Two-factor factorial randomized multi-arm parallel controlled trial of four SARS-CoV-2 surveillance strategies in representative population sample points.

BACKGROUND: The SARS-CoV-2 pandemic is characterized by a constant risk of a rapid increase in infection burden due to the emergence of new variants with higher transmissibility and immune escape. Monitoring the SARS-CoV-2 pandemic has so far mainly relied on passive surveillance, which yields biased epidemiological measures due to the disproportionate number of undetected asymptomatic cases. In contrast, active surveillance could provide more accurate estimates of the true SARS-CoV-2 prevalence that help to forecast the evolution of the pandemic, enabling evidence-based decision-making. OBJECTIVE: The objective of this study was to compare four different approaches of active SARS-CoV-2 surveillance, focusing on feasibility and epidemiological outcomes. METHODS: The randomized, two-factor factorial, multi-arm parallel trial was conducted in 2020 in a German district with 700,000 inhabitants. The epidemiological outcome comprised the SARS-CoV-2 prevalence and its precision. The four study arms combined two factors: i) individuals versus households, ii) direct testing versus testing conditioned on symptom pre-screening. Individuals seven years and older were eligible. Altogether, 27,908 addresses from general population representative samples of 51 municipalities were randomly allocated to the arms and 15 consecutive recruitment weekdays. Data collection and logistics were highly digitized, a website in five languages enabled low-barrier registration and tracking of results. Gargle sample collection kits were sent by post. Participants collected a gargle sample at home and mailed it to the laboratory. Samples were analyzed with RT-LAMP, positive/weak results were confirmed with RT-qPCR. RESULTS: Recruitment took place between 18 November and 11 December 2020. The response rates in the four arms varied between 34% and 41%. The pre-screening classified 17% as COVID-19 symptomatic. Altogether, 4,232 persons without pre-screening and 7,623 participating in the pre-screening provided 5,351 gargle samples, of which 5,319 (99%) could be analyzed, yielding 17 confirmed SARS-CoV-2 infections and a combined prevalence of 0.36% (95% CI [0.14%; 0.59%]) in the arms without, respectively 0.05% (95% CI [0.00%; 0.108%]) with pre-screening (initial contacts only). In more detail, we found a prevalence of 0.31% (95% CI [0.06; 0.58]), respectively 0.35% (95% CI [0.09; 0.6], household members included), and lower estimates with pre-screening (0.07% (95% CI [0.0; 0.15], respectively with household members 0.02 (95% CI [0.0; 0.06]). Asymptomatic infections occurred in 3/11 positive cases with symptom data. The two arms without pre-screening performed best regarding effectiveness and accuracy. CONCLUSIONS: This study has shown that the combination of postal mailing of gargle sample kits as well as returning home-based self-collected liquid gargle samples and a subsequent analysis with high-sensitivity RT-LAMP is generally a feasible way to conduct active SARS-CoV-2 population surveillance without burdening routine diagnostic testing. Efforts to improve participation rates and to facilitate integration into the public health system may increase the potential to effectively monitor the course of the pandemic. CLINICALTRIAL: The trial was registered (30 November 2020) at the German Clinical Trials Register, registration number DRKS00023271. INTERNATIONAL REGISTERED REPORT: RR2-10.1186/s13063-021-05619-5.

Kopfkino: Phases of quarantine among asymptomatic SARS-COV-2 carriers in Germany.

Although a majority of SARS-COV-2 diagnosis are asymptomatic, presymptimatic or minimally symptomatic, little has been described and understood about the illness careers of these individuals. This study explored the lived experience of a SARS-COV-2 diagnosis and subsequent quarantine among individuals in Germany who were diagnosed with SARS-COV-2 during the second wave of the pandemic (late 2020-early 2021), but whose diagnosis was unexpected due to a lack of a known contact, or the asymptomatic nature of their case at the time of diagnosis. In-depth interviews (n â€‹= â€‹22) were conducted by phone or video call, audio-recorded, and transcribed verbatim. Routine debriefings guided data collection and facilitated analysis, which followed a framework approach. Regardless of age, gender or socioeconomic status, data consistently demonstrated a diagnosis and quarantine career marked by five emotional phases: overconfidence, shock and denial, coming to grips and asking questions, enduring, and cautious optimism as quarantine ended. These experiences suggest that providing trustworthy, easily accessible information regarding certain key aspects of the post diagnosis and quarantine period could benefit patients in terms of reducing stress, understanding the consequences of a diagnosis and mitigating foreseeable challenges in terms of personal, logistical and emotional issues. Follow-up research with providers and public health bureaus could inform how to best tailor such messaging for clients who experience an unexpected diagnosis.

