association between epidemic dynamics of covid 19 infection and abo blood group types CORD-Papers-2021-10-25 (Version 1)

Title: Association between epidemic dynamics of Covid-19 infection and ABO blood group types
Abstract: Background: Covid-19 pandemic is the most critical challenge nowadays for the manhood, and the infection and death cases are still speedily increasing. Since there are no available vaccine and specifically effective treatment, to break the infectious way of the pandemic remains the unique measure to efficiently combat Covid-19 infection. Understanding factors that affect the Covid-19 infection can help make better balance between activity restriction and infection dynamics. This study sought to investigate association between Covid-19 infection and blood type distribution. Methods: The big data provided by World Health Organization and Johns Hopkins University were taken to assess epidemic dynamics of Covid-19 infection. Growth rate and doubling time of infection and death cases, reproductive number, infection and death cases in the mid-exponential phase were analyzed in relation to blood type distribution. Results: Growth rate of infection and death cases correlated significantly to blood type A proportion of the population positively while to blood type B proportion negatively. In comparison with lower blood type A population (< 30%) people with higher blood type A ([] 30%) had more infection and death cases in the early exponential phase, higher growth rates, and shorter case doubling time for infection and death. Discussion: Covid-19 infection is significantly associated with blood type distribution and people with blood type A are more susceptible to Covid-19 infection and have higher epidemic dynamics and higher case fatality rate. The results of this study provide important and useful information for fighting Covid-19 pandemic.
Published: 7/15/2020
DOI: 10.1101/2020.07.12.20152074
DOI_URL: http://doi.org/10.1101/2020.07.12.20152074
Author Name: Liu, Y
Author link: https://covid19-data.nist.gov/pid/rest/local/author/liu_y
Author Name: Steinacker, J M
Author link: https://covid19-data.nist.gov/pid/rest/local/author/steinacker_j_m
Author Name: Haeussinger, L
Author link: https://covid19-data.nist.gov/pid/rest/local/author/haeussinger_l
Author Name: Dinse Lambracht, A
Author link: https://covid19-data.nist.gov/pid/rest/local/author/dinse_lambracht_a
sha: e0d3f15d15ec5aaa9a4dde449c50a0e730a7f2f5
license: medrxiv
source_x: MedRxiv; WHO
source_x_url: https://www.who.int/
url: https://doi.org/10.1101/2020.07.12.20152074 http://medrxiv.org/cgi/content/short/2020.07.12.20152074v1?rss=1
has_full_text: TRUE
Keywords Extracted from Text Content: people ≥ blood blood type A Covid-19 blood type B ( blood type B (5 AB patients May15 blood type O DCDpp(1/2 cancers Covid-19 virus Covid-19 RN cardiovascular Covid- 19 people IC-begin DC-dt blood type O or blood type A Robert-Koch-Institute https://doi.org/10.1101/2020.07.12.20152074 doi globe HIV People ABO blood medRxiv preprint 13;14 ACER2 medRxiv preprint Figure 3 ICDpp(1/2 Figure 3c Figure 3 Fig.3 IC-dt ICGR Figure 3b ≥ blood Covir-19 blood type A patients Dpp(1/2 Dpp medRxiv B Figure 3b lockdown herd zone DCGR
Extracted Text Content in Record: First 5000 Characters:Background Covid-19 pandemic is the most critical challenge nowadays for the manhood, and the infection and death cases are still speedily increasing. Since there are no available vaccine and specifically effective treatment, to break the infectious way of the pandemic remains the unique measure to efficiently combat Covid-19 infection. Understanding factors that affect the Covid-19 infection can help make better balance between activity restriction and infection dynamics. This study sought to investigate association between Covid-19 infection and blood type distribution. The big data provided by World Health Organization and Johns Hopkins University were taken to assess epidemic dynamics of Covid-19 infection. Growth rate and doubling time of infection and death cases, reproductive number, infection and death cases in the mid-exponential phase were analyzed in relation to blood type distribution. Growth rate of infection and death cases correlated significantly to blood type A proportion of the population positively while to blood type B proportion negatively. In comparison with lower blood type A population (< 30%) people with higher blood type A (≥ 30%) had more infection and death cases in the early exponential phase, higher growth rates, and shorter case doubling time for infection and death. The pandemic of Covid-19 infection still keeps rapidly increasing worldwide, which threatens very much the public health and causes dramatic knockdown of the global economics and social life. According to the data derived from World Health Organization (WHO) database, up to date there was over 10 million confirmed cases of Covid-19 infection (WHO situation reports on June 29, 2020), and the daily new infection cases maintain at very high level. To control this pandemic outbreak is difficult because factors affecting the Covid- 19 infection have yet not been thoroughly understood, and specific vaccine and treatments are still unavailable. If one looks the Covid-19 infection map provided by Johns Hopkins University (JHU) (for example the map picture on May15, 2020), one would immediately recognize that there is quite a difference among the geographic districts. In fact, after the initial outbreak in China, the Covid-19 pandemic speedily advanced to Europe and simultaneously to New York City, and afterwards this pandemic spread to South America and East Mediterranean zones. Trying to understand the factors that have profound impact on the pandemic is crucial for bringing the pandemic under control since factors associated with the pandemic must be considered to make public policy and medical decisions. ABO blood types are attributed to diverse infectious diseases like malaria, HIV and influenza (1) (2) (3) (4) . It has been reported that among the confirmed Covid-19 infection cases that were treated in the hospitals the proportion of blood type A was significantly higher than that of blood type B (5), and furthermore it has been reported that the severity and clinical outcome of the Covid-19 infection disease were associated with blood types (6) . However, in these previous studies the study subjects were in a relatively small number and/or limited locality so that the data cover only a regional geographic zone and do not reveal the worldwide geographically uneven distribution of Covid-19 infection. Furthermore, the dynamics of Covid-19 had not been dealt with worldwide. We therefore conducted this big-data-analysis on association between dynamics of Covid-19 pandemic and ABO blood types. The big data are derived from the official database presented by World Health Organization (WHO). ABO blood type distribution serves as a typical genetic marker for geographic distribution over the globe for diverse diseases as well as public health issues. Finding out any factors that are attributed to Covid-19 infection might be thus important in fighting Covid-19 pandemics. For an epidemic of an infectious disease the dynamic development of the infection is determinant, and this can be assessed by several parameters classically used, that are among others infection case growth rate (ICGR), infection case doubling time (IC-dt) reproductive number (RN), death case growth rate (DCGR) ,and death case doubling time (DC-dt). The difficulty to determine these parameters is that the current high dynamic in the infection development worldwide so that an endpoint of total infection number remains yet unreached. Instead, we tried to assess on the mid-way of the exponential phase of infection the infection cases and death cases, which was performed based on the epidemical curves of the involved countries displayed by JHU. This study sought to investigate the relationship between the distribution of blood group types and the epidemic dynamics of Covid-19 infection based on analyses of big data that cover worldwide population majority. For analysis of the pandemic of Covid-19 infection the population of six geographic regions divided according
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