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1. A multidisciplinary and structured investigation of three suspected clusters of transverse upper limb reduction defects in France

Author

Boudet-Berquier, Julie, Demattei, Christophe, Guldner, Laurence, Gallay, Anne, Manouvrier, Sylvie, Botton, Jérémie, Philippat, Claire, Delva, Fleur, Bloch, Juliette, Semaille, Caroline, Odent, Sylvie, Perthus, Isabelle, Randrianaivo, Hanitra, Babajko, Sylvie, Barjat, Tiphaine, Beneteau, Claire, Brennetot, Naima, Garne, Ester, Haddad, Georges, Hocine, Mounia, Lacroix, Isabelle, Leuraud, Klervi, Mench, Michel, Morris, Joan, Patrier, Sophie, Sartelet, Arnaud, Verloes, Alain, Bonaldi, Christophe, Le Barbier, Mélina, Gagnière, Bertrand, Pépin, Philippe, Ollivier, Ronan, Bitoun, Monique, King, Lisa, Guajardo-Villar, Andrea, Gomes, Eugenia, Desenclos, Jean-Claude, Regnault, Nolwenn, and Benachi, Alexandra

Published
2024
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4. The health state of France before COVID-19 pandemic between 1990 and 2019: an analysis of the Global Burden of Disease study 2019

Author

Al-Jumaily, Adel, Béjot, Yannick, Jacob, Louis, Magne, Julien, Mansour, Ali, Mokdad, Ali, Pigeolet, Manon, Raad, Mathieu, Mansour, Sedighi, Touvier, Mathilde, Zeitoun, Jean-David, Francis-Oliviero, Florence, Constantinou, Panayotis, Haneef, Romana, Schwarzinger, Michaël, Gallay, Anne, Rachas, Antoine, and Alla, François

Published
2024
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6. The InfAct proposal for a sustainable European health information infrastructure on population health: the Distributed Infrastructure on Population Health (DIPoH)

Author

Sarmiento-Suárez, Rodrigo, Padron-Monedero, Alicia, Bogaert, Petronille, Abboud, Linda, Van Oyen, Herman, Tolonen, Hanna, Tijhuis, Mariken, Seeling, Stefanie, Haneef, Romana, Zaletel, Metka, Palmieri, Luigi, Gallay, Anne, Lapão, Luís Velez, Nogueira, Paulo, Ziese, Thomas, Vukovic, Jakov, Beja, André, Saso, Miriam, and Noguer-Zambrano, Isabel

Published
2022
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7. The burden of injury in Central, Eastern, and Western European sub-region: a systematic analysis from the Global Burden of Disease 2019 Study

Author

Haagsma, Juanita A., Charalampous, Periklis, Ariani, Filippo, Gallay, Anne, Moesgaard Iburg, Kim, Nena, Evangelia, Ngwa, Che Henry, Rommel, Alexander, Zelviene, Ausra, Abegaz, Kedir Hussein, Al Hamad, Hanadi, Albano, Luciana, Liliana Andrei, Catalina, Andrei, Tudorel, Antonazzo, Ippazio Cosimo, Aremu, Olatunde, Arumugam, Ashokan, Atreya, Alok, Aujayeb, Avinash, Ayuso-Mateos, Jose Luis, Engelbert Bain, Luchuo, Banach, Maciej, Winfried Bärnighausen, Till, Barone-Adesi, Francesco, Beghi, Massimiliano, Bennett, Derrick A., Bhagavathula, Akshaya S., Carvalho, Félix, Castelpietra, Giulio, Caterina, Ledda, Chandan, Joht Singh, Couto, Rosa A. S., Cruz-Martins, Natália, Damiani, Giovanni, Dastiridou, Anna, Demetriades, Andreas K., Dias-da-Silva, Diana, Francis Fagbamigbe, Adeniyi, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Ferrara, Pietro, Fischer, Florian, Fra.Paleo, Urbano, Ghirini, Silvia, Glasbey, James C., Glavan, Ionela-Roxana, Gomes, Nelson G. M., Grivna, Michal, Harlianto, Netanja I., Haro, Josep Maria, Hasan, M. Tasdik, Hostiuc, Sorin, Iavicoli, Ivo, Ilic, Milena D., Ilic, Irena M., Jakovljevic, Mihajlo, Jonas, Jost B., Jerzy Jozwiak, Jacek, Jürisson, Mikk, Kauppila, Joonas H., Kayode, Gbenga A., Khan, Moien A. B., Kisa, Adnan, Kisa, Sezer, Koyanagi, Ai, Kumar, Manasi, Kurmi, Om P., La-Vecchia, Carlo, Lamnisos, Demetris, Lasrado, Savita, Lauriola, Paolo, Linn, Shai, Loureiro, Joana A., Lunevicius, Raimundas, Madureira-Carvalho, Aurea, Mechili, Enkeleint A., Majeed, Azeem, Menezes, Ritesh G., Mentis, Alexios-Fotios A., Meretoja, Atte, Mestrovic, Tomislav, Miazgowski, Tomasz, Miazgowski, Bartosz, Mirica, Andreea, Molokhia, Mariam, Mohammed, Shafiu, Monasta, Lorenzo, Mulita, Francesk, David Naimzada, Mukhammad, Negoi, Ionut, Neupane, Subas, Oancea, Bogdan, Orru, Hans, Otoiu, Adrian, Otstavnov, Nikita, Otstavnov, Stanislav S., Padron-Monedero, Alicia, Panda-Jonas, Songhomitra, Pardhan, Shahina, Patel, Jay, Pedersini, Paolo, Pinheiro, Marina, Rakovac, Ivo, Rao, Chythra R., Rawaf, Salman, Rawaf, David Laith, Rodrigues, Violet, Ronfani, Luca, Sagoe, Dominic, Sanmarchi, Francesco, Santric-Milicevic, Milena M., Sathian, Brijesh, Sheikh, Aziz, Shiri, Rahman, Shivalli, Siddharudha, Dora Sigfusdottir, Inga, Sigurvinsdottir, Rannveig, Yurievich Skryabin, Valentin, Aleksandrovna Skryabina, Anna, Smarandache, Catalin-Gabriel, Socea, Bogdan, Sousa, Raúl A. R. C., Steiropoulos, Paschalis, Tabarés-Seisdedos, Rafael, Roberto Tovani-Palone, Marcos, Tozija, Fimka, Van de Velde, Sarah, Juhani Vasankari, Tommi, Veroux, Massimiliano, Violante, Francesco S., Vlassov, Vasiliy, Wang, Yanzhong, Yadollahpour, Ali, Yaya, Sanni, Sergeevich Zastrozhin, Mikhail, Zastrozhina, Anasthasia, Polinder, Suzanne, and Majdan, Marek

Published
2022
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11. The health state of France before COVID-19 pandemic between 1990 and 2019: an analysis of the Global Burden of Disease study 2019

Author

Francis-Oliviero, Florence, primary, Constantinou, Panayotis, additional, Haneef, Romana, additional, Al-Jumaily, Adel, additional, Béjot, Yannick, additional, Jacob, Louis, additional, Magne, Julien, additional, Mansour, Ali, additional, Mokdad, Ali, additional, Pigeolet, Manon, additional, Raad, Mathieu, additional, Mansour, Sedighi, additional, Touvier, Mathilde, additional, Zeitoun, Jean-David, additional, Schwarzinger, Michaël, additional, Gallay, Anne, additional, Rachas, Antoine, additional, and Alla, François, additional

Published
2024
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18. Complex association between post-COVID-19 condition and anxiety and depression symptoms.

