Eviction as a community health exposure

Abstract

Evidence suggests that being evicted harms health. Largely ignored in the existing literature, however, is the possibility that evictions exert community-level health effects, affecting evicted individuals’ social networks and shaping broader community conditions.

In this narrative review, we summarize evidence and lay out a theoretical model for eviction as a community health exposure, mediated through four paths: 1) shifting ecologies of infectious disease and health behaviors, 2) disruption of neighborhood social cohesion, 3) strain on social networks, and 4) increasing salience of eviction risk. We describe methods for parsing eviction's individual and contextual effects and discuss implications for causal inference. We conclude by addressing eviction's potentially multilevel consequences for policy advocacy and cost-benefit analyses.

Full text

Social Science & Medicine 340 (2024) 116496
Available online 7 December 2023
0277-9536/© 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Eviction as a community health exposure
Gabriel L. Schwartz
a
,
e
,
*
, Kathryn M. Leifheit
b
, Mariana C. Arcaya
c
, Danya Keene
d
a
Philip R. Lee Institute for Health Policy Studies, University of California San Francisco, San Francisco, CA, USA
b
Department of Pediatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
c
Department of Urban Studies & Planning, Massachusetts Institute of Technology, Cambridge, MA, USA
d
Department of Social & Behavioral Sciences, Yale School of Public Health, New Haven, CT, USA
e
Urban Health Collaborative & Department of Health Management and Policy, Drexel University Dornsife School of Public Health, Philadelphia, PA, USA
ARTICLE INFO
Handling Editor: Social Epidemiology Ofce
Keywords:
Housing
Eviction
Community health
Neighborhoods
Social determinants of health
Social cohesion
ABSTRACT
Evidence suggests that being evicted harms health. Largely ignored in the existing literature is the possibility that
evictions exert community-level health effects, affecting evicted individuals’ social networks and shaping broader
community conditions.
In this narrative review, we summarize evidence and lay out a theoretical model for eviction as a community
health exposure, mediated through four paths: 1) shifting ecologies of infectious disease and health behaviors, 2)
disruption of neighborhood social cohesion, 3) strain on social networks, and 4) increasing salience of eviction
risk. We describe methods for parsing eviction’s individual and contextual effects and discuss implications for
causal inference. We conclude by addressing eviction’s potentially multilevel consequences for policy advocacy
and cost-benet analyses.
1. Introduction
Residential eviction is a regular occurrence in low- and middle-
income communities in the US. For the past two decades, approxi-
mately 1 in 40 rental households (representing nearly 4 million people
(Graetz et al., 2023)) have been formally evicted each year (The Eviction
Lab, 2018), These annual risks accumulate, such that 1 in 7 children in
large cities are formally evicted by the time they reach adolescence
(Lundberg and Donnelly, 2019). For children living under 50% of the
poverty line, that risk is 1 in 4. True eviction rates are higher still, as
informal evictions—although difcult to measure—may outnumber
formal evictions by as many as 5 to 1 (e.g., being forced to move via
extralegal pressure from a landlord: sudden rent hikes, harassment of
tenants, etc.) (Gromis and Desmond, 2021).
Mounting evidence suggests evictions harm health. While the eld of
eviction epidemiology is still young, studies have linked eviction to
mortality (Rojas, 2017), COVID-19 infection (Leifheit et al., 2021a;
Sandoval-Olascoaga et al., 2021), injection drug use (Pilarinos et al.,
2017; Damon et al., 2019), reduced healthcare access (Chen et al., 2021;
Schwartz et al., 2022a), increased acute (but decreased primary)
healthcare utilization (Schwartz et al., 2022a; Biederman et al., 2022;
Collinson and Reed, 2018), sexually transmitted infections (Kennedy
et al., 2017; Niccolai et al., 2019), food insecurity (Leifheit et al.,
2020a), birth outcomes (Himmelstein and Desmond, 2021; Khadka
et al., 2020; Leifheit et al., 2020b), cognitive development (Schwartz
et al., 2022b), and mental health (Desmond, 2016; Desmond and Kim-
bro, 2015; Leifheit et al., 2021b; V´
asquez-Vera et al., 2017).
To date, epidemiology has largely treated eviction as an individual
phenomenon: evicted people develop worse health. Yet a sizable portion
of this evidence base relies on community-level eviction data to
construct exposure measures (Leifheit et al., 2021a, 2021b; Sandova-
l-Olascoaga et al., 2021; Niccolai et al., 2019; Khadka et al., 2020;
V´
asquez-Vera et al., 2017), due in part to a lack of individual-level data.
Few cohort studies, or even cross-sectional population health surveys,
collect formal or informal eviction histories (Leifheit and Schwartz,
2023). In contrast, The Eviction Lab at Princeton University—which
operates the only national eviction monitoring effort—makes data on
eviction lings and judgements from 2000 to 2018 freely accessible at
multiple levels of geographic aggregation (Gromis and Desmond, 2021).
Area-level eviction rates thus serve as an attractively available proxy for
the eviction risk faced by area residents.
