BACKGROUND AND OBJECTIVES

Test-to-stay concepts apply serial testing of children in daycare after exposure to SARS-CoV-2 without use of quarantine. This study aims to assess the safety of a test-to-stay screening in daycare facilities.

METHODS

714 daycare facilities and approximately 50 000 children ≤6 years in Cologne, Germany participated in a SARS-CoV-2 Pool-polymerase chain reaction (PCR) screening from March 2021 to April 2022. The screening initially comprised post-exposure quarantine and was adapted to a test-to-stay approach during its course. To assess safety of the test-to-stay approach, we explored potential changes in frequencies of infections among children after the adaptation to the test-to-stay approach by applying regression discontinuity in time (RDiT) analyses. To this end, PCR-test data were linked with routinely collected data on reported infections in children and analyzed using ordinary least squares regressions.

RESULTS

219 885 Pool-PCRs and 352 305 Single-PCRs were performed. 6440 (2.93%) Pool-PCRs tested positive, and 17 208 infections in children were reported. We estimated that during a period of 30 weeks, the test-to-stay concept avoided between 7 and 20 days of quarantine per eligible daycare child. RDiT revealed a 26% reduction (Exp. Coef: 0.74, confidence interval 0.52–1.06) in infection frequency among children and indicated no significant increase attributable to the test-to-stay approach. This result was not sensitive to adjustments for 7-day incidence, season, SARS-CoV-2 variant, and socioeconomic status.

CONCLUSIONS

Our analyses provide evidence that suggest safety of the test-to-stay approach compared with quarantine measures. This approach offers a promising option to avoid use of quarantine after exposure to respiratory pathogens in daycare settings.

What’s Known on This Subject:

Test-to-stay approaches have been demonstrated to safely supplant quarantine after SARS-CoV-2 exposure of school children older than 6 years.

What This Study Adds:

This study affirms safety of test-to-stay approaches and extends the evidence to daycare settings and children younger than 6 years.

During the COVID-19 pandemic, daycare facilities were closed to mitigate infections.1 ,2  Systematic screenings for SARS-CoV-2 infections contributed to daycare reopenings, counteracting the profound impact of stay-at-home orders on the development and health of children.1 ,3 6  However, burden of post-exposure quarantine for children exposed to infected children persisted amid rising incidence of infections.7  Test-to-stay approaches supplanted the conventional practice of post-exposure quarantine by frequent serial testing for 5 to 10 subsequent days and reduced the burden of post-exposure quarantine.8 16  Safety of test-to-stay approaches, expressed as equivalence in infections as compared with quarantine approaches, was addressed by several studies.8 16  These reports are mostly restricted to screenings in schools and included the use of facemasks. Thus, evidence on safety of test-to-stay concepts in daycare facilities, without the use of facemasks, and in an age-group less capable of sticking to hygiene rules, is limited.

We previously reported on a city-wide SARS-CoV-2 Pool-polymerase chain reaction (PCR) screening in more than 700 daycare facilities in Cologne, Germany.17  After the reported period that included post-exposure quarantine measures, the screening was adapted to a test-to-stay approach and was continued for 30 weeks (March 2021–April 2022). Our study aimed to investigate the safety of this test-to-stay approach. The corresponding research question was “What is the safety of a test-to-stay approach in daycare as compared to a quarantine approach?”. We hypothesized that safety can be assumed if no substantial increase in frequencies of infections among children in Cologne after the adaptation of the screening concept is detectable.

Analyses were performed under a protocol approved by the institutional review board of the Medical Faculty of the University of Cologne (21-1358).

