Patient characteristics and testing over COVID-19 waves 1 and 2 from the first German COVID-19 testing unit in Munich, Germany.

BACKGROUND: In Munich, the first German case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was detected on 27 January 2020 at the Division of Infectious Diseases and Tropical Medicine of the University Hospital LMU Munich (DIDTM), and consecutively the Covid Testing Unit was established. Germany advocated several public health measures to control the outbreak. This study investigates the effects of measures on health service utilization in the public, which in turn can alter case numbers and test positivity rates. METHOD: Our retrospective observational study was conducted to determine the effects of public health measures on the utilization of a testing facility and positivity rates from the first operational COVID-19 testing facility in Munich for waves 1 and 2 over a period of 14 months. This was accomplished by comparing trends in client characteristics including age, gender, symptoms, and socio-demographic aspects over time to non-pharmaceutical measures in Germany. To depict trend changes in testing numbers over time, we developed a negative binomial model with multiple breakpoints. RESULTS: In total 9861 tests were conducted on 6989 clients. The clients were mostly young (median age: 34), female (60.58%), and asymptomatic (67.89%). Among those who tested positive for SARS-CoV-2, 67.72% were symptomatic while the percentage was 29.06% among those who tested negative. There are other risk factors, but a SARS-CoV-2-positive colleague at work is the most prominent factor. Trend changes in the clients' testing numbers could be attributed to the implementation of various public health measures, testing strategies, and attitudes of individuals toward the pandemic. However, test positivity rates did not change substantially during the second wave of the pandemic. CONCLUSION: We could show that implementation or changes in public health measures have a strong effect on the utilization of testing facilities by the general public, which independently of the true epidemiological background situation can result in changing test numbers.

COVID-19 Testing Unit Munich: Impact of Public Health and Safety Measures on Patient Characteristics and Test Results, January to September 2020.

To assess the course of the COVID-19 pandemic and the impact of non-pharmaceutical interventions, the number of reported positive test results is frequently used as an estimate of the true number of population-wide infections. We conducted a retrospective observational analysis of patient data of the Corona Testing Unit (CTU) in Munich, Bavaria, Germany between January 27th, and September 30th, 2020. We analyzed the course of daily patient numbers over time by fitting a negative binomial model with multiple breakpoints. Additionally, we investigated possible influencing factors on patient numbers and characteristics by literature review of policy papers and key informant interviews with individuals involved in the set-up of the CTU. The 3,963 patients included were mostly young (median age: 34, interquartile range: 27-48), female (66.2%), and working in the healthcare sector (77%). For these, 5,314 real-time RT-PCR tests were conducted with 157 (2.94%) positive results. The overall curve of daily tests and positive results fits the re-ported state-wide incidence in large parts but shows multiple breakpoints with considerable trend changes. These can be most fittingly attributed to testing capacities and -strategies and individual risk behavior, rather than public health measures. With the large impact on patient numbers and pre-test probabilities of various strategic and operational factors, we consider the derived re-ported incidence as a poor measurement to base policy decisions on. Testing units should be prepared to encounter these fluctuations with a quickly adaptable structure.