Recent news reports about
mortality counts for the Coronavirus point to the potential of large
under-counts due to the exclusion of deaths occurring at homes and the
classification of causes of death in the frenzied environment of so many deaths
occurring in communities. [i]
In
addition, national reviews are showing that black mortality rates are much
higher – sometimes twice as much – as their representation in the population
for several communities such as Michigan, Illinois, North Carolina and South
Carolina. [ii] Relatively less
information has been provided in national news reports regarding mortality
rates for Latinos.
Recognizing
these racial disparities, elected officials in Texas are pressing Governor Greg
Abbot to form an emergency task force to evaluate racial disparities
surrounding the coronavirus pandemic since several Texas cities are reporting
that the disease is disproportionately affecting black residents. [iii] Large gaps in data collection, however, exist
at the county and state level, meaning that the full picture is unclear. In response to these concerns, the Governor’s
office offered no comment and continues its policy of not mandating the
collection of this critical information.
As the Texas elected officials emphasized, the demographic data
regarding Covid-19 mortalities is needed to guide resources to the more
vulnerable communities or “hot spots” in the state.
Unfortunately,
accurate estimates of Covid-19 mortality rates by race-ethnicity are
systematically under-estimated because so many of the deaths are not being
classified by race-ethnicity. The
absence of race-ethnic data undermines the planning of intervention strategies
since it is fairly well understood that identifying clusters of infected
persons can expedite a quick intervention and solution to the spread of the
virus.
Thus
far, the knowledge that blacks have higher Covid-19 mortality rates compared to
their population in a community has been attributed to the confluence of co-morbidities
like diabetes, high blood pressure, obesity, and higher prevalence of
cardiovascular disease. Less attention has been devoted, however, to the
influence of social determinants of health – that is, black people tend to live
in poor areas that include poor access to healthy foods and healthcare
providers.[iv] There could be other
correlates that are equally important in explaining these high mortality rates,
such as lack of knowledge about the virus, negative attitudes towards
healthcare providers, religious beliefs, fear of family separation, and other
psychological factors.
An Important Question to Ponder
Given
the gravity of the high mortality rates among blacks and Hispanics, and the
real possibility that they could be higher and likely to spread the virus more
rapidly in these vulnerable communities, why have public officials not mandated
the collection of race-ethnic information for Covid-19 infected persons and
mortalities?
Thus
far, the explanations appear to rest on the assumption or belief that the sheer
volume of mortalities does not allow sufficient time to demographically
classify the corpses. While this theory
may be true, following are a few examples from my research practice that illustrate
the consequences of policies that utilize inaccurate race-ethnic information or
appear indifferent to its inclusion. In general, the solutions were not complicated nor time consuming.
Is Racial Profiling on the Decline?:
A recent analysis of traffic
stops made by the Texas Highway Patrol revealed that racial profiling of
Hispanics was on the decline, although critics suspected that the Department of
Public Safety (DPS) was deliberately misclassifying Texas drivers that they stopped
in order to lower the state’s racial profiling statistics. [v] Further analysis, however, revealed that the
DPS troopers were assigning the race category based on the physical characteristics
of the drivers. For example, by classifying Hispanic drivers as “white,” the
racial profiling statistics were systematically lowered in the State of Texas. The
recommended solution was to simply ask each driver to self-identify their race
or ethnicity by choosing from a card with standard race-ethnic categories that could
be presented by the DPS trooper. [vi]
Relying on Surnames: A Legal Matter
In a Dallas County murder trial that engaged me as
an expert witness, the defense attorney had requested a change of venue because
he felt that a fair trial was not possible for his Hispanic client. Why?
Because the share of Hispanics in the jury pool was likely to be substantially
different from the Hispanic share of the county’s population. I was asked to
conduct a statistical analysis to address this issue; however, the race-ethnic
information recorded by the court for jury pool members was considered
unreliable for the analysis because it was inconsistently recorded. A surname
was the only information available to estimate the Hispanic ethnicity of jury
pool members at an estimated accuracy of 75 percent. A change of venue was justified since the
estimate of Hispanics in the jury pool was not reflective of their
representation in the County’s population. Clearly, a different legal outcome might have
resulted if the venue had not changed.
The Mystery Surrounding the Causes
of Asian Mortalities
Information
about the leading causes of mortality among Asian American subgroups have been
few in epidemiological studies because (a) only seven states collected Asian
subgroup information on death records before 2003, (b) coroners were more
likely to make race-ethnic classification errors for Asian Americans (13%) and
Hispanics (7%) and (c) national health surveys did not report data for Asian
American subgroups. [vii]
As a result, misleading and erroneous
conclusions were often made due to the omission of Asian respondents resulting
from small sample sizes, or the aggregation of data that masked important
differences among the Asian subgroups. For example:
· Asian Indians have
greater coronary heart disease risk than Chinese persons when compared to
non-Hispanic whites;
· Japanese have greater
risk for incident cancers while Asian Indians have the lowest risk;
· Liver cancer mortality
rates are higher for Vietnamese, Koreans and Chinese when compared to other
Asian American subgroups and non-Hispanic whites.
· Colorectal cancer
rates are particularly higher for Japanese and exceed the rates for
non-Hispanic whites and all other Asian subgroups.
