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2. A hospital demand and capacity intervention approach for COVID-19 in the UK

Author

Van Yperen, James, Campillo-Funollet, Eduard, Inkpen, Rebecca, Memon, Anjum, and Madzvamuse, Anotida

Subjects
Quantitative Biology - Populations and Evolution, Mathematics - General Mathematics, Physics - Physics and Society
Abstract

The mathematical interpretation of interventions for the mitigation of epidemics and pandemics in the literature often involves finding the optimal time to initiate an intervention and/or the use of infections to manage impact. Whilst these methods may work in theory, in order to implement they may require information which is likely not available whilst one is in the midst of an epidemic, or they may require impeccable data about infection levels in the community. In practice, testing and cases data is only as good as the policy of implementation and the compliance of the individuals, which means that understanding the levels of infections becomes difficult or complicated from the data that is provided. In this paper, we aim to develop a different approach to the mathematical modelling of interventions, not based on optimality, but based on demand and capacity of local authorities who have to deal with the epidemic on a day to day basis. In particular, we use data-driven modelling to calibrate an Susceptible Exposed Infectious Recovered-Died (SEIR-D) model to infer parameters that depict the dynamics of the epidemic in a region of the UK. We use the calibrated parameters for forecasting scenarios and understand, given a maximum capacity of hospital healthcare services, how the timing of interventions, severity of interventions, and conditions for the releasing of interventions affect the overall epidemic-picture.

Published
2020
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5. Suicide numbers during the first 9-15 months of the COVID-19 pandemic compared with pre-existing trends: An interrupted time series analysis in 33 countries

Author

Pirkis, Jane, Gunnell, David, Shin, Sangsoo, Del Pozo-Banos, Marcos, Arya, Vikas, Aguilar, Pablo Analuisa, Appleby, Louis, Arafat, S. M. Yasir, Arensman, Ella, Ayuso-Mateos, Jose Luis, Balhara, Yatan Pal Singh, Bantjes, Jason, Baran, Anna, Behera, Chittaranjan, Bertolote, Jose, Borges, Guilherme, Bray, Michael, Brečić, Petrana, Caine, Eric, Calati, Raffaella, Carli, Vladimir, Castelpietra, Giulio, Chan, Lai Fong, Chang, Shu-Sen, Colchester, David, Coss-Guzmán, Maria, Crompton, David, Ćurković, Marko, Dandona, Rakhi, De Jaegere, Eva, De Leo, Diego, Deisenhammer, Eberhard A., Dwyer, Jeremy, Erlangsen, Annette, Faust, Jeremy S., Fornaro, Michele, Fortune, Sarah, Garrett, Andrew, Gentile, Guendalina, Gerstner, Rebekka, Gilissen, Renske, Gould, Madelyn, Gupta, Sudhir Kumar, Hawton, Keith, Holz, Franziska, Kamenshchikov, Iurii, Kapur, Navneet, Kasal, Alexandr, Khan, Murad, Kirtley, Olivia J., Knipe, Duleeka, Kõlves, Kairi, Kölzer, Sarah C., Krivda, Hryhorii, Leske, Stuart, Madeddu, Fabio, Marshall, Andrew, Memon, Anjum, Mittendorfer-Rutz, Ellenor, Nestadt, Paul, Neznanov, Nikolay, Niederkrotenthaler, Thomas, Nielsen, Emma, Nordentoft, Merete, Oberlerchner, Herwig, O'Connor, Rory C., Papsdorf, Rainer, Partonen, Timo, Phillips, Michael R., Platt, Steve, Portzky, Gwendolyn, Psota, Georg, Qin, Ping, Radeloff, Daniel, Reif, Andreas, Reif-Leonhard, Christine, Rezaeian, Mohsen, Román-Vázquez, Nayda, Roskar, Saska, Rozanov, Vsevolod, Sara, Grant, Scavacini, Karen, Schneider, Barbara, Semenova, Natalia, Sinyor, Mark, Tambuzzi, Stefano, Townsend, Ellen, Ueda, Michiko, Wasserman, Danuta, Webb, Roger T., Winkler, Petr, Yip, Paul S.F., Zalsman, Gil, Zoja, Riccardo, John, Ann, and Spittal, Matthew J.

Published
2022
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6. Global, regional, and national consumption of animal-source foods between 1990 and 2018: findings from the Global Dietary Database

