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Article

Housing Status and COVID-19 Prevention Recommendations among People Who Use Drugs

by
Izza Zaidi
*,
Ashly E. Jordan
,
Lauren Jessell
,
Leonardo Dominguez Gomez
,
Alex Harocopos
and
Michelle Nolan
Bureau of Alcohol and Drug Use Prevention, Care and Treatment, New York City Department of Health and Mental Hygiene, Queens, NY 11101, USA
*
Author to whom correspondence should be addressed.
COVID 2023, 3(10), 1612-1621; https://doi.org/10.3390/covid3100110
Submission received: 20 September 2023 / Revised: 5 October 2023 / Accepted: 9 October 2023 / Published: 17 October 2023
(This article belongs to the Special Issue COVID and Post-COVID: The Psychological and Social Impact of COVID-19)
Versions Notes

Abstract

:
Housing conditions can increase health risks for people who use opioids (PWUO). Little research documents the influence of housing on PWUO’s ability to practice disease prevention methods. This study examines associations between housing status of PWUO in NYC and their ability to practice COVID-19 prevention recommendations during the initial wave of the pandemic. Participants were recruited via convenience sampling and administered a survey. Eligibility required age ≥18 years, using opioids ≥3times in the prior 30 days, and accessing a health-related service in the prior year. Descriptive and bivariate statistics assessed relationships between housing and the ability to practice social distancing, access soap and running water or hand sanitizer (soap), and access face masks. Multivariable Poisson regression was used to examine relationships between housing and the potential to practice COVID-19 prevention recommendations. The 329 participants were grouped into stable housing (34.3%), unstable/shelter housing (31.9%), and street homeless (33.7%) categories. Street homeless PWUO were significantly less likely to have access to soap and face masks than those stably housed. There were no significant differences between PWUO experiencing unstable and stable housing. PWUO experiencing street homelessness may have had increased vulnerability to COVID-19. Providing low-threshold health-related resources and increasing linkages to housing opportunities could promote health of PWUO experiencing street homelessness during future emergencies.

1. Introduction

Housing is a well-established social determinant of health and previous research has demonstrated that stable, high-quality, and affordable housing promotes the health of individuals [1,2]. Housing conditions also influence the “risk environment”, that is, factors that interact to increase a person’s risk of adverse health outcomes, especially among people who use drugs (PWUD) [1,2,3,4]. Consequently, there was widespread concern that PWUD might not be able to practice some of the mitigation measures aimed at preventing the spread of COVID-19.
Additionally, across the United States, approximately 40 million people reported experiencing financial strain as a result of lost wages due to the COVID-19 pandemic [5], and the closure of non-essential businesses and subsequent widespread layoffs further contributed to increased housing instability and homelessness [6,7,8]. In New York City (NYC), the number of single adults living in shelters increased from 19,094 in February 2020 (before NYC reported its first COVID-19 case) to 20,790 in March 2021 (one year after the start of the COVID-19 pandemic) [9], and it is estimated that thousands more New Yorkers experienced street homelessness during this period [10]. Even prior to COVID-19, a high percentage of PWUD experienced housing instability, suggesting a lack of access to sanitation facilities and the potential of increased risk for disease transmission [11].
Research has also demonstrated the link between economic security and the ability to adopt COVID-19 prevention measures [12,13]. For instance, low-wage workers were less likely to be able to work remotely or in settings where physical distancing was possible [14]. Additionally, many low-wage workers lacked paid sick leave and as such were more likely to work alongside people who could not afford to stay home if sick with COVID-19 [8,12,14,15,16,17]. Literature shows adverse changes in how COVID-19 changed the way some PWUD used substances, how service closures especially impacted PWUD and increased their risk of adverse effects related to their substance use and described specific instance of the importance of housing among PWUD [18,19,20,21]. Research also shows that stigma against PWUD has an effect on support for policy related to resource allocation related to COVID-19 [22]. While one study explores how social distancing behaviors was associated with increased solitary drug use [23], no research documents the influence of housing on PWUD’s ability to practice disease prevention recommendations.
While the federal COVID-19 public health emergency declaration expired on 11 May 2023, there remain little data available about how housing status impacted the ability of PWUD to adopt COVID-19 mitigation strategies [24]. People who use drugs, including people who use opioids (PWUO), are more likely to have comorbidities, including comorbid chronic obstructive pulmonary disease, cardiovascular disease, and respiratory diseases, that increase the risk for severe disease and mortality from COVID-19 [7,11,25,26,27]. PWUD are an underserved population and face challenges related to reduced access to healthcare and support services as well as stigma [27]. To prepare for future emergencies, it is important to understand PWUD’s ability to practice the recommended behaviors to mitigate the spread of COVID-19, including washing hands, practicing social distancing, and wearing a face mask. Given this and the high rates of housing instability during the COVID-19 pandemic [28,29], this paper aims to examine the relationship between housing and PWUD’s ability to practice Centers for Disease Control and Prevention (CDC) recommended COVID-19 prevention strategies during the initial wave of the COVID-19 pandemic in NYC.

