This article was updated on October 21st, 2021 with more recent jail and prison population data. That version should be used instead of this one.
Since the beginning of the COVID-19 pandemic, the strategy to slowing its spread behind bars was clear: Reduce the number of people in jails and prisons. In March, public health and medical officials were already warning that incarcerated people would be uniquely vulnerable to the spread of the disease and its most serious medical consequences, due to their close quarters and high rates of preexisting health conditions.
And yet, more than eight months after the World Health Organization declared the pandemic, prisons and jails have generally failed to reduce their populations enough to protect the health and lives of those who are incarcerated. While state prison populations have slowly declined from pre-pandemic levels, the pace of these modest reductions has slowed since the spring, even as national infection rates continue to rise. And county jails — which made promising reductions in the spring — have failed to sustain those reforms.
Despite the rising national case rate of COVID-19, the number of people held in 514 county jails across the country has increased over the past four months. This graph contains aggregated data collected by NYU’s Public Safety Lab and updates a graph in our September 10th briefing. This graph includes all jails where the Lab was able to report data on March 10th and for at least 75% of the days in our research period. (The Public Safety Lab is continuing to add more jails to its data collection and data is not available for all facilities for all days.) To see county level data for all 514 jails included in this analysis, see Appendix A. This graph presents the data as 7-day rolling averages, which smooths out most of the variations caused by individual facilities not being reported on particular days. The temporary population drops/increases during the last weeks of May and August, as well as the first week of November, are the result of more facilities than usual not being included in the dataset for various reasons, rather than any known policy changes.
As a result of these failures to sufficiently decarcerate, the early warnings of health experts have come true: the COVID-19 case rate in state and federal prisons is more than four times as high as that of the general public, and the death rate is more than twice as high. The Texas prison system alone has had more COVID-19 cases than in four states and Washington, D.C. combined. And since people who work in prisons and jails regularly return to their communities, correctional facilities are dangerously poised to become incubators for the disease and contribute to rising infection rates in surrounding communities.
Initially, many local officials — including sheriffs, prosecutors, and judges — responded quickly to reduce jail populations. In a national sample of 514 county jails of varying sizes, most (88%) decreased their populations from March to July, resulting in an average population reduction across all 514 jails of 26%.1 These population reductions came as the result of various policy changes, including police issuing citations in lieu of arrests, prosecutors declining to charge people for “low-level offenses,” courts reducing cash bail amounts, and jail administrators releasing people detained pretrial or those serving short sentences for “nonviolent offenses.”
But now the data tells a different story. Since July, 77% of the jails in our sample had population increases, suggesting that the early reforms instituted to mitigate COVID-19 have largely been abandoned. For example, by mid-April, the Philadelphia city jail population reportedly dropped by more than 17% after city police suspended low-level arrests and judges released “certain nonviolent detainees” jailed for “low-level charges.” But on May 1st — as the pandemic raged on — the Philadelphia police force announced that they would resume arrests for property crimes, effectively reversing the earlier reduction efforts. Similarly, on July 10th, the sheriff of Jefferson County, Alabama, announced that the jail would limit admissions to only “violent felons that cannot make bond.”2 That effort was quickly abandoned when the jail resumed normal admission operations just one week later. The increasing jail populations across the country suggest that after the first wave of responses to COVID-19, many local officials have allowed jail admissions to return to business as usual.
On the other hand, state prison populations have continued to decline, but not quickly or significantly enough to slow the spread of COVID-19. Even in states where prison populations have dropped, there are still too many people behind bars to accommodate social distancing, effective isolation and quarantine, and increased health care requirements. For example, although California has reduced the state prison population by about 20% since January, the number of large COVID-19 outbreaks in California state prisons suggests that the population reduction needs to be much more drastic. In fact, as of November 18th, California’s state prisons were still holding more people than they were designed for, at 105% of their design capacity.
Prison population data for 21 states where population data was readily available for January, May, July, August, September, October, and November, either directly from the state Departments of Correction or the Vera Institute of Justice. See our COVID-19 response tracker for more information on many of the most important policy changes that led to these small reductions in some states. For the population data for these 21 states, see Appendix B.
Sharp-eyed readers may wonder if Connecticut and Vermont are showing larger declines than most other states because those two states have “unified” prison and jail systems. However, data from both states show that the bulk of their population reduction is coming from within the “sentenced” portion of their populations. (For the Connecticut data, see the Correctional Facility Population Count Report, and for Vermont, see the daily population reports.)
Early in the pandemic, North Dakota quickly reduced its prison population by 19% between January and May 2020, a trend that continued until the beginning of October. But over the past month this trend reversed and the states’ prison population actually started to increase (by 3% from October 8 to November 19). Now, North Dakota is experiencing the state’s first major outbreaks of COVID-19 in prison. In one facility, the James River Correctional Center, more than half of the incarcerated population had active COVID-19 infections as of November 23rd.
According to a October 2020 report from the National Academies of Science, Engineering, and Medicine, the modest declines in prison populations can be largely attributed to changes in arrests, jail bookings, and court closures — not releases. Despite evidence that large-scale releases do not inherently endanger public safety, states have elected to release people from prison on a mostly case-by-case basis, which the National Academies report describes as “procedurally slow and not well suited to crisis situations.”
Thankfully, some states have recognized the inefficiency of case-by-case releases and the necessity of larger-scale releases. For example, in New Jersey,3 Governor Phil Murphy signed (link no longer available) bill S2519 in October, which allowed for the early release of people with less than a year left on their sentences. A few weeks after the bill was signed, more than 2,000 people were released from New Jersey state prisons on November 4th.4
Prisons and jails are notoriously dangerous places during a viral outbreak, and continue to be a major source of a large number of infections in the U.S. The COVID-19 death rate in prisons is three times higher than among the general U.S. population, even when adjusted for age and sex (as the prison population is disproportionately young and male). Since the early days of the pandemic, public health professionals, corrections officials, and criminal justice reform advocates have agreed that decarceration is necessary to protect incarcerated people and the community-at-large from COVID-19. Despite this knowledge, state, federal, and local authorities have failed to reduce jail and prison populations on a major scale, which continues to put incarcerated people’s lives at risk — and by extension, the lives of everyone in greater communities where incarcerated people eventually return, and where correctional staff live and work.
Footnotes
The NYU Public Safety Lab Jail Data Initiative has collected jail populations for over 1,000 facilities from January to November. This sample includes jails of varying size, as well as geographic diversity. For each of our analyses of jail and prison populations during the pandemic (including our earlier analyses in May, August, and September), we included all jails from this database that had population data available for at least 75% of the days in the period being studied, and had data going back to March 10. As time has passed, additional jails have been added to the Jail Data Initiative database, allowing us to increase the number of jails in our sample. For this November analysis, we included 514 jails. (We included all 514 jails that had at least 188 days worth of data, representing at least 75% of the days between March 10th and November 15th; had data available on March 10th; and continued to have data available after August 1st). ↩
The news story from Jefferson County does not make clear whether officials are using “violent” to refer to the crime a person is charged with, crimes of which they have already convicted, a label imposed on them by a risk assessment tool, or something else. ↩
New Jersey is not included in the above graph of state prison population changes because the New Jersey Department of Correction has not published monthly population data for 2020. However, in an October 2020 press release (link no longer available), Governor Phil Murphy claimed the population in state correctional facilities had “decreased by nearly 3,000 people (16%)” since March. ↩
Soon after these releases, 88 people who were released under bill S2519 were quickly arrested by U.S. Immigration and Customs Enforcement (ICE) officials. A spokesperson from ICE claimed that these 88 individuals were “violent offenders or have convictions for serious crimes such as homicide, aggravated assault, drug trafficking and child sexual exploitation.” However, these claims are brought into question when considering that the releases that took place under bill S2519 specifically excluded “people serving time for murder or sexual assault” and those serving time for sexual offenses. Although we did not include ICE facilities in our analysis, there is evidence that ICE detention facilities have a COVID-19 case rate that is up to 13 times higher than that of the general U.S. population. ↩
Appendix A: County jail populations during COVID-19
This table shows the jail populations for 514 county jails where data was available where data was available for March 10th (the day the pandemic was declared) and for 75% of the days between March 10th and November 15th. (This table is a subset of the population data available for over 1,000 local jails from the NYU Public Safety Lab Jail Data Initiative.)
County
State
March population
July population
Most recent population
Percent change from March to July
Percent change from July to the most recent date
Net percent change since March
March date
July date
Most recent date
Autauga
Ala.
171
158
193
-8%
20%
13%
3/10
7/1
11/15
Blount
Ala.
125
117
159
-6%
36%
27%
3/10
7/1
11/15
Chambers
Ala.
134
70
2
-48%
-97%
-99%
3/10
7/1
11/15
Cherokee
Ala.
110
73
76
-34%
4%
-31%
3/10
7/1
11/15
Clay
Ala.
38
31
31
-18%
0%
-18%
3/10
7/1
11/15
Cleburne
Ala.
84
59
70
-30%
19%
-17%
3/10
7/1
11/15
Coffee
Ala.
127
77
83
-39%
8%
-35%
3/10
7/1
11/15
Coosa
Ala.
27
30
25
11%
-17%
-7%
3/10
7/1
11/15
Dale
Ala.
74
65
91
-12%
40%
23%
3/10
7/1
11/15
DeKalb
Ala.
167
141
168
-16%
19%
1%
3/10
7/1
11/15
Franklin
Ala.
121
84
88
-31%
5%
-27%
3/10
7/1
11/15
Houston
Ala.
393
322
386
-18%
20%
-2%
3/10
7/2
11/15
Jackson
Ala.
177
180
233
2%
29%
32%
3/10
7/1
11/15
Limestone
Ala.
251
198
208
-21%
5%
-17%
3/10
7/1
9/3
Marion
Ala.
131
133
146
2%
10%
11%
3/10
7/1
11/15
Morgan
Ala.
615
549
608
-11%
11%
-1%
3/10
7/1
11/15
Pickens
Ala.
106
116
131
9%
13%
24%
3/10
7/1
11/15
Pike
Ala.
62
37
57
-40%
54%
-8%
3/10
7/1
11/15
Randolph
Ala.
64
51
69
-20%
35%
8%
3/10
7/1
11/15
St. Clair
Ala.
219
230
198
5%
-14%
-10%
3/10
7/1
11/15
Talladega
Ala.
301
219
314
-27%
43%
4%
3/10
7/2
11/15
Washington
Ala.
58
39
57
-33%
46%
-2%
3/10
7/1
11/15
Baxter
Ark.
120
83
112
-31%
35%
-7%
3/10
7/1
11/15
Benton
Ark.
673
374
582
-44%
56%
-14%
3/10
7/2
11/15
Boone
Ark.
103
73
95
-29%
30%
-8%
3/10
7/1
11/15
Columbia
Ark.
78
27
36
-65%
33%
-54%
3/10
7/1
11/15
Crawford
Ark.
215
152
266
-29%
75%
24%
3/10
7/1
11/15
Cross
Ark.
69
58
49
-16%
-16%
-29%
3/10
7/1
11/15
Drew
Ark.
63
34
44
-46%
29%
-30%
3/10
7/1
11/15
Faulkner
Ark.
466
222
323
-52%
45%
-31%
3/10
7/1
11/15
Franklin
Ark.
36
21
94
-42%
348%
161%
3/10
7/1
11/15
Hempstead
Ark.
68
48
81
-29%
69%
19%
3/10
7/1
11/15
Howard
Ark.
41
14
29
-66%
107%
-29%
3/10
7/1
11/15
Jefferson
Ark.
293
173
187
-41%
8%
-36%
3/10
7/1
11/15
Johnson
Ark.
63
27
67
-57%
148%
6%
3/10
7/1
11/15
Madison
Ark.
9
1
1
-89%
0%
-89%
3/10
7/4
11/15
Marion
Ark.
42
23
69
-45%
200%
64%
3/10
7/1
11/15
Monroe
Ark.
16
13
9
-19%
-31%
-44%
3/10
7/1
11/15
Nevada
Ark.
55
37
60
-33%
62%
9%
3/10
7/1
11/15
Poinsett
Ark.
80
43
90
-46%
109%
13%
3/10
7/1
11/15
Pope
Ark.
193
133
172
-31%
29%
-11%
3/10
7/1
11/15
Saline
Ark.
233
125
200
-46%
60%
-14%
3/10
7/1
11/15
St. Francis
Ark.
71
36
25
-49%
-31%
-65%
3/10
7/1
11/15
Stone
Ark.
36
34
37
-6%
9%
3%
3/10
7/1
11/15
Union
Ark.
199
141
163
-29%
16%
-18%
3/10
7/1
11/15
Van Buren
Ark.
78
29
42
-63%
45%
-46%
3/10
7/1
11/15
Washington
Ark.
678
399
504
-41%
26%
-26%
3/10
7/1
11/15
White
Ark.
277
81
208
-71%
157%
-25%
3/10
7/1
11/15
Yavapai
Ariz.
537
439
485
-18%
10%
-10%
3/10
7/1
11/15
Yuma
Ariz.
427
357
443
-16%
24%
4%
3/10
7/1
11/15
El Dorado
Calif.
383
325
324
-15%
0%
-15%
3/10
7/1
11/15
Siskiyou
Calif.
91
76
87
-16%
14%
-4%
3/10
7/1
11/15
Stanislaus
Calif.
1343
1048
1121
-22%
7%
-17%
3/10
7/7
11/15
Tulare
Calif.
