Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 14 de 14
Filter
1.
BMJ paediatrics open ; 6(1), 2022.
Article in English | EuropePMC | ID: covidwho-2092727

ABSTRACT

Background The impact of the COVID-19 pandemic on paediatric populations varied between high-income countries (HICs) versus low-income to middle-income countries (LMICs). We sought to investigate differences in paediatric clinical outcomes and identify factors contributing to disparity between countries. Methods The International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC) COVID-19 database was queried to include children under 19 years of age admitted to hospital from January 2020 to April 2021 with suspected or confirmed COVID-19 diagnosis. Univariate and multivariable analysis of contributing factors for mortality were assessed by country group (HICs vs LMICs) as defined by the World Bank criteria. Results A total of 12 860 children (3819 from 21 HICs and 9041 from 15 LMICs) participated in this study. Of these, 8961 were laboratory-confirmed and 3899 suspected COVID-19 cases. About 52% of LMICs children were black, and more than 40% were infants and adolescent. Overall in-hospital mortality rate (95% CI) was 3.3% [=(3.0% to 3.6%), higher in LMICs than HICs (4.0% (3.6% to 4.4%) and 1.7% (1.3% to 2.1%), respectively). There were significant differences between country income groups in intervention profile, with higher use of antibiotics, antivirals, corticosteroids, prone positioning, high flow nasal cannula, non-invasive and invasive mechanical ventilation in HICs. Out of the 439 mechanically ventilated children, mortality occurred in 106 (24.1%) subjects, which was higher in LMICs than HICs (89 (43.6%) vs 17 (7.2%) respectively). Pre-existing infectious comorbidities (tuberculosis and HIV) and some complications (bacterial pneumonia, acute respiratory distress syndrome and myocarditis) were significantly higher in LMICs compared with HICs. On multivariable analysis, LMIC as country income group was associated with increased risk of mortality (adjusted HR 4.73 (3.16 to 7.10)). Conclusion Mortality and morbidities were higher in LMICs than HICs, and it may be attributable to differences in patient demographics, complications and access to supportive and treatment modalities.

