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Estimating the Burden of Influenza-like Illness on Daily Activity at the Population Scale Using Commercial Wearable Sensors

IMPORTANCE: The severity of viral infections can vary widely, from asymptomatic cases to complications leading to hospitalizations and death. Milder cases, despite being more prevalent, often go undocumented, and their public health burden is not accurately estimated. OBJECTIVE: To estimate the true...

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Autores principales: Mezlini, Aziz, Shapiro, Allison, Daza, Eric J., Caddigan, Eamon, Ramirez, Ernesto, Althoff, Tim, Foschini, Luca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9099426/
https://www.ncbi.nlm.nih.gov/pubmed/35552722
http://dx.doi.org/10.1001/jamanetworkopen.2022.11958
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author Mezlini, Aziz
Shapiro, Allison
Daza, Eric J.
Caddigan, Eamon
Ramirez, Ernesto
Althoff, Tim
Foschini, Luca
author_facet Mezlini, Aziz
Shapiro, Allison
Daza, Eric J.
Caddigan, Eamon
Ramirez, Ernesto
Althoff, Tim
Foschini, Luca
author_sort Mezlini, Aziz
collection PubMed
description IMPORTANCE: The severity of viral infections can vary widely, from asymptomatic cases to complications leading to hospitalizations and death. Milder cases, despite being more prevalent, often go undocumented, and their public health burden is not accurately estimated. OBJECTIVE: To estimate the true burden of influenza-like illness (ILI) in the US population using a surrogate measure of daily steps lost as measured by commercial wearable sensors. DESIGN, SETTING, AND PARTICIPANTS: This cohort study modeled data from 15 122 US adults who reported ILI symptoms during the 2018-2019 influenza season (before the COVID-19 pandemic) and who had a sufficient density of wearable sensor data at symptom onset. Participants’ minute-level step data as measured by commercial wearable sensors were collected from October 1, 2018, through June 30, 2019. Minute-level activity time series were transformed into day-level time series per user, indicating the total number of steps daily. MAIN OUTCOMES AND MEASURES: The primary end point was the number of steps lost during the period of 4 days before symptom onset (the latent phase) through 11 days after symptom onset (the symptomatic phase). The association between covariates and steps lost during this interval was also examined. RESULTS: Of the 15 122 participants in this study, 13 108 (86.7%) were women, and the median age was 32 years (IQR, 27-38 years). For their ILI event, 2836 of 15 080 participants (18.8%) sought medical attention, and only 61 (0.4%) were hospitalized. Over the course of an ILI lasting 10 days, the mean cumulative loss was 4437 steps (95% CI, 4143-4731 steps). After weighting, there was an estimated overall nationwide reduction in mobility equivalent to 255.2 billion steps (95% CI, 232.9-277.6 billion steps) lost because of ILI symptoms during the study period. This finding reflects significant changes in routines, mobility, and employment and is equivalent to 15% of the active US population becoming completely immobilized for 1 day. Moreover, 60.6% of this reduction in steps (154.6 billion steps [95% CI, 138.1-171.2 billion steps]) occurred among persons who sought no medical care. Age and educational level were positively associated with steps lost. CONCLUSIONS AND RELEVANCE: These findings suggest that most of the burden of ILI in this study would have been invisible to health care and public health reporting systems. This approach has applications for public health, health care, and clinical research, from estimating costs of lost productivity at population scale, to measuring effectiveness of anti-ILI treatments, to monitoring recovery after acute viral syndromes such as during long COVID-19.
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spelling pubmed-90994262022-05-27 Estimating the Burden of Influenza-like Illness on Daily Activity at the Population Scale Using Commercial Wearable Sensors Mezlini, Aziz Shapiro, Allison Daza, Eric J. Caddigan, Eamon Ramirez, Ernesto Althoff, Tim Foschini, Luca JAMA Netw Open Original Investigation IMPORTANCE: The severity of viral infections can vary widely, from asymptomatic cases to complications leading to hospitalizations and death. Milder cases, despite being more prevalent, often go undocumented, and their public health burden is not accurately estimated. OBJECTIVE: To estimate the true burden of influenza-like illness (ILI) in the US population using a surrogate measure of daily steps lost as measured by commercial wearable sensors. DESIGN, SETTING, AND PARTICIPANTS: This cohort study modeled data from 15 122 US adults who reported ILI symptoms during the 2018-2019 influenza season (before the COVID-19 pandemic) and who had a sufficient density of wearable sensor data at symptom onset. Participants’ minute-level step data as measured by commercial wearable sensors were collected from October 1, 2018, through June 30, 2019. Minute-level activity time series were transformed into day-level time series per user, indicating the total number of steps daily. MAIN OUTCOMES AND MEASURES: The primary end point was the number of steps lost during the period of 4 days before symptom onset (the latent phase) through 11 days after symptom onset (the symptomatic phase). The association between covariates and steps lost during this interval was also examined. RESULTS: Of the 15 122 participants in this study, 13 108 (86.7%) were women, and the median age was 32 years (IQR, 27-38 years). For their ILI event, 2836 of 15 080 participants (18.8%) sought medical attention, and only 61 (0.4%) were hospitalized. Over the course of an ILI lasting 10 days, the mean cumulative loss was 4437 steps (95% CI, 4143-4731 steps). After weighting, there was an estimated overall nationwide reduction in mobility equivalent to 255.2 billion steps (95% CI, 232.9-277.6 billion steps) lost because of ILI symptoms during the study period. This finding reflects significant changes in routines, mobility, and employment and is equivalent to 15% of the active US population becoming completely immobilized for 1 day. Moreover, 60.6% of this reduction in steps (154.6 billion steps [95% CI, 138.1-171.2 billion steps]) occurred among persons who sought no medical care. Age and educational level were positively associated with steps lost. CONCLUSIONS AND RELEVANCE: These findings suggest that most of the burden of ILI in this study would have been invisible to health care and public health reporting systems. This approach has applications for public health, health care, and clinical research, from estimating costs of lost productivity at population scale, to measuring effectiveness of anti-ILI treatments, to monitoring recovery after acute viral syndromes such as during long COVID-19. American Medical Association 2022-05-12 /pmc/articles/PMC9099426/ /pubmed/35552722 http://dx.doi.org/10.1001/jamanetworkopen.2022.11958 Text en Copyright 2022 Mezlini A et al. JAMA Network Open. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article distributed under the terms of the CC-BY-NC-ND License.
spellingShingle Original Investigation
Mezlini, Aziz
Shapiro, Allison
Daza, Eric J.
Caddigan, Eamon
Ramirez, Ernesto
Althoff, Tim
Foschini, Luca
Estimating the Burden of Influenza-like Illness on Daily Activity at the Population Scale Using Commercial Wearable Sensors
title Estimating the Burden of Influenza-like Illness on Daily Activity at the Population Scale Using Commercial Wearable Sensors
title_full Estimating the Burden of Influenza-like Illness on Daily Activity at the Population Scale Using Commercial Wearable Sensors
title_fullStr Estimating the Burden of Influenza-like Illness on Daily Activity at the Population Scale Using Commercial Wearable Sensors
title_full_unstemmed Estimating the Burden of Influenza-like Illness on Daily Activity at the Population Scale Using Commercial Wearable Sensors
title_short Estimating the Burden of Influenza-like Illness on Daily Activity at the Population Scale Using Commercial Wearable Sensors
title_sort estimating the burden of influenza-like illness on daily activity at the population scale using commercial wearable sensors
topic Original Investigation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9099426/
https://www.ncbi.nlm.nih.gov/pubmed/35552722
http://dx.doi.org/10.1001/jamanetworkopen.2022.11958
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