The screening was implemented under the direction of the Youth Welfare Office of Cologne and accompanied by a team of members of the health authorities of Cologne, the University Hospital of Cologne, and a private diagnostic laboratory (Labor Quade). Samples were collected using the Lolli-Method, with a previously determined sensitivity and specificity of 93% to 100% and 100%, respectively (Fig 1).17 19  It consists of sucking a nasopharyngeal swab for 30 seconds and subsequent testing in SARS-CoV-2 Pool-PCR. Samples were collected voluntarily by the children under supervision and support of the daycare staff members or parents. For pool-testing, each child of a daycare group placed a Lolli-swab in a common collection tube. This tube was tested in one PCR-reaction. When a Pool-PCR tested negative, all children of that pool were assumed to be SARS-CoV-2 negative. When a Pool-PCR tested positive, the respective children were retested individually on the next day in Single-PCRs. The identification of an infected child was followed by the isolation of this child. Children exposed to this child were quarantined up to 14 days (median duration 10 days; interquartile range [IQR]: 8–12; Supplemental Fig 6), depending on the specifications of the current Infection Protection Act and the individual situation of the respective contact. During the test-to-stay approach, exposed children were not quarantined but tested in Lolli-Single-PCRs for 5 subsequent days. If tested negative, they could continue to go to daycare.

FIGURE 1

Overview on the screening concept and its specifications. Flowchart depicting the screening concept and both “Quarantine” and “Test-to-stay” approaches.

FIGURE 1

Overview on the screening concept and its specifications. Flowchart depicting the screening concept and both “Quarantine” and “Test-to-stay” approaches.

Close modal

PCR-test Data

PCRs were performed at the Institute of Virology, University Hospital Cologne, and at Labor Quade. Labor Quade reported PCR test data to the Institute of Virology, containing the date of sampling, specimen (Pool- or Single-PCR), test result, and daycare ID (Supplemental Fig 7). During weeks 15 to 17 in 2021, daycare facilities were enrolled gradually, and the data collection system was under construction and misclassified the specimen of positive PCRs. These weeks were excluded from all analyses. Pool sizes were reported as weekly average pool size per daycare facility.

SARS-CoV-2 Index Cases and Contact Persons

The health authorities of Cologne provided data on newly reported SARS-CoV-2 infections (“index cases”) and contact persons recorded with a software developed for the documentation and case management of SARS-CoV-2 in Cologne.20  The data contained the date of the first SARS-CoV-2 detection or the date of the beginning and the end of the quarantine, age, sex, and the zip code of the place of residency (Supplemental Fig 7).

Frequencies of SARS-CoV-2 Variants of Concern and 7-day Incidence

Data on Germany-wide proportions of all reported sequences of variants of concern (VOCs) were collected as part of a national surveillance system and published by the Robert Koch Institute.21  The 7-day incidence was extracted from SurvStat@RKI2.0, an online tool for querying notifiable infectious diseases in Germany.22 

Inhabitants and Socioeconomic Factors of Cologne

Aggregated data on the number of inhabitants in 2020 and socioeconomic factors were published online or provided by the Office for Urban Development and Statistics of Cologne.23 

We reported counts and fractions of total and positive Pool-and Single-PCRs. Pool sizes were reported as median of the weekly mean pool sizes per daycare facility. Cumulative numbers of PCR analyses were estimated by multiplication of the counts of Pool-PCRs with the weekly median pool size and addition of the Single-PCRs. We calculated Spearman correlation coefficient to quantify the association between the weekly fraction of positive Pool-PCRs and the 7-day incidence.

We estimated the amount of quarantine that was avoided by the test-to-stay approach with the following equations:
Exposed children = (Median pool size1)*Pool-PCRs
(1)
where 1 was subtracted from Median pool size to account for one assumed index case within 1 positive pool. Positive Pool-PCRs represents the number of positive Pool-PCRs during the test-to-stay approach. We assumed that all exposed children would have been quarantined in the absence of the test-to-stay approach.
Avoidedquarantinedays = Exposedchildren * Mediandurationofquarantine
(2)
where Median duration of quarantine (days) referred to the screening approach involving quarantine after exposure.

To account for the variability of the individual parameters, we derived a variability range for the days of avoided quarantine by multiplying the first or third quartile of the pool size with the number of positive Pool-PCRs (equation 1) and the exposed children with the first or third quartile of the duration of quarantine (equation 2). The days of avoided quarantine per eligible child were estimated, dividing the number of avoided quarantine days by the number of inhabitants in Cologne aged 2 to 6 years (n = 51 830), assuming that those were eligible for the screening.