Author

Tebeka, Sarah, Carcaillon-Bentata, Laure, Decio, Valentina, Alleaume, Caroline, Beltzer, Nathalie, Gallay, Anne, Lemogne, Cédric, Pignon, Baptiste, Makovski, Tatjana T., and Coste, Joël

Subjects
MENTAL depression, ANXIETY, COVID-19 pandemic, FRENCH people, POST-acute COVID-19 syndrome
Abstract

Background. To assess the associations between anxiety and depressive symptoms and post- COVID-19 condition (PCC) by exploring the direction of these associations and their relevance in the definition of PCC. Methods. Nationwide survey among French adults, recruited between March and April, 2022, using a quota method to capture a representative sample of the general population with regard to sex, age, socioeconomic status, size of the place of residence, and region. We included all participants who met the World Health Organization (WHO) definition of PCC in addition to a random sample of participants infected with SARS-COV-2 for at least 3 months but without PCC. Self-reported anxiety and depressive symptoms, chronic anxiety and depression (for more than 3 years), and anxiety and depression were measured using the GAD-2 and PHQ-2 questionnaires, respectively. Results. In a sample of 1,095 participants with PCC and 1,021 participants infected with SARSCOV- 2 without PCC, 21% had self-reported anxiety and 18% self-reported depression, whereas 33% and 20% had current measured symptoms of anxiety and depression, respectively. The high prevalence of these symptoms cannot only be explained by the characterization of PCC, as only 13.4% of anxiety symptoms and 7.6% of depressive symptoms met the WHO criteria for PCC. Only one participant met the WHO criteria based on self-reported anxiety or depressive symptoms alone, as these were always combined with other symptoms in patients with PCC. Chronic symptoms were associated with PCC (aOR 1.27; 95% CI: 1.00-1.61). In addition, measured anxiety was associated with PCC (aOR = 1.29; 95% CI: 1.02-1.62). Conclusions. Pre-COVID-19 chronic anxiety and depression may play a role in the development of PCC or share vulnerability factors with it. Our results challenge the inclusion of anxiety and depression in the definition of PCC. [ABSTRACT FROM AUTHOR]

Published
2024
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19. Direct impact of COVID-19 by estimating disability-adjusted life years at national level in France in 2020

Author

Haneef, Romana, Fayad, Myriam, Fouillet, Anne, Sommen, Cécile, Bonaldi, Christophe, Wyper, Grant M.A., Pires, Sara Monteiro, Devleesschauwer, Brecht, Rachas, Antoine, Constantinou, Panayotis, Levy-Bruhl, Daniel, Beltzer, Nathalie, Gallay, Anne, Haneef, Romana, Fayad, Myriam, Fouillet, Anne, Sommen, Cécile, Bonaldi, Christophe, Wyper, Grant M.A., Pires, Sara Monteiro, Devleesschauwer, Brecht, Rachas, Antoine, Constantinou, Panayotis, Levy-Bruhl, Daniel, Beltzer, Nathalie, and Gallay, Anne

Abstract

Background The World Health Organization declared a pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), on March 11, 2020. The standardized approach of disability-adjusted life years (DALYs) allows for quantifying the combined impact of morbidity and mortality of diseases and injuries. The main objective of this study was to estimate the direct impact of COVID-19 in France in 2020, using DALYs to combine the population health impact of infection fatalities, acute symptomatic infections and their post-acute consequences, in 28 days (baseline) up to 140 days, following the initial infection. Methods National mortality, COVID-19 screening, and hospital admission data were used to calculate DALYs based on the European Burden of Disease Network consensus disease model. Scenario analyses were performed by varying the number of symptomatic cases and duration of symptoms up to a maximum of 140 days, defining COVID-19 deaths using the underlying, and associated, cause of death. Results In 2020, the estimated DALYs due to COVID-19 in France were 990 710 (1472 per 100 000), with 99% of burden due to mortality (982 531 years of life lost, YLL) and 1% due to morbidity (8179 years lived with disability, YLD), following the initial infection. The contribution of YLD reached 375%, assuming the duration of 140 days of post-acute consequences of COVID-19. Post-acute consequences contributed to 49% of the total morbidity burden. The contribution of YLD due to acute symptomatic infections among people younger than 70 years was higher (67%) than among people aged 70 years and above (33%). YLL among people aged 70 years and above, contributed to 74% of the total YLL. Conclusions COVID-19 had a substantial impact on population health in France in 2020. The majority of population health loss was due to mortality. Men had higher population health

Published
2023

20. Direct impact of COVID-19 by estimating disability-adjusted life years at national level in France in 2020

Author

Haneef, Romana, primary, Fayad, Myriam, additional, Fouillet, Anne, additional, Sommen, Cécile, additional, Bonaldi, Christophe, additional, Wyper, Grant M. A., additional, Pires, Sara Monteiro, additional, Devleesschauwer, Brecht, additional, Rachas, Antoine, additional, Constantinou, Panayotis, additional, Levy-Bruhl, Daniel, additional, Beltzer, Nathalie, additional, and Gallay, Anne, additional

Published
2023
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21. Prevalence of Long Covid in the General Adult Population According to Different Definitions and Sociodemographic and Infection Characteristics. A Nationwide Random Sampling Survey in France after the Omicron Waves in Autumn 2022

Author

Coste, Joël, primary, Delpierre, Cyrille, additional, Richard, Jean-Baptiste, additional, Alleaume, Caroline, additional, Gallay, Anne, additional, Beltzer, Nathalie, additional, Tebeka, Sarah, additional, Lemogne, Cédric, additional, Robineau, Olivier, additional, Steichen, Olivier, additional, and Makovski, Tatjana T., additional

Published
2023
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23. The InfAct proposal for a sustainable European health information infrastructure on population health

Author

Sarmiento-Suárez, Rodrigo, Padron-Monedero, Alicia, Bogaert, Petronille, Abboud, Linda, Van Oyen, Herman, Tolonen, Hanna, Tijhuis, Mariken, Seeling, Stefanie, Haneef, Romana, Zaletel, Metka, Palmieri, Luigi, Gallay, Anne, Lapão, Luís Velez, Nogueira, Paulo, Ziese, Thomas, Vukovic, Jakov, Beja, André, Saso, Miriam, Noguer-Zambrano, Isabel, and Instituto de Higiene e Medicina Tropical (IHMT)

Subjects
Health Information Management, SDG 3 - Good Health and Well-being, Health Policy, Public Health, Environmental and Occupational Health, SDG 9 - Industry, Innovation, and Infrastructure, SDG 11 - Sustainable Cities and Communities
Abstract

© 2022. The Author(s). BACKGROUND: In Europe, data on population health is fragmented, difficult to access, project-based and prone to health information inequalities in terms of availability, accessibility and especially in quality between and within countries. This situation is further exacerbated and exposed by the recent COVID-19 pandemic. The Joint Action on Health Information (InfAct) that builds on previous works of the BRIDGE Health project, carried out collaborative action to set up a sustainable infrastructure for health information in the European Union (EU). The aim of this paper is to present InfAct's proposal for a sustainable research infrastructure, the Distributed Infrastructure on Population Health (DIPoH), which includes the setup of a Health Information Portal on population health to be maintained beyond InfAct's time span. METHODS: The strategy for the proposal was based on three components: scientific initiatives and proposals to improve Health Information Systems (HIS), exploration of technical acceptability and feasibility, and finally obtaining high-level political support.. The technical exploration (Technical Dialogues-TD) was assumed by technical experts proposed by the countries, and political guidance was provided by the Assembly of Members (AoM), which gathered representatives from Ministries of Health and Science of EU/EEA countries. The results from the AoM and the TD were integrated in the sustainability plan compiling all the major outputs of InfAct. RESULTS: The InfAct sustainability plan was organized in three main sections: a proposal of a new research infrastructure on population health (the DIPoH), new health information tools and innovative proposals for HIS, and a comprehensive capacity building programme. These activities were carried out in InfAct and are being further developed in the Population Health Information Research Infrastructure (PHIRI). PHIRI is a practical rollout of DIPoH facilitating and generating the best available evidence for research on health and wellbeing of populations as impacted by COVID-19. CONCLUSIONS: The sustainability plan received wide support from Member States and was recognized to have an added value at EU level. Nevertheless, there were several aspects which still need to be considered for the near future such as: (i) a commitment of stable financial and political support by Member States (MSs), (ii) the availability of resources at regional, national and European level to deal with innovations, and (iii) a more direct involvement from EU and international institutions such as the European Centre for Disease Prevention and Control (ECDC), the World Health Organization (WHO) and the Organisation for Economic Cooperation and Development OECD for providing support and sustainable contributions. publishersversion published