2.
Elife ; 112022 10 05.
Article in English | MEDLINE | ID: covidwho-2056253

ABSTRACT

Background: Whilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, individual-level data on infecting variants are typically only available for a minority of patients and settings. Methods: Here, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries. Results: Our analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61-0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available individual-level data on infecting variant for a subset of the study population. Conclusions: Although clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome. Funding: Bronner P. Gonçalves, Peter Horby, Gail Carson, Piero L. Olliaro, Valeria Balan, Barbara Wanjiru Citarella, and research costs were supported by the UK Foreign, Commonwealth and Development Office (FCDO) and Wellcome [215091/Z/18/Z, 222410/Z/21/Z, 225288/Z/22/Z]; and Janice Caoili and Madiha Hashmi were supported by the UK FCDO and Wellcome [222048/Z/20/Z]. Peter Horby, Gail Carson, Piero L. Olliaro, Kalynn Kennon and Joaquin Baruch were supported by the Bill & Melinda Gates Foundation [OPP1209135]; Laura Merson was supported by University of Oxford's COVID-19 Research Response Fund - with thanks to its donors for their philanthropic support. Matthew Hall was supported by a Li Ka Shing Foundation award to Christophe Fraser. Moritz U.G. Kraemer was supported by the Branco Weiss Fellowship, Google.org, the Oxford Martin School, the Rockefeller Foundation, and the European Union Horizon 2020 project MOOD (#874850). The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission. Contributions from Srinivas Murthy, Asgar Rishu, Rob Fowler, James Joshua Douglas, François Martin Carrier were supported by CIHR Coronavirus Rapid Research Funding Opportunity OV2170359 and coordinated out of Sunnybrook Research Institute. Contributions from Evert-Jan Wils and David S.Y. Ong were supported by a grant from foundation Bevordering Onderzoek Franciscus; and Andrea Angheben by the Italian Ministry of Health "Fondi Ricerca corrente-L1P6" to IRCCS Ospedale Sacro Cuore-Don Calabria. The data contributions of J.Kenneth Baillie, Malcolm G. Semple, and Ewen M. Harrison were supported by grants from the National Institute for Health Research (NIHR; award CO-CIN-01), the Medical Research Council (MRC; grant MC_PC_19059), and by the NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool in partnership with Public Health England (PHE) (award 200907), NIHR HPRU in Respiratory Infections at Imperial College London with PHE (award 200927), Liverpool Experimental Cancer Medicine Centre (grant C18616/A25153), NIHR Biomedical Research Centre at Imperial College London (award IS-BRC-1215-20013), and NIHR Clinical Research Network providing infrastructure support. All funders of the ISARIC Clinical Characterisation Group are listed in the appendix.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , COVID-19/virology , Humans , SARS-CoV-2/genetics
3.
Baruch, Joaquin, Rojek, Amanda, Kartsonaki, Christiana, Vijayaraghavan, Bharath K. T.; Gonçalves, Bronner P.; Pritchard, Mark G.; Merson, Laura, Dunning, Jake, Hall, Matthew, Sigfrid, Louise, Citarella, Barbara W.; Murthy, Srinivas, Yeabah, Trokon O.; Olliaro, Piero, Abbas, Ali, Abdukahil, Sheryl Ann, Abdulkadir, Nurul Najmee, Abe, Ryuzo, Abel, Laurent, Absil, Lara, Acharya, Subhash, Acker, Andrew, Adam, Elisabeth, Adrião, Diana, Al Ageel, Saleh, Ahmed, Shakeel, Ainscough, Kate, Airlangga, Eka, Aisa, Tharwat, Hssain, Ali Ait, Tamlihat, Younes Ait, Akimoto, Takako, Akmal, Ernita, Al Qasim, Eman, Alalqam, Razi, Alberti, Angela, Al‐dabbous, Tala, Alegesan, Senthilkumar, Alegre, Cynthia, Alessi, Marta, Alex, Beatrice, Alexandre, Kévin, Al‐Fares, Abdulrahman, Alfoudri, Huda, Ali, Imran, Ali, Adam, Shah, Naseem Ali, Alidjnou, Kazali Enagnon, Aliudin, Jeffrey, Alkhafajee, Qabas, Allavena, Clotilde, Allou, Nathalie, Altaf, Aneela, Alves, João, Alves, Rita, Alves, João Melo, Amaral, Maria, Amira, Nur, Ampaw, Phoebe, Andini, Roberto, Andréjak, Claire, Angheben, Andrea, Angoulvant, François, Ansart, Séverine, Anthonidass, Sivanesen, Antonelli, Massimo, de Brito, Carlos Alexandre Antunes, Apriyana, Ardiyan, Arabi, Yaseen, Aragao, Irene, Araujo, Carolline, Arcadipane, Antonio, Archambault, Patrick, Arenz, Lukas, Arlet, Jean‐Benoît, Arora, Lovkesh, Arora, Rakesh, Artaud‐Macari, Elise, Aryal, Diptesh, Asensio, Angel, Ashraf, Muhammad, Asif, Namra, Asim, Mohammad, Assie, Jean Baptiste, Asyraf, Amirul, Atique, Anika, Attanyake, A. M. Udara Lakshan, Auchabie, Johann, Aumaitre, Hugues, Auvet, Adrien, Axelsen, Eyvind W.; Azemar, Laurène, Azoulay, Cecile, Bach, Benjamin, Bachelet, Delphine, Badr, Claudine, Bævre‐Jensen, Roar, Baig, Nadia, Baillie, J. Kenneth, Baird, J. Kevin, Bak, Erica, Bakakos, Agamemnon, Bakar, Nazreen Abu, Bal, Andriy, Balakrishnan, Mohanaprasanth, Balan, Valeria, Bani‐Sadr, Firouzé, Barbalho, Renata, Barbosa, Nicholas Yuri, Barclay, Wendy S.; Barnett, Saef Umar, Barnikel, Michaela, Barrasa, Helena, Barrelet, Audrey, Barrigoto, Cleide, Bartoli, Marie, Baruch, Joaquín, Bashir, Mustehan, Basmaci, Romain, Basri, Muhammad Fadhli Hassin, Battaglini, Denise, Bauer, Jules, Rincon, Diego Fernando Bautista, Dow, Denisse Bazan, Beane, Abigail, Bedossa, Alexandra, Bee, Ker Hong, Begum, Husna, Behilill, Sylvie, Beishuizen, Albertus, Beljantsev, Aleksandr, Bellemare, David, Beltrame, Anna, Beltrão, Beatriz Amorim, Beluze, Marine, Benech, Nicolas, Benjiman, Lionel Eric, Benkerrou, Dehbia, Bennett, Suzanne, Bento, Luís, Berdal, Jan‐Erik, Bergeaud, Delphine, Bergin, Hazel, Sobrino, José Luis Bernal, Bertoli, Giulia, Bertolino, Lorenzo, Bessis, Simon, Bevilcaqua, Sybille, Bezulier, Karine, Bhatt, Amar, Bhavsar, Krishna, Bianco, Claudia, Bidin, Farah Nadiah, Singh, Moirangthem Bikram, Humaid, Felwa Bin, Kamarudin, Mohd Nazlin Bin, Bissuel, François, Bitker, Laurent, Bitton, Jonathan, Blanco‐Schweizer, Pablo, Blier, Catherine, Bloos, Frank, Blot, Mathieu, Boccia, Filomena, Bodenes, Laetitia, Bogaarts, Alice, Bogaert, Debby, Boivin, Anne‐Hélène, Bolze, Pierre‐Adrien, Bompart, François, Bonfasius, Aurelius, Borges, Diogo, Borie, Raphaël, Bosse, Hans Martin, Botelho‐Nevers, Elisabeth, Bouadma, Lila, Bouchaud, Olivier, Bouchez, Sabelline, Bouhmani, Dounia, Bouhour, Damien, Bouiller, Kévin, Bouillet, Laurence, Bouisse, Camile, Boureau, Anne‐Sophie, Bourke, John, Bouscambert, Maude, Bousquet, Aurore, Bouziotis, Jason, Boxma, Bianca, Boyer‐Besseyre, Marielle, Boylan, Maria, Bozza, Fernando Augusto, Braconnier, Axelle, Braga, Cynthia, Brandenburger, Timo, Monteiro, Filipa Brás, Brazzi, Luca, Breen, Patrick, Breen, Dorothy, Breen, Patrick, Brickell, Kathy, Browne, Shaunagh, Browne, Alex, Brozzi, Nicolas, Brunvoll, Sonja Hjellegjerde, Brusse‐Keizer, Marjolein, Buchtele, Nina, Buesaquillo, Christian, Bugaeva, Polina, Buisson, Marielle, Buonsenso, Danilo, Burhan, Erlina, Burrell, Aidan, Bustos, Ingrid G.; Butnaru, Denis, Cabie, André, Cabral, Susana, Caceres, Eder, Cadoz, Cyril, Calligy, Kate, Calvache, Jose Andres, Camões, João, Campana, Valentine, Campbell, Paul, Campisi, Josie, Canepa, Cecilia, Cantero, Mireia, Caraux‐Paz, Pauline, Cárcel, Sheila, Cardellino, Chiara Simona, Cardoso, Sofia, Cardoso, Filipe, Cardoso, Filipa, Cardoso, Nelson, Carelli, Simone, Carlier, Nicolas, Carmoi, Thierry, Carney, Gayle, Carqueja, Inês, Carret, Marie‐Christine, Carrier, François Martin, Carroll, Ida, Carson, Gail, Casanova, Maire‐Laure, Cascão, Mariana, Casey, Siobhan, Casimiro, José, Cassandra, Bailey, Castañeda, Silvia, Castanheira, Nidyanara, Castor‐Alexandre, Guylaine, Castrillón, Henry, Castro, Ivo, Catarino, Ana, Catherine, François‐Xavier, Cattaneo, Paolo, Cavalin, Roberta, Cavalli, Giulio Giovanni, Cavayas, Alexandros, Ceccato, Adrian, Cervantes‐Gonzalez, Minerva, Chair, Anissa, Chakveatze, Catherine, Chan, Adrienne, Chand, Meera, Auger, Christelle