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Review 1: "COVID-19 Cases and Hospitalizations Averted by Case Investigation and Contact Tracing in the United States"

Published onJul 27, 2022
Review 1: "COVID-19 Cases and Hospitalizations Averted by Case Investigation and Contact Tracing in the United States"
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key-enterThis Pub is a Review of
COVID-19 cases and hospitalizations averted by case investigation and contact tracing in the United States

ABSTRACTImportanceEvidence of the impact of COVID-19 Case Investigation and Contact Tracing (CICT) programs is lacking. Policymakers need this evidence to assess its value.ObjectiveEstimate COVID-19 cases and hospitalizations averted nationwide by US states’ CICT programs.DesignWe combined data from US CICT programs (e.g., proportion of cases interviewed, contacts notified or monitored, and days to case and contact notification) with incidence data to model CICT impacts over 60 days period (November 25, 2020 to January 23, 2021) during the height of the pandemic. We estimated a range of impacts by varying assumed compliance with isolation and quarantine recommendations.SettingUS States and TerritoriesParticipantsFifty-nine state and territorial health departments that received federal funding supporting COVID-19 pandemic response activities were eligible for inclusion. Of these, 22 states and 1 territory reported all measures necessary for the analysis. These 23 jurisdictions covered 42.5% of the US population (140 million persons), spanned all 4 census regions, and reported data that reflected all 59 federally funded CICT programs.InterventionPublic health case investigation and contact tracingMain Outcomes and MeasuresCases and hospitalizations averted; percent of cases averted among cases not prevented by vaccination and other non-pharmaceutical interventions (other NPIs).ResultsWe estimated 1.11 million cases and 27,231 hospitalizations were averted by CICT programs under a scenario where 80% of interviewed cases and monitored contacts, and 30% of notified contacts fully complied with isolation and quarantine guidance, eliminating their contributions to future transmission. As many as 1.36 million cases and 33,527 hospitalizations could have been prevented if all interviewed cases and monitored contacts had entered into and fully complied with isolation and quarantine guidelines upon being interviewed or notified. Across all scenarios and jurisdictions, CICT averted a median of 21.2% (range: 1.3% – 65.8%) of the cases not prevented by vaccination and other NPIs.Conclusions and RelevanceCICT programs likely had a substantial role in curtailing the pandemic in most jurisdictions during the winter 2020-2021 peak. Differences in impact across jurisdictions indicate an opportunity to further improve CICT effectiveness. These estimates demonstrate the potential benefits from sustaining and improving these programs.KEY POINTSQuestionWhat were the health impacts of COVID-19 case investigation and contact tracing programs (CICT) in the US?FindingsBy combining CICT program data from 22 states and 1 territory with mathematical modeling, we estimate CICT averted between 1.11 to 1.36 million cases and 27,231 to 33,527 hospitalizations over 60 days during the height of the pandemic (winter 2020-21). The upper estimate assumes all interviewed cases and monitored contacts complied with isolation and quarantine guidelines, while the lower estimate assumes fractions of interviewed cases and monitored or notified contacts did so.MeaningCICT programs likely played a critical role in curtailing the pandemic.

RR:C19 Evidence Scale rating by reviewer:

  • Potentially informative. The main claims made are not strongly justified by the methods and data, but may yield some insight. The results and conclusions of the study may resemble those from the hypothetical ideal study, but there is substantial room for doubt. Decision-makers should consider this evidence only with a thorough understanding of its weaknesses, alongside other evidence and theory. Decision-makers should not consider this actionable, unless the weaknesses are clearly understood and there is other theory and evidence to further support it.



Given the routine use and very significant resources devoted to CICT, it is critically important for decision-makers to understand the magnitude of benefit from this infection control measure. However, given the many logistical complexities and multiple variables at play, many of which are not well understood for COVID-19, it is recognized that this is enormously difficult in any real-world study and that there are few available studies addressing this key question.

Overall, while this work provides support for the benefit of CICT largely consistent with previous work, the quantitative estimate of the magnitude of that benefit cannot be reviewed as reliable. As the authors acknowledge, the estimate of the median percent of cases averted by CICT of 21.2% from the current study is half that of the estimate of 42.3% from an earlier, smaller study by this group using essentially the same approach and it is unclear why. Within this study, when the ranges of the estimated outcomes are provided, they are very wide. For example, for the estimate of 21.2% cases averted the range is 1% – 66% while for the number cases of averted in the West under an assumption of high CICT effectiveness, the reported result is 24,326 (5,721-252,325). The authors do address some of these uncertainties when discussing the more detailed results and acknowledge limitations in explaining how their findings vary between jurisdictions and their two studies. However, the proposed explanations should be regarded as speculative and, at times, appear contradictory. A higher number of incident COVID-19 cases is offered both to explain an estimate of more cases being averted in jurisdictions with larger populations but also as potentially burdening health departments and compromising CICT effectiveness to account for their lower estimate compared to their earlier study when there were fewer incident cases. This uncertainty and instability in their estimates are not immediately apparent when the main findings of cases and hospitalizations averted are presented in the abstract, which report simply the point estimates from the models of low and high CICT effectiveness.

Modelling results are only as accurate as the assumptions that are applied. In this case, a key assumption impacting the results is the degree of compliance with isolation and quarantine. The values from the literature cited by these investigators refer to studies from diagnosed cases, not those with potential exposure only, and therefore represent estimates of compliance with isolation, not quarantine. While published estimates of compliance in the literature are very limited, most reported results are much lower than the values of 80% for interviewed cases and monitored contacts and 30% of notified contacts used in this study even for the low estimate model. The authors cite a UK study reporting 40-45% self-reported compliance with isolation. It was unclear how this number was selected as this study reported 18.2% of respondents experiencing COVID-19 symptoms in the last seven days not leaving home since developing symptoms. Compliance with quarantine in this study was reported as 10.9% but not cited by these authors. The assumptions of the low estimate model are likely unrealistically high with respect to compliance which may explain why the aggregated results for cases and hospitalizations averted from the two models are close to each other.

Since our solicitation of reviews, this preprint has been published in JAMA journal and the link to the published manuscript can be found here.

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