Scalable RT-LAMP-based SARS-CoV-2 testing for infection surveillance with applications in pandemic preparedness.

Throughout the SARS-CoV-2 pandemic, limited diagnostic capacities prevented sentinel testing, demonstrating the need for novel testing infrastructures. Here, we describe the setup of a cost-effective platform that can be employed in a high-throughput manner, which allows surveillance testing as an acute pandemic control and preparedness tool, exemplified by SARS-CoV-2 diagnostics in an academic environment. The strategy involves self-sampling based on gargling saline, pseudonymized sample handling, automated RNA extraction, and viral RNA detection using a semiquantitative multiplexed colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay with an analytical sensitivity comparable with RT-qPCR. We provide standard operating procedures and an integrated software solution for all workflows, including sample logistics, analysis by colorimetry or sequencing, and communication of results. We evaluated factors affecting the viral load and the stability of gargling samples as well as the diagnostic sensitivity of the RT-LAMP assay. In parallel, we estimated the economic costs of setting up and running the test station. We performed > 35,000 tests, with an average turnover time of < 6 h from sample arrival to result announcement. Altogether, our work provides a blueprint for fast, sensitive, scalable, cost- and labor-efficient RT-LAMP diagnostics, which is independent of potentially limiting clinical diagnostics supply chains.

From disgusting and complicated to simple and brilliant: Implementation perspectives and lessons learned from users and rejectors of mail-in SARS-CoV-2 gargle tests.

Background: Despite the important role of testing as a measure against the COVID-19 pandemic, user perspectives on SARS-CoV-2 tests remain scarce, inhibiting an improvement of testing approaches. As the world enters the third year of the pandemic, more nuanced perspectives of testing, and opportunities to expand testing in a feasible and affordable manner merit consideration. Methods: Conducted amid the second pandemic wave (late 2020-early 2021) during and after a multi-arm trial evaluating SARS-CoV-2 surveillance strategies in the federal state Baden-Württemberg, Germany, this qualitative sub-study aimed to gain a deeper understanding of how test users and test rejectors perceived mail-in SARS-CoV-2 gargle tests. We conducted 67 semi-structured in-depth interviews (mean duration: 60 min) via telephone or video call. Interviews were audio-recorded, transcribed verbatim and analyzed inductively using thematic analysis. The Consolidated Framework for Implementation Research guided the findings' presentation. Results: Respondents generally described gargle sampling as simple and comfortable. However, individual perceptions of the testing method and its feasibility varied widely from disgusting and complicated to simple and brilliant. Self-sampling was appreciated for lowering infection risks during testing, but also considered more complex. Gargle-sampling increased participants' self-efficacy to sample correctly. Communication (first contact, quantity and content of information, reminders, support system) and trust (in the study, its institutional affiliation and test method) decisively influenced the intervention's acceptability. Conclusion: User-driven insights on how to streamline testing include: consider communication, first impressions of tests and information as key for successful mail-in testing; pay attention to the role of mutual trust between those taking and administering tests; implement gargle self-sampling as a pleasant alternative to swab testing; offer multiple test methods to increase test up-take.

From disgusting and complicated to simple and brilliant: Implementation perspectives and lessons learned from users and rejectors of mail-in SARS-CoV-2 gargle tests