Left largely unexamined is whether area-level eviction rates also
represent something more: contextual effects local evictions may impose
on whole communities. Establishing whether eviction functions as a
* Corresponding author. 3600 Market St, 7th Floor, Philadelphia, PA 19104, USA.
E-mail address: gs839@drexel.edu (G.L. Schwartz).
Contents lists available at ScienceDirect
Social Science & Medicine
journal homepage: www.elsevier.com/locate/socscimed
https://doi.org/10.1016/j.socscimed.2023.116496
Received 14 June 2023; Received in revised form 30 November 2023; Accepted 3 December 2023

Social Science & Medicine 340 (2024) 116496
2
community-level health risk factor, on top of directly harming the health
of evicted people, has real-world implications. First, if the health harms
of eviction extend beyond evicted individuals, studies examining the
effects of eviction only on the evicted would underestimate the full toll of
eviction for population health. Second, the design and implementation
of governmental policies to prevent evictions (and, importantly, the
advocacy case for these policies) may depend heavily on whose health is
impacted by evictions and how.
In this narrative review, we outline a theoretical model linking area-
level evictions and health, using evidence from social science and
epidemiology to suggest that area-level evictions represent a cluster of
exposures that affect both evicted people and their neighbors. We
conclude with implications for research and advocacy.
2. A theoretical model for eviction as a community health
exposure
We hypothesize that area-level evictions result in community-level
changes; these changes then affect the health of non-evicted community
members alongside the direct effects of eviction on evicted people.
Economists would call such health effects of evictions on non-evicted
people ‘spillovers;’ epidemiologists would refer to the phenomenon as
‘interference,’ or among social epidemiologists, ‘contextual effects.’
Although community-level evictions and poor health outcomes share
common causes—deeply racialized processes of disinvestment, neglect,
and exploitation—evidence points toward a causal link through at least
four processes (visualized in Fig. 1): 1) changing ecologies of infectious
disease and health behaviors, 2) disruption of neighborhood social
cohesion, 3) social network strain, and 4) increasing salience of eviction
risk. Though less well-studied, community health may also causally in-
crease community eviction risk, creating a cyclical feedback loop; we
discuss this below as an additional, 5th causal path in need of more
thorough and direct testing. Throughout, we draw on better-developed
models concerning neighborhood foreclosures (Arcaya et al., 2018;
Arcaya, 2017; Houle, 2014), as many of the same methodological and
theoretical issues apply. We also borrow from epidemiologic work on
mass incarceration and police violence, where a community impact lens
is better developed (American Public Health Association, 2020; Bor
et al., 2018; Jahn et al., 2021; Goin et al., 2021).
2.1. Changing ecologies of infectious disease and health behaviors
Where people live and work, and with whom, are elements of local
disease ecology, affecting the spread of infectious and vector-borne
pathogens. Evictions, in moving people around and clearing out hous-
ing units, reshape that ecology.
When evicted families double up with family or friends, residences
are more crowded; residents may be unable to socially distance or isolate
from one another after an infectious disease exposure. Congregate
shelters (a common alternative to living with friends or family) similarly
necessitate living in crowded conditions with little personal space
(Kendall, 2022; Brown, 2020; Ho, 2020; Baggett et al., 2020;
Fig. 1. Theoretical model: evictions as a community health exposure
Note: This diagram is best read from left to right, starting with community evictions and ending with physical health. Here, structural racism and racial capitalism (A)
shape who is at risk of experiencing community evictions as well as (B) modify the relation between community evictions and our theorized mediators, as well as
between these mediators and health.
G.L. Schwartz et al.

Social Science & Medicine 340 (2024) 116496
3
Tobolowsky et al., 2020; Levesque et al., 2022). Simulation studies
demonstrate that evictions can thus increase households’ risk of infec-
tious disease—in particular, of contracting and spreading COVID-19
(Nande et al., 2021). Observational studies of meningococcal disease
likewise nd that adding as few as 2 people to a household doubles
households’ risk of infection (Baker et al., 2000). Doubling up not only
increases risk of disease transmission between household members or
residents of congregate shelters; it also increases infectious disease risk
for communities, as infected people move through community settings.
Individuals may also preemptively double up in order to better afford
housing costs and prevent eviction. The threat of eviction alone may
thus drive crowding-induced infectious disease transmission even if an
individual is not themselves evicted (Arcaya et al., 2020).
Crowding is not the only problem. The threat of eviction causes
stress, which can dysregulate the immune system, decreasing the body’s
ability to ght an infection (Godbout and Glaser, 2006; Schubert, 2014).
Further, eviction threat can change workplace exposures: Arcaya et al.
for example, nd that low-income renters frequently took on additional
front line work during the COVID-19 pandemic in order to make housing
payments, opening up a potential pathway between housing displace-
ment pressure and exposure risk (Arcaya et al., 2020). Eviction and
related displacement could additionally reshape day-to-day mobility,
adding commuting time or necessitating greater mass transit use.