Author

Abbott, Pamela, Abdollahi, Morteza, Abedi, Parvin, Abumweis, Suhad, Adair, Linda, Al Nsour, Mohannad, Al-Daghri, Nasser, Al-Hamad, Nawal, Al-Hooti, Suad, Al-Zenki, Sameer, Alam, Iftikhar, Ali, Jemal H, Alissa, Eman, Anderson, Simon, Anzid, Karim, Arambepola, Carukshi, Arici, Mustafa, Arsenault, Joanne, Asciak, Renzo, Barbieri, Helene E, Barengo, Noël, Barquera, Simon, Bas, Murat, Becker, Wulf, Beer-Borst, Sigrid, Bergman, Per, Biró, Lajos, Boindala, Sesikeran, Bovet, Pascal, Bradshaw, Debbie, Bukhary, Noriklil BI, Bundhamcharoen, Kanitta, Caballero, Mauricio, Calleja, Neville, Cao, Xia, Capanzana, Mario, Carmikle, Jan, Castetbon, Katia, Castro, Michelle, Cerdena, Corazon, Chang, Hsing-Yi, Charlton, Karen, Chen, Yu, Chen, Mei F, Chiplonkar, Shashi, Cho, Yoonsu, Chuah, Khun-Aik, Costanzo, Simona, Cowan, Melanie, Damasceno, Albertino, Dastgiri, Saeed, De Henauw, Stefaan, DeRidder, Karin, Ding, Eric, Dommarco, Rivera, Don, Rokiah, Duante, Charmaine, Duleva, Vesselka, Duran Aguero, Samuel, Ekbote, Veena, El Ati, Jalila, El Hamdouchi, Asmaa, El-kour, Tatyana, Eldridge, Alison, Elmadfa, Ibrahim, Esteghamati, Alireza, Etemad, Zohreh, Fadzil, Fariza, Farzadfar, Farshad, Fernandez, Anne, Fernando, Dulitha, Fisberg, Regina, Forsyth, Simon, Gamboa-Delgado, Edna, Garriguet, Didier, Gaspoz, Jean-Michel, Gauci, Dorothy, Geleijnse, Marianne, Ginnela, Brahmam, Grosso, Giuseppe, Guessous, Idris, Gulliford, Martin, Gunnarsdottir, Ingibjorg, Hadden, Wilbur, Hadziomeragic, Aida, Haerpfer, Christian, Hakeem, Rubina, Haque, Aminul, Hashemian, Maryam, Hemalatha, Rajkumar, Henjum, Sigrun, Hinkov, Hristo, Hjdaud, Zaiton, Hoffman, Daniel, Hopping, Beth, Houshiar-rad, Anahita, Hsieh, Yao-Te, Hung, Shu-Yi, Huybrechts, Inge, Hwalla, Nahla C, Ibrahim, Hajah M, Ikeda, Nayu, Illescas-Zarate, Daniel, Inoue, Manami, Janakiram, Chandrashekar, Jayawardena, Ranil, Jeewon, Rajesh, Jitnarin, Nattinee, Johansson, Lars, Jonsdottir, Olof, Jundishapur, Ahvaz, Kally, Ola, Kandiah, Mirnalini, Karupaiah, Tilakavati, Keinan-Boker, Lital, Kelishadi, Roya, Khadilkar, Anuradha, Kim, Cho-il, Koksal, Eda, Konig, Jurgen, Korkalo, Liisa, Koster, Jeremy, Kovalskys, Irina, Krishnan, Anand, Kruger, Herculina, Kuriyan-Raj, Rebecca, Kweon, Sanghui, Lachat, Carl, Lai, Yuen, Lanerolle, Pulani, Laxmaiah, Avula, Leclercq, Catherine, Lee, Meei-Shyuan, Lee, Hae-Jeung, Lemming, Eva W, Li, Yanping, Lindström, Jaana, Ling, Annie, Liputo, Nur IL, Lopez-Jaramillo, Patricio, Luke, Amy, Lukito, Widjaja, Lupotto, Elisabette, Ma, Yi, Mahdy, Zaleha A, Malekzadeh, Reza, Manan, Wan, Marchioni, Dirce, Marques, Lydia L, Marques-Vidal, Pedro, Martin-Prevel, Yves, Mathee, Angie, Matsumura, Yasuhiro, Mazumdar, Paramita, Memon, Anjum, Mensink, Gert, Meyer, Alexa, Mirmiran, Parvin, Mirzaei, Masoud, Misra, Puneet, Misra, Anoop, Mitchell, Claudette, Mohamed, Hamid JBJ, Mohammadi-Nasrabadi, Fatemeh, Mohammadifard, Noushin, Moy, Foong M, Musaiger, Abdulrahman, Mwaniki, Elizabeth, Myhre, Jannicke, Nagalla, Balakrishna, Naska, Androniki, Ng, Swee A, Ng, Shu W, Ngoan, Le TN, Noshad, Sina, Ochoa, Angelica, Ocke, Marga, Odenkirk, Jillian, Oh, Kyungwon, Oleas, Mariana, Olivares, Sonia, Orfanos, Philippos, Ortiz-Ulloa, Johana, Otero, Johanna, Ovaskainen, Marja-Leena, Pakseresht, Mohammadreza, Palacios, Cristina, Palmer, Pam, Pan, Wen-Harn, Panagiotakos, Demosthenes, Parajuli, Rajendra, Park, Myungsook, Pekcan, Gulden, Petrova, Stefka, Piaseu, Noppawan, Pitsavos, Christos, Polasa, Kalpagam, Posada, Luz, Pourfarzi, Farhad, Preston, Alan M, Rached, Ingrid, Rahbar, Ali R, Rehm, Colin, Richter, Almut, Riley, Leanne, Salanave, Benoit, Sánchez-Romero, Luz M, Sarrafzadegan, Nizal, Sawada, Norie, Sekiyama, Makiko, Selamat, Rusidah, Shamsuddin, Khadijah, Shariff, Zalilah M, Sharma, Sangita, Sibai, Abla M, Sinkko, Harri, Sioen, Isabelle, Sisa, Ivan, Skeaff, Sheila, Steingrimsdottir, Laufey, Strand, Tor, Suarez-Ortegon, Milton F, Swaminathan, Sumathi, Swan, Gillian, Sygnowska, Elzbieta, Szabo, Maria, Szponar, Lucjan, Tan-Khouw, Ilse, Tapanainen, Heli, Tayyem, Reema, Tedla, Bemnet, Tedstone, Alison, Templeton, Robert, Termote, Celine, Thanopoulou, Anastasia, Thorgeirsdottir, Holmfridur, Thorsdottir, Inga, Trichopoulos, Dimitrios, Trichopoulou, Antonia, Tsugane, Shoichiro, Turrini, Aida, van Oosterhout, Coline, Vartiainen, Erkki, Veerman, J Lennert, Virtanen, Suvi, Vollenweider, Peter, Vossenaar, Marieke, Waidyatilaka, Indu, Waskiewicz, Anna, Waterham, Eveline, Wieler, Lothar, Wondwossen, Tizita, Wu, Suh, Yaakub, Roseyati, Yap, Mabel, Yusof, Safiah, Zaghloul, Sahar, Zajkás, Gábor, Zapata, Maria, Zarina, Khairul, Zohoori, Fatemeh V, Miller, Victoria, Reedy, Julia, Cudhea, Frederick, Zhang, Jianyi, Shi, Peilin, Erndt-Marino, Josh, Coates, Jennifer, Micha, Renata, Webb, Patrick, and Mozaffarian, Dariush

Published
2022
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12. Parallel operated hybrid Arithmetic-Salp swarm optimizer for optimal allocation of multiple distributed generation units in distribution networks

Author

Zeeshan Memon Anjum, Dalila Mat Said, Mohammad Yusri Hassan, Zohaib Hussain Leghari, and Gul Sahar

Subjects
Medicine, Science
Abstract

The installation of Distributed Generation (DG) units in the Radial Distribution Networks (RDNs) has significant potential to minimize active power losses in distribution networks. However, inaccurate size(s) and location(s) of DG units increase power losses and associated Annual Financial Losses (AFL). A comprehensive review of the literature reveals that existing analytical, metaheuristic and hybrid algorithms employed on DG allocation problems trap in local or global optima resulting in higher power losses. To address these limitations, this article develops a parallel hybrid Arithmetic Optimization Algorithm and Salp Swarm Algorithm (AOASSA) for the optimal sizing and placement of DGs in the RDNs. The proposed parallel hybrid AOASSA enables the mutual benefit of both algorithms, i.e., the exploration capability of the SSA and the exploitation capability of the AOA. The performance of the proposed algorithm has been analyzed against the hybrid Arithmetic Optimization Algorithm Particle Swarm Optimization (AOAPSO), Salp Swarm Algorithm Particle Swarm Optimization (SSAPSO), standard AOA, SSA, and Particle Swarm Optimization (PSO) algorithms. The results obtained reveals that the proposed algorithm produces quality solutions and minimum power losses in RDNs. The Power Loss Reduction (PLR) obtained with the proposed algorithm has also been validated against recent analytical, metaheuristic and hybrid optimization algorithms with the help of three cases based on the number of DG units allocated. Using the proposed algorithm, the PLR and associated AFL reduction of the 33-bus and 69-bus RDNs improved to 65.51% and 69.14%, respectively. This study will help the local distribution companies to minimize power losses and associated AFL in the long-term planning paradigm.