Background Despite the important role of testing as a measure against the COVID-19 pandemic, user perspectives on SARS-CoV-2 tests remain scarce, inhibiting an improvement of testing approaches. As the world enters the third year of the pandemic, more nuanced perspectives of testing, and opportunities to expand testing in a feasible and affordable manner merit consideration. Methods Conducted amid the second pandemic wave (late 2020–early 2021) during and after a multi-arm trial evaluating SARS-CoV-2 surveillance strategies in the federal state Baden-Württemberg, Germany, this qualitative sub-study aimed to gain a deeper understanding of how test users and test rejectors perceived mail-in SARS-CoV-2 gargle tests. We conducted 67 semi-structured in-depth interviews (mean duration: 60 min) via telephone or video call. Interviews were audio-recorded, transcribed verbatim and analyzed inductively using thematic analysis. The Consolidated Framework for Implementation Research guided the findings' presentation. Results Respondents generally described gargle sampling as simple and comfortable. However, individual perceptions of the testing method and its feasibility varied widely from disgusting and complicated to simple and brilliant. Self-sampling was appreciated for lowering infection risks during testing, but also considered more complex. Gargle-sampling increased participants' self-efficacy to sample correctly. Communication (first contact, quantity and content of information, reminders, support system) and trust (in the study, its institutional affiliation and test method) decisively influenced the intervention's acceptability. Conclusion User-driven insights on how to streamline testing include: consider communication, first impressions of tests and information as key for successful mail-in testing;pay attention to the role of mutual trust between those taking and administering tests;implement gargle self-sampling as a pleasant alternative to swab testing;offer multiple test methods to increase test up-take.

Cost and cost-effectiveness of four different SARS-CoV-2 active surveillance strategies: evidence from a randomised control trial in Germany.

INTRODUCTION: The COVID-19 pandemic has entered its third year and continues to affect most countries worldwide. Active surveillance, i.e. testing individuals irrespective of symptoms, presents a promising strategy to accurately measure the prevalence of SARS-CoV-2. We aimed to identify the most cost-effective active surveillance strategy for COVID-19 among the four strategies tested in a randomised control trial between 18th November 2020 and 23rd December 2020 in Germany. The four strategies included: (A1) direct testing of individuals; (A2) direct testing of households; (B1) testing conditioned on upstream COVID-19 symptom pre-screening of individuals; and (B2) testing conditioned on upstream COVID-19 symptom pre-screening of households. METHODS: We adopted a health system perspective and followed an activity-based approach to costing. Resource consumption data were collected prospectively from a digital individual database, daily time records, key informant interviews and direct observations. Our cost-effectiveness analysis compared each strategy with the status quo and calculated the average cost-effective ratios (ACERs) for one primary outcome (sample tested) and three secondary outcomes (responder recruited, case detected and asymptomatic case detected). RESULTS: Our results showed that A2, with cost per sample tested at 52,89 EURO, had the lowest ACER for the primary outcome, closely followed by A1 (63,33 EURO). This estimate was much higher for both B1 (243,84 EURO) and B2 (181,06 EURO). CONCLUSION: A2 (direct testing at household level) proved to be the most cost-effective of the four evaluated strategies and should be considered as an option to strengthen the routine surveillance system in Germany and similar settings.

Authors' response: Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias.

