ABSTRACT
BNT162b2, an mRNA-based SARS-CoV-2 vaccine (Pfizer- BioNTech), is one of the most effective COVID-19 vaccines and has been approved by more than 130 countries worldwide. However, several studies have reported that the COVID-19 vaccine shows high interpersonal variability in terms of humoral and cellular responses, such as those with respect to SARS-CoV-2 spike protein immunoglobulin (Ig)G, IgA, IgM, neutralizing antibodies, and CD4+ & CD8+ T cells. The objective of this study is to investigate the kinetic changes in anti-SARS-CoV-2 spike IgG (IgG-S) profiles and adverse reactions and their associations with HLA profiles among 100 hospital workers from the Center Hospital of the National Center for Global Health and Medicine (NCGM), Tokyo, Japan. DQA1*03:03:01 (p = 0.017;OR 2.80, 95% CI 1.05-7.25) was significantly associated with higher IgG-S production after two doses of BNT162b2 while DQB1*06:01:01:01 (p = 0.028, OR 0.27, 95% CI 0.05-0.94) was significantly associated with IgG-S declines after two doses of BNT162b2. No HLA alleles were significantly associated with either local symptoms or fever. However, C*12:02:02 (p = 0.058;OR 0.42, 95% CI 0.15-1.16), B*52:01:01 (p = 0.031;OR 0.38, 95% CI 0.14-1.03), DQA1*03:02:01 (p = 0.028;OR 0.39, 95% CI 0.15-1.00) and DPB1*02:01:02 (p = 0.024;OR 0.45, 95% CI 0.21-0.97) appeared significantly associated with protection against systemic symptoms after two doses of BNT162b2 vaccination. Further studies with larger sample sizes are clearly warranted to determine HLA allele associations with the production and long-term sustainability of IgG-S after COVID-19 vaccination.
ABSTRACT
As of Feb. 2021, COVID-19 is still spreading. To overcome this infectious disease, COVID-19 vaccines are being developed around the world. In Japan, inoculation of COVID-19 vaccines to people will be starting soon (as of Feb. 2021). However, desirable vaccination strategies are not clear. Therefore, we investigate the relationship between vaccination strategies and COVID-19 spreading using positive-case data in Japan. The method is SIRVD (Susceptible Infected Recovered Vaccination Death) model, which can represent vaccinated persons. Moreover, we discuss desirable vaccination strategies based on the results. © 2022 Japan Industrial Management Association. All rights reserved.
ABSTRACT
Coronavirus disease 2019 (COVID-19) was announced as an outbreak by the World Health Organization (WHO) in January 2020 and as a pandemic in March 2020. The majority of infected individuals have experienced no or only mild symptoms, ranging from fully asymptomatic cases to mild pneumonic disease. However, a minority of infected individuals develop severe respiratory symptoms. The objective of this study was to identify susceptible HLA alleles and clinical markers that can be used in risk prediction models for the early identification of severe COVID-19 among hospitalized COVID-19 patients. A total of 137 patients with mild COVID-19 (mCOVID-19) and 53 patients with severe COVID-19 (sCOVID-19) were recruited from the Center Hospital of the National Center for Global Health and Medicine (NCGM), Tokyo, Japan for the period of February-August 2020. High-resolution sequencing-based typing for eight HLA genes was performed using next-generation sequencing. In the HLA association studies, HLA-A∗11:01:01:01 [Pc = 0.013, OR = 2.26 (1.27-3.91)] and HLA-C∗12:02:02:01∼HLAB∗ 52:01:01:02 [Pc = 0.020, OR = 2.25 (1.24-3.92)] were found to be significantly associated with the severity of COVID-19. After multivariate analysis controlling for other confounding factors and comorbidities, HLAA∗ 11:01:01:01 [P = 3.34E-03, OR = 3.41 (1.50-7.73)], age at diagnosis [P = 1.29E-02, OR= 1.04 (1.01-1.07)] and sex at birth [P = 8.88E-03, OR= 2.92 (1.31-6.54)] remained significant. The area under the curve of the risk prediction model utilizing HLA-A∗11:01:01:01, age at diagnosis, and sex at birth was 0.772, with sensitivity of 0.715 and specificity of 0.717. To the best of our knowledge, this is the first article which describes associations of HLA alleles with COVID-19 at the 4-field (highest) resolution level. Early identification of potential COVID-19 could help clinicians prioritize medical utility and significantly decrease mortality from COVID-19.
ABSTRACT
The effectiveness of the first dose of vaccination for COVID-19 is different from that of the second dose;therefore, in several studies, various mathematical models that can represent the states of the first and second vaccination doses have been developed. Using the results of these studies and considering the effects of the first and second vaccination doses, we can simulate the spread of infectious diseases. The susceptible-infected-recovered-vaccination1-vaccination2-death (SIRVVD) model is one of the proposed mathematical models;however, it has not been sufficiently theoretically analyzed. Therefore, we obtained an analytical expression for the number of infected persons by considering the numbers of susceptible and vaccinated persons as parameters. We used the solution to determine the target vaccination rate for decreasing the infection numbers of the COVID-19 Delta variant (B.1.617) in Japan. Furthermore, we investigated the target vaccination rates for cases with strong or weak variants by comparing with the COVID-19 Delta variant (B.1.617). This study contributes to the mathematical development of the SIRVVD model and provides insights into the target vaccination rate for decreasing the number of infections. Author
ABSTRACT
In the end of 2019, the emergence of COVID-19 was reported and confirmed for the first time, and it triggered an international pandemic. In Japan, the strong tendency to spread of infection is still continuing. The Japanese Government has been raised two concepts to overcome this difficulty. One is the thorough measures to control of the spread of infection and the other is the economic recovery. The government has carried out the corresponding two policies: the use of COVID-19 Contact-Confirming Application (COCOA) and the application of “GoTo Travel Campaign”. We focus on these two policies and study an ideal situation, which enables us to balance more economic recovery and control of the spread of infection. To pursue this goal, we propose a mathematical model to estimate these policies’s effects and conduct simulations of 28 scenarios. In addition, we analyze each result of the simulation and investigate characteristics of each situation. As a result, we clearly find that it required that not only the increasing the using rate of COCOA but also a positive change of people’s behaviors and awareness. © 2021 Institute of Physics Publishing. All rights reserved.
ABSTRACT
As of November 2020, the COVID-19 pandemic continues to rage across the world. One of the measures that has been taken to curb the spread of the virus is blanket stay-at-home orders. Staying at home significantly limits close contact with others and can, thus, decrease the number of new cases. However, if people refrain from going out, this will cause significant economic damage. For this reason, some people think that these orders should be revoked after a short period of time, and people should get out more often. However, if blanket stay-at-home restrictions are lifted before a significant decrease is seen in the number of new cases, the number of infected people is likely to increase within a short period. This will, in turn, hasten the next round of blanket stay-at-home orders and lead to a further reduction in people who can leave their home. Against this backdrop, this study examines below phenomena, through a multi-agent simulation. The early removal strategies of stay-at-home orders for increasing the number of people leaving their homes have the effect of both increasing and decreasing the number of such people. Therefore, we consider the strategies do not lead to a sufficient increase in the overall number of people leaving their homes. To examine these phenomena, we conducted the simulations that consist of six scenarios with the different removal condition of stay-at-home orders. As a result, we could confirm that when more removal conditions of stay-at-home orders were eased, the tendencies of more number of infected people and death people were increasing with some exceptions. In contrast, there were almost no differences among the numbers of people leaving their home of these scenarios. Based on the results, we also examined the possibility of a strategy that covers both infected people and the number of people allowed to leave their homes.