Chantalat, Chapplain, Jean‐Marc, Chas, Julie, Chatterjee, Allegra, Chaudry, Mobin, Iñiguez, Jonathan Samuel Chávez, Chen, Anjellica, Chen, Yih‐Sharng, Cheng, Matthew Pellan, Cheret, Antoine, Chiarabini, Thibault, Chica, Julian, Chidambaram, Suresh Kumar, Tho, Leong Chin, Chirouze, Catherine, Chiumello, Davide, Cho, Sung‐Min, Cholley, Bernard, Chopin, Marie‐Charlotte, Chow, Ting Soo, Chow, Yock Ping, Chua, Jonathan, Chua, Hiu Jian, Cidade, Jose Pedro, Herreros, José Miguel Cisneros, Citarella, Barbara Wanjiru, Ciullo, Anna, Clarke, Jennifer, Clarke, Emma, Granado, Rolando Claure‐Del, Clohisey, Sara, Cobb, Perren J.; Codan, Cassidy, Cody, Caitriona, Coelho, Alexandra, Coles, Megan, Colin, Gwenhaël, Collins, Michael, Colombo, Sebastiano Maria, Combs, Pamela, Connor, Marie, Conrad, Anne, Contreras, Sofía, Conway, Elaine, Cooke, Graham S.; Copland, Mary, Cordel, Hugues, Corley, Amanda, Cornelis, Sabine, Cornet, Alexander Daniel, Corpuz, Arianne Joy, Cortegiani, Andrea, Corvaisier, Grégory, Costigan, Emma, Couffignal, Camille, Couffin‐Cadiergues, Sandrine, Courtois, Roxane, Cousse, Stéphanie, Cregan, Rachel, Croonen, Sabine, Crowl, Gloria, Crump, Jonathan, Cruz, Claudina, Bermúdez, Juan Luis Cruz, Rojo, Jaime Cruz, Csete, Marc, Cullen, Ailbhe, Cummings, Matthew, Curley, Gerard, Curlier, Elodie, Curran, Colleen, Custodio, Paula, da Silva Filipe, Ana, Da Silveira, Charlene, Dabaliz, Al‐Awwab, Dagens, Andrew, Dahl, John Arne, Dahly, Darren, Dalton, Heidi, Dalton, Jo, Daly, Seamus, Daneman, Nick, Daniel, Corinne, Dankwa, Emmanuelle A.; Dantas, Jorge, D'Aragon, Frédérick, de Loughry, Gillian, de Mendoza, Diego, De Montmollin, Etienne, de Oliveira França, Rafael Freitas, de Pinho Oliveira, Ana Isabel, De Rosa, Rosanna, De Rose, Cristina, de Silva, Thushan, de Vries, Peter, Deacon, Jillian, Dean, David, Debard, Alexa, Debray, Marie‐Pierre, DeCastro, Nathalie, Dechert, William, Deconninck, Lauren, Decours, Romain, Defous, Eve, Delacroix, Isabelle, Delaveuve, Eric, Delavigne, Karen, Delfos, Nathalie M.; Deligiannis, Ionna, Dell'Amore, Andrea, Delmas, Christelle, Delobel, Pierre, Delsing, Corine, Demonchy, Elisa, Denis, Emmanuelle, Deplanque, Dominique, Depuydt, Pieter, Desai, Mehul, Descamps, Diane, Desvallées, Mathilde, Dewayanti, Santi, Dhanger, Pathik, Diallo, Alpha, Diamantis, Sylvain, Dias, André, Diaz, Juan Jose, Diaz, Priscila, Diaz, Rodrigo, Didier, Kévin, Diehl, Jean‐Luc, Dieperink, Wim, Dimet, Jérôme, Dinot, Vincent, Diop, Fara, Diouf, Alphonsine, Dishon, Yael, Djossou, Félix, Docherty, Annemarie B.; Doherty, Helen, Dondorp, Arjen M.; Donnelly, Maria, Donnelly, Christl A.; Donohue, Sean, Donohue, Yoann, Donohue, Chloe, Doran, Peter, Dorival, Céline, D'Ortenzio, Eric, Douglas, James Joshua, Douma, Renee, Dournon, Nathalie, Downer, Triona, Downey, Joanne, Downing, Mark, Drake, Tom, Driscoll, Aoife, Dryden, Murray, Fonseca, Claudio Duarte, Dubee, Vincent, Dubos, François, Ducancelle, Alexandre, Duculan, Toni, Dudman, Susanne, Duggal, Abhijit, Dunand, Paul, Dunning, Jake, Duplaix, Mathilde, Durante‐Mangoni, Emanuele, Durham, Lucian, Dussol, Bertrand, Duthoit, Juliette, Duval, Xavier, Dyrhol‐Riise, Anne Margarita, Ean, Sim Choon, Echeverria‐Villalobos, Marco, Egan, Siobhan, Eggesbø, Linn Margrete, Eira, Carla, El Sanharawi, Mohammed, Elapavaluru, Subbarao, Elharrar, Brigitte, Ellerbroek, Jacobien, Ellingjord‐Dale, Merete, Eloy, Philippine, Elshazly, Tarek, Elyazar, Iqbal, Enderle, Isabelle, Endo, Tomoyuki, Eng, Chan Chee, Engelmann, Ilka, Enouf, Vincent, Epaulard, Olivier, Escher, Martina, Esperatti, Mariano, Esperou, Hélène, Esposito‐Farese, Marina, Estevão, João, Etienne, Manuel, Ettalhaoui, Nadia, Everding, Anna Greti, Evers, Mirjam, Fabre, Marc, Fabre, Isabelle, Faheem, Amna, Fahy, Arabella, Fairfield, Cameron J.; Fakar, Zul, Fareed, Komal, Faria, Pedro, Farooq, Ahmed, Fateena, Hanan, Fatoni, Arie Zainul, Faure, Karine, Favory, Raphaël, Fayed, Mohamed, Feely, Niamh, Feeney, Laura, Fernandes, Jorge, Fernandes, Marília Andreia, Fernandes, Susana, Ferrand, François‐Xavier, Devouge, Eglantine Ferrand, Ferrão, Joana, Ferraz, Mário, Ferreira, Sílvia, Ferreira, Isabel, Ferreira, Benigno, Ferrer‐Roca, Ricard, Ferriere, Nicolas, Ficko, Céline, Figueiredo‐Mello, Claudia, Finlayson, William, Fiorda, Juan, Flament, Thomas, Flateau, Clara, Fletcher, Tom, Florio, Letizia Lucia, Flynn, Deirdre, Foley, Claire, Foley, Jean, Fomin, Victor, Fonseca, Tatiana, Fontela, Patricia, Forsyth, Simon, Foster, Denise, Foti, Giuseppe, Fourn, Erwan, Fowler, Robert A.; Fraher, Marianne, Franch‐Llasat, Diego, Fraser, John F.; Fraser, Christophe, Freire, Marcela Vieira, Ribeiro, Ana Freitas, Friedrich, Caren, Fry, Stéphanie, Fuentes, Nora, Fukuda, Masahiro, Argin, G.; Gaborieau, Valérie, Gaci, Rostane, Gagliardi, Massimo, Gagnard, Jean‐Charles, Gagneux‐Brunon, Amandine, Gaião, Sérgio, Skeie, Linda Gail, Gallagher, Phil, Gamble, Carrol, Gani, Yasmin, Garan, Arthur, Garcia, Rebekha, Barrio, Noelia García, Garcia‐Diaz, Julia, Garcia‐Gallo, Esteban, Garimella, Navya, Garot, Denis, Garrait, Valérie, Gauli, Basanta, Gault, Nathalie, Gavin, Aisling, Gavrylov, Anatoliy, Gaymard, Alexandre, Gebauer, Johannes, Geraud, Eva, Morlaes, Louis Gerbaud, Germano, Nuno, Ghisulal, Praveen Kumar, Ghosn, Jade, Giani, Marco, Gibson, Jess, Gigante, Tristan, Gilg, Morgane, Gilroy, Elaine, Giordano, Guillermo, Girvan, Michelle, Gissot, Valérie, Glikman, Daniel, Glybochko, Petr, Gnall, Eric, Goco, Geraldine, Goehringer, François, Goepel, Siri, Goffard, Jean‐Christophe, Goh, Jin Yi, Golob, Jonathan, Gomez, Kyle, Gómez‐Junyent, Joan, Gominet, Marie, Gonçalves, Bronner P.; Gonzalez, Alicia, Gordon, Patricia, Gorenne, Isabelle, Goubert, Laure, Goujard, Cécile, Goulenok, Tiphaine, Grable, Margarite, Graf, Jeronimo, Grandin, Edward Wilson, Granier, Pascal, Grasselli, Giacomo, Green, Christopher A.; Greene, Courtney, Greenhalf, William, Greffe, Segolène, Grieco, Domenico Luca, Griffee, Matthew, Griffiths, Fiona, Grigoras, Ioana, Groenendijk, Albert, Lordemann, Anja Grosse, Gruner, Heidi, Gu, Yusing, Guedj, Jérémie, Guego, Martin, Guellec, Dewi, Guerguerian, Anne‐Marie, Guerreiro, Daniela, Guery, Romain, Guillaumot, Anne, Guilleminault, Laurent, Guimarães de Castro, Maisa, Guimard, Thomas, Haalboom, Marieke, Haber, Daniel, Habraken, Hannah, Hachemi, Ali, Hackmann, Amy, Hadri, Nadir, Haidri, Fakhir, Hakak, Sheeba, Hall, Adam, Hall, Matthew, Halpin, Sophie, Hameed, Jawad, Hamer, Ansley, Hamers, Raph L.; Hamidfar, Rebecca, Hammarström, Bato, Hammond, Terese, Han, Lim Yuen, Haniffa, Rashan, Hao, Kok Wei, Hardwick, Hayley, Harrison, Ewen M.; Harrison, Janet, Harrison, Samuel Bernard Ekow, Hartman, Alan, Hasan, Mohd Shahnaz, Hashmi, Junaid, Hayat, Muhammad, Hayes, Ailbhe, Hays, Leanne, Heerman, Jan, Heggelund, Lars, Hendry, Ross, Hennessy, Martina, Henriquez‐Trujillo, Aquiles, Hentzien, Maxime, Hernandez‐Montfort, Jaime, Hershey, Andrew, Hesstvedt, Liv, Hidayah, Astarini, Higgins, Eibhilin, Higgins, Dawn, Higgins, Rupert, Hinchion, Rita, Hinton, Samuel, Hiraiwa, Hiroaki, Hirkani, Haider, Hitoto, Hikombo, Ho, Yi Bin, Ho, Antonia, Hoctin, Alexandre, Hoffmann, Isabelle, Hoh, Wei Han, Hoiting, Oscar, Holt, Rebecca, Holter, Jan Cato, Horby, Peter, Horcajada, Juan Pablo, Hoshino, Koji, Houas, Ikram, Hough, Catherine L.; Houltham, Stuart, Hsu, Jimmy Ming‐Yang, Hulot, Jean‐Sébastien, Huo, Stella, Hurd, Abby, Hussain, Iqbal, Ijaz, Samreen, Illes, Hajnal‐Gabriela, Imbert, Patrick, Imran, Mohammad, Sikander, Rana Imran, Imtiaz, Aftab, Inácio, Hugo, Dominguez, Carmen Infante, Ing, Yun Sii, Iosifidis, Elias, Ippolito, Mariachiara, Isgett, Sarah, Isidoro, Tiago, Ismail, Nadiah, Isnard, Margaux, Istre, Mette Stausland, Itai, Junji, Ivulich, Daniel, Jaafar, Danielle, Jaafoura, Salma, Jabot, Julien, Jackson, Clare, Jamieson, Nina, Jaquet, Pierre, Jaud‐Fischer, Coline, Jaureguiberry, Stéphane, Jaworsky, Denise, Jego, Florence, Jelani, Anilawati