The hypothesis that area-level evictions can drive infectious disease
risk is supported by real-world studies leveraging the quasi-random
timing of state eviction moratorium expirations during the COVID-19
pandemic. Analyzing data at the state and individual level, these
studies estimate that state eviction moratoria prevented hundreds of
thousands of COVID-19 cases and tens of thousands of COVID-19 deaths
from March to September 2020 alone; effects were particularly large for
(though not exclusive to) those living in lower income and more rent-
burdened areas (Leifheit et al., 2021a; Sandoval-Olascoaga et al.,
2021). Others have found that rising housing costs at the municipal level
predict higher COVID-19 case rates, even when accounting for an array
of other socioeconomic factors; this association was strongest in com-
munities where residents were disproportionately low-income renters
(Arcaya et al., 2020).
Eviction’s impact on infectious disease risk does not appear limited
to COVID-19. Additional studies have found strong associations with
sexually transmitted infections (Niccolai et al., 2019) and HIV outcomes
(Kennedy et al., 2017; Groves et al., 2021). Two interacting mechanisms
may mediate these risks, one behavioral and one healthcare-related.
First, eviction can change how, when, whether, and under what cir-
cumstances people have sex. Eviction may drive the adoption of survival
sex work or sexual relationships that exchange sex for housing, contexts
where people face economic coercion and thus may be less able to
advocate for condoms or limit their number of sexual partners (Groves
et al., 2021). Eviction-induced poverty may simultaneously make con-
doms less affordable, exacerbating barriers to safe sex (Shen et al.,
2022). Specic to HIV and other blood-borne infections, eviction is also
associated with syringe sharing among youth who use injectable drugs,
increasing HIV transmission risk (Pilarinos et al., 2017). This may be
driven by eviction-induced possessions loss (including personal injec-
tion supplies), displacement away from local syringe exchanges, and
increased public drug use.
Second, evictions reduce patients’ healthcare access. In a study
examining Medicaid patients in New York City, Schwartz and colleagues
(Schwartz et al., 2022a) found that, in the aftermath of an eviction,
evicted patients experienced starkly increased risk of Medicaid disen-
rollment, lled fewer medication prescriptions, and used less ambula-
tory care. Similarly, literature shows that evictions have deleterious
effects on (ability to maintain) adherence to HIV medication regimens
and viral load, which are important for reducing community HIV
transmission (Kennedy et al., 2017). Sexually transmitted infections
may thus become more common not only due to increased or less pro-
tected sexual activity but also because infections are less likely to be
detected or treated in the aftermath of an eviction.
Taking this a step further, many health behaviors inuenced by the
behaviors’ of one’s peers could be shaped by community evictions.
Qualitative and quantitative work suggests, for example, that eviction
shifts whether someone is using drugs as well as the kinds of drugs they
are using and their suppliers of drugs (as they are displaced from their
neighborhoods and struggle to maintain access to nances and social
support) (Damon et al., 2019; McNeil et al., 2021); this would poten-
tially impact overdose risk, not only among evicted people but among
those with whom they share drugs (Brooks-Russell et al., 2014; Card and
Giuliano, 2013; Ivaniushina and Titkova, 2021; Lakon et al., 2015;
Sacerdote, 2014). Accordingly, at least in urban counties, rising eviction
is associated with higher rates of accidental drug and alcohol mortality
(Bradford and Bradford, 2020).
2.2. Disruption of neighborhood social cohesion
People who experience eviction are community members. They have
ties to other community members through which material, informa-
tional, and emotional support is given and received. Eviction can disrupt
these relationships, undermining the social building blocks that enable
community well-being. In particular, evictions may erode communities’
social cohesion and reduce their social capital (Kawachi et al., 2014).
2.2.1. Disrupting social cohesion: A breakdown of community and social
ties
High rates of eviction cause renter households to churn in and out of
low-income neighborhoods. This state of ux and displacement can
leave neighbors struggling to form strong and lasting social ties.
Eviction-induced displacement thus has the potential not only of eroding
specic interpersonal relationships through which social support is
passed, but also destroying the larger protective social structure that
geographically rooted community provides (Gardner, 2011; Greenbaum
et al., 2008). In particular, social cohesion—the connectedness and
solidarity that ows through communities with strong social
bonds—can be lost. (A recent study from New York State, for example,
shows that ZIP codes with higher eviction rates also display lower levels
of economic and social connectivity [Weaver, 2023]).
When communities lose social cohesion, they lose an important
health-promoting resource, leading to declines in well-being. This phe-
nomenon of broken social ties and concomitant declines in health was
famously illustrated in Roseto, Pennsylvania. In the mid-1900s, Roseto
was a community of densely socially connected Italian-Americans that
demonstrated remarkable cardiovascular mortality advantages over
nearby towns populated by other groups of immigrants (Bruhn et al.,
1982). Epidemiologic research found this mortality benet was driven
by the “Roseto effect,” i.e. deep and thickly interwoven social ties
generating meaning, positive mental health, and lower stress (with
attendant benets for residents’ physiologic function) (Wolf and Bruhn,
1993). The children of Roseto’s residents, however, became increasingly
integrated into the US’ dominant culture of atomization, with in-
dividuals retreating into nuclear family units and letting the dense social
ties that buttressed their parents’ community dissolve. Roseto residents’
mortality advantage, in turn, disappeared (Egolf et al., 1992). Since
Roseto, hundreds of studies have linked social cohesion to health,
pointing not only to lower stress but also to the ways more socially
cohered communities share information, promote access to jobs and
educational opportunities, and provide emotional and material support
in times of crisis (Kawachi et al., 2014; Berkman, 2000; Oberndorfer
et al., 2022).