Published
2022

15. The Sussex COVID-19 Modelling Cell: the methods and successes of a collaboration between public health teams in local authorities, NHS hospital trusts, NHS commissioners, and universities

Author

Van Yperen, James, primary, Campillo-Funollet, Eduard, additional, Memon, Anjum, additional, Allman, Phil, additional, Clay, Jacqueline, additional, Dorey, Matt, additional, Evans, Graham, additional, Gilchrist, Kate, additional, and Madzvamuse, Anotida, additional

Published
2023
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19. A hospital demand and capacity intervention approach for COVID-19

Author

Ndeffo-Mbah, Martial L, Van Yperen, James, Campillo-Funollet, Eduard, Inkpen, Rebecca, Memon, Anjum, Madzvamuse, Anotida, Ndeffo-Mbah, Martial L, Van Yperen, James, Campillo-Funollet, Eduard, Inkpen, Rebecca, Memon, Anjum, and Madzvamuse, Anotida

Abstract

The mathematical interpretation of interventions for the mitigation of epidemics in the literature often involves finding the optimal time to initiate an intervention and/or the use of the number of infections to manage impact. Whilst these methods may work in theory, in order to implement effectively they may require information which is not likely to be available in the midst of an epidemic, or they may require impeccable data about infection levels in the community. In reality, testing and cases data can only be as good as the policy of implementation and the compliance of the individuals, which implies that accurately estimating the levels of infections becomes difficult or complicated from the data that is provided. In this paper, we demonstrate a different approach to the mathematical modelling of interventions, not based on optimality or cases, but based on demand and capacity of hospitals who have to deal with the epidemic on a day to day basis. In particular, we use data-driven modelling to calibrate a susceptible-exposed-infectious-recovered-died type model to infer parameters that depict the dynamics of the epidemic in several regions of the UK. We use the calibrated parameters for forecasting scenarios and understand, given a maximum capacity of hospital healthcare services, how the timing of interventions, severity of interventions, and conditions for the releasing of interventions affect the overall epidemic-picture. We provide an optimisation method to capture when, in terms of healthcare demand, an intervention should be put into place given a maximum capacity on the service. By using an equivalent agent-based approach, we demonstrate uncertainty quantification on the likelihood that capacity is not breached, by how much if it does, and the limit on demand that almost guarantees capacity is not breached.