2. Materials and Methods

2.1. Study Design

This study has been previously described in detail [30]. Briefly, we conducted structured in-person surveys outdoors between June and September 2020 (n = 329). We used convenience sampling, with recruitment conducted via street intercept (n = 181, 55.1%) or in front of one of four NYC syringe services programs (SSPs) (n = 148, 44.9%). By utilizing in-person convenience sampling during a time much research transitioned to using tele-remote methods, we were able to engage PWUD who may not be engaged with services or have access to the required technology or resources to participate in tele-remote research. In-person data collection also allowed staff to build rapport and minimize participant burden by allowing staff to meet potential participants where they were [30]. Eligibility criteria included the following: (1) ≥18 years of age, (2) English or Spanish speaking, (3) use of opioids ≥3 times in the past 30 days, and (4) use of at least one of eight service touchpoints (i.e., SSP, outpatient substance use disorder treatment, medication for opioid use disorder (MOUD) treatment (including methadone or buprenorphine treatment), homeless shelter, emergency department, hepatitis C treatment, or COVID-19 isolation hotel (a designated hotel where individuals with COVID-19 could isolate)) [31]. A total of 516 PWUO were screened for eligibility; 332 were eligible, and 329 participated in the survey. All participants provided verbal consent and received a $25 gift card as an honorarium.

2.2. Procedures

All recommended CDC guidelines on COVID-19 prevention were followed during recruitment and survey administration. All surveys were conducted outdoors with six feet of distance between parties and both the study team and participants wore face masks for the duration of the 30 min survey as a protection from COVID-19 transmission. No survey materials were passed between the study team and participants, aside from the exchange of the gift card. Surveys were administered using computer-assisted personal interview devices.

2.3. Exposure

The primary exposure was housing status. Participants were asked where they had spent “the majority of their nights” since the COVID-19 pandemic began in March 2020. Participants could select from the following options: “my own room/apartment/home that I rent or own”, “my own room apartment/home that is supported/subsidized housing”, “my own room/apartment/home that is single room occupancy (SRO)”, “I’m permanently living in a family or friends home”, “I’m temporarily living in a family or friend’s home because I don’t have a place of my own”, “COVID-19 isolation hotel”, “a hotel as an alternative to congregate housing”, “vehicle”, “bus/train/subway station”, “street or another outside public space”, “other shelter or emergency housing”, or “other”.
This housing variable was recoded into a categorical variable with three categories: stable housing, unstable housing, and street homelessness. Those who selected “my own room/apartment/home that I rent or own”, “my own room/apartment/home that is supported housing/subsidized housing”, “my own room/apartment/home that is SRO”, or “permanently living in a family or friends’ home” were coded as having stable housing. Those grouped into the unstable housing category selected “temporarily living in a family or friends’ home because I don’t have a place of my own”, “COVID-19 isolation hotel”, “a hotel as an alternative to congregate housing”, or “other shelter or emergency housing”. Street homelessness included those who selected “vehicle”, “bus/train/subway station”, or “street or another outside public space”.

2.4. Outcome

At the time of the survey, CDC COVID-19 prevention recommendations included maintaining physical distance, frequent handwashing, and wearing a face mask to reduce disease transmission and prevent infection [32]. Vaccines were not available at the time the survey was administered [33]. Outcomes of interest were COVID-19 prevention recommendations, specifically, social distancing, access to soap and running water or hand sanitizer (for handwashing), and access to a face mask when wanted or needed. These outcomes were measured using a scale to assess how often participants practiced or had the ability to practice these CDC prevention recommendations. Participants reported that they practiced each “not at all”, “rarely”, “some of the time”, or “most of the time”. Responses were dichotomized as “most of the time” versus all other responses.

2.5. Statistical Analyses

Descriptive statistics (frequencies and percentages) were calculated for the 329 participants who completed the study. We conducted bivariate analysis to assess the relationship between housing status and the ability to follow three COVID-19 prevention recommendations (social distancing, access to soap and running water or hand sanitizer, and access to a face mask). Multivariable Poisson regression was used to examine the relationship between housing status and the ability to follow COVID-19 prevention recommendations and was adjusted for potential confounders (age, race, gender, income, and use of MOUD). A separate model was run for the ability to follow each COVID-19 prevention recommendation, resulting in three models. We used multivariable Poisson regression because, unlike logistic regression, the results from robust Poisson can be interpreted as prevalence ratios. Due to sparse data, ten surveys where participants identified their gender as transgender, non-binary, or gender non-conforming were omitted from modeling.
Missing data were imputed using multiple imputation by chained equations (MICE) for the 13 observations (4%) with missing data; all 13 observations were missing income data. Imputation models included variables associated with either missingness or the missing income variable (age group, having access to soap and running water or hand sanitizer, housing status, and COVID-19 testing status). We assumed income data were missing at random [34] and constructed 20 datasets. Model estimates were based on 20 datasets and combined using Rubin’s rules [35].
All analyses were conducted using R (Version 3.5.2) [36]. Surveillance procedures were approved by NYC Department of Health and Mental Hygiene’s Institutional Review Board (IRB 20-008).