Qualitative research paints a rich picture of what is lost when
geographically-rooted communities are disrupted, helping to ground
our hypothesis about the potential impacts of eviction. For example,
research has examined the experiences of public housing residents in the
wake of public housing demolitions, elucidating the loss of social
cohesion associated with these policy-induced “evictions.” Multiple
G.L. Schwartz et al.

Social Science & Medicine 340 (2024) 116496
4
studies point to the way in which longstanding residential communities
can foster close relationships among neighbors; prior to relocation,
many public-housing residents described their neighbors as “kinfolk”
(Stack, 1975), with public-housing residents operating like “one large
family” where residents helped each other and “everyone had your
back” (Clampet–Lundquist, 2010; Greenbaum, 2008; Manzo et al.,
2008). Residents reported that their relationships with neighbors pro-
vided a meaningful social role that kept them going. In one study, older
adults described their communities as places where they were treated as
respected elders who were called on to resolve disputes and care for
youth (Keene and Ruel, 2013). Upon losing those roles (when their
housing projects were destroyed), former public-housing residents
described a grief so profound it felt like losing a family member (Keene
and Ruel, 2013). This is not to discount the very real problems public
housing can pose for residents, but it does illustrate concrete benets
stable residential communities provide.
Evictions that destroy geographically rooted community,
then—particularly mass waves of eviction affecting large portions of
neighborhoods’ residents, as regularly occurs in some US cities (Wolf
and Bruhn, 1993; Waldman, 2022; Woolley et al., 2008; Bjella, 2022)—
may induce grief and depression, which has a well-established inuence
on physical well-being (Cassano and Fava, 2002; Kubzansky et al., 2014;
Penninx et al., 2013; Stroebe et al., 2007; Seiler et al., 2020). Once
displaced, public housing demolition studies suggest evicted families
may struggle to rebuild their social networks in their new neighbor-
hoods, causing a net negative loss in geographically-rooted social ties
(Greenbaum et al., 2008; Clampet- and Lundquist, 2004).
2.2.2. Implications for social capital and political power
Lost social cohesion can also chip away at social capital, dened as
the reciprocity, mutual aid, and material resources that ow through
socially cohered networks (Kawachi et al., 2014). Reduced social capital
renders communities less able to marshal collective power to meet
neighborhood needs by pooling community resources (Baylis et al.,
2013; Aida, 2018; Flora, 1998) or pressuring local government to invest
in their communities (Payne and Williams, 2008; Altschuler et al., 2004;
Krishna, 2002). As a consequence, communities may have less control
over environmental exposures (e.g., the placement of a highway or
pollution source), investments in green space, maintenance of roads and
sidewalks, and the availability of economic and educational opportunity
(Woolley et al., 2008; Smiley, 2020; Mazumdar et al., 2018).
Accordingly, community evictions are associated with measurable
reductions in social capital and political power. At the neighborhood
level, rising eviction rates coincide with fewer 311 calls (requests to
local government to make basic repairs, such as lling potholes and
replacing street signs) (van Holm and Monaghan, 2021) and lower voter
turnout (Weaver, 2023; Slee and Desmond, 2023). Related research on
“urban renewal,” which led to mass evictions in urban communities of
color (particularly, Black communities), similarly shows that forced
displacement can lead to declines in political power and subsequent
harms to community well-being (Fullilove, 2001; Fullilove and Wallace,
2011). And qualitative research with people displaced by public-housing
demolitions points to decreases in civic engagement and collective po-
litical agency (Keene, 2016). Across an array of contexts, then,
displacement-induced reductions in civic engagement and political ca-
pacity hobble communities’ ability to advocate for and create
health-promoting structures or curb neighborhood stressors.
2.2.3. Implications for crime victimization
Finally, a breakdown of social cohesion adversely impacts commu-
nities’ safety. Absent social cohesion, communities with high rates of
eviction may be less socially invested in one another, less likely to
interact regularly in public, and less able to provide “eyes on the street”
and social accountability to prevent interpersonal violence (Kawachi
et al., 2014; Jacobs, 1961). Moreover, lacking the material and
emotional support social cohesion fosters, community members may be
more likely to engage in crime as a means of survival (Mills and Zhang,
2014) or more likely to experience emotional crises (Kingsbury et al.,
2020; Breedvelt et al., 2022; Gullett et al., 2022) that could lead to
physical altercations. Increasing neighborhood eviction rates are
consequently associated with increases in neighborhood crime (rob-
beries, burglaries, and homicides), (Semenza et al., 2022) a pattern re-
ected in similar research on foreclosures (Immergluck and Smith,
2006).