Outcome

The outcome for the regression discontinuity in time (RDiT) was defined as the weekly count of index cases aged 2 to 6 years in Cologne divided by the weekly count of positive Pool-PCRs (Supplemental Fig 8). We assumed that an infected child in a daycare facility would be detected in the screening and the corresponding positive Pool-PCR would contribute to the denominator of the outcome. We expected that secondary infections would occur in the daycare facility. The infected child and the secondary infections would be reported to the health authorities and contribute to the count of reported index cases aged 2 to 6 years in Cologne, which, in addition to the reported infections in children that were acquired elsewhere than at daycare, defined the numerator of the outcome. We hypothesized that the transition from the quarantine approach to the test-to-stay approach might affect the number of secondary infections and, thus, the outcome.

Analyses were restricted to weeks that did not meet the criteria of low-testing periods as we expected that in those, the denominator of the outcome would be underestimated (eg, during roll-out of the screening or holiday seasons). We defined a low-testing period as a week in which less than 70% of the average weekly count of Pool-PCRs during the entire screening were performed.

RDiT Framework

We followed current best practice for RDiT.24 26  The interruption was defined as the change of the test concept from a quarantine approach to a test-to-stay approach (Supplemental Fig 9). A lag-period of 2 weeks, in which observations were censored, followed the interruption to account for the SARS-CoV-2 incubation period and to allow the newly introduced test concept to be fully implemented.27  We applied triangular kernel weights to assign higher weights to observations lying closer to the interruption, a common strategy in RDiT to address time-dependent bias or confounders, such as changes in immunization. We modeled the outcome based on a Gamma regression with the following equation:
Y = β0 + β1*(Time) + β2*(Testconcept)+ β3*(Time*Testconcept) + e
(3)
where Y is the outcome. β0 is the intercept. Time is the running variable (weeks). β1 reflects the slope before the interruption. Test concept is a dummy variable (0 = quarantine; 1 = test-to-stay). β2 describes the effect of the interruption on the outcome. The interaction term Time * Test concept allows for the slope of the regression line to differ on either side of the interruption (β3). ε is the error term. Coefficients were exponentiated and interpreted on a multiplicative scale. The presence of autocorrelation was assessed with plots of functions of autocorrelation and partial autocorrelation.

Data-driven Optimal Bandwidth Calculation

The width of the time period (“bandwidth”) drawn around the interruption is an important choice in RDiT.24 ,25  We determined a mean squared error (MSE)-optimal bandwidth, minimizing the MSE of the regression fit.28 ,29  We examined variations of the β2-coefficient across different bandwidth choices (1, 1.25, 1.5, 1.75, and 2 times the MSE-optimal bandwidth).

Robustness Check

We extended the model specification given in equation (3) to a second-order polynomial regression instead of a linear regression (Appendix 1).

Testing Continuity of Baseline Covariates

RDiT requires continuity of baseline covariates across the interruption.24 ,25  This verifies that changes in the outcome are attributable to the defined interruption and not to coincident changes of covariates. Continuity was assessed with the help of the RDiT framework by applying local linear regressions. Assuming normal distribution, we modeled the median pool size, the fraction of the Delta variant, the 7-day incidence, and the weekly fraction of susceptible children (Appendix 2).

Sensitivity Analyses

We included the 7-day incidence, the seasons, and the fraction of the respective SARS-CoV-2 variant in Germany in the Gamma regression model (Supplemental Information, Appendix A). We ran stratified analyses for districts with low and middle or high socioeconomic status (SES), as well as age-ranges of the reported index cases (2–3 years and 4–6 years) (Appendix 3).30 

Analyses were performed using Microsoft Excel for Mac (v.14.7.3.), Prism 9.0 (GraphPad) and R within RStudio (v. 2023.03.0 + 386) and additional R packages.31 33 

The screening was conducted from March 2021 to April 2022 in Cologne, Germany (1.1 million inhabitants). All daycare facilities in Cologne and 51 830 children aged 2 to 6 years were eligible to participate twice weekly. The quarantine approach was conducted from week 11 to 36 (2021) and was substituted by the test-to-stay approach from week 37 (2021) to week 14 (2022) (Table 1, Fig 2). During the screening, 714 daycare facilities participated, 4 VOCs emerged (Alpha, Beta, BA.1, and BA.2), and the SARS-CoV-2 7-day incidence in Cologne ranged from 8.67 infections per 100 000 inhabitants (week 25, 2021) to 2573 (week 9, 2022) (Supplemental Fig 10).

