South Korea data assists create framework to recognize COVID-19 susceptible areas worldwide


South Korea data helps create framework to identify COVID-19 vulnerable areas worldwide TTUHSC’s Yoonjung Lee, Pharm.D., Ph.D., joined a group of scientists who developed a structure to determine pockets of COVID-19-vulnerable populations through using socioeconomic status and epidemiological determinants. Credit: TTUHSC Though the U.S. and South Korea recorded their first official COVID-19 case on the exact same day, January 20, 2020, there were noteworthy distinctions in how each nation would ultimately address what has ended up being the world’s most severe pandemic given that 1918.

Yoonjung Lee, Pharm.D., Ph.D., a pharmacy preceptor and pharmaceutical sciences scientist at the Texas Tech University Health Sciences Center (TTUHSC) Jerry H. Hodge School of Pharmacy, said she was shocked at how South Korea successfully handled the pandemic without the business shutdowns and lockdowns that occurred in China, the U.S. and lots of European nations.

“I am amazed at how the Korean government had timely and reliable public health interventions to not only address COVID-19, but also to deal with COVID-19-vulnerable populations simultaneously,” Lee said. “That might be why the occurrences of COVID-19 cases dramatically reduced towards the late phase of our research study.”

The research study Lee referred to is one that she and a group of researchers just recently carried out to establish a methodological framework for identifying pockets of COVID-19-vulnerable populations through making use of socioeconomic status (SES) and epidemiological factors. They then applied data taken from South Korea’s action to COVID-19 to operationalize and demonstrate the worth of the structure.

Their study, “Precision Mapping of COVID-19 Vulnerable Places by Epidemiological and Socioeconomic Danger Factors, Developed Utilizing South Korean Data,” was released Jan. 12 in the International Journal of Environmental Research and Public Health.

In previous research study carried out throughout and after more current, and less serious pandemics such as SARS (Serious Severe Breathing Syndrome), swine influenza (H1N1) and MERS (Middle East Respiratory Syndrome), investigators had specified a gap in how these illnesses were found and dealt with among varying populations. Those populations thought about to be socioeconomically disadvantaged appeared to bear the impact of the illness while those populations considered to be more affluent and educated were considerably less affected.

Because of these earlier research studies, Lee said the research team thought there was the prospective to decrease the outbreak of COVID-19 by making use of targeted interventions. However, those earlier studies focused entirely on socioeconomic handpicked by their private investigators. More current studies also had supplied COVID-19 risk elements but none had actually recognized COVID-19-vulnerable areas associated with SES and epidemiological factors particular enough to the virus.

“Indeed, the previous research studies used SES variables based on scientists’ preferences, irrespective of their COVID-19 importance. Consequently, the SES procedures throughout these research studies were incomparable, limiting their effectiveness,” she added.

Lee stated her group’s COVID-19 study identified and utilized 7 particular socioeconomic and epidemiologic elements: healthcare access, health behavior, crowding, area morbidity, education, problem to social distancing and population movement.

To ensure they captured info about the study population’s socioeconomic and population health that was as complete as possible, Lee stated the group used Coleman’s Foundations of Social Theory, which combines the observed social actions of people with the logical concept of economists that competes people acts independently of one another and for their own self-interest.

“Coleman’s Social Theory directed us to collect data in each of three essential domains– material, human and social capitals– that concertedly identify each geographical system’s SES and area-health status in the study,” Lee discussed.

Lee said the group further filtered the research study’s variables by utilizing Blumenshine’s conceptual mechanistic structure, which describes the potential reasons for disparities in the U.S. during an influenza or respiratory infection pandemic. It associates those variations to varying levels of direct exposure to the infection, differences in vulnerability to the illness and unique variations in access to health care.

“That directed us to causally relevant variables to COVID-19, as they figure out the likelihood of being exposed to the infection agent, of contracting the disease upon direct exposure and of getting prompt and reliable treatment after the illness has established,” Lee stated.

Integrating Coleman’s Foundations of Social Theory and Blumenshine’s mechanistic structure assisted the research team formulate a universal SES definition and choose SES indications that were mechanistically and casually pertinent to COVID-19 health outcomes. The advancement of this methodological framework made this research distinct due to the fact that it permitted the group to recognize COVID-19-vulnerable locales through their associated SES and epidemiological determinants.

“Through this method, we might have universal SES variables with appropriate generalizability and methodological capability,” Lee said. “As a result, this assisted make our study’s regression design stronger and more accurate by using SES variables that related to COVID-19.”

Lee stated the significance of the research is that it offers a methodological structure and accuracy mapping method that is worldwide replicable for COVID-19 and future pandemics due to the fact that it offers robust SES measurements based upon the recognized theories for reducing bias from approximate data selections. In truth, she competed, the novelty of the work talks to the integrity of the study’s design and the analytical methodology of the research.

“Firstly, the integrated use of worldwide and spatial statistical approaches increased the precision as international designs confirmed the geographical model,” Lee stated. “Second of all, we teamed up in this study with Alan da Silva, who developed the unfavorable binomial extension of the geographically weighted regression. His application of this approach removed the tool’s erroneous use while likewise optimizing the design to study the data. Finally, our study revealed the progression of the COVID-19 epidemic over 3 consecutive time-periods, which was an unique technique at the time of the research study.”

In utilizing the South Korea information, the research study showed the threat of COVID-19 increased with higher location morbidity, risky health habits, crowding and population mobility. Other aspects that influenced danger consisted of education, lower social distancing and the ability to access health. Yet, Lee stated, falling COVID-19 risks and spatial shifts over three consecutive time periods (early-phase, middle-phase and late-phase) reflected efficient public health interventions in South Korea.

“This finding can be various if other information is used, though the South Korean information, based on our understanding, was the most detailed and openly available data with open access, which was the reason why we used South Korean information in our study,” Lee said. “For that reason, as illustrated in our study, it is vital to identify COVID-19-vulnerable locales associated with SES and COVID-19 specific epidemiological elements and after that to target prompt and reliable public health interventions toward these places for efficient pandemic control.”

Other members of the research team included Principal Private investigator David O. Carpenter, M.D., and primary author Bayarmagnai Weinstein, M.D., MPH, from the University of Albany; Alan R da Silva, Ph.D., (University of Brasília); Dimitrios E. Kouzoukas, Ph.D., (Edward Hines, Jr. VA Hospital); Tanima Bose, Ph.D., (Ludwig-Maximilian University of Munich); Gwang-Jin Kim, Ph.D., (University of Freiburg-Germany); Paola A. Correa, Ph.D., (Howard Hughes Medical Institute); Santhi Pondugula, Ph.D., (University of Florida); and Jihoo Kim, M.S., (Hanyang University-Seoul).

Proof of social factors affecting COVID-19 infection available to policymakers early in the pandemic More information: Bayarmagnai Weinstein et al, Precision Mapping of COVID-19 Susceptible Areas by Epidemiological and Socioeconomic Danger Factors, Developed Using South Korean Information, International Journal of Environmental Research and Public Health (2021 ). DOI: 10.3390/ ijerph18020604

Provided by Texas Tech University Health Sciences Center

Citation: South Korea information assists develop structure to identify COVID-19 susceptible areas worldwide (2021, April 7) recovered 11 April 2021 from

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