Estimating the efficacy of symptom-based screening for COVID-19

Callahan, Alison; Steinberg, Ethan; Fries, Jason; Gombar, Saurabh; Patel, Birju; Corbin, Conor K.; Shah, Nigam H.

doi:10.1038/s41746-020-0300-0

Cited by 70 publications

(34 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some works criticize the use of symptom-based screening strategies to quantify an individual likelihood of having COVID-19, due to the non-specific nature of some symptoms and the existence of co-infections with other respiratory viruses [8]. However, our results evidenced that such a strategy contributes to optimizing the overall testing strategy.…”

Section: Discussionmentioning

confidence: 73%

App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning

Dantas

Peres

Bastos

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Tests are scarce resources, especially in low and middle-income countries, and the optimization of testing programs during a pandemic is critical for the effectiveness of the disease control. Hence, we aim to use the combination of symptoms to build a regression model as a screening tool to identify people and areas with a higher risk of SARS-CoV-2 infection to be prioritized for testing. Materials and Methods: We applied machine learning techniques and provided a visualization of potential regions with high densities of COVID-19 as a risk map. We performed a retrospective analysis of individuals registered in "Dados do Bem", an app-based symptom tracker in use in Brazil. Results: From April 28 to July 16, 2020, 337,435 individuals registered their symptoms through the app. Of these, 49,721 participants were tested for SARS-CoV-2 infection, being 5,888 (11.8%) positive. Among self-reported symptoms, loss of smell (OR[95%CI]: 4.6 [4.4 - 4.9]), fever (2.6 [2.5 - 2.8]), and shortness of breath (2.1 [1.6-2.7]) were associated with SARS-CoV-2 infection. Our final model obtained a competitive performance, with only 7% of false-negative users among the predicted as negatives (NPV = 0.93). From the 287,714 users still not tested, our model estimated that only 34.5% are potentially infected, thus reducing the need for extensive testing of all registered users. The model was incorporated by the "Dados do Bem" app aiming to prioritize users for testing. We developed an external validation in the state of Goias and found that of the 465 users selected, 52% tested positive. Conclusions: Our results showed that the combination of symptoms might predict SARS-Cov-2 infection and, therefore, can be used as a tool by decision-makers to refine testing and disease control strategies.

show abstract

Section: Discussionmentioning

confidence: 73%

App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning

Dantas

Peres

Bastos

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…In the spring of 2020, the COVID-19 pandemic in the Northern Hemisphere coincided with the seasonal onset of tick exposure, presenting a new risk for confusion in the diagnosis of acute tick-borne disease. Symptom screening for COVID-19 is not specific, even if respiratory symptoms are present [ 11 ]. Using fever alone as a screening tool is highly nonspecific, and in our case, it led physicians to pursue the diagnosis of COVID-19 to the exclusion of other possible causes.…”

Section: Discussionmentioning

confidence: 99%

Lyme Disease in the Era of COVID-19: A Delayed Diagnosis and Risk for Complications

Novak

Scheeler

Aucott

2021

Case Reports in Infectious Diseases

View full text Add to dashboard Cite

We describe a patient with fever and myalgia who did not have COVID-19 but instead had Lyme disease. We propose that the co-occurrence of COVID-19 and Lyme disease during the spring of 2020 resulted in a delayed diagnosis of Lyme disease due to COVID-19 pandemic-related changes in healthcare workflow and diagnostic reasoning. This delayed diagnosis of Lyme disease in the patient we describe resulted in disseminated infection and sixth nerve palsy. We present the use of telemedicine to aid in the diagnosis of Lyme disease and to provide prompt access to diagnosis and care during the ongoing COVID-19 pandemic and in the future.

show abstract

“…At present, little is known about the specific symptoms of COVID-19[ 71 ]. An analysis of the trends of a pandemic is reinforced by open source, public databases with medical annotations.…”

Section: Discussionmentioning

confidence: 99%

“…An analysis of the trends of a pandemic is reinforced by open source, public databases with medical annotations. Medical records on past paths of human mobility should be used to refine the total profile of virus-human relationships with acceptable anonymity[ 71 ]. Since partial data are available at the initial time of deposit, the information may need to continual updates.…”

Section: Discussionmentioning

confidence: 99%

Virus database annotations assist in tracing information on patients infected with emerging pathogens

Nakashima

Takeya

Kuba

et al. 2020

Informatics in Medicine Unlocked

View full text Add to dashboard Cite

The global pandemic of SARS-CoV-2 has disrupted human social activities. In restarting economic activities, successive outbreaks by new variants are concerning. Here, we evaluated the applicability of public database annotations to estimate the virulence, transmission trends and origins of emerging SARS-CoV-2 variants. Among the detectable multiple mutations, we retraced the mutation in the spike protein. With the aid of the protein database, structural modelling yielded a testable scientific hypothesis on viral entry to host cells. Simultaneously, annotations for locations and collection dates suggested that the variant virus emerged somewhere in the world in approximately February 2020, entered the USA and propagated nationwide with periodic sampling fluctuation likely due to an approximately 5-day incubation delay. Thus, public database annotations are useful for automated elucidation of the early spreading patterns in relation to human behaviours, which should provide objective reference for local governments for social decision making to contain emerging substrains. We propose that additional annotations for past paths and symptoms of the patients should further assist in characterizing the exact virulence and origins of emerging pathogens.

show abstract

Estimating the efficacy of symptom-based screening for COVID-19

Cited by 70 publications

References 14 publications

App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning

App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning

Lyme Disease in the Era of COVID-19: A Delayed Diagnosis and Risk for Complications

Virus database annotations assist in tracing information on patients infected with emerging pathogens

Contact Info

Product

Resources

About