key: cord-313543-ad3c0hve authors: Amram, Ofer; Amiri, Solmaz; Lutz, Robert B.; Rajan, Bhardwaj; Monsivais, Pablo title: Development of a vulnerability index for diagnosis with the novel coronavirus, COVID-19, in Washington State, USA date: 2020-06-26 journal: Health Place DOI: 10.1016/j.healthplace.2020.102377 sha: doc_id: 313543 cord_uid: ad3c0hve ●. In the United States, morbidity and mortality from COVID-19 infection varies substantially among populations and geographic regions; ●. Variation has been attributed to chronic disease burden, and certain sociodemographic factors; ●. We developed an index of COVID-19 vulnerability using a regression modeling approach with observed diagnosis at the Zipcode level in Washington State; ●. The resulting index can be used by policy makers for the targeting of public health and health care resources. With nearly two million cases diagnosed and more than 115,000 deaths to date in the United States (US), 1 facilities also at elevated risk. 2 Additionally, individuals with underlying medical conditions including heart disease, chronic lung disease, moderate to severe asthma, severe obesity, diabetes, chronic kidney disease, liver disease, and the immunocompromised are at increased risk. 2 Other trends in risk factors beyond age and chronic disease have been emerging. For example, data from the CDC indicate a significantly higher case fatality in male versus female patients and African Americans compared to other racial groups. 3 More research will likely be performed in the next few months to examine associations such as these. One approach to characterizing and quantifying the underlying factors that make some communities or populations more or less susceptible to a particular health hazards is a vulnerability index. For example, The CDC's Social Vulnerability Index is widely used in health research, particularly in the fields of medical emergencies and evacuation planning. 4 The Pampalon index is a deprivation index developed in Canada that aims to quantify health inequalities and wellness both in terms and social and material deprivation. 5 Multiple indices of vulnerability to COVID-19 and its impacts in the US are emerging online and in rapid reports. These vulnerability indices have been largely based on different a priori selections of sociodemographic variables and chronic disease prevalence estimates within administrative areas, often at the county level. [6] [7] [8] One study applied the CDC's Social Vulnerability Index to COVID-19 mortality 9 while others have used non-COVID disease statistics to drive the selection of index components. 10 In this article, we demonstrate an empirical approach to developing a small-area COVID-19 vulnerability index using statistics on diagnoses in two counties from Washington State, USA, along with demographic and population health. The COVID-19 diagnosis rates for the two most populous counties in Washington State were obtained from the King and Spokane County Departments of Health. 11, 12 Sociodemographic characteristics of ZIP codes were obtained from the 2018 American Community Survey 5-year estimates. 13 Registered deaths for the state were obtained from the Washington State Department of Health, Center for Health Statistics for the years 2011-2017. 14 Use of de-identified publicly available data did not warrant a review by an Institutional Review Board. The outcome was COVID-19 diagnosis rates. King and Spokane County have made these data available to the public via data dashboards that list the number and rates of COVID-19 across ZIP codes. Census data were used to calculate percent of nonwhite population, including African Americans, American Indian or Alaska Natives, Asians or other Pacific Islanders, multiracial, and Hispanics. Percent of population in transportation, protective service (firefighting and prevention, and other protective service workers including supervisors and Law enforcement workers including supervisors), healthcare support, and practitioners and technical occupations. Percent of population below federal poverty line, and population density. We used logarithmic transformation of population density in analyses. The burden of comorbidities that have been linked to greater vulnerabilithy to COVID-19 was operationalized as mortality due to diabetes, heart disease, and chronic lower respiratory disease. For each ZIP code, rates of mortality from these conditions were calculated among people 65 years and above. We used decedents' address, their underlying causes of death, and the associated International Classification of Diseases (ICD-10) codes. Residential locations with address matching accuracy of 80% or above were included in the analyses. Unadjusted and adjusted multilevel modeling were performed to examine factors associated with COVID-19 diagnosis rates. We treated COVID-19 diagnosis rates across ZIP codes at level-1 nested within level-2 counties. Inclusion of random intercept in the multilevel models accommodated the likelihood of COVID-19 diagnosis rates to vary across the two counties. The data were analyzed using the