TABLE 1

Summary of the Screening Program

CharacteristicsQuarantine Approachan (%)Test-to-stay Approach n (%)Entire Screening n (%)
Duration    
 Time period Week 11 2021–week 36 2021 Week 37 2021–week 14 2022 Week 11 2021–week 14 2022 
 Weeks 26 30 56 
Daycare facilities    
 Total 694 712 714 
Pool-PCRs    
 Total 87 856 132 029 219 885 
 Positivea 142 (0.16) 6298 (4.77) 6440 (2.93) 
Single-PCRs    
 Total 5704 346 601 352 305 
 Positivea 111 12 343 12 454 
Index cases (2–6 y in Cologne)    
 Total 1203 16 005 17 208 
CharacteristicsQuarantine Approachan (%)Test-to-stay Approach n (%)Entire Screening n (%)
Duration    
 Time period Week 11 2021–week 36 2021 Week 37 2021–week 14 2022 Week 11 2021–week 14 2022 
 Weeks 26 30 56 
Daycare facilities    
 Total 694 712 714 
Pool-PCRs    
 Total 87 856 132 029 219 885 
 Positivea 142 (0.16) 6298 (4.77) 6440 (2.93) 
Single-PCRs    
 Total 5704 346 601 352 305 
 Positivea 111 12 343 12 454 
Index cases (2–6 y in Cologne)    
 Total 1203 16 005 17 208 
a

During the roll-out of the screening (weeks 15–17 in 2021), daycare facilities were enrolled gradually, and the data collection system was under construction and misclassified the specimen of positive PCRs. Thus, these weeks were excluded from all analyses.

FIGURE 2

Implementation of the screening concept in daycare facilities. The number of tested daycare facilities, performed PCRs, median pool sizes, and cumulative number of performed analyses are stratified by calendar week. The horizontal lines in the Box-Whisker-Plot indicate the medians, the lines at the top and at the bottom of the boxes indicate first and third quartiles and the error bars represent minimum and maximum pool sizes. Data on pool sizes were not available during the roll-out.

FIGURE 2

Implementation of the screening concept in daycare facilities. The number of tested daycare facilities, performed PCRs, median pool sizes, and cumulative number of performed analyses are stratified by calendar week. The horizontal lines in the Box-Whisker-Plot indicate the medians, the lines at the top and at the bottom of the boxes indicate first and third quartiles and the error bars represent minimum and maximum pool sizes. Data on pool sizes were not available during the roll-out.

Close modal

219 885 Pool-PCRs and 352 305 Single-PCRs were performed. Median of weekly mean pool sizes per daycare facility was 11.5 (IQR: 8–14.6) swabs per pool (Supplemental Fig 11). Approximately 2 897 437 SARS-CoV-2 analyses were performed in total (Table 1, Fig 2). Of the Pool-PCRs, 6440 (2.93%) tested positive (Table 1, Fig 3A). The fraction of positive Pool-PCRs ranged from 0.0% in weeks 24 to 27 (2021) to 12.44% in week 9 (2022) (Supplemental Fig 12) and correlated strongly with the total SARS-CoV-2 7-day incidence in Cologne (rs = 0.96, CI: 0.94–0.98; Fig 3B). Of the Single-PCRs, 12 454 tested positive. During the entire screening, the health authorities in Cologne reported 17 208 index cases among children aged 2 to 6 years (Table 1, Fig 3A). Subsequently, our estimation suggests that the screening identified 72.4% of all reported index cases aged 2 to 6 years in Cologne.