We thank van Tongeren et al for responding to our study on occupational disparities in SARS-CoV-2 infection risks during the first pandemic wave in Germany (1). The authors address the potential for bias resulting from differential testing between occupational groups and propose an alternative analytical strategy for dealing with selective testing. In the following, we want to discuss two aspects of this issue, namely (i) the extent and reasons of differential testing in our cohort and (ii) the advantages and disadvantages of different analytical approaches to study risk factors for SARS-CoV-2 infection. Our study relied on nationwide prospective cohort data including more than 100 000 workers in order to compare the incidence of infections between different occupations and occupational status positions. We found elevated infection risks in personal services and business administration, in essential occupations (including health care) and among people in higher occupational status positions (ie, managers and highly skilled workers) during the first pandemic wave in Germany (2). Van Tongeren's et al main concern is that the correlations found could be affected by a systematic bias because people in healthcare professions get tested more often than employees in other professions. A second argument is that better-off people could be more likely to use testing as they are less affected by direct costs (prices for testing) and the economic hardship associated with a positive test result (eg, loss of earnings in the event of sick leave). We share the authors' view that differential testing must be considered when analysing and interpreting the data. Thus, in our study, we examined the proportion of tests conducted in each occupational group as part of the sensitivity analyses (see supplementary figure S1, accessible at www.sjweh.fi/article/4037). As expected, testing proportions were exceptionally high in medical occupations (due to employer requirements). However, we did not observe systematic differences among non-medical occupations or when categorising by skill-level or managerial responsibility. This might be explained by several reasons. First, SARS-CoV-2 testing was free of charge during the first pandemic wave in Germany, but reporting a risk contact or having symptoms was a necessary condition for testing ( https://www.bundesgesundheitsministerium.de/coronavirus/chronik-coronavirus.html (accessed 5 September 2022). The newspaper article cited by van Tongeren et al is misleading as it refers to a calendar date after our study period. Second, different motivation for testing due to economic hardship in case of a positive test result is an unlikely explanation, because Germany has a universal healthcare system, including paid sick leave and sickness benefits for all workers (3). Self-employed people carry greater financial risks in case of sickness. We therefore included self-employment in the multivariable analyses to address this potential source of bias. While the observed inverse social gradient may be surprising, it actually matches with findings of ecological studies from Germany (4, 5), the United States (6, 7) as well as Spain, Portugal, Sweden, The Netherlands, Israel, and Hong Kong (8), all of which observed higher infection rates in wealthier neighbourhoods during the initial outbreak phase of the pandemic. One possible explanation is the higher mobility of managers and better educated workers, who are more likely to participate in meetings and engage in business travel and holiday trips like skiing. Given the increasing number of studies providing evidence for this hypothesis, we conclude that the inverse social gradient in our study likely reflects different exposure probabilities and is not a result of systematic bias. This also holds true for the elevated infection risks in essential workers, which is actually corroborated by a large body of research (9-11). Regarding differential likelihood of testing, van Tongeren et al state that "[i]t is relatively simple to address this problem by using a test-negative design" (1). As van Tongeren et al describe, this is a case-control approach only including individuals who were tested (without considering those who were not tested). However, the proposed analytical strategy can lead to another (more serious) selection bias if testing proportions and/or testing criteria differ between groups (12). This can be easily illustrated when comparing the results based on a time-incidence design with those obtained by a test-negative design as shown in table 1 (see PDF). Both approaches show similar results in terms of vertical occupational differences. Infection was more common if individuals had a high skill level or had a managerial position, but associations were stronger in the time-incidence design and did not reach statistical significance in the test-negative design (as indicated by the confidence intervals overlapping "1"). Unfortunately, the test-negative approach relies on a strongly reduced sample size and thus results in greater statistical uncertainty and loss of statistical power (13). In contrast, the test-negative design yields a different picture when estimating the association between essential occupation and infection risk: In this analysis, essential workers did not differ from non-essential workers in their chance of being infected with SARS-CoV-2 (the test-negative design even exhibits a lower chance for essential workers). This is rather counter-intuitive and is not in accordance with what we know about the occupational hazards of healthcare workers during the pandemic (14). The main problem is that proportions of positive tests are highly unreliable when testing proportions and/or testing criteria differ between groups. As essential workers were tested more often without being symptomatic (due to employer requirements), a lower proportion of positive tests in this group does not necessarily correspond to a lower risk of infection. Consequently, we are not convinced that the test-negative design should be the 'gold standard' for studying risk factors for SARS-CoV-2 infections (15). Especially problematic is the loss of statistical power (increasing the probability of a type II error) and the low validity of the test-positivity when test criteria and/or test proportions differ between groups. References 1. van Tongeren M, Rhodes S, Pearce N. Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias. Scand J Work Environ Health 2022;48(7):586-587. https://doi.org/10.5271/sjweh.4052. 2. Reuter M, Rigó M, Formazin M, Liebers F, Latza U, Castell S, et al. Occupation and SARS-CoV-2 infection risk among 108 960 workers during the first pandemic wave in Germany. Scand J Work Environ Health 2022;48:446-56. https://doi.org/10.5271/sjweh.4037. 3. Busse R, Blümel M, Knieps F, Bärnighausen T. Statutory health insurance in Germany: a health system shaped by 135 years of solidarity, self-governance, and competition. Lancet 2017;390:882-97. https://doi.org/10.1016/S0140-6736(17)31280-1. 4. Wachtler B, Michalski N, Nowossadeck E, Diercke M, Wahrendorf M, Santos-Hövener C, et al. Socioeconomic inequalities in the risk of SARS-CoV-2 infection - First results from an analysis of surveillance data from Germany. J Heal Monit 2020;5:18-29. https://doi.org/10.25646/7057. 5. Plümper T, Neumayer E. The pandemic predominantly hits poor neighbourhoods? SARS-CoV-2 infections and COVID-19 fatalities in German districts. Eur J Public Health 2020;30:1176-80. https://doi.org/10.1093/eurpub/ckaa168. 6. Abedi V, Olulana O, Avula V, Chaudhary D, Khan A, Shahjouei S, et al. Racial, Economic, and Health Inequality and COVID-19 Infection in the United States. J Racial Ethn Heal Disparities 2021;8:732-42. https://doi.org/10.1007/s40615-020-00833-4. 7. Mukherji N. The Social and Economic Factors Underlying the Incidence of COVID-19 Cases and Deaths in US Counties During the Initial Outbreak Phase. Rev Reg Stud 2022;52. https://doi.org/10.52324/001c.35255. 8. Beese F, Waldhauer J, Wollgast L, Pförtner T, Wahrendorf M, Haller S, et al. Temporal Dynamics of Socioeconomic Inequalities in COVID-19 Outcomes Over the Course of the Pandemic-A Scoping Review. Int J Public Health 2022;67:1-14. https://doi.org/10.3389/ijph.2022.1605128. 9. Nguyen LH, Drew DA, Graham MS, Joshi AD, Guo C-G, Ma W, et al. Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study. Lancet Public Heal 2020;5:e475-83. https://doi.org/10.1016/S2468-2667(20)30164-X. 10. Chou R, Dana T, Buckley DI, Selph S, Fu R, Totten AM. Epidemiology of and Risk Factors for Coronavirus Infection in Health Care Workers. Ann Intern Med 2020;173:120-36. https://doi.org/10.7326/M20-1632. 11. Stringhini S, Zaballa M-E, Pullen N, de Mestral C, Perez-Saez J, Dumont R, et al. Large variation in anti-SARS-CoV-2 antibody prevalence among essential workers in Geneva, Switzerland. Nat Commun 2021;12:3455. https://doi.org/10.1038/s41467-021-23796-4. 12. Accorsi EK, Qiu X, Rumpler E, Kennedy-Shaffer L, Kahn R, Joshi K, et al. How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19. Eur J Epidemiol 2021;36:179-96. https://doi.org/10.1007/s10654-021-00727-7. 13. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd Editio. New York: Routledge; 2013. https://doi.org/10.4324/9780203771587. 14. The Lancet. The plight of essential workers during the COVID-19 pandemic. Lancet 2020;395:1587. https://doi.org/10.1016/S0140-6736(20)31200-9. 15. Vandenbroucke JP, Brickley EB, Pearce N, Vandenbroucke-Grauls CMJE. The Evolving Usefulness of the Test-negative Design in Studying Risk Factors for COVID-19. Epidemiology 2022;33:e7-8. https://doi.org/10.1097/EDE.0000000000001438.