lmer package in R. The significance level was set at 0.05 (two-tailed). One hundred and sixteen ZIP codes were included in the analyses (81 in King County and 35 in Spokane County). Four ZIP codes had missing COVID-19 diagnosis rates and were excluded. COVID-19 diagnosis rates varied from 0 to 362 per 100,000 people. Percent of non-white population ranged from one to 72%, percent of service occupations from zero to 30%, percent of population below federal poverty line from zero to 38%, mortality rates from zero to 3,523 per 100,000 people, and population density from 0.18 to 18,990 per square miles. These indicators were significant both in bivariate models and in the multivariable adjusted model, concordant with recent reports, which indicate that Black, Hispanic, and poorer populations are more likely to be exposed to and impacted by COVID-19. There are several hypotheses attempting to explain this phenomenon. The first is that nonwhite populations are less likely to have jobs that can be performed from home. A recent published report by US Bureau of Statistics showed that only 19% of Black and 16.2% of Hispanic can Telework compared to 29.9% of white and 37% of Asian respectively. 15 Indeed, the percentage of the resident population in each ZIP code engaged in service occupations was strongly and significantly associated with infection. Secondly, these populations are more likely to have other underlying health conditions and less likely to have medical coverage and therefore less likely to access health services if they are experiencing symptoms of COVID-19, 16 ultimately leading to an increase in transmission rates. Our vulnerability index has several strengths. First, the index components (predictors) were selected based on the emerging literature, and the index was tested using actual COVID-19 cases at a ZIP code level, which are relatively small geographic areas. In addition, the primary data used in this index are widely available to local health authorities across the United States. Mortality data are routinely collected by the local departments of health across the nation, and in some states, are also available to researchers. The census data, which makes up most of the indicators in the model, can be downloaded freely from the US census data website. A limitation of this index is that we only used ZIP code level COVID-19 cases from two counties in Washington State to assess its validity. The current lack of data on COVID-19 cases and related deaths will need to be addressed before more insight on the impact of this disease on the population can be gleaned. A better understanding of who is impacted by this highly infectious and deadly disease can play a key role in preventing and reducing the burden of COVID-19 on our health care system. Identifying populations at risk can facilitate a reduction of their morbidity and mortality rates while allowing us to better contain the overall spread of the disease. This COVID-19 vulnerability index is based on Zip-code level and publicly-available data on demographic, socioeconomic, and medical risk factors can be used to understand population-and community-level variation in susceptibility to COVID-19 across Washington State. Making this and similar indices available to the scientific community, public health experts, and local governments will lead to a better understanding of where outbreaks may occur and which populations need more support than others. This could facilitate more effective resource allocation to communities with limited ability to manage transmission of COVID-19. Targeted interventions such as social distancing, the deployment of personal protective equipment for essential workers, and educational and training programs could help curtail the worst possible outcomes of this pandemic. However, there is a need to improve access to data on where and when COVID-19 cases and deaths occur. COVID-19): Cases in the U.S People who are at higher risk for severe illness Provisional death counts for coronavirus disease (covid-19) Measuring community vulnerability to natural and anthropogenic hazards: the Centers for Disease Control and Prevention's Social Vulnerability Index A deprivation index for health planning in Canada Surgo Foundation. The COVID-19 Community Vulnerability Index map Health Vulnerability Index Covid-19 Vulnerability Mapping for the US's 500 Largest Cities Impact of Social Vulnerability on COVID-19 Incidence and Outcomes in the United States COVID-19 data dashboard Spokane County COVID-19 Case Data American Community Survey 5-year estimates DATA FROM THE AMERICAN TIME USE SURVEY In the United States, morbidity and mortality from COVID-19 infection varies substantially among populations and geographic regions -Variation has been attributed to chronic disease burden, and certain sociodemographic factors -We developed an index of COVID-19 vulnerability using a regression modeling approach with observed diagnosis at the Zipcode level in Washington State -The resulting index can be used by policy makers for the targeting of public health and health care resources