The
study investigators also discussed the results of recent pharmacogenomics
studies that document how some Asian American subgroups respond differently to
a variety of drug treatments, including chemotherapy, anti-coagulants,
anti-platelets, and anticonvulsants. The inclusion of Asian subgroup categories
in major health surveys and in the processing of medical information has
greatly expanded medical knowledge and treatment related to Asian subgroups. At least in the medical arena, the study
investigators clearly illustrated that carelessness or indifference to the use
of Asian subgroup identities can have significant consequences.
Thus,
it should be obvious that missing or inaccurate race-ethnic information can
have serious consequences to our quality of life and should not be dismissed so
easily by public officials who believe that it requires a great investment of
time.
Current Technology Points to
a Simple Solution for the Covid-19
In
the absence of information regarding the race-ethnic background of a given
population, we can take comfort in knowing that it is now possible to classify
the race-ethnic background of an individual based on their first name, last
name and their residential zip code. Ethnic Technologies developed a proprietary
classification system called E-Tech 2020 [viii] which has been utilized
in several survey studies that I have conducted in past years. In one national study of black, Latino and
Asian consumers in the U.S., race-ethnicity information was missing and
presented a major barrier to the sample design and planning of the survey. The E-Tech tool was used to estimate a
race-ethnic category in a database of 200,000 household addresses that allowed
us to plan the appropriate language for the questionnaires and manage a team of
telephone interviewers with the relevant language skills. The completed surveys that we received
confirmed that the accuracy of the assigned race-ethnic category using the
E-Tech tool was 80-90 percent when compared to the self-reported race-ethnicity
of the survey respondents. Self-identification
has usually been found to be a more valid measure of a person’s race and ethnicity,
while surname and language preference have also been used although considered
less valid measures. [ix] In a more recent review and analysis using geo-coding and surnames to estimate race and ethnicity, the investigators concluded that the combined approach can yield positive predictive values of 80 percent, thereby offering a viable means for assigning race and ethnicity for the purpose of examining disparities in care until self-reported data can be systematically collected. [x] While not a perfect measure, the E-Tech tool has
been shown to be quite useful in my past research experience.
What
is the relevance of the E-Tech tool for the Covid-19 situation? Simply, it can drastically reduce the amount
of time needed to identify the likely race-ethnic categories for a listing of
mortalities that includes their names and addresses. Moreover, the E-Tech tool is affordable and likely
to fit most public agency budgets. By
using this service, public officials could more readily identify clusters of
vulnerable populations, such as blacks and Latinos, that require immediate
intervention to minimize the spread of the coronavirus. While the accuracy of the E-Tech tool in
estimating a person’s race-ethnic classification is not 100 percent, it nevertheless
presents a significant advantage over the current system of delays and backlogs
that are typical in public agencies.
I
challenge Gov. Abbott and other public officials to mandate the classification
of race-ethnicity for all Covid-19 infections and mortalities using the E-Tech tool or perhaps another service that accomplishes similar results. Indeed,
this action would illustrate true leadership in our collective efforts to stop
the threat of this deadly virus.
Reference Notes
[i] Gillum, J., Song, L. and Kao, J. (2020, April 14). There’s been a spike in people dying at home
in several cities. That suggests coronavirus deaths are higher than
reported. Accessed on 4-15-20 at https://www.propublica.org/article/theres-been-a-spike-in-people-dying-at-home-in-several-cities-that-suggests-coronavirus-deaths-are-higher-than-reported
[ii] Ray, R. (2020, April 9). Why are Blacks dying at higher rates from
COVID-19? The Brookings
Institution. Accessed on 5-15-20 at https://www.brookings.edu/blog/fixgov/2020/04/09/why-are-blacks-dying-at-higher-rates-from-covid-19/
[iii] Morris, A. (2020, April 14). Texas elected officials push for emergency
response to racial disparities emerging in Covid-19 pandemic. The Dallas Morning News, accessed on
4-14-20 at https://www.dallasnews.com/news/public-health/2020/04/14/texas-elected-officials-push-for-emergency-response-to-racial-disparities-emerging-in-covid-19-pandemic/
[iv] Yancy, C.W. (2020, April 15). Covid-19
and African Americans. JAMA Network. Access on 4-15-20 at https://jamanetwork.com/journals/jama/fullarticle/2764789
[v] Rincón, E. T. (2016). How DPS can
improve its system of recording race/ethnicity during traffic stops. Dallas
News, Jan. 2016. Available at https://www.dallasnews.com/opinion/commentary/2016/01/27/edward-t.-rincon-how-dps-can-improve-its-system-of-recording-raceethnicity-during-traffic-stops
[vi] Ibid.
[vii] Holland, A.T. & Palaniappan, L.P.
(2012, June 22). Problems in the collection and interpretation of
Asian-American health data: Omission, aggregation, and extrapolation. Ann.
Epidemiol. 2(6).
[ix]
Rincón, E. T. (in press). The Culture
of Research, Writers Marq, Dallas, Texas.
(x) Fiscella, K. and Fremont, A.M. (2006). Use of geocoding and surname analysis to estimate race and ethnicity. Health Services Research, 41-4, Part I. Access on 4-17-20 at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1797082
(x) Fiscella, K. and Fremont, A.M. (2006). Use of geocoding and surname analysis to estimate race and ethnicity. Health Services Research, 41-4, Part I. Access on 4-17-20 at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1797082
