Opposing views: associations of political polarization, political party affiliation, and social trust with COVID-19 vaccination intent and receipt.

INTRODUCTION: Political polarization has increased in the USA within recent years. Studies have shown Republicans are less likely to accept COVID-19 vaccinations than Democrats; however, little is known regarding the association between COVID-19 vaccination acceptance and political polarization. METHODS: We used data from a nationally-representative survey of 1427 participants conducted between 9 February 2021 and 17 February 2021. We estimated multivariate-adjusted odds ratios for COVID-19 vaccination intent and receipt according to perceived political polarization (measured as the perceived size of the ideological gap between Democrats and Republicans), political party affiliation, and social trust, controlling for demographic and socioeconomic factors. RESULTS: Among participants perceiving high levels of polarization, Republicans (versus Democrats) reported a 90% lower odds of vaccination intent (OR = 0.10 [0.05, 0.19], P < 0.001). Participants with high (versus low) social trust and low perceived polarization had a 2-folder higher vaccination intent (OR = 2.39 [1.34, 4.21], P = 0.003); this association was substantially weaker in the high perceived polarization group. CONCLUSIONS: High perceived levels of political polarization appear to magnify the decrease in the odds of receiving the COVID-19 vaccine and the intent to get vaccinated among Republicans versus Democrats. Political polarization may further attenuate the protective associations of high social capital with vaccination.

COVID-19 to go? The role of disasters and evacuation in the COVID-19 pandemic.

Since the start of the pandemic, some U.S. communities have faced record storms, fires, and floods. Communities have confronted the increased challenge of curbing the spread of COVID-19 amid evacuation orders and short-term displacement that result from hazards. This raises the question of whether disasters, evacuations, and displacements have resulted in above-average infection rates during the COVID-19 pandemic. This study investigates the relationship between disaster intensity, sheltering-in-place, evacuation-related mobility, and contagion following Hurricane Zeta in Southeastern Louisiana and The Wildfires in Napa and Sonoma Counties, California, known as the Glass Fire. We draw on data from the county subdivision level and mapped and aggregated tallies of Facebook user movement from the Facebook Data for Good program's GeoInsights Portal. We test the effects of disasters, evacuation, and shelter-in-place behaviors on COVID-19 spread using panel data models, matched panel models, and synthetic control experiments. Our findings suggest associations between disaster intensity and higher rates of COVID-19 cases. We also find that while sheltering-in-place led to decreases in the spread of COVID-19, evacuation-related mobility did not result in our hypothesized surge of cases immediately after the disasters. The findings from this study aim to inform policymakers and scholars about how to better respond to disasters during multi-crisis events, such as offering hotel accommodations to evacuees instead of mass shelters and updating intake and accommodation procedures at shelters, such as administration temperature screenings, offering hand sanitizing stations, and providing isolated areas for ill evacuees.

Uneven paths: Soft Policy's benefits to recovery in Louisiana Parishes after Hurricanes Katrina and Rita.

Factors driving community recovery trajectories after disaster are not well understood. We assess why some communities show stronger recoveries from disaster than others, examining the role of four policy toolkits that U.S. county governments frequently adopt to recover from disaster. Using mixed methods, we examine the cases of Hurricanes Katrina and Rita with a novel dataset of recovery policies adopted within each Louisiana parish following the disasters. We typologize recovery strategies and analyze policy adoption patterns after crises. To compare which policy toolkit leads to the best recovery outcomes, we use synthetic control experiments on the 20 parishes hit by Hurricanes Katrina and Rita between August and September 2005, tracking net income inflow and net in-migration measures from 1997 to 2018 over 1408 parish-year observations, paired with qualitative case studies of parish policies and recovery outcomes. On average, soft and local recovery policies focused on community policies and feedback helped parishes stem the flow of finances away from the disaster-zone, as did infrastructural 'hard' policies, to a degree. in comparison, state policies focused on top-down planning experienced weaker recovery. Evidence shows that soft and local policy toolkits can accelerate recovery and that governments seeking to rebuild infrastructure should invest in locally-engaged community development in order to attain better overall recovery.

In the hands of a few: Disaster recovery committee networks.