3. Results

Demographic characteristics, housing status, and COVID-19 prevention recommendations are presented in Table 1. The majority of participants were male (67.5%), most were aged ≥ 35 (84.5%), and one-third identified as Hispanic (32.2%). Among the participants, 34.3% were stably housed, 31.9% were unstably housed, and 33.7% were experiencing street homelessness (Table 1).
Three-quarters (75.7%) of the overall sample had access to soap, running water, or hand sanitizer most of the time, 79.3% had access to a face mask most of the time, and 75.5% were able to practice social distancing most of the time (Table 1).
The unadjusted and adjusted prevalence ratios (PR and aPR, respectively) and the relationship between housing status and the ability to practice each of the COVID-19 prevention recommendations are presented in Table 2. The ability to practice social distancing most of the time did not differ by housing status. Compared with individuals with stable housing, individuals with unstable housing (PR = 0.89, 95% confidence interval (CI): 0.80–0.98) and those experiencing street homelessness (PR = 0.54, 95% CI: 0.45–0.65) had less access to soap and running water or hand sanitizer most of the time. Individuals experiencing street homelessness were less likely to have access to a face mask most of the time (PR = 0.78, 95% CI: 0.67–0.92) compared with individuals with stable housing. Having access to a face mask most of the time did not differ between individuals with stable housing and individuals with unstable housing (PR = 1.03, 95% CI: 0.94–1.15).
After adjusting for potential confounders, there was still no relationship between housing status and the ability to practice social distancing most of the time. Those experiencing street homelessness were still less likely both to have access to soap and running water or hand sanitizer most of the time (aPR = 0.56, 95% CI: 0.45–0.68) and to have access to a face mask most of the time (aPR = 0.82, 95% CI: 0.69–0.97) than those experiencing stable housing (Table 2).

4. Discussion

Our findings highlight that people experiencing street homelessness lacked the basic resources needed to reduce the risk of COVID-19, including soap, running water, and hand sanitizer [28,37]. While most of the PWUO surveyed were able to practice COVID-19 prevention recommendations, individuals experiencing street homelessness were significantly less likely both to have access to a face mask and have access to soap and running water or hand sanitizer most of the time compared with those who were stably housed. People who use opioids who were experiencing homelessness may have lacked access to a physical space or social services where they could access these resources. Interestingly, our results showed that people with unstable housing did not significantly differ in their ability to practice prevention recommendations most of the time compared to those with stable housing, suggesting that those experiencing street homelessness are a particularly high-need population. Many PWUO face barriers to housing support related to abstinence or treatment requirements and cannot easily access shelters [38,39]. Future emergency plans, including pandemic preparedness plans, should include PWUO as a special population and develop specific approaches and strategies to ensure their protection.
Our findings are broadly consistent with other data that indicated people experiencing street homelessness or unstable housing were particularly affected by COVID-19-related closures of facilities, such as drop-in centers, food pantries, and major transportation systems [29,40]. Service and transportation system closures reduced access to basic necessities and forced many people experiencing homelessness to choose between staying in close quarters with others or living unsheltered [38]. Other surveys have found that people experiencing homelessness reported not having access to adequate sanitation facilities [37,38,41]. During the initial wave of the pandemic, the closure of non-essential businesses led to individuals experiencing street homelessness having fewer options for public bathrooms [38,40]. As such, those who primarily relied on public bathrooms to meet sanitation needs were less able to practice the COVID-19 hand hygiene prevention recommendation. Among people who inject drugs specifically, lack of access to sanitation also has implication for increased infection rates [6,42].
The congregate nature of shelter-based housing can increase the risk of COVID-19 transmission [43]. Once infected, those in congregate facilities may be at higher risk of serious illness from COVID-19 due to disproportionate rates of untreated chronic medical and mental health conditions and increased healthcare barriers among this population [38,44]. Our findings did not identify that those who reported being unstably housed differed significantly in their ability to practice social distancing, to access a face mask, or to access soap and running water or hand sanitizer than those who were stably housed. In NYC, city shelters were “de-densified” by moving 9000 residents from congregate shelters into vacant hotel rooms, which may have facilitated some participants’ ability to practice social distancing [45,46,47] and other forms of COVID-19 mitigation strategies.
This study has limitations. First, the study utilized a convenience sample and is not broadly generalizable to PWUO. The cross-sectional design of the survey shows a snapshot of the experiences of PWUO in NYC and does not reflect changes over time. However, convenience sampling allowed us to capture the experiences of those experiencing street homelessness, those not connected to services, and those who did not have access to the needed resources to engage in tele-remote research during a public health emergency, making these data valuable [30]. Second, this analysis only includes responses from those identifying as male or female due to the small number of other gender identities among participants. While likely not representative of all gender identities of PWUO in NYC, this analysis still reflects responses from some of the most economically disadvantaged New Yorkers. Third, the survey asked about participants’ ability to access a face mask and soap and running water or hand sanitizer, not whether they used them. Though findings speak to accessibility rather than use, people can only use personal protective equipment and wash their hands if they have the necessary resources. People’s ability to access resources and space for disease prevention is important to explore further to better prepare for future emergencies and mitigate inequity. Further, these data do not indicate nuances within the housing status categories (e.g., number of individuals living in a participant’s housing unit) to understand transmission risk. Finally, the results cannot indicate an association between practicing COVID-19 prevention recommendations and subsequent COVID-19 infection, morbidity, or mortality. Nonetheless, to our knowledge, this is the first study of the effect of housing on the ability to follow these three COVID-19 prevention recommendations among PWUO in the US.
Housing is one of the most important factors in mitigating disease spread and improving health and well-being [40,48,49]. People experiencing street homelessness are likely to continue having difficulty practicing basic COVID-19 prevention strategies if their housing needs are not fulfilled. Public health programming and policy responses should focus on providing structural and programmatic support to New Yorkers experiencing homelessness, including stable housing, for example low-threshold, community-centered, permanent living spaces where PWUO could receive the needed support [40]. In the absence of health programming and policy responses that ensure that people receive needed and appropriate shelter, equitable access to programs such as those providing mobile hygiene facilities—particularly in the context of widespread public bathroom and facility closures—may be important [50]. Further, to mitigate increasing health disparities and minimize service interruptions during crises, such as in the COVID-19 pandemic, the specific needs of PWUO should be accounted for in public health planning, including emergency preparedness planning.

