Fatal opioid-detected overdoses in Region 4, 2018-2022
Race
2018
2019
2020
2021
2022
Sex
2018
2019
2020
2021
2022
Race and sex
2018
2019
2020
2021
2022
Age
2018
2019
2020
2021
2022
Day of week
2018
2019
2020
2021
2022
Month
2018
2019
2020
2021
2022
Town of OD
2018
2019
2020
2021
2022
Injury town v. residence town
2018
## [1] "There were 47 instances where a person's residence town didn't match up with their injury town, out of 203 ODs in 2018 in region 4. This is 0.231527 of all ODs in this year."## [1] "Here's a more in-depth look at out-of-town ODs in specific towns:"## Town name Out-of-town ODs Total ODs Proportion of out-of-town ODs
## 1 Hartford 33 89 0.37
## 2 West Hartford 3 12 0.25
## 3 East Hartford 3 20 0.15
## 4 Windsor 1 7 0.14
## 5 Bloomfield 0 3 0
## 6 Enfield 2 15 0.132019
## [1] "There were 41 instances where a person's residence town didn't match up with their injury town, out of 217 ODs in 2019 in region 4. This is 0.188940. "## [1] "Here's a more in-depth look at out-of-town ODs in specific towns:"## Town name Out-of-town ODs Total ODs Proportion of out-of-town ODs
## 1 Hartford 21 108 0.19
## 2 West Hartford 0 4 0
## 3 East Hartford 2 23 0.09
## 4 Windsor 0 7 0
## 5 Bloomfield 0 2 0
## 6 Enfield 2 12 0.172020
## [1] "There were 52 instances where a person's residence town didn't match up with their injury town, out of 217 ODs in 2020 in region 4. This is 0.239631. "## [1] "Here's a more in-depth look at out-of-town ODs in specific towns:"## Town name Out-of-town ODs Total ODs Proportion of out-of-town ODs
## 1 Hartford 26 101 0.26
## 2 West Hartford 2 7 0.29
## 3 East Hartford 5 23 0.22
## 4 Windsor 4 6 0.67
## 5 Bloomfield 1 4 0.25
## 6 Enfield 4 14 0.292021
## [1] "There were 47 instances where a person's residence town didn't match up with their injury town, out of 234 ODs in 2021 in region 4. This is 0.200855. "## [1] "Here's a more in-depth look at out-of-town ODs in specific towns:"## Town name Out-of-town ODs Total ODs Proportion of out-of-town ODs
## 1 Hartford 27 124 0.22
## 2 West Hartford 2 5 0.4
## 3 East Hartford 6 22 0.27
## 4 Windsor 0 7 0
## 5 Bloomfield 0 0 NaN
## 6 Enfield 0 9 02022
## [1] "There were 42 instances where a person's residence town didn't match up with their injury town, out of 221 ODs in 2022 in region 4. This is 0.190045. "## [1] "Here's a more in-depth look at out-of-town ODs in specific towns:"## Town name Out-of-town ODs Total ODs Proportion of out-of-town ODs
## 1 Hartford 24 131 0.18
## 2 West Hartford 3 10 0.3
## 3 East Hartford 3 20 0.15
## 4 Windsor 3 5 0.6
## 5 Bloomfield 1 2 0.5
## 6 Enfield 1 6 0.17Injury location
2018
2019
2020
2021
2022
Are people dying in their own homes?