Published
2023

20. Sugar-sweetened beverage intakes among adults between 1990 and 2018 in 185 countries

Author

Lara-Castor, Laura, Micha, Renata, Cudhea, Frederick, Miller, Victoria, Shi, Peilin, Zhang, Jianyi, Sharib, Julia R., Erndt-Marino, Josh, Cash, Sean B., Mozaffarian, Dariush, Bas, Murat, Ali, Jemal Haidar, Abumweis, Suhad, Krishnan, Anand, Misra, Puneet, Hwalla, Nahla Chawkat, Janakiram, Chandrashekar, Liputo, Nur Indrawaty, Musaiger, Abdulrahman, Pourfarzi, Farhad, Alam, Iftikhar, DeRidder, Karin, Termote, Celine, Memon, Anjum, Turrini, Aida, Lupotto, Elisabetta, Piccinelli, Raffaela, Sette, Stefania, Anzid, Karim, Vossenaar, Marieke, Mazumdar, Paramita, Rached, Ingrid, Rovirosa, Alicia, Zapata, María Elisa, Asayehu, Tamene Taye, Oduor, Francis, Boedecker, Julia, Aluso, Lilian, Ortiz-Ulloa, Johana, Meenakshi, J.V., Castro, Michelle, Grosso, Giuseppe, Waskiewicz, Anna, Khan, Umber S., Thanopoulou, Anastasia, Malekzadeh, Reza, Calleja, Neville, Ocke, Marga, Etemad, Zohreh, Nsour, Mohannad Al, Waswa, Lydiah M., Nurk, Eha, Arsenault, Joanne, Lopez-Jaramillo, Patricio, Sibai, Abla Mehio, Damasceno, Albertino, Arambepola, Carukshi, Lopes, Carla, Severo, Milton, Lunet, Nuno, Torres, Duarte, Tapanainen, Heli, Lindstrom, Jaana, Virtanen, Suvi, Palacios, Cristina, Roos, Eva, Agdeppa, Imelda Angeles, Desnacido, Josie, Capanzana, Mario, Misra, Anoop, Khouw, Ilse, Ng, Shu Wen, Delgado, Edna Gamboa, Caballero, Mauricio, Otero, Johanna, Lee, Hae Jeung, Koksal, Eda, Guessous, Idris, Lachat, Carl, De Henauw, Stefaan, Rahbar, Ali Reza, Tedstone, Alison, Naska, Androniki, Mathee, Angie, Ling, Annie, Tedla, Bemnet, Hopping, Beth, Ginnela, Brahmam, Leclercq, Catherine, Duante, Charmaine, Haerpfer, Christian, Hotz, Christine, Pitsavos, Christos, Rehm, Colin, van Oosterhout, Coline, Cerdena, Corazon, Bradshaw, Debbie, Trichopoulos, Dimitrios, Gauci, Dorothy, Fernando, Dulitha, Sygnowska, Elzbieta, Vartiainen, Erkki, Farzadfar, Farshad, Zajkas, Gabor, Swan, Gillian, Ma, Guansheng, Pekcan, Gulden, Ibrahim, Hajah Masni, Sinkko, Harri, Barbieri, Helene Enghardt, Sioen, Isabelle, Myhre, Jannicke, Gaspoz, Jean Michel, Odenkirk, Jillian, Bundhamcharoen, Kanitta, Nelis, Keiu, Zarina, Khairul, Biro, Lajos, Johansson, Lars, Steingrimsdottir, Laufey, Riley, Leanne, Yap, Mabel, Inoue, Manami, Szabo, Maria, Ovaskainen, Marja Leena, Lee, Meei Shyuan, Chan, Mei Fen, Cowan, Melanie, Kandiah, Mirnalini, Kally, Ola, Jonsdottir, Olof, Palmer, Pam, Vollenweider, Peter, Orfanos, Philippos, Asciak, Renzo, Templeton, Robert, Don, Rokiah, Yaakub, Roseyati, Selamat, Rusidah, Yusof, Safiah, Al-Zenki, Sameer, Hung, Shu Yi, Beer-Borst, Sigrid, Wu, Suh, Lukito, Widjaja, Hadden, Wilbur, Becker, Wulf, Cao, Xia, Ma, Yi, Lai, Yuen, Hjdaud, Zaiton, Ali, Jennifer, Gravel, Ron, Tao, Tina, Veerman, Jacob Lennert, Chiplonkar, Shashi, Arici, Mustafa, Ngoan, Le Tran, Panagiotakos, Demosthenes, Li, Yanping, Trichopoulou, Antonia, Barengo, Noel, Khadilkar, Anuradha, Ekbote, Veena, Mohammadifard, Noushin, Kovalskys, Irina, Laxmaiah, Avula, Rachakulla, Harikumar, Rajkumar, Hemalatha, Meshram, Indrapal, Avula, Laxmaiah, Arlappa, Nimmathota, Hemalatha, Rajkumar, Iacoviello, Licia, Bonaccio, Marialaura, Costanzo, Simona, Martin-Prevel, Yves, Castetbon, Katia, Jitnarin, Nattinee, Hsieh, Yao Te, Olivares, Sonia, Tejeda, Gabriela, Hadziomeragic, Aida, de Moura Souza, Amanda, Pan, Wen Harn, Huybrechts, Inge, de Brauw, Alan, Moursi, Mourad, Maghroun, Maryam, Zeba, Augustin Nawidimbasba, Sarrafzadegan, Nizal, Keinan-Boker, Lital, Goldsmith, Rebecca, Shimony, Tal, Jordan, Irmgard, Mastiholi, Shivanand C., Mwangi, Moses, Kombe, Yeri, Bukania, Zipporah, Alissa, Eman, Al-Daghri, Nasser, Sabico, Shaun, Gulliford, Martin, Diba, Tshilenge S., Oh, Kyungwon, Kweon, Sanghui, Park, Sihyun, Cho, Yoonsu, Al-Hooti, Suad, Luangphaxay, Chanthaly, Douangvichit, Daovieng, Siengsounthone, Latsamy, Marques-Vidal, Pedro, Rybak, Constance, Luke, Amy, Piaseu, Noppawan, Rojroongwasinkul, Nipa, Sundram, Kalyana, Koster, Jeremy, Baykova, Donka, Abedi, Parvin, Sandjaja, Sandjaja, Fadzil, Fariza, Bukhary, Noriklil Bukhary Ismail, Bovet, Pascal, Chen, Yu, Sawada, Norie, Tsugane, Shoichiro, Rangelova, Lalka, Petrova, Stefka, Duleva, Vesselka, Lindroos, Anna Karin, Sipinen, Jessica Petrelius, Moraeus, Lotta, Bergman, Per, Siamusantu, Ward, Szponar, Lucjan, Chang, Hsing Yi, Sekiyama, Makiko, Le Nguyen Bao, Khanh, Nagalla, Balakrishna, Polasa, Kalpagam, Boindala, Sesikeran, El Ati, Jalila, Silva, Ivonne Ramirez, Dommarco, Juan Rivera, Barquera, Simon, Rodríguez-Ramírez, Sonia, Illescas-Zarate, Daniel, Sanchez-Romero, Luz Maria, Ikeda, Nayu, Zaghloul, Sahar, Houshiar-rad, Anahita, Mohammadi-Nasrabadi, Fatemeh, Abdollahi, Morteza, Chuah, Khun Aik, Mahdy, Zaleha Abdullah, Eldridge, Alison, Ding, Eric L., Kruger, Herculina, Henjum, Sigrun, Fernandez, Anne, Suarez-Ortegon, Milton Fabian, Al-Hamad, Nawal, Janská, Veronika, Tayyem, Reema, Mirmiran, Parvin, Kelishadi, Roya, Lemming, Eva Warensjo, Richter, Almut, Mensink, Gert, Wieler, Lothar, Hoffman, Daniel, Salanave, Benoit, Il Kim, Cho, Kuriyan-Raj, Rebecca, Swaminathan, Sumathi, Garriguet, Didier, Dastgiri, Saeed, Vaask, Sirje, Karupaiah, Tilakavati, Zohoori, Fatemeh Vida, Esteghamati, Alireza, Hashemian, Maryam, Noshad, Sina, Mwaniki, Elizabeth, Yakes-Jimenez, Elizabeth, Chileshe, Justin, Mwanza, Sydney, Marques, Lydia Lera, Preston, Alan Martin, Aguero, Samuel Duran, Oleas, Mariana, Posada, Luz, Ochoa, Angelica, Shamsuddin, Khadijah, Shariff, Zalilah Mohd, Jan Bin Jan Mohamed, Hamid, Manan, Wan, Nicolau, Anca, Tudorie, Cornelia, Poh, Bee Koon, Abbott, Pamela, Pakseresht, Mohammadreza, Sharma, Sangita, Strand, Tor, Alexy, Ute, Nöthlings, Ute, Carmikle, Jan, Brown, Ken, Waidyatilaka, Indu, Lanerolle, Pulani, Jayawardena, Ranil, Long, Julie M., Hambidge, Michael, Krebs, Nancy F., Haque, Aminul, Keding, Gudrun B., Korkalo, Liisa, Erkkola, Maijaliisa, Freese, Riitta, Eleraky, Laila, Stuetz, Wolfgang, Thorsdottir, Inga, Gunnarsdottir, Ingibjorg, Serra-Majem, Lluis, Moy, Foong Ming, Anderson, Simon, Jeewon, Rajesh, Zugravu, Corina Aurelia, Adair, Linda, Skeaff, Sheila, Marchioni, Dirce, Fisberg, Regina, Henry, Carol, Ersino, Getahun, Zello, Gordon, Meyer, Alexa, Elmadfa, Ibrahim, Mitchell, Claudette, Balfour, David, Geleijnse, Johanna