FIGURE 3

Detection of SARS-CoV-2 infections in daycare facilities. (A) the number and fraction of positive Pool-PCRs and the number of reported index cases (2–6 years) are stratified by calendar week. During the roll-out of the screening (weeks 15, 16, 17 in 2021) the data collection system misclassified the specimen (Pool or Single-PCR) of positive PCRs. Thus, data on positive PCRs are not available for these weeks. (B) Spearman correlation between 7-day incidence in Cologne and fraction of positive Pool-PCRs. Each black dot represents 1 week. 95% CI is indicated by the bright red area.

FIGURE 3

Detection of SARS-CoV-2 infections in daycare facilities. (A) the number and fraction of positive Pool-PCRs and the number of reported index cases (2–6 years) are stratified by calendar week. During the roll-out of the screening (weeks 15, 16, 17 in 2021) the data collection system misclassified the specimen (Pool or Single-PCR) of positive PCRs. Thus, data on positive PCRs are not available for these weeks. (B) Spearman correlation between 7-day incidence in Cologne and fraction of positive Pool-PCRs. Each black dot represents 1 week. 95% CI is indicated by the bright red area.

Close modal

During the test-to-stay approach, 6298 Pool-PCRs tested positive (Table 1). The median duration of quarantine after exposure to SARS-CoV-2 of children aged 2 to 6 years in Cologne was 10 days (IQR: 8–12) (Supplemental Fig 6). Consequently, we estimated that 661 290 days (variability range: 352 688–1 027 833) spent in quarantine were avoided during the test-to-stay approach. This translated to 13 days (variability range: 7–20) of avoided quarantine per eligible daycare child during a period of 30 weeks (Fig 4).

FIGURE 4

Estimation of quarantine avoidance. The number of positive Pool-PCRs, pool sizes, estimated contact persons and cumulative estimated avoided days of quarantine are stratified by calendar week. The horizontal lines in the Box-Whisker-Plot indicate the medians, the lines at the top and at the bottom of the boxes indicate first and third quartiles and the error bars represent minimum and maximum pool sizes. VR, variability range.

FIGURE 4

Estimation of quarantine avoidance. The number of positive Pool-PCRs, pool sizes, estimated contact persons and cumulative estimated avoided days of quarantine are stratified by calendar week. The horizontal lines in the Box-Whisker-Plot indicate the medians, the lines at the top and at the bottom of the boxes indicate first and third quartiles and the error bars represent minimum and maximum pool sizes. VR, variability range.

Close modal

Applying RDiT analyses, we aimed to assess the safety of the test-to-stay approach in comparison with the quarantine approach with the underlying causal framework depicted in a directed acyclic graph (Supplemental Fig 13, Supplemental Table 2).25  We first incorporated all observations in the Gamma regression model (“global Gamma regression model”), which yielded an exponentiated β2-coefficient of 0.74 (95% CI: 0.52–1.06) (Fig 5A). This translated to 26% less index cases per positive Pool-PCR attributable to the change of the test concept and indicated no substantial increase in infections among children. No clear presence of autocorrelated residuals was detectable (Supplemental Fig 14). To address biases arising from potential unobserved confounders that are not in proximity of the interruption, we gradually narrowed the underlying bandwidth of the global Gamma regression model in a sequence of local Gamma regressions (Fig 5B, Supplemental Fig 15). Overall, the main result of the global Gamma regression model was not sensitive to the choice of the bandwidth, minimizing the risk of bias because of time-dependent factors, such as immunization rates. We verified that the result of the global Gamma regression model was similar when using a second-order polynomial specification instead of a linear regression (Supplemental Fig 16).

FIGURE 5

Assessment of safety of the test-to-stay approach: RDiT. (A) RDiT global Gamma regression model. Model fit, 95% CI and the lag period are indicated in their respective color. (B) Exponentiated coefficient estimates of local Gamma regressions with distinct bandwidths. Error bars indicate 95% CI.

FIGURE 5

Assessment of safety of the test-to-stay approach: RDiT. (A) RDiT global Gamma regression model. Model fit, 95% CI and the lag period are indicated in their respective color. (B) Exponentiated coefficient estimates of local Gamma regressions with distinct bandwidths. Error bars indicate 95% CI.