Mat, Jenum, Synne, Jimbo‐Sotomayor, Ruth, Joe, Ong Yiaw, Jorge García, Ruth N.; Jørgensen, Silje Bakken, Joseph, Cédric, Joseph, Mark, Joshi, Swosti, Jourdain, Mercé, Jouvet, Philippe, Jung, Hanna, Jung, Anna, Juzar, Dafsah, Kafif, Ouifiya, Kaguelidou, Florentia, Kaisbain, Neerusha, Kaleesvran, Thavamany, Kali, Sabina, Kalicinska, Alina, Kalleberg, Karl Trygve, Kalomoiri, Smaragdi, Kamaluddin, Muhammad Aisar Ayadi, Kamaruddin, Zul Amali Che, Kamarudin, Nadiah, Kamineni, Kavita, Kandamby, Darshana Hewa, Kandel, Chris, Kang, Kong Yeow, Kanwal, Darakhshan, Karpayah, Pratap, Kartsonaki, Christiana, Kasugai, Daisuke, Kataria, Anant, Katz, Kevin, Kaur, Aasmine, Kay, Christy, Keane, Hannah, Keating, Seán, Kedia, Pulak, Kelly, Claire, Kelly, Yvelynne, Kelly, Andrea, Kelly, Niamh, Kelly, Aoife, Kelly, Sadie, Kelsey, Maeve, Kennedy, Ryan, Kennon, Kalynn, Kernan, Maeve, Kerroumi, Younes, Keshav, Sharma, Khalid, Imrana, Khalid, Osama, Khalil, Antoine, Khan, Coralie, Khan, Irfan, Khan, Quratul Ain, Khanal, Sushil, Khatak, Abid, Khawaja, Amin, Kherajani, Krish, Kho, Michelle E.; Khoo, Ryan, Khoo, Denisa, Khoo, Saye, Khoso, Nasir, Kiat, Khor How, Kida, Yuri, Kiiza, Peter, Granerud, Beathe Kiland, Kildal, Anders Benjamin, Kim, Jae Burm, Kimmoun, Antoine, Kindgen‐Milles, Detlef, King, Alexander, Kitamura, Nobuya, Kjetland, Eyrun Floerecke Kjetland, Klenerman, Paul, Klont, Rob, Bekken, Gry Kloumann, Knight, Stephen R.; Kobbe, Robin, Kodippily, Chamira, Vasconcelos, Malte Kohns, Koirala, Sabin, Komatsu, Mamoru, Kosgei, Caroline, Kpangon, Arsène, Krawczyk, Karolina, Krishnan, Vinothini, Krishnan, Sudhir, Kruglova, Oksana, Kumar, Ganesh, Kumar, Deepali, Kumar, Mukesh, Vecham, Pavan Kumar, Kuriakose, Dinesh, Kurtzman, Ethan, Kutsogiannis, Demetrios, Kutsyna, Galyna, Kyriakoulis, Konstantinos, Lachatre, Marie, Lacoste, Marie, Laffey, John G.; Lagrange, Marie, Laine, Fabrice, Lairez, Olivier, Lakhey, Sanjay, Lalueza, Antonio, Lambert, Marc, Lamontagne, François, Langelot‐Richard, Marie, Langlois, Vincent, Lantang, Eka Yudha, Lanza, Marina, Laouénan, Cédric, Laribi, Samira, Lariviere, Delphine, Lasry, Stéphane, Lath, Sakshi, Latif, Naveed, Launay, Odile, Laureillard, Didier, Lavie‐Badie, Yoan, Law, Andy, Lawrence, Teresa, Lawrence, Cassie, Le, Minh, Le Bihan, Clément, Le Bris, Cyril, Le Falher, Georges, Le Fevre, Lucie, Le Hingrat, Quentin, Le Maréchal, Marion, Le Mestre, Soizic, Le Moal, Gwenaël, Le Moing, Vincent, Le Nagard, Hervé, Le Turnier, Paul, Leal, Ema, Santos, Marta Leal, Lee, Heng Gee, Lee, Biing Horng, Lee, Yi Lin, Lee, Todd C.; Lee, James, Lee, Jennifer, Lee, Su Hwan, Leeming, Gary, Lefebvre, Laurent, Lefebvre, Bénédicte, Lefèvre, Benjamin, LeGac, Sylvie, Lelievre, Jean‐Daniel, Lellouche, François, Lemaignen, Adrien, Lemee, Véronique, Lemeur, Anthony, Lemmink, Gretchen, Lene, Ha Sha, Lennon, Jenny, León, Rafael, Leone, Marc, Leone, Michela, Lepiller, Quentin, Lescure, François‐Xavier, Lesens, Olivier, Lesouhaitier, Mathieu, Lester‐Grant, Amy, Levy, Yves, Levy, Bruno, Levy‐Marchal, Claire, Lewandowska, Katarzyna, L'Her, Erwan, Bassi, Gianluigi Li, Liang, Janet, Liaquat, Ali, Liegeon, Geoffrey, Lim, Kah Chuan, Lim, Wei Shen, Lima, Chantre, Lina, Lim, Lina, Bruno, Lind, Andreas, Lingad, Maja Katherine, Lingas, Guillaume, Lion‐Daolio, Sylvie, Lissauer, Samantha, Liu, Keibun, Livrozet, Marine, Lizotte, Patricia, Loforte, Antonio, Lolong, Navy, Loon, Leong Chee, Lopes, Diogo, Lopez‐Colon, Dalia, Lopez‐Revilla, Jose W.; Loschner, Anthony L.; Loubet, Paul, Loufti, Bouchra, Louis, Guillame, Lourenco, Silvia, Lovelace‐Macon, Lara, Low, Lee Lee, Lowik, Marije, Loy, Jia Shyi, Lucet, Jean Christophe, Bermejo, Carlos Lumbreras, Luna, Carlos M.; Lungu, Olguta, Luong, Liem, Luque, Nestor, Luton, Dominique, Lwin, Nilar, Lyons, Ruth, Maasikas, Olavi, Mabiala, Oryane, Machado, Moïse, Macheda, Gabriel, Madiha, Hashmi, Maestro de la Calle, Guillermo, Mahieu, Rafael, Mahy, Sophie, Maia, Ana Raquel, Maier, Lars S.; Maillet, Mylène, Maitre, Thomas, Malfertheiner, Maximilian, Malik, Nadia, Mallon, Paddy, Maltez, Fernando, Malvy, Denis, Manda, Victoria, Mandelbrot, Laurent, Manetta, Frank, Mankikian, Julie, Manning, Edmund, Manuel, Aldric, Sant'Ana Malaque, Ceila Maria, Marino, Flávio, Marino, Daniel, Markowicz, Samuel, Maroun Eid, Charbel, Marques, Ana, Marquis, Catherine, Marsh, Brian, Marsh, Laura, Marshal, Megan, Marshall, John, Martelli, Celina Turchi, Martin, Dori‐Ann, Martin, Emily, Martin‐Blondel, Guillaume, Martin‐Loeches, Ignacio, Martinot, Martin, Martin‐Quiros, Alejandro, Martins, João, Martins, Ana, Martins, Nuno, Rego, Caroline Martins, Martucci, Gennaro, Martynenko, Olga, Marwali, Eva Miranda, Marzukie, Marsilla, Maslove, David, Mason, Sabina, Masood, Sobia, Nor, Basri Mat, Matan, Moshe, Mathew, Meghena, Mathieu, Daniel, Mattei, Mathieu, Matulevics, Romans, Maulin, Laurence, Maxwell, Michael, Maynar, Javier, Mazzoni, Thierry, Evoy, Natalie Mc, Sweeney, Lisa Mc, McArthur, Colin, McArthur, Colin, McCarthy, Anne, McCarthy, Aine, McCloskey, Colin, McConnochie, Rachael, McDermott, Sherry, McDonald, Sarah E.; McElroy, Aine, McElwee, Samuel, McEneany, Victoria, McGeer, Allison, McKay, Chris, McKeown, Johnny, McLean, Kenneth A.; McNally, Paul, McNicholas, Bairbre, McPartlan, Elaine, Meaney, Edel, Mear‐Passard, Cécile, Mechlin, Maggie, Meher, Maqsood, Mehkri, Omar, Mele, Ferruccio, Melo, Luis, Memon, Kashif, Mendes, Joao Joao, Menkiti, Ogechukwu, Menon, Kusum, Mentré, France, Mentzer, Alexander J.; Mercier, Noémie, Mercier, Emmanuelle, Merckx, Antoine, Mergeay‐Fabre, Mayka, Mergler, Blake, Merson, Laura, Mesquita, António, Meta, Roberta, Metwally, Osama, Meybeck, Agnès, Meyer, Dan, Meynert, Alison M.; Meysonnier, Vanina, Meziane, Amina, Mezidi, Mehdi, Michelanglei, Céline, Michelet, Isabelle, Mihelis, Efstathia, Mihnovit, Vladislav, Miranda‐Maldonado, Hugo, Misnan, Nor Arisah, Mohamed, Tahira Jamal, Mohamed, Nik Nur Eliza, Moin, Asma, Molina, David, Molinos, Elena, Molloy, Brenda, Mone, Mary, Monteiro, Agostinho, Montes, Claudia, Montrucchio, Giorgia, Moore, Shona C.; Moore, Sarah, Cely, Lina Morales, Moro, Lucia, Morton, Ben, Motherway, Catherine, Motos, Ana, Mouquet, Hugo, Perrot, Clara Mouton, Moyet, Julien, Mudara, Caroline, Mufti, Aisha Kalsoom, Muh, Ng Yong, Muhamad, Dzawani, Mullaert, Jimmy, Müller, Fredrik, Müller, Karl Erik, Munblit, Daniel, Muneeb, Syed, Munir, Nadeem, Munshi, Laveena, Murphy, Aisling, Murphy, Lorna, Murphy, Aisling, Murris, Marlène, Murthy, Srinivas, Musaab, Himed, Muvindi, Himasha, Muyandy, Gugapriyaa, Myrodia, Dimitra Melia, Mohd‐Hanafiah, Farah Nadia, Nagpal, Dave, Nagrebetsky, Alex, Narasimhan, Mangala, Narayanan, Nageswaran, Khan, Rashid Nasim, Nazerali‐Maitland, Alasdair, Neant, Nadège, Neb, Holger, Nekliudov, Nikita, Nelwan, Erni, Neto, Raul, Neumann, Emily, Ng, Pauline Yeung, Ng, Wing Yiu, Nghi, Anthony, Nguyen, Duc, Choileain, Orna Ni, Leathlobhair, Niamh Ni, Nichol, Alistair, Nitayavardhana, Prompak, Nonas, Stephanie, Noordin, Nurul Amani Mohd, Noret, Marion, Norharizam, Nurul Faten Izzati, Norman, Lisa, Notari, Alessandra, Noursadeghi, Mahdad, Nowicka, Karolina, Nowinski, Adam, Nseir, Saad, Nunez, Jose I.; Nurnaningsih, Nurnaningsih, Nusantara, Dwi Utomo, Nyamankolly, Elsa, Nygaard, Anders Benteson, Brien, Fionnuala O.; Callaghan, Annmarie O.; O'Callaghan, Annmarie, Occhipinti, Giovanna, Oconnor, Derbrenn, O'Donnell, Max, Ogston, Tawnya, Ogura, Takayuki, Oh, Tak‐Hyuk, O'Halloran, Sophie, O'Hearn, Katie, Ohshimo, Shinichiro, Oldakowska, Agnieszka, Oliveira, João, Oliveira, Larissa, Olliaro, Piero L.; Ong, Jee Yan, Ong, David S. Y.; Oosthuyzen, Wilna, Opavsky, Anne, Openshaw, Peter, Orakzai, Saijad, Orozco‐Chamorro, Claudia Milena, Ortoleva, Jamel, Osatnik, Javier, O'Shea, Linda, O'Sullivan, Miriam, Othman, Siti