Published
2022

24. The burden of injury in Central, Eastern, and Western European sub-region:a systematic analysis from the Global Burden of Disease 2019 Study

Author

Haagsma, Juanita A., Charalampous, Periklis, Ariani, Filippo, Gallay, Anne, Moesgaard Iburg, Kim, Nena, Evangelia, Ngwa, Che Henry, Rommel, Alexander, Zelviene, Ausra, Abegaz, Kedir Hussein, Al Hamad, Hanadi, Albano, Luciana, Liliana Andrei, Catalina, Andrei, Tudorel, Antonazzo, Ippazio Cosimo, Aremu, Olatunde, Arumugam, Ashokan, Atreya, Alok, Aujayeb, Avinash, Ayuso-Mateos, Jose Luis, Engelbert Bain, Luchuo, Banach, Maciej, Winfried Bärnighausen, Till, Barone-Adesi, Francesco, Beghi, Massimiliano, Bennett, Derrick A., Bhagavathula, Akshaya S., Carvalho, Félix, Castelpietra, Giulio, Caterina, Ledda, Chandan, Joht Singh, Couto, Rosa A.S., Cruz-Martins, Natália, Damiani, Giovanni, Dastiridou, Anna, Demetriades, Andreas K., Dias-da-Silva, Diana, Francis Fagbamigbe, Adeniyi, Fereshtehnejad, Seyed Mohammad, Fernandes, Eduarda, Ferrara, Pietro, Fischer, Florian, Fra.Paleo, Urbano, Ghirini, Silvia, Glasbey, James C., Glavan, Ionela Roxana, Gomes, Nelson G.M., Grivna, Michal, Harlianto, Netanja I., Haro, Josep Maria, Hasan, M. Tasdik, Hostiuc, Sorin, Iavicoli, Ivo, Ilic, Milena D., Ilic, Irena M., Jakovljevic, Mihajlo, Jonas, Jost B., Jerzy Jozwiak, Jacek, Jürisson, Mikk, Kauppila, Joonas H., Kayode, Gbenga A., Khan, Moien A.B., Kisa, Adnan, Kisa, Sezer, Koyanagi, Ai, Kumar, Manasi, Kurmi, Om P., La-Vecchia, Carlo, Lamnisos, Demetris, Lasrado, Savita, Lauriola, Paolo, Linn, Shai, Loureiro, Joana A., Lunevicius, Raimundas, Madureira-Carvalho, Aurea, Mechili, Enkeleint A., Majeed, Azeem, Menezes, Ritesh G., Mentis, Alexios Fotios A., Meretoja, Atte, Mestrovic, Tomislav, Miazgowski, Tomasz, Miazgowski, Bartosz, Mirica, Andreea, Molokhia, Mariam, Mohammed, Shafiu, Monasta, Lorenzo, Mulita, Francesk, David Naimzada, Mukhammad, Negoi, Ionut, Neupane, Subas, Oancea, Bogdan, Orru, Hans, Otoiu, Adrian, Otstavnov, Nikita, Otstavnov, Stanislav S., Padron-Monedero, Alicia, Panda-Jonas, Songhomitra, Pardhan, Shahina, Patel, Jay, Pedersini, Paolo, Pinheiro, Marina, Rakovac, Ivo, Rao, Chythra R., Rawaf, Salman, Rawaf, David Laith, Rodrigues, Violet, Ronfani, Luca, Sagoe, Dominic, Sanmarchi, Francesco, Santric-Milicevic, Milena M., Sathian, Brijesh, Sheikh, Aziz, Shiri, Rahman, Shivalli, Siddharudha, Dora Sigfusdottir, Inga, Sigurvinsdottir, Rannveig, Yurievich Skryabin, Valentin, Aleksandrovna Skryabina, Anna, Smarandache, Catalin Gabriel, Socea, Bogdan, Sousa, Raúl A.R.C., Steiropoulos, Paschalis, Tabarés-Seisdedos, Rafael, Roberto Tovani-Palone, Marcos, Tozija, Fimka, Van de Velde, Sarah, Juhani Vasankari, Tommi, Veroux, Massimiliano, Violante, Francesco S., Vlassov, Vasiliy, Wang, Yanzhong, Yadollahpour, Ali, Yaya, Sanni, Sergeevich Zastrozhin, Mikhail, Zastrozhina, Anasthasia, Polinder, Suzanne, Majdan, Marek, Haagsma, Juanita A., Charalampous, Periklis, Ariani, Filippo, Gallay, Anne, Moesgaard Iburg, Kim, Nena, Evangelia, Ngwa, Che Henry, Rommel, Alexander, Zelviene, Ausra, Abegaz, Kedir Hussein, Al Hamad, Hanadi, Albano, Luciana, Liliana Andrei, Catalina, Andrei, Tudorel, Antonazzo, Ippazio Cosimo, Aremu, Olatunde, Arumugam, Ashokan, Atreya, Alok, Aujayeb, Avinash, Ayuso-Mateos, Jose Luis, Engelbert Bain, Luchuo, Banach, Maciej, Winfried Bärnighausen, Till, Barone-Adesi, Francesco, Beghi, Massimiliano, Bennett, Derrick A., Bhagavathula, Akshaya S., Carvalho, Félix, Castelpietra, Giulio, Caterina, Ledda, Chandan, Joht Singh, Couto, Rosa A.S., Cruz-Martins, Natália, Damiani, Giovanni, Dastiridou, Anna, Demetriades, Andreas K., Dias-da-Silva, Diana, Francis Fagbamigbe, Adeniyi, Fereshtehnejad, Seyed Mohammad, Fernandes, Eduarda, Ferrara, Pietro, Fischer, Florian, Fra.Paleo, Urbano, Ghirini, Silvia, Glasbey, James C., Glavan, Ionela Roxana, Gomes, Nelson G.M., Grivna, Michal, Harlianto, Netanja I., Haro, Josep Maria, Hasan, M. Tasdik, Hostiuc, Sorin, Iavicoli, Ivo, Ilic, Milena D., Ilic, Irena M., Jakovljevic, Mihajlo, Jonas, Jost B., Jerzy Jozwiak, Jacek, Jürisson, Mikk, Kauppila, Joonas H., Kayode, Gbenga A., Khan, Moien A.B., Kisa, Adnan, Kisa, Sezer, Koyanagi, Ai, Kumar, Manasi, Kurmi, Om P., La-Vecchia, Carlo, Lamnisos, Demetris, Lasrado, Savita, Lauriola, Paolo, Linn, Shai, Loureiro, Joana A., Lunevicius, Raimundas, Madureira-Carvalho, Aurea, Mechili, Enkeleint A., Majeed, Azeem, Menezes, Ritesh G., Mentis, Alexios Fotios A., Meretoja, Atte, Mestrovic, Tomislav, Miazgowski, Tomasz, Miazgowski, Bartosz, Mirica, Andreea, Molokhia, Mariam, Mohammed, Shafiu, Monasta, Lorenzo, Mulita, Francesk, David Naimzada, Mukhammad, Negoi, Ionut, Neupane, Subas, Oancea, Bogdan, Orru, Hans, Otoiu, Adrian, Otstavnov, Nikita, Otstavnov, Stanislav S., Padron-Monedero, Alicia, Panda-Jonas, Songhomitra, Pardhan, Shahina, Patel, Jay, Pedersini, Paolo, Pinheiro, Marina, Rakovac, Ivo, Rao, Chythra R., Rawaf, Salman, Rawaf, David Laith, Rodrigues, Violet, Ronfani, Luca, Sagoe, Dominic, Sanmarchi, Francesco, Santric-Milicevic, Milena M., Sathian, Brijesh, Sheikh, Aziz, Shiri, Rahman, Shivalli, Siddharudha, Dora Sigfusdottir, Inga, Sigurvinsdottir, Rannveig, Yurievich Skryabin, Valentin, Aleksandrovna Skryabina, Anna, Smarandache, Catalin Gabriel, Socea, Bogdan, Sousa, Raúl A.R.C., Steiropoulos, Paschalis, Tabarés-Seisdedos, Rafael, Roberto Tovani-Palone, Marcos, Tozija, Fimka, Van de Velde, Sarah, Juhani Vasankari, Tommi, Veroux, Massimiliano, Violante, Francesco S., Vlassov, Vasiliy, Wang, Yanzhong, Yadollahpour, Ali, Yaya, Sanni, Sergeevich Zastrozhin, Mikhail, Zastrozhina, Anasthasia, Polinder, Suzanne, and Majdan, Marek

