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1. Social and moral psychology of COVID-19 across 69 countries

Author

Flavio Azevedo, Tomislav Pavlović, Gabriel G. Rêgo, F. Ceren Ay, Biljana Gjoneska, Tom W. Etienne, Robert M. Ross, Philipp Schönegger, Julián C. Riaño-Moreno, Aleksandra Cichocka, Valerio Capraro, Luca Cian, Chiara Longoni, Ho Fai Chan, Jay J. Van Bavel, Hallgeir Sjåstad, John B. Nezlek, Mark Alfano, Michele J. Gelfand, Michèle D. Birtel, Aleksandra Cislak, Patricia L. Lockwood, Koen Abts, Elena Agadullina, John Jamir Benzon Aruta, Sahba Nomvula Besharati, Alexander Bor, Becky L. Choma, Charles David Crabtree, William A. Cunningham, Koustav De, Waqas Ejaz, Christian T. Elbaek, Andrej Findor, Daniel Flichtentrei, Renata Franc, June Gruber, Estrella Gualda, Yusaku Horiuchi, Toan Luu Duc Huynh, Agustin Ibanez, Mostak Ahamed Imran, Jacob Israelashvili, Katarzyna Jasko, Jaroslaw Kantorowicz, Elena Kantorowicz-Reznichenko, André Krouwel, Michael Laakasuo, Claus Lamm, Caroline Leygue, Ming-Jen Lin, Mohammad Sabbir Mansoor, Antoine Marie, Lewend Mayiwar, Honorata Mazepus, Cillian McHugh, John Paul Minda, Panagiotis Mitkidis, Andreas Olsson, Tobias Otterbring, Dominic J. Packer, Anat Perry, Michael Bang Petersen, Arathy Puthillam, Tobias Rothmund, Hernando Santamaría-García, Petra C. Schmid, Drozdstoy Stoyanov, Shruti Tewari, Bojan Todosijević, Manos Tsakiris, Hans H. Tung, Radu G. Umbres, Edmunds Vanags, Madalina Vlasceanu, Andrew Vonasch, Meltem Yucel, Yucheng Zhang, Mohcine Abad, Eli Adler, Narin Akrawi, Hamza Alaoui Mdarhri, Hanane Amara, David M. Amodio, Benedict G. Antazo, Matthew Apps, Mouhamadou Hady Ba, Sergio Barbosa, Brock Bastian, Anton Berg, Maria P. Bernal-Zárate, Michael Bernstein, Michał Białek, Ennio Bilancini, Natalia Bogatyreva, Leonardo Boncinelli, Jonathan E. Booth, Sylvie Borau, Ondrej Buchel, C. Daryl Cameron, Chrissie F. Carvalho, Tatiana Celadin, Chiara Cerami, Hom Nath Chalise, Xiaojun Cheng, Kate Cockcroft, Jane Conway, Mateo Andres Córdoba-Delgado, Chiara Crespi, Marie Crouzevialle, Jo Cutler, Marzena Cypryańska, Justyna Dabrowska, Michael A. Daniels, Victoria H. Davis, Pamala N. Dayley, Sylvain Delouvée, Ognjan Denkovski, Guillaume Dezecache, Nathan A. Dhaliwal, Alelie B. Diato, Roberto Di Paolo, Marianna Drosinou, Uwe Dulleck, Jānis Ekmanis, Arhan S. Ertan, Hapsa Hossain Farhana, Fahima Farkhari, Harry Farmer, Ali Fenwick, Kristijan Fidanovski, Terry Flew, Shona Fraser, Raymond Boadi Frempong, Jonathan A. Fugelsang, Jessica Gale, E. Begoña Garcia-Navarro, Prasad Garladinne, Oussama Ghajjou, Theofilos Gkinopoulos, Kurt Gray, Siobhán M. Griffin, Bjarki Gronfeldt, Mert Gümren, Ranju Lama Gurung, Eran Halperin, Elizabeth Harris, Volo Herzon, Matej Hruška, Guanxiong Huang, Matthias F. C. Hudecek, Ozan Isler, Simon Jangard, Frederik J. Jorgensen, Frank Kachanoff, John Kahn, Apsara Katuwal Dangol, Oleksandra Keudel, Lina Koppel, Mika Koverola, Emily Kubin, Anton Kunnari, Yordan Kutiyski, Oscar Moreda Laguna, Josh Leota, Eva Lermer, Jonathan Levy, Neil Levy, Chunyun Li, Elizabeth U. Long, Marina Maglić, Darragh McCashin, Alexander L. Metcalf, Igor Mikloušić, Soulaimane El Mimouni, Asako Miura, Juliana Molina-Paredes, César Monroy-Fonseca, Elena Morales-Marente, David Moreau, Rafał Muda, Annalisa Myer, Kyle Nash, Tarik Nesh-Nash, Jonas P. Nitschke, Matthew S. Nurse, Yohsuke Ohtsubo, Victoria Oldemburgo de Mello, Cathal O’Madagain, Michal Onderco, M. Soledad Palacios-Galvez, Jussi Palomöki, Yafeng Pan, Zsófia Papp, Philip Pärnamets, Mariola Paruzel-Czachura, Zoran Pavlović, César Payán-Gómez, Silva Perander, Michael Mark Pitman, Rajib Prasad, Joanna Pyrkosz-Pacyna, Steve Rathje, Ali Raza, Kasey Rhee, Claire E. Robertson, Iván Rodríguez-Pascual, Teemu Saikkonen, Octavio Salvador-Ginez, Gaia C. Santi, Natalia Santiago-Tovar, David Savage, Julian A. Scheffer, David T. Schultner, Enid M. Schutte, Andy Scott, Madhavi Sharma, Pujan Sharma, Ahmed Skali, David Stadelmann, Clara Alexandra Stafford, Dragan Stanojević, Anna Stefaniak, Anni Sternisko, Augustin Stoica, Kristina K. Stoyanova, Brent Strickland, Jukka Sundvall, Jeffrey P. Thomas, Gustav Tinghög, Benno Torgler, Iris J. Traast, Raffaele Tucciarelli, Michael Tyrala, Nick D. Ungson, Mete S. Uysal, Paul A. M. Van Lange, Jan-Willem van Prooijen, Dirk van Rooy, Daniel Västfjäll, Peter Verkoeijen, Joana B. Vieira, Christian von Sikorski, Alexander Cameron Walker, Jennifer Watermeyer, Erik Wetter, Ashley Whillans, Katherine White, Rishad Habib, Robin Willardt, Michael J. A. Wohl, Adrian Dominik Wójcik, Kaidi Wu, Yuki Yamada, Onurcan Yilmaz, Kumar Yogeeswaran, Carolin-Theresa Ziemer, Rolf A. Zwaan, Paulo S. Boggio, and Waldir M. Sampaio

Subjects
Science
Abstract

Abstract The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through persuasive messaging and collective behaviour change. To help scholars better understand the social and moral psychology behind public health behaviour, we present a dataset comprising of 51,404 individuals from 69 countries. This dataset was collected for the International Collaboration on Social & Moral Psychology of COVID-19 project (ICSMP COVID-19). This social science survey invited participants around the world to complete a series of moral and psychological measures and public health attitudes about COVID-19 during an early phase of the COVID-19 pandemic (between April and June 2020). The survey included seven broad categories of questions: COVID-19 beliefs and compliance behaviours; identity and social attitudes; ideology; health and well-being; moral beliefs and motivation; personality traits; and demographic variables. We report both raw and cleaned data, along with all survey materials, data visualisations, and psychometric evaluations of key variables.

Published
2023
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2. National identity predicts public health support during a global pandemic

Author

Jay J. Van Bavel, Aleksandra Cichocka, Valerio Capraro, Hallgeir Sjåstad, John B. Nezlek, Tomislav Pavlović, Mark Alfano, Michele J. Gelfand, Flavio Azevedo, Michèle D. Birtel, Aleksandra Cislak, Patricia L. Lockwood, Robert Malcolm Ross, Koen Abts, Elena Agadullina, John Jamir Benzon Aruta, Sahba Nomvula Besharati, Alexander Bor, Becky L. Choma, Charles David Crabtree, William A. Cunningham, Koustav De, Waqas Ejaz, Christian T. Elbaek, Andrej Findor, Daniel Flichtentrei, Renata Franc, Biljana Gjoneska, June Gruber, Estrella Gualda, Yusaku Horiuchi, Toan Luu Duc Huynh, Augustin Ibanez, Mostak Ahamed Imran, Jacob Israelashvili, Katarzyna Jasko, Jaroslaw Kantorowicz, Elena Kantorowicz-Reznichenko, André Krouwel, Michael Laakasuo, Claus Lamm, Caroline Leygue, Ming-Jen Lin, Mohammad Sabbir Mansoor, Antoine Marie, Lewend Mayiwar, Honorata Mazepus, Cillian McHugh, John Paul Minda, Panagiotis Mitkidis, Andreas Olsson, Tobias Otterbring, Dominic J. Packer, Anat Perry, Michael Bang Petersen, Arathy Puthillam, Julián C. Riaño-Moreno, Tobias Rothmund, Hernando Santamaría-García, Petra C. Schmid, Drozdstoy Stoyanov, Shruti Tewari, Bojan Todosijević, Manos Tsakiris, Hans H. Tung, Radu G. Umbreș, Edmunds Vanags, Madalina Vlasceanu, Andrew Vonasch, Meltem Yucel, Yucheng Zhang, Mohcine Abad, Eli Adler, Narin Akrawi, Hamza Alaoui Mdarhri, Hanane Amara, David M. Amodio, Benedict G. Antazo, Matthew Apps, F. Ceren Ay, Mouhamadou Hady Ba, Sergio Barbosa, Brock Bastian, Anton Berg, Maria P. Bernal-Zárate, Michael Bernstein, Michał Białek, Ennio Bilancini, Natalia Bogatyreva, Leonardo Boncinelli, Jonathan E. Booth, Sylvie Borau, Ondrej Buchel, C. Daryl Cameron, Chrissie F. Carvalho, Tatiana Celadin, Chiara Cerami, Hom Nath Chalise, Xiaojun Cheng, Luca Cian, Kate Cockcroft, Jane Conway, Mateo Andres Córdoba-Delgado, Chiara Crespi, Marie Crouzevialle, Jo Cutler, Marzena Cypryańska, Justyna Dabrowska, Michael A. Daniels, Victoria H. Davis, Pamala N. Dayley, Sylvain Delouvee, Ognjan Denkovski, Guillaume Dezecache, Nathan A. Dhaliwal, Alelie B. Diato, Roberto Di Paolo, Marianna Drosinou, Uwe Dulleck, Jānis Ekmanis, Arhan S. Ertan, Tom W. Etienne, Hapsa Hossain Farhana, Fahima Farkhari, Harry Farmer, Ali Fenwick, Kristijan Fidanovski, Terry Flew, Shona Fraser, Raymond Boadi Frempong, Jonathan A. Fugelsang, Jessica Gale, E. Begoña Garcia-Navarro, Prasad Garladinne, Oussama Ghajjou, Theofilos Gkinopoulos, Kurt Gray, Siobhán M. Griffin, Bjarki Gronfeldt, Mert Gümren, Ranju Lama Gurung, Eran Halperin, Elizabeth Harris, Volo Herzon, Matej Hruška, Guanxiong Huang, Matthias F. C. Hudecek, Ozan Isler, Simon Jangard, Frederik J. Jørgensen, Frank Kachanoff, John Kahn, Apsara Katuwal Dangol, Oleksandra Keudel, Lina Koppel, Mika Koverola, Emily Kubin, Anton Kunnari, Yordan Kutiyski, Oscar Laguna, Josh Leota, Eva Lermer, Jonathan Levy, Neil Levy, Chunyun Li, Elizabeth U. Long, Chiara Longoni, Marina Maglić, Darragh McCashin, Alexander L. Metcalf, Igor Mikloušić, Soulaimane El Mimouni, Asako Miura, Juliana Molina-Paredes, César Monroy-Fonseca, Elena Morales-Marente, David Moreau, Rafał Muda, Annalisa Myer, Kyle Nash, Tarik Nesh-Nash, Jonas P. Nitschke, Matthew S. Nurse, Yohsuke Ohtsubo, Victoria Oldemburgo de Mello, Cathal O’Madagain, Michal Onderco, M. Soledad Palacios-Galvez, Jussi Palomäki, Yafeng Pan, Zsófia Papp, Philip Pärnamets, Mariola Paruzel-Czachura, Zoran Pavlović, César Payán-Gómez, Silva Perander, Michael Mark Pitman, Rajib Prasad, Joanna Pyrkosz-Pacyna, Steve Rathje, Ali Raza, Gabriel G. Rêgo, Kasey Rhee, Claire E. Robertson, Iván Rodríguez-Pascual, Teemu Saikkonen, Octavio Salvador-Ginez, Waldir M. Sampaio, Gaia C. Santi, Natalia Santiago-Tovar, David Savage, Julian A. Scheffer, Philipp Schönegger, David T. Schultner, Enid M. Schutte, Andy Scott, Madhavi Sharma, Pujan Sharma, Ahmed Skali, David Stadelmann, Clara Alexandra Stafford, Dragan Stanojević, Anna Stefaniak, Anni Sternisko, Augustin Stoica, Kristina K. Stoyanova, Brent Strickland, Jukka Sundvall, Jeffrey P. Thomas, Gustav Tinghög, Benno Torgler, Iris J. Traast, Raffaele Tucciarelli, Michael Tyrala, Nick D. Ungson, Mete S. Uysal, Paul A. M. Van Lange, Jan-Willem van Prooijen, Dirk van Rooy, Daniel Västfjäll, Peter Verkoeijen, Joana B. Vieira, Christian von Sikorski, Alexander Cameron Walker, Jennifer Watermeyer, Erik Wetter, Ashley Whillans, Robin Willardt, Michael J. A. Wohl, Adrian Dominik Wójcik, Kaidi Wu, Yuki Yamada, Onurcan Yilmaz, Kumar Yogeeswaran, Carolin-Theresa Ziemer, Rolf A. Zwaan, and Paulo S. Boggio

Subjects
Science
Abstract

Understanding collective behaviour is an important aspect of managing the pandemic response. Here the authors show in a large global study that participants that reported identifying more strongly with their nation reported greater engagement in public health behaviours and support for public health policies in the context of the pandemic.