M., Manary, Mark, El-kour, Tatyana, Nikiema, Laetitia, Mirzaei, Masoud, Hakeem, Rubina, Lara-Castor, Laura, Micha, Renata, Cudhea, Frederick, Miller, Victoria, Shi, Peilin, Zhang, Jianyi, Sharib, Julia R., Erndt-Marino, Josh, Cash, Sean B., Mozaffarian, Dariush, Bas, Murat, Ali, Jemal Haidar, Abumweis, Suhad, Krishnan, Anand, Misra, Puneet, Hwalla, Nahla Chawkat, Janakiram, Chandrashekar, Liputo, Nur Indrawaty, Musaiger, Abdulrahman, Pourfarzi, Farhad, Alam, Iftikhar, DeRidder, Karin, Termote, Celine, Memon, Anjum, Turrini, Aida, Lupotto, Elisabetta, Piccinelli, Raffaela, Sette, Stefania, Anzid, Karim, Vossenaar, Marieke, Mazumdar, Paramita, Rached, Ingrid, Rovirosa, Alicia, Zapata, María Elisa, Asayehu, Tamene Taye, Oduor, Francis, Boedecker, Julia, Aluso, Lilian, Ortiz-Ulloa, Johana, Meenakshi, J.V., Castro, Michelle, Grosso, Giuseppe, Waskiewicz, Anna, Khan, Umber S., Thanopoulou, Anastasia, Malekzadeh, Reza, Calleja, Neville, Ocke, Marga, Etemad, Zohreh, Nsour, Mohannad Al, Waswa, Lydiah M., Nurk, Eha, Arsenault, Joanne, Lopez-Jaramillo, Patricio, Sibai, Abla Mehio, Damasceno, Albertino, Arambepola, Carukshi, Lopes, Carla, Severo, Milton, Lunet, Nuno, Torres, Duarte, Tapanainen, Heli, Lindstrom, Jaana, Virtanen, Suvi, Palacios, Cristina, Roos, Eva, Agdeppa, Imelda Angeles, Desnacido, Josie, Capanzana, Mario, Misra, Anoop, Khouw, Ilse, Ng, Shu Wen, Delgado, Edna Gamboa, Caballero, Mauricio, Otero, Johanna, Lee, Hae Jeung, Koksal, Eda, Guessous, Idris, Lachat, Carl, De Henauw, Stefaan, Rahbar, Ali Reza, Tedstone, Alison, Naska, Androniki, Mathee, Angie, Ling, Annie, Tedla, Bemnet, Hopping, Beth, Ginnela, Brahmam, Leclercq, Catherine, Duante, Charmaine, Haerpfer, Christian, Hotz, Christine, Pitsavos, Christos, Rehm, Colin, van Oosterhout, Coline, Cerdena, Corazon, Bradshaw, Debbie, Trichopoulos, Dimitrios, Gauci, Dorothy, Fernando, Dulitha, Sygnowska, Elzbieta, Vartiainen, Erkki, Farzadfar, Farshad, Zajkas, Gabor, Swan, Gillian, Ma, Guansheng, Pekcan, Gulden, Ibrahim, Hajah Masni, Sinkko, Harri, Barbieri, Helene Enghardt, Sioen, Isabelle, Myhre, Jannicke, Gaspoz, Jean Michel, Odenkirk, Jillian, Bundhamcharoen, Kanitta, Nelis, Keiu, Zarina, Khairul, Biro, Lajos, Johansson, Lars, Steingrimsdottir, Laufey, Riley, Leanne, Yap, Mabel, Inoue, Manami, Szabo, Maria, Ovaskainen, Marja Leena, Lee, Meei Shyuan, Chan, Mei Fen, Cowan, Melanie, Kandiah, Mirnalini, Kally, Ola, Jonsdottir, Olof, Palmer, Pam, Vollenweider, Peter, Orfanos, Philippos, Asciak, Renzo, Templeton, Robert, Don, Rokiah, Yaakub, Roseyati, Selamat, Rusidah, Yusof, Safiah, Al-Zenki, Sameer, Hung, Shu Yi, Beer-Borst, Sigrid, Wu, Suh, Lukito, Widjaja, Hadden, Wilbur, Becker, Wulf, Cao, Xia, Ma, Yi, Lai, Yuen, Hjdaud, Zaiton, Ali, Jennifer, Gravel, Ron, Tao, Tina, Veerman, Jacob Lennert, Chiplonkar, Shashi, Arici, Mustafa, Ngoan, Le Tran, Panagiotakos, Demosthenes, Li, Yanping, Trichopoulou, Antonia, Barengo, Noel, Khadilkar, Anuradha, Ekbote, Veena, Mohammadifard, Noushin, Kovalskys, Irina, Laxmaiah, Avula, Rachakulla, Harikumar, Rajkumar, Hemalatha, Meshram, Indrapal, Avula, Laxmaiah, Arlappa, Nimmathota, Hemalatha, Rajkumar, Iacoviello, Licia, Bonaccio, Marialaura, Costanzo, Simona, Martin-Prevel, Yves, Castetbon, Katia, Jitnarin, Nattinee, Hsieh, Yao Te, Olivares, Sonia, Tejeda, Gabriela, Hadziomeragic, Aida, de Moura Souza, Amanda, Pan, Wen Harn, Huybrechts, Inge, de Brauw, Alan, Moursi, Mourad, Maghroun, Maryam, Zeba, Augustin Nawidimbasba, Sarrafzadegan, Nizal, Keinan-Boker, Lital, Goldsmith, Rebecca, Shimony, Tal, Jordan, Irmgard, Mastiholi, Shivanand C., Mwangi, Moses, Kombe, Yeri, Bukania, Zipporah, Alissa, Eman, Al-Daghri, Nasser, Sabico, Shaun, Gulliford, Martin, Diba, Tshilenge S., Oh, Kyungwon, Kweon, Sanghui, Park, Sihyun, Cho, Yoonsu, Al-Hooti, Suad, Luangphaxay, Chanthaly, Douangvichit, Daovieng, Siengsounthone, Latsamy, Marques-Vidal, Pedro, Rybak, Constance, Luke, Amy, Piaseu, Noppawan, Rojroongwasinkul, Nipa, Sundram, Kalyana, Koster, Jeremy, Baykova, Donka, Abedi, Parvin, Sandjaja, Sandjaja, Fadzil, Fariza, Bukhary, Noriklil Bukhary Ismail, Bovet, Pascal, Chen, Yu, Sawada, Norie, Tsugane, Shoichiro, Rangelova, Lalka, Petrova, Stefka, Duleva, Vesselka, Lindroos, Anna Karin, Sipinen, Jessica Petrelius, Moraeus, Lotta, Bergman, Per, Siamusantu, Ward, Szponar, Lucjan, Chang, Hsing Yi, Sekiyama, Makiko, Le Nguyen Bao, Khanh, Nagalla, Balakrishna, Polasa, Kalpagam, Boindala, Sesikeran, El Ati, Jalila, Silva, Ivonne Ramirez, Dommarco, Juan Rivera, Barquera, Simon, Rodríguez-Ramírez, Sonia, Illescas-Zarate, Daniel, Sanchez-Romero, Luz Maria, Ikeda, Nayu, Zaghloul, Sahar, Houshiar-rad, Anahita, Mohammadi-Nasrabadi, Fatemeh, Abdollahi, Morteza, Chuah, Khun Aik, Mahdy, Zaleha Abdullah, Eldridge, Alison, Ding, Eric L., Kruger, Herculina, Henjum, Sigrun, Fernandez, Anne, Suarez-Ortegon, Milton Fabian, Al-Hamad, Nawal, Janská, Veronika, Tayyem, Reema, Mirmiran, Parvin, Kelishadi, Roya, Lemming, Eva Warensjo, Richter, Almut, Mensink, Gert, Wieler, Lothar, Hoffman, Daniel, Salanave, Benoit, Il Kim, Cho, Kuriyan-Raj, Rebecca, Swaminathan, Sumathi, Garriguet, Didier, Dastgiri, Saeed, Vaask, Sirje, Karupaiah, Tilakavati, Zohoori, Fatemeh Vida, Esteghamati, Alireza, Hashemian, Maryam, Noshad, Sina, Mwaniki, Elizabeth, Yakes-Jimenez, Elizabeth, Chileshe, Justin, Mwanza, Sydney, Marques, Lydia Lera, Preston, Alan Martin, Aguero, Samuel Duran, Oleas, Mariana, Posada, Luz, Ochoa, Angelica, Shamsuddin, Khadijah, Shariff, Zalilah Mohd, Jan Bin Jan Mohamed, Hamid, Manan, Wan, Nicolau, Anca, Tudorie, Cornelia, Poh, Bee Koon, Abbott, Pamela, Pakseresht, Mohammadreza, Sharma, Sangita, Strand, Tor, Alexy, Ute, Nöthlings, Ute, Carmikle, Jan, Brown, Ken, Waidyatilaka, Indu, Lanerolle, Pulani, Jayawardena, Ranil, Long, Julie M., Hambidge, Michael, Krebs, Nancy F., Haque, Aminul, Keding, Gudrun B., Korkalo, Liisa, Erkkola, Maijaliisa, Freese, Riitta, Eleraky, Laila, Stuetz, Wolfgang, Thorsdottir, Inga, Gunnarsdottir, Ingibjorg, Serra-Majem, Lluis, Moy, Foong Ming, Anderson, Simon, Jeewon, Rajesh, Zugravu, Corina Aurelia, Adair, Linda, Skeaff, Sheila, Marchioni, Dirce, Fisberg, Regina, Henry, Carol, Ersino, Getahun, Zello, Gordon, Meyer, Alexa, Elmadfa, Ibrahim, Mitchell, Claudette, Balfour, David, Geleijnse, Johanna M., Manary, Mark, El-kour, Tatyana, Nikiema, Laetitia, Mirzaei, Masoud, and Hakeem, Rubina

