | 1,727 | +32.9% |
| 75 | Denton County Estimated | 1,726 | -8.1% |
| 76 | Durham County Estimated | 1,634 | +5.8% |
| 77 | Allegheny County Estimated | 1,632 | -33.3% |
| 78 | Suffolk County Estimated | 1,611 | -25.6% |
| 79 | Henrico County Estimated | 1,588 | +47.9% |
| 80 | Plymouth County Estimated | 1,487 | -1.5% |
| 81 | DuPage County Estimated | 1,481 | -33.3% |
| 82 | Alexandria city Estimated | 1,480 | +38.1% |
| 83 | Dane County Estimated | 1,464 | +30.6% |
| 84 | Tippecanoe County Estimated | 1,449 | -26.6% |
| 85 | Nassau County Estimated | 1,445 | -23.5% |
| 86 | Mercer County Estimated | 1,408 | -15.4% |
| 87 | Hillsborough County Estimated | 1,403 | +0.5% |
| 88 | Davidson County Estimated | 1,389 | -59.2% |
| 89 | Guilford County Estimated | 1,369 | +7.6% |
| 90 | Baltimore city Estimated | 1,354 | -9.6% |
| 91 | Pinellas County Estimated | 1,306 | -32.4% |
| 92 | Champaign County Estimated | 1,299 | -22.8% |
| 93 | Milwaukee County Estimated | 1,258 | -48.9% |
| 94 | Bernalillo County Estimated | 1,241 | +72.8% |
| 95 | Polk County Estimated | 1,232 | +172.6% |
| 96 | Jefferson County Estimated | 1,220 | +72.3% |
| 97 | Osceola County Estimated | 1,203 | -85.1% |
| 98 | Erie County Estimated | 1,193 | -50.3% |
| 99 | Providence County Estimated | 1,177 | -71.5% |
| 100 | Pierce County Estimated | 1,133 | +4.1% |
| 101 | Multnomah County Estimated | 1,106 | -28.5% |
| 102 | Johnson County Estimated | 1,103 | +93.5% |
| 103 | East Baton Rouge Parish Estimated | 1,078 | +55.8% |
| 104 | Montgomery County Estimated | 1,066 | -38.4% |
| 105 | Richland County Estimated | 1,044 | -6.1% |
| 106 | Brazos County Estimated | 1,022 | +2.4% |
| 107 | Minnehaha County Estimated | 1,020 | +218.8% |
| 108 | Arapahoe County Estimated | 1,013 | -58.8% |
| 109 | Montgomery County Estimated | 1,003 | +57.7% |
| 110 | New Castle County Estimated | 969 | +93.8% |
| 111 | Cumberland County Estimated | 948 | +69.6% |
| 112 | Bristol County Estimated | 932 | -49.2% |
| 113 | Montgomery County Estimated | 930 | -9.6% |
| 114 | Jackson County Estimated | 914 | +8.3% |
| 115 | Delaware County Estimated | 891 | -42% |
| 116 | Washington County Estimated | 868 | -30.9% |
| 117 | Seminole County Estimated | 859 | -64.3% |
| 118 | Howard County Estimated | 857 | +5.2% |
| 118 | Oklahoma County Estimated | 857 | -33.4% |
| 120 | Douglas County Estimated | 836 | -41.7% |
| 121 | Monroe County Estimated | 832 | -30.7% |
| 122 | Kent County Estimated | 830 | -30.1% |
| 123 | Williamson County Estimated | 827 | -11.3% |
| 124 | Summit County Estimated | 826 | +12.5% |
| 125 | Lehigh County Estimated | 797 | -71% |
| 126 | Alachua County Estimated | 791 | -20.5% |
| 127 | St. Louis city Estimated | 763 | +3% |
| 128 | Monroe County Estimated | 761 | -70.6% |
| 129 | Tulsa County Estimated | 758 | -39.5% |
| 130 | Onondaga County Estimated | 757 | -33.7% |
| 131 | Ingham County Estimated | 747 | -36.3% |
| 131 | Virginia Beach city Estimated | 747 | +154.9% |
| 133 | Washtenaw County Estimated | 738 | -44.3% |
| 134 | Richmond city Estimated | 722 | +30.8% |
| 135 | Yuma County Estimated | 720 | +129.3% |
| 136 | Story County Estimated | 719 | +119.9% |
| 137 | Sarasota County Estimated | 709 | -16.9% |
| 138 | Orleans Parish Estimated | 696 | +57.8% |
| 139 | Morris County Estimated | 683 | -13.3% |
| 140 | Denver County Estimated | 673 | -69.7% |
| 141 | Centre County Estimated | 648 | -26.3% |
| 141 | Luzerne County Estimated | 648 | -44.3% |
| 141 | Somerset County Estimated | 648 | +10.2% |
| 144 | Stearns County Estimated | 644 | -3.3% |
| 145 | Camden County Estimated | 617 | -51.3% |
| 146 | Johnson County Estimated | 609 | -45.2% |
| 146 | Shelby County Estimated | 609 | -63.9% |
| 148 | Manatee County Estimated | 607 | -29.9% |
