Data provided by Big Local News. Data from the National Health Security Preparedness Index. The overall index is useful for examining a state’s readiness in dealing with any number of issues. There also are specific metrics that directly relate to states’ abilities to respond to the Coronavirus pandemic. With that in mind, we have pulled out and processed key metrics -- from preparedness for surge testing to evaluating how many people in each state have access to paid time off. Our goal is to make it easier for journalists to access and analyze for their reporting. For more information, please start with the NHSPI_READ_ME file. Questions? Contact biglocalnews@stanford.edu.

Data source: Big Local News · About: big-local-datasette

306 rows sorted by Per_lhd_emgncy_coord

View and edit SQL

Suggested facets: Year

Link rowid Year Data Dates State Per_lhd_emgncy_coord ▼
67 2018 2013 & 2016 HI  
68 2017 2013 & 2016 HI  
69 2016 2013 & 2016 HI  
70 2015 2013 & 2016 HI  
71 2014 2013 & 2016 HI  
72 2013 2013 & 2016 HI  
235 2018 2013 & 2016 RI  
236 2017 2013 & 2016 RI  
237 2016 2013 & 2016 RI  
238 2015 2013 & 2016 RI  
239 2014 2013 & 2016 RI  
240 2013 2013 & 2016 RI  
1 2018 2013 & 2016 AK 100.0
2 2017 2013 & 2016 AK 100.0
3 2016 2013 & 2016 AK 100.0
22 2015 2013 & 2016 AZ 100.0
23 2014 2013 & 2016 AZ 100.0
24 2013 2013 & 2016 AZ 100.0
43 2018 2013 & 2016 DC 100.0
44 2017 2013 & 2016 DC 100.0
45 2016 2013 & 2016 DC 100.0
46 2015 2013 & 2016 DC 100.0
47 2014 2013 & 2016 DC 100.0
48 2013 2013 & 2016 DC 100.0
55 2018 2013 & 2016 FL 100.0
56 2017 2013 & 2016 FL 100.0
57 2016 2013 & 2016 FL 100.0
61 2018 2013 & 2016 GA 100.0
62 2017 2013 & 2016 GA 100.0
63 2016 2013 & 2016 GA 100.0
79 2018 2013 & 2016 ID 100.0
80 2017 2013 & 2016 ID 100.0
81 2016 2013 & 2016 ID 100.0
82 2015 2013 & 2016 ID 100.0
83 2014 2013 & 2016 ID 100.0
84 2013 2013 & 2016 ID 100.0
109 2018 2013 & 2016 LA 100.0
110 2017 2013 & 2016 LA 100.0
111 2016 2013 & 2016 LA 100.0
121 2018 2013 & 2016 MD 100.0
122 2017 2013 & 2016 MD 100.0
123 2016 2013 & 2016 MD 100.0
124 2015 2013 & 2016 MD 100.0
125 2014 2013 & 2016 MD 100.0
126 2013 2013 & 2016 MD 100.0
130 2015 2013 & 2016 ME 100.0
131 2014 2013 & 2016 ME 100.0
132 2013 2013 & 2016 ME 100.0
133 2018 2013 & 2016 MI 100.0
134 2017 2013 & 2016 MI 100.0
135 2016 2013 & 2016 MI 100.0
136 2015 2013 & 2016 MI 100.0
137 2014 2013 & 2016 MI 100.0
138 2013 2013 & 2016 MI 100.0
151 2018 2013 & 2016 MS 100.0
152 2017 2013 & 2016 MS 100.0
153 2016 2013 & 2016 MS 100.0
175 2018 2013 & 2016 NE 100.0
176 2017 2013 & 2016 NE 100.0
177 2016 2013 & 2016 NE 100.0
178 2015 2013 & 2016 NE 100.0
179 2014 2013 & 2016 NE 100.0
180 2013 2013 & 2016 NE 100.0
184 2015 2013 & 2016 NH 100.0
185 2014 2013 & 2016 NH 100.0
186 2013 2013 & 2016 NH 100.0
196 2015 2013 & 2016 NM 100.0
197 2014 2013 & 2016 NM 100.0
198 2013 2013 & 2016 NM 100.0
202 2015 2013 & 2016 NV 100.0
203 2014 2013 & 2016 NV 100.0
204 2013 2013 & 2016 NV 100.0
220 2015 2013 & 2016 OK 100.0
221 2014 2013 & 2016 OK 100.0
222 2013 2013 & 2016 OK 100.0
226 2015 2013 & 2016 OR 100.0
227 2014 2013 & 2016 OR 100.0
228 2013 2013 & 2016 OR 100.0
232 2015 2013 & 2016 PA 100.0
233 2014 2013 & 2016 PA 100.0
234 2013 2013 & 2016 PA 100.0
241 2018 2013 & 2016 SC 100.0
242 2017 2013 & 2016 SC 100.0
243 2016 2013 & 2016 SC 100.0
244 2015 2013 & 2016 SC 100.0
245 2014 2013 & 2016 SC 100.0
246 2013 2013 & 2016 SC 100.0
265 2018 2013 & 2016 UT 100.0
266 2017 2013 & 2016 UT 100.0
267 2016 2013 & 2016 UT 100.0
268 2015 2013 & 2016 UT 100.0
269 2014 2013 & 2016 UT 100.0
270 2013 2013 & 2016 UT 100.0
271 2018 2013 & 2016 VA 100.0
272 2017 2013 & 2016 VA 100.0
273 2016 2013 & 2016 VA 100.0
274 2015 2013 & 2016 VA 100.0
275 2014 2013 & 2016 VA 100.0
276 2013 2013 & 2016 VA 100.0
280 2015 2013 & 2016 VT 100.0

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CREATE TABLE [M107_per_lhd_emgncy_coord] (
   [Year] INTEGER,
   [Data Dates] TEXT,
   [State] TEXT,
   [Per_lhd_emgncy_coord] TEXT
);