Abstract

Sugar-sweetened beverages (SSBs) are associated with cardiometabolic diseases and social inequities. For most nations, recent estimates and trends of intake are not available; nor variation by education or urbanicity. We investigated SSB intakes among adults between 1990 and 2018 in 185 countries, stratified subnationally by age, sex, education, and rural/urban residence, using data from the Global Dietary Database. In 2018, mean global SSB intake was 2.7 (8 oz = 248 grams) servings/week (95% UI 2.5-2.9) (range: 0.7 (0.5-1.1) in South Asia to 7.8 (7.1-8.6) in Latin America/Caribbean). Intakes were higher in male vs. female, younger vs. older, more vs. less educated, and urban vs. rural adults. Variations by education and urbanicity were largest in Sub-Saharan Africa. Between 1990 and 2018, SSB intakes increased by +0.37 (+0.29, +0.47), with the largest increase in Sub-Saharan Africa. These findings inform intervention, surveillance, and policy actions worldwide, highlighting the growing problem of SSBs for public health in Sub-Saharan Africa.

Published
2023

21. Incident type 2 diabetes attributable to suboptimal diet in 184 countries

Author

O’Hearn, Meghan, Lara-Castor, Laura, Cudhea, Frederick, Miller, Victoria, Reedy, Julia, Shi, Peilin, Zhang, Jianyi, Wong, John B., Economos, Christina D., Micha, Renata, Mozaffarian, Dariush, Bas, Murat, Ali, Jemal Haidar, Abumweis, Suhad, Krishnan, Anand, Misra, Puneet, Hwalla, Nahla Chawkat, Janakiram, Chandrashekar, Liputo, Nur Indrawaty, Musaiger, Abdulrahman, Pourfarzi, Farhad, Alam, Iftikhar, DeRidder, Karin, Termote, Celine, Memon, Anjum, Turrini, Aida, Lupotto, Elisabetta, Piccinelli, Raffaela, Sette, Stefania, Anzid, Karim, Vossenaar, Marieke, Mazumdar, Paramita, Rached, Ingrid, Rovirosa, Alicia, Zapata, María Elisa, Asayehu, Tamene Taye, Oduor, Francis, Boedecker, Julia, Aluso, Lilian, Ortiz-Ulloa, Johana, Meenakshi, J.V., Castro, Michelle, Grosso, Giuseppe, Waskiewicz, Anna, Khan, Umber S., Thanopoulou, Anastasia, Ocke, Marga, Ma, Guansheng, Chileshe, Justin, Geleijnse, Johanna M., O’Hearn, Meghan, Lara-Castor, Laura, Cudhea, Frederick, Miller, Victoria, Reedy, Julia, Shi, Peilin, Zhang, Jianyi, Wong, John B., Economos, Christina D., Micha, Renata, Mozaffarian, Dariush, Bas, Murat, Ali, Jemal Haidar, Abumweis, Suhad, Krishnan, Anand, Misra, Puneet, Hwalla, Nahla Chawkat, Janakiram, Chandrashekar, Liputo, Nur Indrawaty, Musaiger, Abdulrahman, Pourfarzi, Farhad, Alam, Iftikhar, DeRidder, Karin, Termote, Celine, Memon, Anjum, Turrini, Aida, Lupotto, Elisabetta, Piccinelli, Raffaela, Sette, Stefania, Anzid, Karim, Vossenaar, Marieke, Mazumdar, Paramita, Rached, Ingrid, Rovirosa, Alicia, Zapata, María Elisa, Asayehu, Tamene Taye, Oduor, Francis, Boedecker, Julia, Aluso, Lilian, Ortiz-Ulloa, Johana, Meenakshi, J.V., Castro, Michelle, Grosso, Giuseppe, Waskiewicz, Anna, Khan, Umber S., Thanopoulou, Anastasia, Ocke, Marga, Ma, Guansheng, Chileshe, Justin, and Geleijnse, Johanna M.

Abstract

The global burden of diet-attributable type 2 diabetes (T2D) is not well established. This risk assessment model estimated T2D incidence among adults attributable to direct and body weight-mediated effects of 11 dietary factors in 184 countries in 1990 and 2018. In 2018, suboptimal intake of these dietary factors was estimated to be attributable to 14.1 million (95% uncertainty interval (UI), 13.8–14.4 million) incident T2D cases, representing 70.3% (68.8–71.8%) of new cases globally. Largest T2D burdens were attributable to insufficient whole-grain intake (26.1% (25.0–27.1%)), excess refined rice and wheat intake (24.6% (22.3–27.2%)) and excess processed meat intake (20.3% (18.3–23.5%)). Across regions, highest proportional burdens were in central and eastern Europe and central Asia (85.6% (83.4–87.7%)) and Latin America and the Caribbean (81.8% (80.1–83.4%)); and lowest proportional burdens were in South Asia (55.4% (52.1–60.7%)). Proportions of diet-attributable T2D were generally larger in men than in women and were inversely correlated with age. Diet-attributable T2D was generally larger among urban versus rural residents and higher versus lower educated individuals, except in high-income countries, central and eastern Europe and central Asia, where burdens were larger in rural residents and in lower educated individuals. Compared with 1990, global diet-attributable T2D increased by 2.6 absolute percentage points (8.6 million more cases) in 2018, with variation in these trends by world region and dietary factor. These findings inform nutritional priorities and clinical and public health planning to improve dietary quality and reduce T2D globally.