When disaster strikes, urban planners often rely on feedback and guidance from committees of officials, residents, and interest groups when crafting reconstruction policy. Focusing on recovery planning committees after Japan's 2011 earthquake, tsunami, and nuclear disasters, we compile and analyze a dataset on committee membership patterns across 39 committees with 657 members. Using descriptive statistics and social network analysis, we examine 1) how community representation through membership varied among committees, and 2) in what ways did committees share members, interlinking members from certain interests groups. This study finds that community representation varies considerably among committees, negatively related to the prevalence of experts, bureaucrats, and business interests. Committee membership overlap occurred heavily along geographic boundaries, bridged by engineers and government officials. Engineers and government bureaucrats also tend to be connected to more members of the committee network than community representatives, giving them prized positions to disseminate ideas about best practices in recovery. This study underscores the importance of diversity and community representation in disaster recovery planning to facilitate equal participation, information access, and policy implementation across communities.

County-level political group density, partisan polarization, and individual-level mortality among adults in the United States: A lagged multilevel study.

Objective: To investigate the associations between county-level political group density, partisan polarization, and individual-level mortality from all causes and from coronary heart disease (CHD) in the United States. Methods: Using data from five survey waves (1998-2006) of the General Social Survey-National Death Index dataset and the County Presidential Election Return 2000 dataset, we fit weighted Cox proportional hazards models to estimate the associations between (1) political group density and (2) partisan polarization measured at the county level in 2000 (n = 313 counties) categorized into quartiles with individual-level mortality (n = 14,983 participants) from all causes and CHD, controlling for individual- and county-level factors. Maximum follow-up was from one year after the survey up until 2014. We conducted these analyses using two separate measures based on county-level vote share differences and party affiliation ideological extremes. Results: In the overall sample, we found no evidence of associations between county-level political group density and individual-level mortality from all causes. There was evidence of a 13% higher risk of dying from heart disease in the highest quartile of county-level polarization (hazards ratio, HR = 1.13; 95% CI = 0.74-1.71). We observed heterogeneity of effects based on individual-level political affiliation. Among those identifying as Democrats, residing in counties with high (vs. low) levels of polarization appeared to be protective against mortality, with an associated 18% lower risk of dying from all causes (HR = 0.82, 95% CI = 0.71-0.94). This association was strongest in areas with the highest concentrations of Democrats. Conclusions: Among all study participants, political group density and polarization at the county level in 2000 were not linked to individual-level mortality. At the same time, we found that Democratic party affiliation may be protective against the adverse effects of high polarization, particularly in counties with high concentrations of Democrats. Future research should further explore these associations to potentially identify new structural interventions to address political determinants of population health.

Election-Related Post-Traumatic Stress: Evidence from the 2020 U.S. Presidential Election.

The 2020 U.S. presidential election saw rising political tensions among ordinary voters and political elites, with fears of election violence culminating in the January 6 riot. We hypothesized that the 2020 election might have been traumatic for some voters, producing measurable symptoms of post-traumatic stress disorder (PTSD). We also hypothesized that negative sentiment toward the opposing party correlates with PTSD. We measured PTSD using a modified version of the PCL-5, a validated PTSD screener, for 573 individuals from a nationally representative YouGov sample. We modeled the association between affective polarization and PTSD, controlling for political, demographic, and psychological traits. We estimate that 12.5% of American adults (95% CI: 9.2% to 15.9%) experienced election-related PTSD, far higher than the annual PTSD prevalence of 3.5%. Additionally, negativity toward opposing partisans correlated with PTSD symptoms. These findings highlight a potential need to support Americans affected by election-related trauma.

Social capital's impact on COVID-19 outcomes at local levels.

Over the past thirty years, disaster scholars have highlighted that communities with stronger social infrastructure-including social ties that enable trust, mutual aid, and collective action-tend to respond to and recover better from crises. However, comprehensive measurements of social capital across communities have been rare. This study adapts Kyne and Aldrich's (Risk Hazards Crisis Public Policy 11, 61-86, 2020) county-level social capital index to the census-tract level, generating social capital indices from 2011 to 2018 at the census-tract, zipcode, and county subdivision levels. To demonstrate their usefulness to disaster planners, public health experts, and local officials, we paired these with the CDC's Social Vulnerability Index to predict the incidence of COVID-19 in case studies in Massachusetts, Wisconsin, Illinois, and New York City. We found that social capital predicted 41-49% of the variation in COVID-19 outbreaks, and up to 90% with controls in specific cases, highlighting its power as diagnostic and predictive tools for combating the spread of COVID.

