Rate and predictive parameters of novel Coronavirus 2019 (Sars-CoV-2) infections in a German General Practice

Moritz Paar*, Christoph Strumann, Heinz Giesen

*Corresponding author for this work


Key Points: In our clinical cross-sectional study, we identified 107 of 347 patients who were tested positive for antibodies of novel Coronavirus 2019 (SARS-CoV-2). Main symptoms were exhaustion and cough, exposition to other COVID-19-patients appeared frequently. Background: There is urgent need for information on predictive parameters on immunity and infectivity in Coronavirus disease-2019 (COVID-19) pandemic. Our aim was to investigate distribution of novel Coronavirus 2019 (SARS-CoV-2) infections in a German General Practice and to learn about possible predictive parameters regarding infection and pathways of transmission. Methods: In our cross-sectional study, we tested 347 patients of our General Practice using 2019-nCoV-2-IgG/IgM antibody test [2019-nCoV2 IgG/IgM Rapid Test Cassette (Ref.: INCP-402/INCP-402B; ACRO, BIOTECH, INC.)]. We asked for 13 specific symptoms and 4 questions to investigate patients’ surroundings. Results: A total of 107 of 347 patients were tested positive for antibodies (Immunoglobulin M-positive and/or Immunoglobulin G-positive). In antibody-positive group, body aches and rhinorrhea were seen more often and there were significantly less asymptomatic patients. Stay in area of risk was significantly more frequent in antibody-positive group as well as contact to infected persons. Distribution of other symptoms was not significantly different between both groups. Most adults or children with SARS-CoV-2 infection presented with mild flu-like symptoms. Conclusion: A total of 30% of patients had antibodies. It was not possible to identify one solid predictive symptom. Serological testing may be helpful for the diagnosis of suspected patients with negative RT-PCR results and for the identification of asymptomatic infections.

Original languageEnglish
JournalIrish Journal of Medical Science
Publication statusPublished - 2021

Research Areas and Centers

  • Research Area: Center for Population Medicine and Public Health (ZBV)

DFG Research Classification Scheme

  • 205-02 Public Health, Health Services Research and Social Medicine

Coronavirus related work

  • Research on SARS-CoV-2 / COVID-19


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