Abstract

Background: Injury remains a major concern to public health in the European region. Previous iterations of the Global Burden of Disease (GBD) study showed wide variation in injury death and disability adjusted life year (DALY) rates across Europe, indicating injury inequality gaps between sub-regions and countries. The objectives of this study were to: 1) compare GBD 2019 estimates on injury mortality and DALYs across European sub-regions and countries by cause-of-injury category and sex; 2) examine changes in injury DALY rates over a 20 year-period by cause-of-injury category, sub-region and country; and 3) assess inequalities in injury mortality and DALY rates across the countries. Methods: We performed a secondary database descriptive study using the GBD 2019 results on injuries in 44 European countries from 2000 to 2019. Inequality in DALY rates between these countries was assessed by calculating the DALY rate ratio between the highest-ranking country and lowest-ranking country in each year. Results: In 2019, in Eastern Europe 80 [95% uncertainty interval (UI): 71 to 89] people per 100,000 died from injuries; twice as high compared to Central Europe (38 injury deaths per 100,000; 95% UI 34 to 42) and three times as high compared to Western Europe (27 injury deaths per 100,000; 95%UI 25 to 28). The injury DALY rates showed less pronounced differences between Eastern (5129 DALYs per 100,000; 95% UI: 4547 to 5864), Central (2940 DALYs per 100,000; 95% UI: 2452 to 3546) and Western Europe (1782 DALYs per 100,000; 95% UI: 1523 to 2115). Injury DALY rate was lowest in Italy (1489 DALYs per 100,000) and highest in Ukraine (5553 DALYs per 100,000). The difference in injury DALY rates by country was larger for males compared to females. The DALY rate ratio was highest in 2005, with DALY rate in the lowest-ranking country (Russian Federation) 6.0 times higher compared to the highest-ranking country (Malta). After 2005, the DALY rate ratio between the lowest- and the hi

Published
2022

25. The burden of injury in Central, Eastern, and Western European sub-region: a systematic analysis from the Global Burden of Disease 2019 Study