5. Conclusions

Participants who reported experiencing street homelessness were significantly less able to access soap and running water or hand sanitizer and to access face masks during the COVID-19 pandemic than those who reported unstable or stable housing in the adjusted model. The results demonstrate the increased vulnerability of PWUO reporting street homelessness as compared to those with any form of housing. Public health programming, policy responses, and emergency preparedness planning could be strengthened to support PWUO experiencing street homelessness. Increasing linkages to adequate housing options may be especially important for unhoused PWUO during future public health emergencies.

Author Contributions

Conceptualization, I.Z., A.E.J., L.J. and A.H.; methodology, I.Z., A.E.J. and M.N.; software, M.N., L.D.G. and I.Z.; validation, L.D.G.; formal analysis, I.Z. and M.N.; investigation, I.Z., L.J. and L.D.G.; resources, A.E.J., L.J. and A.H.; data curation, I.Z., A.E.J., L.J. and L.D.G.; writing—original draft preparation, I.Z.; writing—review and editing, I.Z., A.E.J., L.J., L.D.G., M.N. and A.H.; visualization, I.Z.; supervision, A.H. and M.N.; project administration, A.H. and L.J.; funding acquisition, A.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Centers for Disease Control and Prevention’s Overdose Data to Action, grant number NU17CE924978. Any opinions, findings, conclusions, or recommendations expressed in this manuscript are those of the authors and do not necessarily reflect the views of the Centers for Disease Control and Prevention.

Institutional Review Board Statement

The study was designated as “Not Human Subjects Research” and approved by the Institutional Review Board of the New York City Department of Health and Mental Hygiene (protocol code IRB 20-008, approved 14 February 2020). This work was designated as “Not Human Subjects Research” as participants did not have to provide any identifiable private information or identifiable biospecimens, nor did participants in this surveillance activity become subjects in research as recipients of test articles or controls.

Informed Consent Statement

Verbal consent was obtained from all participants, in line with the IRB determination of this work as public health surveillance and not human subjects research. All methods, including obtaining consent, were carried out in accordance with the relevant guidelines and regulations approved by the NYC Department of Health and Mental Hygiene’s Institutional Review Board.

Data Availability Statement

All data analyzed during this study are included in this article. Data analyzed are also available from the corresponding author.

Acknowledgments

The authors would like to thank the other members of the Overdose Data to Action team who helped coordinate surveillance activities.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

PWUDpeople who use drugs
CDCCenters for Disease Control and Prevention
NYCNew York City
PWUOpeople who use opioids
SSPsyringe services program
SROsingle room occupancy
MOUDmedication for opioid use disorder
MICEmultiple imputation by chained equations
IRBInstitutional Review Board
PRunadjusted prevalence ratios
aPRadjusted prevalence ratios
CIconfidence interval

