Abstract
Background Social capital has been associated with health outcomes in communities and can explain
variations in different geographic localities. Social capital has also been associated with behaviors that
promote better health and reduce the impacts of diseases . During the COVID-19 pandemic, social
distancing, face masking, and vaccination have all been essential in controlling contagion. These behaviors
have not been uniformly ad opted by communities in the United States. Using different facets of social
capital to explain the differences in public behaviors among communities during pandemics is lacking.
Objective
This study examines the relationship among public health behavior—vaccination, face masking,
and physical distancing—during COVID-19 pandemic and social capital indices in counties in the United
States.
Methods
We used publicly available vaccination data as of June 2021, face masking data in July 2020, and
mobility data from mobile phones movements from the end of March 2020. Then, correlation analysis was
conducted with county -level social capital index and its subindices (family unity, community health,
institutional health, and collective efficacy) that were obtained from the Social Capital Project by the United
States Senate.
Results
We found the social capital index and its subindices differentially correlate with different public
health behaviors. Vaccination is associated with institutional healt h: positively with fully vaccinated
population and negatively with vaccination hesitancy. Also, wearing masks negatively associate s with
community health, whereases reduced mobility associate s with better community health. Further,
residential mobility positively associates with family unity. By comparing correlation coefficients, we find
that social capital and its subindices have largest effect sizes on vaccination and residential mobility.
Conclusion
Our results show that different facets of social capital are significantly associated with adoption
of protective behaviors, e.g., social distancing, face masking, and vaccination. As such, our results suggest
that differential facets of social capital imply a Swiss cheese model of pandemic control planning where,
e.g., institutional health and community health, provide partially overlapping behavioral benefits.
* This work was supported in part by NSF grant ECCS-2033900 and by the Center for Pathogen Diagnostics through the ZJU-UIUC Dynamic Engineering
Science Interdisciplinary Research Enterprise (DESIRE).
Corresponding author: Lav R. Varshney (
[email protected])
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NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.
Introduction
Social capital has been developed as a concept to characterize the value of a community structure (1,2). To
better reflect the nature of communities, social capital has further been defined as the quality of the
relationship among community members, which is represented in trust and reciprocal aid that derive mutual
benefits to all parties (3). It has now become widely used to understand social determinants of public health
(4,5). In particular, social capital in communities has been associated wi th health outcomes, such as
mortality rate, obesity, and diabetes (6,7) and can explain the variation in health status across different
geographic areas (3). For the United States, social capital has been operationalized and measured on county
and state levels (8,9).
Social capital is measured using several social elements that each reflect a different aspect of a community
(8,9). These facets of social life , such as family unity and institutional trust, can further explain specific
social outcomes or behaviors. For example, s ocial capital stemming from family support has been
associated with better mental health (10), better mechanisms for coping with stress (11), and lower suicide
rates (12). Social capital stemming from civic participation, such as taking part in religious or volunteer
groups, promote d better sense of responsibility, and in turn created healthier neighborhoods and higher
levels of life satisfaction (13).
Social Capital and COVID-19
After the declaration of COVID-19 as a pandemic (14), social distancing and wearing masks were
recommended as non-pharmaceutical interventions to contain the spread. Even though recommendations
were widely announced and justified, not all communities abided uniformly to the new recommendations.
Some communities increased an individual sense of responsibility to take actions, e.g., social distancing,
to protect self and others (15), whereas other communities found it difficult to isolate and eliminate social
gatherings (16,17). Thus, growth of COVID-19 differed among communities and has been associated
with social capital and some of its dimensions. The number of COVID-19 confirmed cases decreased with
better community health (18), whereases mortality rate increased with lower social capital levels (19), and
lack of institutional trust and civic engagement (17). Collective adherence to protective behaviors during
a pandemic might mitigate the critical consequences of its spread.
Physical Distancing
Since COVID-19 is highly infectious and transmits easily with face-to-face interaction, social distancing
proved to be an effective mitigation strategy to contain COVID-19 spread (20). Cases decrease by 48%
and fatalities by 60% three weeks after states implemented lockdown orders (21). Physical distancing
strategies took a variety of forms, from limiting people's gatherings to fully restricting movements by
lockdown orders. In the United States, there were distinctive patterns in mobility reduction among
different sociodemographic groups, where some communities voluntarily stayed at home and limited their
movements even more after lockdown orders (22).