Published
2022
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3. Author Correction: National identity predicts public health support during a global pandemic

Author

Jay J. Van Bavel, Aleksandra Cichocka, Valerio Capraro, Hallgeir Sjåstad, John B. Nezlek, Tomislav Pavlović, Mark Alfano, Michele J. Gelfand, Flavio Azevedo, Michèle D. Birtel, Aleksandra Cislak, Patricia L. Lockwood, Robert Malcolm Ross, Koen Abts, Elena Agadullina, John Jamir Benzon Aruta, Sahba Nomvula Besharati, Alexander Bor, Becky L. Choma, Charles David Crabtree, William A. Cunningham, Koustav De, Waqas Ejaz, Christian T. Elbaek, Andrej Findor, Daniel Flichtentrei, Renata Franc, Biljana Gjoneska, June Gruber, Estrella Gualda, Yusaku Horiuchi, Toan Luu Duc Huynh, Agustin Ibanez, Mostak Ahamed Imran, Jacob Israelashvili, Katarzyna Jasko, Jaroslaw Kantorowicz, Elena Kantorowicz-Reznichenko, André Krouwel, Michael Laakasuo, Claus Lamm, Caroline Leygue, Ming-Jen Lin, Mohammad Sabbir Mansoor, Antoine Marie, Lewend Mayiwar, Honorata Mazepus, Cillian McHugh, John Paul Minda, Panagiotis Mitkidis, Andreas Olsson, Tobias Otterbring, Dominic J. Packer, Anat Perry, Michael Bang Petersen, Arathy Puthillam, Julián C. Riaño-Moreno, Tobias Rothmund, Hernando Santamaría-García, Petra C. Schmid, Drozdstoy Stoyanov, Shruti Tewari, Bojan Todosijević, Manos Tsakiris, Hans H. Tung, Radu G. Umbreș, Edmunds Vanags, Madalina Vlasceanu, Andrew Vonasch, Meltem Yucel, Yucheng Zhang, Mohcine Abad, Eli Adler, Narin Akrawi, Hamza Alaoui Mdarhri, Hanane Amara, David M. Amodio, Benedict G. Antazo, Matthew Apps, F. Ceren Ay, Mouhamadou Hady Ba, Sergio Barbosa, Brock Bastian, Anton Berg, Maria P. Bernal-Zárate, Michael Bernstein, Michał Białek, Ennio Bilancini, Natalia Bogatyreva, Leonardo Boncinelli, Jonathan E. Booth, Sylvie Borau, Ondrej Buchel, C. Daryl Cameron, Chrissie F. Carvalho, Tatiana Celadin, Chiara Cerami, Hom Nath Chalise, Xiaojun Cheng, Luca Cian, Kate Cockcroft, Jane Conway, Mateo Andres Córdoba-Delgado, Chiara Crespi, Marie Crouzevialle, Jo Cutler, Marzena Cypryańska, Justyna Dabrowska, Michael A. Daniels, Victoria H. Davis, Pamala N. Dayley, Sylvain Delouvee, Ognjan Denkovski, Guillaume Dezecache, Nathan A. Dhaliwal, Alelie B. Diato, Roberto Di Paolo, Marianna Drosinou, Uwe Dulleck, Jānis Ekmanis, Arhan S. Ertan, Tom W. Etienne, Hapsa Hossain Farhana, Fahima Farkhari, Harry Farmer, Ali Fenwick, Kristijan Fidanovski, Terry Flew, Shona Fraser, Raymond Boadi Frempong, Jonathan A. Fugelsang, Jessica Gale, E. Begoña Garcia-Navarro, Prasad Garladinne, Oussama Ghajjou, Theofilos Gkinopoulos, Kurt Gray, Siobhán M. Griffin, Bjarki Gronfeldt, Mert Gümren, Ranju Lama Gurung, Eran Halperin, Elizabeth Harris, Volo Herzon, Matej Hruška, Guanxiong Huang, Matthias F. C. Hudecek, Ozan Isler, Simon Jangard, Frederik J. Jørgensen, Frank Kachanoff, John Kahn, Apsara Katuwal Dangol, Oleksandra Keudel, Lina Koppel, Mika Koverola, Emily Kubin, Anton Kunnari, Yordan Kutiyski, Oscar Laguna, Josh Leota, Eva Lermer, Jonathan Levy, Neil Levy, Chunyun Li, Elizabeth U. Long, Chiara Longoni, Marina Maglić, Darragh McCashin, Alexander L. Metcalf, Igor Mikloušić, Soulaimane El Mimouni, Asako Miura, Juliana Molina-Paredes, César Monroy-Fonseca, Elena Morales-Marente, David Moreau, Rafał Muda, Annalisa Myer, Kyle Nash, Tarik Nesh-Nash, Jonas P. Nitschke, Matthew S. Nurse, Yohsuke Ohtsubo, Victoria Oldemburgo de Mello, Cathal O’Madagain, Michal Onderco, M. Soledad Palacios-Galvez, Jussi Palomäki, Yafeng Pan, Zsófia Papp, Philip Pärnamets, Mariola Paruzel-Czachura, Zoran Pavlović, César Payán-Gómez, Silva Perander, Michael Mark Pitman, Rajib Prasad, Joanna Pyrkosz-Pacyna, Steve Rathje, Ali Raza, Gabriel G. Rêgo, Kasey Rhee, Claire E. Robertson, Iván Rodríguez-Pascual, Teemu Saikkonen, Octavio Salvador-Ginez, Waldir M. Sampaio, Gaia C. Santi, Natalia Santiago-Tovar, David Savage, Julian A. Scheffer, Philipp Schönegger, David T. Schultner, Enid M. Schutte, Andy Scott, Madhavi Sharma, Pujan Sharma, Ahmed Skali, David Stadelmann, Clara Alexandra Stafford, Dragan Stanojević, Anna Stefaniak, Anni Sternisko, Augustin Stoica, Kristina K. Stoyanova, Brent Strickland, Jukka Sundvall, Jeffrey P. Thomas, Gustav Tinghög, Benno Torgler, Iris J. Traast, Raffaele Tucciarelli, Michael Tyrala, Nick D. Ungson, Mete S. Uysal, Paul A. M. Van Lange, Jan-Willem van Prooijen, Dirk van Rooy, Daniel Västfjäll, Peter Verkoeijen, Joana B. Vieira, Christian von Sikorski, Alexander Cameron Walker, Jennifer Watermeyer, Erik Wetter, Ashley Whillans, Robin Willardt, Michael J. A. Wohl, Adrian Dominik Wójcik, Kaidi Wu, Yuki Yamada, Onurcan Yilmaz, Kumar Yogeeswaran, Carolin-Theresa Ziemer, Rolf A. Zwaan, and Paulo S. Boggio

Subjects
Science
Published
2022
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4. Mathematical models for predicting human mobility in the context of infectious disease spread: introducing the impedance model

Author

Kankoé Sallah, Roch Giorgi, Linus Bengtsson, Xin Lu, Erik Wetter, Paul Adrien, Stanislas Rebaudet, Renaud Piarroux, and Jean Gaudart

Subjects
Human mobility, Disease spread, Impedance model, Spatial statistics, Epidemiology, Radiation model, Computer applications to medicine. Medical informatics, R858-859.7
Abstract

Abstract Background Mathematical models of human mobility have demonstrated a great potential for infectious disease epidemiology in contexts of data scarcity. While the commonly used gravity model involves parameter tuning and is thus difficult to implement without reference data, the more recent radiation model based on population densities is parameter-free, but biased. In this study we introduce the new impedance model, by analogy with electricity. Previous research has compared models on the basis of a few specific available spatial patterns. In this study, we use a systematic simulation-based approach to assess the performances. Methods Five hundred spatial patterns were generated using various area sizes and location coordinates. Model performances were evaluated based on these patterns. For simulated data, comparison measures were average root mean square error (aRMSE) and bias criteria. Modeling of the 2010 Haiti cholera epidemic with a basic susceptible–infected–recovered (SIR) framework allowed an empirical evaluation through assessing the goodness-of-fit of the observed epidemic curve. Results The new, parameter-free impedance model outperformed previous models on simulated data according to average aRMSE and bias criteria. The impedance model achieved better performances with heterogeneous population densities and small destination populations. As a proof of concept, the basic compartmental SIR framework was used to confirm the results obtained with the impedance model in predicting the spread of cholera in Haiti in 2010. Conclusions The proposed new impedance model provides accurate estimations of human mobility, especially when the population distribution is highly heterogeneous. This model can therefore help to achieve more accurate predictions of disease spread in the context of an epidemic.

Published
2017
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6. Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