2.3. Strain on social networks
Evicted people frequently “double up” in the months after an evic-
tion by moving in with friends or relatives (Link et al., 1994). (Though
some evicted individuals may move to congregate or emergency shel-
ters, these locations are often in short supply (Moses, 2019) and are
typically places of last resort [Robinson et al., 2022; Zeger, 2021]).
Qualitative research demonstrates that this doubling up strains social
relationships, stressing both evicted people and their new housemates
(Desmond, 2016; Babajide et al., 2016; Keene et al., 2022). The
combining households must crowd into limited space and navigate
potentially conicting preferences around household rules, schedules,
eating habits, etc. Many doubled-up evictees express depression, frus-
tration, and a loss of autonomy (Babajide et al., 2016; Skobba and Goetz,
2015). Focusing on the receiving households, Keene and colleagues nd
that these “informal housing providers” report multiple stressors asso-
ciated with providing housing, including crowded conditions, lack of
privacy, increase in expenses, caretaking demands, and, importantly,
threats to their own housing stability when they violate the terms of
their lease in order to take in a network member (Keene et al., 2022).
This stress and interpersonal strain can have negative consequences for
their health, disrupting sleep and health routines, and straining social
bonds that provide health-promoting social support (Desmond, 2016;
Keene et al., 2022; Skobba and Goetz, 2015).
While likely felt most acutely among the people evictees move in
with, eviction can strain social bonds widely. Low-income communities
provide tremendous amounts of care for each other (Stack, 1975).
Eviction increases the need for this care, perhaps to a level that is un-
sustainable; this includes eviction’s capacity to worsen poverty and
contribute to acute health crises, criminal legal system involvement, and
changes in substance use patterns (Schwartz et al., 2022a; Collinson and
Reed, 2018; Desmond, 2016; McNeil et al., 2021; Gottlieb and Moose,
2018). Resulting increased care burdens can directly impact caregivers’
health, including via increased stress, lost sleep, missed work, and more
(Bauer and Sousa-Poza, 2015; Ho et al., 2009; Burton and Bromell,
2010). Further, ethnographic work describes interpersonal tension
induced when housing-insecure families threatened by eviction repeat-
edly reach out to their limited network asking for money or a place to
live to avoid homelessness (Desmond, 2016). Over time, these repeated
asks made many relationships feel untenably transactional and extrac-
tive, leading to relationship loss. Eviction can thus serve as an enduring
toxin to the social bonds that sustain communities’ health, engendering
stress and poor mental health throughout.
2.4. Increasing salience of eviction risk
2.4.1. Community evictions as a threat to personal housing security
Area-level evictions may also change residents’ perceptions of their
personal eviction risk or the quality of their neighborhoods, with im-
plications for health. Seeing neighbors forced out of their homes and
their possessions piled on the street could increase the salience of
eviction’s consequences and increase the psychological duress people
feel when struggling to pay rent. Evictions are concentrated geograph-
ically, with certain buildings and neighborhoods representing an outsize
share of metros’ eviction rates (Rutan and Desmond, 2021; Seymour and
Akers, 2021a, 2021b; Rudolph et al., 2021). Moreover, “serial eviction”
is a well-documented phenomenon, with large landlords batch ling
G.L. Schwartz et al.

Social Science & Medicine 340 (2024) 116496
5
evictions (often repeatedly targeting the same tenant) as a rent collec-
tion tool (Immergluck et al., 2020; Leung et al., 2023). These practices
could signal to nearby renters that landlords are ready to serve an
eviction notices if renters fall behind. This matters for health because the
threat of eviction is itself a potent stressor (Leifheit et al., 2021b;
V´
asquez-Vera et al., 2017). Ethnographic work, for example, demon-
strates that poor mental health and psychological stress increase well
before an eviction is executed—even before it is led—suggesting the
threat alone is enough to damage health (Desmond, 2016). Data from
the COVID-19 pandemic using quasi-experimental methods yield a
similar conclusion, showing that state eviction moratoria were effective
in reducing population mental distress—but only if they blocked land-
lords from threatening tenants with eviction via notice and ling (as
opposed to merely blocking eviction executions) (Leifheit et al., 2021b).
Papers by Arcaya et al. corroborate the ability of local housing
market conditions to affect community residents’ health via spillovers.
The authors linked Massachusetts foreclosures to the Framingham
Offspring Cohort, regressing health onto the number of recent fore-
closures within 100 m of participants’ homes. Even though participants
were not themselves foreclosed upon, nearby foreclosures were associ-
ated with longitudinal changes to stress-related risk factors for car-
diometabolic disease, including increased systolic blood pressure
(Arcaya et al., 2014) and weight gain (Arcaya et al., 2013). Effects were
partially mediated by alcohol consumption, a common coping behavior
in the face of stress. Though the salience of proximate foreclosures and
evictions likely differs between homeowners and renters, these studies
show that the housing experiences of one household can spill over to
affect the stress-related health behaviors and disease risk of their
neighbors.