| 149 | Boone County Estimated | 600 | +2.7% |
| 150 | Charleston County Estimated | 589 | +8.3% |
| 151 | Hamilton County Estimated | 588 | -34.1% |
| 152 | Anchorage Municipality Estimated | 582 | +85.9% |
| 153 | Cumberland County Estimated | 581 | +49.4% |
| 153 | Yakima County Estimated | 581 | +515% |
| 155 | Lake County Estimated | 563 | -39.2% |
| 156 | Yolo County Estimated | 550 | -36.4% |
| 157 | Hampshire County Estimated | 546 | -6.5% |
| 158 | Butler County Estimated | 541 | +30% |
| 159 | Albany County Estimated | 540 | -22.9% |
| 160 | Bartholomew County Estimated | 539 | -26.3% |
| 161 | St. Joseph County Estimated | 538 | -30.2% |
| 162 | Norfolk city Estimated | 533 | +223% |
| 163 | Webb County Estimated | 527 | +48.9% |
| 164 | Sedgwick County Estimated | 518 | -27.5% |
| 165 | Fayette County Estimated | 517 | +46.9% |
| 165 | Polk County Estimated | 517 | -86.4% |
| 167 | Orange County Estimated | 515 | +17.6% |
| 168 | Chester County Estimated | 514 | -51.5% |
| 169 | Lancaster County Estimated | 512 | -64.8% |
| 170 | St. Lucie County Estimated | 508 | -35.4% |
| 171 | Pinal County Estimated | 506 | +52.4% |
| 172 | Allen County Estimated | 504 | -31.3% |
| 173 | Dauphin County Estimated | 503 | -56.5% |
| 174 | Forsyth County Estimated | 498 | -4.2% |
| 175 | Monongalia County Estimated | 491 | +1,302.9% |
| 176 | Hawaii County Estimated | 488 | -13.2% |
| 177 | Macomb County Estimated | 487 | -56% |
| 178 | Chesterfield County Estimated | 476 | +40.8% |
| 179 | Frederick County Estimated | 475 | +0.2% |
| 180 | Horry County Estimated | 474 | +22.8% |
| 181 | Pasco County Estimated | 473 | -53.8% |
| 182 | Berks County Estimated | 472 | -78.7% |
| 182 | Dakota County Estimated | 472 | -17.2% |
| 184 | Linn County Estimated | 471 | +112.2% |
| 185 | Wyandotte County Estimated | 459 | -25% |
| 186 | Lexington County Estimated | 457 | +1.3% |
| 187 | Warren County Estimated | 450 | +27.5% |
| 188 | Volusia County Estimated | 447 | -74.4% |
| 189 | Doña Ana County Estimated | 442 | +213.5% |
| 190 | Brevard County Estimated | 439 | -57.2% |
| 191 | Montgomery County Estimated | 438 | +64.7% |
| 192 | Lancaster County Estimated | 430 | -42.2% |
| 193 | Utah County Estimated | 429 | -61.5% |
| 194 | Maui County Estimated | 425 | -32.5% |
| 195 | Rockland County Estimated | 421 | -26.4% |
| 196 | Berkeley County Estimated | 414 | +36.2% |
| 197 | Erie County Estimated | 413 | -40.1% |
| 197 | Newport News city Estimated | 413 | +49.1% |
| 199 | Chatham County Estimated | 412 | -22.6% |
| 199 | Grant County Estimated | 412 | +707.8% |
| 199 | Merrimack County Estimated | 412 | +22.6% |
| 199 | Olmsted County Estimated | 412 | -8.4% |
| 203 | Harrisonburg city Estimated | 410 | +13.9% |
| 204 | Tompkins County Estimated | 406 | -11.5% |
| 205 | McLean County Estimated | 399 | -25.6% |
| 206 | Chittenden County Estimated | 398 | +5% |
| 206 | Lucas County Estimated | 398 | +24.8% |
| 208 | Portage County Estimated | 394 | +45.4% |
| 209 | Anne Arundel County Estimated | 391 | +2.9% |
| 210 | Nueces County Estimated | 389 | +3.7% |
| 211 | Leon County Estimated | 383 | -27.5% |
| 212 | Forsyth County Estimated | 382 | -30.5% |
| 212 | Strafford County Estimated | 382 | +20.9% |
| 214 | Washington County Estimated | 378 | -1.3% |
| 215 | Roanoke city Estimated | 377 | +50.2% |
| 216 | Waukesha County Estimated | 371 | +50.2% |
| 217 | Benton County Estimated | 370 | +28.9% |
| 218 | Anoka County Estimated | 365 | -5.9% |
| 218 | St. Charles County Estimated | 365 | -18.9% |
| 220 | Skagit County Estimated | 364 | +208.5% |
| 221 | Whitman County Estimated | 362 | -13.2% |
| 222 | Midland County Estimated | 358 | +7.2% |
| 223 | Black Hawk County Estimated | 357 | +102.8% |
