@article{LiangBencurovaPsotaetal.2021,
  author    = {Liang, Chunguang and Bencurova, Elena and Psota, Eric and Neurgaonkar, Priya and Prelog, Martina and Scheller, Carsten and Dandekar, Thomas},
  title     = {Population-predicted MHC class II epitope presentation of SARS-CoV-2 structural proteins correlates to the case fatality rates of COVID-19 in different countries},
  series = {International Journal of Molecular Sciences},
  volume    = {22},
  journal   = {International Journal of Molecular Sciences},
  number    = {5},
  issn      = {1422-0067},
  doi       = {10.3390/ijms22052630},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-258936},
  year      = {2021},
  abstract  = {We observed substantial differences in predicted Major Histocompatibility Complex II (MHCII) epitope presentation of SARS-CoV-2 proteins for different populations but only minor differences in predicted MHCI epitope presentation. A comparison of this predicted epitope MHC-coverage revealed for the early phase of infection spread (till day 15 after reaching 128 observed infection cases) highly significant negative correlations with the case fatality rate. Specifically, this was observed in different populations for MHC class II presentation of the viral spike protein (p-value: 0.0733 for linear regression), the envelope protein (p-value: 0.023), and the membrane protein (p-value: 0.00053), indicating that the high case fatality rates of COVID-19 observed in some countries seem to be related with poor MHC class II presentation and hence weak adaptive immune response against these viral envelope proteins. Our results highlight the general importance of the SARS-CoV-2 structural proteins in immunological control in early infection spread looking at a global census in various countries and taking case fatality rate into account. Other factors such as health system and control measures become more important after the early spread. Our study should encourage further studies on MHCII alleles as potential risk factors in COVID-19 including assessment of local populations and specific allele distributions.},
  language  = {en}
}
@article{PradaMaagSiegmundetal.2022,
  author    = {Prada, Juan Pablo and Maag, Luca Estelle and Siegmund, Laura and Bencurova, Elena and Liang, Chunguang and Koutsilieri, Eleni and Dandekar, Thomas and Scheller, Carsten},
  title     = {Estimation of R0 for the spread of SARS-CoV-2 in Germany from excess mortality},
  series = {Scientific Reports},
  volume    = {12},
  journal   = {Scientific Reports},
  number    = {1},
  doi       = {10.1038/s41598-022-22101-7},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-301415},
  year      = {2022},
  abstract  = {For SARS-CoV-2, R0 calculations in the range of 2-3 dominate the literature, but much higher estimates have also been published. Because capacity for RT-PCR testing increased greatly in the early phase of the Covid-19 pandemic, R0 determinations based on these incidence values are subject to strong bias. We propose to use Covid-19-induced excess mortality to determine R0 regardless of RT-PCR testing capacity. We used data from the Robert Koch Institute (RKI) on the incidence of Covid cases, Covid-related deaths, number of RT-PCR tests performed, and excess mortality calculated from data from the Federal Statistical Office in Germany. We determined R0 using exponential growth estimates with a serial interval of 4.7 days. We used only datasets that were not yet under the influence of policy measures (e.g., lockdowns or school closures). The uncorrected R0 value for the spread of SARS-CoV-2 based on RT-PCR incidence data was 2.56 (95\% CI 2.52-2.60) for Covid-19 cases and 2.03 (95\% CI 1.96-2.10) for Covid-19-related deaths. However, because the number of RT-PCR tests increased by a growth factor of 1.381 during the same period, these R0 values must be corrected accordingly (R0corrected = R0uncorrected/1.381), yielding 1.86 for Covid-19 cases and 1.47 for Covid-19 deaths. The R0 value based on excess deaths was calculated to be 1.34 (95\% CI 1.32-1.37). A sine-function-based adjustment for seasonal effects of 40\% corresponds to a maximum value of R0January = 1.68 and a minimum value of R0July = 1.01. Our calculations show an R0 that is much lower than previously thought. This relatively low range of R0 fits very well with the observed seasonal pattern of infection across Europe in 2020 and 2021, including the emergence of more contagious escape variants such as delta or omicron. In general, our study shows that excess mortality can be used as a reliable surrogate to determine the R0 in pandemic situations.},
  language  = {en}
}