Published
2023

22. Children’s and adolescents’ rising animal-source food intakes in 1990–2018 were impacted by age, region, parental education and urbanicity

Author

Miller, Victoria, Webb, Patrick, Cudhea, Frederick, Zhang, Jianyi, Reedy, Julia, Shi, Peilin, Erndt-Marino, Josh, Coates, Jennifer, Micha, Renata, Mozaffarian, Dariush, Bas, Murat, Ali, Jemal Haidar, Abumweis, Suhad, Krishnan, Anand, Misra, Puneet, Hwalla, Nahla Chawkat, Janakiram, Chandrashekar, Liputo, Nur Indrawaty, Musaiger, Abdulrahman, Pourfarzi, Farhad, Alam, Iftikhar, DeRidder, Karin, Termote, Celine, Memon, Anjum, Turrini, Aida, Lupotto, Elisabetta, Piccinelli, Raffaela, Sette, Stefania, Anzid, Karim, Vossenaar, Marieke, Mazumdar, Paramita, Rached, Ingrid, Rovirosa, Alicia, Zapata, María Elisa, Asayehu, Tamene Taye, Oduor, Francis, Boedecker, Julia, Aluso, Lilian, Ortiz-Ulloa, Johana, Meenakshi, J.V., Castro, Michelle, Grosso, Giuseppe, Waskiewicz, Anna, Khan, Umber S., Thanopoulou, Anastasia, Malekzadeh, Reza, Ocke, Marga, Geleijnse, Johanna M., Miller, Victoria, Webb, Patrick, Cudhea, Frederick, Zhang, Jianyi, Reedy, Julia, Shi, Peilin, Erndt-Marino, Josh, Coates, Jennifer, Micha, Renata, Mozaffarian, Dariush, Bas, Murat, Ali, Jemal Haidar, Abumweis, Suhad, Krishnan, Anand, Misra, Puneet, Hwalla, Nahla Chawkat, Janakiram, Chandrashekar, Liputo, Nur Indrawaty, Musaiger, Abdulrahman, Pourfarzi, Farhad, Alam, Iftikhar, DeRidder, Karin, Termote, Celine, Memon, Anjum, Turrini, Aida, Lupotto, Elisabetta, Piccinelli, Raffaela, Sette, Stefania, Anzid, Karim, Vossenaar, Marieke, Mazumdar, Paramita, Rached, Ingrid, Rovirosa, Alicia, Zapata, María Elisa, Asayehu, Tamene Taye, Oduor, Francis, Boedecker, Julia, Aluso, Lilian, Ortiz-Ulloa, Johana, Meenakshi, J.V., Castro, Michelle, Grosso, Giuseppe, Waskiewicz, Anna, Khan, Umber S., Thanopoulou, Anastasia, Malekzadeh, Reza, Ocke, Marga, and Geleijnse, Johanna M.

Abstract

Animal-source foods (ASF) provide nutrition for children and adolescents’ physical and cognitive development. Here, we use data from the Global Dietary Database and Bayesian hierarchical models to quantify global, regional and national ASF intakes between 1990 and 2018 by age group across 185 countries, representing 93% of the world’s child population. Mean ASF intake was 1.9 servings per day, representing 16% of children consuming at least three daily servings. Intake was similar between boys and girls, but higher among urban children with educated parents. Consumption varied by age from 0.6 at <1 year to 2.5 servings per day at 15–19 years. Between 1990 and 2018, mean ASF intake increased by 0.5 servings per week, with increases in all regions except sub-Saharan Africa. In 2018, total ASF consumption was highest in Russia, Brazil, Mexico and Turkey, and lowest in Uganda, India, Kenya and Bangladesh. These findings can inform policy to address malnutrition through targeted ASF consumption programmes.

Published
2023

23. The Contribution of Environmental Science to Mental Health Research: A Scoping Review

Author

Roberts, Michaela, Colley, Kathryn, Currie, Margaret, Eastwood, Antonia, Li, Kuang-Heng, Avery, Lisa M., Beevers, Lindsay C., Braithwaite, Isobel, Dallimer, Martin, Davies, Zoe G., Fisher, Helen L., Gidlow, Christopher J., Memon, Anjum, Mudway, Ian S., Naylor, Larissa A., Reis, Stefan, Smith, Pete, Stansfeld, Stephen A., Wilkie, Stephanie, Irvine, Katherine N., Roberts, Michaela, Colley, Kathryn, Currie, Margaret, Eastwood, Antonia, Li, Kuang-Heng, Avery, Lisa M., Beevers, Lindsay C., Braithwaite, Isobel, Dallimer, Martin, Davies, Zoe G., Fisher, Helen L., Gidlow, Christopher J., Memon, Anjum, Mudway, Ian S., Naylor, Larissa A., Reis, Stefan, Smith, Pete, Stansfeld, Stephen A., Wilkie, Stephanie, and Irvine, Katherine N.

Abstract

Mental health is influenced by multiple complex and interacting genetic, psychological, social, and environmental factors. As such, developing state-of-the-art mental health knowledge requires collaboration across academic disciplines, including environmental science. To assess the current contribution of environmental science to this field, a scoping review of the literature on environmental influences on mental health (including conditions of cognitive development and decline) was conducted. The review protocol was developed in consultation with experts working across mental health and environmental science. The scoping review included 202 English-language papers, published between 2010 and 2020 (prior to the COVID-19 pandemic), on environmental themes that had not already been the subject of recent systematic reviews; 26 reviews on climate change, flooding, air pollution, and urban green space were additionally considered. Studies largely focused on populations in the USA, China, or Europe and involved limited environmental science input. Environmental science research methods are primarily focused on quantitative approaches utilising secondary datasets or field data. Mental health measurement was dominated by the use of self-report psychometric scales. Measures of environmental states or exposures were often lacking in specificity (e.g., limited to the presence or absence of an environmental state). Based on the scoping review findings and our synthesis of the recent reviews, a research agenda for environmental science’s future contribution to mental health scholarship is set out. This includes recommendations to expand the geographical scope and broaden the representation of different environmental science areas, improve measurement of environmental exposure, prioritise experimental and longitudinal research designs, and giving greater consideration to variation between and within communities and the mediating pathways by which environment influences mental hea

Published
2023

24. Author Correction : Global dietary quality in 185 countries from 1990 to 2018 show wide differences by nation, age, education, and urbanicity