References

  1. Ferrer, R.L. Social determinants of health. In Chronic Illness Care; Springer: Cham, Switzerland, 2018; pp. 435–449. [Google Scholar]
  2. Fazel, S.; Geddes, J.R.; Kushel, M. The health of homeless people in high-income countries: Descriptive epidemiology, health consequences, and clinical and policy recommendations. Lancet 2014, 384, 1529–1540. [Google Scholar] [CrossRef] [PubMed]
  3. Baxter, A.J.; Tweed, E.J.; Katikireddi, S.V.; Thomson, H. Effects of Housing First approaches on health and well-being of adults who are homeless or at risk of homelessness: Systematic review and meta-analysis of randomised controlled trials. J. Epidemiol. Community Health 2019, 73, 379–387. [Google Scholar] [CrossRef] [PubMed]
  4. Rhodes, T. Risk Environments and Drug Harms: A social Science for Harm Reduction Approach; Elsevier: Amsterdam, The Netherlands, 2009; Volume 20, pp. 193–201. [Google Scholar]
  5. Mehdipanah, R. Housing as a Determinant of COVID-19 Inequities; American Public Health Association: Washington, DC, USA, 2020; Volume 110, pp. 1369–1370. [Google Scholar]
  6. Vasylyeva, T.I.; Smyrnov, P.; Strathdee, S.; Friedman, S.R. Challenges posed by COVID-19 to people who inject drugs and lessons from other outbreaks. J. Int. AIDS Soc. 2020, 23, e25583. [Google Scholar] [CrossRef] [PubMed]
  7. Grebely, J.; Cerdá, M.; Rhodes, T. COVID-19 and the health of people who use drugs: What is and what could be? Int. J. Drug Policy 2020, 83, 102958. [Google Scholar] [CrossRef]
  8. Cowan, E.; Khan, M.R.; Shastry, S.; Edelman, E.J. Conceptualizing the effects of the COVID-19 pandemic on people with opioid use disorder: An application of the social ecological model. Addict. Sci. Clin. Pract. 2021, 16, 4. [Google Scholar] [CrossRef]
  9. New York City Homeless Municipal Shelter Population, 1983–Present; Coalition for the Homeless: New York, NY, USA, 2021.
  10. Basic Facts About Homelessness: New York City; [Updated 2022]; Coalition for the Homeless: New York, NY, USA, 2021; Available online: https://www.coalitionforthehomeless.org/basic-facts-about-homelessness-new-york-city/ (accessed on 3 December 2022).
  11. Karb, R.; Samuels, E.; Vanjani, R.; Trimbur, C.; Napoli, A. Homeless shelter characteristics and prevalence of SARS-CoV-2. West. J. Emerg. Med. 2020, 21, 1048. [Google Scholar] [CrossRef]
  12. Shin, S.H.; Ji, H.; Lim, H. Heterogeneity in preventive behaviors during COVID-19: Health risk, economic insecurity, and slanted information. Soc. Sci. Med. 2021, 278, 113944. [Google Scholar] [CrossRef]
  13. Probst, T.M.; Lee, H.J.; Bazzoli, A. Economic stressors and the enactment of CDC-recommended COVID-19 prevention behaviors: The impact of state-level context. J. Appl. Psychol. 2020, 105, 1397–1407. [Google Scholar] [CrossRef]
  14. Dobosh, K.; Tiberio, J.; Dongchung, T.Y.; Marder, T.; Deng, W.Q.; Hinterland, K.; Gould, L.H.; Seligson, A.L.; Dumas, S.E. Inequities in New Yorkers Experiences of the COVID-19 Pandemic; Epi Data Brief (123); New York City Department of Health and Mental Hygiene: New York, NY, USA, 2021.
  15. Dominguez-Gomez, L.; Jessel, L.; Zaidi, I.; Nolan, M.; Harocopos, A. Basic Needs among People Who Use Opioids in New York City during the COVID-19 Pandemic; Epi Data Brief (131); New York City Department of Health and Mental Hygiene: New York, NY, USA, 2022.
  16. Henkel, D. Unemployment and substance use: A review of the literature (1990–2010). Curr. Drug Abus. Rev. 2011, 4, 4–27. [Google Scholar] [CrossRef]
  17. Williams, C.T.; Latkin, C.A. Neighborhood socioeconomic status, personal network attributes, and use of heroin and cocaine. Am. J. Prev. Med. 2007, 32 (Suppl. S6), S203–S210. [Google Scholar] [CrossRef]
  18. Scallan, E.; Bodkin, C.; Wiwcharuk, J.; O’Shea, T.; Lennox, R. Finding stability amidst the COVID-19 pandemic: The impact of emergency temporary housing for people who use drugs. Drug Alcohol. Rev. 2022, 41, 7–8. [Google Scholar] [CrossRef] [PubMed]
  19. Ali, F.; Russell, C.; Nafeh, F.; Rehm, J.; LeBlanc, S.; Elton-Marshall, T. Changes in substance supply and use characteristics among people who use drugs (PWUD) during the COVID-19 global pandemic: A national qualitative assessment in Canada. Int. J. Drug Policy 2021, 93, 103237. [Google Scholar] [CrossRef] [PubMed]
  20. Russell, C.; Ali, F.; Nafeh, F.; Rehm, J.; LeBlanc, S.; Elton-Marshall, T. Identifying the impacts of the COVID-19 pandemic on service access for people who use drugs (PWUD): A national qualitative study. J. Subst. Abus. Treat. 2021, 129, 108374. [Google Scholar] [CrossRef] [PubMed]