Zubaidah, Ouamara, Nadia, Ouissa, Rachida, Oziol, Eric, Pagadoy, Maïder, Pages, Justine, Palacios, Mario, Palacios, Amanda, Palmarini, Massimo, Panarello, Giovanna, Panda, Prasan Kumar, Paneru, Hem, Pang, Lai Hui, Panigada, Mauro, Pansu, Nathalie, Papadopoulos, Aurélie, Parke, Rachael, Parker, Melissa, Parra, Briseida, Pasha, Taha, Pasquier, Jérémie, Pastene, Bruno, Patauner, Fabian, Patel, Drashti, Pathmanathan, Mohan Dass, Patrão, Luís, Patricio, Patricia, Patrier, Juliette, Patterson, Lisa, Pattnaik, Rajyabardhan, Paul, Mical, Paul, Christelle, Paulos, Jorge, Paxton, William A.; Payen, Jean‐François, Peariasamy, Kalaiarasu, Jiménez, Miguel Pedrera, Peek, Giles J.; Peelman, Florent, Peiffer‐Smadja, Nathan, Peigne, Vincent, Pejkovska, Mare, Pelosi, Paolo, Peltan, Ithan D.; Pereira, Rui, Perez, Daniel, Periel, Luis, Perpoint, Thomas, Pesenti, Antonio, Pestre, Vincent, Petrou, Lenka, Petrovic, Michele, Petrov‐Sanchez, Ventzislava, Pettersen, Frank Olav, Peytavin, Gilles, Pharand, Scott, Picard, Walter, Picone, Olivier, de Piero, Maria, Pierobon, Carola, Piersma, Djura, Pimentel, Carlos, Pinto, Raquel, Pires, Catarina, Pironneau, Isabelle, Piroth, Lionel, Pitaloka, Ayodhia, Pius, Riinu, Plantier, Laurent, Png, Hon Shen, Poissy, Julien, Pokeerbux, Ryadh, Pokorska‐Spiewak, Maria, Poli, Sergio, Pollakis, Georgios, Ponscarme, Diane, Popielska, Jolanta, Porto, Diego Bastos, Post, Andra‐Maris, Postma, Douwe F.; Povoa, Pedro, Póvoas, Diana, Powis, Jeff, Prapa, Sofia, Preau, Sébastien, Prebensen, Christian, Preiser, Jean‐Charles, Prinssen, Anton, Pritchard, Mark G.; Priyadarshani, Gamage Dona Dilanthi, Proença, Lucia, Pudota, Sravya, Puéchal, Oriane, Semedi, Bambang Pujo, Pulicken, Mathew, Purcell, Gregory, Quesada, Luisa, Quinones‐Cardona, Vilmaris, González, Víctor Quirós, Quist‐Paulsen, Else, Quraishi, Mohammed, Rabaa, Maia, Rabaud, Christian, Rabindrarajan, Ebenezer, Rafael, Aldo, Rafiq, Marie, Rahardjani, Mutia, Rahman, Rozanah Abd, Rahman, Ahmad Kashfi Haji Ab, Rahutullah, Arsalan, Rainieri, Fernando, Rajahram, Giri Shan, Ramachandran, Pratheema, Ramakrishnan, Nagarajan, Ramli, Ahmad Afiq, Rammaert, Blandine, Ramos, Grazielle Viana, Rana, Asim, Rangappa, Rajavardhan, Ranjan, Ritika, Rapp, Christophe, Rashan, Aasiyah, Rashan, Thalha, Rasheed, Ghulam, Rasmin, Menaldi, Rätsep, Indrek, Rau, Cornelius, Ravi, Tharmini, Raza, Ali, Real, Andre, Rebaudet, Stanislas, Redl, Sarah, Reeve, Brenda, Rehman, Attaur, Reid, Liadain, Reikvam, Dag Henrik, Reis, Renato, Rello, Jordi, Remppis, Jonathan, Remy, Martine, Ren, Hongru, Renk, Hanna, Resseguier, Anne‐Sophie, Revest, Matthieu, Rewa, Oleksa, Reyes, Luis Felipe, Reyes, Tiago, Ribeiro, Maria Ines, Ricchiuto, Antonia, Richardson, David, Richardson, Denise, Richier, Laurent, Ridzuan, Siti Nurul Atikah Ahmad, Riera, Jordi, Rios, Ana L.; Rishu, Asgar, Rispal, Patrick, Risso, Karine, Nuñez, Maria Angelica Rivera, Rizer, Nicholas, Robba, Chiara, Roberto, André, Roberts, Stephanie, Robertson, David L.; Robineau, Olivier, Roche‐Campo, Ferran, Rodari, Paola, Rodeia, Simão, Abreu, Julia Rodriguez, Roessler, Bernhard, Roger, Pierre‐Marie, Roger, Claire, Roilides, Emmanuel, Rojek, Amanda, Romaru, Juliette, Roncon‐Albuquerque, Roberto, Roriz, Mélanie, Rosa‐Calatrava, Manuel, Rose, Michael, Rosenberger, Dorothea, Roslan, Nurul Hidayah Mohammad, Rossanese, Andrea, Rossetti, Matteo, Rossignol, Bénédicte, Rossignol, Patrick, Rousset, Stella, Roy, Carine, Roze, Benoît, Rusmawatiningtyas, Desy, Russell, Clark D.; Ryan, Maria, Ryan, Maeve, Ryckaert, Steffi, Holten, Aleksander Rygh, Saba, Isabela, Sadaf, Sairah, Sadat, Musharaf, Sahraei, Valla, Saint‐Gilles, Maximilien, Sakiyalak, Pranya, Salahuddin, Nawal, Salazar, Leonardo, Saleem, Jodat, Sales, Gabriele, Sallaberry, Stéphane, Salmon Gandonniere, Charlotte, Salvator, Hélène, Sanchez, Olivier, Sanchez‐Miralles, Angel, Sancho‐Shimizu, Vanessa, Sandhu, Gyan, Sandhu, Zulfiqar, Sandrine, Pierre‐François, Sandulescu, Oana, Santos, Marlene, Sarfo‐Mensah, Shirley, Banheiro, Bruno Sarmento, Sarmiento, Iam Claire E.; Sarton, Benjamine, Satya, Ankana, Satyapriya, Sree, Satyawati, Rumaisah, Saviciute, Egle, Savvidou, Parthena, Saw, Yen Tsen, Schaffer, Justin, Schermer, Tjard, Scherpereel, Arnaud, Schneider, Marion, Schroll, Stephan, Schwameis, Michael, Schwartz, Gary, Scott, Janet T.; Scott‐Brown, James, Sedillot, Nicholas, Seitz, Tamara, Selvanayagam, Jaganathan, Selvarajoo, Mageswari, Semaille, Caroline, Semple, Malcolm G.; Senian, Rasidah Bt, Senneville, Eric, Sequeira, Filipa, Sequeira, Tânia, Neto, Ary Serpa, Balazote, Pablo Serrano, Shadowitz, Ellen, Shahidan, Syamin Asyraf, Shamsah, Mohammad, Shankar, Anuraj, Sharjeel, Shaikh, Sharma, Pratima, Shaw, Catherine A.; Shaw, Victoria, Sheharyar, Ashraf, Shetty, Rohan, Shetty, Rajesh Mohan, Shi, Haixia, Shiekh, Mohiuddin, Shime, Nobuaki, Shimizu, Keiki, Shrapnel, Sally, Shrestha, Pramesh Sundar, Shrestha, Shubha Kalyan, Shum, Hoi Ping, Mohammed, Nassima Si, Siang, Ng Yong, Sibiude, Jeanne, Siddiqui, Atif, Sigfrid, Louise, Sillaots, Piret, Silva, Catarina, Silva, Rogério, Silva, Maria Joao, Heng, Benedict Sim Lim, Sin, Wai Ching, Sinatti, Dario, Singh, Punam, Singh, Budha Charan, Sitompul, Pompini Agustina, Sivam, Karisha, Skogen, Vegard, Smith, Sue, Smood, Benjamin, Smyth, Coilin, Smyth, Michelle, Snacken, Morgane, So, Dominic, Soh, Tze Vee, Solberg, Lene Bergendal, Solomon, Joshua, Solomon, Tom, Somers, Emily, Sommet, Agnès, Song, Rima, Song, Myung Jin, Song, Tae, Chia, Jack Song, Sonntagbauer, Michael, Soom, Azlan Mat, Søraas, Arne, Søraas, Camilla Lund, Sotto, Alberto, Soum, Edouard, Sousa, Marta, Sousa, Ana Chora, Uva, Maria Sousa, Souza‐Dantas, Vicente, Sperry, Alexandra, Spinuzza, Elisabetta, Darshana, B. P. Sanka Ruwan Sri, Sriskandan, Shiranee, Stabler, Sarah, Staudinger, Thomas, Stecher, Stephanie‐Susanne, Steinsvik, Trude, Stienstra, Ymkje, Stiksrud, Birgitte, Stolz, Eva, Stone, Amy, Streinu‐Cercel, Adrian, Streinu‐Cercel, Anca, Stuart, David, Stuart, Ami, Subekti, Decy, Suen, Gabriel, Suen, Jacky Y.; Sultana, Asfia, Summers, Charlotte, Supic, Dubravka, Suppiah, Deepashankari, Surovcová, Magdalena, Suwarti, Suwarti, Svistunov, Andrey, Syahrin, Sarah, Syrigos, Konstantinos, Sztajnbok, Jaques, Szuldrzynski, Konstanty, Tabrizi, Shirin, Taccone, Fabio S.; Tagherset, Lysa, Taib, Shahdattul Mawarni, Talarek, Ewa, Taleb, Sara, Talsma, Jelmer, Tamisier, Renaud, Tampubolon, Maria Lawrensia, Tan, Kim Keat, Tan, Yan Chyi, Tanaka, Taku, Tanaka, Hiroyuki, Taniguchi, Hayato, Taqdees, Huda, Taqi, Arshad, Tardivon, Coralie, Tattevin, Pierre, Taufik, M. Azhari, Tawfik, Hassan, Tedder, Richard S.; Tee, Tze Yuan, Teixeira, João, Tejada, Sofia, Tellier, Marie‐Capucine, Teoh, Sze Kye, Teotonio, Vanessa, Téoulé, François, Terpstra, Pleun, Terrier, Olivier, Terzi, Nicolas, Tessier‐Grenier, Hubert, Tey, Adrian, Thabit, Alif Adlan Mohd, Thakur, Anand, Tham, Zhang Duan, Thangavelu, Suvintheran, Thibault, Vincent, Thiberville, Simon‐Djamel, Thill, Benoît, Thirumanickam, Jananee, Thompson, Shaun, Thomson, Emma C.; Thurai, Surain Raaj Thanga, Thwaites, Ryan S.; Tierney, Paul, Tieroshyn, Vadim, Timashev, Peter S.; Timsit, Jean‐François, Vijayaraghavan, Bharath Kumar Tirupakuzhi, Tissot, Noémie, Toh, Jordan Zhien Yang, Toki, Maria, Tonby, Kristian, Tonnii, Sia Loong, Torres, Margarida, Torres, Antoni, Santos‐Olmo, Rosario Maria Torres, Torres‐Zevallos, Hernando, Towers, Michael, Trapani, Tony, Treoux, Théo, Tromeur, Cécile, Trontzas, Ioannis, Trouillon, Tiffany, Truong, Jeanne, Tual, Christelle, Tubiana, Sarah, Tuite, Helen, Turmel, Jean‐Marie, Turtle, Lance C. W.; Tveita, Anders, Twardowski, Pawel, Uchiyama, Makoto, Udayanga, P. G. Ishara, Udy, Andrew, Ullrich, Roman, Uribe, Alberto, Usman, Asad.
Influenza and Other Respiratory Viruses ; 2022.
Article in English | Web of Science | ID: covidwho-2019369