Wearing Masks
Face masking also has been an effective non-pharmaceutical intervention which lowers the risks of testing
positive for COVID-19 infection by 70% (23,24). In April 2020, with the absence of vaccines, the Centers
for Disease Control and Prevention (CDC) recommended the use of cloth masks in public (25), especially
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after finding that infectious microbes of COVID -19 can be transmitted from persons without symptoms
(26,27). All sociodemographic groups adopted mask wearing but there were large r increases in specific
geographic areas such as the Midwest , and 76% of the population wears masks when leaving their homes
(28).
Vaccination
For pandemic extinction, it is believed that 70% to 80% of the population must be vaccinated (29,30) and
the threshold decreases with following protective health behaviors, such as face masking and social
distancing (31). At the initial stage of vaccination development in 2020, half of the U.S. population did not
intend to take the vaccine because of health concerns and low confidence in the vaccine (32,33). Also,
media misinformation about vaccination strongly lowered people’s intention to be vaccinated, and some
sociodemographic groups were impacted differently (34). However, the hesit ancy against vaccination
started to decline by May 2021 among all demographic groups (35). As hesitancy declined, about 51% of
the U.S. population are fully vaccinated as of August 2021(36).
Social responses toward pandemics are critical in containing the spread and mitigating its exacerbated
effects. The way communities are structured impacts individuals’ ability to adopt new behaviors, and hence,
follow public health recommendations (37). This study aims to explore the association, if any, between
different social capital facets and public health behaviors: social distancing, wearing masks and vaccination,
during the COVID-19 pandemic at the county-level in the United States.
Data and Methods
We estimate the effects of social capital on public health behaviors related to COVID-19 pandemic. Table
1 summarizes the variables we used in the analysis with descriptive statistics at the county-level.
Table 1: List of variables and descriptives
Variable Notes Mean SD Minimum Maximum
Social Capital Standardized 0.00 1.00 -4.32 2.97
Family Unity Standardized 0.00 1.00 -4.93 2.66
Community Health Standardized 0.00 1.00 -1.67 7.07
Institutional Health Standardized 0.00 1.00 -4.66 2.99
Collective Efficacy Standardized 0.00 1.00 -8.42 1.22
Fully Vaccination Cummulative percentage of
population as of June 2021 28.96 14.39 0.00 99.90
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Vaccine Hesitancy Rate Cummulative percentage of
population as of June 2021 13.18 4.21 3.81 25.61
Always Wearing Masks Percentage of population on
July 2020 50.81 15.22 11.50 88.90
Never Wearing Masks Percentage of population on
July 2020 7.99 5.85 0.00 43.20
Mobility Index Week of 23 March 2020 3.18 0.53 0.65 4.16
Retail and Recreation
(percent change from
baseline)
Week of 23 March 2020 -35.84 13.43 -91.29 112.80
Residential (percent
change from baseline) Week of 23 March 2020 15.68 3.83 7.33 31.43
We obtained county-level social capital indices from the Social Capital Project (9), which comprise four
subindices: family unity which considers the structure of families in terms of marriage and children;
community health which considers participation in civic life such as involvement in volunteering and
religious groups; institutional health which considers confidence in media/corporations/schools, and
participation in institutions such as elections and census; and collective efficacy which is the converse of
social disorganization, operationalized via violent crime rates.
To assess public health behavior, we considered vaccination rate, vaccination hesitancy, mask usage, and
changes in mobility patterns at relevant times during COVID-19. We used county-level data considering
the fully vaccinated population (38), and estimated vaccine hesitancy (36) as of June 2021. County-level
mask usage data is based on a survey of 250,000 people conducted between July 2-14, 2020 (39): we
consider extreme responses of “never” and “always”. County-level mobility index is computed by Cuebiq
firm (40) based on changes in mobile phone movement. Changes in retail and recreation, and residential
mobility are obtained from Google Community Mobility Reports (41). We consider the March 23, 2020
week for mobility data before wide mandates of lockdowns were issued.
The bivariate relationships between each social capital index and public health behavior are assessed
using standardized linear regression. Statistical analysis along with P-values and 95% confidence
intervals are reported. All analyses have been done using statsmodels package in Python (42).