Occupation and SARS-CoV-2 infection risk among 108 960 workers during the first pandemic wave in Germany.

OBJECTIVE: The aim of this study was to identify the occupational risk for a SARS-CoV-2 infection in a nationwide sample of German workers during the first wave of the COVID-19 pandemic (1 February-31 August 2020). METHODS: We used the data of 108 960 workers who participated in a COVID follow-up survey of the German National Cohort (NAKO). Occupational characteristics were derived from the German Classification of Occupations 2010 (Klassifikation der Berufe 2010). PCR-confirmed SARS-CoV-2 infections were assessed from self-reports. Incidence rates (IR) and incidence rate ratios (IRR) were estimated using robust Poisson regression, adjusted for person-time at risk, age, sex, migration background, study center, working hours, and employment relationship. RESULTS: The IR was 3.7 infections per 1000 workers [95% confidence interval (CI) 3.3-4.1]. IR differed by occupational sector, with the highest rates observed in personal (IR 4.8, 95% CI 4.0-5.6) and business administration (IR 3.4, 95% CI 2.8-3.9) services and the lowest rates in occupations related to the production of goods (IR 2.0, 95% CI 1.5-2.6). Infections were more frequent among essential workers compared with workers in non-essential occupations (IRR 1.95, 95% CI 1.59-2.40) and among highly skilled compared with skilled professions (IRR 1.36, 95% CI 1.07-1.72). CONCLUSIONS: The results emphasize higher infection risks in essential occupations and personal-related services, especially in the healthcare sector. Additionally, we found evidence that infections were more common in higher occupational status positions at the beginning of the pandemic.

