Assessing COVID-19 risk, vulnerability and infection prevalence in communities

Abstract

Background The spread of coronavirus in the United States with nearly five and half million confirmed cases and over 170,000 deaths has strained public health and health care systems. While many have focused on clinical outcomes, less attention has been paid to vulnerability and risk of infection. In this study, we developed a planning tool that examines factors that affect vulnerability to COVID-19. Methods Across 46 variables, we defined five broad categories: 1) access to medical services, 2) underlying health conditions, 3) environmental exposures, 4) vulnerability to natural disasters, and 5) sociodemographic, behavioral, and lifestyle factors. The developed tool was validated by comparing the estimated overall vulnerability with the real-time reported normalized confirmed cases of COVID-19. Analysis A principal component analysis was undertaken to reduce the dimensions. In order to identify vulnerable census tracts, we conducted rank-based exceedance and K-means cluster analyses. Results All of the 5 vulnerability categories, as well as the overall vulnerability, showed significant (P-values <<0.05) and relatively strong correlations (0.203<ρ<0.57) with the normalized confirmed cases of COVID-19 at the census tract level. Our study showed a total of 722,357 (~17% of the County population) people, including 171,403 between the ages of 45–65 (~4% of County’s population), and 76,719 seniors (~2% of County population), are at a higher risk based on the aforementioned categories. The exceedance and K-means cluster analysis demonstrated that census tracts in the northeastern, eastern, southeastern and northwestern regions of the County are at highest risk. Conclusion Policymakers can use this planning tool to identify neighborhoods at high risk for becoming hot spots; efficiently match community resources with needs, and ensure that the most vulnerable have access to equipment, personnel, and medical interventions.

The exposure risk to COVID-19 in most affected countries: A vulnerability assessment model

“…Another study [18], with a similar objective to this study, developing a planning tool that compares the estimated general vulnerability, with confirmed cases of COVID-19 reported in The countries vulnerabilities with high exposure risk to COVID-19 were identified based on each indicator measurement (ranging from 0 (bad) to 1 (good)). Among the advantages of our study, we can say that it is not a probability, but a risk of real exposure.…”

“…Another study [ 18 ], with a similar objective to this study, developing a planning tool that compares the estimated general vulnerability, with confirmed cases of COVID-19 reported in real-time. The vulnerability considered new variables (indicators) grouped into categories (factors), as in the reference articles cited in the introduction, but using estimates to replace missing data from various sectors, at the county (local) level.…”

The Exposure Risk to COVID-19 in Most Affected Countries: A Vulnerability Assessment Model

“…Another study [18], with a similar objective to this study, developing a planning tool that compares the estimated general vulnerability, with confirmed cases of COVID-19 reported in The countries vulnerabilities with high exposure risk to COVID-19 were identified based on each indicator measurement (ranging from 0 (bad) to 1 (good)). https://doi.org/10.1371/journal.pone.0248075.t002…”

Households at Higher Risk of Losing at Least One Individual in India: if COVID-19 is a new normal

“…COVID-19 severity is higher in those countries where there is already an aging population, with higher risk and requirement of hospilization [Sen, K., 2020]. In New York, 10 percent of total population and 16 percent of senior population are vulnerable and at highest risk of COVID-19 [Kiaghad et al, 2020] and similar results from present study indicates that the household with older people and males are at higher risk of developing a chronic morbidity and hence are at increased risk of severe COVID-19 disease. Other studies have also shown that more males have been reported to have COVID-19 and majority among the deceased (73%: Lake M 2020, Zheng Zet al, 2020).…”

“…Other comorbidities that are highly associated with COVID-19 are cancers, strokes and, respiratory infections including asthma and chronic obstructive pulmonary disease (COPD) (Singh AK et al, 2020; Zheng Z et al, 2020; Clark A et al, 2020; Kunal S et al, 2020; Lake M. A. 2020; Kiaghadi, A et al, 2020; Yao Q et al 2020). According to global estimates, most of the mortality due to COVID-19 attributed to either one or more comorbidities (Fang et al, 2020; Leung et al, 2020).…”