Datasets used in this study are publicly available (except Cuebiq data) and using them in this research
does comply with their owners’ terms and conditions. Cuebiq data is restricted and to request its access
one can apply here: https://www.cuebiq.com/.
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Results
Social capital subindices associate differently with COVID-19 vaccination, masking, and mobility change
behaviors, illustrated in the Swiss cheese model (43,44) that we extend to social capital (Fig 1). Each
public behavior affected by different social capital facets resembles a defensive layer against the spread of
COVID-19. The Swiss cheese model is created from the radar charts shown in Fig 2.
Figure 1:A Swiss cheese model for social capital, with pentagons representing the five social capital indices’ impact on social
behaviors
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Figure 2: Details of bivariate correlation for each public behavior against social capital indices represented in radar charts
Fig 2 specifies the differences in correlation sizes for each public health behavior against social capital
and its four subindices. Correlation coefficients of full vaccination are the largest, and of residential
mobility are the second largest, whereas mobility and mask usage have smaller effect sizes. Family unity
has similar effect sizes for all public health behaviors except largest for the mobility index. Community
health has greatest effect size for masking, less for vaccination, and least for the mobility indices.
Institutional health has greatest effect size for vaccination and change in residential mobility but smallest
in masking. Collective efficacy has smallest effect size for mobility and largest effect size for mask
wearing.
Vaccination mostly associates significantly with institutional health, positively with fully vaccinated
population, but negatively with increased hesitant population (Table 2). Fig 3-A shows that over time,
counties with high institutional health have an increasing rate of vaccination unlike counties with lower
institutional health. Further, Fig 3-B shows that hesitant population is less in counties with higher
institutional health.
Most counties have individuals who constantly wear masks, while fewer counties have people who rarely
wear masks (Fig 4-A). Wearing masks mostly associate with community health, positively with reduced
masks usage and negatively with widely mask usage (Table 2). Fig 4-B shows that counties with higher
community health have less people who always wear masks.
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Figure 3: A) Fully vaccinated population over time in counties with high and low institutional health. B) Estimated hesitant
population in counties with high and low institutional health. (The highest and lowest 25% of counties are considered).
Figure 4: A) Population that wears masks in counties. B) Population that always wears masks in counties with high and low
community health (The highest and lowest 25% of counties are considered).
In general, people reduced their visits in recreational areas more than in residential areas (Fig 5-A).
Reduced mobility associates mostly with higher overall social capital and secondly with community
health (Table 2). Fig 5-B shows that counties with better community health tend to move less. Reduced
recreational mobility, as well, associate mostly with higher overall social capital (Table 2) and secondly
with better institutional health (Fig 5-C). While increased residential mobility associates mostly with
higher family unity (Table 2) as seen in Fig 5-D.
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Figure 5: Fig 5: A) The change of recreation and residential mobility in counties. B) Mobility index in counties with high and low
community health. C) Recreation and retail mobility in counties with high and low institutional health. D) Residential mobility
with high and low family unity. (The highest and lowest 25% of counties are considered).