1562
1200
1342
-23%
12%
-14%
3/10
7/1
11/15
Yuba
Calif.
383
207
212
-46%
2%
-45%
3/10
7/1
11/15
Arapahoe
Colo.
1123
681
789
-39%
16%
-30%
3/10
7/1
11/15
Bent
Colo.
55
26
51
-53%
96%
-7%
3/10
7/1
11/15
Boulder
Colo.
647
396
453
-39%
14%
-30%
3/10
7/1
11/15
Douglas
Colo.
339
204
272
-40%
33%
-20%
3/10
7/1
11/15
Jefferson
Colo.
1258
640
804
-49%
26%
-36%
3/10
7/1
11/15
Pueblo
Colo.
643
389
446
-40%
15%
-31%
3/10
7/1
11/15
Alachua
Fla.
729
664
736
-9%
11%
1%
3/10
7/1
11/14
Broward
Fla.
1706
1576
1658
-8%
5%
-3%
3/10
7/1
11/15
Clay
Fla.
418
437
448
5%
3%
7%
3/10
7/1
11/15
DeSoto
Fla.
147
162
164
10%
1%
12%
3/10
7/3
11/15
Flagler
Fla.
203
184
182
-9%
-1%
-10%
3/10
7/1
11/15
Lake
Fla.
18
7
17
-61%
143%
-6%
3/10
7/1
11/15
Monroe
Fla.
510
388
429
-24%
11%
-16%
3/10
7/1
11/15
Nassau
Fla.
236
177
224
-25%
27%
-5%
3/10
7/1
11/15
Okeechobee
Fla.
256
248
282
-3%
14%
10%
3/10
7/1
11/15
Sarasota
Fla.
866
775
899
-11%
16%
4%
3/10
7/1
11/15
St. Lucie
Fla.
1303
1219
1305
-6%
7%
0%
3/10
7/1
11/15
Walton
Fla.
435
411
444
-6%
8%
2%
3/10
7/1
11/15
Bartow
Ga.
671
519
610
-23%
18%
-9%
3/10
7/1
11/15
Berrien
Ga.
96
73
94
-24%
29%
-2%
3/10
7/1
11/15
Brantley
Ga.
122
124
95
2%
-23%
-22%
3/10
7/1
11/15
Bulloch
Ga.
343
251
309
-27%
23%
-10%
3/10
7/1
11/15
Burke
Ga.
106
94
112
-11%
19%
6%
3/10
7/1
11/15
Camden
Ga.
112
120
130
7%
8%
16%
3/10
7/1
11/15
Carroll
Ga.
441
286
358
-35%
25%
-19%
3/10
7/1
11/15
Catoosa
Ga.
228
131
233
-43%
78%
2%
3/10
7/1
11/15
Columbia
Ga.
276
175
204
-37%
17%
-26%
3/10
7/1
11/15
Coweta
Ga.
412
266
346
-35%
30%
-16%
3/10
7/1
11/15
Decatur
Ga.
116
113
152
-3%
35%
31%
3/10
7/1
11/15
Dodge
Ga.
123
121
126
-2%
4%
2%
3/10
7/1
11/15
Dougherty
Ga.
579
409
548
-29%
34%
-5%
3/10
7/1
11/15
Douglas
Ga.
681
339
564
-50%
66%
-17%
3/10
7/1
11/15
Effingham
Ga.
236
149
176
-37%
18%
-25%
3/10
7/1
11/15
Elbert
Ga.
95
54
66
-43%
22%
-31%
3/10
7/1
11/15
Fayette
Ga.
205
129
185
-37%
43%
-10%
3/10
7/1
11/15
Floyd
Ga.
639
464
547
-27%
18%
-14%
3/10
7/1
11/15
Gordon
Ga.
290
239
260
-18%
9%
-10%
3/10
7/1
11/15
Habersham
Ga.
162
110
133
-32%
21%
-18%
3/10
7/1
11/15
Haralson
Ga.
184
111
164
-40%
48%
-11%
3/10
7/1
11/15
Jackson
Ga.
143
110
160
-23%
45%
12%
3/10
7/1
11/15
Lamar
Ga.
58
39
57
-33%
46%
-2%
3/10
7/2
11/15
Laurens
Ga.
337
271
294
-20%
8%
-13%
3/10
7/1
11/15
Liberty
Ga.
209
171
210
-18%
23%
0%
3/10
7/1
11/15
McDuffie
Ga.
92
92
78
0%
-15%
-15%
3/10
7/1
10/22
Monroe
Ga.
128
97
140
-24%
44%
9%
3/10
7/1
11/15
Oconee
Ga.
27
17
26
-37%
53%
-4%
3/10
7/1
10/13
Pickens
Ga.
77
80
74
4%
-8%
-4%
3/10
7/1
10/12
Polk
Ga.
179
155
159
-13%
3%
-11%
3/10
7/1
11/15
Rabun
Ga.
108
58
86
-46%
48%
-20%
3/10
7/1
11/15
Richmond
Ga.
1021
884
1000
-13%
13%
-2%
3/10
7/1
11/15
Spalding
Ga.
386
260
350
-33%
35%
-9%
3/10
7/1
11/15
Sumter
Ga.
157
127
157
-19%
24%
0%
3/10
7/1
11/15
Tattnall
Ga.
87
36
79
-59%
119%
-9%
3/10
7/1
11/15
Turner
Ga.
67
65
62
-3%
-5%
-7%
3/10
7/1
11/15
Union
Ga.
49
32
55
-35%
72%
12%
3/10
7/1
11/15
Upson
Ga.
103
58
114
-44%
97%
11%
3/10
7/1
11/15
Ware
Ga.
419
341
388
-19%
14%
-7%
3/10
7/1
11/15
Washington
Ga.
78
74
97
-5%
31%
24%
3/10
7/1
11/15
Whitfield
Ga.
484
350
403
-28%
15%
-17%
3/10
7/1
11/15
Worth
Ga.
69
83
75
20%
-10%
9%
3/10
7/1
11/15
Buena Vista
Iowa
22
7
14
-68%
100%
-36%
3/10
7/1
11/15
Cerro Gordo
Iowa
68
36
55
-47%
53%
-19%
3/10
7/1
11/15
Clinton
Iowa
59
35
63
-41%
80%
7%
3/10
7/1
11/15
Dallas
Iowa
27
30
44
11%
47%
63%
3/10
7/1
11/15
Dickinson
Iowa
13
5
4
-62%
-20%
-69%
3/10
7/1
11/15
Hardin
Iowa
84
75
56
-11%
-25%
-33%
3/10
7/1
11/15
Ida
Iowa
7
1
2
-86%
100%
-71%
3/10
7/1
11/15
Lyon
Iowa
14
10
11
-29%
10%
-21%
3/10
7/1
11/15
Plymouth
Iowa
41
28
34
-32%
21%
-17%
3/10
7/1
11/15
Polk
Iowa
885
520
747
-41%
44%
-16%
3/10
7/1
11/15
Scott
Iowa
454
239
304
-47%
27%
-33%
3/10
7/1
11/15
Story
Iowa
70
26
60
-63%
131%
-14%
3/10
7/1
11/15
Worth
Iowa
8
2
3
-75%
50%
-63%
3/10
7/1
11/15
Blaine
Idaho
64
46
22
-28%
-52%
-66%
3/10
7/1
11/15
Bonner
Idaho
151
128
134
-15%
5%
-11%
3/10
7/1
11/15
Bonneville
Idaho
392
266
250
-32%
-6%
-36%
3/10
7/1
11/15
Canyon
Idaho
445
378
351
-15%
-7%
-21%
3/10
7/1
11/15
Nez Perce
Idaho
128
84
82
-34%
-2%
-36%
3/10
7/1
11/15
Power
Idaho
14
9
10
-36%
11%
-29%
3/10
7/1
11/15
Washington
Idaho
40
35
31
-13%
-11%
-23%
3/10
7/1
11/15
Douglas
Ill.
24
32
17
33%
-47%
-29%
3/10
7/1
8/19
Kendall
Ill.
156
137
151
-12%
10%
-3%
3/10
7/1
11/15
Macon
Ill.
300
256
283
-15%
11%
-6%
3/10
7/1
11/15
Moultrie
Ill.
24
28
34
17%
21%
42%
3/10
7/1
11/15
Randolph
Ill.
25
22
31
-12%
41%
24%
3/10
7/1
11/15
Will
Ill.
687
601
641
-13%
7%
-7%
3/10
7/1
11/15
Woodford
Ill.
52
54
70
4%
30%
35%
3/10
7/1
11/15
Clinton
Ind.
151
119
158
-21%
33%
5%
3/10
7/1
11/15
Dearborn
Ind.
233
239
284
3%
19%
22%
3/10
7/1
11/15
Hamilton
Ind.
294
208
299
-29%
44%
2%
3/10
7/1
11/15
Hendricks
Ind.
265
195
239
-26%
23%
-10%
3/10
7/1
9/28
Jackson
Ind.
249
168
202
-33%
20%
-19%
3/10
7/1
11/15
Perry
Ind.
66
46
72
-30%
57%
9%
3/10
7/1
10/12
Starke
Ind.
119
92
96
-23%
4%
-19%
3/10
7/1
10/12
Tippecanoe
Ind.
508
397
472
-22%
19%
-7%
3/10
7/1
11/15
Brown
Kan.
12
11
28
-8%
155%
133%
3/10
7/1
11/15
Chase
Kan.
132
87
83
-34%
-5%
-37%
3/10
8/24*
11/15
Cherokee
Kan.
81
42
82
-48%
95%
1%
3/10
7/1
11/15
Coffey
Kan.
28
20
26
-29%
30%
-7%
3/10
7/1
11/15
Crawford
Kan.
74
51
74
-31%
45%
0%
3/10
7/1
11/15
Dickinson
Kan.
20
15
11
-25%
-27%
-45%
3/10
7/1
11/15
Doniphan
Kan.
9
6
5
-33%
-17%
-44%
3/10
7/1
11/15
Finney
Kan.
95
77
57
-19%
-26%
-40%
3/10
7/1
11/15
Geary
Kan.
100
75
94
-25%
25%
-6%
3/10
7/1
11/13
Jackson
Kan.
82
53
69
-35%
30%
-16%
3/10
7/1
11/15
Jefferson
Kan.
28
29
18
4%
-38%
-36%
3/10
7/1
11/15
Pratt
Kan.
22
12
13
-45%
8%
-41%
3/10
7/1
11/15
Rooks
Kan.
18
9
7
-50%
-22%
-61%
3/10
7/1
11/15
Shawnee
Kan.
540
400
450
-26%
13%
-17%
3/10
7/1
11/15
Sherman
Kan.
18
24
26
33%
8%
44%
3/10
7/1
11/15
Sumner
Kan.
142
41
101
-71%
146%
-29%
3/10
7/1
11/15
Thomas
Kan.
14
10
12
-29%
20%
-14%
3/10
7/1
11/15
Trego
Kan.
11
6
9
-45%
50%
-18%
3/10
7/1
11/15
Wabaunsee
Kan.
9
6
8
-33%
33%
-11%
3/10
7/1
11/15
Woodson
Kan.
9
8
12
-11%
50%
33%
3/10
7/1
11/15
Allen
Ky.
80
40
41
-50%
3%
-49%
3/10
7/1
11/15
Bell
Ky.
117
93
132
-21%
42%
13%
3/10
7/1
9/28
Boone
Ky.
453
372
492
-18%
32%
9%
3/10
7/1
11/15
Breckinridge
Ky.
211
132
181
-37%
37%
-14%
3/10
7/1
9/28
Campbell
Ky.
588
474
477
-19%
1%
-19%
3/10
7/1
9/28
Carter
Ky.
210
129
180
-39%
40%
-14%
3/10
7/1
10/12
Christian
Ky.
768
522
613
-32%
17%
-20%
3/10
7/1
11/15
Clark
Ky.
303
141
154
-53%
9%
-49%
3/10
7/1
10/12
Daviess
Ky.
717
496
606
-31%
22%
-15%
3/10
7/1
9/28
Franklin
Ky.
287
199
189
-31%
-5%
-34%
3/10
7/1
10/12
Graves
Ky.
182
143
150
-21%
5%
-18%
3/10
7/1
11/15
Harlan
Ky.
220
168
180
-24%
7%
-18%
3/10
7/1
10/12
Hart
Ky.
190
135
155
-29%
15%
-18%
3/10
7/1
10/12
Jackson
Ky.
128
81
78
-37%
-4%
-39%
3/10
7/1
10/12
Jessamine
Ky.
142
84
80
-41%
-5%
-44%
3/10
7/1
10/12
Larue
Ky.
143
87
129
-39%
48%
-10%
3/10
7/1
10/12
Letcher
Ky.
108
87
95
-19%
9%
-12%
3/10
7/1
11/15
Lewis
Ky.
69
49
47
-29%
-4%
-32%
3/10
7/1
10/12
Mason
Ky.
184
103
128
-44%
24%
-30%
3/10
7/1
10/12
Nelson
Ky.
116
97
49
-16%
-49%
-58%
3/10
7/1
10/12
Pike
Ky.
443
320
342
-28%
7%
-23%
3/10
7/1
9/28
Pulaski
Ky.
351
227
285
-35%
26%
-19%
3/10
7/1
9/28
Rockcastle
Ky.
102
59
63
-42%
7%
-38%
3/10
7/1
10/12
Rowan
Ky.
321
231
266
-28%
15%
-17%
3/10
7/1
10/13
Russell
Ky.