Author

Tomislav Pavlović, Flavio Azevedo, Koustav De, Julián C Riaño-Moreno, Marina Maglić, Theofilos Gkinopoulos, Patricio Andreas Donnelly-Kehoe, César Payán-Gómez, Guanxiong Huang, Jaroslaw Kantorowicz, Michèle D Birtel, Philipp Schönegger, Valerio Capraro, Hernando Santamaría-García, Meltem Yucel, Agustin Ibanez, Steve Rathje, Erik Wetter, Dragan Stanojević, Jan-Willem van Prooijen, Eugenia Hesse, Christian T Elbaek, Renata Franc, Zoran Pavlović, Panagiotis Mitkidis, Aleksandra Cichocka, Michele Gelfand, Mark Alfano, Robert M Ross, Hallgeir Sjåstad, John B Nezlek, Aleksandra Cislak, Patricia Lockwood, Koen Abts, Elena Agadullina, David M Amodio, Matthew A J Apps, John Jamir Benzon Aruta, Sahba Besharati, Alexander Bor, Becky Choma, William Cunningham, Waqas Ejaz, Harry Farmer, Andrej Findor, Biljana Gjoneska, Estrella Gualda, Toan L D Huynh, Mostak Ahamed Imran, Jacob Israelashvili, Elena Kantorowicz-Reznichenko, André Krouwel, Yordan Kutiyski, Michael Laakasuo, Claus Lamm, Jonathan Levy, Caroline Leygue, Ming-Jen Lin, Mohammad Sabbir Mansoor, Antoine Marie, Lewend Mayiwar, Honorata Mazepus, Cillian McHugh, Andreas Olsson, Tobias Otterbring, Dominic Packer, Jussi Palomäki, Anat Perry, Michael Bang Petersen, Arathy Puthillam, Tobias Rothmund, Petra C Schmid, David Stadelmann, Augustin Stoica, Drozdstoy Stoyanov, Kristina Stoyanova, Shruti Tewari, Bojan Todosijević, Benno Torgler, Manos Tsakiris, Hans H Tung, Radu Gabriel Umbreș, Edmunds Vanags, Madalina Vlasceanu, Andrew J Vonasch, Yucheng Zhang, Mohcine Abad, Eli Adler, Hamza Alaoui Mdarhri, Benedict Antazo, F Ceren Ay, Mouhamadou El Hady Ba, Sergio Barbosa, Brock Bastian, Anton Berg, Michał Białek, Ennio Bilancini, Natalia Bogatyreva, Leonardo Boncinelli, Jonathan E Booth, Sylvie Borau, Ondrej Buchel, Chrissie Ferreira de Carvalho, Tatiana Celadin, Chiara Cerami, Hom Nath Chalise, Xiaojun Cheng, Luca Cian, Kate Cockcroft, Jane Conway, Mateo A Córdoba-Delgado, Chiara Crespi, Marie Crouzevialle, Jo Cutler, Marzena Cypryańska, Justyna Dabrowska, Victoria H Davis, John Paul Minda, Pamala N Dayley, Sylvain Delouvée, Ognjan Denkovski, Guillaume Dezecache, Nathan A Dhaliwal, Alelie Diato, Roberto Di Paolo, Uwe Dulleck, Jānis Ekmanis, Tom W Etienne, Hapsa Hossain Farhana, Fahima Farkhari, Kristijan Fidanovski, Terry Flew, Shona Fraser, Raymond Boadi Frempong, Jonathan Fugelsang, Jessica Gale, E Begoña García-Navarro, Prasad Garladinne, Kurt Gray, Siobhán M Griffin, Bjarki Gronfeldt, June Gruber, Eran Halperin, Volo Herzon, Matej Hruška, Matthias F C Hudecek, Ozan Isler, Simon Jangard, Frederik Jørgensen, Oleksandra Keudel, Lina Koppel, Mika Koverola, Anton Kunnari, Josh Leota, Eva Lermer, Chunyun Li, Chiara Longoni, Darragh McCashin, Igor Mikloušić, Juliana Molina-Paredes, César Monroy-Fonseca, Elena Morales-Marente, David Moreau, Rafał Muda, Annalisa Myer, Kyle Nash, Jonas P Nitschke, Matthew S Nurse, Victoria Oldemburgo de Mello, M Soledad Palacios-Galvez, Yafeng Pan, Zsófia Papp, Philip Pärnamets, Mariola Paruzel-Czachura, Silva Perander, Michael Pitman, Ali Raza, Gabriel Gaudencio Rêgo, Claire Robertson, Iván Rodríguez-Pascual, Teemu Saikkonen, Octavio Salvador-Ginez, Waldir M Sampaio, Gaia Chiara Santi, David Schultner, Enid Schutte, Andy Scott, Ahmed Skali, Anna Stefaniak, Anni Sternisko, Brent Strickland, Jeffrey P Thomas, Gustav Tinghög, Iris J Traast, Raffaele Tucciarelli, Michael Tyrala, Nick D Ungson, Mete Sefa Uysal, Dirk Van Rooy, Daniel Västfjäll, Joana B Vieira, Christian von Sikorski, Alexander C Walker, Jennifer Watermeyer, Robin Willardt, Michael J A Wohl, Adrian Dominik Wójcik, Kaidi Wu, Yuki Yamada, Onurcan Yilmaz, Kumar Yogeeswaran, Carolin-Theresa Ziemer, Rolf A Zwaan, Paulo Sergio Boggio, Ashley Whillans, Paul A M Van Lange, Rajib Prasad, Michal Onderco, Cathal O'Madagain, Tarik Nesh-Nash, Oscar Moreda Laguna, Emily Kubin, Mert Gümren, Ali Fenwick, Arhan S Ertan, Michael J Bernstein, Hanane Amara, Jay Joseph Van Bavel, Brain and Cognition, Public Administration, Pavlovic, Tomislav, Avezedo, Flávio, De, Koustav, Maglić, Marina, Donnelly-Kehoe, Patricio Andreas, Payán-Gómez, César, Van Bavel, Jay J., Schmid, Petra Claudia, Crouzevialle, Marie, Willardt, Robin, et al., Ivo Pilar Institute of Social Sciences, University of Cambridge [UK] (CAM), University of Kentucky (UK), Universidad El Bosque [Bogota], University of Crete [Heraklion] (UOC), Universidad del Rosario [Bogota], Universidad Nacional de Colombia [Bogotà] (UNAL), City University of Hong Kong [Hong Kong] (CUHK), Universiteit Leiden, University of Greenwich, University of St Andrews [Scotland], Middlesex University [London], Pontifical Xavierian University, Duke University [Durham], Universidad Adolfo Ibáñez [Santiago], University of California (UC), Trinity College Dublin, Stockholm School of Economics (SSE), University of Belgrade [Belgrade], Vrije Universiteit Amsterdam [Amsterdam] (VU), Universidad Mayor de San Andrés (UMSA), Aarhus University [Aarhus], University of Kent [Canterbury], Stanford University, Macquarie University, Norwegian School of Economics and Business Administration, SWPS University of Social Sciences and Humanities (SWPS), University of Birmingham [Birmingham], University of Oxford, Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Vysšaja škola èkonomiki = National Research University Higher School of Economics [Moscow] (HSE), University of Amsterdam [Amsterdam] (UvA), Sunway University [Malaysia], University of the Witwatersrand [Johannesburg] (WITS), University of Toronto, National University of Sciences and Technology [Islamabad] (NUST), Comenius University in Bratislava, Macedonian Academy of Sciences and Arts [Skopje, North Macedonia] (MASA), Universidad de Huelva, University of Southampton, BRAC University, The Hebrew University of Jerusalem (HUJ), Erasmus University Rotterdam, Kieskompas, Helsingin yliopisto = Helsingfors universitet = University of Helsinki, University of Vienna [Vienna], Reichman University [Herzliya], Aalto University, Universidad Nacional Autónoma de México = National Autonomous University of Mexico (UNAM), National Taiwan University [Taiwan] (NTU), HEMS School, BI Norwegian Business School [Oslo], University of Limerick (UL), Karolinska Institutet [Stockholm], University of Agder (UIA), Lehigh University [Bethlehem], Monk Prayogshala, Friedrich-Schiller-Universität = Friedrich Schiller University Jena [Jena, Germany], Eidgenössische Technische Hochschule Zürich - Swiss Federal Institute of Technology in Zürich (ETH Zurïch), University of Bayreuth, National School of Political and Administrative Studies (SNSPA), Plovdiv University 'Paisii Hilendarski', Indian Institute of Management Indore (IMM Indore), Institute of Social Sciences Belgrade, Queensland University of Technology [Brisbane] (QUT), Royal Holloway [University of London] (RHUL), University of London [London], National University of Political Studies and Public Administration, University of Latvia (LU), New York University [New York] (NYU), NYU System (NYU), University of Canterbury [Christchurch], Hebei University of Technology [Tianjin], Université Mohammed VI Polytechnique [Ben Guerir] (UM6P), AnsuR Technologies [Fornebu], Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD), Victoria University [Melbourne], University of Wrocław [Poland] (UWr), IMT Institute for Advanced Studies [Lucca], Université de Florence, Università degli Studi di Firenze = University of Florence (UniFI), London School of Economics and Political Science (LSE), TBS Education, Slovak Academy of Science [Bratislava] (SAS), Santa Catarina State University (UDESC), University of Bologna/Università di Bologna, Tribhuvan University, Shenzhen Univerisity [Shenzhen], University of Virginia, Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), University of Western Ontario (UWO), Université de Rennes 2 (UR2), Laboratoire de Psychologie Sociale et Cognitive (LAPSCO), Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), University of British Columbia (UBC), University of Queensland [Brisbane], Pennsylvania State University (Penn State), Penn State System, Westfälische Wilhelms-Universität Münster = University of Münster (WWU), The University of Sydney, University of Waterloo [Waterloo], University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), University of Colorado [Boulder], University of Regensburg, Kyiv School of economic (KSE), Linköping University (LIU), Monash University [Clayton], Ansbach University of Applied Sciences, Ludwig Maximilian University [Munich] (LMU), Department of Management - London School of Economics and Political Science (LSE), Questrom School of Business, Boston University [Boston] (BU), Dublin City University [Dublin] (DCU), University of Auckland [Auckland], Maria Curie-Sklodowska University (UMCS), City University of New York [New York] (CUNY), University of Alberta, Australian National University (ANU), University of Silesia in Katowice, Universidad Complutense de Madrid = Complutense University of Madrid [Madrid] (UCM), Zhejiang University, Mackenzie Presbyterian University [São Paulo] (UPM), NYU Department of Psychology [New-York University], NYU System (NYU)-NYU System (NYU), University of Turku, City College of New York [CUNY] (CCNY), University of Groningen [Groningen], Carleton University, Département d'Etudes Cognitives - ENS Paris (DEC), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Faculté de Gouvernance, Sciences Économiques et Sociales [UM6P] (FGSES), University College of London [London] (UCL), Susquehanna University, University of Antwerp (UA), University of Exeter, University of Koblenz-Landau, Nicolaus Copernicus University [Toruń], University of California [San Diego] (UC San Diego), Kyushu University, Kadir Has University (KHAS), Harvard Business School, Harvard University, Vidyasagar College For Women, Koç University, Hult International Business School, Boǧaziçi üniversitesi = Boğaziçi University [Istanbul], Penn State Abington, Pennsylvania Commonwealth System of Higher Education (PCSHE)-Penn State System, Communication Science, Network Institute, Communication Choices, Content and Consequences (CCCC), Social Psychology, IBBA, A-LAB, University of St Andrews. Philosophy, University of St Andrews. School of Psychology and Neuroscience, Pavlović, Tomislav [0000-0002-4470-3715], Azevedo, Flavio [0000-0001-9000-8513], De, Koustav [0000-0001-9562-0672], Riaño-Moreno, Julián C [0000-0003-4182-0550], Maglić, Marina [0000-0002-6851-4601], Gkinopoulos, Theofilos [0000-0003-1070-6245], Donnelly-Kehoe, Patricio Andreas [0000-0002-3738-9537], Payán-Gómez, César [0000-0002-0633-1332], Huang, Guanxiong [0000-0002-8588-1454], Kantorowicz, Jaroslaw [0000-0002-1186-5427], Birtel, Michèle D [0000-0002-2383-9197], Schönegger, Philipp [0000-0001-9930-487X], Capraro, Valerio [0000-0002-0579-0166], Santamaría-García, Hernando [0000-0001-9422-3579], Yucel, Meltem [0000-0002-7274-5971], Ibanez, Agustin [0000-0001-6758-5101], Rathje, Steve [0000-0001-6727-571X], Wetter, Erik [0000-0002-5821-6651], Stanojević, Dragan [0000-0002-3667-2461], van Prooijen, Jan-Willem [0000-0001-6236-0819], Hesse, Eugenia [0000-0002-9077-9833], Elbaek, Christian T [0000-0002-7039-4565], Franc, Renata [0000-0002-1909-2393], Pavlović, Zoran [0000-0002-9231-5100], Mitkidis, Panagiotis [0000-0002-9495-7369], Cichocka, Aleksandra [0000-0003-1703-1586], Alfano, Mark [0000-0001-5879-8033], Ross, Robert M [0000-0001-8711-1675], Sjåstad, Hallgeir [0000-0002-8730-1038], Nezlek, John B [0000-0003-4963-3637], Cislak, Aleksandra [0000-0002-9880-6947], Lockwood, Patricia [0000-0001-7195-9559], Abts, Koen [0000-0001-8546-8347], Agadullina, Elena [0000-0002-1505-1412], Amodio, David M [0000-0001-7746-0150], Apps, Matthew AJ [0000-0001-5793-2202], Aruta, John Jamir Benzon [0000-0003-4155-1063], Besharati, Sahba [0000-0003-2836-7982], Bor, Alexander [0000-0002-2624-9221], Choma, Becky [0000-0002-8286-8983], Ejaz, Waqas [0000-0002-2492-4115], Farmer, Harry [0000-0002-3684-0605], Findor, Andrej [0000-0002-5896-6989], Gjoneska, Biljana [0000-0003-1200-6672], Gualda, Estrella [0000-0003-0220-2135], Huynh, Toan LD [0000-0002-6653-7447], Imran, Mostak Ahamed [0000-0002-5101-3149], Israelashvili, Jacob [0000-0003-1289-223X], Kantorowicz-Reznichenko, Elena [0000-0001-8128-7290], Krouwel, André [0000-0003-0952-6028], Kutiyski, Yordan [0000-0003-0889-4232], Laakasuo, Michael [0000-0003-2826-6073], Lamm, Claus [0000-0002-5422-0653], Levy, Jonathan [0000-0003-1007-2393], Leygue, Caroline [0000-0002-0355-1030], Lin, Ming-Jen [0000-0002-7174-2226], Mansoor, Mohammad Sabbir [0000-0002-6541-3506], Marie, Antoine [0000-0002-7958-0153], Mayiwar, Lewend [0000-0003-1404-4779], Mazepus, Honorata [0000-0002-5005-9399], McHugh, Cillian [0000-0002-9701-3232], Olsson, Andreas [0000-0001-5272-7744], Otterbring, Tobias [0000-0002-0283-8777], Packer, Dominic [0000-0001-8420-6548], Palomäki, Jussi [0000-0001-6063-0926], Perry, Anat [0000-0003-2329-856X], Petersen, Michael Bang [0000-0002-6782-5635], Puthillam, Arathy [0000-0003-2426-8362], Rothmund, Tobias [0000-0003-2979-5129], Schmid, Petra C [0000-0002-9990-5445], Stadelmann, David [0000-0002-1211-9936], Stoica, Augustin [0000-0003-0585-1114], Stoyanov, Drozdstoy [0000-0002-9975-3680], Stoyanova, Kristina [0000-0001-8362-6444], Tewari, Shruti [0000-0003-1903-7252], Todosijević, Bojan [0000-0002-6116-993X], Torgler, Benno [0000-0002-9809-963X], Tsakiris, Manos [0000-0001-7753-7576], Tung, Hans H [0000-0001-5332-7582], Umbreș, Radu Gabriel [0000-0002-6121-4518], Vanags, Edmunds [0000-0003-1932-936X], Vlasceanu, Madalina [0000-0003-2138-1968], Vonasch, Andrew J [0000-0002-2784-5420], Zhang, Yucheng [0000-0001-9435-6734], Abad, Mohcine [0000-0002-4964-5411], Adler, Eli [0000-0002-9005-5536], Mdarhri, Hamza Alaoui [0000-0001-9831-6561], Antazo, Benedict [0000-0001-9993-8960], Ay, F Ceren [0000-0003-4444-2268], Ba, Mouhamadou El Hady [0000-0002-2707-1242], Barbosa, Sergio [0000-0003-1989-158X], Bastian, Brock [0000-0003-4619-3322], Berg, Anton [0000-0001-7143-762X], Białek, Michał [0000-0002-5062-5733], Bilancini, Ennio [0000-0002-2027-3992], Bogatyreva, Natalia [0000-0002-6024-2322], Boncinelli, Leonardo [0000-0003-0626-5133], Booth, Jonathan E [0000-0002-8563-4613], Borau, Sylvie [0000-0003-1564-0695], Buchel, Ondrej [0000-0002-0139-5513], de Carvalho, Chrissie Ferreira [0000-0002-1369-6188], Celadin, Tatiana [0000-0002-7743-3117], Cerami, Chiara [0000-0003-1974-3421], Chalise, Hom Nath [0000-0002-9301-6890], Cian, Luca [0000-0002-8051-1366], Cockcroft, Kate [0000-0002-6166-8050], Conway, Jane [0000-0003-3883-349X], Córdoba-Delgado, Mateo A [0000-0002-2264-7388], Crespi, Chiara [0000-0002-7851-9887], Crouzevialle, Marie [0000-0002-5538-6030], Cutler, Jo [0000-0003-1073-764X], Cypryańska, Marzena [0000-0001-9234-562X], Dabrowska, Justyna [0000-0002-8821-7161], Davis, Victoria H [0000-0002-7207-4629], Minda, John Paul [0000-0002-4081-010X], Dayley, Pamala N [0000-0001-8955-9502], Delouvée, Sylvain [0000-0002-4029-597X], Denkovski, Ognjan [0000-0002-9739-4100], Dezecache, Guillaume [0000-0002-9366-6287], Dhaliwal, Nathan A [0000-0002-4667-0689], Di Paolo, Roberto [0000-0002-6081-6656], Dulleck, Uwe [0000-0002-0953-5963], Ekmanis, Jānis [0000-0003-1781-1785], Etienne, Tom W [0000-0002-4299-6593], Farkhari, Fahima [0000-0002-8484-5128], Fidanovski, Kristijan [0000-0002-9006-0140], Flew, Terry [0000-0003-4485-9338], Fraser, Shona [0000-0003-1505-0652], Frempong, Raymond Boadi [0000-0002-4603-5570], Fugelsang, Jonathan [0000-0002-6342-7023], Gale, Jessica [0000-0001-5677-8629], García-Navarro, E Begoña [0000-0001-6913-8882], Gray, Kurt [0000-0001-5816-2676], Griffin, Siobhán M [0000-0002-3613-2844], Gronfeldt, Bjarki [0000-0001-9941-7903], Gruber, June [0000-0002-7789-1353], Halperin, Eran [0000-0002-3379-2935], Herzon, Volo [0000-0001-7781-1651], Hruška, Matej [0000-0002-4521-3697], Hudecek, Matthias FC [0000-0002-7696-766X], Isler, Ozan [0000-0002-4638-2230], Jangard, Simon [0000-0002-7876-4161], Jørgensen, Frederik [0000-0002-5461-912X], Keudel, Oleksandra [0000-0001-6322-3103], Koppel, Lina [0000-0002-6302-0047], Koverola, Mika [0000-0001-8227-6120], Kunnari, Anton [0000-0002-2951-6399], Leota, Josh [0000-0002-7714-4630], Lermer, Eva [0000-0002-6600-9580], Li, Chunyun [0000-0001-5909-0889], Longoni, Chiara [0000-0002-4945-4957], McCashin, Darragh [0000-0003-2686-2111], Mikloušić, Igor [0000-0002-6539-2901], Monroy-Fonseca, César [0000-0003-4696-8159], Morales-Marente, Elena [0000-0002-1227-9606], Moreau, David [0000-0002-1957-1941], Muda, Rafał [0000-0003-4953-6642], Myer, Annalisa [0000-0002-2363-4757], Nash, Kyle [0000-0003-0461-3835], Nitschke, Jonas P [0000-0002-3244-8585], Nurse, Matthew S [0000-0003-1787-5914], de Mello, Victoria Oldemburgo [0000-0003-2867-8529], Palacios-Galvez, Maria Soledad [0000-0002-6802-6202], Pan, Yafeng [0000-0002-5633-8313], Papp, Zsófia [0000-0001-6257-0568], Pärnamets, Philip [0000-0001-8360-9097], Paruzel-Czachura, Mariola [0000-0002-8716-9778], Perander, Silva [0000-0001-6711-8079], Pitman, Michael [0000-0001-5532-5388], Raza, Ali [0000-0002-2438-6054], Rêgo, Gabriel Gaudencio [0000-0003-3304-4723], Robertson, Claire [0000-0001-8403-6358], Rodríguez-Pascual, Iván [0000-0002-5385-3643], Saikkonen, Teemu [0000-0001-9619-3270], Salvador-Ginez, Octavio [0000-0002-1652-8788], Sampaio, Waldir M [0000-0002-6066-4314], Santi, Gaia Chiara [0000-0002-9253-6122], Schultner, David [0000-0003-2253-4065], Schutte, Enid [0000-0002-6653-5409], Scott, Andy [0000-0002-3294-0078], Skali, Ahmed [0000-0002-4753-3280], Stefaniak, Anna [0000-0002-1706-7784], Sternisko, Anni [0000-0002-2507-3076], Strickland, Brent [0000-0002-7573-3722], Thomas, Jeffrey P [0000-0002-5939-5559], Tinghög, Gustav [0000-0002-8159-1249], Tucciarelli, Raffaele [0000-0002-0342-308X], Tyrala, Michael [0000-0001-5268-8319], Ungson, Nick D [0000-0003-2494-4498], Uysal, Mete Sefa [0000-0002-8698-9213], Van Rooy, Dirk [0000-0003-2525-5408], Västfjäll, Daniel [0000-0003-2873-4500], Vieira, Joana B [0000-0001-7335-4588], von Sikorski, Christian [0000-0002-3787-8277], Walker, Alexander C [0000-0003-1431-6770], Watermeyer, Jennifer [0000-0001-7918-8832], Willardt, Robin [0000-0002-2495-3450], Wohl, Michael JA [0000-0001-6945-5562], Wójcik, Adrian Dominik [0000-0002-7073-6019], Wu, Kaidi [0000-0001-6881-7437], Yamada, Yuki [0000-0003-1431-568X], Yilmaz, Onurcan [0000-0002-6094-7162], Yogeeswaran, Kumar [0000-0002-1978-5077], Ziemer, Carolin-Theresa [0000-0002-0794-7702], Zwaan, Rolf A [0000-0001-9967-7879], Boggio, Paulo Sergio [0000-0002-6109-0447], Van Lange, Paul AM [0000-0001-7774-6984], Prasad, Rajib [0000-0003-0913-1624], Onderco, Michal [0000-0001-9911-3782], O'Madagain, Cathal [0000-0002-4086-524X], Nesh-Nash, Tarik [0000-0002-5532-9095], Kubin, Emily [0000-0003-0606-8594], Gümren, Mert [0000-0002-3298-6295], Fenwick, Ali [0000-0002-5412-9745], Ertan, Arhan S [0000-0001-9730-8391], Bernstein, Michael J [0000-0002-8083-9839], Amara, Hanane [0000-0003-0732-2320], Van Bavel, Jay Joseph [0000-0002-2520-0442], Apollo - University of Cambridge Repository, Sociale Psychologie (Psychologie, FMG), ASCoR Other Research (FMG), Department of Neuroscience and Biomedical Engineering, Aalto-yliopisto, Department of Digital Humanities, Department of Psychology and Logopedics, Cognitive Science, High Performance Cognition group, Mind and Matter, and Department of Computer Science