2018
## [1] "There were 125 people who OD'd in their own residence."## [1] "The proportion of decedents ODing in their own residence was 0.595238."## [1] "Out of everyone who OD'd in a residence, 0.791139 of people OD'd in their own residence."2019
## [1] "There were 140 people who OD'd in their own residence."## [1] "The proportion of decedents ODing in their own residence was 0.580913."## [1] "Out of everyone who OD'd in a residence, 0.782123 of people OD'd in their own residence."2020
## [1] "There were 133 people who OD'd in their own residence."## [1] "The proportion of decedents ODing in their own residence was 0.565957."## [1] "Out of everyone who OD'd in a residence, 0.715054 of people OD'd in their own residence."2021
## [1] "There were 160 people who OD'd in their own residence."## [1] "The proportion of decedents ODing in their own residence was 0.658436."## [1] "Out of everyone who OD'd in a residence, 0.837696 of people OD'd in their own residence."2022
## [1] "There were 152 people who OD'd in their own residence."## [1] "The proportion of decedents ODing in their own residence was 0.633333."## [1] "Out of everyone who OD'd in a residence, 0.817204 of people OD'd in their own residence."Most common substances
2018
## Rows: 5
## Columns: 32
## Groups: cocaine, combo..her.pharm.or.fent..OR.pharm.fent, heronly, pharmonly, fentonly, heroin, X6.mam, morphine, hermor_nocod, codeine, cod_w_no_hermor, di.H.codeine, hydromorphone, oxymorphone, hydrocodone, oxycodone, methadone, buprenorphine, fentanyl..4ANPP.too., Frankens, fent.or.frankens, tramadol, opioid.analogs..e.g...U47700., otherop, pharma_w_meth_no_fent.or.op.analogs.or.cod.or..other.op., pharma_nobupnometh, other, benzos, amphetamine, EtOH [4]
## $ cocaine <int> 1, 0, 1, 0, 0
## $ combo..her.pharm.or.fent..OR.pharm.fent <int> 0, 0, 0, 0, 0
## $ heronly <int> 0, 0, 0, 0, 0
## $ pharmonly <int> 0, 0, 0, 0, 0
## $ fentonly <int> 1, 1, 1, 1, 1
## $ heroin <int> 0, 0, 0, 0, 0
## $ X6.mam <int> 0, 0, 0, 0, 0
## $ morphine <int> 0, 0, 0, 0, 0
## $ hermor_nocod <int> 0, 0, 0, 0, 0
## $ codeine <int> 0, 0, 0, 0, 0
## $ cod_w_no_hermor <int> 0, 0, 0, 0, 0
## $ di.H.codeine <int> 0, 0, 0, 0, 0
## $ hydromorphone <int> 0, 0, 0, 0, 0
## $ oxymorphone <int> 0, 0, 0, 0, 0
## $ hydrocodone <int> 0, 0, 0, 0, 0
## $ oxycodone <int> 0, 0, 0, 0, 0
## $ methadone <int> 0, 0, 0, 0, 0
## $ buprenorphine <int> 0, 0, 0, 0, 0
## $ fentanyl..4ANPP.too. <int> 1, 1, 1, 1, 1
## $ Frankens <int> 0, 0, 0, 0, 0
## $ fent.or.frankens <int> 1, 1, 1, 1, 1
## $ tramadol <int> 0, 0, 0, 0, 0
## $ opioid.analogs..e.g...U47700. <int> 0, 0, 0, 0, 0
## $ otherop <int> 0, 0, 0, 0, 0
## $ pharma_w_meth_no_fent.or.op.analogs.or.cod.or..other.op. <int> 0, 0, 0, 0, 0
## $ pharma_nobupnometh <int> 0, 0, 0, 0, 0
## $ other <int> 0, 0, 1, 0, 1
## $ benzos <int> 0, 0, 1, 0, 0
## $ amphetamine <int> 0, 0, 0, 0, 0
## $ EtOH <int> 0, 0, 0, 0, 0
## $ THC <int> 0, 0, 0, 1, 0
## $ n <int> 17, 16, 8, 7,~The top 5 substance combinations for 2018 are:
- cocaine, fent only
- fent only
- cocaine, fent only, other, benzos
- fent only, weed
- fent only, other
2019