Although less well-documented, hearing about neighbors being
evicted might prevent tenants from advocating for their right to safe,
health-promoting housing. Fearing eviction, tenants might feel dis-
empowered when it comes time to ask landlords for needed repairs, pest
and mold remediation, etc. Such fears are not unfounded: although
retaliatory evictions are illegal in most states, tenants often report
receiving eviction notices following repair requests (Desmond, 2016;
Volk and Christie, 2019; Handa, 2016; Urban et al., 2019). Reporting
from Philadelphia, for example, found that tenants who led complaints
about housing conditions frequently received eviction lings within
months of the complaint (Volk and Christie, 2019). Though nationwide
surveys on tenants’ fear of retaliatory evictions are scarce in the United
States, surveys in England (Levelling Up Housing and Communities
Committee, 2016) and Australia (CHOICE National Shelter, 2017) nd
roughly half of each countries’ renters fear their landlord would attempt
to evict or “blacklist” them if they requested needed repairs. Seeing
neighbors evicted may amplify those fears, driving up the prevalence of
habitability violations such as mold, rodent or cockroach infestations or
extreme temperatures and increasing tenants’ risk of respiratory illness,
injury, and poor mental health (American Lung Association, 2020;
Evans et al., 2000; Gielen et al., 2015; Wimalasena et al., 2021).
2.4.2. When communities are targets: structural racism in eviction risk and
spatial stigma
Eviction risk is not random. By design—that is, as determined by
decades of ongoing interpersonal and structural racism in housing, ed-
ucation, employment, criminal-legal systems, and nancial institutions’
assessments of neighborhood and individual investment risk (Swope and
Hern´
andez, 2019; Rothstein, 2017; Blankenship et al., 2023; Leifheit
et al., 2022)—eviction rates are higher in racially/ethnically marginal-
ized communities. Nationally, Black people represent 13.6% of the
population but 18.6% of renters and 43.4% of all evictions; that trans-
lates to 1 in 5 Black renters in the US being threatened with eviction each
year, roughly half of whom are evicted (Graetz et al., 2023). Indeed,
evictions are part of an ongoing legacy of targeted, serial displacement
of racially marginalized communities through processes such as urban
renewal and gentrication (Fullilove and Wallace, 2011;
Rucks-Ahidiana, 2022; Whittaker et al.). Evictions can be wielded as a
tool to accelerate racialized dispossession, paving the way for rent in-
creases and a growing share of higher income and White residents
(Whittaker et al.; Dantzler, 2021; Moskowitz, 2017). Conversely, prev-
alent area-level evictions can reify racialized spatial stigma that de-
values property, reduces investments, and contributes to psychosocial
stress and poor health among residents (Keene and Padilla, 2014; Keene
et al., 2018) (while still allowing landlords to extract the highest
possible prots [Desmond and Wilmers, 2019]).
Area-level evictions may thus have distinct impacts in racially/
ethnically marginalized communities. First, in these communities,
housing market activity that displaces neighbors and changes neigh-
borhood conditions, such as frequent local evictions, may be rightfully
interpreted as a form of structural racism (Binet et al., 2022). Structural
racism in the housing market imposes a psychological cost on residents
beyond fear and stress about one’s personal housing situation. A
community-based participatory research project focused on gentrica-
tion in Eastern Massachusetts, for example, found that higher levels of
perceived ownership of neighborhood change was associated with better
mental health, even when accounting for individual residential stability
(Binet et al., 2022). This research dovetails with a thoughtful literature
on (A) sense of control over one’s life and living conditions as a deter-
minant of health (Whitehead et al., 2016), and (B) the psychological
impact of understanding one’s neighborhood or school as a target of
discrimination, with attendant spatial stigma that affects residents’
sense of self and societal value (Keene et al., 2018; Seaton and Yip,
2009). These matter for health both because having actually low power
over one’s surroundings and living conditions negatively impacts one’s
access to resources and freedom from toxic exposures (see “Implications
for social capital and political power” above), and because perceived low
power over one’s surroundings and living conditions induces chronic
psychological duress (Whitehead et al., 2016).
Second, the loss of social support and social capital neighborhood
evictions engender may have heightened consequences for Black com-
munities given the critical role that identity-afrming social support
networks play in mitigating the health impacts of racism (Stack, 1975;
Geronimus, 2000). That is: if community institutions and social ties play
a uniquely critical role in helping Black communities thrive and survive
in the face of structural oppression—not to mention resist and contest it
(Michener, 2023)—disrupting those ties and institutions through evic-
tion will have disproportionate consequences for Black communities’
well-being.
