A Syndromic Surveillance Tool to Detect Anomalous Clusters of COVID-19 Symptoms in the United States

Güemes, Amparo; Ray, Soumyajit; Aboumerhi, Khaled; Desjardins, Michael R.; Kvit, Anton; Corrigan, Anne E.; Fries, Brendan; Shields, Timothy; Stevens, Robert; Curriero, Frank C.; Etienne‐Cummings, Ralph

doi:10.1101/2020.08.18.20177295

Cited by 6 publications

(6 citation statements)

References 32 publications

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“…6 Estes objetivos ganham particular relevância se for tido em conta o tempo decorrido entre a infeção e a notificação da doença: estima-se que a vigilância laboratorial de COVID-19 revele o estado de evolução da doença na população, com duas a quatro semanas de atraso. 7 Por outro lado, a existência de situações de subnotificação laboratorial ou de incongruências em bases de dados oficiais (decorrentes de alterações na estrutura de informação, de definição de caso, ou vieses na data de notificação) 8 torna evidente a necessidade de complementar os sistemas de vigilância laboratorial com outros que permitam uma monitorização da doença mais precoce.…”

Section: Introductionunclassified

Deteção Precoce de COVID-19 em Portugal: Uso de Registos Clínicos

Torres¹,

Silva²,

Kislaya³

et al. 2021

Acta Med Port

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Introduction: Syndromic surveillance allows early detection of changes in the population’s morbidity pattern. The aim of this study is to evaluate the usefulness of indicators related to access to healthcare services, in COVID-19 surveillance.Material and Methods: A time series analysis was performed using the weekly incidence rate of COVID-19 in Mainland Portugal, between weeks 14/2020 (March 30 to April 5) and 25/2020 (June 15 to 21), and six indicators: 1) COVID-19 consultations in primary healthcare; 2) number of COVID-19 emergency department visits; 3) number of emergency department visits due to viral pneumonia; 4) number of hospitalizations due to viral pneumonia; 5) proportion of emergency department visits due to viral pneumonia; and 6) proportion of hospitalizations for viral pneumonia. Pearson correlation and cross-correlations were computed.Results: A strong correlation was found between the weekly incidence rate of COVID-19 and all indicators. [(1) 0.76; (2) 0.82; (3) 0.77; (4) 0.84; (5) 0.86; e (6) 0.90]. Emergency department visits and hospitalizations for viral pneumonia detect variations in the frequency of the disease with a one week lag compared to the incidence rate of COVID-19, in one week. COVID-19 consultations in primary healthcare and emergency department visits trail behind the incidence rate of COVID-19, in one week. The proportion of viral pneumonias in emergency department visits, or hospitalizations, is temporally aligned with the weekly incidence rate of COVID-19.Discussion: The delay found in the COVID-19 primary healthcare consultations and emergency department visits, may be related to changes in access to healthcare services and clinical coding. Emergency department visits and hospitalizations for viral pneumonia may be useful in the early detection of COVID-19. Viral pneumonia may have been coded as being of unknown origin. Future monitoring of these indicators is necessary to ascertain whether the incidence of COVID-19 is significantly influenced by changes in testing strategies. The indicators described in this study will be an asset for the optimization of testing strategies, allocation of healthcare resources to the communities that are most vulnerable to severe morbidity and assessing vaccination impact. As such, surveillance systems based on clinical data will be a valuable complementary tool to SINAVE.Conclusion: The indicators under analysis could be used regularly, with special attention to viral pneumonias, to detect outbreaks of COVID-19. Information on pneumonia of unknown etiology may be considered in the surveillance of COVID-19.

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Section: Introductionunclassified

Deteção Precoce de COVID-19 em Portugal: Uso de Registos Clínicos

Torres¹,

Silva²,

Kislaya³

et al. 2021

Acta Med Port

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“…One successful approach to responding to the need for timely trends and insights has been to leverage syndromic surveillance through surveys (7)(8)(9)(10)(11)(12). Previous work on influenza, and now COVID-19, has demonstrated the utility of this approach based on self-reported symptoms and other data, including burden estimation, hot-spot identification, and mitigation tracking (13)(14)(15)(16), in near real-time.…”

mentioning

confidence: 99%

Global monitoring of the impact of the COVID-19 pandemic through online surveys sampled from the Facebook user base

Astley

Tuli

Cord

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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Simultaneously tracking the global impact of COVID-19 is challenging because of regional variation in resources and reporting. Leveraging self-reported survey outcomes via an existing international social media network has the potential to provide standardized data streams to support monitoring and decision-making worldwide, in real time, and with limited local resources. The University of Maryland Global COVID-19 Trends and Impact Survey (UMD-CTIS), in partnership with Facebook, has invited daily cross-sectional samples from the social media platform's active users to participate in the survey since its launch on April 23, 2020. We analyzed UMD-CTIS survey data through December 20, 2020, from 31,142,582 responses representing 114 countries/territories weighted for nonresponse and adjusted to basic demographics. We show consistent respondent demographics over time for many countries/territories. Machine Learning models trained on national and pooled global data verified known symptom indicators. COVID-like illness (CLI) signals were correlated with government benchmark data. Importantly, the best benchmarked UMD-CTIS signal uses a single survey item whereby respondents report on CLI in their local community. In regions with strained health infrastructure but active social media users, we show it is possible to define COVID-19 impact trajectories using a remote platform independent of local government resources. This syndromic surveillance public health tool is the largest global health survey to date and, with brief participant engagement, can provide meaningful, timely insights into the global COVID-19 pandemic at a local scale.

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“…It allows registered users to provide filling of daily questions related to medical history and to provide information related to COVID-19. The main purpose of this study was to understand the symptoms of coronavirus [105] . Similarly, the COVID RADAR symptom Tracker applies data collection to detect loss of smell and taste [106] .…”

Section: Results and Overview Of Selected Studiesmentioning

confidence: 99%