  21. Kesten, J.M.; Holland, A.; Linton, M.-J.; Family, H.; Scott, J.; Horwood, J.; Hickman, M.; Telfer, M.; Ayres, R.; Hussey, D. Living Under Coronavirus and Injecting Drugs in Bristol (LUCID-B): A qualitative study of experiences of COVID-19 among people who inject drugs. Int. J. Drug Policy 2021, 98, 103391. [Google Scholar] [CrossRef] [PubMed]
  22. Schneider, K.E.; Wilson, D.; Dayton, L.; Goodell, E.M.A.; Latkin, C.A. Political partisanship and stigma against people who use drugs in opinions about allocating COVID-19 prevention resources to vulnerable populations. Int. J. Drug Policy 2021, 95, 103301. [Google Scholar] [CrossRef]
  23. Schneider, K.E.; Allen, S.T.; Rouhani, S.; Morris, M.; Haney, K.; Saloner, B.; Sherman, S.G. Increased solitary drug use during COVID-19: An unintended consequence of social distancing. Int. J. Drug Policy 2023, 111, 103923. [Google Scholar] [CrossRef]
  24. End of the Federal COVID-19 Public Health Emergency (PHE) Declaration: Centers for Disease Control and Prevention. 2023; [Updated 5 May 2023]. Available online: https://www.cdc.gov/coronavirus/2019-ncov/your-health/end-of-phe.html (accessed on 20 May 2023).
  25. Pauly, B.B.; Reist, D.; Belle-Isle, L.; Schactman, C. Housing and harm reduction: What is the role of harm reduction in addressing homelessness? Int. J. Drug Policy 2013, 24, 284–290. [Google Scholar] [CrossRef]
  26. Genberg, B.L.; Astemborski, J.; Piggott, D.A.; Woodson-Adu, T.; Kirk, G.D.; Mehta, S.H. The health and social consequences during the initial period of the COVID-19 pandemic among current and former people who inject drugs: A rapid phone survey in Baltimore, Maryland. Drug Alcohol. Depend. 2021, 221, 108584. [Google Scholar] [CrossRef]
  27. Volkow, N.D. Collision of the COVID-19 and Addiction Epidemics. Ann. Intern. Med. 2020, 173, 61–62. [Google Scholar] [CrossRef]
  28. Holloway, I.W.; Spaulding, A.C.; Ochoa, A.M.; Randall, L.A.; King, A.R.; Frew, P.M.; Team, H.S. COVID-19 vulnerability among people who use drugs: Recommendations for global public health programmes and policies. J. Int. AIDS Soc. 2020, 23, e25551. [Google Scholar] [CrossRef]
  29. Tsai, J.; Wilson, M. COVID-19: A potential public health problem for homeless populations. Lancet Public Health 2020, 5, e186–e187. [Google Scholar] [CrossRef] [PubMed]
  30. Jessell, L.; Zaidi, I.; Dominguez-Gomez, L.; Harocopos, A. Collecting Data During the COVID-19 Pandemic: Lessons from an In-Person Survey of People Who Use Opioids. Public Health Rep. 2022, 137, 272–277. [Google Scholar] [CrossRef] [PubMed]
  31. NYC Test & Trace Corps Take Care Program Helps More than 10,000 Guests Safely Separate in Free Hotel Rooms to Stop the Spread of COVID-19; NYC Health and Hospitals: New York, NY, USA, 2021; Available online: www.nychealthandhospitals.org (accessed on 25 April 2021).
  32. Honein, M.A.; Christie, A.; Rose, D.A.; Brooks, J.T.; Meaney-Delman, D.; Cohn, A.; Sauber-Schatz, E.K.; Walker, A.; McDonald, L.C.; Liburd, L.C.; et al. Summary of Guidance for Public Health Strategies to Address High Levels of Community Transmission of SARS-CoV-2 and Related Deaths, December 2020. MMWR Morb. Mortal. Wkly. Rep. 2020, 69, 1860–1867. [Google Scholar] [CrossRef]
  33. AJMC. A Timeline of COVID-19 Developments in 2020. Am. J. Manag. Care 2021. Available online: https://www.ajmc.com/view/a-timeline-of-covid19-developments-in-2020 (accessed on 20 April 2021).
  34. Ryder, A.B.; Wilkinson, A.V.; McHugh, M.K.; Saunders, K.; Kachroo, S.; D’Amelio, A., Jr.; Bondy, M.; Etzel, C.J. The advantage of imputation of missing income data to evaluate the association between income and self-reported health status (SRH) in a Mexican American cohort study. J. Immigr. Minor Health 2011, 13, 1099–1109. [Google Scholar] [CrossRef]
  35. Rubin, D.B. Multiple Imputation for Survey Nonresponse; Wiley: New York, NY, USA, 1987. [Google Scholar]
  36. Team, R.C. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2018; Available online: https://www.R-project.org/ (accessed on 6 October 2021).
  37. Montgomery, M.P.; Carry, M.G.; Garcia-Williams, A.G.; Marshall, B.; Besrat, B.; Bejarano, F.; Carlson, J.; Rutledge, T.; Mosites, E. Hand hygiene during the COVID-19 pandemic among people experiencing homelessness-Atlanta, Georgia, 2020. J. Community Psychol. 2021, 49, 2441–2453. [Google Scholar] [CrossRef]
  38. Routhier, G. State of the Homeless 2021; Coalition for the Homeless: New York, NY, USA, 2021. [Google Scholar]
  39. Watson, D.P.; Shuman, V.; Kowalsky, J.; Golembiewski, E.; Brown, M. Housing First and harm reduction: A rapid review and document analysis of the US and Canadian open-access literature. Harm Reduct. J. 2017, 14, 30. [Google Scholar] [CrossRef]