## Rows: 5
## Columns: 33
## Groups: xyla, combo, heronly, pharmonly, fentonly, Heroin, X6.mam, Morphine, hermor_nocod, Codeine, cod.w.no.hermor, di.H.codeine, Hydromorphone, oxymorphone, Hydrocodone, Oxycodone, Methadone, bup, fentanyl..4.ANPP.too., frankens, fent...frankens, tramadol, opioid.analogs..e.g...U47700., Other.Op, pharma.w.meth.bup.no.fent.or.other.op, pharma_nobupnometh, other, benzos, cocaine, amphetamine, EtOH [5]
## $ xyla <int> 0, 0, 0, 0, 0
## $ combo <int> 0, 0, 0, 0, 0
## $ heronly <int> 0, 0, 0, 0, 0
## $ pharmonly <int> 0, 0, 0, 0, 0
## $ fentonly <int> 1, 1, 1, 1, 1
## $ Heroin <int> 0, 0, 0, 0, 0
## $ X6.mam <int> 0, 0, 0, 0, 0
## $ Morphine <int> 0, 0, 0, 0, 0
## $ hermor_nocod <int> 0, 0, 0, 0, 0
## $ Codeine <int> 0, 0, 0, 0, 0
## $ cod.w.no.hermor <int> 0, 0, 0, 0, 0
## $ di.H.codeine <int> 0, 0, 0, 0, 0
## $ Hydromorphone <int> 0, 0, 0, 0, 0
## $ oxymorphone <int> 0, 0, 0, 0, 0
## $ Hydrocodone <int> 0, 0, 0, 0, 0
## $ Oxycodone <int> 0, 0, 0, 0, 0
## $ Methadone <int> 0, 0, 0, 0, 0
## $ bup <int> 0, 0, 0, 0, 0
## $ fentanyl..4.ANPP.too. <int> 1, 1, 1, 1, 1
## $ frankens <int> 0, 0, 0, 0, 0
## $ fent...frankens <int> 1, 1, 1, 1, 1
## $ tramadol <int> 0, 0, 0, 0, 0
## $ opioid.analogs..e.g...U47700. <int> 0, 0, 0, 0, 0
## $ Other.Op <int> 0, 0, 0, 0, 0
## $ pharma.w.meth.bup.no.fent.or.other.op <int> 0, 0, 0, 0, 0
## $ pharma_nobupnometh <int> 0, 0, 0, 0, 0
## $ other <int> 0, 0, 0, 0, 1
## $ benzos <int> 0, 0, 0, 0, 0
## $ cocaine <int> 1, 0, 0, 1, 1
## $ amphetamine <int> 0, 0, 0, 0, 0
## $ EtOH <int> 0, 0, 1, 1, 0
## $ THC <int> 0, 0, 0, 0, 0
## $ n <int> 21, 12, 9, 8, 8The top 5 substance combinations for 2019 are:
- fent only, cocaine
- fent only
- fent only, alcohol
- fent only, cocaine, alcohol
- fent only, cocaine, other
2020
## Rows: 5
## Columns: 32
## Groups: combo, heronly, pharmonly, fentonly, Heroin, X6.mam, Morphine, hermor_nocod, Codeine, cod.w.no.hermor, di.H.codeine, Hydromorphone, oxymorphone, Hydrocodone, Oxycodone, Methadone, bup, fentanyl..4.ANPP.too., frankens, fent...frankens, tramadol, opioid.analogs..e.g...U47700., Other.Op, pharma.w.meth.bup.no.fent.or.other.op, pharma_nobupnometh, other, benzos, cocaine, amphetamine, EtOH [4]
## $ combo <chr> "0", "0", "0", "0", "0"
## $ heronly <chr> "0", "0", "0", "0", "0"
## $ pharmonly <chr> "0", "0", "0", "0", "0"
## $ fentonly <chr> "1", "1", "1", "1", "1"
## $ Heroin <dbl> 0, 0, 0, 0, 0
## $ X6.mam <dbl> 0, 0, 0, 0, 0
## $ Morphine <dbl> 0, 0, 0, 0, 0
## $ hermor_nocod <dbl> 0, 0, 0, 0, 0
## $ Codeine <dbl> 0, 0, 0, 0, 0
## $ cod.w.no.hermor <dbl> 0, 0, 0, 0, 0
## $ di.H.codeine <dbl> 0, 0, 0, 0, 0
## $ Hydromorphone <dbl> 0, 0, 0, 0, 0
## $ oxymorphone <dbl> 0, 0, 0, 0, 0
## $ Hydrocodone <dbl> 0, 0, 0, 0, 0
## $ Oxycodone <dbl> 0, 0, 0, 0, 0
## $ Methadone <dbl> 0, 0, 0, 0, 0
## $ bup <dbl> 0, 0, 0, 0, 0
## $ fentanyl..4.ANPP.too. <dbl> 1, 1, 1, 1, 1
## $ frankens <dbl> 0, 0, 0, 0, 0
## $ fent...frankens <dbl> 1, 1, 1, 1, 1
## $ tramadol <dbl> 0, 0, 0, 0, 0
## $ opioid.analogs..e.g...U47700. <dbl> 0, 0, 0, 0, 0
## $ Other.Op <dbl> 0, 0, 0, 0, 0
## $ pharma.w.meth.bup.no.fent.or.other.op <dbl> 0, 0, 0, 0, 0
## $ pharma_nobupnometh <dbl> 0, 0, 0, 0, 0
## $ other <dbl> 0, 1, 0, 1, 1
## $ benzos <dbl> 0, 0, 0, 0, 0
## $ cocaine <dbl> 1, 1, 1, 1, 0
## $ amphetamine <dbl> 0, 0, 0, 0, 0
## $ EtOH <dbl> 0, 0, 0, 1, 0
## $ THC <dbl> 0, 0, 1, 0, 0
## $ n <int> 19, 17, 12, 11, 9The top 5 substance combinations for 2020 are:
- fent only, cocaine