ABSTRACT

Introduction: Case definitions are used to guide clinical practice, surveillance and research protocols. However, how they identify COVID-19-hospitalised patients is not fully understood. We analysed the proportion of hospitalised patients with laboratory-confirmed COVID-19, in the ISARIC prospective cohort study database, meeting widely used case definitions. Methods: Patients were assessed using the Centers for Disease Control (CDC), European Centre for Disease Prevention and Control (ECDC), World Health Organization (WHO) and UK Health Security Agency (UKHSA) case definitions by age, region and time. Case fatality ratios (CFRs) and symptoms of those who did and who did not meet the case definitions were evaluated. Patients with incomplete data and non-laboratory-confirmed test result were excluded. Results: A total of 263,218 of the patients (42%) in the ISARIC database were included. Most patients (90.4%) were from Europe arid Central Asia. The proportions of patients meeting the case definitions were 56.8% (WHO), 74.4% (UKHSA), 81.6% (ECDC) and 82.3% (CDC). For each case definition, patients at the extremes of age distribution met the criteria less frequently than those aged 30 to 70 years;geographical and time variations were also observed. Estimated CFRs were similar for the patients who met the case definitions. However, when more patients did riot meet the case definition, the CFR increased. Conclusions: The performance of case definitions might be different in different regions and may change over time. Similarly concerning is the fact that older patients often did not meet case definitions, risking delayed medical care. While epidemiologists must balance their analytics with field applicability, ongoing revision of case definitions is necessary to improve patient care through early diagnosis and limit potential nosocomial spread.

