Delayed Interventions, Low Compliance, and Health Disparities Amplified the Early Spread of COVID-19

Abstract

The United States (US) public health interventions were rigorous and rapid, yet failed to arrest the spread of the Coronavirus Disease 2019 (COVID-19) pandemic as infections spread throughout the US. Many factors have contributed to the spread of COVID-19, and the success of public health interventions depends on the level of community adherence to preventative measures. Public health professionals must also understand regional demographic variation in health disparities and determinants to target interventions more effectively. In this study, a systematic evaluation of three significant interventions employed in the US, and their effectiveness in slowing the early spread of COVID-19 was conducted. Next, community-level compliance with a state-level stay at home orders was assessed to determine COVID-19 spread behavior. Finally, health disparities that may have contributed to the disproportionate acceleration of early COVID-19 spread between certain counties were characterized. The contribution of these factors for the disproportionate spread of the disease was analyzed using both univariate and multivariate statistical analyses. Results of this investigation show that delayed implementation of public health interventions, a low level of compliance with the stay at home orders, in conjunction with health disparities, significantly contributed to the early spread of the COVID-19 pandemic.

Systematic review of empirical studies comparing the effectiveness of non-pharmaceutical interventions against COVID-19

“…Chaudhry et al 46 found that days to travel restrictions was positively associated with the number of cases. Both Islam et al 33 and Jalali et al 43 concluded that earlier implementation of lockdowns was associated with a greater reduction in incidence of COVID-19 and in the latter case they also found an association with early introduction of face mask requirements. Papadopoulos et al 37 concluded that early timing of lockdown introduction is of greater importance than its stringency.…”

“…With respect to the geographical scope, eleven studies analysed more than 65% of the world's territories 16 , 17 , 21 , 23 , 32 , 33 , 34 , 35 , 36 , 37 , 38 . Some focused on specific areas, with nine studies analysing data from the United States, performing mostly state-level 20 , 26 , 31 , 39 , 40 , 41 , but also county-level 22 , 42 , 43 analyses, three studies estimating the effects of NPIs in Europe 28 , 29 , 44 and two studies in all OECD countries 19 , 45 . Five studies selected specific countries that belong to different world regions 15 , 24 , 25 , 30 , 46 and three included both countries and US states 18 , 27 , 47 .…”

“…Several authors used sophisticated and flexible methods, like Bayesian longitudinal models 18 , 19 , 24 , 25 , 29 , 30 , 31 or event studies 15 , 20 , 36 , 42 , while others used linear regression 16 , 21 , 23 , 28 , 34 , 35 , 38 and simple correlation coefficients 37 , 43 . The quality of the statistical methodology is evaluated in the risk of bias tool in Annex 2.…”

Socioeconomic Deprivation, Sleep Duration, and Mental Health during the First Year of the COVID-19 Pandemic

“…This result is consistent with the literature where greater neighborhood deprivation was associated with worse mental health [ 65 ]. Communities with lower socio-economic status have endured the greatest mental and physical health burden from the pandemic compared to adults with a higher socioeconomic status [ 1 , 2 , 3 , 4 ]. These results indicate a critical need to understand the relationship between socioeconomic disadvantage and mental health particularly during a global health pandemic in order to mitigate negative short- and long-term consequences.…”

“…The coronavirus disease 2019 (COVID-19) pandemic has underscored health disparities in the United States. For example, neighborhoods with lower median family income and higher unemployment rates have higher rates of COVID-19 transmission, hospitalization, and death [ 1 , 2 , 3 , 4 ]. There is an established relationship between poor health outcomes and socioeconomic deprivation, often assessed via the social deprivation index (SDI), a composite measure of the effects of poverty and deprivation based on income, education, employment, housing, household characteristics, transportation, and demographics [ 5 ].…”