- fent only, other, cocaine
- fent only, cocaine, weed
- fent only, other, cocaine, alcohol
- fent only, other
2021
## Rows: 5
## Columns: 32
## Groups: combo, her.only, pharm.only, fent.only, Heroin, X6.mam, Morphine, hermor_nocod, Codeine, cod.w.no.hermor, di.H.codeine, Hydromorphone, oxymorphone, Hydrocodone, Oxycodone, Methadone, bup, fentanyl..4.ANPP.despropionyl.fent.too., frankens, fent...frankens, tramadol, opioid.analogs.e.g.mitragynine, Other.Op, pharma.w.meth.bup.no.fent.or.other.op, pharma_nobupnometh, other, benzos, cocaine, amphetamine..including.eutylone., EtOH [5]
## $ combo <int> 0, 0, 0, 0, 0
## $ her.only <int> 0, 0, 0, 0, 0
## $ pharm.only <int> 0, 0, 0, 0, 0
## $ fent.only <int> 1, 1, 1, 1, 1
## $ Heroin <int> 0, 0, 0, 0, 0
## $ X6.mam <int> 0, 0, 0, 0, 0
## $ Morphine <int> 0, 0, 0, 0, 0
## $ hermor_nocod <int> 0, 0, 0, 0, 0
## $ Codeine <int> 0, 0, 0, 0, 0
## $ cod.w.no.hermor <int> 0, 0, 0, 0, 0
## $ di.H.codeine <int> 0, 0, 0, 0, 0
## $ Hydromorphone <int> 0, 0, 0, 0, 0
## $ oxymorphone <int> 0, 0, 0, 0, 0
## $ Hydrocodone <int> 0, 0, 0, 0, 0
## $ Oxycodone <int> 0, 0, 0, 0, 0
## $ Methadone <int> 0, 0, 0, 0, 0
## $ bup <int> 0, 0, 0, 0, 0
## $ fentanyl..4.ANPP.despropionyl.fent.too. <int> 1, 1, 1, 1, 1
## $ frankens <int> 0, 0, 0, 0, 0
## $ fent...frankens <int> 1, 1, 1, 1, 1
## $ tramadol <int> 0, 0, 0, 0, 0
## $ opioid.analogs.e.g.mitragynine <int> 0, 0, 0, 0, 0
## $ Other.Op <int> 0, 0, 0, 0, 0
## $ pharma.w.meth.bup.no.fent.or.other.op <int> 0, 0, 0, 0, 0
## $ pharma_nobupnometh <int> 0, 0, 0, 0, 0
## $ other <int> 1, 0, 0, 0, 1
## $ benzos <int> 0, 0, 0, 0, 0
## $ cocaine <int> 1, 1, 0, 1, 0
## $ amphetamine..including.eutylone. <int> 0, 0, 0, 0, 0
## $ EtOH <int> 0, 0, 1, 1, 0
## $ THC <int> 0, 0, 0, 0, 0
## $ n <int> 15, 13, 12, 12, 12The top 5 substance combinations for 2021 are:
- fent only, other, cocaine
- fent only, cocaine
- fent only, alcohol
- fent only, cocaine, alcohol
- fent only, other
2022
## Rows: 5
## Columns: 32
## Groups: combo, her.only, pharm.only, fent.only, Heroin, X6.mam, Morphine, hermor_nocod, Codeine, cod.w.no.hermor, di.H.codeine, Hydro.morphone, oxy.morphone, Hydro.codone, Oxy.codone, Methadone, bup, fentanyl..4.ANPP.despropionyl.fent.too., frankens, fent...frankens, tramadol, opioid.analogs.e.g.mitragynine, Other.Op, pharma.w.meth.bup.no.fent.or.other.op, pharma_nobupnometh, other, benzos, cocaine, amphetamine.including.eutylone.MDMA, EtOH [4]
## $ combo <int> 0, 0, 0, 0, 0
## $ her.only <int> 0, 0, 0, 0, 0
## $ pharm.only <int> 0, 0, 0, 0, 0
## $ fent.only <int> 1, 1, 1, 1, 1
## $ Heroin <int> 0, 0, 0, 0, 0
## $ X6.mam <int> 0, 0, 0, 0, 0
## $ Morphine <int> 0, 0, 0, 0, 0
## $ hermor_nocod <int> 0, 0, 0, 0, 0
## $ Codeine <int> 0, 0, 0, 0, 0
## $ cod.w.no.hermor <int> 0, 0, 0, 0, 0
## $ di.H.codeine <int> 0, 0, 0, 0, 0
## $ Hydro.morphone <int> 0, 0, 0, 0, 0
## $ oxy.morphone <int> 0, 0, 0, 0, 0
## $ Hydro.codone <int> 0, 0, 0, 0, 0
## $ Oxy.codone <int> 0, 0, 0, 0, 0
## $ Methadone <int> 0, 0, 0, 0, 0
## $ bup <int> 0, 0, 0, 0, 0
## $ fentanyl..4.ANPP.despropionyl.fent.too. <int> 1, 1, 1, 1, 1
## $ frankens <int> 0, 0, 0, 0, 0
## $ fent...frankens <int> 1, 1, 1, 1, 1
## $ tramadol <int> 0, 0, 0, 0, 0
## $ opioid.analogs.e.g.mitragynine <int> 0, 0, 0, 0, 0
## $ Other.Op <int> 0, 0, 0, 0, 0
## $ pharma.w.meth.bup.no.fent.or.other.op <int> 0, 0, 0, 0, 0
## $ pharma_nobupnometh <int> 0, 0, 0, 0, 0
## $ other <int> 1, 1, 0, 1, 0
## $ benzos <int> 0, 0, 0, 0, 0
## $ cocaine <int> 1, 0, 1, 0, 0
## $ amphetamine.including.eutylone.MDMA <int> 0, 0, 0, 0, 0
## $ EtOH <int> 0, 0, 0, 0, 0
## $ THC <int> 0, 0, 0, 1, 0
## $ n <int> 28, 14, 13, 13, 12The top 5 substance combinations for 2022 are:
- fent only, other, cocaine
- fent only, other
- fent only, cocaine
- fent only, other, weed
- fent only
How many people were using chronically?
I identify chronic users crudely – I look for entries where the words “chronic” [can sometimes indicate chronic pain, meaning opioid scripts], “Chronic”, “user”, “drug use”, “drug user”, “drug abuse”, “snort”, “snorts”, “drug abuse”, “addict”, “addicted”, “rehab”, “sober house”, “clean” or “abuse” pops up in either the notes field or immediate cause of death, because that generally means that the person had chronic drug use [based on my look at the data]
2018
## [1] "There were at least 65 people with known chronic use out of 210 decedents in 2018, which is 30.952381 percent of all decedents."2019
## [1] "There were at least 78 people with known chronic use out of 241 decedents in 2019, which is 32.365145 percent of all decedents."2020
## [1] "There were at least 113 people with known chronic use out of 235 decedents in 2020, which is 48.085106 percent of all decedents."2021
## [1] "There were at least 110 people with known chronic use out of 243 decedents in 2021, which is 45.267490 percent of all decedents."2022
## [1] "There were at least 119 people with known chronic use out of 240 decedents in 2022, which is 49.583333 percent of all decedents."Who did decedents live with?
Please note: this field and all fields explored below are only available up to 2020.
2018
2019
2020
% cases found in <24h and >=24h
2018
## [1] "There were 130 people found within 24 hours, which is 0.619048 of all decedents."## [1] "There were 48 people found in over 24 hours, which is 0.228571 of all decedents."2019
## [1] "There were 160 people found within 24 hours, which is 0.663900 of all decedents."## [1] "There were 51 people found in over 24 hours, which is 0.211618 of all decedents."2020
## [1] "There were 158 people found within 24 hours, which is 0.672340 of all decedents."## [1] "There were 45 people found in over 24 hours, which is 0.191489 of all decedents."Race of <24h and >=24h decedents
2018
Under 24h
Over 24h
2019
Under 24h
Over 24h
2020
Under 24h
Over 24h
Town of OD of <24h and >=24h decedents
2018
Under 24h
Over 24h
2019
Under 24h
Over 24h
2020
Under 24h
Over 24h
Injury location for <24h and >=24h
2018
Under 24h
Over 24h
2019
Under 24h
Over 24h
2020
Under 24h
Over 24h