Subjects
Hälso- och sjukvårdsorganisation, hälsopolitik och hälsoekonomi, Economics, COVID-19, social distancing, hygiene, policy support, public health measures, J Political Science, [SHS.PSY]Humanities and Social Sciences/Psychology, psychology, Settore SECS-P/02 - Politica Economica, Q1, H Social Sciences, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], SDG 3 - Good Health and Well-being, RA0421, RA0421 Public health. Hygiene. Preventive Medicine, Machine learning, Psychology, Nationalekonomi, Settore SECS-P/01 - Economia Politica, MCC, Computer. Automation, Psykologi (exklusive tillämpad psykologi), DAS, Health Care Service and Management, Health Policy and Services and Health Economy, [SHS.SCIPO]Humanities and Social Sciences/Political science, Psychology (excluding Applied Psychology), machine learning, Settore SECS-P/03 - Scienza delle Finanze, 5171 Political Science, Human medicine, COVID-19, social distancing, hygiene, policy support, public health measures
Abstract

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic., PNAS Nexus, 1 (3), ISSN:2752-6542

Published
2022
Full Text
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8. Empowering society by reusing privately held data for official statistics - A European approach

Author

Silvina Bakardzhleva, Luis Cardo Jalón, Florent Diverchy, David Dreyer Lassen, Wieteke Dupain, Paolo Garonna, Christoph Gerlinger, David Gonzalez Martinez, Emmanuel Letouzé, Mart Mägi, Geta Mitrea, Felicia Pelagalli, Dominik Rozkrut, Geert Somers, Kaisa Vent, Stefaan Verhulst, Erik Wetter, Susanna Zaccarin, Dimitris Zissis, Bakardzhleva, Silvina, Cardo Jalón, Lui, Diverchy, Florent, Dreyer Lassen, David, Dupain, Wieteke, Garonna, Paolo, Gerlinger, Christoph, Gonzalez Martinez, David, Letouzé, Emmanuel, Mägi, Mart, Mitrea, Geta, Pelagalli, Felicia, Rozkrut, Dominik, Somers, Geert, Vent, Kaisa, Verhulst, Stefaan, Wetter, Erik, Zaccarin, Susanna, and Zissis, Dimitris

Subjects
official statistics, new data source, re-use, new data sources, privately held data
Abstract

The High-Level Expert Group on facilitating the use of new data sources for official statistics has been created in the context of the data and digital strategy of the European Commission (EC). The task of the Expert Group is to provide recommendations aimed at enhancing data sharing between businesses and government (B2G) for the purpose of producing official statistics (B2G4S). The Expert Group consists of high-level experts with various backgrounds that are particularly relevant to B2G4S. Businesses generate and use data primarily for business-related purposes. The motivation for B2G4S stems from the high societal value that such privately held data can potentially generate when transformed into reliable, relevant and timely official statistics that are made available to everybody, for free. Transforming data into statistical information requires cooperation between private data holders and statistical authorities. On a voluntary basis there have been many collaborative efforts by businesses and statistical authorities to produce statistics based on privately held data, but for various reasons the use of such data for official statistics is still far below the level required to provide society with the high-quality and timely official statistics it needs in the increasingly data-driven world.

