1
|
Castro Blanco E, Dalmau Llorca MR, Aguilar Martín C, Carrasco-Querol N, Gonçalves AQ, Hernández Rojas Z, Coma E, Fernández-Sáez J. A Predictive Model of the Start of Annual Influenza Epidemics. Microorganisms 2024; 12:1257. [PMID: 39065025 PMCID: PMC11278734 DOI: 10.3390/microorganisms12071257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 06/14/2024] [Accepted: 06/17/2024] [Indexed: 07/28/2024] Open
Abstract
Influenza is a respiratory disease that causes annual epidemics during cold seasons. These epidemics increase pressure on healthcare systems, sometimes provoking their collapse. For this reason, a tool is needed to predict when an influenza epidemic will occur so that the healthcare system has time to prepare for it. This study therefore aims to develop a statistical model capable of predicting the onset of influenza epidemics in Catalonia, Spain. Influenza seasons from 2011 to 2017 were used for model training, and those from 2017 to 2018 were used for validation. Logistic regression, Support Vector Machine, and Random Forest models were used to predict the onset of the influenza epidemic. The logistic regression model was able to predict the start of influenza epidemics at least one week in advance, based on clinical diagnosis rates of various respiratory diseases and meteorological variables. This model achieved the best punctual estimates for two of three performance metrics. The most important variables in the model were the principal components of bronchiolitis rates and mean temperature. The onset of influenza epidemics can be predicted from clinical diagnosis rates of various respiratory diseases and meteorological variables. Future research should determine whether predictive models play a key role in preventing influenza.
Collapse
Affiliation(s)
- Elisabet Castro Blanco
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Campus Terres de l’Ebre, Universitat Rovira i Virgili, 43500 Tortosa, Spain
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
| | - Maria Rosa Dalmau Llorca
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Campus Terres de l’Ebre, Universitat Rovira i Virgili, 43500 Tortosa, Spain
- Servei d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
| | - Carina Aguilar Martín
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
- Unitat d’Avaluació, Direcció d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
| | - Noèlia Carrasco-Querol
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
| | - Alessandra Queiroga Gonçalves
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
| | - Zojaina Hernández Rojas
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Servei d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
| | - Ermengol Coma
- Primary Healthcare Information Systems, Health Institute of Catalonia, 08007 Catalonia, Spain;
| | - José Fernández-Sáez
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
- Servei d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
- Unitat de Recerca, Gerència Territorial Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
- Unitat Docent de Medicina de Familia i Comunitària, Tortosa-Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
| |
Collapse
|
2
|
Perramon-Malavez A, Bravo M, de Rioja VL, Català M, Alonso S, Álvarez-Lacalle E, López D, Soriano-Arandes A, Prats C. A semi-empirical risk panel to monitor epidemics: multi-faceted tool to assist healthcare and public health professionals. Front Public Health 2024; 11:1307425. [PMID: 38259774 PMCID: PMC10801172 DOI: 10.3389/fpubh.2023.1307425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 12/19/2023] [Indexed: 01/24/2024] Open
Abstract
Introduction Bronchiolitis, mostly caused by Respiratory Syncytial Virus (RSV), and influenza among other respiratory infections, lead to seasonal saturation at healthcare centers in temperate areas. There is no gold standard to characterize the stages of epidemics, nor the risk of respiratory infections growing. We aimed to define a set of indicators to assess the risk level of respiratory viral epidemics, based on both incidence and their short-term dynamics, and considering epidemical thresholds. Methods We used publicly available data on daily cases of influenza for the whole population and bronchiolitis in children <2 years from the Information System for Infection Surveillance in Catalonia (SIVIC). We included a Moving Epidemic Method (MEM) variation to define epidemic threshold and levels. We pre-processed the data with two different nowcasting approaches and performed a 7-day moving average. Weekly incidences (cases per 105 population) were computed and the 5-day growth rate was defined to create the effective potential growth (EPG) indicator. We performed a correlation analysis to define the forecasting ability of this index. Results Our adaptation of the MEM method allowed us to define epidemic weekly incidence levels and epidemic thresholds for bronchiolitis and influenza. EPG was able to anticipate daily 7-day cumulative incidence by 4-5 (bronchiolitis) or 6-7 (influenza) days. Discussion We developed a semi-empirical risk panel incorporating the EPG index, which effectively anticipates surpassing epidemic thresholds for bronchiolitis and influenza. This panel could serve as a robust surveillance tool, applicable to respiratory infectious diseases characterized by seasonal epidemics, easy to handle for individuals lacking a mathematical background.