Close modal

The weekly median pool size (β2 = −0.89, CI: −4.12 to 3.23), the share of the Delta variant (β2 = −0.57, CI: −1.42 to 0.28), and the weekly fraction of susceptible children (β2 = 0.28, CI: −0.07 to 0.63) showed continuity among the interruption. The 7-day incidence did not meet the continuity assumption (β2 = −147, CI: −244 to −49) (Supplemental Fig 17).

We accounted for 7-day incidence, seasons, and SARS-CoV-2 variant in separate global models and detected no substantial differences of the corresponding effect estimates or their respective precision (Supplemental Fig 18). Stratification by SES and age-range indicated differences between the statistical significance of the β2-coefficients of the analyzed strata but there was no indication of an increase in infection frequency (Supplemental Fig 19 and 20).

This study provided evidence suggesting safety of a SARS-CoV-2 Pool-PCR test-to-stay screening in daycare facilities as compared with a post-exposure quarantine concept. We analyzed one of the most comprehensive test-to-stay screenings in daycare facilities worldwide.34 37  This screening was one of the earliest attempts to disestablish the use of quarantine of daycare children in Germany. Our estimation of the impact of the test-to-stay concept on quarantine avoidance showed a substantial reduction in the time spent in quarantine. Our RDiT analyses did not indicate evidence of a discernible increase in infections after quarantine measures were discontinued.

Post-exposure quarantine effectively serves as mitigation strategy.38 ,39  However, its subsequent disruption of childcare has substantial negative implications for children, such as impairment of cognitive development or executive functions and adverse effects on mental or physical health.40 42  Furthermore, quarantine was shown to negatively impact parents, increasing negative mood or likelihood of losing temper and punishment.43 45  Additionally, high-frequent and unexpected disruption of daycare attendance impacts workforce participation of parents because of the necessity of at-home childcare.44 ,46  Thus, strategies of reducing duration of quarantine are valuable for children and their families but need thorough safety assessment.

Our study advances current evidence on safety of test-to-stay approaches to the setting of daycare, as previous studies were primarily conducted in schools with children and adolescents older than 6 years, and they incorporated the use of facemasks.8 16  In contrast, the screening analyzed in this article was conducted in the absence of the use of facemasks and in an age-group less capable of sticking to hygiene rules. Furthermore, the mentioned studies were conducted during the predominance of one respective SARS-CoV-2 VOC.8 16  In contrast, our analyses spanned a period during which 4 distinct SARS-CoV-2 VOCs have emerged (Alpha, Delta, BA.1, and BA.2). These variants show distinct virological features that could affect the effectiveness of infection control measures (eg, incubation period or basic reproduction number).27 ,47 49  We show that safety of the test-to-stay screening was not affected by these VOCs. Finally, previous studies mainly report on short-term observations with rather small variations in the incidence, whereas our analyses encompass 13 months with low and high incidence periods, providing more generalizable evidence.

One limitation of this study is that the ethical and political circumstances during the COVID-19 pandemic did not justify addressing the research question by a randomized controlled trial, emerging from the initial screening with a quarantine approach. Thus, the quasi-experimental study design differs from the ideal experimental design. Second, as we analyzed aggregated data, we cannot deduce any causal statements on the level of individual children. Further individualization of the data was not possible because of the challenge of matching index cases with their corresponding positive Pool-PCRs. Additionally, matching with contact tracing data was not possible, which does not allow for assessments of changes in infection site or the general risk of infection in daycare, for example by comparing secondary attack rates in daycare with those in households. Third, the risk of bias caused by unmeasured confounders needs to be acknowledged. It might comprise changes in data collection practices of the health authorities or in test indication for SARS-CoV-2 testing beyond the screening. However, we assume that most index cases were constantly reported and recorded, as the screening detected most of all notified index cases among children. Furthermore, we assumed that the risk of confounding or bias, such as changes in immunization, increases with increasing distance from the interruption and applied kernel weights and different bandwidths to address this risk.