Published
2022

9. Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus

Author

Donal Bisanzio, Thomas W. Scott, G. R. William Wint, T. Alex Perkins, Nicole Davis Weaver, Lucas Earl, Laurie B. Marczak, Erik Wetter, Hongjie Yu, Shengjie Lai, Dingdong Yi, Simon I. Hay, Wim Van Bortel, Cedric Marsboom, Francis Schaffner, Giovanini E. Coelho, David M. Pigott, Jane P. Messina, Xin Lu, Robert C. Reiner, Linus Bengtsson, Andrew J. Tatem, David L. Smith, Chester G. Moore, Shreya Shirude, Qiyong Liu, Peter A. Jones, Kimberly J. Johnson, Roberta G. Carvalho, John S. Brownstein, Moritz U. G. Kraemer, Oliver J. Brady, Nuno R. Faria, Louis Lambrechts, Nick Golding, Marius Gilbert, Heinrich H. Nax, Guy Hendrickx, Oliver G. Pybus, Simon Cauchemez, Catherine Linard, University of Oxford [Oxford], Boston Children's Hospital, Harvard Medical School [Boston] (HMS), University of Washington [Seattle], London School of Hygiene and Tropical Medicine (LSHTM), Université libre de Bruxelles (ULB), Fonds National de la Recherche Scientifique [Bruxelles] (FNRS), Harvard University [Cambridge], University of Nottingham, UK (UON), Eck Institute for Global Health, University of Notre Dame [Indiana] (UND), Fudan University [Shanghai], University of Southampton, Flowminder Foundation, Central South University [Changsha], National University of Defense Technology [China], Southwestern University of Finance and Economics [Chengdu, China], Waen Associates Ltd, Pan American Health Organization [Washington] (PAHO), Ministry of Health [Brasília, Brazil], European Centre for Disease Prevention and Control (ECDC), Institute of Tropical Medicine [Antwerp] (ITM), Egis Avia (FRANCE), Francis Schaffner Consultancy, Colorado State University [Fort Collins] (CSU), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Karolinska Institutet [Stockholm], Stockholm School of Economics (SSE), Interactions Virus-Insectes - Insect-Virus Interactions (IVI), Centre National de la Recherche Scientifique (CNRS)-Institut Pasteur [Paris], Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Université de Namur [Namur] (UNamur), University of California [Davis] (UC Davis), University of California, Chinese Center for Disease Control and Prevention, Shandong University, University of Melbourne, The authors thank S. Ray for providing comments during the revision process. M.U.G.K. acknowledges funding from the Society in Science, The Branco Weiss Fellowship, administered by the ETH Zurich. M.U.G.K. also acknowledges funding from the Training Grant from the National Institute of Child Health and Human Development (T32HD040128). M.U.G.K., S.I.H., J.P.M., N.G., O.J.B. and G.R.W.W. acknowledge funding from the International Research Consortium on Dengue Risk Assessment Management and Surveillance (IDAMS, European Commission 7th Framework Programme no. 21893). O.B.J. was funded by a Sir Henry Wellcome Fellowship funded by the Wellcome Trust (grant number 206471/Z/17/Z) and a grant from the Bill and Melinda Gates Foundation (OP1183567). S.I.H. received a grant from the Research for Health in Humanitarian Crises (R2HC) Programme, managed by Enhancing Learning and Research for Humanitarian Assistance (ELRHA, no. 13468), which also supported M.U.G.K. and N.G. The R2HC programme aims to improve health outcomes by strengthening the evidence base for public health interventions in humanitarian crises. The £8 million R2HC programme is funded equally by the Wellcome Trust and Department of International Development (DFiD), with ELRHA overseeing the programme’s execution and management. S.I.H. was also funded by a Senior Research Fellowship from the Wellcome Trust (no. 95066) and grants from the Bill & Melinda Gates Foundation (OPP1106023, OPP1093011, OPP1132415 and OPP1159934). This study was made possible by the support of the American people through the US Agency for International Development Emerging Pandemic Threats Program-2 PREDICT-2 (Cooperative Agreement number AID-OAA-A-14-00102), which also supported M.U.G.K. J.S.B. is supported by the National Library of Medicine of the National Institutes of Health (R01LM010812 and R01LM011965), which also supports M.U.G.K. D.L.S. is funded by the National Institutes of Health and National Institute of Allergy and Infectious Diseases (no. U10AI089674). H.H.N. was funded by the European Commission through the European Research Council Advanced Investigator Grant ‘Momentum’ 324247. L.L. received funding from the French Government’s Investissement d’Avenir program, Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases (grant ANR-10-LABX-62-IBEID), the French Agence Nationale de la Recherche (grant ANR-16-CE35-0004), the City of Paris Emergence(s) programme in Biomedical Research, and the European Union’s Horizon 2020 research and innovation programme under ZikaPLAN grant agreement No. 734584. S.C. received funding from the AXA Research Fund, the Investissement d’Avenir program, the Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (Grant ANR-10-LABX-62-IBEID), the Models of Infectious Disease Agent Study of the National Institute of General Medical Sciences, the INCEPTION project (PIA/ANR-16-CONV-0005), and the European Union’s Horizon 2020 research and innovation programme under ZIKAlliance grant agreement No 734548. N.G. is supported by a University of Melbourne McKenzie fellowship. W.V.B., G.H. and F.S. acknowledge funding from VBORNET and VectorNet, an ECDC and EFSA-funded project (no. ECDC/09/018 and OC/EFSA/AHAW/2013/02), and thank all contributing VBORNET and VectorNet experts for data sharing. T.W.S., R.C.R. and L.L. received funding from the National Institutes of Health Program Project grant (no. P01 AI098670). X.L. is supported by the Natural Science Foundation of China (71771213, 71522014, 71725001, 91846301 and 71790615). This work was also partially supported by the European Union’s Horizon 2020 Research and Innovation Programme under ZIKAlliance Grant Agreement no. 734548., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-16-CE35-0004,MOSQUIBIOTA,Contribution de la diversité bactérienne intestinale à la capacité vectorielle d'Aedes aegypti(2016), European Project: 734548,ZIKAlliance(2016), European Project: 324247,EC:FP7:ERC,ERC-2012-ADG_20120411,MOMENTUM(2013), European Project: 281803,EC:FP7:HEALTH,FP7-HEALTH-2011-single-stage,IDAMS(2011), University of Oxford, Harvard University, European Centre for Disease Prevention and Control [Stockholm, Sweden] (ECDC), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), and University of California (UC)

Subjects
Microbiology (medical), Microbiologie et protistologie [parasitologie hum. et anim.], Aedes albopictus, Arbovirus Infections, Immunology, Aedes aegypti, medicine.disease_cause, Applied Microbiology and Biotechnology, Arbovirus, Microbiology, Article, Dengue fever, Zika virus, 03 medical and health sciences, Genetics, medicine, Chikungunya, 030304 developmental biology, Aedes, 0303 health sciences, biology, 030306 microbiology, Ecology, virus diseases, Cell Biology, biology.organism_classification, medicine.disease, 3. Good health, Microbiologie et protistologie [entomologie,phytoparasitolog.], Geography, [SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology, Infectious diseases
Abstract

The global population at risk from mosquito-borne diseases—including dengue, yellow fever, chikungunya and Zika—is expanding in concert with changes in the distribution of two key vectors: Aedes aegypti and Aedes albopictus. The distribution of these species is largely driven by both human movement and the presence of suitable climate. Using statistical mapping techniques, we show that human movement patterns explain the spread of both species in Europe and the United States following their introduction. We find that the spread of Ae. aegypti is characterized by long distance importations, while Ae. albopictus has expanded more along the fringes of its distribution. We describe these processes and predict the future distributions of both species in response to accelerating urbanization, connectivity and climate change. Global surveillance and control efforts that aim to mitigate the spread of chikungunya, dengue, yellow fever and Zika viruses must consider the so far unabated spread of these mosquitos. Our maps and predictions offer an opportunity to strategically target surveillance and control programmes and thereby augment efforts to reduce arbovirus burden in human populations globally., 0, SCOPUS: ar.j, SCOPUS: er.j, info:eu-repo/semantics/published

Published
2019
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10. National identity predicts public health support during a global pandemic

Author

Jay Joseph Van Bavel, Aleksandra Cichocka, Valerio Capraro, Hallgeir Sjåstad, John B. Nezlek, Mark Alfano, Flavio Azevedo, Aleksandra Cislak, Patricia Lockwood, Robert M Ross, Elena Agadullina, Matthew A J Apps, JOHN JAMIR BENZON R. ARUTA, Alexander Bor, Charles Crabtree, William A. Cunningham, Koustav De, Christian T. Elbaek, Waqas Ejaz, Andrej Findor, Biljana Gjoneska, Yusaku Horiuchi, Toan Luu Duc Huynh, Agustin Ibanez, Jacob Israelashvili, Katarzyna Jasko, Jaroslaw Kantorowicz, Elena Kantorowicz-Reznichenko, André Krouwel, Michael Laakasuo, Claus Lamm, Caroline Leygue, Mohammad Sabbir Mansoor, Lewend Mayiwar, Honorata Mazepus, Cillian McHugh, Panagiotis Mitkidis, Andreas Olsson, Tobias Otterbring, Anat Perry, Dominic Packer, Michael Bang Petersen, Arathy Puthillam, Tobias Rothmund, SHRUTI TEWARI, Manos Tsakiris, Hans Tung, Meltem Yucel, Edmunds Vanags, Madalina Vlasceanu, Benedict Guzman Antazo, Sergio Barbosa, Brock Bastian, Ennio Bilancini, Natalia Bogatyreva, Leonardo Boncinelli, Jonathan E. Booth, Sylvie Borau, Ondrej Buchel, Chrissie Ferreira Carvalho, Tatiana Celadin, Chiara Cerami, Luca Cian, Chiara Crespi, Jo Cutler, Sylvain Delouvée, Guillaume Dezecache, Roberto Di Paolo, Uwe Dulleck, Tom Etienne, Fahima Farkhari, Jonathan Albert Fugelsang, Theofilos Gkinopoulos, Kurt Gray, Siobhán M Griffin, Bjarki Gronfeldt, June Gruber, Elizabeth Ann Harris, Matej Hruška, Ozan Isler, Simon Jangard, Frederik Juhl Jørgensen, Lina Koppel, Josh Leota, Eva Lermer, Neil L Levy, Chiara Longoni, Asako Miura, Rafał Muda, Annalisa Myer, Kyle Nash, Jonas P. Nitschke, Yohsuke Ohtsubo, Victoria Oldemburgo de Mello, Yafeng Pan, Papp Zsófia, Philip Pärnamets, Mariola Paruzel-Czachura, Michael Mark Pitman, Joanna Pyrkosz-Pacyna, Steve Rathje, Ali Raza, Kasey Rhee, Gabriel Gaudencio do Rêgo, Claire Robertson, Octavio Salvador-Ginez, Waldir M. Sampaio, David Alan Savage, Julian Andrew Scheffer, Philipp Schönegger, Andy Scott, Ahmed Skali, Brent Strickland, Clara Alexandra Stafford, Anna Stefaniak, Anni Sternisko, Gustav Tinghög, Benno Torgler, Raffaele Tucciarelli, Nick D'Angelo Ungson, Mete Sefa Uysal, Jan-Willem van Prooijen, Dirk Van Rooy, Daniel Västfjäll, Joana Vieira, Alexander C. Walker, Erik Wetter, Robin Richard Willardt, Adrian Dominik Wojcik, Kaidi Wu, Yuki Yamada, Onurcan Yilmaz, Kumar Yogeeswaran, Rolf Antonius Zwaan, Paulo Boggio, Daryl Cameron, Michael Tyrala, Estrella Gualda, David Moreau, Jussi Palomäki, and Matthias F. C. Hudecek

Subjects
medicine.medical_specialty, Economic growth, Distancing, Public health, media_common.quotation_subject, Psychological intervention, Public policy, Hygiene, Political science, Pandemic, National identity, medicine, World Values Survey, media_common
Abstract

Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors that associated with people reported adopting public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = -.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics.

Published
2020
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11. Population mobility reductions associated with travel restrictions during the Ebola epidemic in Sierra Leone: use of mobile phone data

Author

Sergio Ramos, Elisabeth zu Erbach-Schoenberg, Elaine Weidman-Grunewald, Caroline O. Buckee, Amy Wesolowski, Xin Lu, Linus Bengtsson, Corey M. Peak, Simon Moritz, Daniel Power, Erik Wetter, and Andrew J. Tatem

Subjects
Geographic mobility, Epidemiology, mobile phone data, 030231 tropical medicine, Internet privacy, Big data, Population Dynamics, Infectious Disease, medicine.disease_cause, Sierra leone, Sierra Leone, 03 medical and health sciences, 0302 clinical medicine, big data, medicine, Humans, Ebola epidemic, human mobility, population mobility, 030212 general & internal medicine, Epidemics, Retrospective Studies, Infection Control, Travel, Ebola virus, business.industry, Incidence, Anomaly detection algorithm, quarantine, General Medicine, Hemorrhagic Fever, Ebola, 3. Good health, travel restrictions, Geography, Mobile phone, Scale (social sciences), business, Effect modification, Cell Phone
Abstract

Background: Travel restrictions were implemented on an unprecedented scale in 2015 in Sierra Leone to contain and eliminate Ebola virus disease. However, the impact of epidemic travel restrictions on mobility itself remains difficult to measure with traditional methods. New 'big data' approaches using mobile phone data can provide, in near real-time, the type of information needed to guide and evaluate control measures.Methods: We analysed anonymous mobile phone call detail records (CDRs) from a leading operator in Sierra Leone between 20 March and 1 July in 2015. We used an anomaly detection algorithm to assess changes in travel during a national 'stay at home' lockdown from 27 to 29 March. To measure the magnitude of these changes and to assess effect modification by region and historical Ebola burden, we performed a time series analysis and a crossover analysis.Results: Routinely collected mobile phone data revealed a dramatic reduction in human mobility during a 3-day lockdown in Sierra Leone. The number of individuals relocating between chiefdoms decreased by 31% within 15 km, by 46% for 15-30 km and by 76% for distances greater than 30 km. This effect was highly heterogeneous in space, with higher impact in regions with higher Ebola incidence. Travel quickly returned to normal patterns after the restrictions were lifted.Conclusions: The effects of travel restrictions on mobility can be large, targeted and measurable in near real-time. With appropriate anonymization protocols, mobile phone data should play a central role in guiding and monitoring interventions for epidemic containment.