Table 2: Bivariate correlation estimation table. Each line represents a regression analysis between a public
health behavior and social capital index
Public Health Behavior Social Capital Index Estimated coefficient (95% CI) p-value 𝑅2 N
Fully Vaccination Social Capital 0.248 (0.21 to 0.28) 2.6×10−43 0.0617 2991
Family Unity 0.113 (0.08 to 0.15) 5.18×10−10 0.0127 3020
Community Health 0.146 (0.11 to 0.18) 1.95×10−16 0.0213 3138
Institutional Health 0.33 (0.3 to 0.36) 6.99×10−80 0.1088 3111
Collective Efficacy 0.065 (0.03 to 0.1) 0 0.0043 3022
Vaccine Hesitancy Rate Social Capital -0.148 (-0.18 to -0.11) 4.59×10−16 0.0218 2992
Family Unity -0.128 (-0.16 to -0.09) 1.95×10−12 0.0163 3021
Community Health 0.003 (-0.03 to 0.04) 0.85 0 3139
Institutional Health -0.261 (-0.29 to -0.23) 1.54×10−49 0.068 3112
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Collective Efficacy 0.001 (-0.03 to 0.04) 0.95 0 3023
Always Wearing Masks Social Capital -0.329 (-0.36 to -0.3) 1.56×10−76 0.1083 2992
Family Unity -0.19 (-0.23 to -0.16) 5.68×10−26 0.0361 3021
Community Health -0.37 (-0.4 to -0.34) 1.27×10−102 0.1371 3139
Institutional Health -0.19 (-0.22 to -0.15) 1.49×10−26 0.0359 3112
Collective Efficacy -0.201 (-0.24 to -0.17) 7.28×10−29 0.0403 3023
Never Wearing Masks Social Capital 0.184 (0.15 to 0.22) 4.15×10−24 0.0337 2992
Family Unity 0.094 (0.06 to 0.13) 2.45×10−7 0.0088 3021
Community Health 0.267 (0.23 to 0.3) 1.88×10−52 0.0714 3139
Institutional Health 0.097 (0.06 to 0.13) 6.58×10−8 0.0093 3112
Collective Efficacy 0.105 (0.07 to 0.14) 7.02×10−9 0.011 3023
Mobility Index Social Capital -0.276 (-0.31 to -0.24) 2.56×10−53 0.076 2992
Family Unity -0.214 (-0.25 to -0.18) 1.39×10−32 0.0457 3021
Community Health -0.267 (-0.3 to -0.23) 1.65×10−52 0.0715 3139
Institutional Health -0.233 (-0.27 to -0.2) 1.26×10−39 0.0543 3112
Collective Efficacy -0.09 (-0.13 to -0.05) 7.18×10−7 0.0081 3023
Retail and Recreation
Mobility
Social Capital -0.267 (-0.3 to -0.23) 4.59×10−42 0.0712 2503
Family Unity -0.204 (-0.24 to -0.17) 5.19×10−25 0.0416 2516
Community Health -0.231 (-0.27 to -0.19) 2.57×10−32 0.0535 2548
Institutional Health -0.264 (-0.3 to -0.23) 1.12×10−41 0.0697 2535
Collective Efficacy -0.075 (-0.11 to -0.04) 0 0.0056 2505
Residential Mobility Social Capital 0.322 (0.27 to 0.37) 3.51×10−33 0.104 1314
Family Unity 0.36 (0.31 to 0.41) 1.36×10−41 0.1298 1315
Community Health 0.021 (-0.03 to 0.07) 0.45 0.0004 1317
Institutional Health 0.322 (0.27 to 0.37) 4.41×10−33 0.1035 1316
Collective Efficacy 0.158 (0.1 to 0.21) 9.11×10−9 0.025 1309
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Discussion
During pandemics, social capital and its dimensions play a role in differentiating public responses towards
health policies and interventions, and in turn health outcomes diverge. Trusting institutions reduced anxiety
during SARS pandemic (45), and predicted vaccination acceptance during H1N1 pandemic (46,47). Also,
people’s intentions to wearing masks and washing hands increased with better social capital (7).
Similarly, d uring the COVID -19 pandemic, behavioral responses such as vaccinati on, masking, and
physical distancing have differed among United States counties . Here we have shown that facets of social
capital are associated with behavioral responses to the COVID-19 pandemic in different ways. Our findings
show that trusting institutions may promote vaccination and reduce vaccination hesitanc y. Also,
communities with more engagement in civic life tend to reduce their mobility . This supports the findings
of Bargain and Aminjonov (2020), Barrios et al. (2021), and Durante et al. (2021), where communities with
higher civic life engagement increased the sense of responsibility in individuals to lower their gatherings .
However, higher community health may motivate people to relax their face masking, and this can be
explained with overall reduced mobility and less face-to-face interactions. People stay home with better
family unity whereas recreational visits decrease with better social capital and institutional health.
Our results suggest that s ocial capital and its subindices are essential in explaining differences in public
behaviors during health crises which may help determine policies in local communities. Further, our results
show that differential facets of social capi tal imply a Swiss cheese model of pandemic control planning
where multiple layers of public behaviors differently affected by social capital can act against contagion
spread. There might be some barriers, such as community structure, misinformation from me dia, and
medical concerns, for an individual to adopt new behaviors in pandemics. Therefore, more effort might be
needed to help individuals to adhere to new protective behaviors especially in communities that generally
have lower social capital.
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