116
99
91
-15%
-8%
-22%
3/10
7/1
9/28
Taylor
Ky.
239
145
172
-39%
19%
-28%
3/10
7/1
9/28
Todd
Ky.
135
84
88
-38%
5%
-35%
3/10
7/1
11/15
Union
Ky.
72
45
18
-38%
-60%
-75%
3/10
7/1
8/14
Wayne
Ky.
193
125
124
-35%
-1%
-36%
3/10
7/1
10/12
Allen
La.
102
64
58
-37%
-9%
-43%
3/10
7/1
11/15
Assumption
La.
101
89
102
-12%
15%
1%
3/10
7/1
11/15
Avoyelles
La.
424
328
320
-23%
-2%
-25%
3/10
7/1
11/15
Beauregard
La.
161
137
174
-15%
27%
8%
3/10
7/1
11/15
Bienville
La.
41
27
26
-34%
-4%
-37%
3/10
7/1
11/15
Bogalusa City
La.
18
10
13
-44%
30%
-28%
3/10
7/1
11/15
Caldwell
La.
610
504
588
-17%
17%
-4%
3/10
7/1
11/15
Cameron
La.
27
19
12
-30%
-37%
-56%
3/10
7/1
11/15
Catahoula
La.
72
49
52
-32%
6%
-28%
3/10
7/1
11/15
Claiborne
La.
575
463
437
-19%
-6%
-24%
3/10
7/1
11/15
EaSt. Feliciana
La.
244
216
239
-11%
11%
-2%
3/10
7/1
11/15
Evangeline
La.
74
57
66
-23%
16%
-11%
3/10
7/1
11/15
Franklin
La.
815
688
804
-16%
17%
-1%
3/10
7/1
11/15
Hammond City
La.
14
11
7
-21%
-36%
-50%
3/10
7/1
11/15
Iberia
La.
403
325
360
-19%
11%
-11%
3/10
7/1
11/15
Iberville
La.
106
111
105
5%
-5%
-1%
3/10
7/1
11/15
Jackson
La.
131
115
138
-12%
20%
5%
3/10
7/1
11/15
Jefferson Davis
La.
159
72
123
-55%
71%
-23%
3/10
7/1
11/15
Lafayette
La.
990
528
549
-47%
4%
-45%
3/10
7/1
11/15
Lafourche
La.
458
313
322
-32%
3%
-30%
3/10
7/1
11/15
LaSalle
La.
73
58
82
-21%
41%
12%
3/10
7/1
11/15
Lincoln
La.
246
233
232
-5%
0%
-6%
3/10
7/1
9/13
Madison
La.
35
38
66
9%
74%
89%
3/10
7/1
11/15
Morehouse
La.
464
505
475
9%
-6%
2%
3/10
7/1
11/15
Oakdale
La.
1
1
1
0%
0%
0%
3/10
7/1
11/15
Ouachita
La.
1134
991
1089
-13%
10%
-4%
3/10
7/1
11/15
Pointe Coupee
La.
98
72
67
-27%
-7%
-32%
3/10
7/1
11/15
Red River
La.
64
54
48
-16%
-11%
-25%
3/10
7/1
11/15
Richland
La.
751
583
676
-22%
16%
-10%
3/10
7/1
11/15
Sabine
La.
203
163
157
-20%
-4%
-23%
3/10
7/1
11/15
Shreveport
La.
63
12
28
-81%
133%
-56%
3/10
7/1
11/15
St. Charles
La.
458
416
433
-9%
4%
-5%
3/10
7/1
11/15
St. James
La.
68
40
49
-41%
23%
-28%
3/10
7/1
11/15
St. John
La.
146
125
95
-14%
-24%
-35%
3/10
7/1
11/15
St. Mary
La.
223
169
170
-24%
1%
-24%
3/10
7/1
11/15
Sulphur
La.
11
16
12
45%
-25%
9%
3/10
7/1
11/15
Tangipahoa
La.
572
449
523
-22%
16%
-9%
3/10
7/1
11/15
Tensas
La.
18
18
23
0%
28%
28%
3/10
7/1
11/15
Terrebonne
La.
645
490
573
-24%
17%
-11%
3/10
7/1
11/15
Vermilion
La.
146
129
153
-12%
19%
5%
3/10
7/1
11/15
Vernon
La.
131
100
135
-24%
35%
3%
3/10
7/1
11/15
Ville Platte
La.
16
7
13
-56%
86%
-19%
3/10
7/1
11/15
Washington
La.
163
139
190
-15%
37%
17%
3/10
7/1
11/15
Webster
La.
627
546
635
-13%
16%
1%
3/10
7/1
11/15
WeSt. Baton Rouge
La.
320
249
249
-22%
0%
-22%
3/10
7/1
11/15
WeSt. Feliciana
La.
25
14
129
-44%
821%
416%
3/10
7/1
11/15
Winnfield
La.
24
22
29
-8%
32%
21%
3/10
7/1
11/15
Worcester
Mass.
766
487
556
-36%
14%
-27%
3/10
7/1
11/14
Allegany
Md.
189
138
151
-27%
9%
-20%
3/10
7/1
11/15
Garrett
Md.
9
7
10
-22%
43%
11%
3/10
7/1
8/18
Prince Georges
Md.
884
726
944
-18%
30%
7%
3/10
7/1
11/15
Cumberland
Maine
349
283
329
-19%
16%
-6%
3/10
7/1
11/15
Delta
Mich.
125
105
111
-16%
6%
-11%
3/10
7/1
11/15
Midland
Mich.
101
53
68
-48%
28%
-33%
3/10
7/1
10/12
Wayne
Mich.
2086
2129
2802
2%
32%
34%
3/10
7/1
11/15
Beltrami
Minn.
113
86
88
-24%
2%
-22%
3/10
7/1
11/15
Blue Earth
Minn.
114
65
76
-43%
17%
-33%
3/10
7/1
11/15
Brown
Minn.
18
16
18
-11%
13%
0%
3/10
7/1
10/12
Carlton
Minn.
33
15
27
-55%
80%
-18%
3/10
7/1
11/15
Chisago
Minn.
61
23
39
-62%
70%
-36%
3/10
7/1
11/15
Clay
Minn.
117
61
89
-48%
46%
-24%
3/10
7/1
11/15
Clearwater
Minn.
17
11
8
-35%
-27%
-53%
3/10
7/1
11/15
Crow Wing
Minn.
155
98
95
-37%
-3%
-39%
3/10
7/1
11/15
Fillmore
Minn.
7
9
8
29%
-11%
14%
3/10
7/1
11/15
Hubbard
Minn.
63
30
50
-52%
67%
-21%
3/10
7/1
11/15
Isanti
Minn.
57
28
43
-51%
54%
-25%
3/10
7/1
11/15
Kanabec
Minn.
45
18
14
-60%
-22%
-69%
3/10
7/1
11/15
Kandiyohi
Minn.
91
66
62
-27%
-6%
-32%
3/10
7/1
11/15
Lac Qui Parle
Minn.
4
4
3
0%
-25%
-25%
3/10
7/1
11/15
Le Sueur
Minn.
23
9
11
-61%
22%
-52%
3/10
7/1
11/15
McLeod
Minn.
36
18
25
-50%
39%
-31%
3/10
7/1
11/15
Mille Lacs
Minn.
79
44
40
-44%
-9%
-49%
3/10
7/1
11/15
Morrison
Minn.
31
18
22
-42%
22%
-29%
3/10
7/1
11/15
Mower
Minn.
79
46
51
-42%
11%
-35%
3/10
7/1
11/13
Nicollet
Minn.
26
12
12
-54%
0%
-54%
3/10
7/1
11/15
Pennington
Minn.
34
29
39
-15%
34%
15%
3/10
7/1
11/15
Pipestone
Minn.
14
8
8
-43%
0%
-43%
3/10
8/18*
11/15
Redwood
Minn.
12
14
7
17%
-50%
-42%
3/10
7/1
11/15
Renville
Minn.
39
14
21
-64%
50%
-46%
3/10
7/1
11/15
Roseau
Minn.
21
11
8
-48%
-27%
-62%
3/10
7/1
11/15
Scott
Minn.
140
58
89
-59%
53%
-36%
3/10
7/1
11/15
Sherburne
Minn.
307
261
250
-15%
-4%
-19%
3/10
7/1
11/15
Sibley
Minn.
9
1
8
-89%
700%
-11%
3/10
7/1
11/15
Swift
Minn.
4
3
3
-25%
0%
-25%
3/10
7/1
11/15
Todd
Minn.
21
7
27
-67%
286%
29%
3/10
7/1
11/15
Wilkin
Minn.
9
3
6
-67%
100%
-33%
3/10
7/1
11/15
Winona
Minn.
30
17
28
-43%
65%
-7%
3/10
7/1
11/15
Wright
Minn.
182
98
98
-46%
0%
-46%
3/10
7/1
11/2
Yellow Medicine
Minn.
15
8
16
-47%
100%
7%
3/10
7/1
11/15
Barry
Mo.
45
46
57
2%
24%
27%
3/10
7/1
11/15
Bates
Mo.
31
22
8
-29%
-64%
-74%
3/10
7/1
10/12
Benton
Mo.
35
18
36
-49%
100%
3%
3/10
7/1
11/15
Bollinger
Mo.
19
13
17
-32%
31%
-11%
3/10
7/1
10/12
Boone
Mo.
252
198
237
-21%
20%
-6%
3/10
7/1
11/15
Buchanan
Mo.
217
149
207
-31%
39%
-5%
3/10
7/1
11/15
Cape Girardeau
Mo.
148
160
219
8%
37%
48%
3/10
8/18*
11/15
Christian
Mo.
101
66
81
-35%
23%
-20%
3/10
7/1
10/12
Clay
Mo.
300
213
221
-29%
4%
-26%
3/10
7/1
11/15
Jackson
Mo.
839
688
800
-18%
16%
-5%
3/10
7/1
11/15
Jasper
Mo.
200
168
165
-16%
-2%
-18%
3/10
7/3
11/15
Johnson
Mo.
202
75
129
-63%
72%
-36%
3/10
7/1
11/15
Joplin
Mo.
56
36
31
-36%
-14%
-45%
3/10
7/1
11/15
Lawrence
Mo.
77
71
73
-8%
3%
-5%
3/10
7/1
11/15
Lewis
Mo.
8
7
12
-13%
71%
50%
3/10
7/1
11/15
Marion
Mo.
79
57
70
-28%
23%
-11%
3/10
7/1
11/15
McDonald
Mo.
34
41
29
21%
-29%
-15%
3/10
7/1
10/12
Morgan
Mo.
79
59
115
-25%
95%
46%
3/10
7/1
11/15
Nodaway
Mo.
12
11
10
-8%
-9%
-17%
3/10
7/1
11/15
Saline
Mo.
57
43
52
-25%
21%
-9%
3/10
7/1
10/12
Stone
Mo.
65
69
63
6%
-9%
-3%
3/10
7/1
11/15
Adams
Miss.
76
82
73
8%
-11%
-4%
3/10
7/1
11/15
Clay
Miss.
68
51
60
-25%
18%
-12%
3/10
7/1
10/26
Hancock
Miss.
203
196
205
-3%
5%
1%
3/10
7/1
10/12
Jackson
Miss.
338
357
370
6%
4%
9%
3/10
7/1
11/15
Jasper
Miss.
30
23
23
-23%
0%
-23%
3/10
7/1
11/15
Kemper
Miss.
380
371
369
-2%
-1%
-3%
3/10
7/1
11/15
Lamar
Miss.
106
84
93
-21%
11%
-12%
3/10
7/1
10/12
Lee
Miss.
194
198
228
2%
15%
18%
3/10
7/1
11/15
Sunflower
Miss.
49
44
41
-10%
-7%
-16%
3/10
7/1
11/12
Tunica
Miss.
27
24
21
-11%
-13%
-22%
3/10
7/1
11/15
Broadwater
Mont.
47
35
39
-26%
11%
-17%
3/10
7/1
11/15
Chouteau
Mont.
11
18
10
64%
-44%
-9%
3/10
7/25
9/8
Glacier
Mont.
8
10
6
25%
-40%
-25%
3/10
7/1
10/22
Lewis and Clark
Mont.
102
104
99
2%
-5%
-3%
3/10
7/1
11/15
Ravalli
Mont.
41
38
40
-7%
5%
-2%
3/10
7/1
11/15
Rosebud
Mont.
11
10
12
-9%
20%
9%
3/10
7/7
11/15
Valley
Mont.
40
26
24
-35%
-8%
-40%
3/10
7/2
11/15
Alamance
N.C.
361
220
263
-39%
20%
-27%
3/10
7/1
11/15
Anson
N.C.
49
50
53
2%
6%
8%
3/10
7/1
11/6
Brunswick
N.C.
244
163
228
-33%
40%
-7%
3/10
7/1
11/15
Buncombe
N.C.
504
347
400
-31%
15%
-21%
3/10
7/1
10/14
Burke
N.C.
133
126
149
-5%
18%
12%
3/10
7/1
11/15
Cabarrus
N.C.
323
192
193
-41%
1%
-40%
3/10
7/1
11/15
Carteret
N.C.
165
100
149
-39%
49%
-10%
3/10
7/1
11/15
Catawba
N.C.
302
224
273
-26%
22%
-10%
3/10
7/1
11/15
Chatham
N.C.
1749
1205
1350
-31%
12%
-23%
3/10
7/1
11/15
Clay
N.C.
