A Delphi consensus checklist helped assess the need to develop rapid guideline recommendations.

BACKGROUND AND OBJECTIVES: We aimed to develop a checklist to aid guideline developers in determining which scientific or societal cause ("triggers") are relevant when considering to initiate a rapid recommendation procedure. METHODS: We conducted a two-round modified Delphi procedure with a panel of Dutch guideline experts, clinicians, and patient representatives. A previously conducted systematic literature review and semistructured interviews with four science journalists were used to generate a list of potential items. This item list was submitted to the panel for discussion, reduction and refinement into a checklist. RESULTS: Thirteen experts took part. Two questionnaires were completed in which participants scored an initial list of 64 items based on relevance. During two online meetings, the scores were discussed, irrelevant items were removed, and relevant items were reformulated into seven questions. The final "quickscan assessment of the need for a rapid recommendation" covers user perspective, scientific evidence, clinical relevance, clinical practice variation, applicability, quality of care and public health outcomes, and ethical/legal considerations. CONCLUSION: The quickscan aids guideline developers in systematically assessing whether a trigger expresses a valid need for developing a rapid recommendation. Future research could focus on the applicability and validity of the checklist within guideline development programs.

Effectiveness of contact tracing apps for SARS-CoV-2: a rapid systematic review.

OBJECTIVE: To systematically review evidence on effectiveness of contact tracing apps (CTAs) for SARS-CoV-2 on epidemiological and clinical outcomes. DESIGN: Rapid systematic review. DATA SOURCES: EMBASE (OVID), MEDLINE (PubMed), BioRxiv and MedRxiv were searched up to 28 October 2020. STUDY SELECTION: Studies, both empirical and model-based, assessing effect of CTAs for SARS-CoV-2 on reproduction number (R), total number of infections, hospitalisation rate, mortality rate, and other epidemiologically and clinically relevant outcomes, were eligible for inclusion. DATA EXTRACTION: Empirical and model-based studies were critically appraised using separate checklists. Data on type of study (ie, empirical or model-based), sample size, (simulated) time horizon, study population, CTA type (and associated interventions), comparator and outcomes assessed, were extracted. The most important findings were extracted and narratively summarised. Specifically for model-based studies, characteristics and values of important model parameters were collected. RESULTS: 2140 studies were identified, of which 17 studies (2 empirical, 15 model-based studies) were eligible and included in this review. Both empirical studies were observational (non-randomised) studies and at high risk of bias, most importantly due to risk of confounding. Risk of bias of model-based studies was considered low for 12 out of 15 studies. Most studies demonstrated beneficial effects of CTAs on R, total number of infections and mortality rate. No studies assessed effect on hospitalisation. Effect size was dependent on model parameters values used, but in general, a beneficial effect was observed at CTA adoption rates of 20% or higher. CONCLUSIONS: CTAs have the potential to be effective in reducing SARS-CoV-2 related epidemiological and clinical outcomes, though effect size depends on other model parameters (eg, proportion of asymptomatic individuals, or testing delays), and interventions after CTA notification. Methodologically sound comparative empirical studies on effectiveness of CTAs are required to confirm findings from model-based studies.