Effectiveness and cost-effectiveness of four different strategies for SARS-CoV-2 surveillance in the general population (CoV-Surv Study): study protocol for a two-factorial randomized controlled multi-arm trial with cluster sampling.

BACKGROUND: To achieve higher effectiveness in population-based SARS-CoV-2 surveillance and to reliably predict the course of an outbreak, screening, and monitoring of infected individuals without major symptoms (about 40% of the population) will be necessary. While current testing capacities are also used to identify such asymptomatic cases, this rather passive approach is not suitable in generating reliable population-based estimates of the prevalence of asymptomatic carriers to allow any dependable predictions on the course of the pandemic. METHODS: This trial implements a two-factorial, randomized, controlled, multi-arm, prospective, interventional, single-blinded design with cluster sampling and four study arms, each representing a different SARS-CoV-2 testing and surveillance strategy based on individuals' self-collection of saliva samples which are then sent to and analyzed by a laboratory. The targeted sample size for the trial is 10,000 saliva samples equally allocated to the four study arms (2500 participants per arm). Strategies differ with respect to tested population groups (individuals vs. all household members) and testing approach (without vs. with pre-screening survey). The trial is complemented by an economic evaluation and qualitative assessment of user experiences. Primary outcomes include costs per completely screened person, costs per positive case, positive detection rate, and precision of positive detection rate. DISCUSSION: Systems for active surveillance of the general population will gain more importance in the context of pandemics and related disease prevention efforts. The pandemic parameters derived from such active surveillance with routine population monitoring therefore not only enable a prospective assessment of the short-term course of a pandemic, but also a more targeted and thus more effective use of local and short-term countermeasures. TRIAL REGISTRATION: ClinicalTrials.gov DRKS00023271 . Registered November 30, 2020, with the German Clinical Trials Register (Deutsches Register Klinischer Studien).

Effectiveness and cost-effectiveness of four different strategies for SARS-CoV-2 surveillance in the general population (CoV-Surv Study): a structured summary of a study protocol for a cluster-randomised, two-factorial controlled trial.