314
209
215
-33%
3%
-32%
3/10
7/1
9/28
Cleveland
N.C.
324
184
248
-43%
35%
-23%
3/10
7/1
11/15
Davidson
N.C.
340
210
246
-38%
17%
-28%
3/10
7/1
11/15
Guilford
N.C.
1051
772
741
-27%
-4%
-29%
3/10
7/1
11/15
Lee
N.C.
119
96
127
-19%
32%
7%
3/10
7/1
11/15
Lincoln
N.C.
148
63
123
-57%
95%
-17%
3/10
7/1
11/15
Moore
N.C.
138
100
130
-28%
30%
-6%
3/10
7/1
11/15
New Hanover
N.C.
444
353
465
-20%
32%
5%
3/10
7/1
11/15
Pender
N.C.
88
66
84
-25%
27%
-5%
3/10
7/1
11/15
Randolph
N.C.
255
193
215
-24%
11%
-16%
3/10
7/1
11/15
Richmond
N.C.
114
75
104
-34%
39%
-9%
3/10
7/1
11/15
Rowan
N.C.
341
223
277
-35%
24%
-19%
3/10
7/1
11/15
Sampson
N.C.
253
167
211
-34%
26%
-17%
3/10
7/2
11/15
Stanly
N.C.
156
98
129
-37%
32%
-17%
3/10
7/1
11/12
Transylvania
N.C.
77
45
40
-42%
-11%
-48%
3/10
7/1
11/15
Wake
N.C.
1246
1054
1173
-15%
11%
-6%
3/10
7/1
11/15
Washington
N.C.
459
305
290
-34%
-5%
-37%
3/10
7/1
11/15
Stutsman
N.D.
47
35
41
-26%
17%
-13%
3/10
7/1
11/15
Williams
N.D.
90
102
96
13%
-6%
7%
3/10
7/1
11/15
Hall
Neb.
275
198
257
-28%
30%
-7%
3/10
7/1
11/15
Lancaster
Neb.
625
451
587
-28%
30%
-6%
3/10
7/1
11/15
Lincoln
Neb.
117
116
118
-1%
2%
1%
3/10
7/1
11/15
Bergen
N.J.
618
283
312
-54%
10%
-50%
3/10
7/1
11/15
Burlington
N.J.
375
257
367
-31%
43%
-2%
3/10
7/1
11/15
Cumberland
N.J.
337
246
308
-27%
25%
-9%
3/10
7/1
11/15
Hunterdon
N.J.
46
28
31
-39%
11%
-33%
3/10
7/1
11/15
Ocean
N.J.
326
242
316
-26%
31%
-3%
3/10
7/1
11/15
Salem
N.J.
302
267
326
-12%
22%
8%
3/10
7/1
11/15
Sussex
N.J.
75
41
57
-45%
39%
-24%
3/10
7/1
11/15
Bernalillo
N.M.
1680
1315
1267
-22%
-4%
-25%
3/10
7/1
11/15
Curry
N.M.
183
160
168
-13%
5%
-8%
3/10
7/1
11/15
Hobbs
N.M.
11
7
13
-36%
86%
18%
3/10
7/1
11/15
Lea
N.M.
234
138
155
-41%
12%
-34%
3/10
7/1
11/15
San Juan
N.M.
508
312
468
-39%
50%
-8%
3/10
7/1
11/15
Monroe
N.Y.
766
587
708
-23%
21%
-8%
3/10
7/1
11/15
Adams
Ohio
42
35
45
-17%
29%
7%
3/10
7/1
10/12
Clinton
Ohio
80
52
56
-35%
8%
-30%
3/10
7/1
11/15
Delaware
Ohio
233
160
162
-31%
1%
-30%
3/10
7/1
11/15
Erie
Ohio
129
73
86
-43%
18%
-33%
3/10
7/1
11/15
Franklin
Ohio
2002
1503
1758
-25%
17%
-12%
3/10
7/1
11/15
Guernsey
Ohio
105
83
87
-21%
5%
-17%
3/10
7/1
11/15
Hamilton
Ohio
1499
1114
1409
-26%
26%
-6%
3/10
7/1
11/15
Knox
Ohio
96
75
75
-22%
0%
-22%
3/10
7/1
9/2
Morrow
Ohio
104
53
60
-49%
13%
-42%
3/10
7/1
11/15
Ottawa
Ohio
92
59
58
-36%
-2%
-37%
3/10
7/1
10/12
Pickaway
Ohio
119
110
90
-8%
-18%
-24%
3/10
7/1
11/15
Wood
Ohio
169
96
143
-43%
49%
-15%
3/10
7/1
11/15
Choctaw
Okla.
29
22
30
-24%
36%
3%
3/10
7/1
8/20
Comanche
Okla.
357
278
274
-22%
-1%
-23%
3/10
7/1
11/15
Creek
Okla.
225
149
204
-34%
37%
-9%
3/10
7/1
11/15
Garvin
Okla.
67
59
75
-12%
27%
12%
3/10
7/1
11/15
Mayes
Okla.
77
93
109
21%
17%
42%
3/10
7/1
11/15
McClain
Okla.
96
59
78
-39%
32%
-19%
3/10
7/1
11/15
Okmulgee
Okla.
174
192
180
10%
-6%
3%
3/10
7/1
11/15
Pawnee
Okla.
53
28
22
-47%
-21%
-58%
3/10
7/1
8/20
Pottawatomie
Okla.
203
184
202
-9%
10%
0%
3/10
7/1
11/15
Wagoner
Okla.
89
97
108
9%
11%
21%
3/10
7/1
11/15
Baker
Ore.
32
14
16
-56%
14%
-50%
3/10
7/1
11/15
Clackamas
Ore.
427
198
220
-54%
11%
-48%
3/10
7/1
11/15
Clatsop
Ore.
56
38
50
-32%
32%
-11%
3/10
7/1
11/15
Coos
Ore.
81
38
38
-53%
0%
-53%
3/10
7/1
11/15
Douglas
Ore.
200
123
107
-39%
-13%
-47%
3/10
7/1
11/15
Harney
Ore.
8
2
6
-75%
200%
-25%
3/10
7/1
11/15
Jackson
Ore.
321
251
270
-22%
8%
-16%
3/10
7/1
11/15
Jefferson
Ore.
60
46
76
-23%
65%
27%
3/10
7/1
11/15
Josephine
Ore.
185
145
80
-22%
-45%
-57%
3/10
7/1
11/15
Klamath
Ore.
136
73
100
-46%
37%
-26%
3/10
7/1
11/15
Lincoln
Ore.
161
73
99
-55%
36%
-39%
3/10
7/1
11/15
Marion
Ore.
420
274
282
-35%
3%
-33%
3/10
7/1
11/15
Marion Work Center
Ore.
90
33
49
-63%
48%
-46%
3/10
7/1
11/15
Multnomah
Ore.
1118
638
764
-43%
20%
-32%
3/10
7/1
11/15
Polk
Ore.
109
60
82
-45%
37%
-25%
3/10
7/1
11/15
Tillamook
Ore.
64
39
30
-39%
-23%
-53%
3/10
7/1
11/15
Wasco
Ore.
132
60
77
-55%
28%
-42%
3/10
7/1
11/9
Washington
Ore.
874
516
566
-41%
10%
-35%
3/10
7/1
11/15
Yamhill
Ore.
166
54
96
-67%
78%
-42%
3/10
7/1
11/15
Cumberland
Pa.
409
221
243
-46%
10%
-41%
3/10
7/1
11/15
Dauphin
Pa.
1110
864
993
-22%
15%
-11%
3/10
7/1
10/23
Lancaster
Pa.
786
669
682
-15%
2%
-13%
3/10
7/1
11/15
Anderson City
S.C.
95
80
82
-16%
3%
-14%
3/10
7/1
11/15
Berkeley
S.C.
438
292
356
-33%
22%
-19%
3/10
7/1
11/15
Cherokee
S.C.
357
259
333
-27%
29%
-7%
3/10
7/1
11/15
Darlington
S.C.
161
129
169
-20%
31%
5%
3/10
7/4
11/15
Kershaw
S.C.
80
86
101
8%
17%
26%
3/10
7/1
11/15
Laurens
S.C.
226
161
243
-29%
51%
8%
3/10
7/1
11/15
Lexington
S.C.
498
316
413
-37%
31%
-17%
3/10
7/1
11/15
Marion
S.C.
66
58
63
-12%
9%
-5%
3/10
7/1
11/15
Pickens
S.C.
302
224
188
-26%
-16%
-38%
3/10
7/1
11/15
Sumter
S.C.
309
266
272
-14%
2%
-12%
3/10
7/1
11/15
York Prison
S.C.
61
7
27
-89%
286%
-56%
3/10
7/1
11/15
Clay
S.D.
12
12
10
0%
-17%
-17%
3/10
7/1
11/15
Blount
Tenn.
534
458
488
-14%
7%
-9%
3/10
7/1
11/15
Giles
Tenn.
163
128
113
-21%
-12%
-31%
3/10
7/1
10/12
Macon
Tenn.
300
256
283
-15%
11%
-6%
3/10
7/1
11/15
Polk
Tenn.
181
154
172
-15%
12%
-5%
3/10
7/1
11/15
Roane
Tenn.
206
206
155
0%
-25%
-25%
3/10
7/1
11/15
Sevier
Tenn.
390
390
404
0%
4%
4%
3/10
7/1
11/15
Shelby
Tenn.
1807
1412
1311
-22%
-7%
-27%
3/10
7/1
11/15
Wayne
Tenn.
151
100
138
-34%
38%
-9%
3/10
7/1
11/15
Archer
Texas
26
27
30
4%
11%
15%
3/10
7/1
11/14
Bell
Texas
859
762
956
-11%
25%
11%
3/10
7/1
11/15
Brown
Texas
161
148
171
-8%
16%
6%
3/10
7/1
11/15
Calhoun
Texas
76
84
62
11%
-26%
-18%
3/10
7/1
11/15
Cochran
Texas
12
13
10
8%
-23%
-17%
3/10
7/1
11/15
Coleman
Texas
33
31
24
-6%
-23%
-27%
3/10
7/1
11/15
DeWitt
Texas
81
84
74
4%
-12%
-9%
3/10
7/1
11/15
Edwards
Texas
10
7
8
-30%
14%
-20%
3/10
7/1
11/15
Ellis
Texas
375
303
348
-19%
15%
-7%
3/10
7/1
11/14
Erath
Texas
79
68
72
-14%
6%
-9%
3/10
7/1
11/15
Galveston
Texas
991
839
944
-15%
13%
-5%
3/10
7/1
11/15
Hopkins
Texas
159
187
193
18%
3%
21%
3/10
7/1
11/15
Jim Wells
Texas
61
59
41
-3%
-31%
-33%
3/10
7/1
11/15
Lavaca
Texas
25
19
17
-24%
-11%
-32%
3/10
7/1
11/15
Liberty
Texas
240
271
227
13%
-16%
-5%
3/10
7/1
11/15
Lubbock
Texas
1242
1274
1238
3%
-3%
0%
3/10
7/1
11/15
Milam
Texas
137
138
138
1%
0%
1%
3/10
7/1
11/15
Parmer
Texas
28
22
19
-21%
-14%
-32%
3/10
7/1
11/15
Polk
Texas
184
158
198
-14%
25%
8%
3/10
7/2
11/15
Randall
Texas
413
382
401
-8%
5%
-3%
3/10
7/1
11/15
Robertson
Texas
43
32
50
-26%
56%
16%
3/10
7/1
11/15
Rockwall
Texas
220
219
240
0%
10%
9%
3/10
7/2
11/15
Shelby
Texas
37
39
40
5%
3%
8%
3/10
7/1
11/15
Terry
Texas
83
89
95
7%
7%
14%
3/10
7/1
11/15
Titus
Texas
133
92
97
-31%
5%
-27%
3/10
7/1
11/15
Tom Green
Texas
392
413
440
5%
7%
12%
3/10
7/1
11/15
Wharton
Texas
145
100
122
-31%
22%
-16%
3/10
7/1
11/15
Cache
Utah
183
108
127
-41%
18%
-31%
3/10
7/1
11/15
Salt Lake
Utah
2138
1166
1411
-45%
21%
-34%
3/10
7/1
11/15
Sanpete
Utah
13
14
15
8%
7%
15%
3/10
7/1
11/15
Tooele
Utah
214
169
168
-21%
-1%
-21%
3/10
7/1
11/15
Blue Ridge Bedford
Va.
100
78
108
-22%
38%
8%
3/10
7/1
9/28
Blue Ridge Halifax
Va.
179
172
174
-4%
1%
-3%
3/10
7/1
9/28
Blue Ridge Lynchburg
Va.
466
383
501
-18%
31%
8%
3/10
7/1
9/28
Danville
Va.
363
312
322
-14%
3%
-11%
3/10
7/1
11/15
Middle Peninsula
Va.
169
162
167
-4%
3%
-1%
3/10
7/25
11/15
Middle River
Va.
900
733
927
-19%
26%
3%
3/10
7/1
11/15
Norfolk
Va.
935
667
871
-29%
31%
-7%
3/10
7/1
11/15
Pamunkey
Va.
376
296
395
-21%
33%
5%
3/10
7/1
9/28
Riverside
Va.
1360
1144
1272
-16%
11%
-6%
3/10
7/1
11/15
Roanoke
Va.
173
145
167
-16%
15%
-3%
3/10
7/1
11/15
Virginia Beach
Va.