Author

Haagsma, J, Charalampous, P, Ariani, F, Gallay, A, Moesgaard Iburg, K, Nena, E, Ngwa, C, Rommel, A, Zelviene, A, Abegaz, K, Al Hamad, H, Albano, L, Liliana Andrei, C, Andrei, T, Antonazzo, I, Aremu, O, Arumugam, A, Atreya, A, Aujayeb, A, Ayuso-Mateos, J, Engelbert Bain, L, Banach, M, Winfried Bärnighausen, T, Barone-Adesi, F, Beghi, M, Bennett, D, Bhagavathula, A, Carvalho, F, Castelpietra, G, Caterina, L, Chandan, J, Couto, R, Cruz-Martins, N, Damiani, G, Dastiridou, A, Demetriades, A, Dias-da-Silva, D, Francis Fagbamigbe, A, Fereshtehnejad, S, Fernandes, E, Ferrara, P, Fischer, F, Fra. Paleo, U, Ghirini, S, Glasbey, J, Glavan, I, Gomes, N, Grivna, M, Harlianto, N, Haro, J, Hasan, M, Hostiuc, S, Iavicoli, I, Ilic, M, Ilic, I, Jakovljevic, M, Jonas, J, Jerzy Jozwiak, J, Jürisson, M, Kauppila, J, Kayode, G, Khan, M, Kisa, A, Kisa, S, Koyanagi, A, Kumar, M, Kurmi, O, La-Vecchia, C, Lamnisos, D, Lasrado, S, Lauriola, P, Linn, S, Loureiro, J, Lunevicius, R, Madureira-Carvalho, A, Mechili, E, Majeed, A, Menezes, R, Mentis, A, Meretoja, A, Mestrovic, T, Miazgowski, T, Miazgowski, B, Mirica, A, Molokhia, M, Mohammed, S, Monasta, L, Mulita, F, David Naimzada, M, Negoi, I, Neupane, S, Oancea, B, Orru, H, Otoiu, A, Otstavnov, N, Otstavnov, S, Padron-Monedero, A, Panda-Jonas, S, Pardhan, S, Patel, J, Pedersini, P, Pinheiro, M, Rakovac, I, Rao, C, Rawaf, S, Rawaf, D, Rodrigues, V, Ronfani, L, Sagoe, D, Sanmarchi, F, Santric-Milicevic, M, Sathian, B, Sheikh, A, Shiri, R, Shivalli, S, Dora Sigfusdottir, I, Sigurvinsdottir, R, Yurievich Skryabin, V, Aleksandrovna Skryabina, A, Smarandache, C, Socea, B, Sousa, R, Steiropoulos, P, Tabarés-Seisdedos, R, Roberto Tovani-Palone, M, Tozija, F, Van de Velde, S, Juhani Vasankari, T, Veroux, M, Violante, F, Vlassov, V, Wang, Y, Yadollahpour, A, Yaya, S, Sergeevich Zastrozhin, M, Zastrozhina, A, Polinder, S, Majdan, M, Haagsma, Juanita A., Charalampous, Periklis, Ariani, Filippo, Gallay, Anne, Moesgaard Iburg, Kim, Nena, Evangelia, Ngwa, Che Henry, Rommel, Alexander, Zelviene, Ausra, Abegaz, Kedir Hussein, Al Hamad, Hanadi, Albano, Luciana, Liliana Andrei, Catalina, Andrei, Tudorel, Antonazzo, Ippazio Cosimo, Aremu, Olatunde, Arumugam, Ashokan, Atreya, Alok, Aujayeb, Avinash, Ayuso-Mateos, Jose Luis, Engelbert Bain, Luchuo, Banach, Maciej, Winfried Bärnighausen, Till, Barone-Adesi, Francesco, Beghi, Massimiliano, Bennett, Derrick A., Bhagavathula, Akshaya S., Carvalho, Félix, Castelpietra, Giulio, Caterina, Ledda, Chandan, Joht Singh, Couto, Rosa A. S., Cruz-Martins, Natália, Damiani, Giovanni, Dastiridou, Anna, Demetriades, Andreas K., Dias-da-Silva, Diana, Francis Fagbamigbe, Adeniyi, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Ferrara, Pietro, Fischer, Florian, Fra. Paleo, Urbano, Ghirini, Silvia, Glasbey, James C., Glavan, Ionela-Roxana, Gomes, Nelson G. M., Grivna, Michal, Harlianto, Netanja I., Haro, Josep Maria, Hasan, M. Tasdik, Hostiuc, Sorin, Iavicoli, Ivo, Ilic, Milena D., Ilic, Irena M., Jakovljevic, Mihajlo, Jonas, Jost B., Jerzy Jozwiak, Jacek, Jürisson, Mikk, Kauppila, Joonas H., Kayode, Gbenga A., Khan, Moien A. B., Kisa, Adnan, Kisa, Sezer, Koyanagi, Ai, Kumar, Manasi, Kurmi, Om P., La-Vecchia, Carlo, Lamnisos, Demetris, Lasrado, Savita, Lauriola, Paolo, Linn, Shai, Loureiro, Joana A., Lunevicius, Raimundas, Madureira-Carvalho, Aurea, Mechili, Enkeleint A., Majeed, Azeem, Menezes, Ritesh G., Mentis, Alexios-Fotios A., Meretoja, Atte, Mestrovic, Tomislav, Miazgowski, Tomasz, Miazgowski, Bartosz, Mirica, Andreea, Molokhia, Mariam, Mohammed, Shafiu, Monasta, Lorenzo, Mulita, Francesk, David Naimzada, Mukhammad, Negoi, Ionut, Neupane, Subas, Oancea, Bogdan, Orru, Hans, Otoiu, Adrian, Otstavnov, Nikita, Otstavnov, Stanislav S., Padron-Monedero, Alicia, Panda-Jonas, Songhomitra, Pardhan, Shahina, Patel, Jay, Pedersini, Paolo, Pinheiro, Marina, Rakovac, Ivo, Rao, Chythra R., Rawaf, Salman, Rawaf, David Laith, Rodrigues, Violet, Ronfani, Luca, Sagoe, Dominic, Sanmarchi, Francesco, Santric-Milicevic, Milena M., Sathian, Brijesh, Sheikh, Aziz, Shiri, Rahman, Shivalli, Siddharudha, Dora Sigfusdottir, Inga, Sigurvinsdottir, Rannveig, Yurievich Skryabin, Valentin, Aleksandrovna Skryabina, Anna, Smarandache, Catalin-Gabriel, Socea, Bogdan, Sousa, Raúl A. R. C., Steiropoulos, Paschalis, Tabarés-Seisdedos, Rafael, Roberto Tovani-Palone, Marcos, Tozija, Fimka, Van de Velde, Sarah, Juhani Vasankari, Tommi, Veroux, Massimiliano, Violante, Francesco S., Vlassov, Vasiliy, Wang, Yanzhong, Yadollahpour, Ali, Yaya, Sanni, Sergeevich Zastrozhin, Mikhail, Zastrozhina, Anasthasia, Polinder, Suzanne, Majdan, Marek, Haagsma, J, Charalampous, P, Ariani, F, Gallay, A, Moesgaard Iburg, K, Nena, E, Ngwa, C, Rommel, A, Zelviene, A, Abegaz, K, Al Hamad, H, Albano, L, Liliana Andrei, C, Andrei, T, Antonazzo, I, Aremu, O, Arumugam, A, Atreya, A, Aujayeb, A, Ayuso-Mateos, J, Engelbert Bain, L, Banach, M, Winfried Bärnighausen, T, Barone-Adesi, F, Beghi, M, Bennett, D, Bhagavathula, A, Carvalho, F, Castelpietra, G, Caterina, L, Chandan, J, Couto, R, Cruz-Martins, N, Damiani, G, Dastiridou, A, Demetriades, A, Dias-da-Silva, D, Francis Fagbamigbe, A, Fereshtehnejad, S, Fernandes, E, Ferrara, P, Fischer, F, Fra. Paleo, U, Ghirini, S, Glasbey, J, Glavan, I, Gomes, N, Grivna, M, Harlianto, N, Haro, J, Hasan, M, Hostiuc, S, Iavicoli, I, Ilic, M, Ilic, I, Jakovljevic, M, Jonas, J, Jerzy Jozwiak, J, Jürisson, M, Kauppila, J, Kayode, G, Khan, M, Kisa, A, Kisa, S, Koyanagi, A, Kumar, M, Kurmi, O, La-Vecchia, C, Lamnisos, D, Lasrado, S, Lauriola, P, Linn, S, Loureiro, J, Lunevicius, R, Madureira-Carvalho, A, Mechili, E, Majeed, A, Menezes, R, Mentis, A, Meretoja, A, Mestrovic, T, Miazgowski, T, Miazgowski, B, Mirica, A, Molokhia, M, Mohammed, S, Monasta, L, Mulita, F, David Naimzada, M, Negoi, I, Neupane, S, Oancea, B, Orru, H, Otoiu, A, Otstavnov, N, Otstavnov, S, Padron-Monedero, A, Panda-Jonas, S, Pardhan, S, Patel, J, Pedersini, P, Pinheiro, M, Rakovac, I, Rao, C, Rawaf, S, Rawaf, D, Rodrigues, V, Ronfani, L, Sagoe, D, Sanmarchi, F, Santric-Milicevic, M, Sathian, B, Sheikh, A, Shiri, R, Shivalli, S, Dora Sigfusdottir, I, Sigurvinsdottir, R, Yurievich Skryabin, V, Aleksandrovna Skryabina, A, Smarandache, C, Socea, B, Sousa, R, Steiropoulos, P, Tabarés-Seisdedos, R, Roberto Tovani-Palone, M, Tozija, F, Van de Velde, S, Juhani Vasankari, T, Veroux, M, Violante, F, Vlassov, V, Wang, Y, Yadollahpour, A, Yaya, S, Sergeevich Zastrozhin, M, Zastrozhina, A, Polinder, S, Majdan, M, Haagsma, Juanita A., Charalampous, Periklis, Ariani, Filippo, Gallay, Anne, Moesgaard Iburg, Kim, Nena, Evangelia, Ngwa, Che Henry, Rommel, Alexander, Zelviene, Ausra, Abegaz, Kedir Hussein, Al Hamad, Hanadi, Albano, Luciana, Liliana Andrei, Catalina, Andrei, Tudorel, Antonazzo, Ippazio Cosimo, Aremu, Olatunde, Arumugam, Ashokan, Atreya, Alok, Aujayeb, Avinash, Ayuso-Mateos, Jose Luis, Engelbert Bain, Luchuo, Banach, Maciej, Winfried Bärnighausen, Till, Barone-Adesi, Francesco, Beghi, Massimiliano, Bennett, Derrick A., Bhagavathula, Akshaya S., Carvalho, Félix, Castelpietra, Giulio, Caterina, Ledda, Chandan, Joht Singh, Couto, Rosa A. S., Cruz-Martins, Natália, Damiani, Giovanni, Dastiridou, Anna, Demetriades, Andreas K., Dias-da-Silva, Diana, Francis Fagbamigbe, Adeniyi, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Ferrara, Pietro, Fischer, Florian, Fra. Paleo, Urbano, Ghirini, Silvia, Glasbey, James C., Glavan, Ionela-Roxana, Gomes, Nelson G. M., Grivna, Michal, Harlianto, Netanja I., Haro, Josep Maria, Hasan, M. Tasdik, Hostiuc, Sorin, Iavicoli, Ivo, Ilic, Milena D., Ilic, Irena M., Jakovljevic, Mihajlo, Jonas, Jost B., Jerzy Jozwiak, Jacek, Jürisson, Mikk, Kauppila, Joonas H., Kayode, Gbenga A., Khan, Moien A. B., Kisa, Adnan, Kisa, Sezer, Koyanagi, Ai, Kumar, Manasi, Kurmi, Om P., La-Vecchia, Carlo, Lamnisos, Demetris, Lasrado, Savita, Lauriola, Paolo, Linn, Shai, Loureiro, Joana A., Lunevicius, Raimundas, Madureira-Carvalho, Aurea, Mechili, Enkeleint A., Majeed, Azeem, Menezes, Ritesh G., Mentis, Alexios-Fotios A., Meretoja, Atte, Mestrovic, Tomislav, Miazgowski, Tomasz, Miazgowski, Bartosz, Mirica, Andreea, Molokhia, Mariam, Mohammed, Shafiu, Monasta, Lorenzo, Mulita, Francesk, David Naimzada, Mukhammad, Negoi, Ionut, Neupane, Subas, Oancea, Bogdan, Orru, Hans, Otoiu, Adrian, Otstavnov, Nikita, Otstavnov, Stanislav S., Padron-Monedero, Alicia, Panda-Jonas, Songhomitra, Pardhan, Shahina, Patel, Jay, Pedersini, Paolo, Pinheiro, Marina, Rakovac, Ivo, Rao, Chythra R., Rawaf, Salman, Rawaf, David Laith, Rodrigues, Violet, Ronfani, Luca, Sagoe, Dominic, Sanmarchi, Francesco, Santric-Milicevic, Milena M., Sathian, Brijesh, Sheikh, Aziz, Shiri, Rahman, Shivalli, Siddharudha, Dora Sigfusdottir, Inga, Sigurvinsdottir, Rannveig, Yurievich Skryabin, Valentin, Aleksandrovna Skryabina, Anna, Smarandache, Catalin-Gabriel, Socea, Bogdan, Sousa, Raúl A. R. C., Steiropoulos, Paschalis, Tabarés-Seisdedos, Rafael, Roberto Tovani-Palone, Marcos, Tozija, Fimka, Van de Velde, Sarah, Juhani Vasankari, Tommi, Veroux, Massimiliano, Violante, Francesco S., Vlassov, Vasiliy, Wang, Yanzhong, Yadollahpour, Ali, Yaya, Sanni, Sergeevich Zastrozhin, Mikhail, Zastrozhina, Anasthasia, Polinder, Suzanne, and Majdan, Marek

