Open data for monitoring COVID-19 in Spain: Descriptive study <span class="so-article-trans-title" dir="auto"> Translated title: Datos abiertos de monitorización de la COVID-19 en España: estudio descriptivo </span>

Guisado-Clavero, Marina; Astier-Peña, María Pilar; Gómez-Bravo, Raquel; Ares-Blanco, Sara

doi:10.1016/j.eimce.2023.04.003

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Open data for monitoring COVID-19 in Spain: Descriptive study Translated title: Datos abiertos de monitorización de la COVID-19 en España: estudio descriptivo

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Author(s): Marina Guisado-Clavero ^a , María Pilar Astier-Peña ^b ^, ^c , Raquel Gómez-Bravo ^d , Sara Ares-Blanco ^e ^, ^f ^, ^*

Publication date (Electronic): 5 April 2023

Journal: Enfermedades Infecciosas Y Microbiologia Clinica (English Ed.)

Publisher: Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. Published by Elsevier España, S.L.U.

Keywords: Primary health, COVID-19, Open access, Health policy, Public health, Epidemiological monitoring, Atención primaria, COVID-19, Datos abiertos, Políticas de salud, Salud pública, Vigilancia epidemiológica

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Abstract

Background

The indicators of the pandemic have been based on the total number of diagnosed cases of COVID-19, the number of people hospitalized or in intensive care units, and deaths from the infection. The aim of this study is to describe the available data on diagnostic tests, health service used for the diagnosis of COVID-19, case detection and monitoring.

Method

Descriptive study with review of official data available on the websites of the Spanish health councils corresponding to 17 Autonomous Communities, 2 Autonomous cities and the Ministry of Health. The variables collected refer to contact tracing, technics for diagnosis, use of health services and follow-up.

Results

All regions of Spain show data on diagnosed cases of COVID-19 and deaths. Hospitalized cases and intensive care admissions are shown in all regions except the Balearic Islands. Diagnostic tests for COVID-19 have been registered in all regions except Madrid region and Extremadura, with scarcely information on what type of test has been performed (present in 7 CCAA), requesting service and study of contacts.

Conclusions

The information available on the official websites of the Health Departments of the different regions of Spain are heterogeneous. Data from the use of health service or workload in Primary Care, Emergency department or Out of hours services are almost non-existent.

Translated abstract

Objetivo

Los indicadores del estado de pandemia se han basado en el número total de casos diagnosticados de la COVID-19, el número de personas hospitalizadas o en unidades de cuidados intensivos y los fallecimientos por la infección. El objetivo de este estudio es describir los datos disponibles sobre pruebas diagnósticas, servicio sanitario utilizado para el diagnóstico de COVID-19 y seguimiento/detección de casos.

Método

Estudio descriptivo con revisión de datos oficiales disponibles en las páginas web de las consejerías de sanidad de España correspondientes a 17 Comunidades Autónomas (CCAA), 2 ciudades Autónomas y el Ministerio de Sanidad. Las variables recogidas hacen referencia al estudio de contactos, diagnóstico de casos, uso de servicios sanitarios y seguimiento.

Resultados

Todas las regiones de España muestran datos de los casos diagnosticados de COVID-19 y fallecidos. Los casos hospitalizados e ingresos en cuidados intensivos se muestran en todas las regiones excepto Baleares. Las pruebas diagnósticas de COVID-19 se han registrado en todas las regiones excepto Comunidad de Madrid y Extremadura, habiendo poca información sobre qué tipo de prueba se ha realizado (presente en 7 CCAA), servicio peticionario y estudio de contactos.

Conclusiones

La información disponible en las páginas web oficiales de las Consejerías de Sanidad de las diferentes regiones de España son heterogéneas. Los datos sobre el uso o carga laboral a nivel de Atención Primaria o Servicios de urgencias hospitalarios y extrahospitalarios son cuasi inexistentes.

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Most cited references 25

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Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention

Zunyou Wu, Jennifer M. McGoogan (2020)

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Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts

Joel Hellewell, Sam Abbott, Amy Gimma … (2020)