1509
1142
1260
-24%
10%
-17%
3/10
7/6
11/15
Virginia Peninsula
Va.
370
310
352
-16%
14%
-5%
3/10
7/1
9/28
Western Virginia
Va.
944
733
825
-22%
13%
-13%
3/10
7/1
11/15
Chelan
Wash.
190
143
169
-25%
18%
-11%
3/10
7/1
11/15
Clallam Forks
Wash.
17
10
10
-41%
0%
-41%
3/10
7/1
11/15
Clark
Wash.
655
402
427
-39%
6%
-35%
3/10
7/1
11/15
Columbia
Wash.
6
8
8
33%
0%
33%
3/10
7/1
11/15
Grays Harbor
Wash.
177
122
117
-31%
-4%
-34%
3/10
7/1
11/15
Grays Harbor Aberdeen
Wash.
20
16
9
-20%
-44%
-55%
3/10
7/1
11/15
Grays Harbor Hoquiam
Wash.
31
19
21
-39%
11%
-32%
3/10
7/1
11/15
Island
Wash.
68
45
58
-34%
29%
-15%
3/10
7/1
11/15
Jefferson
Wash.
28
20
19
-29%
-5%
-32%
3/10
7/1
11/15
King Issaquah
Wash.
56
23
41
-59%
78%
-27%
3/10
7/1
11/15
King Kirkland
Wash.
18
8
10
-56%
25%
-44%
3/10
7/1
10/15
Kitsap
Wash.
379
204
282
-46%
38%
-26%
3/10
7/1
11/15
Lewis
Wash.
191
144
182
-25%
26%
-5%
3/10
7/1
11/15
Okanogan
Wash.
159
86
94
-46%
9%
-41%
3/10
7/1
11/15
Skagit
Wash.
275
137
178
-50%
30%
-35%
3/10
7/1
11/15
Skamania
Wash.
24
23
28
-4%
22%
17%
3/10
7/1
11/15
Snohomish
Wash.
743
369
503
-50%
36%
-32%
3/10
7/1
11/15
Snohomish Lynnwood
Wash.
49
10
21
-80%
110%
-57%
3/10
7/1
11/15
Snohomish Marysville
Wash.
35
8
13
-77%
63%
-63%
3/10
7/1
11/15
Thurston Olympia
Wash.
22
7
15
-68%
114%
-32%
3/10
7/1
11/15
Walla Walla
Wash.
83
62
75
-25%
21%
-10%
3/10
7/1
11/15
Whatcom
Wash.
292
200
240
-32%
20%
-18%
3/10
7/1
11/15
Whitman
Wash.
31
17
27
-45%
59%
-13%
3/10
7/1
11/15
Yakima
Wash.
871
426
516
-51%
21%
-41%
3/10
7/1
11/15
Brown
Wis.
699
573
609
-18%
6%
-13%
3/10
7/1
11/15
Douglas
Wis.
156
107
168
-31%
57%
8%
3/10
7/1
11/15
Eau Claire
Wis.
273
186
175
-32%
-6%
-36%
3/10
7/1
11/15
Kenosha
Wis.
564
427
519
-24%
22%
-8%
3/10
7/1
11/15
La Crosse
Wis.
151
84
82
-44%
-2%
-46%
3/10
7/1
11/15
Lincoln
Wis.
104
69
60
-34%
-13%
-42%
3/10
7/1
11/15
Manitowoc
Wis.
204
171
158
-16%
-8%
-23%
3/10
7/1
11/15
Milwaukee
Wis.
1920
1493
1457
-22%
-2%
-24%
3/10
7/1
11/15
Ozaukee
Wis.
195
161
162
-17%
1%
-17%
3/10
7/1
11/15
Racine
Wis.
753
562
636
-25%
13%
-16%
3/10
7/1
11/15
Sawyer
Wis.
114
86
75
-25%
-13%
-34%
3/10
7/1
11/15
Sheboygan
Wis.
347
329
305
-5%
-7%
-12%
3/10
7/1
11/15
*Some jails did not have population data in the NYU database for July. We used the first August population available for those jails.
Appendix B: State prison populations during COVID-19
Prison populations for 21 states where monthly data was readily available for the period from January to November 2020.
Early this year — before COVID-19 began to tear through U.S. prisons — five people were killed in Mississippi state prisons over the course of one week. A civil rights lawyer reported in February that he was receiving 30 to 60 letters each week describing pervasive “beatings, stabbings, denial of medical care, and retaliation for grievances” in Florida state prisons. That same month, people incarcerated in the Souza-Baranowski Correctional Center in Massachusetts filed a lawsuit documenting allegations of abuse at the hands of correctional officers, including being tased, punched, and attacked by guard dogs.
While these horrific stories received some media coverage, the plague of violence behind bars is often overlooked and ignored. And when it does receive public attention, a discussion of the effects on those forced to witness this violence is almost always absent. Most people in prison want to return home to their families without incident, and without adding time to their sentences by participating in further violence. But during their incarceration, many people become unwilling witnesses to horrific and traumatizing violence, as brought to light in a February publication by Professors Meghan Novisky and Robert Peralta.
In their study — one of the first studies on this subject — Novisky and Peralta interview recently incarcerated people about their experiences with violence behind bars. They find that prisons have become “exposure points” for extreme violence that undermines rehabilitation, reentry, and mental and physical health. Because this is a qualitative (rather than quantitative) study based on extensive open-ended interviews, the results are not necessarily generalizable. However, studies like this provide insight into individual experiences and point to areas in need of further study.
Participants in Novisky and Peralta’s study reported witnessing frequent, brutal acts of violence, including stabbings, attacks with scalding substances, multi-person assaults, and murder. They also described the lingering effects of witnessing these traumatic events, including hypervigilance, anxiety, depression, and avoidance. These traumatic events affect health and social function in ways that are not so different from the aftereffects faced by survivors of direct violence and war.
Violence behind bars is inescapable and traumatizing
Violence in prison is unavoidable. By design, prisons offer few safe spaces where one can sneak away — and those that exist offer only a small measure of protection. Novisky and Peralta’s findings echo previous research revealing that incarcerated people often “feel safer” in their private spaces, such as cells, or in a supervised or structured public space, such as a chapel, rather than in public spaces like showers, reception, or on their unit. However, even inside their cells, people remain vulnerable to seeing or hearing violence and being victimized themselves.
Participants in Novisky and Peralta’s study discussed graphic, horrific acts of violence they had witnessed during their incarceration: stabbings, beatings, broken bones, and attacks with makeshift weapons. Some participants were even forced into direct, involuntary participation, by being required to clean up blood after an attack or murder. “I used so much bleach in that bathroom … I just couldn’t look,” one participant recalled. “I just kept pouring the bleach in it [the blood], and pouring the bleach in it, and then I would mop it.” As the authors succinctly state, “the burdens of violence are placed not just on the direct victims, but also on witnesses of violence.”
Responses to witnessed violence behind bars can result in post-traumatic stress symptoms, like anxiety, depression, avoidance, hypersensitivity, hypervigilance, suicidality, flashbacks, and difficulty with emotional regulation. Participants described experiencing flashbacks and being hypervigilant, even after release. One participant explained: “I’m trying to change my life and my thinking. But it [the violence] always pops up. I get flashbacks about it … just how the violence is. In a split second you can be cool. And then the next thing you know, there’s people getting stabbed or a fight breaks out over nothin’.”
The effects of witnessing violence are compounded by pre-existing mental health conditions, which are more common in prisons and jails than in the general public. As one participant in the Novisky and Peralta study put it, prison is no place to recover from past traumas or to manage ongoing mental health concerns: “I don’t think it [prison] made my PTSD worse, it just made the PTSD I already had trigger the symptoms.”
Violence in prison by the numbers
Prisons are inherently violent places where incarcerated people (often with their own histories of victimization and trauma) are frequently exposed to violence with disastrous consequences. Because there is no national survey of how many people witness violence behind bars, we compiled data from various Bureau of Justice Statistics surveys and a 2010 nationally representative study to show the prevalence of violence. The table below shows the most recent data available,1 although it is likely that many of these events are underreported.
Given the vast number of violent interactions occurring behind bars, as well as the close quarters and scarce privacy in correctional facilities, it is likely that most or all incarcerated people witness some kind of violence.
Estimating the prevalence of violence in prisons and jails
1,473 substantiated incidents in state and federal prisons and local jails in 2015
Prison is rarely the first place that incarcerated people experience violence
Even before entering a prison or jail, incarcerated people are more likely than those on the outside to have experiencedabuse and trauma. An extensive 2014 study found that 30% to 60% of men in state prisons had post-traumatic stress disorder (PTSD), compared to 3% to 6% of the general male population. According to the Bureau of Justice Statistics, 36.7% of women in state prisons experienced childhood abuse, compared to 12 to 17% of all adult women in the U.S. (although this research has not been updated since 1999). In fact, at least half of incarcerated women identify at least one traumatic event in their lives.
The effects of this earlier trauma carries over into people’s incarceration. Most people entering prison have experienced a “legacy of victimization” that puts them at higher risk for substance use, PTSD, depression, and criminal behavior. Irritability and aggressive behavior are also common responses to trauma, either acutely or as symptoms of PTSD. Rather than providing treatment or rehabilitation to disrupt the ongoing trauma that justice-involved people often face, existing research suggests our criminal justice system functions in a way that only perpetuates a cycle of violence. It is not surprising, then, that violence behind bars is common.
The relationship between past traumas and violence in prisons is further illuminated by a growing body of psychological research revealing that traumatic experiences (direct or indirect) increase the likelihood of mental illnesses. And we know that incarcerated people with a history of mental health problems are more likely to engage in physical or verbal assault against staff or other incarcerated people.2
Violence continues after release
The cycle of violence also continues after prison. An analysis of homicide victims in Baltimore, Maryland, found that the vast majority were justice system-involved, and one in four victims were on parole or probation at the time of their murder. Other research has found that formerly incarcerated Black adults are more likely than those with no history of incarceration to be beaten, mugged, raped, sexually assaulted, stalked, or to witness another person being seriously injured.
“Gladiator school” and ties to PTSD among veterans
While the effects of witnessing violence in correctional facilities have not been extensively studied, Novisky and Peralta’s findings are reminiscent of the significant body of psychological research about veterans, witnessed violence, and post-traumatic stress symptoms. And while a prison is not a war zone, the study participants themselves made these comparisons, describing prison as “going through a nuclear war,” “a jungle where only the strong survive,” “needing to go be ready to go to war constantly,” and “gladiator school.” Veterans, regardless of exposure to combat, are disproportionately at risk for post-traumatic stress disorder (PTSD) and can experience the same debilitating symptoms of PTSD that Novisky and Peralta document among recently incarcerated people.
In an article drawing attention to PTSD among our nation’s veterans, journalist Sebastian Junger describes his own experience with symptoms of PTSD after witnessing violence in Afghanistan. Importantly, he points out that only about 10 percent of our armed forces actually see combat, so the exorbitantly high rates of PTSD among returning servicemembers are not only caused by direct exposure to danger.3 The extensive psychological research on witnessed violence among veterans helps us better understand the risks of witnessing violence in other contexts; with the findings from Novisky and Peralta’s study, we can see a similar pattern of post-traumatic stress symptoms among incarcerated people who have witnessed acts of violence, even if they did not participate directly.
Witnessing violence — whether on a neighborhood block, prison unit, or a battlefield — carries serious ramifications. Exposure to this kind of stress can lead to poor health outcomes, such as cardiovascular disease, autoimmune disorders, and even certain cancers, which are compounded by inadequate correctional health care. Previous research has also shown that violent prison conditions — including direct victimization, the perception of a threatening prison environment, and hostile relationships with correctional officers — increase the likelihood of recidivism.
Moving forward
Novisky and Peralta’s study should be read as a call for more research — and concern — about prison violence. Future research should focus on the effects of witnessed violence on further marginalized populations, including women, youth, transgender people, people with disabilities, and people of color behind bars.
The researchers also recommend policy changes related to their findings. In prisons, they recommend trauma-informed training of correctional staff, assessing incarcerated people to identify those most at risk for victimization, and the expansion of correctional healthcare to include more robust mental health and trauma-informed services. They also recommend that providers in the reentry system receive training regarding the potential consequences of exposure to extreme violence behind bars, such as PTSD, distrust, and anxiety.
While it is important to address the immediate, serious needs of people dealing with the trauma of prison violence, the only way to truly minimize the harm is to limit exposure to the violent prison environment. That means, at a minimum, taking Novisky and Peralta’s final recommendation to heart: changing the “overall frequency with which incarceration is relied upon as a sanction.” We need to reduce lengthy sentences and divert more people from incarceration to more supportive interventions. It also means changing how we respond to violence, as we explore in more depth in our April 2020 report about sentences for violent offenses, Reforms without Results.
Vast research with veterans shows that trauma comes not only from direct violent victimization, but can also stem from witnessing violence. Research among non-incarcerated populations further shows that trauma and chronic stress have a number of adverse effects (link no longer available) on the human mind and body. And studies done behind bars show us that incarceration takes a toll on physical and mental health, and that accessing adequate care in prison is a challenge in and of itself. With all of these factors at play and with violence undermining what little rehabilitative effect the justice system hopes to have, we are stacking the cards against incarcerated people.