Abstract

Background: Injury remains a major concern to public health in the European region. Previous iterations of the Global Burden of Disease (GBD) study showed wide variation in injury death and disability adjusted life year (DALY) rates across Europe, indicating injury inequality gaps between sub-regions and countries. The objectives of this study were to: 1) compare GBD 2019 estimates on injury mortality and DALYs across European sub-regions and countries by cause-of-injury category and sex; 2) examine changes in injury DALY rates over a 20 year-period by cause-of-injury category, sub-region and country; and 3) assess inequalities in injury mortality and DALY rates across the countries. Methods: We performed a secondary database descriptive study using the GBD 2019 results on injuries in 44 European countries from 2000 to 2019. Inequality in DALY rates between these countries was assessed by calculating the DALY rate ratio between the highest-ranking country and lowest-ranking country in each year. Results: In 2019, in Eastern Europe 80 [95% uncertainty interval (UI): 71 to 89] people per 100,000 died from injuries; twice as high compared to Central Europe (38 injury deaths per 100,000; 95% UI 34 to 42) and three times as high compared to Western Europe (27 injury deaths per 100,000; 95%UI 25 to 28). The injury DALY rates showed less pronounced differences between Eastern (5129 DALYs per 100,000; 95% UI: 4547 to 5864), Central (2940 DALYs per 100,000; 95% UI: 2452 to 3546) and Western Europe (1782 DALYs per 100,000; 95% UI: 1523 to 2115). Injury DALY rate was lowest in Italy (1489 DALYs per 100,000) and highest in Ukraine (5553 DALYs per 100,000). The difference in injury DALY rates by country was larger for males compared to females. The DALY rate ratio was highest in 2005, with DALY rate in the lowest-ranking country (Russian Federation) 6.0 times higher compared to the highest-ranking country (Malta). After 2005, the DALY rate ratio between the lowest- and the highe

Published
2022

26. Additional file 1 of Methodological guidelines to estimate population-based health indicators using linked data and/or machine learning techniques

Author

Haneef, Romana, Tijhuis, Mariken, Thi��baut, Rodolphe, M��jek, Ond��ej, Prista��, Ivan, Tolenan, Hanna, and Gallay, Anne

Abstract

Additional file 1. It describes the search strategies used to identify citations related to data linkage and/or machine learning technique used for studies focused on health status monitoring and health care.

Published
2022
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27. Additional file 2 of Ability of municipality-level deprivation indices to capture social inequalities in perinatal health in France: A nationwide study using preterm birth and small for gestational age to illustrate their relevance

Author

Barry, Yaya, Le Strat, Yann, Azria, Elie, Gorza, Maud, Pilkington, Hugo, Vandentorren, Sthéphanie, Gallay, Anne, and Regnault, Nolwenn

Abstract

Additional file 2: Appendix 2. SNDS and National perinatal surveys analyses: Multilevel models. Presentation of all covariables of the different multilevel models used in the NPS and SNDS statistical analyses.

Published
2022
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28. Additional file 4 of Ability of municipality-level deprivation indices to capture social inequalities in perinatal health in France: A nationwide study using preterm birth and small for gestational age to illustrate their relevance

Author

Barry, Yaya, Le Strat, Yann, Azria, Elie, Gorza, Maud, Pilkington, Hugo, Vandentorren, Sthéphanie, Gallay, Anne, and Regnault, Nolwenn

Abstract

Additional file 4: Appendix 4. Multivariate multilevel analyses for the FDep components in the SNDS. Association between FDep components and preterm birth and small for gestational age.

Published
2022
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29. Additional file 5 of Ability of municipality-level deprivation indices to capture social inequalities in perinatal health in France: A nationwide study using preterm birth and small for gestational age to illustrate their relevance

Author

Barry, Yaya, Le Strat, Yann, Azria, Elie, Gorza, Maud, Pilkington, Hugo, Vandentorren, Sthéphanie, Gallay, Anne, and Regnault, Nolwenn

Abstract

Additional file 5: Appendix 5. Multivariate multilevel analyses for the FDep components in the SNDS. Association between FEDI components and preterm birth and small for gestational age.

Published
2022
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30. Additional file 1 of Ability of municipality-level deprivation indices to capture social inequalities in perinatal health in France: A nationwide study using preterm birth and small for gestational age to illustrate their relevance

Author

Barry, Yaya, Le Strat, Yann, Azria, Elie, Gorza, Maud, Pilkington, Hugo, Vandentorren, Sthéphanie, Gallay, Anne, and Regnault, Nolwenn

Abstract

Additional file 1: Appendix 1. Algorithms of definition of covariables in the SNDS. Algorithms of the main exposure in the SNDS analyses.

Published
2022
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32. The burden of injury in Central, Eastern, and Western European sub-region: a systematic analysis from the Global Burden of Disease 2019 Study