2.5. Reverse causation
In the opposite direction, individuals’ poor health can increase
community risk of evictions. Multiple studies have identied health
status and healthcare access as causes of eviction (Schwartz et al., 2021;
Allen et al., 2019; Linde and Egede, 2023; Zewde et al., 2019). Previ-
ously, we’ve explained these associations as resulting from
individual-level processes whereby out-of-pocket costs and disability
lead to missed work, nancial hardship, and ultimately delinquent rent
(Schwartz et al., 2021). But it’s equally true that an individual’s illness
and associated costs can strain the social and nancial resources of their
networks (especially their families [Golics et al., 2013; Skufca and
Rainville, 2021]), causing eviction risk spillovers. Caregivers of cancer
patients, for example, often miss work, or even lose their jobs due to
caregiving responsibilities (Bradley, 2019). Informal caregivers of de-
mentia patients face similar challenges (Cancino and Zinin, 2016).
Eviction and poor health may therefore operate as a feedback loop at
the community-level, cyclically accumulating sociobiological disad-
vantage within geographic and social networks (Fig. 1) (Schwartz et al.,
2021). On the one hand, this means eviction and poor health may
powerfully (re)produce social stratication, entrapping communities in
subjugated sociospatial positions. On the other, intervening to improve
community health or prevent evictions would intervene
G.L. Schwartz et al.

Social Science & Medicine 340 (2024) 116496
6
countercyclically: preserving housing instability would protect commu-
nities’ health, which would safeguard communities’ housing, and so on.
3. Discussion
The evidence above suggests eviction operates at multiple levels,
acting as an individual and contextual health exposure. Researchers
must attend to these multilevel dynamics, both because they pose
important methodological challenges but also because they have the
potential to change our conception of who is treated by eviction (and
therefore whose health would improve if policymakers lowered eviction
rates).
If eviction exerts contextual effects, population attributable risks of
eviction would have to be calculated by summing two mathematical
products: those found by multiplying (1) the impact of individual-level
eviction by the number of people who are evicted, and (2) the impact
of community-level eviction by the number of people who live in com-
munity with evictees. Even a small contextual effect would translate into
substantial public health benets for eviction prevention, given the
much larger pool of people we would consider ‘treated.’ A corollary is
that individual-level effects are likely to be underestimated in studies
examining individual-level evictions alone while ignoring contextual
effects; this is because un-evicted sample members may be treated by
eviction, too (via its contextual effects), complicating individual-level
causal contrasts. As evidence about area evictions as a community
health exposure accumulates, epidemiologists must respond by adapting
the way we estimate the costs and benets of different housing policy
choices.
Taking the potentially contextual effects of eviction seriously also
shifts the constituency for eviction prevention. Eviction of course pri-
marily impacts low- and middle-income households and their commu-
nities, and as a result of structural racism hugely disproportionately
burdens communities of color (Graetz et al., 2023). But the evidence
reviewed above suggests the health harms of eviction may nonetheless
stretch beyond evicted families and cross the boundaries of social and
geographic segregation (especially for infectious disease) (Sandoval-O-
lascoaga et al., 2021; Nande et al., 2021). If everyone’s health is put at
risk by a neighborhood eviction (however unevenly distributed that risk
might be), the well-being of entire communities—and constituencies—is
at stake. Expanding who we understand to be impacted by eviction may
shape support for eviction prevention policies.
3.1. Paths forward: interpreting & estimating area-level eviction rate
coefcients
When we see an association between area-level eviction rates and
health outcomes, it is hard to know the extent to which the association is
driven by effects among evicted households versus community spill-
overs. Whether that distinction matters depends on one’s goal. If esti-
mates are used to inform upstream interventions—i.e., some action that
prevents eviction at scale—it may not be necessary for an ecological
study to disentangle the paths through which eviction is causing poor
health. Lowering eviction rates in an area will intervene on all paths
between eviction and health, and so the collective impact of area-level
evictions on area-level health through all mediating paths is in fact
what one wants to estimate. Here, the challenge will be making a
compelling causal argument that a given study design has eliminated
selection and confounding. Leveraging policy changes as natural ex-
periments is one promising path forward.
If, however, one wanted to: (A) calculate an unbiased estimate of the
effects of eviction on evicted individuals; (B) inform downstream
interventions—e.g., accurately describing the effects of eviction on in-
dividuals’ healthcare access to healthcare payers, thus demonstrating
the importance of providing housing supports to the patients they
insure; or (C) inform advocacy efforts more broadly, parsing would
become consequential, necessitating studies capable of separating out
individual from contextual paths. To start, qualitative work exploring
the ways eviction shapes the well-being of evicted people’s neighbors
and families is essential for eshing out and testing the pathways
described above.
Quantitative studies interested in separating eviction’s individual
and contextual effects might use individual eviction and health data
measured longitudinally and linked to area-level eviction rates. Say, for
example, that we were interested in the relationship between eviction
and risk of preterm birth. In a longitudinal cohort, we could collect
detailed residential histories on each person over the entire course of
their pregnancy; each individual may have moved or been displaced
several times, and thus may have lived in anywhere from 1 to n neigh-
borhoods indexed by k. We could then t the following model:
logit(p) = β0+β1Evict +β2∑
n
k=1
(
ω
k∗AreaEvictk) + L
′
X(1)
where Evict represents an indicator for whether each individual was
evicted at some point during their pregnancy (or a count of evictions
they experienced); AreaEvictk measures the eviction rate in each
neighborhood k that a given cohort member lived in during their
pregnancy;
ω
k is a weight representing the proportion of each person’s
pregnancy that they lived in neighborhood k; X is a vector of measured
covariates; L is a vector of covariate coefcients; and p is the probability
of preterm birth. In this model, the coefcient β2 would provide an es-
timate of the contextual effect of evictions, independent of individuals’
direct exposure to eviction.