OBJECTIVES: In this cluster-randomised controlled study (CoV-Surv Study), four different "active" SARS-CoV-2 testing strategies for general population surveillance are evaluated for their effectiveness in determining and predicting the prevalence of SARS-CoV-2 infections in a given population. In addition, the costs and cost-effectiveness of the four surveillance strategies will be assessed. Further, this trial is supplemented by a qualitative component to determine the acceptability of each strategy. Findings will inform the choice of the most effective, acceptable and affordable strategy for SARS-CoV-2 surveillance, with the most effective and cost-effective strategy becoming part of the local public health department's current routine health surveillance activities. Investigating its everyday performance will allow us to examine the strategy's applicability to real time prevalence prediction and the usefulness of the resulting information for local policy makers to implement countermeasures that effectively prevent future nationwide lockdowns. The authors would like to emphasize the importance and relevance of this study and its expected findings in the context of population-based disease surveillance, especially in respect to the current SARS-CoV-2 pandemic. In Germany, but also in many other countries, COVID-19 surveillance has so far largely relied on passive surveillance strategies that identify individuals with clinical symptoms, monitor those cases who then tested positive for the virus, followed by tracing of individuals in close contact to those positive cases. To achieve higher effectiveness in population surveillance and to reliably predict the course of an outbreak, screening and monitoring of infected individuals without major symptoms (about 40% of the population) will be necessary. While current testing capacities are also used to identify such asymptomatic cases, this rather passive approach is not suitable in generating reliable population-based estimates of the prevalence of asymptomatic carriers to allow any dependable predictions on the course of the pandemic. To better control and manage the SARS-CoV-2 pandemic, current strategies therefore need to be complemented by an active surveillance of the wider population, i.e. routinely conducted testing and monitoring activities to identify and isolate infected individuals regardless of their clinical symptoms. Such active surveillance strategies will enable more effective prevention of the spread of the virus as they can generate more precise population-based parameters during a pandemic. This essential information will be required in order to determine the best strategic and targeted short-term countermeasures to limit infection spread locally. TRIAL DESIGN: This trial implements a cluster-randomised, two-factorial controlled, prospective, interventional, single-blinded design with four study arms, each representing a different SARS-CoV-2 testing and surveillance strategy. PARTICIPANTS: Eligible are individuals age 7 years or older living in Germany's Rhein-Neckar Region who consent to provide a saliva sample (all four arms) after completion of a brief questionnaire (two arms only). For the qualitative component, different samples of study participants and non-participants (i.e. eligible for study, but refuse to participate) will be identified for additional interviews. For these interviews, only individuals age 18 years or older are eligible. INTERVENTION AND COMPARATOR: Of the four surveillance strategies to be assessed and compared, Strategy A1 is considered the gold standard for prevalence estimation and used to determine bias in other arms. To determine the cost-effectiveness, each strategy is compared to status quo, defined as the currently practiced passive surveillance approach. Strategy A1: Individuals (one per household) receive information and study material by mail with instructions on how to produce a saliva sample and how to return the sample by mail. Once received by the laboratory, the sample is tested for SARS-CoV-2 using Reverse Transcription Loop-mediated Isothermal Amplification (RT-LAMP). Strategy A2: Individuals (one per household) receive information and study material by mail with instructions on how to produce their own as well as saliva samples from each household member and how to return these samples by mail. Once received by the laboratory, the samples are tested for SARS-CoV-2 using RT-LAMP. Strategy B1: Individuals (one per household) receive information by mail on how to complete a brief pre-screening questionnaire which asks about COVID-19 related clinical symptoms and risk exposures. Only individuals whose pre-screening score crosses a defined threshold, will then receive additional study material by mail with instructions on how to produce a saliva sample and how to return the sample by mail. Once received by the laboratory, the saliva sample is tested for SARS-CoV-2 using RT-LAMP. Strategy B2: Individuals (one per household) receive information by mail on how to complete a brief pre-screening questionnaire which asks about COVID-19 related clinical symptoms. Only individuals whose pre-screening score crosses a defined threshold, will then receive additional study material by mail with instructions how to produce their own as well as saliva samples from each household member and how to return these samples by mail. Once received by the laboratory, the samples are tested for SARS-CoV-2 using RT-LAMP. In each strategy, RT-LAMP positive samples are additionally analyzed with qPCR in order to minimize the number of false positives. MAIN OUTCOMES: The identification of the one best strategy will be determined by a set of parameters. Primary outcomes include costs per correctly screened person, costs per positive case, positive detection rate, and precision of positive detection rate. Secondary outcomes include participation rate, costs per asymptomatic case, prevalence estimates, number of asymptomatic cases per study arm, ratio of symptomatic to asymptomatic cases per study arm, participant satisfaction. Additional study components (not part of the trial) include cost effectiveness of each of the four surveillance strategies compared to passive monitoring (i.e. status quo), development of a prognostic model to predict hospital utilization caused by SARS-CoV-2, time from test shipment to test application and time from test shipment to test result, and perception and preferences of the persons to be tested with regard to test strategies. RANDOMISATION: Samples are drawn in three batches of three continuous weeks. Randomisation follows a two-stage process. First, a total of 220 sampling points have been allocated to the three different batches. To obtain an integer solution, the Cox-algorithm for controlled rounding has been used. Afterwards, sample points have been drawn separately per batch, following a probability proportional to size (PPS) random sample. Second, for each cluster the same number of residential addresses is randomly sampled from the municipal registries (self-weighted sample of individuals). The 28,125 addresses drawn per municipality are then randomly allocated to the four study arms A1, A2, B1, and B2 in the ratio 5 to 2.5 to 14 to 7 based on the expected response rates in each arm and the sensitivity and specificity of the pre-screening tool as applied in strategy B1 and B2. Based on the assumptions, this allocation should yield 2500 saliva samples in each strategy. Although a municipality can be sampled by multiple batches and the overall number of addresses per municipality might vary, the number of addresses contacted in each arm is kept constant. BLINDING (MASKING): The design is single-blinded, meaning the staff conducting the SARS-CoV-2 tests are unaware of the study arm assignment of each single participant and test sample. SAMPLE SIZES: Total sample size for the trial is 10,000 saliva samples equally allocated to the four study arms (i.e. 2,500 participants per arm). For the qualitative component, up to 60 in-depth interviews will be conducted with about 30 study participants (up to 15 in each arm A and B) and 30 participation refusers (up to 15 in each arm A and B) purposefully selected from the quantitative study sample to represent a variety of gender and ages to explore experiences with admission or rejection of study participation. Up to 25 asymptomatic SARS-CoV-2 positive study participants will be purposefully selected to explore the way in which asymptomatic men and women diagnosed with SARS-CoV-2 give meaning to their diagnosis and to the dialectic between feeling concurrently healthy and yet also being at risk for transmitting COVID-19. In addition, 100 randomly selected study participants will be included to explore participants' perspective on testing processes and implementation. TRIAL STATUS: Final protocol version is "Surveillance_Studienprotokoll_03Nov2020_v1_2" from November 3, 2020. Recruitment started November 18, 2020 and is expected to end by or before December 31, 2020. TRIAL REGISTRATION: The trial is currently being registered with the German Clinical Trials Register (Deutsches Register Klinischer Studien), DRKS00023271 ( https://www.drks.de/drks_web/navigate.do?navigationId=trial . HTML&TRIAL_ID=DRKS00023271). Retrospectively registered 30 November 2020. FULL PROTOCOL: The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.