Footnotes
The forthcoming release of data from the Bureau of Justice Statistics Survey of Prison Inmates, 2016 (expected before 2021), will provide updated information. ↩
Based on data from 2011 to 2012, the Bureau of Justice Statistics reports that 14.2% of people who indicate experiencing serious psychological distress in the past 30 days are written up or charged with some kind of assault while incarcerated in state prison, compared to 11.6% of people with any history of mental health problems, and 4.1% of people with no indications of mental health problems. ↩
Studies of U.S. Iraq and Afghanistan war veterans suggest that the lifetime prevalence of PTSD for veterans is anywhere from 13.5% (which is more than double that of the general population) to 30%. ↩
The high cost of calling home from prisons and jails rightly gets a lot of attention in the press, but the industry’s practice of tacking on hidden fees is getting an increasing amount of attention from regulators and the savviest correctional facilities. These fees can be called by a variety of different names and can add up to significant costs to the families of people in prison. The problem got so bad that the companies were potentially making more from fees than from selling their product — phone calls.
The good news is that in 2015, the Federal Communications Commission prohibited or capped many of the fees that companies can charge consumers to open, have, fund or close an account. Most notably, the FCC capped the amount that can be charged for an “automated payment” i.e., to make a credit card deposit via the internet or a telephone keypad, at $3. At the time that the FCC capped those fees, some prison phone providers were charging fees as high as $9.50 to make a deposit, despite the fact that most companies in most other industries would be so thrilled to have customers pre-pay for services that they wouldn’t charge a fee at all.
The even better news is that some correctional systems are standing up for the low-income families that pay for these calls by pushing back against some of these unnecessary fees. We found that 15 state prison systems and at least one county jail1 have eliminated automated payment/deposit fees entirely.
State prison systems where there is no credit card fee to make deposits to prepaid accounts, October 2020
When consumers make pre-payment deposits to receive phone calls from these 15 state prison systems, consumers are charged only for the amount they are pre-paying for calls and not an additional payment fee. In October 2020, we attempted to make deposits to receive calls from each of the 50 states on the relevant providers’ websites, and discovered that in these 15 states, no additional fee was charged. In all other states, a $3 or similar payment fee was added to our proposed payment.
State Prison System
Vendor
Arizona
ICSolutions
California
GTL
Delaware
GTL
Indiana
GTL
Kansas
ICSolutions
Maryland
GTL
Michigan
GTL
Minnesota
GTL
Montana
ICSolutions
New Jersey
GTL
Ohio
GTL
Oregon
ICSolutions
South Carolina
GTL
Virginia
GTL
West Virginia
ICSolutions
Our survey looked only at the results of these contracts, but it seems clear from the available information that this outcome was the result of savvy negotiating by the facilities and not the generosity of the providers. How these contracts came to be is not always readily or publicly available, but we discovered enough evidence from the small number of readily available records to conclude that most or all of these 15 states sought out this result. For example, the original Requests for Proposals in Indiana and New Jersey said that the states would not accept bids that included deposit fees. And while we did not have access to Oregon’s original advertisement, the contract includes a prohibition on charging fees.
In sum, if states want to prohibit their phone companies from sticking their hands into consumer’s pockets with unnecessary fees, they can do so. Fifteen of them already have.
Footnotes
We did not attempt to survey deposit fees for calls from jails, but we know that at least one county jail contract — Dallas, Texas with Securus — prohibits deposit/pre-payment fees. ↩
As COVID-19 makes jails more dangerous than ever, people are looking closer at policies and programs that keep people out of jail and in their homes pretrial. Criminal justice reformers have long supported such measures, but opponents — including district attorneys, police departments, and the commercial bail industry — often claim pretrial reform puts community safety at risk. We put these claims to the test.
We found four states, as well as nine cities and counties, where there is existing data on public safety from before and after the adoption of pretrial reforms. All but one of these jurisdictions saw decreases or negligible increases in crime after implementing reforms. The one exception is New York State, where the reform law existed for just a few months before it was largely rolled back.
Below, we describe the reforms implemented in each of these 13 jurisdictions, the effect these reforms had on the pretrial population (if available), and the effect on public safety. We find that whether the jurisdictions eliminated money bail for some or all charges, began using a validated risk assessment tool, introduced services to remind people of upcoming court dates, or implemented some combination of these policies, the results were the same: Releasing people pretrial did not negatively impact public safety.
About 75% of people held by jails are legally innocent and awaiting trial, often because they are too poor to make bail. The overall jail population hasn’t always been so heavily dominated by pretrial detainees. As we’ve previously reported, increased arrests and a growing reliance on money bail over the last three decades have contributed to a significant rise in pretrial detention. And just three days of pretrial detention can have detrimental effects on an individual’s employment, housing, financial stability, and family wellbeing.
In this analysis, public safety is measured through the narrow lens of crime rates. But pretrial reforms promote other types of safety that are more difficult to measure, such as the safety of individuals who can remain at home instead of in a jail cell, children who are able to stay in their parents’ care, and community members who are spared the health risks (including, currently, the increased risk of COVID-19 exposure) that come from jail churn. (Furthermore, research has found that pretrial detention can actually increase the odds of future offending, which is clearly counterproductive from a crime rate-defined public safety standpoint.)
States and counties can and should build on these pretrial reforms. More progress can be made to continue reducing the number of people held pretrial, and address concerns such as racial bias inherent in pretrial risk assessment tools.1 But the data is clear: When it comes to public safety, these reforms are a step in the right direction.
State level reforms
New Jersey
Reform: In 2017, the New Jersey legislature passed a law implementing a risk-informed approach to pretrial release and virtually eliminated the use of cash bail.
Impact: The pretrial population decreased 50% from 2015 to 2018. By 2019, the overall jail population declined 45%.
Public safety: Violent crimes decreased by 16% from 2016 to 2018. There was a negligible difference in the number of people arrested while on pretrial release.
New Mexico
Reform: A 2016 voter-approved constitutional amendment prohibits judges from imposing bail amounts that people cannot afford, enables the release of many low-risk defendants without bond, and allows defendants to request relief from the requirement to post bond. (The Eighth Amendment already forbids excessive bail, but in practice, bail is regularly set at unaffordable levels in courts around the country.)
The impact of this reform on the jail population isn’t known.
Public safety: State-wide crime rates have declined since the reforms took effect in mid-2017. Furthermore, the safety rate, or the number of people released pretrial who are not charged with committing a new crime, increased from 74% to 83.2% after the reforms took effect.
Kentucky
Reform:Kentucky began using a validated pretrial risk assessment tool in 2013. In 2017, the state began allowing release of low-risk defendants without seeing a judge. In addition, a statewide pretrial services agency is required to make a release recommendation within 24 hours of arrest, and reminds people of upcoming court dates via automated texts and calls.
Impact: Judges have released more people on their own recognizance since 2013.
Public safety: The new criminal activity rate, which measures the rate at which people commit new crimes while awaiting trial, has not changed.
New York
Reform: A law that went into effect on January 1, 2020 eliminated the use of money bail and pretrial detention for most misdemeanors and many nonviolent felony cases. It also prohibited judges from considering public safety in their release decisions. But on April 3, the bail reform was amended, scaling back some of the changes. The new law, which took effect on July 1, expanded the list of charges for which bail can be set and gave judges more discretion in setting conditions of release.
Impact: The pretrial population declined 45% from April 2019 to March 2020. It is estimated that the April reform will result in an increase in the jail population, though it will likely still be lower than if no reforms were instituted at all.
Public safety: The NYPD asserted in March 2020 that the original bail reform measures were a “significant reason” for increased arrests in six crime categories from February 2019 to February 2020. However, researchers from Human Rights Watch argued that the reforms had not been in place long enough to pinpoint them as the driving force behind a rise in crime, and accused prosecutors, police, and bail bond agents of spreading “sensational stories and misleading statistics” to kill the reforms. Ultimately, New York’s short implementation period (just three months) and the absence of more complete data make the original reform’s impact on public safety unclear.
County and city level reforms
San Francisco, Calif.
Reform: Following collaboration between various judicial and public safety departments, the city has used a validated risk assessment tool since 2016. The San Francisco Pretrial Diversion Project also helps by offering alternatives to fines, dismissals of charges for “first time misdemeanor offenders” who complete treatment plans, and other forms of support for people navigating the system. In 2020, the District Attorney announced his office would no longer ask for cash bail.
Impact: The jail population has decreased by an average of 47%.
Public safety: The city’s new criminal activity rate, which measures the rate at which people commit new crimes while awaiting trial, is 10%. This puts it on par with Washington, D.C. which is often used as a model of pretrial reform success.
Washington, D.C.
Reform: The District’s Pretrial Services Agency has used a risk assessment tool since the agency was created by Congress in 1967, but their reforms go much further: Judges cannot set money bail that results in someone’s pretrial detention, there are limits to the amount of time people can spend in jail after their arrest, and the Pretrial Services Agency can connect people to employment, housing, and general social services resources.
Impact: Over 90% of arrestees are released without a financial bond.
Public safety: In FY 2019, 87% of people were not rearrested when released pretrial, and 99% weren’t rearrested for a violent crime.
Philadelphia, Pa.
Reform: In 2018, the District Attorney’s office stopped seeking money bail for some misdemeanors and nonviolent felonies, which made up the majority of all cases.
Impact: 90% of people facing misdemeanor charges were released without bail.
Public safety: Researchers found no difference in recidivism after the reforms.
Santa Clara County, Calif.
Reform: Santa Clara courts began using a validated risk assessment in 2012, and their pretrial services agency sends court date reminders to those released pretrial. In addition, community organizations such as a churches partner with individuals to remind them of court dates, provide transportation, and offer other assistance.
Impact: The number of people released without cash bail increased 45% after the reforms.
Public safety: 99% of people released were not rearrested.
Cook County, Ill.
Reform: As of 2017, judges must consider what people can afford when setting bail amounts.
Impact: The pretrial population has declined by about 16%. The percentage of people released without cash bail has doubled, and the increase was most dramatic for Black people.
Public safety: The number of overall crimes and violent crimes have continued to decline. The vast majority (link no longer available) (99.4%) of people who were released pretrial between October 2017 and December 2018 were not charged with any new violent offenses, and 83% remained charge-free while their cases were pending.
Yakima County, Wash.
Reform:Yakima County began using a validated risk assessment tool in 2015, at the recommendation of local judicial and public safety stakeholders. The county also implemented a pretrial services program that offers services like helping people obtain mental health or drug treatment and sending automatic court date reminders.
Impact: After one year, pretrial detention rates decreased from 47% to 27%, and racial disparities decreased.
Public safety: After pretrial services were instituted, the reoffense rate declined by 20%.
New Orleans, La.
Reform: A 2017 ordinance passed by the city council virtually eliminated money bail for people arrested on municipal offenses. Since then, the city has implemented a risk assessment tool and releases some low-risk arrestees without bail.
Impact: There was a 337% increase in the number of arrestees released without bail from 2009 to 2019 (1.9% to 8.3%).
Public safety: A subsequent crime analysis found that defendants released without paying bail were no more likely to be rearrested than those who paid bail.
Harris County, Texas
Reform: Since 2019, the majority of misdemeanor defendants automatically qualify for jail release on no-cash bonds.
Impact: While it’s unclear how much the pretrial population has decreased, the gap between the number of white and Black defendants who are detained pretrial has narrowed.
Public safety: Rearrest rates did not increase after the reforms were implemented.
Jefferson County, Colo.
Reform: Following a pretrial reform pilot study, Jefferson County eliminated its money bail schedule and began using a risk assessment tool in 2010.
The impact of this reform on the jail population isn’t known.
Public safety: People released without money bail were slightly less likely to have a new arrest or filing than those released on money bail.
Risk assessment tools base their results on existing criminal justice data, which in turn reflect years of biased policing and racial disparities. And ultimately, final decisions over detainment or release are made by people, who are subject to bias. Thus, while risk assessment tools give the impression of fairness, how fair they are in practice depends on the historical data they are based on, as well as the individual using the tools. ↩
During his campaign, President-elect Joe Biden released a long criminal justice reform platform with many laudable goals, and he is now in a position to begin translating those goals into policy. Of course, Biden won’t be president until late January, but his hard work of preparing to govern begins now.
As he prepares to take office, it’s important to be aware that the success of some of Biden’s criminal justice goals will hinge on how he implements them. It is all too easy for lawmakers to apply their energy for criminal justice reform in ways that will fail to make a dent or that actually reinforce mass incarceration. For example, Biden has proposed to:
Use the president’s clemency power to release people convicted of nonviolent drug crimes. A president willing to use clemency in a broad, sweeping manner could significantly reduce the federal prison population — without needing to consult Congress. But if President-elect Biden spends too much time reviewing clemency applications to avoid all possible risk, it’s unlikely that he will make a big impact. To understand why, recall President Obama’s record on clemency: Obama created a bold clemency initiative, but also created unnecessary layers of administrative oversight that led to most applications being denied or “set aside.” In 2016, we wrote about the more efficient ways that a president can use the power of clemency.
End all incarceration for drug use alone, and instead divert individuals to drug courts and treatment.Almost half of all people in federal prisons are there for drug offenses. But sending more people to drug courts — alternative courts that mix supervision with treatment — actually runs contrary to Biden’s goal of ending incarceration for drug use. Why? Because drug courts are still overseen by judges, who frequently throw people back in jail for failing to keep up with stringent requirements. Moreover, prison sentences for people convicted of drug possession are typically not long to begin with. As a result, the Drug Policy Alliance found, drug courts don’t significantly reduce incarceration. To end incarceration for drug use, focus on reducing drug possession enforcement overall – not just modifying the way drug users are punished.
