Examining Social Vulnerability and the Association With COVID-19 Incidence in Harris County, Texas

Abstract

Studies have investigated the association between social vulnerability and SARS-CoV-2 incidence. However, few studies have examined small geographic units such as census tracts, examined geographic regions with large numbers of Hispanic and Black populations, controlled for testing rates, and incorporated stay-at-home measures into their analyses. Understanding the relationship between social vulnerability and SARS-CoV-2 incidence is critical to understanding the interplay between social determinants and implementing risk mitigation guidelines to curtail the spread of infectious diseases. The objective of this study was to examine the relationship between CDC's Social Vulnerability Index (SVI) and SARS-CoV-2 incidence while controlling for testing rates and the proportion of those who stayed completely at home among 783 Harris County, Texas census tracts. SARS-CoV-2 incidence data were collected between May 15 and October 1, 2020. The SVI and its themes were the primary exposures. Median percent time at home was used as a covariate to measure the effect of staying at home on the association between social vulnerability and SARS-CoV-2 incidence. Data were analyzed using Kruskal Wallis and negative binomial regressions (NBR) controlling for testing rates and staying at home. Results showed that a unit increase in the SVI score and the SVI themes were associated with significant increases in SARS-CoV-2 incidence. The incidence risk ratio (IRR) was 1.090 (95% CI, 1.082, 1.098) for the overall SVI; 1.107 (95% CI, 1.098, 1.115) for minority status/language; 1.090 (95% CI, 1.083, 1.098) for socioeconomic; 1.060 (95% CI, 1.050, 1.071) for household composition/disability, and 1.057 (95% CI, 1.047, 1.066) for housing type/transportation. When controlling for stay-at-home, the association between SVI themes and SARS-CoV-2 incidence remained significant. In the NBR model that included all four SVI themes, only the socioeconomic and minority status/language themes remained significantly associated with SARS-CoV-2 incidence. Community-level infections were not explained by a communities' inability to stay at home. These findings suggest that community-level social vulnerability, such as socioeconomic status, language barriers, use of public transportation, and housing density may play a role in the risk of SARS-CoV-2 infection regardless of the ability of some communities to stay at home because of the need to work or other reasons.

Morbimortalidade por COVID-19 no contexto social da região de saúde Cariri, Ceará

“…Percebe-se, neste estudo, que indicadores de vulnerabilidade social podem ser influenciadores do aumento de casos de COVID-19. Em pesquisa realizada nos bairros de Fortaleza, Ceará, evidenciou-se que os indicadores possuíam influência na incidência da COVID-19 na metrópole, ou seja, quanto maior o nível de escolaridade, menor é o risco de contrair o vírus (19,20,21) .…”

Disproportionate impacts of COVID-19 in a large US city

“…In the US, the first wave of the COVID-19 pandemic disproportionately harmed essential workers [5,6], residents of long-term care facilities [71], racial and ethnic minority populations [72], and socially vulnerable neighborhoods within cities [31,44,73,74]. Public health agencies and government officials have tried to address these disparities through targeted testing, vaccination, distribution of personal protective equipment, information campaigns, and paid sick leave [15][16][17][18][19].…”

“…To prevent, detect, and reduce disparities in infectious disease burden, we need to increase the geographic and temporal resolution of our surveillance efforts, while reducing biases. Published estimates of COVID-19 burden in underserved populations are often derived directly from reported case or death counts, without correcting for ascertainment biases or disentangling risks of infection from risks of severe outcomes [7][8][9][30][31][32][33][34][35][36][37][38][39][40]. When available, both serological [41,42] and hospitalization data [43] can be used to estimate reporting rates.…”

Differential associations of mask mandates on COVID-19 infection and mortality by community social vulnerability

“…4 , 5 Though prior studies have documented this relationship for cohorts limited by time (e.g., the initial few months of the pandemic) or by different geographic levels or regions, these studies have not considered whether the relationship between community-level social vulnerability and COVID-19 has changed over time and to what extent. 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 Such an examination can provide a better understanding of the unfolding nature of the pandemic in communities deemed more vulnerable to disease outbreaks by the CDC.…”