COVID-19-related knowledge, attitudes and practices: a mixed-mode cross-sectional survey in Liberia.

OBJECTIVES: To examine the knowledge, attitudes and practices (KAP) of COVID-19 of rural and urban residents in Liberia to inform the development of local social and behaviour change communication strategies. DESIGN: Cross-sectional, mixed-mode (online and telephone) survey using non-probability sampling. SETTING: All 15 counties in Liberia with a focus on Maryland County. PARTICIPANTS: From 28 May to 28 June 2020, data were collected from a total of 431 adults aged 18 years and older (telephone 288 (66.8%); online 143 (33.2%)) out of a total of 741 contacts. MAIN OUTCOME MEASURES: KAP scores. Frequencies and proportions were calculated, followed by univariate and multivariable analyses to examine the association between KAP scores and the sociodemographic variables. RESULTS: Around 69% of the online survey respondents were younger than 35 years of age, compared with 56% in the telephone interviews. The majority (87%) of online respondents had completed tertiary education, compared with 77% of the telephone respondents. Male participants, on average, achieved higher knowledge (52%) and attitude scores (72%), in contrast to females (49% and 67%, respectively). Radio (71%) was the most cited source for COVID-19 information, followed by social media (63%). After controlling for sociodemographic variables, adaptive regression modelling revealed that survey mode achieved 100% importance for predicting knowledge and practice levels with regard to COVID-19. CONCLUSIONS: The survey population demonstrated moderate COVID-19 knowledge, with significant differences between survey mode and educational level. Correct knowledge of COVID-19 was associated with appropriate practices in Maryland County. Generalisation of survey findings must be drawn carefully owing to the limitations of the sampling methods. Yet, given the differences in knowledge gaps between survey modes, sex, education, occupation and place of residence, it is recommended that information is tailored to different audiences.

Simulation of pooled-sample analysis strategies for COVID-19 mass testing.

OBJECTIVE: To evaluate two pooled-sample analysis strategies (a routine high-throughput approach and a novel context-sensitive approach) for mass testing during the coronavirus disease 2019 (COVID-19) pandemic, with an emphasis on the number of tests required to screen a population. METHODS: We used Monte Carlo simulations to compare the two testing strategies for different infection prevalences and pooled group sizes. With the routine high-throughput approach, heterogeneous sample pools are formed randomly for polymerase chain reaction (PCR) analysis. With the novel context-sensitive approach, PCR analysis is performed on pooled samples from homogeneous groups of similar people that have been purposively formed in the field. In both approaches, all samples contributing to pools that tested positive are subsequently analysed individually. FINDINGS: Both pooled-sample strategies would save substantial resources compared to individual analysis during surge testing and enhanced epidemic surveillance. The context-sensitive approach offers the greatest savings: for instance, 58-89% fewer tests would be required for a pooled group size of 3 to 25 samples in a population of 150 000 with an infection prevalence of 1% or 5%. Correspondingly, the routine high-throughput strategy would require 24-80% fewer tests than individual testing. CONCLUSION: Pooled-sample PCR screening could save resources during COVID-19 mass testing. In particular, the novel context-sensitive approach, which uses pooled samples from homogeneous population groups, could substantially reduce the number of tests required to screen a population. Pooled-sample approaches could help countries sustain population screening over extended periods of time and thereby help contain foreseeable second-wave outbreaks.