Author

Charalampous, Periklis, primary, Haagsma, Juanita A., additional, Ariani, Filippo, additional, Gallay, Anne, additional, Iburg, Kim Moesgaard, additional, Nena, Evangelia, additional, Ngwa, Che Henry, additional, Rommel, Alexander, additional, Zelviene, Ausra, additional, Abegaz, Kedir Hussein, additional, Hamad, Hanadi Al, additional, Albano, Luciana, additional, Andrei, Catalina Liliana, additional, Andrei, Tudorel, additional, Antonazzo, Ippazio Cosimo, additional, Aremu, Olatunde, additional, Arumugam, Ashokan, additional, Atreya, Alok, additional, Aujayeb, Avinash, additional, Ayuso-Mateos, Jose Luis, additional, Bain, Luchuo Engelbert, additional, Banach, Maciej, additional, Bärnighausen, Till Winfried, additional, Barone-Adesi, Francesco, additional, Beghi, Massimiliano, additional, Bennett, Derrick A., additional, Bhagavathula, Akshaya S., additional, Carvalho, Félix, additional, Castelpietra, Giulio, additional, Caterina, Ledda, additional, Chandan, Joht Singh, additional, Couto, Rosa A.S., additional, Cruz-Martins, Natália, additional, Damiani, Giovanni, additional, Dastiridou, Anna, additional, Demetriades, Andreas K., additional, Dias-da-Silva, Diana, additional, Fagbamigbe, Adeniyi Francis, additional, Fereshtehnejad, Seyed-Mohammad, additional, Fernandes, Eduarda, additional, Ferrara, Pietro, additional, Fischer, Florian, additional, Fra.Paleo, Urbano, additional, Ghirini, Silvia, additional, Glasbey, James C., additional, Glavan, Ionela-Roxana, additional, Gomes, Nelson G.M., additional, Grivna, Michal, additional, Harlianto, Netanja I., additional, Haro, Josep Maria, additional, Hasan, M. Tasdik, additional, Hostiuc, Sorin, additional, Iavicoli, Ivo, additional, Ilic, Milena D., additional, Ilic, Irena M., additional, Jakovljevic, Mihajlo, additional, Jonas, Jost B., additional, Jozwiak, Jacek Jerzy, additional, Jürisson, Mikk, additional, Kauppila, Joonas H., additional, Kayode, Gbenga A., additional, Khan, Moien A.B., additional, Kisa, Adnan, additional, Kisa, Sezer, additional, Koyanagi, Ai, additional, Kumar, Manasi, additional, Kurmi, Om P., additional, La-Vecchia, Carlo, additional, Lamnisos, Demetris, additional, Lasrado, Savita, additional, Lauriola, Paolo, additional, Linn, Shai, additional, Loureiro, Joana A., additional, Lunevicius, Raimundas, additional, Madureira-Carvalho, Aurea, additional, Mechili, Enkeleint A., additional, Majeed, Azeem, additional, Menezes, Ritesh G., additional, Mentis, Alexios-Fotios A., additional, Meretoja, Atte, additional, Mestrovic, Tomislav, additional, Miazgowski, Tomasz, additional, Miazgowski, Bartosz, additional, Mirica, Andreea, additional, Molokhia, Mariam, additional, Mohammed, Shafiu, additional, Monasta, Lorenzo, additional, Mulita, Francesk, additional, Naimzada, Mukhammad David, additional, Negoi, Ionut, additional, Neupane, Subas, additional, Oancea, Bogdan, additional, Orru, Hans, additional, Otoiu, Adrian, additional, Otstavnov, Nikita, additional, Otstavnov, Stanislav S., additional, Padron-Monedero, Alicia, additional, Panda-Jonas, Songhomitra, additional, Pardhan, Shahina, additional, Patel, Jay, additional, Pedersini, Paolo, additional, Pinheiro, Marina, additional, Rakovac, Ivo, additional, Rao, Chythra R., additional, Rawaf, Salman, additional, Rawaf, David Laith, additional, Rodrigues, Violet, additional, Ronfani, Luca, additional, Sagoe, Dominic, additional, Sanmarchi, Francesco, additional, Santric-Milicevic, Milena M., additional, Sathian, Brijesh, additional, Sheikh, Aziz, additional, Shiri, Rahman, additional, Shivalli, Siddharudha, additional, Sigfusdottir, Inga Dora, additional, Sigurvinsdottir, Rannveig, additional, Skryabin, Valentin Yurievich, additional, Skryabina, Anna Aleksandrovna, additional, Smarandache, Catalin-Gabriel, additional, Socea, Bogdan, additional, Sousa, Raúl A.R.C., additional, Steiropoulos, Paschalis, additional, Tabarés-Seisdedos, Rafael, additional, Tovani-Palone, Marcos Roberto, additional, Tozija, Fimka, additional, de Velde, Sarah Van, additional, Vasankari, Tommi Juhani, additional, Veroux, Massimiliano, additional, Violante, Francesco S., additional, Vlassov, Vasiliy, additional, Wang, Yanzhong, additional, Yadollahpour, Ali, additional, Yaya, Sanni, additional, Zastrozhin, Mikhail Sergeevich, additional, Zastrozhina, Anasthasia, additional, Polinder, Suzanne, additional, and Majdan, Marek, additional

Published
2022
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33. Use of artificial intelligence for public health surveillance

Author

Haneef, Romana, Kab, Sofiane, Hrzic, Rok, Fuentes, Sonsoles, Fosse-Edorh, Sandrine, Cosson, Emmanuel, Gallay, Anne, Santé publique France - French National Public Health Agency [Saint-Maurice, France], Cohortes épidémiologiques en population (CONSTANCES), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay-Université Paris Cité (UPCité), University of Maastricht [Maastricht, Pays-Bas], Hôpital Avicenne [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Demarquay, Sandrine

Subjects
[SDV] Life Sciences [q-bio], Artificial intelligence, Diabetes mellitus, Electronic health records and public health surveillance, Incidence, [SDV]Life Sciences [q-bio], Health indicator, Machine learning technique, Supervise learning
Abstract

International audience; Abstract Background The use of machine learning techniques is increasing in healthcare which allows to estimate and predict health outcomes from large administrative data sets more efficiently. The main objective of this study was to develop a generic machine learning (ML) algorithm to estimate the incidence of diabetes based on the number of reimbursements over the last 2 years. Methods We selected a final data set from a population-based epidemiological cohort (i.e., CONSTANCES) linked with French National Health Database (i.e., SNDS). To develop this algorithm, we adopted a supervised ML approach. Following steps were performed: i. selection of final data set, ii. target definition, iii. Coding variables for a given window of time, iv. split final data into training and test data sets, v. variables selection, vi. training model, vii. Validation of model with test data set and viii. Selection of the model. We used the area under the receiver operating characteristic curve (AUC) to select the best algorithm. Results The final data set used to develop the algorithm included 44,659 participants from CONSTANCES. Out of 3468 variables from SNDS linked to CONSTANCES cohort were coded, 23 variables were selected to train different algorithms. The final algorithm to estimate the incidence of diabetes was a Linear Discriminant Analysis model based on number of reimbursements of selected variables related to biological tests, drugs, medical acts and hospitalization without a procedure over the last 2 years. This algorithm has a sensitivity of 62%, a specificity of 67% and an accuracy of 67% [95% CI: 0.66–0.68]. Conclusions Supervised ML is an innovative tool for the development of new methods to exploit large health administrative databases. In context of InfAct project, we have developed and applied the first time a generic ML-algorithm to estimate the incidence of diabetes for public health surveillance. The ML-algorithm we have developed, has a moderate performance. The next step is to apply this algorithm on SNDS to estimate the incidence of type 2 diabetes cases. More research is needed to apply various MLTs to estimate the incidence of various health conditions.

Published
2021

35. Additional file 1 of Recommendations to plan a national burden of disease study

Author

Haneef, Romana, Schmidt, Jürgen, Gallay, Anne, Devleesschauwer, Brecht, Grant, Ian, Rommel, Alexander, Wyper, Grant MA, Van Oyen, Herman, Hilderink, Henk, Ziese, Thomas, and Newton, John

Abstract

Additional file 1. It describes the summary of survey results and the format of questionnaire used to identify the need of European countries for BoD studies.

Published
2021
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36. Additional file 3 of Recommendations to plan a national burden of disease study

Author

Haneef, Romana, Schmidt, Jürgen, Gallay, Anne, Devleesschauwer, Brecht, Grant, Ian, Rommel, Alexander, Wyper, Grant MA, Van Oyen, Herman, Hilderink, Henk, Ziese, Thomas, and Newton, John

Abstract

Additional file 3. It describes the study results comparing the country health profiles and national health statistics and inputs from different countries.

Published
2021
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37. Additional file 1 of Use of artificial intelligence for public health surveillance: a case study to develop a machine Learning-algorithm to estimate the incidence of diabetes mellitus in France

Author

Haneef, Romana, Kab, Sofiane, Hrzic, Rok, Fuentes, Sonsoles, Fosse-Edorh, Sandrine, Cosson, Emmanuel, and Gallay, Anne

Abstract

Additional file 1. It describes the summary of results with three boosted algorithms [boosted version of logistic regression, boosted C5.0 classification model, and XGBoost] to our set of four models [i.e., 1. Linear discriminant analysis (LDA), 2. Logistic regression (LR), 3. Flexible discriminant analysis (FDA) and 4. Decision tree model (C5)]. It includes Table S 1.1 (main analysis), Table S1.2 (sensitivity analysis: over sampling), Table S1.3 (sensitivity analysis: down sampling), Table S2 (description of models used and the set of hyperparameters explored) and Table S3 (Area under curve: AUC).