| 223 | Pulaski County Estimated | 357 | +139.6% |
| 225 | Beaufort County Estimated | 356 | +65.6% |
| 226 | Clark County Estimated | 353 | +2.9% |
| 227 | Whatcom County Estimated | 351 | -1.7% |
| 228 | Clayton County Estimated | 345 | -29.3% |
| 229 | Galveston County Estimated | 344 | -5% |
| 229 | Otero County Estimated | 344 | +84.9% |
| 231 | Barnstable County Estimated | 343 | -13.4% |
| 232 | Jefferson County Estimated | 337 | -32.9% |
| 233 | Boulder County Estimated | 336 | -67.6% |
| 234 | Potter County Estimated | 334 | +0.3% |
| 235 | Hendry County Estimated | 332 | -11.9% |
| 236 | Adams County Estimated | 330 | -73.8% |
| 236 | Albemarle County Estimated | 330 | +86.4% |
| 238 | Hampden County Estimated | 327 | -89.8% |
| 238 | Lackawanna County Estimated | 327 | -62.4% |
| 240 | Lafayette Parish Estimated | 323 | +104.4% |
| 241 | Escambia County Estimated | 322 | +84% |
| 242 | Marin County Estimated | 321 | -38.2% |
| 243 | Delaware County Estimated | 318 | +25.7% |
| 244 | Lynchburg city Estimated | 315 | +42.5% |
| 245 | York County Estimated | 313 | +16.8% |
| 246 | Lubbock County Estimated | 311 | -8.8% |
| 247 | Atlantic County Estimated | 310 | -40.3% |
| 248 | Brookings County Estimated | 309 | +180.9% |
| 248 | Bucks County Estimated | 309 | -54.8% |
| 248 | Spartanburg County Estimated | 309 | 0% |
Other periods
About this ranking
Estimated moves into the area from abroad minus moves out of the area to other countries, from July 1 of the previous year through June 30 of the reported year. United States: Census Bureau estimates, including people born in the United States and abroad, moves between the states and Puerto Rico, and net movement of the Armed Forces overseas. Canada: Statistics Canada immigrants, minus net emigration, plus the net change in non-permanent residents. Australia: ABS net overseas migration for the financial year. United Kingdom local authorities: Office for National Statistics mid-year estimates, counting people who move for at least 12 months.
A component of each country's official population estimates. Methods differ between the statistical offices, so compare places within a country first. Differs from the World Bank net_migration series, which uses calendar years and a different method.
Every value in the ranking comes from the same publisher and the same period, so the counties are compared on one definition. 9 counties with data in other periods have no value for 2019 and are left out rather than filled from another source. Equal values share a rank.
How to cite
U.S. Census Bureau. Population Estimates Program: net international migration, July 1 of the previous year to June 30 of the reported year; vintage 2020 files for 2011 to 2020 and the latest 2020s vintage from 2021. https://www.census.gov/programs-surveys/popest/data/data-sets.html. Retrieved 2026-10-12.Citation styles
APA 7
U.S. Census Bureau. (2026). Population Estimates Program: net international migration, July 1 of the previous year to June 30 of the reported year; vintage 2020 files for 2011 to 2020 and the latest 2020s vintage from 2021 (US counties by net international migration, July to June, 2019) [Data set]. Retrieved October 12, 2026, from https://www.census.gov/programs-surveys/popest/data/data-sets.html
MLA 9
Population Estimates Program: net international migration, July 1 of the previous year to June 30 of the reported year; vintage 2020 files for 2011 to 2020 and the latest 2020s vintage from 2021, US counties by net international migration, July to June, 2019. U.S. Census Bureau, 26 Mar. 2026, https://www.census.gov/programs-surveys/popest/data/data-sets.html. Invokely, https://invokely.ai/rankings/net-international-migration-july-june/us-counties?period=2019. Accessed 12 Oct. 2026.