The harmful effects of partisan polarization on health.

Partisan polarization significantly drives stress and anxiety among Americans, and recent aggregate-level studies suggest polarization may be shaping their health. This individual-level study uses a new representative dataset of 2,752 US residents surveyed between December 2019 and January 2020, some US residents report more days of poor physical and mental health per month than others. Using negative binomial models, zero inflated models, and visualizations, we find evidence that polarization is linked to declines in physical health: the more distant an individual feels politically from the average voter in their state, the worse health outcomes he or she reports. By uncovering the individual-level political correlates of health, this study aims to encourage further study and attention to the broader consequences of political polarization on American communities.

The dual effect of social ties on COVID-19 spread in Japan.

We investigate why some communities experience worse COVID-19 outcomes than others. Past studies have linked the resilience of communities against crisis to social vulnerability and the capacity of local governments to provide public goods and services like health care. Disaster studies, which frequently examine the effect of social ties and mobility, may better help illuminate the current spread of COVID-19. We analyze Japan's 47 prefectures from February 12 to August 31 using 62,722 individual confirmed cases of COVID-19, paired with daily tallies of aggregate Facebook user movement among neighborhoods. Controlling for mobility levels, health care systems, government finance, gender balance, age, income, and education levels of communities, our analysis indicates that areas with strong linking social ties see no or far lower levels of COVID-19 case rates initially. However, case fatality rates rise in such communities once the disease enters as they lack horizontal (bonding) ties which can mitigate its health impacts. We anticipate this study to be a starting point for broader studies of how social ties and mobility influence COVID-19 outcomes worldwide along with shining a light on how different types of social relationships play different roles as a crisis or disaster progresses.

Bowling alone or distancing together? The role of social capital in excess death rates from COVID19.

Much attention on the spread and impact of the ongoing pandemic has focused on institutional factors such as government capacity along with population-level characteristics such as race, income, and age. This paper draws on a growing body of evidence that bonding, bridging, and linking social capital - the horizontal and vertical ties that bind societies together - impact public health to explain why some U.S. counties have seen higher (or lower) excess deaths during the COVID19 pandemic than others. Drawing on county-level reports from the Centers for Disease Control and Prevention (CDC) since February 2020, we calculated the number of excess deaths per county compared to 2018. Starting with a panel dataset of county observations over time, we used coarsened exact matching to create smaller but more similar sets of communities that differ primarily in social capital. Controlling for several factors, including politics and governance, health care quality, and demographic characteristics, we find that bonding and linking social capital reduce the toll of COVID-19 on communities. Public health officials and community organizations should prioritize building and maintaining strong social ties and trust in government to help combat the pandemic.

Is divisive politics making Americans sick? Associations of perceived partisan polarization with physical and mental health outcomes among adults in the United States.

OBJECTIVES: To investigate whether changes in perceived partisan polarization since the 2016 US presidential election and current perceptions of polarization are associated with the onset of physical and mental health conditions in adults. METHODS: We surveyed a nationally-representative sample (n = 2752) of US adults between December 2019 and January 2020. We used multivariable logistic regression to estimate associations between perceived polarization and the incidence of hypertension, high cholesterol, obesity, diabetes, and anxiety, depressive, and sleep disorders in or after 2016 and current self-rated health. Our secondary exposure variables measured perceptions of mass and elite polarization at the state and national level. Perceived mass polarization measured perceptions of the partisan gap between Democrat and Republican voters; perceived elite polarization measured perceptions of the partisan gap between Democrat and Republican elected officials. RESULTS: Participants reporting an increase in polarization had 52-57% higher odds of developing depressive disorders (OR = 1.52, 95% CI: 1.01, 2.29, P = 0.047) and anxiety disorders (OR = 1.57, 95% CI: 1.07, 2.29, P = 0.02) compared to participants who perceived no change in polarization. Those reporting high (vs. low) levels of perceived state-level mass polarization had a 49% higher odds of incident depressive disorders (P = 0.03). Participants who perceived high levels of state-level elite polarization reported a 71% higher odds of incident depressive disorders (P = 0.004) and a 49% higher odds of incident sleep disorders (P = 0.03). CONCLUSIONS: Perceptions of partisan polarization may represent important factors that are linked to the onset of mental health and sleep disorders.