4.
Sci Data ; 9(1): 454, 2022 07 30.
Article in English | MEDLINE | ID: covidwho-1967615

ABSTRACT

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use.


Subject(s)
COVID-19 , Hospitalization , Humans , Pandemics , Prospective Studies , SARS-CoV-2
5.
BMJ Open ; 12(5): e054601, 2022 05 04.
Article in English | MEDLINE | ID: covidwho-1891819

ABSTRACT

BACKGROUND: Many COVID-19 patients are discharged home from hospital with instructions to self-isolate. This reduces the burden on potentially overwhelmed hospitals. The Royal Melbourne Hospital (RMH) Home Monitoring Programme (HMP) is a model of care for COVID-19 patients which chiefly tracks pulse oximetry and body temperature readings. OBJECTIVE: To evaluate the feasibility and acceptability of the HMP from a patient perspective. DESIGN, SETTINGS AND PARTICIPANTS: Of 46 COVID-19 patients who used the HMP through RMH during April to August 2020, 16 were invited to participate in this qualitative evaluation study; all accepted, including 6 healthcare workers. Attempts were made to recruit a gender-balanced sample across a range of COVID-19 severities and comorbidities. Participants completed a brief semistructured phone interview discussing their experience of using the HMP. OUTCOME MEASURES AND ANALYSIS: A thematic analysis of interview data was conducted. Feasibility was defined as the HMP's reported ease of use. Acceptability was considered holistically by reviewing themes in the interview data. RESULTS: The HMP allowed clinical deterioration to be recognised as it occurred enabling prompt intervention. All participants reported a positive opinion of the HMP, stating it was highly acceptable and easy to use. Almost all participants said they found using it reassuring. Patients frequently mentioned the importance of the monitoring clinicians as an information conduit. The most suggested improvement was to monitor a broader set of symptoms. CONCLUSIONS: The HMP is highly feasible and acceptable to patients. This model of care could potentially be implemented on a mass-scale to reduce the burden of COVID-19 on hospitals. A key benefit of the HMP is the ability to reassure patients they will receive suitable intervention should they deteriorate while isolating outside of hospital settings.


Subject(s)
COVID-19 , COVID-19/epidemiology , Hospitals , Humans , Monitoring, Physiologic , Qualitative Research
6.
Emerg Med Australas ; 34(5): 758-768, 2022 10.
Article in English | MEDLINE | ID: covidwho-1759137

ABSTRACT

OBJECTIVE: To identify behavioural drivers and barriers that may have contributed to changes in ED attendance during the first 10 months of the coronavirus disease 2019 (COVID-19) pandemic in Victoria. METHODS: We conducted a mixed methods analysis of patients who attended one of eight participating EDs between 1 November 2019 and 31 December 2020. A random sample of patients were chosen after their visit and invited to participate in an online survey assessing behavioural drivers and barriers to attendance. The study timespan was divided into four periods based on local and world events to assess changes in attitudes and behaviours over this period. RESULTS: A total of 5600 patients were invited to complete the survey and 606 (11%) submitted sufficient information for analysis. There were significant differences in participants' attitudes towards healthcare and EDs, levels of concern about contracting and spreading COVID-19 and the influence of mask wearing. Patients expressed more concern about the safety of an ED during the largest outbreak of COVID-19 infections than they did pre-COVID, but this difference was not sustained once community infection numbers dropped. General concerns about hospital attendance were higher after COVID than they were pre-COVID. A total of 27% of patients specifically stated that they had delayed their ED attendance. CONCLUSION: Patients expressed increased concerns around attending ED during the first 10 months of the 2020 COVID-19 pandemic and frequently cited COVID-19 as a reason for delaying their presentation. These factors would be amenable to mitigation via focussed public health messaging.


Subject(s)
COVID-19 , Pandemics , COVID-19/epidemiology , Emergency Service, Hospital , Humans , Public Health , SARS-CoV-2
7.
ERJ open research ; 2021.
Article in English | EuropePMC | ID: covidwho-1610380

ABSTRACT

Due to the large number of patients with severe COVID-19, many were treated outside of the traditional walls of the ICU, and in many cases, by personnel who were not trained in critical care. The clinical characteristics and the relative impact of caring for severe COVID-19 patients outside of the ICU is unknown. This was a multinational, multicentre, prospective cohort study embedded in the ISARIC WHO COVID-19 platform. Severe COVID-19 patients were identified as those admitted to an ICU and/or those treated with one of the following treatments: invasive or non-invasive mechanical ventilation, high-flow nasal cannula, inotropes, and vasopressors. A logistic Generalised Additive Model was used to compare clinical outcomes among patients admitted and not to the ICU. A total of 40 440 patients from 43 countries and six continents were included in this analysis. Severe COVID-19 patients were frequently male (62.9%), older adults (median [IQR], 67 years [55, 78]), and with at least one comorbidity (63.2%). The overall median (IQR) length of hospital stay was 10 days (5–19) and was longer in patients admitted to an ICU than in those that were cared for outside of ICU (12 [6–23] versus 8 [4–15] days, p<0.0001). The 28-day fatality ratio was lower in ICU-admitted patients (30.7% [5797/18831] versus 39.0% [7532/19295], p<0.0001). Patients admitted to an ICU had a significantly lower probability of death than those who were not (adjusted OR:0.70, 95%CI: 0.65-0.75, p<0.0001). Patients with severe COVID-19 admitted to an ICU had significantly lower 28-day fatality ratio than those cared for outside of an ICU.

8.
Elife ; 102021 11 23.
Article in English | MEDLINE | ID: covidwho-1529015

ABSTRACT

Background: There is potentially considerable variation in the nature and duration of the care provided to hospitalised patients during an infectious disease epidemic or pandemic. Improvements in care and clinician confidence may shorten the time spent as an inpatient, or the need for admission to an intensive care unit (ICU) or high dependency unit (HDU). On the other hand, limited resources at times of high demand may lead to rationing. Nevertheless, these variables may be used as static proxies for disease severity, as outcome measures for trials, and to inform planning and logistics. Methods: We investigate these time trends in an extremely large international cohort of 142,540 patients hospitalised with COVID-19. Investigated are: time from symptom onset to hospital admission, probability of ICU/HDU admission, time from hospital admission to ICU/HDU admission, hospital case fatality ratio (hCFR) and total length of hospital stay. Results: Time from onset to admission showed a rapid decline during the first months of the pandemic followed by peaks during August/September and December 2020. ICU/HDU admission was more frequent from June to August. The hCFR was lowest from June to August. Raw numbers for overall hospital stay showed little variation, but there is clear decline in time to discharge for ICU/HDU survivors. Conclusions: Our results establish that variables of these kinds have limitations when used as outcome measures in a rapidly evolving situation. Funding: This work was supported by the UK Foreign, Commonwealth and Development Office and Wellcome [215091/Z/18/Z] and the Bill & Melinda Gates Foundation [OPP1209135]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.