Summary Background Isolation of cases and contact tracing is used to control outbreaks of infectious diseases, and has been used for coronavirus disease 2019 (COVID-19). Whether this strategy will achieve control depends on characteristics of both the pathogen and the response. Here we use a mathematical model to assess if isolation and contact tracing are able to control onwards transmission from imported cases of COVID-19. Methods We developed a stochastic transmission model, parameterised to the COVID-19 outbreak. We used the model to quantify the potential effectiveness of contact tracing and isolation of cases at controlling a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-like pathogen. We considered scenarios that varied in the number of initial cases, the basic reproduction number (R 0), the delay from symptom onset to isolation, the probability that contacts were traced, the proportion of transmission that occurred before symptom onset, and the proportion of subclinical infections. We assumed isolation prevented all further transmission in the model. Outbreaks were deemed controlled if transmission ended within 12 weeks or before 5000 cases in total. We measured the success of controlling outbreaks using isolation and contact tracing, and quantified the weekly maximum number of cases traced to measure feasibility of public health effort. Findings Simulated outbreaks starting with five initial cases, an R 0 of 1·5, and 0% transmission before symptom onset could be controlled even with low contact tracing probability; however, the probability of controlling an outbreak decreased with the number of initial cases, when R 0 was 2·5 or 3·5 and with more transmission before symptom onset. Across different initial numbers of cases, the majority of scenarios with an R 0 of 1·5 were controllable with less than 50% of contacts successfully traced. To control the majority of outbreaks, for R 0 of 2·5 more than 70% of contacts had to be traced, and for an R 0 of 3·5 more than 90% of contacts had to be traced. The delay between symptom onset and isolation had the largest role in determining whether an outbreak was controllable when R 0 was 1·5. For R 0 values of 2·5 or 3·5, if there were 40 initial cases, contact tracing and isolation were only potentially feasible when less than 1% of transmission occurred before symptom onset. Interpretation In most scenarios, highly effective contact tracing and case isolation is enough to control a new outbreak of COVID-19 within 3 months. The probability of control decreases with long delays from symptom onset to isolation, fewer cases ascertained by contact tracing, and increasing transmission before symptoms. This model can be modified to reflect updated transmission characteristics and more specific definitions of outbreak control to assess the potential success of local response efforts. Funding Wellcome Trust, Global Challenges Research Fund, and Health Data Research UK.

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Collateral damage: the impact on outcomes from cancer surgery of the COVID-19 pandemic

Amit Sud, Michael E.B. Jones, John Broggio … (2020)

Background Cancer diagnostics and surgery have been disrupted by the response of healthcare services to the COVID-19 pandemic. Progression of cancers during delay will impact on patient long-term survival. Methods We generated per-day hazard ratios of cancer progression from observational studies and applied these to age-specific, stage-specific cancer survival for England 2013-2017. We modelled per-patient delay of three months and six months and periods of disruption of one year and two years. Using healthcare resource costing, we contextualise attributable lives saved and life-years gained from cancer surgery to equivalent volumes of COVID-19 hospitalisations. Findings Per year, 94,912 resections for major cancers result in 80,406 long-term survivors and 1,717,051 life years gained. Per-patient delay of three/six months would cause attributable death of 4,755/10,760 of these individuals with loss of 92,214/208,275 life-years. For cancer surgery, average life-years gained (LYGs) per patient are 18.1 under standard conditions and 17.1/15.9 with a delay of three/six months (an average loss of 0.97/2.19 LYG per patient). Taking into account units of healthcare resource (HCRU), surgery results on average per patient in 2.25 resource-adjusted life-years gained (RALYGs) under standard conditions and 2.12/1.97 RALYGs following delay of three/six months. For 94,912 hospital COVID-19 admissions, there are 482,022 LYGs requiring of 1,052,949 HCRUs. Hospitalisation of community-acquired COVID-19 patients yields on average per patient 5.08 LYG and 0.46 RALYGs. Interpretation Modest delays in surgery for cancer incur significant impact on survival. Delay of three/six months in surgery for incident cancers would mitigate 19%/43% of life-years gained by hospitalisation of an equivalent volume of admissions for community-acquired COVID-19. This rises to 26%/59% when considering resource-adjusted life-years gained. To avoid a downstream public health crisis of avoidable cancer deaths, cancer diagnostic and surgical pathways must be maintained at normal throughput, with rapid attention to any backlog already accrued.

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Author and article information

Journal

Journal ID (nlm-ta): Enferm Infecc Microbiol Clin (Engl Ed)

Journal ID (iso-abbrev): Enferm Infecc Microbiol Clin (Engl Ed)

Title: Enfermedades Infecciosas Y Microbiologia Clinica (English Ed.)

Publisher: Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. Published by Elsevier España, S.L.U.

ISSN (Electronic): 2529-993X

Publication date PMC-release: 5 April 2023

Publication date (Electronic): 5 April 2023

Affiliations

[a ]Unidad Docente Multiprofesional de Atención Familiar y Comunitaria del área norte de la Comunidad de Madrid, Madrid, Spain

[b ]Centro de Salud Univérsitas, Servicio Aragonés de Salud, Zaragoza, Spain

[c ]GdT de Seguridad del paciente de semFYC y del GdT de Calidad y Seguridad de WONCA, Zaragoza, Spain

[d ]Research Group Self-Regulation and Health, Institute for Health and Behaviour, Department of Behavioural and CognitiveSciences, Faculty of Humanities, Education, and Social Sciences, Universidad de Luxemburgo, Luxemburgo, Luxemburgo

[e ]Centro de Salud Federica Montseny, Gerencia Asistencial de Atención Primaria, Servicio Madrileño de Salud, Madrid, Spain

[f ]Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain

Author notes

[* ]Corresponding author.

Article

Publisher Item ID: S2529-993X(23)00102-8

DOI: 10.1016/j.eimce.2023.04.003

PMC ID: 10073586

SO-VID: 704c4c9f-ac70-4ed2-8c68-4585ed62b205

License:

Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.