The test-to-stay approach substantially reduced the use of quarantine after SARS-CoV-2 exposure. There was no indication of a relevant increase in infections among children with this approach. This highlights it as a safe alternative to quarantine after exposure to SARS-CoV-2 in daycare. Test-to-stay approaches could prove valuable as infection control measures after exposure to emerging respiratory pathogens in daycare during future outbreaks.

The authors thank all children and staff in tested daycare facilities for support and participation; Moritz Lorenz and Paula Lorenz for supporting the development of the Lolli-Method; Sascha Nickel and Anne Fries as well as all staff members of their daycare facilities for their impetus for the development of the Lolli-Method and screening adaptions; all members of the Institute of Virology, University Hospital Cologne; all staff of Labor Quade for conducting the screening and providing data; Stephan Glaremin (Amt für Jugend, Arbeit und Soziales der Stadt Düsseldorf) for administrative support during implementation of the screening in Cologne; Janna Seifried and Sindy Böttcher (Robert Koch Institute) for continuous support and discussions; and Stefan Konigorski and Mayram Ganji (Berlin School of Public Health) for statistical support and discussion.

Dr Dewald designed the screening, implemented the screening, planned the study, conducted the study, wrote the manuscript, and managed the administrative framework; Dr Steger designed the screening, implemented the screening, and helped to interpret the findings; Ms Fish, Ms Torre-Lage, Ms Hellriegel, Ms Milz, Ms Kolb-Bastigkeit, Mr Rubio Quintanares, and Drs Heger and Suárez implemented the screening and designed, planned, and optimized logistics of the screening; Ms Fries, Mr Buess, Mr Marizy, Ms Michaelis, and Dr Kossow partnered as public health scientists, participated in the planning, implementation, and continuous execution of the screening, collected and provided data on SARS-CoV-2 infections in Cologne, and helped to interpret the findings; Drs Pirkl, Aigner, Oberste, Orduz, and Prof Hellmich, and Ms Wong advised statistical analysis, aided in setting up the conceptual framework of the regression discontinuity in time analysis, and helped to interpret the findings; Profs Fätkenheuer and  Dötsch designed, planned, and implemented the screening program and helped to interpret the findings; Drs Moench and Quade implemented the screening, aided the design of the screening, optimized logistics of the screening and data collection system, and collected and provided data on PCR tests; Mr Neumann designed the screening, planned and supervised the implementation of the screening and participated in the continuous execution of the screening; Dr Kaiser designed the screening, implemented the screening, helped to interpret the findings, and managed the administrative framework; Ms Schranz supervised the planning and conducting of the study and manuscript preparation, aided in setting up the conceptual framework of the regression discontinuity in time analysis, and helped to interpret the findings; Prof Klein planned and designed the screening, designed the study, aided the manuscript preparation, and helped to interpret the findings; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

FUNDING: Funding was provided by the German Ministry of Education and Research (BMBF) (registration number: 01KX2021) within Bundesweites Forschungsnetz “Angewandte Surveillance und Testung” (B-FAST) project of the “NaFoUniMedCovid19” consortium. Furthermore, funding was provided by the Bundesministerium für Bildung und Forschung (registration number: ZMI1-2521COR004) and by the German Research Foundation (DFG, CRC 1310). Additionally, funding was provided by EUCARE, EU grant 101046016. Finally, we acknowledge support for the Article Processing Charge from the DFG (German Research Foundation, 491454339), by the German Center for Infection Research (TI 07.001_011) and by the ministry for work, health, and social affairs of the state of North Rhine-Westphalia (CPS-1-1F).

CONFLICT OF INTEREST DISCLOSURES: Felix Dewald, Florian Klein, and Rolf Kaiser hold EU-wide trademark protection for the terms “Lolli-Test” (018503959) and “Lolli-Methode” (018503958). All other authors have indicated they have no conflicts of interest relevant to this article to disclose.

IQR

interquartile range

MSE

mean squared error

PCR

polymerase chain reaction

RDiT

regression discontinuity in time

RKI

Robert Koch Institute

SES

socioeconomic status

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Supplementary data