Published
2018

12. Detecting climate adaptation with mobile network data in Bangladesh: anomalies in communication, mobility and consumption patterns during cyclone Mahasen

Author

Pål Sundsøy, Md. Nadiruzzaman, David Wrathall, Kenth Engø-Monsen, Taimur Qureshi, Andrew J. Tatem, Asif M. Iqbal, Geoffrey Canright, Erik Wetter, Linus Bengtsson, and Xin Lu

Subjects
Atmospheric Science, 010504 meteorology & atmospheric sciences, Meteorology, media_common.quotation_subject, Population, Climate change adaptation, Anomaly detection, 010501 environmental sciences, 01 natural sciences, Article, Mobile network data, education, Migration, 0105 earth and related environmental sciences, media_common, Global and Planetary Change, education.field_of_study, Resilience, Warning system, Storm, Disaster risk, Geography, 13. Climate action, Mobile phone, Cellular network, Cyclone, Psychological resilience
Abstract

Large-scale data from digital infrastructure, like mobile phone networks, provides rich information on the behavior of millions of people in areas affected by climate stress. Using anonymized data on mobility and calling behavior from 5.1 million Grameenphone users in Barisal Division and Chittagong District, Bangladesh, we investigate the effect of Cyclone Mahasen, which struck Barisal and Chittagong in May 2013. We characterize spatiotemporal patterns and anomalies in calling frequency, mobile recharges, and population movements before, during and after the cyclone. While it was originally anticipated that the analysis might detect mass evacuations and displacement from coastal areas in the weeks following the storm, no evidence was found to suggest any permanent changes in population distributions. We detect anomalous patterns of mobility both around the time of early warning messages and the storm’s landfall, showing where and when mobility occurred as well as its characteristics. We find that anomalous patterns of mobility and calling frequency correlate with rainfall intensity (r = .75, p

Published
2016
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13. A trip to work: Estimation of origin and destination of commuting patterns in the main metropolitan regions of Haiti using CDR

Author

Christopher James Brooks, Nancy Lozano-Gracia, Erik Wetter, Linus Bengtsson, Jonathan Gray, Elisabeth zu Erbach-Schoenberg, Priya Burci, Sarah Elizabeth Antos, Andrew J. Tatem, Guilherme Zagatti, Maximilian Albert, Paolo Avner, and Miguel Gonzalez

Subjects
0301 basic medicine, Population, 0211 other engineering and technologies, Context (language use), Urbanisation, 02 engineering and technology, Development, CDRNon-supervised learning, Disease cluster, lcsh:HD72-88, lcsh:Economic growth, development, planning, 03 medical and health sciences, Urban planning, Urbanization, ddc:330, Economic geography, education, Estimation, education.field_of_study, Commuting, General Engineering, Call detail records, 021107 urban & regional planning, Census, Metropolitan area, Computer Science Applications, 030104 developmental biology, Geography, lcsh:Electrical engineering. Electronics. Nuclear engineering, General Economics, Econometrics and Finance, lcsh:TK1-9971
Abstract

The rapid, unplanned urbanisation in Haiti creates a series of urban mobility challenges which can contribute to job market fragmentation and decrease the quality of life in the city. Data on population and job distributions, and on home-work commuting patterns in major urban centres are scarce. The most recent census took place in 2003 and events such as the 2010 earthquake have caused major redistributions of the population. In this data scarce context, our work takes advantage of nationwide de-identified Call Detail Records (CDR) from the main mobile operator in the country to investigate night and daytime populations densities and commuting patterns. We use a non-supervised learning algorithm to identify meaningful locations for individuals. These locations are then labelled according to a scoring criteria. The labelled locations are distributed in a grid with cells measuring 500 × 500 m in order to aggregate the individual level data and to create origin-destination matrices of weighted connections between home and work locations. The results suggest that labor markets are fragmented in Haiti. The two main urban centres, Port-au-Prince and Cap-Haïtien suffer from low employment accessibility as measured by the percentage of the population that travels beyond their identified home cluster (1 km radius) during the day. The data from the origin-destination matrices suggest that only 42 and 40 percent of the population are considered to be commuters in Port-au-Prince and Cap-Haïtien respectively. Keywords: Urbanisation, Call detail records, CDR, Non-supervised learning, Commuting, Urban planning

Published
2018

14. Remotely measuring populations during a crisis by overlaying two data sources

Author

Xin Lu, Erik Wetter, Linus Bengtsson, Nita Bharti, and Andrew J. Tatem

Subjects
Satellite Imagery, Warfare, Health (social science), Light, Movement, Humanitarian crisis, Cote d ivoire, Crisis, Humans, Medicine, Mobile phones, Population Density, Refugees, Data collection, Weight measurement scales, business.industry, Communication, Data Collection, Environmental resource management, Public Health, Environmental and Occupational Health, Original Articles, General Medicine, Altruism, Cote d'Ivoire, Remote Sensing Technology, Emergencies, business, Cell Phone
Abstract

Background Societal instability and crises can cause rapid, large-scale movements. These movements are poorly understood and difficult to measure but strongly impact health. Data on these movements are important for planning response efforts. We retrospectively analyzed movement patterns surrounding a 2010 humanitarian crisis caused by internal political conflict in Côte d'Ivoire using two different methods. Methods We used two remote measures, nighttime lights satellite imagery and anonymized mobile phone call detail records, to assess average population sizes as well as dynamic population changes. These data sources detect movements across different spatial and temporal scales. Results The two data sources showed strong agreement in average measures of population sizes. Because the spatiotemporal resolution of the data sources differed, we were able to obtain measurements on long- and short-term dynamic elements of populations at different points throughout the crisis. Conclusions Using complementary, remote data sources to measure movement shows promise for future use in humanitarian crises. We conclude with challenges of remotely measuring movement and provide suggestions for future research and methodological developments.

Published
2015
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15. Publisher Correction: Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus

Author

Nicole Davis Weaver, Lucas Earl, Laurie B. Marczak, G. R. William Wint, Nuno R. Faria, Cedric Marsboom, Dingdong Yi, Giovanini E. Coelho, Shreya Shirude, Andrew J. Tatem, David M. Pigott, Louis Lambrechts, Shengjie Lai, Linus Bengtsson, Simon Cauchemez, Hongjie Yu, David L. Smith, Chester G. Moore, Roberta G. Carvalho, Xin Lu, Oliver J. Brady, Catherine Linard, Kimberly B. Johnson, Moritz U. G. Kraemer, Oliver G. Pybus, Robert Reiner, Qiyong Liu, Thomas W. Scott, Simon I. Hay, Donal Bisanzio, T. Alex Perkins, Marius Gilbert, Heinrich H. Nax, Guy Hendrickx, Nick Golding, Peter A. Jones, John S. Brownstein, Francis Schaffner, Jane P. Messina, Erik Wetter, and Wim Van Bortel

Subjects
Microbiology (medical), medicine.medical_specialty, History, media_common.quotation_subject, 030231 tropical medicine, Immunology, Library science, Mosquito Vectors, Arbovirus Infections, Applied Microbiology and Biotechnology, Microbiology, 03 medical and health sciences, 0302 clinical medicine, Aedes, Hygiene, Epidemiology, medicine, Genetics, Animals, Humans, China, media_common, 030304 developmental biology, 0303 health sciences, 030306 microbiology, Public health, Published Erratum, Spell, Cell Biology, Infectious Disease Epidemiology, Publisher Correction, 3. Good health, Medical Microbiology, Tropical medicine, Infectious diseases, Female, Arboviruses
Abstract

The global population at risk from mosquito-borne diseases-including dengue, yellow fever, chikungunya and Zika-is expanding in concert with changes in the distribution of two key vectors: Aedes aegypti and Aedes albopictus. The distribution of these species is largely driven by both human movement and the presence of suitable climate. Using statistical mapping techniques, we show that human movement patterns explain the spread of both species in Europe and the United States following their introduction. We find that the spread of Ae. aegypti is characterized by long distance importations, while Ae. albopictus has expanded more along the fringes of its distribution. We describe these processes and predict the future distributions of both species in response to accelerating urbanization, connectivity and climate change. Global surveillance and control efforts that aim to mitigate the spread of chikungunya, dengue, yellow fever and Zika viruses must consider the so far unabated spread of these mosquitos. Our maps and predictions offer an opportunity to strategically target surveillance and control programmes and thereby augment efforts to reduce arbovirus burden in human populations globally.

Published
2019
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16. Mapping poverty using mobile phone and satellite data

Author

Erik Wetter, Xin Lu, Linus Bengtsson, Pål Sundsøy, Andrew J. Tatem, Tomas J. Bird, Victor A. Alegana, Kenth Engø-Monsen, Yves-Alexandre de Montjoye, Asif M. Iqbal, Carla Pezzulo, Joshua E. Blumenstock, Khandakar N. Hadiuzzaman, Jessica Steele, and Johannes Bjelland

Subjects
DYNAMICS, WEALTH, 010504 meteorology & atmospheric sciences, Computer science, IMAGERY, computer.software_genre, 01 natural sciences, Biochemistry, 010104 statistics & probability, remote sensing, Theoretical, poverty mapping, Models, 11. Sustainability, Statistics, Econometrics, Bayesian geostatistical modelling, Relative value, 1. No poverty, Satellite Communications, Multidisciplinary Sciences, APPROXIMATE BAYESIAN-INFERENCE, Science & Technology - Other Topics, Aggregate data, INDIA, Biotechnology, Research Article, Geospatial analysis, General Science & Technology, mobile phone data, MODELS, Biomedical Engineering, Biophysics, Bioengineering, No Poverty, Biomaterials, Predictive Value of Tests, Humans, 0101 mathematics, Poverty, 0105 earth and related environmental sciences, Data collection, Science & Technology, Mobile broadband, Models, Theoretical, Mobile phone, Generic health relevance, Rural area, Life Sciences–Mathematics interface, computer, Cell Phone
Abstract

Poverty is one of the most important determinants of adverse health outcomes globally, a major cause of societal instability and one of the largest causes of lost human potential. Traditional approaches to measuring and targeting poverty rely heavily on census data, which in most low- and middle-income countries (LMICs) are unavailable or out-of-date. Alternate measures are needed to complement and update estimates between censuses. This study demonstrates how public and private data sources that are commonly available for LMICs can be used to provide novel insight into the spatial distribution of poverty. We evaluate the relative value of modelling three traditional poverty measures using aggregate data from mobile operators and widely available geospatial data. Taken together, models combining these data sources provide the best predictive power (highest r 2 = 0.78) and lowest error, but generally models employing mobile data only yield comparable results, offering the potential to measure poverty more frequently and at finer granularity. Stratifying models into urban and rural areas highlights the advantage of using mobile data in urban areas and different data in different contexts. The findings indicate the possibility to estimate and continually monitor poverty rates at high spatial resolution in countries with limited capacity to support traditional methods of data collection.

Published
2017

17. Data from a pre-publication independent replication initiative examining ten moral judgement effects

Author

Carlos T. Wilson, Lynn Wong, Jennifer Jordan, Erik W. Cheries, P. Scott Ramsay, Andrew Canavan, Nikhil Madan, Jun Gu, Felix Cheung, Warren Tierney, Aaron M. Sackett, Nicole J. Hartwich, Cong Wei, Harvey Packham, Alexandra A. Mislin, Jesse Chandler, Andrew C. Hafenbrack, Hoai Huong Ngo, Daniel Diermeier, Clintin P. Davis-Stober, Timo P. Luoma, Lily Jiang, Wendy L. Bedwell, Walter Sowden, Daniel C. Molden, Xiaomin Sun, Deanna M. Kennedy, Jennifer Miles, Anthony N. Washburn, Maarten Marsman, Christina M. Tworek, Martin Schweinsberg, David Tannenbaum, Christilene du Plessis, Monica Gamez-Djokic, Eliza Bivolaru, S. Amy Sommer, Tabitha Anderson, Andrei Cimpian, Nicole Legate, Tehlyr Kellogg, Peter H. Ditto, Victoria L. Brescoll, Matt Motyl, Yoel Inbar, Anne-Laure Sellier, Justin E. Heinze, Christopher W. Bauman, Toshio Murase, Quentin Frederik Gronau, Kristie Hein, Adam Hahn, Eric Luis Uhlmann, Peter Meindl, Mark A. Clark, Rebecca Hofstein Grady, Israr Qureshi, Malavika Srinivasan, Eli Awtrey, Heidi Maibeucher, Sophie Charlotte Darroux, Michael Schaerer, Sapna Cheryan, Alice Amell, Michelangelo Vianello, Eko Yi Liao, Jennifer L. Ray, Jason Dana, Sarah E. Frick, Jay J. Van Bavel, Fiery Cushman, Daniel Storage, Luke Lei Zhu, Diana Cordon, Brittany E. Hanson, Alexander Ly, George E. Newman, Erik Wetter, Jesse Graham, Eric-Jan Wagenmakers, Tatiana Sokolova, Nico Thornley, Veritati - Repositório Institucional da Universidade Católica Portuguesa, and Psychologische Methodenleer (Psychologie, FMG)

Subjects
Statistics and Probability, Data Descriptor, Research groups, Computer science, Applied psychology, Judgement, 050109 social psychology, Library and Information Sciences, Morals, Research management, 050105 experimental psychology, Education, Information Systems, Statistics, Probability and Uncertainty, Replication (statistics), Information system, Humans, Psychology, 0501 psychology and cognitive sciences, Ethics, Statistics, 05 social sciences, Reproducibility of Results, Replicate, Data science, Computer Science Applications, Probability and Uncertainty, Decision making
Abstract

We present the data from a crowdsourced project seeking to replicate findings in independent laboratories before (rather than after) they are published. In this Pre-Publication Independent Replication (PPIR) initiative, 25 research groups attempted to replicate 10 moral judgment effects from a single laboratory’s research pipeline of unpublished findings. The 10 effects were investigated using online/lab surveys containing psychological manipulations (vignettes) followed by questionnaires. Results revealed a mix of reliable, unreliable, and culturally moderated findings. Unlike any previous replication project, this dataset includes the data from not only the replications but also from the original studies, creating a unique corpus that researchers can use to better understand reproducibility and irreproducibility in science.