Chicago (author-date)
U.S. Census Bureau. 2026. Population Estimates Program: net international migration, July 1 of the previous year to June 30 of the reported year; vintage 2020 files for 2011 to 2020 and the latest 2020s vintage from 2021. US counties by net international migration, July to June, 2019. Dataset. Accessed October 12, 2026. https://www.census.gov/programs-surveys/popest/data/data-sets.html. Also distributed by Invokely, https://invokely.ai/rankings/net-international-migration-july-june/us-counties?period=2019.
Harvard
U.S. Census Bureau (2026) Population Estimates Program: net international migration, July 1 of the previous year to June 30 of the reported year; vintage 2020 files for 2011 to 2020 and the latest 2020s vintage from 2021, US counties by net international migration, July to June, 2019 [Dataset]. Available at: https://www.census.gov/programs-surveys/popest/data/data-sets.html, via Invokely: https://invokely.ai/rankings/net-international-migration-july-june/us-counties?period=2019 (Accessed: 12 October 2026).
BibTeX
@misc{census_us_counties_by_net_2019,
author = {{U.S. Census Bureau}},
title = {{Population Estimates Program: net international migration, July 1 of the previous year to June 30 of the reported year; vintage 2020 files for 2011 to 2020 and the latest 2020s vintage from 2021: US counties by net international migration, July to June, 2019}},
year = {2026},
howpublished = {Data set},
url = {https://www.census.gov/programs-surveys/popest/data/data-sets.html},
urldate = {2026-10-12},
note = {Accessed via Invokely, https://invokely.ai/rankings/net-international-migration-july-june/us-counties?period=2019. Publisher attribution: U.S. Census Bureau. Population Estimates Program: net international migration, July 1 of the previous year to June 30 of the reported year; vintage 2020 files for 2011 to 2020 and the latest 2020s vintage from 2021. https://www.census.gov/programs-surveys/popest/data/data-sets.html. Retrieved 2026-10-12.},
}
RIS
TY - DATA
AU - U.S. Census Bureau
TI - Population Estimates Program: net international migration, July 1 of the previous year to June 30 of the reported year; vintage 2020 files for 2011 to 2020 and the latest 2020s vintage from 2021: US counties by net international migration, July to June, 2019
PY - 2026
DA - 2026/03/26
PB - U.S. Census Bureau
DB - Invokely
UR - https://www.census.gov/programs-surveys/popest/data/data-sets.html
L2 - https://invokely.ai/rankings/net-international-migration-july-june/us-counties?period=2019
Y2 - 2026/10/12
N1 - Accessed via Invokely, https://invokely.ai/rankings/net-international-migration-july-june/us-counties?period=2019.
N1 - Publisher attribution: U.S. Census Bureau. Population Estimates Program: net international migration, July 1 of the previous year to June 30 of the reported year; vintage 2020 files for 2011 to 2020 and the latest 2020s vintage from 2021. https://www.census.gov/programs-surveys/popest/data/data-sets.html. Retrieved 2026-10-12.
ER -
Use this data in your AI agent
Invokely serves this figure to AI assistants through MCP and to code through a REST API, with the source and citation attached. Ask your assistant:
Rank US counties by net international migration, July to June using official data, and cite the source.
rank_places {"indicator":"net_international_migration_july_june","level":"province","within":"United States","limit":10}
GET https://invokely.ai/api/v1/rank?indicator=net_international_migration_july_june&level=province&within=United%20States&limit=10Questions
Which county has the highest net international migration, July to June?
Miami-Dade County, with 36,756 in 2019, according to the U.S. Census Bureau.
Which county has the lowest net international migration, July to June?
Riverside County, with -1,216 in 2019.
Where does this ranking come from?
Every value comes from one source and one period, so the places are comparable: U.S. Census Bureau, Population Estimates Program: net international migration, July 1 of the previous year to June 30 of the reported year; vintage 2020 files for 2011 to 2020 and the latest 2020s vintage from 2021. Retrieved 2026-10-12. 9 counties have no value for 2019 and are not ranked.