Collapse
Affiliation(s)
- Aida Perramon-Malavez
- Department of Physics, Computational Biology and Complex Systems (BIOCOM-SC) group, Barcelona School of Agri-Food and Biosystems Engineering, Universitat Politècnica de Catalunya, Castelldefels, Spain
| | - Mario Bravo
- Department of Physics, Computational Biology and Complex Systems (BIOCOM-SC) group, Barcelona School of Agri-Food and Biosystems Engineering, Universitat Politècnica de Catalunya, Castelldefels, Spain
| | - Víctor López de Rioja
- Department of Physics, Computational Biology and Complex Systems (BIOCOM-SC) group, Barcelona School of Agri-Food and Biosystems Engineering, Universitat Politècnica de Catalunya, Castelldefels, Spain
| | - Martí Català
- Health Data Sciences, NDORMS, University of Oxford, Oxford, United Kingdom
| | - Sergio Alonso
- Department of Physics, Computational Biology and Complex Systems (BIOCOM-SC) group, Barcelona School of Agri-Food and Biosystems Engineering, Universitat Politècnica de Catalunya, Castelldefels, Spain
| | - Enrique Álvarez-Lacalle
- Department of Physics, Computational Biology and Complex Systems (BIOCOM-SC) group, Barcelona School of Agri-Food and Biosystems Engineering, Universitat Politècnica de Catalunya, Castelldefels, Spain
| | - Daniel López
- Department of Physics, Computational Biology and Complex Systems (BIOCOM-SC) group, Barcelona School of Agri-Food and Biosystems Engineering, Universitat Politècnica de Catalunya, Castelldefels, Spain
| | - Antoni Soriano-Arandes
- Paediatric Infectious Diseases and Immunodeficiencies Unit, Children’s Hospital, Vall d’Hebron Barcelona Hospital Campus, Barcelona, Catalonia, Spain
- Infection and Immunity in Paediatric Patients, Vall d’Hebron Research Institute, Barcelona, Catalonia, Spain
| | - Clara Prats
- Department of Physics, Computational Biology and Complex Systems (BIOCOM-SC) group, Barcelona School of Agri-Food and Biosystems Engineering, Universitat Politècnica de Catalunya, Castelldefels, Spain
| |
Collapse
|
3
|
Dalmau Llorca MR, Castro Blanco E, Aguilar Martín C, Carrasco-Querol N, Hernández Rojas Z, Gonçalves AQ, Fernández-Sáez J. Early Detection of the Start of the Influenza Epidemic Using Surveillance Systems in Catalonia (PREVIGrip Study). INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:17048. [PMID: 36554929 PMCID: PMC9779123 DOI: 10.3390/ijerph192417048] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 11/29/2022] [Accepted: 12/08/2022] [Indexed: 06/06/2023]
Abstract
Sentinel physician networks are the method of influenza surveillance recommended by the World Health Organization. Weekly clinical diagnoses based on clinical history are a surveillance method that provides more immediate information. The objective of this study is to evaluate which influenza surveillance system is capable of the earliest detection of the start of the annual influenza epidemic. We carried out an ecological time-series study based on influenza data from the population of Catalonia from the 2010-2011 to the 2018-2019 seasons. Rates of clinical diagnoses and of confirmed cases in Catalonia were used to study the changes in trends in the different surveillance systems, the differences in area and time lag between the curves of the different surveillance systems using Joinpoint regression, Simpson's 1/3 method and cross-correlation, respectively. In general, changes in the trend of the curves were detected before the beginning of the epidemic in most seasons, using the rates for the complete seasons and the pre-epidemic rates. No time lag was observed between clinical diagnoses and the total confirmed cases. Therefore, clinical diagnoses in Primary Care could be a useful tool for early detection of the start of influenza epidemics in Catalonia.
