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Analysis of institutional authors

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Analytical reference framework to analyze non-COVID-19 events

Publicated to:Population Health Metrics. 21 (1): 16- - 2023-12-01 21(1), DOI: 10.1186/s12963-023-00316-8

Authors: Villamil, Maria del Pilar; Velasco, Nubia; Barrera, David; Segura-Tinoco, Andres; Bernal, Oscar; Hernandez, Jose Tiberio

Affiliations

Departamento de Ingeniería Industrial, Pontificia Universidad Javeriana, Bogotá, Colombia. - Author
Department of Systems and Computing Engineering, Universidad de Los Andes, Bogotá, Colombia. - Author
Department of Systems and Computing Engineering, Universidad de Los Andes, Bogotá, Colombia. mavillam@uniandes.edu.co. - Author
Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain. - Author
Pontificia Univ Javeriana, Dept Ingn Ind, Bogota, Colombia - Author
School of Government, Universidad de los Andes, Bogotá, Colombia. - Author
School of Management, Universidad de los Andes, Bogotá, Colombia. - Author
Univ Andes, Dept Syst & Comp Engn, Bogota, Colombia - Author
Univ Andes, Sch Govt, Bogota, Colombia - Author
Univ Andes, Sch Management, Bogota, Colombia - Author
Univ Autonoma Madrid, Escuela Politecn Super, Madrid, Spain - Author
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Abstract

The COVID-19 pandemic has disrupted the healthcare system, leading to delays in detection of other non-COVID-19 diseases. This paper presents ANE Framework (Analytics for Non-COVID-19 Events), a reliable and user-friendly analytical forecasting framework designed to predict the number of patients with non-COVID-19 diseases. Prior to 2020, there were analytical models focused on specific illnesses and contexts. Then, most models have focused on understanding COVID-19 behavior. There is a lack of analytical frameworks that enable disease forecasting for non-COVID-19 diseases.The ANE Framework utilizes time series analysis to generate forecasting models. The framework leverages daily data from official government sources and employs SARIMA models to forecast the number of non-COVID-19 cases, such as tuberculosis and suicide attempts.The framework was tested on five different non-COVID-19 events. The framework performs well across all events, including tuberculosis and suicide attempts, with a Mean Absolute Percentage Error (MAPE) of up to 20% and the consistency remains independent of the behavior of each event. Moreover, a pairwise comparison of averages can lead to over or underestimation of the impact. The disruption caused by the pandemic resulted in a 17% gap (2383 cases) between expected and reported tuberculosis cases, and a 19% gap (2464 cases) for suicide attempts. These gaps varied between 20 and 64% across different cities and regions. The ANE Framework has proven to be reliable for analyzing several diseases and exhibits the flexibility to incorporate new data from various sources. Regular updates and the inclusion of new associated data enhance the framework's effectiveness.Current pandemic shows the necessity of developing flexible models to be adapted to different illness data. The framework developed proved to be reliable for the different diseases analyzed, presenting enough flexibility to update with new data or even include new data from different databases. To keep updated on the result of the project allows the inclusion of new data associated with it. Similarly, the proposed strategy in the ANE framework allows for improving the quality of the obtained results with news events.© 2023. BioMed Central Ltd., part of Springer Nature.

Keywords
no covid-19 eventssarimasuicide attempttuberculosisForecasting modelsNo covid-19 eventsSarimaSuicide attemptTuberculosis

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Population Health Metrics due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2023, it was in position , thus managing to position itself as a Q1 (Primer Cuartil), in the category Public Health, Environmental and Occupational Health. Notably, the journal is positioned above the 90th percentile.

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-05-02:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 8.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 8 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 8.08.
  • The number of mentions on the social network X (formerly Twitter): 1 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://repositorio.uam.es/handle/10486/711564
Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Colombia.