Published
2021
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39. Recommendations to Plan a National Burden of Disease Study

Author

Haneef, Romana, primary, Schmidt, Jürgen, additional, Gallay, Anne, additional, Devleesschauwer, Brecht, additional, Grant, Ian, additional, Rommel, Alexander, additional, Wyper, Grant MA, additional, Oyen, Herman Van, additional, Hilderink, Henk, additional, Ziese, Thomas, additional, and Newton, John, additional

Published
2021
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40. Additional file 7 of Innovative use of data sources: a cross-sectional study of data linkage and artificial intelligence practices across European countries

Author

Haneef, Romana, Delnord, Marie, Vernay, Michel, Bauchet, Emmanuelle, Gaidelyte, Rita, Oyen, Herman Van, Or, Zeynep, Pérez-Gómez, Beatriz, Palmieri, Luigi, Achterberg, Peter, Tijhuis, Mariken, Zaletel, Metka, Mathis-Edenhofer, Stefan, Ondřej Májek, Haaheim, Håkon, Tolonen, Hanna, and Gallay, Anne

Abstract

Additional file 7. It is a doc. Word file and describes examples of health determinants identified using linked data across European countries in 2019.

Published
2020
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41. Additional file 3 of Innovative use of data sources: a cross-sectional study of data linkage and artificial intelligence practices across European countries

Author

Haneef, Romana, Delnord, Marie, Vernay, Michel, Bauchet, Emmanuelle, Gaidelyte, Rita, Oyen, Herman Van, Or, Zeynep, Pérez-Gómez, Beatriz, Palmieri, Luigi, Achterberg, Peter, Tijhuis, Mariken, Zaletel, Metka, Mathis-Edenhofer, Stefan, Ondřej Májek, Haaheim, Håkon, Tolonen, Hanna, and Gallay, Anne

Subjects
Data_FILES
Abstract

Additional file 3. It is a doc. Word file and include a table describing the names of survey respondents, their institutes and email addresses.

Published
2020
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42. Additional file 4 of Innovative use of data sources: a cross-sectional study of data linkage and artificial intelligence practices across European countries

Author

Haneef, Romana, Delnord, Marie, Vernay, Michel, Bauchet, Emmanuelle, Gaidelyte, Rita, Oyen, Herman Van, Or, Zeynep, Pérez-Gómez, Beatriz, Palmieri, Luigi, Achterberg, Peter, Tijhuis, Mariken, Zaletel, Metka, Mathis-Edenhofer, Stefan, Ondřej Májek, Haaheim, Håkon, Tolonen, Hanna, and Gallay, Anne

Abstract

Additional file 4. It is a doc. Word file and describes different data sources used for linkage across European countries in 2019.

Published
2020
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43. Additional file 8 of Innovative use of data sources: a cross-sectional study of data linkage and artificial intelligence practices across European countries

Author

Haneef, Romana, Delnord, Marie, Vernay, Michel, Bauchet, Emmanuelle, Gaidelyte, Rita, Oyen, Herman Van, Or, Zeynep, Pérez-Gómez, Beatriz, Palmieri, Luigi, Achterberg, Peter, Tijhuis, Mariken, Zaletel, Metka, Mathis-Edenhofer, Stefan, Ondřej Májek, Haaheim, Håkon, Tolonen, Hanna, and Gallay, Anne

Abstract

Additional file 8. It is a doc. Word file and describes examples of health intervention indicators estimated using linked data across European countries in 2019.

Published
2020
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44. Additional file 1 of Innovative use of data sources: a cross-sectional study of data linkage and artificial intelligence practices across European countries

Author

Haneef, Romana, Delnord, Marie, Vernay, Michel, Bauchet, Emmanuelle, Gaidelyte, Rita, Oyen, Herman Van, Or, Zeynep, Pérez-Gómez, Beatriz, Palmieri, Luigi, Achterberg, Peter, Tijhuis, Mariken, Zaletel, Metka, Mathis-Edenhofer, Stefan, Ondřej Májek, Haaheim, Håkon, Tolonen, Hanna, and Gallay, Anne

Abstract

Additional file 1. It is a doc. Word file. It describes the search strategies used to identify citations related to data linkage and machine learning technique used for health status monitoring.

Published
2020
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45. Additional file 6 of Innovative use of data sources: a cross-sectional study of data linkage and artificial intelligence practices across European countries

Author

Haneef, Romana, Delnord, Marie, Vernay, Michel, Bauchet, Emmanuelle, Gaidelyte, Rita, Oyen, Herman Van, Or, Zeynep, Pérez-Gómez, Beatriz, Palmieri, Luigi, Achterberg, Peter, Tijhuis, Mariken, Zaletel, Metka, Mathis-Edenhofer, Stefan, Ondřej Májek, Haaheim, Håkon, Tolonen, Hanna, and Gallay, Anne

Abstract

Additional file 6. It is a doc. Word file and describes examples of health outcome indicators estimated using linked data across European countries in 2019.

Published
2020
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46. Additional file 5 of Innovative use of data sources: a cross-sectional study of data linkage and artificial intelligence practices across European countries

Author

Haneef, Romana, Delnord, Marie, Vernay, Michel, Bauchet, Emmanuelle, Gaidelyte, Rita, Oyen, Herman Van, Or, Zeynep, Pérez-Gómez, Beatriz, Palmieri, Luigi, Achterberg, Peter, Tijhuis, Mariken, Zaletel, Metka, Mathis-Edenhofer, Stefan, Ondřej Májek, Haaheim, Håkon, Tolonen, Hanna, and Gallay, Anne

Abstract

Additional file 5. It is a doc word file and describes examples of different combinations of data linkage across European countries in 2019.

Published
2020
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47. Campylobacter antimicrobial drug resistance among humans, broiler chickens, and pigs, France

Author

Gallay, Anne, Prouzet-Mauleon, Valerie, Kempf, Isabelle, Lehours, Philippe, Labadi, Leila, Camou, Christine, Denis, Martine, de Valk, Henriette, Desenclos, Jean-Claude, and Megraud, Francis

Subjects
Campylobacter infections -- Risk factors, Campylobacter infections -- Diagnosis, Campylobacter infections -- Care and treatment, Anti-infective agents -- Health aspects
Abstract

We describe isolates from human Campylobacter infection in the French population and the isolates' antimicrobial drug resistance patterns since 1986 and compare the trends with those of isolates from broiler [...]

Published
2007

50. Liste des collaborateurs

Author

Alcaraz, Isabelle, primary, Aubin, François, additional, de Barbeyrac, Bertille, additional, Bébéar, Cécile M., additional, Bébéar, Christiane, additional, Bernard, Agathe, additional, Bianchi, Anne, additional, Bourgault-Villada, Isabelle, additional, Bouscarat, Fabrice, additional, Casin, Isabelle, additional, Caumes, Éric, additional, Derancourt, Christian, additional, Drobacheff-Thiébaut, Christine, additional, Dupin, Nicolas, additional, Farhi, David, additional, de Chauvin, Martine Feuilhade, additional, Fouéré, Sébastien, additional, Fournier, Lionel, additional, Gallay, Anne, additional, Gayno, Sophie, additional, Gerhardt, Philippe, additional, Juguet, Frédéric, additional, Lassau, François, additional, Le Goff, Jérôme, additional, Lepargneur, Jean-Pierre, additional, Méria, Paul, additional, Misery, Laurent, additional, Morini, Jean-Pierre, additional, Passeron, Alain, additional, Pelletier, Fabien, additional, Ramel, Françoise, additional, Timsit, Julie, additional, Vernay-Vaïsse, Chantal, additional, Vexiau-Robert, Dominique, additional, and Viraben, Roland, additional

Published
2009
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