Tracking changes in SARS-CoV-2 transmission with a novel outpatient sentinel surveillance system in Chicago, USA
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Abstract
Public health indicators typically used for COVID-19 surveillance can be biased or lag changing community transmission patterns. The United States city of Chicago opportunistically investigated whether sentinel surveillance of recently symptomatic individuals receiving outpatient diagnostic testing for SARS-CoV-2 could accurately assess the instantaneous reproductive number R(t) and provide early warning of changes in transmission. Patients tested at community-based diagnostic testing sites between September 2020 and June 2021, and reporting symptom onset within four days preceding their test, formed the sentinel population. R(t) calculated from sentinel cases agreed well with R(t) from other indicators. Retrospectively, trends in sentinel cases did not precede trends in COVID-19 hospital admissions by any identifiable lead time. In deployment, sentinel surveillance held an operational recency advantage of nine days over hospital admissions. The promising performance of opportunistic sentinel surveillance suggests that deliberately designed outpatient sentinel surveillance would provide robust early warning of increasing transmission.
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SciScore for 10.1101/2022.05.10.22274869: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources R(t) estimation: R(t) was estimated from case time series with epyestim v0.1 [27], a Python implementation of the method developed by Cori et al. [30]. Pythonsuggested: (IPython, RRID:SCR_001658)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Even with these limitations related to the sentinel population chosen for this study, estimates of community transmission derived from sentinel cases approximated those of established, hospitalization-based indicators – with a …
SciScore for 10.1101/2022.05.10.22274869: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources R(t) estimation: R(t) was estimated from case time series with epyestim v0.1 [27], a Python implementation of the method developed by Cori et al. [30]. Pythonsuggested: (IPython, RRID:SCR_001658)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Even with these limitations related to the sentinel population chosen for this study, estimates of community transmission derived from sentinel cases approximated those of established, hospitalization-based indicators – with a population based sample and standardized collection of symptom information, such as the UK’s Office for National Statistics Infection Survey [42], the performance and value of this sentinel surveillance model may be enhanced. In Chicago, the low volume of sentinel samples ultimately limited the precision of trends estimated from sentinel surveillance. However, that even a low-volume, unrepresentative, and opportunistic outpatient sentinel surveillance performed fairly well strongly suggests that a deliberate sentinel surveillance system, with high testing volume, routine reporting of date of symptom onset, and representative sampling of outpatient providers, would provide robust early warning. With sufficient sentinel sampling volume, neighborhood-level R(t) estimations should be possible. Under conditions of exponential growth, even 1-2 weeks’ early warning could save lives.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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