  40. Aronowitz, S.V.; Engel-Rebitzer, E.; Lowenstein, M.; Meisel, Z.; Anderson, E.; South, E. “We have to be uncomfortable and creative”: Reflections on the impacts of the COVID-19 pandemic on overdose prevention, harm reduction & homelessness advocacy in Philadelphia. SSM Qual. Res. Health 2021, 1, 100013. [Google Scholar]
  41. Homeless Guidance on People Experiencing Unsheltered Homelessness. Centers for Disease Control and Prevention. 2022. Available online: https://www.cdc.gov/coronavirus/2019-ncov/community/homeless-shelters/unsheltered-homelessness.html (accessed on 14 October 2022).
  42. Harris, M.; Scott, J.; Hope, V.; Wright, T.; McGowan, C.; Ciccarone, D. Navigating environmental constraints to injection preparation: The use of saliva and other alternatives to sterile water among unstably housed PWID in London. Harm Reduct. J. 2020, 17, 24. [Google Scholar] [CrossRef]
  43. Tobolowsky, F.A.; Gonzales, E.; Self, J.L.; Rao, C.Y.; Keating, R.; Marx, G.E.; McMichael, T.M.; Lukoff, M.D.; Duchin, J.S.; Huster, K.; et al. COVID-19 Outbreak Among Three Affiliated Homeless Service Sites—King County, Washington, 2020. MMWR Morb. Mortal. Wkly. Rep. 2020, 69, 523–526. [Google Scholar] [CrossRef]
  44. Self, J.L.; Montgomery, M.P.; Toews, K.A.; Samuels, E.A.; Imbert, E.; McMichael, T.M.; Marx, G.E.; Lohff, C.; Andrews, T.; Ghinai, I.; et al. Shelter Characteristics, Infection Prevention Practices, and Universal Testing for SARS-CoV-2 at Homeless Shelters in 7 US Urban Areas. Am. J. Public Health 2021, 111, 854–859. [Google Scholar] [CrossRef] [PubMed]
  45. Colburn, G.; Fyall, R.; Thompson, S.; Dean, T.; McHugh, C.; Moraras, P.; Ewing, V.; Argodale, S. Impact of Hotels as Non-Congregate Emergency Shelters: An Analysis of Investments in Hotels as Emergency Shelter in King County, WA during the COVID-19 Pandemic. Nov. 2020; University of Washington: Seattle, WA, USA, 2020; Available online: https://kcrha.org/wp-content/uploads/2020/11/Impact-of-Hotels-as-ES-Study_Full-Report_Final-11302020.pdf (accessed on 17 February 2021).
  46. Padgett, D.; Henwood, B.F.; Tsemberis, S.J. Housing First: Ending Homelessness, Transforming Systems, and Changing Lives; Oxford University Press: New York, NY, USA, 2016. [Google Scholar]
  47. Newman, A. Homeless Men Lose Court Battle to Stay in Upper West Side Hotel. The New York Times, 3 June 2021; A18. [Google Scholar]
  48. Pollack, C.E.; Saloner, B.; Lucas, S.; Warren, E.; Chaubal, M.; Kennedy-Hendricks, A. Leveraging the Affordable Housing Sector to Respond to the Opioid Crisis. Public Health Rep. 2021, 137, 00333549211007591. [Google Scholar] [CrossRef] [PubMed]
  49. Milaney, K.; Passi, J.; Zaretsky, L.; Liu, T.; O’Gorman, C.M.; Hill, L.; Dutton, D. Drug use, homelessness and health: Responding to the opioid overdose crisis with housing and harm reduction services. Harm Reduct. J. 2021, 18, 92. [Google Scholar] [CrossRef] [PubMed]
  50. Marshall, A.; Dugan, J.A. Addressing hygiene needs of housing insecure populations: A qualitative analysis of Seattle and King County’s mobile hygiene station intervention. Public Health Pract. 2022, 4, 100332. [Google Scholar] [CrossRef] [PubMed]
Table 1. Sociodemographics. Ability to follow COVID-19 recommendations.
Table 1. Sociodemographics. Ability to follow COVID-19 recommendations.
Housing Status (%)
Stable HousingUnstable HousingStreet Homeless
N% (CI)N% (CI)N% (CI)N% (CI)
329100%113100%105100%111100%
Housing
Stable housing11334.3% (29.3–39.8%)
Unstable/shelter housing10531.9% (27.0–37.3%)
Street homeless11133.7% (28.7–39.2%)
Gender
Man22267.5% (62.1–72.5%)7263.7% (54.1–72.4%)7470.5% (60.7–78.8%)7668.5% (58.9–76.8%)
Woman9729.5% (24.7–34.8%)3732.7% (24.4–42.3%)2725.7% (17.9–35.3%)3329.7% (21.6–39.2%)
Transgender man10.3% (0.0–2.0%)00.0% (0.0–4.1%)00.0% (0.0–4.4%)10.9% (0.0–5.6%)
Transgender woman61.8% (0.7–4.1%)43.5% (1.1–9.4%)21.9% (0.3–7.4%)00.0% (0.0–4.2%)
Gender non-binary person20.6 (0.1–2.4%)00.0% (0.0–4.1%)21.9% (0.3–7.4%)00.0% (0.0–4.2%)
Gender non-conforming person10.3% (0.0–2.0%)00.0% (0.0–4.1%)00.0% (0.0–4.4%)10.9% (0.0–5.6%)
Race/ethnicity
Hispanic/Latino/a10632.2% (27.3–37.6%)3633.0% (24.5–42.8%)3634.7% (25.6–44.8%)3830.6% (22.4–40.2%)
Black/African American7221.9% (17.6–26.8%)2724.8% (17.2–34.1%)2826.7% (18.6–36.6%)1715.3% (9.4–23.7%)
White8927.1% (22.4–32.3%)2622.0% (14.9–31.2%)2524.8% (16.9–34.5%)3834.2% (25.7–43.9%)
Other6218.8% (14.9–23.6%)2421.2% (14.3–30.1%)1615.2% (9.2–23.9%)2219.8% (13.1–28.7%)
Age (years)
18–345115.5% (11.9–20.0%)98.0% (3.9–15.0%)1312.4% (7.0–20.6%)2926.1% (18.5–35.5%)
35–4410130.7% (25.8–36.0%)2623.0% (15.8–32.0%)3331.4% (22.9–41.3%)4237.8% (29.0–47.6%)
45–549428.6% (23.8–33.8%)3631.9% (23.6–41.4%)3129.5% (21.2–39.3%)2724.3% (16.9–33.6%)