Such an analysis, of course, requires temporally and spatially
detailed residential histories. This is important in general when studying
the effects of contextual variables: low income people move frequently,
often between neighborhoods that are substantively different with
respect to, for example, levels of neighborhood poverty (Jackson and
Mare, 2007). For evicted people—100% of whom move, and among
whom residential addresses may change rapidly in the wake of their
eviction—such detailed histories are especially essential. Using
time-xed contextual measures would obscure this important
within-person variation. Ideally, eviction rates would also be measured
at ne levels of time and geography, though this is currently rarely
available in the US.
In Equation (1), we have assumed that no sample members share
neighborhoods. In some cohort studies, such as the Panel Study of In-
come Dynamics—where respondents are spread out across the entire
United States—such an assumption may basically hold. In many multi-
level datasets, however, sample members are intentionally selected such
that they are collectively representative of the larger units from which
they are sampled, e.g., neighborhoods (Sampson et al., 2022). In these
cases, neighborhood clustering will loom large. Appropriate models will
have to treat individuals as having been nested within, and
cross-classied between, residential neighborhoods as they move over
time.
3.2. Complications for causal inference
The fact that sample members in multilevel datasets may share
neighborhoods, however, creates additional problems. In particular, it
violates the stable unit treatment value assumption (SUTVA) that the
potential outcomes for any sample member i are independent of the
treatment assigned to any other sample member j (i.e., the assumption of
non-interference, or of no spillovers) (Schwartz et al., 2012). If, as we
propose above, member i’s eviction changes the community eviction
rate experienced by sample member j, and the effect of community
evictions is anything but 0, SUTVA cannot hold.
In the presence of a SUTVA violation, we must apply special methods
to estimate average treatment effects (e.g., see Laffers and Mellace
[Laffers and Mellace, 2020]). Absent these methods, any study of
individual-level evictions in which sample members share
G.L. Schwartz et al.

Social Science & Medicine 340 (2024) 116496
7
neighborhoods can only be said to causally identify the effects of evic-
tion on health if β2 from Equation (1) above equals 0 (i.e., the contextual
effects of eviction are negligible). To estimate how large the bias is when
estimating the effects of eviction while ignoring SUTVA violations,
simulation studies at various geographic scales would be needed.
The appropriate geographic scale for a given analysis is not obvious.
Although we have focused on “neighborhoods” for illustrative purposes,
the practical challenge for researchers is to work through (theoretically
and empirically) which geographic scales are most relevant for people’s
social or ecological networks, broadly dened. Alternately, one could
abandon geography entirely and focus on family or kin networks as a
unit of analysis; but dening a social network, too, requires scale
choices.
Regarding methods for disentangling our hypothesized pathways,
one could imagine mediation analyses to estimate each pathway’s
relative contribution (Rudolph et al., 2021). It will be difcult, however,
to collate data that sufciently represent (A) each construct along with
(B) all exposure-mediator and mediator-outcome confounders. It may be
more feasible to build evidence for these paths one by one, nding
strong causal designs to test relationships between eviction and each
mediator and then between each mediator and health. Such analyses
could triangulate across many different methods, including qualitative
studies.
4. Conclusion
Eviction epidemiology is nascent. Nearly any study rigorously eval-
uating the impact of individual- or community-level evictions on health
is an important step forward for the eld. If this literature is to be used to
design interventions, as inputs for cost-benet analyses, or as the basis
for advocacy, however, epidemiologists must engage with the likely
reality that the health impacts of evictions are not conned to those who
are evicted. Conceptualizing evictions as a community-level health
exposure requires us to break new analytic and theoretical ground, for
the health of evicted families and, inevitably, the health of us all.
Funding
GL Schwartz was supported by the Drexel FIRST (Faculty Institu-
tional Recruitment for Sustainable Transformation) Program (NIH Grant
No. U54CA267735-03). KM Leifheit (R01NR020854) and DE Keene
(R01NR020748) were supported by grants from the National Institute of
Nursing Research. The remaining authors did not receive any specic
grant from funding agencies in the public, commercial, or not-for-prot
sectors. No funder had any role in the analysis, writing, or submission of
this paper.
CRediT authorship contribution statement
Gabriel L. Schwartz: Conceptualization, Investigation, Methodol-
ogy, Project administration, Visualization, Writing - original draft,
Writing - review & editing. Kathryn M. Leifheit: Investigation, Visu-
alization, Writing - original draft, Writing - review & editing. Mariana
C. Arcaya: Supervision, Validation, Writing - original draft, Writing -
review & editing. Danya Keene: Supervision, Validation, Writing -
original draft, Writing - review & editing.
Data availability
No data was used for the research described in the article.
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