“End the school to prison pipeline” by doubling the number of mental health professionals in schools. The school to prison pipeline is a national disgrace, but its roots go far beyond a shortage of counselors in schools. High arrest rates in schools have also been linked with high-stakes testing regimes, overworked teachers, and the presence of police officers in schools (often called “School Resource Officers”). In fact, schools that retain police officers on campus have arrest rates 5 times higher than schools without those officers. If a Biden administration funds new mental health programs to reduce arrests in schools, it should pair this funding with general support for cash-strapped classrooms — and a reduction in the number of School Resource Officers — to see real results.
Ensure that people leaving prison have housing, by expanding funding for halfway houses. Biden is correct to prioritize housing for formerly incarcerated people to increase health and safety. But halfway houses (as we explained in our guide to understanding them) are nothing like normal housing. They are a step down from prison, and most residents are required to be there as a condition of their parole. Halfway houses have staff who control when residents can come and go, and they are often run by the same private prison companies that Biden wants to purge from the criminal justice system. A halfway house is not a housing plan for someone leaving prison. To guarantee that formerly incarcerated people have stable homes, the government should invest in voluntary transitional housing, affordable housing in gentrifying areas, and permanent housing for the homeless.
Use grants to encourage states to place “non-violent” youth in community-based alternatives to prison. This proposal is one of a number of programs in Biden’s plan that applies to “non-violent offenders” only. But the labels “violent” and “non-violent” are nebulous ones, imposed by the criminal justice system, and conceal important parts of every individual’s personal history. Especially for youth, there is no need to means-test criminal justice reform by automatically excluding anyone with the “violent” label in their paperwork. As we explained in Youth Confinement: The Whole Pie, community-based consequences are more effective than incarceration for youth charged with all kinds of offenses, including violent ones.
As we keep our eyes on the Biden administration’s action on criminal justice reform, it’s important to remember that state prisons and local jails incarcerate vastly more people than federal facilities do. Local and state lawmakers don’t need to wait for the White House to make much-needed law and policy changes.
But the president still has a great deal of power — through executive orders, cabinet appointments, policy guidance, and the bully pulpit — to reshape the criminal justice system. In fact, the legacies of past presidents (such as the Clinton administration) are clearer than ever right now as crowded prisons enable COVID-19 to spread like wildfire. The Biden administration needs to get to work immediately to prevent more COVID-19 deaths behind bars, reduce the prison population, and help people leaving prison reenter society safely, and it’s important that the administration allocate its energy in the right places. There is no time to waste.
Yesterday, the Prison Policy Initiative filed comments before the California Public Utility Commission, calling for it to reduce the cost of calling home from California prisons and jails. Our comments included a comprehensive survey of the phone rates in each county.
In 2015, the Federal Communications Commission capped the cost of interstate calls at 21¢ per minute and is currently accepting comments on a proposal to lower that cap further still. However, FCC rate caps only apply to calls that cross states lines. But most calls do not cross state lines and those calls can cost far more — up to 90¢ per minute. For now, it is up to individual states to set rate caps for calls that stay within a state, so the California Public Utility Commission announced on October 19 that it was requesting comments on whether and how it should begin to regulate the industry.
Our comments review the cost of in-state calls from California facilities, as well as the too-high cost of video calls from California facilities. Our comments also addressed two other harmful practices: the prevalence of vendors bundling the phone and video services together into one complicated exploitative contract; and evidence showing that some vendors are charging more than the maximum $3 deposit fees authorized by the Federal Communications Commission.
The Utilities Commission will be accepting reply comments on November 19 and holding a pre-hearing conference on December 10. The Utilities Commission expects to have a proposed decision in the spring or summer of 2021. All of the documents filed in this rulemaking are available in Docket 20-10-002.
After skyrocketing for decades, overall incarceration rates have finally been on a slow decline since 2008. But a closer look at the data reveals a major exception: women. From 2009 to 2018, the number of women in city and county jails increased by 23% — a rise that effectively cancelled out more than 40% of the simultaneous 7.5% decrease in the men’s jail population. Meanwhile, reductions in state and federal prison populations have mostly affected men.
Women make up about 10% of people in jails and prisons. This means that patterns unique to women’s incarceration are easily obscured when we focus exclusively on the larger, overall incarcerated population. And when we overlook incarcerated women as a unique group, we also fail to address the additional challenges they face — including different health care needs and a greater likelihood of being a primary caretaker of young children — that make their growing numbers all the more alarming.
Since public health research shows that women are also affected in unique ways by the opioid crisis, we decided to see whether drug enforcement trends and substance abuse could be contributing to the rising number of women behind bars.
Increased drug arrests for women
Over the past 35 years, total arrests have risen 25% for women, while decreasing 33% for men. The increase among women is largely driven by drugs: During that period, drug related arrests increased nearly 216% for women, compared to 48% for men.1
Changes in policing in the 1990s contributed to this rise. The shift toward “broken windows” policing — or arresting people for minor offenses to supposedly prevent major crime — resulted in increased arrests for both men and women. But these policies particularly affected women, who are more likely to be involved in relatively minor drug crimes like simple possession than higher-level drug offenses.
More than a quarter of women in jail are held for drug crimes, which holds true for both convicted and unconvicted women. (Another 32 percent are held for property offenses, which are often linked to drug dependence and abuse.) In state prisons as well, the share of women incarcerated for drug and property crimes is greater than for their male counterparts.2
Where are the increases in women’s incarceration happening?
We looked to see if the increase in women’s incarceration was driven by rising arrests in rural areas, where the opioid crisis has hit particularly hard. But we found that women’s drug arrests were actually up in all county types over the last decade (by 25% in rural, 23% in urban, and 26% in suburban counties).
We also checked to see if there was a significant change in white women’s incarceration, since the current3 opioid epidemic is widely viewed as a white issue. Here we did find a relevant trend: Although prison and jail incarceration rates remain higher for Black and Hispanic women than for white women, incarceration is particularly on the rise among white women. From 2010 to 2019, overall prison incarceration rates for white women increased by 2% — while simultaneously decreasing for white men, Black men, Hispanic men, Black women, and Hispanic women. When we look back a decade further, which captures the beginning of the prescription drug crisis, the gender disparity in growth was even greater: Incarceration rates increased 38% for white women and 28% for Hispanic women from 2000 to 2010, compared to 2% and 3% for white and Hispanic men, respectively.
We also found that growth in women’s incarceration is primarily happening at the jail level. Unlike incarcerated men, incarcerated women are more likely to be in county or city jails than in state or federal prison. Most of these jailed women (60%) have not been convicted of a crime and are being held pretrial, often because they cannot afford bail. This isn’t surprising when you consider that most women held on bond have incomes that fall below the poverty line.
Trends in addiction among women
Knowing that drug arrests are on the rise, we looked to see if addiction is increasing among women, particularly opioid abuse. We found that although women and men are equally likely to develop a substance use disorder, 57% of those misusing opioids are women. The health toll is enormous: Women entered emergency rooms due to painkiller misuse an average of once every three minutes in 2010. Women’s rising opioid use is also reflected in an almost 600% increase in opioid overdose deaths from 1999 to 2016, compared to a 312% increase for men over the same time frame.
Researchers find that women may be more likely to receive opioid prescriptions due to a variety of factors: Women are more likely to seek out health care, go to the doctor regularly, and report experiencing pain, including chronic pain. Health care providers are also more likely to miss signs of addiction in women. (Disparate access to health care may also contribute to the rise in the incarceration of white women specifically. White people, who have higher rates of access to health insurance and physicians, were more likely to become addicted to prescription drugs like OxyContin than Black and Hispanic people.)
Drug dependence is also more pronounced among incarcerated women than incarcerated men. The most recent data available show that in 2009, around 70% of women serving sentences in prisons and jails struggled with drug abuse and dependence.4 And from 2004 to 2009, drug abuse and dependence among women in state prisons grew at twice the rate of men.
Additional challenges for incarcerated women
The growing number of incarcerated women face unique challenges that prisons and jails aren’t equipped to address. Incarcerated women are more likely to have a history of abuse, trauma, and mental health problems than incarcerated men.5 One-third of women in jails, for example, report experiencing serious psychological distress in the past 30 days. Women may also have additional health considerations, including pregnancy and reproductive health concerns.
Incarceration also has devastating effects on the families of incarcerated women. The majority of women in prisons and jails are mothers to minor children, and most incarcerated mothers were their children’s primary caretaker before their incarceration. The trauma of having a parent incarcerated leaves lasting negative impacts on children, and parental incarceration can cause financial instability for families.
For the sake of incarcerated women and their families, more needs to be done to understand the continued rise in women’s incarceration — and to make sure reforms impact women as well as men.
Footnotes
This data – and the data in the following graph – comes from the “Arrestee Sex” table from the FBI Crime Data Explorer. A previous version of this briefing stated total arrests had risen 15% for women, while decreasing 40% for men. The previous version of the following graph stated that drug related arrests increased nearly 190% for women and 34% for men. These percentages were based on more limited data presented in the FBI Crime Data Explorer tables entitled “Male Arrests By Age” and “Female Arrests By Age.” ↩
According to the BJS’ Prisoners Series reports from 2010 to 2019, the percentage of women in state prisons held on drug offenses remained at around 25% from 2009 to 2018, while an average of 27% were held for property offenses. Over the same time period, an average of 15% of men in state prisons were held for drug offenses and 17% for property offenses. ↩
In the 1970s, Black and Latinx communities experienced a heroin epidemic that did not receive the same amount of public awareness, sympathy, or resources as the current opioid epidemic. ↩
It’s possible the percentage of people incarcerated who are drug dependent is even higher, since the most recent data are from 2009, and heroin deaths didn’t start to rise until 2010. Additionally, the data exclude people detained in jails who are not convicted — which is about 75% of all people in jails. ↩
Across the country, local governments are building more jail space rather than working to reduce incarceration. New data shows that this trend is especially visible on tribal lands.
New data from the Bureau of Justice Statistics shows that the number of jails in Indian country has risen rapidly in recent years, from 68 jails in 2000 to 84 in 2018 (an increase of almost 24%). The number of people in Indian country jails has also grown — by over 1,000 people, or about 60% — even though the total number of people living in these areas has hardly changed.1
The rapid expansion of jail space in Indian country — that is, on tribal lands — holds with a recent nationwide trend. Jail populations have skyrocketed over the past three decades, leading first to overcrowding, and then to sheriffs announcing that they need to build more jails to alleviate overcrowding. But as we’ve previously discussed, while new jails might make existing jails less crowded in the short term, they can enable more incarceration in the long term. And in Indian country, it appears that they have.
As of 2018, 35% of Indian country jails are still holding more people than they were designed for. Compare this number to the 34% of Indian country jails that were above capacity in 2013: The share of overcrowded jails has actually increased slightly over the last several years.2 Only 55 jails in Indian country have populations consistently below their maximum capacity. As the number of jail beds has grown, so has the number of people incarcerated:
Building new jails in Indian country — as in the U.S. in general — enables the criminal justice system to lock up more people for longer periods of time. Most people in jails are being held pretrial; in other words, they are still legally innocent. Indeed, the share of people held pretrial in Indian country jails increased by 20 percentage points (an 80% increase) from 1999 to 2018, and the average length of stay in Indian country jails has doubled since 2002. (At the same time, the share of local jail populations outside of Indian country that are held pretrial has increased by 23% and the average length of stay has stretched by 33%.)
Counties can safely reduce pretrial detention by passing common-sense laws such as money bail reform. On the other hand, allowing pretrial detention to rise by building more jails means that more poor people are separated from their homes, families, and jobs before trial, and subjected to the dangerous conditions of incarceration.
Another startling finding from the report is that for 16% of people in Indian country jails, the most serious charge on which they are held is “public intoxication.” Only about 1.5% of people in U.S. jails in general are held on charges of drunkenness,3 so why is it so much more common in Indian country? Recent studies suggest that the frequency of alcohol consumption among Native Americans is not significantly higher than that of white people or the general population, contrary to stereotypes. But Indian country jails are locking up more people for public intoxication than they do for domestic violence, assault, sexual assault, burglary, larceny, drug offenses, and driving under the influence.
The answer likely has to do with local governments using police and jails to “fix” the problem of people being intoxicated in public, rather than expanding health care and housing to help them get their lives back on track. During the last three decades of jail expansion, jails — particularly in areas where social services are poorly funded — have frequently been used to house people with substance use disorders, including alcohol use, despite the fact that jails are unable to provide effective medical and mental health care to incarcerated people.
There are severe consequences to relying on jails to solve or hide social problems. We know that incarceration can be harmful to individuals and communities, but in Indian country, the effects are even more pronounced:
Health: Native people are more likely to suffer from chronic illnesses like liver disease, diabetes, and heart disease. Given that jails are not equipped to care for people with long-term illnesses, and that jails themselves are often dangerous environments (with poor food, sanitation, and temperature regulation), the chance that a Native person will die from their illness while incarcerated is serious.4
Unemployment: The unemployment rate of Native people in the U.S. is 2.7 percentage points higher than that of the general U.S. population. Incarceration — even without a conviction — hinders individuals’ ability to maintain or find employment, compounding the risk of unemployment among Native people.
Poverty: Native communities are some of the poorest in the U.S.: 1 in 3 Native Americans lives in poverty, and Native people have a poverty rate more than double that of the general population. And incarceration, as we’ve previously reported, only makes people poorer (by keeping them out of the workforce and saddling them with debts).
