Wisconsin: Census data for your State Plan

701,774 of 5,828,067 civilian noninstitutionalized residents of Wisconsin report a disability, 12.0%. 2019–2023 ACS 5-year estimates.

The state in numbers

What Wisconsin's centers reported.

Counties

Population and people with a disability for each of Wisconsin's 72 counties, with the disability count by age band. Each estimate has a margin of error that is wide for small counties; the Census Bureau publishes the margins with the table.

Civilian noninstitutionalized population with a disability by county, WisconsinU.S. Census Bureau, American Community Survey 2019-2023 5-year estimates, tables B18101 and B18101A-I (civilian noninstitutionalized population)
CountyPopulationWith a disabilityDisability rateUnder 1818 to 6465 and over
Adams County20,2474,41821.8%2171,8862,315
Ashland County15,8192,51115.9%1721,2751,064
Barron County46,2596,61414.3%4263,0493,139
Bayfield County16,2992,71516.7%1881,1051,422
Brown County266,79231,01611.6%2,75116,78011,485
Buffalo County13,2852,03015.3%1228551,053
Burnett County16,6583,15819.0%1291,4261,603
Calumet County52,4925,0789.7%2892,4632,326
Chippewa County64,0767,23911.3%5483,3083,383
Clark County34,2764,11612.0%3662,0611,689
Columbia County56,9236,74211.8%4843,5402,718
Crawford County15,3381,83211.9%537321,047
Dane County561,01049,9888.9%4,35226,14019,496
Dodge County84,76610,20012.0%4745,0834,643
Door County30,0383,61212.0%1161,1952,301
Douglas County43,5316,60415.2%4753,0693,060
Dunn County45,0125,87413.0%4743,3512,049
Eau Claire County105,73314,00313.2%1,2247,7345,045
Florence County4,55977817.1%41373364
Fond du Lac County102,35612,49112.2%1,1186,3764,997
Forest County9,0771,62617.9%101783742
Grant County50,6405,50510.9%3192,9022,284
Green County36,7404,40512.0%3112,2291,865
Green Lake County19,0002,95515.6%2851,2861,384
Iowa County23,6862,80711.9%1741,3761,257
Iron County6,06197016.0%40453477
Jackson County19,8852,79914.1%1651,4181,216
Jefferson County85,49610,19111.9%7735,4623,956
Juneau County25,4284,39817.3%3032,1871,908
Kenosha County166,96021,95513.1%1,82711,5798,549
Kewaunee County20,5212,46312.0%1771,2501,036
La Crosse County119,19313,96511.7%9326,6386,395
Lafayette County16,7191,78810.7%182728878
Langlade County19,2753,37217.5%3271,6161,429
Lincoln County27,9604,17014.9%1991,9002,071
Manitowoc County80,61410,57213.1%1,0205,3164,236
Marathon County137,02017,13012.5%1,1888,2837,659
Marinette County41,3736,33915.3%5642,8672,908
Marquette County15,6492,83118.1%2491,2661,316
Menominee County4,23464115.1%39366236
Milwaukee County920,579115,60012.6%10,02163,72441,855
Monroe County45,4406,20313.7%4373,1692,597
Oconto County39,0345,60414.4%3572,8282,419
Oneida County37,5015,50114.7%2812,5362,684
Outagamie County190,12720,64110.9%1,81910,0458,777
Ozaukee County91,8609,42610.3%7443,9254,757
Pepin County7,31488012.0%49363468
Pierce County42,0184,29210.2%4442,2241,624
Polk County44,9496,26013.9%4193,1222,719
Portage County70,1677,99911.4%3804,3613,258
Price County13,9392,35216.9%909911,271
Racine County192,63426,50113.8%2,85813,51610,127
Richland County17,1042,44914.3%1331,1551,161
Rock County162,89221,36213.1%1,79810,9458,619
Rusk County13,9952,42617.3%1141,0971,215
Sauk County65,1887,94912.2%7463,4253,778
Sawyer County17,8672,94916.5%1901,4421,317
Shawano County40,4306,16615.3%4092,8932,864
Sheboygan County115,46312,87711.2%1,0846,2515,542
St. Croix County94,1169,3339.9%6554,8673,811
Taylor County19,8182,47112.5%1591,1701,142
Trempealeau County30,4423,32810.9%3471,4771,504
Vernon County30,6483,26010.6%1811,6771,402
Vilas County23,2433,58115.4%2911,4071,883
Walworth County104,78312,60612.0%8456,2545,507
Washburn County16,5992,64015.9%1651,1541,321
Washington County136,71413,4619.8%1,0175,6286,816
Waukesha County406,83138,1069.4%2,41115,55620,139
Waupaca County50,6007,37014.6%3753,8503,145
Waushara County23,8253,80216.0%1521,7661,884
Winnebago County167,39221,20612.7%1,51310,9418,752
Wood County73,55511,27215.3%1,0595,1725,041

Draft indicator language

Illustrations, not recommendations

These sentences show what an indicator looks like when the Census denominator is written into it, with Wisconsin's numbers filled in. The council, the designated state entity and the centers decide the targets. The plan's own definition of served, unserved and underserved governs; nothing here replaces it.

  1. Statewide reach. "By the end of the plan period, the Independent Living network will serve at least 3,151 consumers statewide, 44.9 per 10,000 of the 701,774 civilian noninstitutionalized residents with a disability (2019–2023 ACS 5-year estimates), the national median rate in report year 2023." The 2023 baseline is 4,318 consumers, 61.5 per 10,000.
  2. Reach in the largest county. "Centers will serve at least 519 consumers who live in Milwaukee County, 44.9 per 10,000 of its 115,600 residents with a disability, and will report the county figure each quarter."
  3. Presence in the smallest county. "At least one center will record consumers served in Menominee County (641 residents with a disability) in every quarter of the plan period, and the network will report reach per 10,000 for that county annually, noting the estimate's margin of error."
  4. Working-age reach. "Of consumers served, at least the share corresponding to the state's age mix will be aged 18 to 64. In Wisconsin, 350,637 of 701,774 people with a disability (50%) are of working age."
  5. Youth transition. "The network will serve at least N young people aged 14 to 24 each year, against a base of 54,737 children under 18 with a disability in the state (the Census band does not match 14 to 24 exactly; the plan should say so)."
  6. Improvement on baseline. "The network will increase consumers served by 10% over the 2023 baseline, from 4,318 to 4,750, and will publish reach per 10,000 by county each year so the increase can be seen where it happens."

Each of these needs the same twelve-month window and the same definition of a consumer at every center. Without that, the numerator cannot be trusted, and no denominator fixes it. The common definitions are the place to start.

Read before using

How penetration rates and thresholds work, and the county table as a CSV.