55 and older8325.2% (20.7–30.3%)4232.7% (28.4–46.8%)2826.7% (18.7–36.3%)1311.7% (6.6–19.5%)
Average monthly income since COVID-19
$0–$49913942.3% (36.9–47.8%)3531.0% (22.8–40.5%)5047.6% (37.9–57.5%)5448.6% (39.1–58.3%)
$500–$9998927.1% (22.4–32.3%)3934.5% (26.0–44.1%)2523.8% (16.3–33.3%)2522.5% (15.4–31.6%)
$1000–$15005215.8% (12.1–20.3%)2118.6% (12.1–27.2%)1615.2% (9.2–23.9%)1513.5% (8.0–21.6%)
>$15003510.6% (7.6–14.6%)1412.4% (7.2–20.2%)1211.4% (6.3–19.5%)98.1% (4.0–15.2%)
Declined/Missing144.3% (2.4–7.2%)43.5% (1.1–9.4%)21.9% (0.3–7.4%)87.2% (3.4–14.1%)
Used MOUD since COVID
Yes16951.4% (45.8–56.9%)7566.4% (56.8–74.8%)5956.2% (46.2–65.7%)3531.5% (23.2–41.1%)
No16048.6% (43.1–54.2%)3833.6% (25.2–43.2%)4643.8% (34.3–53.8%)7668.5% (58.9–76.8%)
Housing Status (%)
Stable HousingUnstable HousingStreet Homeless
N% (CI)N% (CI)N% (CI)N% (CI)
329 113100%105100%111100%
Access to soap, running water, hand sanitizer when needed since COVID-19/1 March
Never/Rarely/Sometimes8024.3%
(19.9–29.4%)		76.2%
(2.7–12.8%)		1817.1%
(10.7–26.0%)		5549.5%
(40.0–59.1%)
Most of the time24975.7%
(70.6–80.1%)		10693.8%
(87.2–97.3%)		8782.9%
(74.0–89.3%)		5650.5%
(40.9–60.0%)
Access to face mask when wanted or needed since COVID-19/1 March
Never/Rarely/Sometimes6820.7%
(16.5–25.5%)		1715.0%
(9.3–23.3%)		1312.4%
(7.0–20.6%)		3834.2%
(25.7–43.9%)
Most of the time26179.3%
(74.5–83.5%)		9685.0%
(76.7–90.7%)		9287.6%
(79.4–93.0%)		7365.8%
(56.1–74.3%
Familiar with social distancing
No30.9%
(0.2–3.0%)		00.0%
(0.0–4.2%)		11.0%
(0.0–6.0%)		21.8%
(0.3–7.0%)
Yes32699.1%
(97.0–99.8%)		113100.0%
(95.8–100%)		10499.0%
(94.0–100.0%)		10998.2%
(93.0–99.7%)
Ability to practice social distancing when wanted or needed (n = 326)
Never/Rarely/Sometimes802.5%
(1.1–5.0%)		2623.0%
(15.8–32.1%)		2523.8%
(16.3–33.3%)		2926.6%
(18.8–36.1%)
Most of the time24675.5%
(70.3–80.0%)		8777.0%
(67.9–84.2%)		7975.2%
(65.7–82.9%)		8073.4%
(72.1–80.0%)
Abbreviations: MOUD, medication for opioid use disorder; CI, confidence interval.
Table 2. Unadjusted and adjusted prevalence ratios for ability to follow COVID-19 recommendations most of the time versus less than most of the time by housing status 1.
Table 2. Unadjusted and adjusted prevalence ratios for ability to follow COVID-19 recommendations most of the time versus less than most of the time by housing status 1.
Unadjusted PR (95% CI)Adjusted PR (95% CI) 2
Ability to Follow COVID-19 Recommendations Most of the Time(95% CI)Ability to Follow COVID-19 Recommendations Most of the Time(95% CI)
Ability to practice social distancing when wanted or neededAbility to practice social distancing when wanted or needed
Stable housingRefRefRefRef
Unstable housing0.99(0.86–1.15)1.02(0.87–1.18)
Street homeless0.94(0.81–1.10)1.02(0.88–1.20)
Access to soap and water or hand sanitizer when wanted or neededAccess to soap and water or hand sanitizer when wanted or needed
Stable housingRefRefRefRef
Unstable housing0.89 *(0.80–0.98)0.91(0.82–1.01)
Street homeless0.54 *(0.45–0.65)0.56 *(0.45–0.68)
Access to face mask when wanted or neededAccess to face mask when wanted or needed
Stable housingRefRefRefRef
Unstable housing1.03(0.94–1.15)1.05(0.93–1.17)
Street homeless0.78 *(0.67–0.92)0.82 *(0.69–0.97)
Abbreviations: PR, prevalence ratio; CI, confidence interval; Ref, reference; 1 Ten surveys where participants identified their gender as transgender, non-binary, or gender non-conforming omitted from modelling due to small cell sizes; 2 Adjusted for age, race, gender, income, MOUD; * Significant result.
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Zaidi, I.; Jordan, A.E.; Jessell, L.; Dominguez Gomez, L.; Harocopos, A.; Nolan, M. Housing Status and COVID-19 Prevention Recommendations among People Who Use Drugs. COVID 2023, 3, 1612-1621. https://doi.org/10.3390/covid3100110

AMA Style

Zaidi I, Jordan AE, Jessell L, Dominguez Gomez L, Harocopos A, Nolan M. Housing Status and COVID-19 Prevention Recommendations among People Who Use Drugs. COVID. 2023; 3(10):1612-1621. https://doi.org/10.3390/covid3100110

Chicago/Turabian Style

Zaidi, Izza, Ashly E. Jordan, Lauren Jessell, Leonardo Dominguez Gomez, Alex Harocopos, and Michelle Nolan. 2023. "Housing Status and COVID-19 Prevention Recommendations among People Who Use Drugs" COVID 3, no. 10: 1612-1621. https://doi.org/10.3390/covid3100110

APA Style

Zaidi, I., Jordan, A. E., Jessell, L., Dominguez Gomez, L., Harocopos, A., & Nolan, M. (2023). Housing Status and COVID-19 Prevention Recommendations among People Who Use Drugs. COVID, 3(10), 1612-1621. https://doi.org/10.3390/covid3100110

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