Subject(s)
Hospitalization/statistics & numerical data , Outcome Assessment, Health Care/statistics & numerical data , SARS-CoV-2/pathogenicity , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/therapy , Child , Child, Preschool , Female , Humans , Infant , Intensive Care Units/statistics & numerical data , Length of Stay/statistics & numerical data , Male , Middle Aged , Retrospective Studies , Young Adult
9.
Lancet Reg Health West Pac ; 9: 100115, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1117260

ABSTRACT

BACKGROUND: In Australia, COVID-19 diagnosis relies on RT-PCR testing which is relatively costly and time-consuming. To date, few studies have assessed the performance and implementation of rapid antigen-based SARS-CoV-2 testing in a setting with a low prevalence of COVID-19 infections, such as Australia. METHODS: This study recruited participants presenting for COVID-19 testing at three Melbourne metropolitan hospitals during a period of low COVID-19 prevalence. The Abbott PanBioTM COVID-19 Ag point-of-care test was performed alongside RT-PCR. In addition, participants with COVID-19 notified to the Victorian Government were invited to provide additional swabs to aid validation. Implementation challenges were also documented. FINDINGS: The specificity of the Abbott PanBioTM COVID-19 Ag test was 99.96% (95% CI 99.73 - 100%). Sensitivity amongst participants with RT-PCR-confirmed infection was dependent upon the duration of symptoms reported, ranging from 77.3% (duration 1 to 33 days) to 100% in those within seven days of symptom onset. A range of implementation challenges were identified which may inform future COVID-19 testing strategies in a low prevalence setting. INTERPRETATION: Given the high specificity, antigen-based tests may be most useful in rapidly triaging public health and hospital resources while expediting confirmatory RT-PCR testing. Considering the limitations in test sensitivity and the potential for rapid transmission in susceptible populations, particularly in hospital settings, careful consideration is required for implementation of antigen testing in a low prevalence setting. FUNDING: This work was funded by the Victorian Department of Health and Human Services. The funder was not involved in data analysis or manuscript preparation.

11.
Emerg Med Australas ; 32(5): 809-813, 2020 10.
Article in English | MEDLINE | ID: covidwho-733269

ABSTRACT

OBJECTIVE: Early during the coronavirus disease 2019 (COVID-19) pandemic, Australian EDs experienced an unprecedented surge in patients seeking screening. Understanding what proportion of these patients require testing and who can be safely screened in community-based models of care is critical for workforce and infrastructure planning across the healthcare system, as well as public messaging campaigns. METHODS: In this cross-sectional survey, we screened patients presenting to a COVID-19 screening clinic in a tertiary ED. We assessed the proportion of patients who met testing criteria; self-reported symptom severity; reasons why they came to the ED for screening and views on community-based care. RESULTS: We include findings from 1846 patients. Most patients (55.3%) did not meet contemporaneous criteria for testing and most (57.6%) had mild or no (13.4%) symptoms. The main reason for coming to the ED was being referred by a telephone health service (31.3%) and 136 (7.4%) said they tried to contact their general practitioner but could not get an appointment. Only 47 (2.6%) said they thought the disease was too specialised for their general practitioner to manage. CONCLUSIONS: While capacity building in acute care facilities is an important part of pandemic planning, it is also important that patients not needing hospital level of care can be assessed and treated elsewhere. We have identified a significant proportion of people at this early stage in the pandemic who have sought healthcare at hospital but who might have been assisted in the community had services been available and public health messaging structured to guide them there.


Subject(s)
Coronavirus Infections/diagnosis , Health Services Accessibility/statistics & numerical data , Mass Screening/organization & administration , Pandemics/statistics & numerical data , Patient Preference , Pneumonia, Viral/diagnosis , Ambulatory Care Facilities/statistics & numerical data , Australia , COVID-19 , Coronavirus Infections/epidemiology , Cross-Sectional Studies , Emergency Service, Hospital/statistics & numerical data , Female , Humans , Incidence , Male , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , Public Health , Risk Assessment , Tertiary Care Centers
12.
BMC Med ; 18(1): 265, 2020 08 21.
Article in English | MEDLINE | ID: covidwho-725429

ABSTRACT

BACKGROUND: New emerging infections have no known treatment. Assessing potential drugs for safety and efficacy enables clinicians to make evidence-based treatment decisions and contributes to overall outbreak control. However, it is difficult to launch clinical trials in the unpredictable environment of an outbreak. We conducted a bibliometric systematic review for the 2009 influenza pandemic to determine the speed and quality of evidence generation for treatments. This informs approaches to high-quality evidence generation in this and future pandemics. METHODS: We searched PubMed for all clinical data (including clinical trial, observational and case series) describing treatment for patients with influenza A(H1N1)pdm09 and ClinicalTrials.gov for research that aimed to enrol patients with the disease. RESULTS: Thirty-three thousand eight hundred sixty-nine treatment courses for patients hospitalised with A(H1N1)pdm09 were detailed in 160 publications. Most were retrospective observational studies or case series. Five hundred ninety-two patients received treatment (or placebo) as participants in a registered interventional clinical trial with results publicly available. None of these registered trial results was available during the timeframe of the pandemic, and the median date of publication was 213 days after the Public Health Emergency of International Concern ended. CONCLUSION: Patients were frequently treated for pandemic influenza with drugs not registered for this indication, but rarely under circumstances of high-quality data capture. The result was a reliance on use under compassionate circumstances, resulting in continued uncertainty regarding the potential benefits and harms of anti-viral treatment. Rapid scaling of clinical trials is critical for generating a quality evidence base during pandemics.


Subject(s)
Antiviral Agents/therapeutic use , Compassionate Use Trials , Inappropriate Prescribing/prevention & control , Influenza A Virus, H1N1 Subtype , Influenza, Human/drug therapy , Off-Label Use , Betacoronavirus , Bibliometrics , COVID-19 , Coronavirus Infections/drug therapy , Coronavirus Infections/epidemiology , Cost-Benefit Analysis , Global Health , Humans , Influenza, Human/epidemiology , Pandemics , Pneumonia, Viral/drug therapy , Pneumonia, Viral/epidemiology , Research Design , SARS-CoV-2 , Treatment Outcome
13.
Med J Aust ; 213(3): 126-133, 2020 08.
Article in English | MEDLINE | ID: covidwho-643293

ABSTRACT

INTRODUCTION: The global pandemic of coronavirus disease 2019 (COVID-19) has caused significant worldwide disruption. Although Australia and New Zealand have not been affected as much as some other countries, resuscitation may still pose a risk to health care workers and necessitates a change to our traditional approach. This consensus statement for adult cardiac arrest in the setting of COVID-19 has been produced by the Australasian College for Emergency Medicine (ACEM) and aligns with national and international recommendations. MAIN RECOMMENDATIONS: In a setting of low community transmission, most cardiac arrests are not due to COVID-19. Early defibrillation saves lives and is not considered an aerosol generating procedure. Compression-only cardiopulmonary resuscitation is thought to be a low risk procedure and can be safely initiated with the patient's mouth and nose covered. All other resuscitative procedures are considered aerosol generating and require the use of airborne personal protective equipment (PPE). It is important to balance the appropriateness of resuscitation against the risk of infection. Methods to reduce nosocomial transmission of COVID-19 include a physical barrier such as a towel or mask over the patient's mouth and nose, appropriate use of PPE, minimising the staff involved in resuscitation, and use of mechanical chest compression devices when available. If COVID-19 significantly affects hospital resource availability, the ethics of resource allocation must be considered. CHANGES IN MANAGEMENT: The changes outlined in this document require a significant adaptation for many doctors, nurses and paramedics. It is critically important that all health care workers have regular PPE and advanced life support training, are able to access in situ simulation sessions, and receive extensive debriefing after actual resuscitations. This will ensure safe, timely and effective management of the patients with cardiac arrest in the COVID-19 era.


Subject(s)
Cardiopulmonary Resuscitation/methods , Coronavirus Infections/epidemiology , Emergency Service, Hospital/organization & administration , Heart Arrest/therapy , Pandemics , Pneumonia, Viral/epidemiology , Adult , Algorithms , Australia/epidemiology , Betacoronavirus , COVID-19 , Cardiopulmonary Resuscitation/standards , Coronavirus Infections/transmission , Cross Infection/prevention & control , Humans , Infection Control/methods , Infection Control/standards , Infectious Disease Transmission, Patient-to-Professional/prevention & control , New Zealand/epidemiology , Personal Protective Equipment , Pneumonia, Viral/transmission , SARS-CoV-2
SELECTION OF CITATIONS
SEARCH DETAIL