Published
2016
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18. The pipeline project: Pre-publication independent replications of a single laboratory's research pipeline

Author

Walter Sowden, Martin Schweinsberg, Sophie Charlotte Darroux, Andrew C. Hafenbrack, Cong Wei, Lily Jiang, Michelangelo Vianello, Warren Tierney, Heidi Maibuecher, Luke Lei Zhu, Israr Qureshi, Deanna M. Kennedy, Nikhil Madan, Daniel Storage, Rebecca Hofstein Grady, Malavika Srinivasan, Wendy L. Bedwell, Nicole J. Hartwich, Daniel Diermeier, Eric Luis Uhlmann, Peter Meindl, Christilene du Plessis, Harvey Packham, Jennifer L. Ray, Jesse Chandler, Eli Awtrey, Tatiana Sokolova, Sapna Cheryan, Toshio Murase, Christopher W. Bauman, Felix Cheung, Nicole Legate, Jason Dana, Erik W. Cheries, Jun Gu, Thomas Donahue, Alexandra A. Mislin, Tabitha Anderson, Erik Wetter, Daniel C. Molden, Tehlyr Kellogg, Peter H. Ditto, Diana Cordon, Andrei Cimpian, Eko Yi Liao, Jennifer Jordan, Aaron M. Sackett, Clintin P. Davis-Stober, Alexander Ly, Kristie Hein, Jesse Graham, S. Amy Sommer, Maarten Marsman, Jay J. Van Bavel, Eric-Jan Wagenmakers, Matt Motyl, Lynn Wong, Eliza Bivolaru, Quentin Frederik Gronau, Fiery Cushman, Xiaomin Sun, Brittany E. Hanson, Yoel Inbar, Philip S. Ramsay, Justin E. Heinze, Mark A. Clark, George E. Newman, Nico Thornley, Jennifer Miles, Monica Gamez-Djokic, Anthony N. Washburn, Christina M. Tworek, Michael Schaerer, Andrew Canavan, David Tannenbaum, Anne-Laure Sellier, Adam Hahn, Carlos T. Wilson, Hoai Huong Ngo, Timo P. Luoma, Sarah E. Frick, Victoria L. Brescoll, Veritati - Repositório Institucional da Universidade Católica Portuguesa, Psychologische Methodenleer (Psychologie, FMG), Research programme OB, Department of Marketing, and Research Group: Marketing

Subjects
CONFIDENCE, Research groups, Sociology and Political Science, Experimental Replication, Social Psychology, IMPACT, FLEXIBILITY, Replication Process, Data_MISCELLANEOUS, Crowdsourcing science, Meta-science, Methodology, Replication, Reproducibility, Research transparency, 050109 social psychology, ECONOMISTS, Crowdsourcing, Cardiovascular, INCREASE, 050105 experimental psychology, Outsourcing, PSYCHOLOGY, FUTURE, Sciences, Replication (statistics), Psychology, 0501 psychology and cognitive sciences, CRISIS, business.industry, 05 social sciences, Pipeline (software), Heart Disease, REPLICABILITY, Scale (social sciences), Cognitive Sciences, business, Social psychology, RESPONSES
Abstract

This crowdsourced project introduces a collaborative approach to improving the reproducibility of scientific research, in which findings are replicated in qualified independent laboratories before (rather than after) they are published. Our goal is to establish a non-adversarial replication process with highly informative final results. To illustrate the Pre-Publication Independent Replication (PPIR) approach, 25 research groups conducted replications of all ten moral judgment effects which the last author and his collaborators had 'in the pipeline' as of August 2014. Six findings replicated according to all replication criteria, one finding replicated but with a significantly smaller effect size than the original, one finding replicated consistently in the original culture but not outside of it, and two findings failed to find support. In total, 40% of the original findings failed at least one major replication criterion. Potential ways to implement and incentivize pre-publication independent replication on a large scale are discussed. (PsycINFO Database Record (c) 2019 APA, all rights reserved)

Published
2016

19. Census-derived migration data as a tool for informing malaria elimination policy

Author

Nick W. Ruktanonchai, Xin Lu, Erik Wetter, Roberto C. Córdoba, Andrew J. Tatem, Darlene Bhavnani, Linus Bengtsson, Elisabeth zu Erbach-Schoenberg, Keith H. Carter, Arnaud Le Menach, and Alessandro Sorichetta

Subjects
Costa Rica, Veterinary medicine, Human mobility, Human Migration, 030231 tropical medicine, Population, Psychological intervention, Microdata (statistics), Nicaragua, Malaria elimination, Biology, 03 medical and health sciences, 0302 clinical medicine, Disease Transmission, Infectious, medicine, Humans, 030212 general & internal medicine, Disease Eradication, education, Census data, Migration, Health policy, Travel, education.field_of_study, Human migration, business.industry, Health Policy, Research, 1. No poverty, Mobile phone data, Censuses, Census, medicine.disease, Haiti, Malaria, 3. Good health, Infectious Diseases, Mobile phone, Demographic economics, Parasitology, business
Abstract

Background Numerous countries around the world are approaching malaria elimination. Until global eradication is achieved, countries that successfully eliminate the disease will contend with parasite reintroduction through international movement of infected people. Human-mediated parasite mobility is also important within countries near elimination, as it drives parasite flows that affect disease transmission on a subnational scale. Methods Movement patterns exhibited in census-based migration data are compared with patterns exhibited in a mobile phone data set from Haiti to quantify how well migration data predict short-term movement patterns. Because short-term movement data were unavailable for Mesoamerica, a logistic regression model fit to migration data from three countries in Mesoamerica is used to predict flows of infected people between subnational administrative units throughout the region. Results Population flows predicted using census-based migration data correlated strongly with mobile phone-derived movements when used as a measure of relative connectivity. Relative population flows are therefore predicted using census data across Mesoamerica, informing the areas that are likely exporters and importers of infected people. Relative population flows are used to identify community structure, useful for coordinating interventions and elimination efforts to minimize importation risk. Finally, the ability of census microdata inform future intervention planning is discussed in a country-specific setting using Costa Rica as an example. Conclusions These results show long-term migration data can effectively predict the relative flows of infected people to direct malaria elimination policy, a particularly relevant result because migration data are generally easier to obtain than short-term movement data such as mobile phone records. Further, predicted relative flows highlight policy-relevant population dynamics, such as major exporters across the region, and Nicaragua and Costa Rica’s strong connection by movement of infected people, suggesting close coordination of their elimination efforts. Country-specific applications are discussed as well, such as predicting areas at relatively high risk of importation, which could inform surveillance and treatment strategies. Electronic supplementary material The online version of this article (doi:10.1186/s12936-016-1315-5) contains supplementary material, which is available to authorized users.

Published
2016

20. Unveiling hidden migration and mobility patterns in climate stressed regions: A longitudinal study of six million anonymous mobile phone users in Bangladesh

Author

Md. Nadiruzzaman, Geoffrey Canright, Pål Sundsøy, Erik Wetter, Andrew J. Tatem, David Wrathall, Taimur Qureshi, Xin Lu, Kenth Engø-Monsen, Linus Bengtsson, and Asif M. Iqbal

Subjects
Longitudinal study, 010504 meteorology & atmospheric sciences, Geography, Planning and Development, Climate change, 010501 environmental sciences, Management, Monitoring, Policy and Law, Mobile data, 01 natural sciences, Extreme weather, Adaptation, Migration, 0105 earth and related environmental sciences, Bangladesh, Global and Planetary Change, Ecology, Human migration, business.industry, Mobile broadband, Individual mobility, Geography, Disaster, Mobile phone, Cellular network, business, Cartography
Abstract

Climate change is likely to drive migration from environmentally stressed areas. However quantifying short and long-term movements across large areas is challenging due to difficulties in the collection of highly spatially and temporally resolved human mobility data. In this study we use two datasets of individual mobility trajectories from six million de-identified mobile phone users in Bangladesh over three months and two years respectively. Using data collected during Cyclone Mahasen, which struck Bangladesh in May 2013, we show first how analyses based on mobile network data can describe important short-term features (hours–weeks) of human mobility during and after extreme weather events, which are extremely hard to quantify using standard survey based research. We then demonstrate how mobile data for the first time allow us to study the relationship between fundamental parameters of migration patterns on a national scale. We concurrently quantify incidence, direction, duration and seasonality of migration episodes in Bangladesh. While we show that changes in the incidence of migration episodes are highly correlated with changes in the duration of migration episodes, the correlation between in- and out-migration between areas is unexpectedly weak. The methodological framework described here provides an important addition to current methods in studies of human migration and climate change.

Published
2016

21. Rapid and Near Real-Time Assessments of Population Displacement Using Mobile Phone Data Following Disasters: The 2015 Nepal Earthquake

Author

Christopher James Brooks, Heather Chamberlain, Maximilian Albert, Lenka Pitonakova, Sam Guthrie, Simon Tudge, Andrew J. Tatem, Xin Lu, Linus Bengtsson, Daniel Power, Miguel Gonzalez, Christopher Hughes, Caroline O. Buckee, Elisabeth zu Erbach-Schoenberg, Robin Wilson, and Erik Wetter

Subjects
Geographic mobility, education.field_of_study, 010504 meteorology & atmospheric sciences, Warning system, business.industry, Environmental resource management, Population, Medicine (miscellaneous), Poison control, Computer security, computer.software_genre, 01 natural sciences, 03 medical and health sciences, 0302 clinical medicine, Earthquake casualty estimation, Mobile phone, Damages, Medicine, 030212 general & internal medicine, business, Natural disaster, education, computer, 0105 earth and related environmental sciences, Research Article
Abstract

INTRODUCTION: Sudden impact disasters often result in the displacement of large numbers of people. These movements can occur prior to events, due to early warning messages, or take place post-event due to damages to shelters and livelihoods as well as a result of long-term reconstruction efforts. Displaced populations are especially vulnerable and often in need of support. However, timely and accurate data on the numbers and destinations of displaced populations are extremely challenging to collect across temporal and spatial scales, especially in the aftermath of disasters. Mobile phone call detail records were shown to be a valid data source for estimates of population movements after the 2010 Haiti earthquake, but their potential to provide near real-time ongoing measurements of population displacements immediately after a natural disaster has not been demonstrated. METHODS: A computational architecture and analytical capacity were rapidly deployed within nine days of the Nepal earthquake of 25th April 2015, to provide spatiotemporally detailed estimates of population displacements from call detail records based on movements of 12 million de-identified mobile phones users. RESULTS: Analysis shows the evolution of population mobility patterns after the earthquake and the patterns of return to affected areas, at a high level of detail. Particularly notable is the movement of an estimated 390,000 people above normal from the Kathmandu valley after the earthquake, with most people moving to surrounding areas and the highly-populated areas in the central southern area of Nepal. DISCUSSION: This analysis provides an unprecedented level of information about human movement after a natural disaster, provided within a very short timeframe after the earthquake occurred. The patterns revealed using this method are almost impossible to find through other methods, and are of great interest to humanitarian agencies. Language: en

Published
2016

22. The Legitimacy of Data Partnerships for Sustainable Development

Author

Andreas Rasche, Mette Morsing, and Erik Wetter

Subjects
Sustainable development, 0502 economics and business, 05 social sciences, 050602 political science & public administration, Context (language use), General Medicine, Business, Public administration, 050203 business & management, Legitimacy, 0506 political science
Abstract

This paper critically examines the legitimacy attached to new types of public- private data partnerships occurring in the context of sustainable development. We discuss the input and output legitim...

Published
2018
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23. Evaluation of a Schanz Pin Technique for Posterior Cruciate Ligament Tensioning during Reconstruction

Author

Erik Wetter, Vincent H. Key, and Terence E. McIff

Subjects
Joint Instability, Male, musculoskeletal diseases, Knee Joint, Bone Nails, Prosthesis Implantation, Proximal tibia, Cadaver, medicine, Humans, Orthopedics and Sports Medicine, Femur, Tibia, Anterior drawer, Aged, business.industry, Anatomy, musculoskeletal system, Sagittal plane, Biomechanical Phenomena, medicine.anatomical_structure, Posterior cruciate ligament, Ligament, Female, Posterior Cruciate Ligament, Surgery, business, Cadaveric spasm
Abstract

Maximum anterior positioning of the tibia relative to the femur during posterior cruciate ligament (PCL) reconstruction is essential for achieving a tight graft and stable joint. A Schanz pin inserted in the proximal tibia is sometimes used to pull the proximal tibia forward during tensioning of the graft in PCL reconstruction. This study was designed to evaluate whether this technique provides more anterior translation than the traditional anterior drawer technique. Eight fresh-frozen cadaveric knees were tested using both methods in randomized order: pulling anteriorly on a 5-mm Schanz pin in the proximal tibia or a leather strap behind the calf designed to simulate a surgeon's hand performing an anterior drawer maneuver. An anteriorly directed force was applied from 0 to 60 N, and the sagittal position of the tibia in relation to the femur was recorded using a mini C-arm. Tests were performed first on the intact knees, again after the PCL had been cut, and again following transection of the popliteal-fibular ligament. We found a statistically significant ( P < 0.05) increase in tibial translation, ranging between 1 and 2 mm, when the tibia was pulled by the Schanz pin compared with the strap under every set of conditions. This greater anterior translation could improve the stability of the postreconstructed knee.

Published
2010
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24. Improving Business Failure Prediction for New Firms: Benchmarking Financial Models with Human and Social Capital

Author

Karl Wennberg and Erik Wetter

Subjects
Finance, Economics and Econometrics, Entrepreneurship, Financial performance, business.industry, Benchmarking, Economics, Predictive power, Business failure prediction, Financial modeling, business, Tertiary sector of the economy, Industrial organization, Social capital
Abstract

Business failure prediction is a prominent issue in research and practice. However, the relation between financial performance and firm default in new firms is more complex than previously assumed and both finance researchers and practitioners can benefit from the existing research on entrepreneurship and new firm performance. Developing measures for human and social capital grounded in previous research, we find that either of these variables have considerably higher predictive power than the standard financial model in predicting which firms stay in business and which firms that default. With regards to new firms in high-technology and service industries, the traditional financial model does not beat the predictive accuracy of simply flipping a coin.