Collapse
Affiliation(s)
- M. Rosa Dalmau Llorca
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain
- Servei d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
- Campus Terres de l’Ebre, Universitat Rovira i Virgili, 43500 Tortosa, Spain
| | - Elisabet Castro Blanco
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain
- Campus Terres de l’Ebre, Universitat Rovira i Virgili, 43500 Tortosa, Spain
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
| | - Carina Aguilar Martín
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain
- Servei d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
- Unitat d’Avaluació, Direcció d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
| | - Noèlia Carrasco-Querol
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
| | - Zojaina Hernández Rojas
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain
- Servei d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
- Campus Terres de l’Ebre, Universitat Rovira i Virgili, 43500 Tortosa, Spain
| | - Alessandra Queiroga Gonçalves
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain
- Servei d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
| | - José Fernández-Sáez
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain
- Servei d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
- Campus Terres de l’Ebre, Universitat Rovira i Virgili, 43500 Tortosa, Spain
- Unitat de Recerca, Gerència Territorial Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
- Unitat Docent de Medicina de Familia i Comunitària, Tortosa-Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
| |
Collapse
|
4
|
Hammond A, Kim JJ, Sadler H, Vandemaele K. Influenza surveillance systems using traditional and alternative sources of data: A scoping review. Influenza Other Respir Viruses 2022; 16:965-974. [PMID: 36073312 DOI: 10.1111/irv.13037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 08/03/2022] [Accepted: 08/04/2022] [Indexed: 11/28/2022] Open
Abstract
OBJECTIVE While the World Health Organization's recommendation of syndromic sentinel surveillance for influenza is an efficient method to collect high-quality data, limitations exist. Aligned with the Research Recommendation 1.1.2 of the WHO Public Health Research Agenda for Influenza-to identify reliable complementary influenza surveillance systems which provide real-time estimates of influenza activity-we performed a scoping review to map the extent and nature of published literature on the use of non-traditional sources of syndromic surveillance data for influenza. METHODS We searched three electronic databases (PubMed, Web of Science, and Scopus) for articles in English, French, and Spanish, published between January 1 2007 and January 28 2022. Studies were included if they directly compared at least one non-traditional with a traditional influenza surveillance system in terms of correlation in activity or timeliness. FINDINGS We retrieved 823 articles of which 57 were included for analysis. Fifteen articles considered electronic health records (EHR), 11 participatory surveillance, 10 online searches and webpage traffic, seven Twitter, five absenteeism, four telephone health lines, three medication sales, two media reporting, and five looked at other miscellaneous sources of data. Several articles considered more than one non-traditional surveillance method. CONCLUSION We identified eight categories and a miscellaneous group of non-traditional influenza surveillance systems with varying levels of evidence on timeliness and correlation to traditional surveillance systems. Analyses of EHR and participatory surveillance systems appeared to have the most agreement on timeliness and correlation to traditional systems. Studies suggested non-traditional surveillance systems as complements rather than replacements to traditional systems.
Collapse
Affiliation(s)
- Aspen Hammond
- Global Influenza Programme, World Health Organization, Geneva, Switzerland
| | - John J Kim
- Global Influenza Programme, World Health Organization, Geneva, Switzerland.,School of Pharmacy, University of Waterloo, Kitchener, Ontario, Canada
| | - Holly Sadler
- Global Influenza Programme, World Health Organization, Geneva, Switzerland
| | | |
Collapse
|