Additional file 1 of From first to second wave: follow-up of the prospective COVID-19 cohort (KoCo19) in Munich (Germany)
Creators: name: Radon, Katja
name: Bakuli, Abhishek
name: Pütz, Peter
name: Le Gleut, Ronan
name: Guggenbuehl Noller, Jessica Michelle
name: Olbrich, Laura
name: Saathoff, Elmar
name: Garí, Mercè
name: Schälte, Yannik
name: Frahnow, Turid
name: Wölfel, Roman
name: Pritsch, Michael
name: Rothe, Camilla
name: Pletschette, Michel
name: Rubio-Acero, Raquel
name: Beyerl, Jessica
name: Metaxa, Dafni
name: Forster, Felix
name: Thiel, Verena
name: Castelletti, Noemi
name: Rieß, Friedrich
name: Diefenbach, Maximilian N.
name: Fröschl, Günter
name: Bruger, Jan
name: Winter, Simon
name: Frese, Jonathan
name: Puchinger, Kerstin
name: Brand, Isabel
name: Kroidl, Inge
name: Wieser, Andreas
name: Hoelscher, Michael
name: Hasenauer, Jan
name: Fuchs, Christiane
Publisher: name: figshare
Year: 2021
Subjects: subject: Medicine
subject: Biotechnology
subject: Biological Sciences not elsewhere classified
subject: Mental Health
subject: Infectious Diseases
subject: FOS: Health sciences
subject: Virology
subject: Computational Biology

description: Additional file 1: Figure S1. For sensitivity and specificity adjusted (left) and unadjusted (right) SARS-CoV-2 sero-prevalence over the follow-up period excluding DBS intermediates. The 95% confidence intervals for the weekly sero-prevalence are based on the 2.5 and 97.5 percentiles from 5,000 repetitions of a cluster bootstrap that accounts for within household clustering. The estimates do not account for sample weights. Figure S2. Comparison of the sero-positivity over the follow-up period accounting for sampling weights. Figure S3. Sero-prevalence estimates across the different boroughs of Munich using CAR model priors with a single level of spatial autocorrelation as random effects. Figure S4. Sero-prevalence estimates across the different boroughs of Munich with CAR model priors through the dissimilarity of the population density in neighbouring boroughs for spatial autocorrelation. Figure S5. Distribution of mean within-cluster variance of test results under 10,000 random permutation of cluster assignments, with clusters being households, buildings, and geospatial clusters of different sizes. Household membership left invariant for building and geospatial clusters. Left: Value distribution. Right: 50%, 95%, 99% CIs. Black lines (left) and dots (right) indicate the observed values. Table S1. Comparison of the follow-up plasma results, using DBS or Venous Blood Samples. Table S2. Comparison of the estimates for the covariate of population density at the constituency level using the Poisson and the negative binomial model. Table S3. Course of SARS-CoV-2 antibody status within the KoCo19 follow-up participants. Table S4. Summary across age group and sex for the response to the behaviour questionnaires stratified by sex. p-values are from Pearson’s Chi-squared test with simulated p-value (based on 10000 replicates). Table S5. Summary across age group and sex for the response to the behaviour questionnaires stratified by age group. p- values are from Pearson’s Chi-squared test with simulated p-value (based on 10000 replicates).