Published
2009
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25. Exploring the high-resolution mapping of gender-disaggregated development indicators

Author

Graeme Hornby, Nick W. Ruktanonchai, Alessandro Sorichetta, Carla Pezzulo, Jessica Steele, Victor A. Alegana, Tomas J. Bird, Linus Bengtsson, Claudio Bosco, Andrew J. Tatem, Corrine W. Ruktanonchai, and Erik Wetter

Subjects
Male, Rural Population, Geographic information system, Geographic Mapping, computer.software_genre, 01 natural sciences, Biochemistry, Multivariate interpolation, 010104 statistics & probability, 0302 clinical medicine, Econometrics, geographic information system, 030212 general & internal medicine, mapping, Sanitation, 10. No inequality, Contraception Behavior, Growth Disorders, education.field_of_study, development indicators, 1. No poverty, Middle Aged, Explained variation, Geography, Scale (social sciences), Female, geo-statistics, Research Article, Biotechnology, Adult, Geospatial analysis, Adolescent, Population, Biomedical Engineering, Biophysics, Nigeria, Nutritional Status, Bioengineering, Context (language use), Biomaterials, 03 medical and health sciences, Sex Factors, Literacy, Humans, Computer Simulation, 0101 mathematics, education, Poverty, Demography, Spatial Analysis, business.industry, Bayes Theorem, Kenya, Health indicator, Socioeconomic Factors, Neural Networks, Computer, Life Sciences–Mathematics interface, business, computer
Abstract

Improved understanding of geographical variation and inequity in health status, wealth and access to resources within countries is increasingly being recognized as central to meeting development goals. Development and health indicators assessed at national or subnational scale can often conceal important inequities, with the rural poor often least well represented. The ability to target limited resources is fundamental, especially in an international context where funding for health and development comes under pressure. This has recently prompted the exploration of the potential of spatial interpolation methods based on geolocated clusters from national household survey data for the high-resolution mapping of features such as population age structures, vaccination coverage and access to sanitation. It remains unclear, however, how predictable these different factors are across different settings, variables and between demographic groups. Here we test the accuracy of spatial interpolation methods in producing gender-disaggregated high-resolution maps of the rates of literacy, stunting and the use of modern contraceptive methods from a combination of geolocated demographic and health surveys cluster data and geospatial covariates. Bayesian geostatistical and machine learning modelling methods were tested across four low-income countries and varying gridded environmental and socio-economic covariate datasets to build 1×1 km spatial resolution maps with uncertainty estimates. Results show the potential of the approach in producing high-resolution maps of key gender-disaggregated socio-economic indicators, with explained variance through cross-validation being as high as 74–75% for female literacy in Nigeria and Kenya, and in the 50–70% range for many other variables. However, substantial variations by both country and variable were seen, with many variables showing poor mapping accuracies in the range of 2–30% explained variance using both geostatistical and machine learning approaches. The analyses offer a robust basis for the construction of timely maps with levels of detail that support geographically stratified decision-making and the monitoring of progress towards development goals. However, the great variability in results between countries and variables highlights the challenges in applying these interpolation methods universally across multiple countries, and the importance of validation and quantifying uncertainty if this is undertaken.

Published
2017
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26. Using mobile phone data to predict the spatial spread of cholera

Author

Erik Wetter, Stanislas Rebaudet, Kankoe Sallah, Linus Bengtsson, Sandra Moore, Renaud Piarroux, Xin Lu, Jean Gaudart, HAL AMU, Administrateur, Department of Public Health Sciences, Karolinska Institutet [Stockholm], Flowminder Foundation, Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale (SESSTIM - U912 INSERM - Aix Marseille Univ - IRD), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), College of Information System and Management, National University of Defence Technology, Infections Parasitaires : Transmission, Physiopathologie et Thérapeutiques (IP-TPT), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Service de Santé des Armées, Stockholm School of Economics (SSE), Institut de Recherche pour le Développement (IRD)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Aix Marseille Université (AMU), and Service de Santé des Armées-Assistance Publique - Hôpitaux de Marseille (APHM)-Aix Marseille Université (AMU)-Institut de Recherche pour le Développement (IRD)

Subjects
Geographic mobility, Geographic information system, STRATEGIES, TRANSMISSION, INFECTIOUS-DISEASE, UNITED-STATES, Geographic Mapping, HIERARCHIES, Computer security, computer.software_genre, PANDEMIC INFLUENZA, Sensitivity and Specificity, Article, law.invention, Disease Outbreaks, Spatio-Temporal Analysis, SANITATION, Cholera, law, Environmental health, medicine, Humans, Subscriber identity module, Multidisciplinary, business.industry, MORTALITY, Outbreak, Reproducibility of Results, EPIDEMIC CHOLERA, medicine.disease, Haiti, 3. Good health, Geography, Mobile phone, Infectious disease (medical specialty), [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Preparedness, Population Surveillance, Geographic Information Systems, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business, computer, Cell Phone
Abstract

Effective response to infectious disease epidemics requires focused control measures in areas predicted to be at high risk of new outbreaks. We aimed to test whether mobile operator data could predict the early spatial evolution of the 2010 Haiti cholera epidemic. Daily case data were analysed for 78 study areas from October 16 to December 16, 2010. Movements of 2.9 million anonymous mobile phone SIM cards were used to create a national mobility network. Two gravity models of population mobility were implemented for comparison. Both were optimized based on the complete retrospective epidemic data, available only after the end of the epidemic spread. Risk of an area experiencing an outbreak within seven days showed strong dose-response relationship with the mobile phone-based infectious pressure estimates. The mobile phone-based model performed better (AUC 0.79) than the retrospectively optimized gravity models (AUC 0.66 and 0.74, respectively). Infectious pressure at outbreak onset was significantly correlated with reported cholera cases during the first ten days of the epidemic (p < 0.05). Mobile operator data is a highly promising data source for improving preparedness and response efforts during cholera outbreaks. Findings may be particularly important for containment efforts of emerging infectious diseases, including high-mortality influenza strains.

Published
2014
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27. Commentary: Containing the Ebola outbreak – the potential and challenge of mobile network data

Author

Amy Wesolowski, Andrew J. Tatem, Erik Wetter, Caroline O. Buckee, Xin Lu, and Linus Bengtsson

Subjects
disease outbreak, 0303 health sciences, business.industry, disease model, Medicine (miscellaneous), Outbreak, cellphone, Data science, mobility, 03 medical and health sciences, 0302 clinical medicine, ebola, Commentary, Cellular network, Medicine, 030212 general & internal medicine, business, travel, 030304 developmental biology
Published
2014

28. Approaching the Limit of Predictability in Human Mobility

Author

Xin Lu, Erik Wetter, Nita Bharti, Andrew J. Tatem, and Linus Bengtsson

Subjects
Computer science, Population Dynamics, 02 engineering and technology, Article, Pattern Recognition, Automated, Entropy (classical thermodynamics), Statistics, 0202 electrical engineering, electronic engineering, information engineering, Humans, Entropy (information theory), Entropy (energy dispersal), Predictability, Entropy (arrow of time), Simulation, Travel, Models, Statistical, Multidisciplinary, Markov chain, Entropy (statistical thermodynamics), 020206 networking & telecommunications, Markov Chains, Predictive power, 020201 artificial intelligence & image processing, Algorithms, Cell Phone, Entropy (order and disorder)
Abstract

In this study we analyze the travel patterns of 500,000 individuals in Cote d'Ivoire using mobile phone call data records. By measuring the uncertainties of movements using entropy, considering both the frequencies and temporal correlations of individual trajectories, we find that the theoretical maximum predictability is as high as 88%. To verify whether such a theoretical limit can be approached, we implement a series of Markov chain (MC) based models to predict the actual locations visited by each user. Results show that MC models can produce a prediction accuracy of 87% for stationary trajectories and 95% for non-stationary trajectories. Our findings indicate that human mobility is highly dependent on historical behaviors, and that the maximum predictability is not only a fundamental theoretical limit for potential predictive power, but also an approachable target for actual prediction accuracy.

Published
2013
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29. Opening the Black Box of a Corporation in Dispute: Manager ? Lawyer Coproduction of Response to Business Conflict

Author

Adrian Borbely and Erik Wetter

Subjects
Conflict resolution strategy, Coproduction, business.industry, Political science, Conflict resolution, Conflict resolution research, Online dispute resolution, ComputingMilieux_LEGALASPECTSOFCOMPUTING, Dispute mechanism, Public relations, business, Alternative dispute resolution, Dispute resolution
Abstract

Companies in dispute vary both in how systematically they consider negotiated dispute resolution and in how their legal and decision-making functions interact with each other. Approaching business conflict resolution as a professional service leads to the adoption of new agency assumptions for the study of within-party manager-lawyer relationships in conflict settings and their possible impact on the organization’s propensity to use ADR. When we consider that conflict resolution is not a task clients simply delegate to lawyers but that the two categories will actually craft response to conflict in coproduction with each other, we are able to isolate new internal barriers to conflict resolution. Based on exploratory qualitative data, this contribution explores the notion of coproduction in conflict resolution. It isolates the different lawyer-manager coproduction schemes and drafts a first list of their determinants (structural, organizational and personal). All of this aims to reflect on different ways to increase consideration for ADR in conflict resolution strategy phases, with the idea that for negotiated dispute resolution to take ground in organizations, some organizational change may prove necessary.

Published
2011
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30. Computer Templating of Hip Resurfacing Arthroplasty

Author

James Slover, Erik Wetter, and Henrik Malchau

Subjects
musculoskeletal diseases, Orthodontics, biology, business.industry, medicine.medical_treatment, biology.organism_classification, Hip resurfacing, Arthroplasty, Hip replacement (animal), Femoral head, Valgus, medicine.anatomical_structure, Notching, medicine, Femur, business, Femoral neck
Abstract

The goals of conventional hip replacement surgery typically include restoration of leg length and femoral offset, and pre-operative templating has been an essential component of achieving these goals with surgery. Hip resurfacing has more limited ability to alter these variables than does conventional hip replacement [1,2]. Despite this, preoperative templating may be even more critical when planning for a hip resurfacing procedure for several reasons. First, not all patients with osteo-arthritis of the hip are appropriate for resurfacing, and templat-ing can assist in determining if a patient’s anatomy is suitable for hip resurfacing [3]. Like any hip replacement procedure, the positioning of the femoral and acetabular components is critical to the long-term success of a hip resurfacing procedure [4]. The acetabular component must be positioned with appropriate anteversion and verticality for postoperative hip stability and avoidance of impingement. Excessive vertical positioning of the acetabular component can lead to increased contact stresses and rapid wear of the metal on metal bearing. The femoral component must also be positioned properly to ensure success. Neutral or slight valgus orientation is optimal. Varus positioning or notching of the cortex of the femoral neck, particularly on the tension side, can lead to femoral neck fracture [5,6]. Furthermore, the acetabular and femoral components can only match each other within select ranges. Because of the limitations the retained femoral head presents, the acetabular component must be implanted first. However, it is important to understand the femoral component sizes that can be matched to a particular acetabular component. Typically, each acetabu-lar component can be matched with only two femoral sizes. If the femur cannot accommodate these sizes, then the acetabular component size must be altered or the plan for hip resurfacing must be abandoned in favor of a total hip replacement construct. It is more difficult to change these parameters than in conventional total hip replacement, where a wider variety of stem and neck length options are possible. In addition, it is far easier and more efficient to plan for any alteration in the operative plan before undertaking an operative procedure. Finally, it is crucial to plan for the possibility of intraoperative conversion from hip resurfacing to total hip replacement. This may become necessary for several reasons. For example, if excessive femoral head cysts become evident, such that the stability of the femoral component comes into question, or if a technical error such as creation of a significant notch or fracture in the femoral neck occurs, then conversion to a total hip construct is necessary. This possibility should be planned for and discussed with the patient beforehand. The purpose of this chapter is to discuss the use of computer templating for preoperative planning of hip resurfacing arthroplasty.

Published
2009
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31. Superlattice growth and rearrangement during evaporation-induced nanoparticle self-assembly

Author

Elisabeth Josten, Erik Wetterskog, Artur Glavic, Peter Boesecke, Artem Feoktystov, Elke Brauweiler-Reuters, Ulrich Rücker, German Salazar-Alvarez, Thomas Brückel, and Lennart Bergström

Subjects
Medicine, Science
Abstract

Abstract Understanding the assembly of nanoparticles into superlattices with well-defined morphology and structure is technologically important but challenging as it requires novel combinations of in-situ methods with suitable spatial and temporal resolution. In this study, we have followed evaporation-induced assembly during drop casting of superparamagnetic, oleate-capped γ-Fe2O3 nanospheres dispersed in toluene in real time with Grazing Incidence Small Angle X-ray Scattering (GISAXS) in combination with droplet height measurements and direct observation of the dispersion. The scattering data was evaluated with a novel method that yielded time-dependent information of the relative ratio of ordered (coherent) and disordered particles (incoherent scattering intensities), superlattice tilt angles, lattice constants, and lattice constant distributions. We find that the onset of superlattice growth in the drying drop is associated with the movement of a drying front across the surface of the droplet. We couple the rapid formation of large, highly ordered superlattices to the capillary-induced fluid flow. Further evaporation of interstitital solvent results in a slow contraction of the superlattice. The distribution of lattice parameters and tilt angles was significantly larger for superlattices prepared by fast evaporation compared to slow evaporation of the solvent.

Published
2017
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