The recent jail-building boom in Indian country — and nationwide — reflects an unfortunate preference for using police and incarceration to solve problems that stem from inequality. As we explained in our 2019 report Does our county really need a bigger jail?, the right response to a burgeoning jail population is not to build more jail beds, but to reform local criminal justice systems and guarantee people the basic resources (including housing, healthcare, and employment) that they need to succeed.
Footnotes
In 2000, there were 944,000 American Indian or Alaskan Native people living in Indian country, according to the U.S. Census. In 2016-2018, there were 939,000, according to the U.S. Bureau of Labor Statistics. ↩
These calculations are based on the number of people held on the days in June 2018 and June 2013, respectively, on which the custody population of each facility was the largest, referred to as the “peak population.” ↩
This percentage is calculated from data used for our report Mass Incarceration: The Whole Pie 2020. 7,000 people are detained pretrial in jail on charges of “drunkenness/morals” (i.e. that is the most serious charge on which they are being held) and 4,000 are serving a sentence in jail for that same offense. Those 11,000 people make up only 1.5% of all 746,000 people in jails. ↩
Given that the death rate for American Indian and Alaska Native people is already 1.3 times higher than the general U.S. population, it is safe to assume that the rate for American Indian and Alaska Native people in jail is even higher than that of non-Native people in jails. ↩
Last week, the Bureau of Justice Statistics (BJS) released Prisoners in 2019, an annual report that breaks down the number of people incarcerated in state and federal prisons. Along with the report, BJS released a press release that paints a deceptively rosy picture of mass incarceration in the United States, which has been parroted by numerousmediaoutlets.
The press release boasts that the United States’ incarceration rate (419 per 100,000 people) is at its lowest since 1995, and that Black Americans are incarcerated at the lowest rate in 30 years. But this framing misses the bigger picture: 1.4 million Americans, who are disproportionately Black, are still incarcerated in state and federal prisons — meaning that the prison population is still five times larger than it was in 1975, before the “war on crime” really took hold and the number of people under correctional control exploded.1 Moreover, the slow pace of decarceration, especially for Black people and women, means we are looking at decades more of racially disparate mass incarceration in the United States unless lawmakers are willing to make much bolder changes.
If knowing the historical context is helpful, so is understanding that incarceration goes beyond federal and state prisons. 738,000 people, disproportionately Black, are locked up in local jails as of 2018. That year (the most recent for which BJS has published jail data), there were 4.7 times as many people incarcerated in local jails as there were in 1978. This increase is largely due to the rise in pretrial detention — the jailing of people who are still awaiting trial and haven’t been found guilty of a crime. (The newly-released prison data also obscures the fact that in some places, people who would have been held by state prisons in 1995 are now held by local jails, most notably in California, where this “realignment” was enacted in an effort to reduce prison overcrowding. There and in other states, changes to sentencing structures have shifted people out of prisons but into jails.)
Not only is our state and federal prison population still massive, the data in the report reveals that our pace of decarceration has been stubbornly slow. Recent criminal justice reforms have not been nearly enough to counteract the massive growth of our prison populations over the past forty years. At the current pace of decarceration:
It will be 2044 when the federal prison population returns to pre-mass incarceration levels — 24 years from now.
It will be 2088 when state prison populations return to pre-mass incarceration levels — 68 years from now.
It will take until 2039 for the Black incarceration rate to equal the 2019 white incarceration rate—19 years from now.
And it will be 2199 when the women’s prison population returns to pre-mass incarceration levels — 179 years from now.
Troublingly, the report shows that, at least in the year before the COVID-19 pandemic, some states were moving backwards. From 2018 to 2019, Indiana’s prison population increased by 1.1%, Alaska’s grew by 2.2%, Georgia’s rose 2.2%, Nebraska’s increased by 3.5%, North Dakota and Alabama both saw a 5.5% increase, and most disturbingly, Idaho’s prison population grew by 8.9%. Even worse, almost all of these states have prison systems that are already overcrowded, or close to their maximum capacity. Nebraska and Idaho’s prisons, for example, are holding 115% and 110%, respectively, of their highest capacity. (During the pandemic, at least some of these states have reduced their prison populations more significantly, but it remains to be seen whether these reductions will last.)
The federal prison system’s population is declining at a faster rate than state prisons, but the report shows that reforms are not going far enough. Nonviolent drug offenses are still a defining characteristic of our federal prison system. In 2019, 46% of people locked up in federal prisons were serving time for a drug offense, while only 8% were serving time for a violent offense.
The report also boasts that the Black incarceration rate is at its lowest since 1989. While Black Americans certainly are incarcerated at a lower rate than they have been at other points in U.S. history, it’s important to put these numbers in perspective. Black Americans are still incarcerated in state and federal prisons at five times the rate of white Americans. 1.1% of all Black Americans are incarcerated, compared to 0.2% of white Americans. The numbers are even more disturbing when we focus in on Black men. 1 in 50 Black men are incarcerated, including over 1 in 25 Black men between 25 and 44 years old.
Finally, the report reveals that the women’s prison population is declining at less than half the rate of the men’s population. Between 2009 and 2019, the men’s prison population declined by 1.2% per year, while the women’s population has declined by 0.5%, or 550 people per year. This is despite the fact that women’s state prison populations grew 834% over nearly 40 years — more than double the pace of the growth among men.
Prisoners in 2019 underscores the need for bold criminal justice reforms that dramatically reduce our prison populations and eliminate the pervasive racial disparities in our criminal justice system. And as we have noted before, states must pay special attention to women’s incarceration. Criminal justice reforms are even more urgent as COVID-19 sweeps through prisons and jails across the country, putting millions of lives at risk.
Sources and methodology
The late 1970s is an especially useful point of reference because it is right before the “war on crime” really took hold-incarceration rates had been relatively flat for decades and the number of people under correctional control had not yet exploded. In order to determine our baselines we used incarceration rates to ensure that 1975 was representative of historical trends. We used 1975 as our starting point for the prison population comparisons and projections.
The data for our state and federal prison projections came from the Bureau of Justice Statistics reports Prisoners in 2019 and Historical Statistics on Prisoners in State and Federal Institutions, Yearend 1925-86. For the federal prison population, we used 1975 as our baseline (24,131 people) and 2012 (197,050) as our peak value with an average yearly decline since the peak (6,100/year) to arrive at our projection of 2044. And for the population held in state prisons, we used 1975 as our baseline (216,462) and 2009 (1,365,688) as our peak value with an average yearly decline since the peak (15,168/year) to arrive at our projection of 2088.
For our racial disparity projection, we relied on data in Table 5 of Prisoners in 2019. We used the current incarceration rate for white individuals (214) as our baseline, and focused on the change in the incarceration rate for Black individuals between 2009 (the year prison populations peaked) and 2019, which declined by an average of 44.8 people per 100,000 per year. It would therefore take over 19 years for the Black incarceration rate to reach the 2019 white incarceration rate.
Finally, for women’s incarceration, we used 1975 as a baseline (with 8,675 women in state and federal prisons), and 2009 (113,485 women) as the peak with an average decline of 553 women per year to arrive at our projection of 2199.
Footnotes
In 1975, there were 216,462 people incarcerated in state prisons, and 24,131 people incarcerated in federal prisons for a combined population of 240,593. In 2019, there were 1,430,805 million people incarcerated in state and federal prisons. ↩
Prisons and jails are increasingly turning to electronic law libraries, moving from traditional book collections to databases accessed via shared kiosks or tablets. As of 2018, 88% of states have transitioned to electronic-only legal research tools. And in 2020, with a pandemic making in-person gatherings risky, even more prisons and jails may be moving to make services like law libraries digital.
These legal resources are essential for people behind bars, who have a constitutional right to access the courts, which includes the right to assistance in preparing and presenting a valid legal claim.1 When prisons provide this assistance in the form of an electronic law library, it’s important to understand how and why these systems are put in place.
In particular, there’s a world of difference between a prison system that designs a digital library with the needs of incarcerated people in mind, compared to one that digitizes its library primarily to cut the costs of running a physical library. To illustrate this difference, consider the two markedly different approaches that Oregon and South Dakota took when implementing an electronic law library system. While neither state’s program is perfect, both provide valuable lessons in the importance of system design.
Oregon
Oregon’s new program is unique because of the way it was designed. It originated with State Law Librarian Cathryn Bowie, who noticed a substantial number of requests for materials that already existed but which were inaccessible to those in the state prison system. While the resulting online system is expected to save the state money over time, it was designed with usability, not budget cutting, as the primary focus. Oregon’s system is an online legal research system provided by a vendor called Fastcase, with external links disabled. Oregon’s system for legal research has several key features:
Planning process. Planning for the Oregon project started with librarian Bowie visiting every prison in the state and asking incarcerated people about their research needs. Although the content is provided by a vendor (Fastcase), the system was designed in-house, as a collaboration between the state law library and the Department of Corrections.
Cross-agency. The research platform is available not only to adults in the state prison system, but also to patients in the Oregon State Hospital and juveniles confined in the Oregon Youth Authority.
Expansion plans. According to Bowie, the project’s designers are not resting on their laurels. Having established the basic functionality and security of the research platform, the designers are evaluating future enhancements (again, driven by user needs). For example, the research platform is now available on desktop computers in facility libraries, but project managers are working on ways to make the resource more readily available to people in segregation or who otherwise have difficulty accessing the library. Other features that could be in the works in the future include educational programs, an expanded catalogue of publications, and electronic court filing capabilities.
Ongoing training. Bowie continues to tour the state, training incarcerated people on the new electronic legal research system. Unlike South Dakota where training is conducted by a marketing employee of the contractor, Oregon’s training is conducted by the person who is in charge of the program: thus user feedback and suggestions can go straight to the program manager, without having to filter through layers of corporate bureaucracy.
No system is perfect, and surely, Oregon’s law library system has shortcomings. Still, the very fact that it is designed and managed with the specific needs of incarcerated users in mind is a step in the right direction.
South Dakota
On the other hand, South Dakota’s law library system design is largely a result of cost cutting efforts by prison administrators. Prior to 2017, South Dakota provided legal assistance to people in its state prison system via contract attorneys and paralegals who would visit facilities and provide one-on-one assistance to people who needed help. However, in October 2017, the state eliminated this system and replaced it with a computer research program provided by Lexis-Nexis. Users are expected to access this database via computer tablets issued by communications company Global Tel*Link (“GTL”).
The switch saved the state over $80,000 on its regular contracting, not to mention savings on other costs, like printed law books.2 Yet, the cost savings is only part of the story:
Technical failures. When the tablets were rolled out, many users reported persistent connection problems that prevented them from actually doing legal research. Managers eventually concluded that the system’s wireless signals could not travel through the thick reinforced concrete that was used in many facilities, something that apparently was not tested prior to the rollout of the new system.
Economic unfairness. Although people in South Dakota receive a tablet for free, woe be to those who experience malfunctions. GTL’s corporate representative did not even know if there was technical assistance for people whose tablets fail through no fault of their own. However, if an “investigation” determines that the user is responsible for damage, then they must pay $199 for a replacement. GTL buys the tablets for $80 each.
Technology instead of help. The Lexis app that runs on the GTL tablets is the same software that legal professionals use (Lexis Advance), with external links disabled. On the one hand, this is helpful since plenty of training materials for Lexis Advance already exist. On the other hand, it’s a vivid illustration of the folly of not providing regular in-person assistance to incarcerated people who need legal help. Law schools and law firms spend considerable resources training lawyers (or soon-to-be lawyers) how to navigate Lexis’s dense collection of information. It is willful indifference to simply give an app to a population of non-lawyers with below-average levels of formal education and unfamiliarity with technology, and expect them to perform legal research. Even GTL’s corporate representative admitted that the tablets are used by “individuals who, in many instances…have no familiarity with tablet technology.” Lexis did provide some on-site training when the program first started, but now only offers live training upon the DOC’s request, via a Missouri-based employee who is responsible for numerous states. It’s unclear whether the DOC regularly schedules such trainings, but it is clear that user education is an afterthought.
Lack of detailed planning. Incarcerated people sued South Dakota in 1998, alleging constitutional violations of their right to access the courts. When the state settled those lawsuits, it agreed to maintain specified legal resources at all state prisons. It would be logical that the new computerized research system would be designed to honor the state’s obligations under the settlement agreement, but Lexis-Nexis’s corporate representative testified that he was unaware of the settlement or its contents.
Conclusion
South Dakota and Oregon illustrate two radically different approaches states can take to updating their prison law libraries: Take the time to identify people’s needs, and then work collaboratively to continue to train users and modify the systems as necessary; or offload the burden of providing a law library onto a private company, who in turn throws a digital product at incarcerated people and wishes them the best. Unfortunately, by now, many other prison systems have likely taken South Dakota’s path. But with incarcerated people’s access to the courts on the line, states need to focus not on cost-cutting, but on usability.
A Note on Methodology
This piece was written using a combination of sources. The information on Oregon’s law library largely came from an interview on the radio show Think Out Loud with librarian Bowie and an interview by the author. For South Dakota, we drew on two depositions from a 2018 class action case, Brakeall v. Kaemingk. The information used in this briefing can be found in the deposition of Brian Peters at pages 20-35, and the deposition of Anders Ganten at pages 21-34.
In 2017, the South Dakota legal aid contract cost $137,400. Other costs, like paper law books and fees for alternate lawyers when the on-site attorney had a conflict, added up to over $276,000 in 2017. The Lexis-Nexis research program cost only $54,720 in the first year. ↩