Author

Miller, Victoria, Webb, Patrick, Cudhea, Frederick, Shi, Peilin, Zhang, Jianyi, Reedy, Julia, Erndt-Marino, Josh, Coates, Jennifer, Mozaffarian, Dariush, Bas, Murat, Ali, Jemal Haidar, Abumweis, Suhad, Krishnan, Anand, Misra, Puneet, Hwalla, Nahla Chawkat, Janakiram, Chandrashekar, Liputo, Nur Indrawaty, Musaiger, Abdulrahman, Pourfarzi, Farhad, Alam, Iftikhar, DeRidder, Karin, Termote, Celine, Memon, Anjum, Turrini, Aida, Lupotto, Elisabetta, Piccinelli, Raffaela, Sette, Stefania, Anzid, Karim, Vossenaar, Marieke, Mazumdar, Paramita, Rached, Ingrid, Rovirosa, Alicia, Zapata, María Elisa, Asayehu, Tamene Taye, Oduor, Francis, Boedecker, Julia, Aluso, Lilian, Ortiz-Ulloa, Johana, Meenakshi, J.V., Castro, Michelle, Grosso, Giuseppe, Waskiewicz, Anna, Khan, Umber S., Thanopoulou, Anastasia, Malekzadeh, Reza, Calleja, Neville, Ocke, Marga, Ma, Guansheng, Chileshe, Justin, Geleijnse, Johanna M., Miller, Victoria, Webb, Patrick, Cudhea, Frederick, Shi, Peilin, Zhang, Jianyi, Reedy, Julia, Erndt-Marino, Josh, Coates, Jennifer, Mozaffarian, Dariush, Bas, Murat, Ali, Jemal Haidar, Abumweis, Suhad, Krishnan, Anand, Misra, Puneet, Hwalla, Nahla Chawkat, Janakiram, Chandrashekar, Liputo, Nur Indrawaty, Musaiger, Abdulrahman, Pourfarzi, Farhad, Alam, Iftikhar, DeRidder, Karin, Termote, Celine, Memon, Anjum, Turrini, Aida, Lupotto, Elisabetta, Piccinelli, Raffaela, Sette, Stefania, Anzid, Karim, Vossenaar, Marieke, Mazumdar, Paramita, Rached, Ingrid, Rovirosa, Alicia, Zapata, María Elisa, Asayehu, Tamene Taye, Oduor, Francis, Boedecker, Julia, Aluso, Lilian, Ortiz-Ulloa, Johana, Meenakshi, J.V., Castro, Michelle, Grosso, Giuseppe, Waskiewicz, Anna, Khan, Umber S., Thanopoulou, Anastasia, Malekzadeh, Reza, Calleja, Neville, Ocke, Marga, Ma, Guansheng, Chileshe, Justin, and Geleijnse, Johanna M.

Published
2023

27. The Contribution of Environmental Science to Mental Health Research: A Scoping Review

Author

Roberts, Michaela, primary, Colley, Kathryn, additional, Currie, Margaret, additional, Eastwood, Antonia, additional, Li, Kuang-Heng, additional, Avery, Lisa M., additional, Beevers, Lindsay C., additional, Braithwaite, Isobel, additional, Dallimer, Martin, additional, Davies, Zoe G., additional, Fisher, Helen L., additional, Gidlow, Christopher J., additional, Memon, Anjum, additional, Mudway, Ian S., additional, Naylor, Larissa A., additional, Reis, Stefan, additional, Smith, Pete, additional, Stansfeld, Stephen A., additional, Wilkie, Stephanie, additional, and Irvine, Katherine N., additional

Published
2023
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31. Health Promotion in Pre-Service Teacher Education: Effects of a Pilot Inter-Professional Curriculum Change

Author

Byrne, Jenny, Speller, Viv, Dewhirst, Sue, Roderick, Paul, Almond, Palo, Grace, Marcus, and Memon, Anjum

Abstract

Purpose: The purpose of this paper is to discuss a curriculum change in the provision of health promotion in pre-service teacher education in a one-year postgraduate certificate in education (PGCE) secondary course in one Higher Education Institution (HEI) in England. Design/methodology/approach: The paper describes the iterative development process, from an initial survey and mapping of the existing pre-service teacher training programme, which provided an evidence base for the piloting of a new health promotion component in the curriculum, and its subsequent evaluation. Changes to the health promotion element of the curriculum reflect the programme philosophy which balances the requirements of a competency based curriculum with a more liberal approach to education and training in which pre-service teachers are expected to critically reflect on, and evaluate their practice. This work adopts a socio-constructivist approach to teacher education, in which teachers develop their knowledge, skills and attitudes by interacting with others through dialogue, and learning from more knowledgeable others in a cooperative and scaffolded manner. Findings: The paper presents the results of these changes and discusses implications for their sustainability. The changes made to the health promotion component of the programme and their implementation would not have been possible without the inter-professional collaboration that took place over three years. Originality/value: To the authors' knowledge similar work involving a multi-disciplinary collaborative approach to the development of a health education component of a pre-service teacher education curriculum has not been employed or reported. (Contains 3 tables.)

Published
2012
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32. What Factors Are Important in Smoking Cessation Amongst Deprived Communities?: A Qualitative Study

Author

Henderson, Hazel J., Memon, Anjum, Lawson, Kate, Jacobs, Barbara, and Koutsogeorgou, Eleni

Abstract

Objective: There is limited evidence regarding effective smoking cessation interventions in deprived communities. This study explored what factors are considered most important in smoking cessation, from the perspective of a group of NHS Stop Smoking Service users from a deprived community. Design: A qualitative study. Setting: A deprived community in Brighton and Hove City, Southeast England. Methods: Fifteen adults who had used the local NHS Stop Smoking Service were recruited to the focus groups. Thematic analysis was used to identify key themes regarding factors that were considered most helpful during the smoking cessation attempt. Results: Factors deemed most important for a successful smoking cessation attempt were counsellors' attitude and knowledge, flexibility of appointments, personalized one-to-one support including additional support between sessions, all provided in an accessible local community setting. Individuals were most likely to decide to quit smoking for health reasons, and support from family and friends was important during the quit attempt. Conclusion: This study shows that smokers from deprived communities require more intensive, flexible and personalized support from a stop smoking service which should ideally be located in their community setting. A more innovative, tailored and less prescriptive approach to providing stop smoking services may help to improve cessation rates among smokers in deprived communities. (Contains 1 table.)

Published
2011
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33. Developing Trainee School Teachers' Expertise as Health Promoters

Author

Speller, Viv, Byrne, Jenny, Dewhirst, Sue, Almond, Palo, Mohebati, Lisa, Norman, Melanie, Polack, Sarah, Memon, Anjum, Grace, Marcus, Margetts, Barrie, and Roderick, Paul

Abstract

Purpose: The purpose of this paper is to report the outcome of an education and public health collaboration investigating the impact of adapted training to enhance teachers' potential role to promote child health and wellbeing. Design/methodology/approach: The study was conducted in three phases: a survey of the health education content in universities in initial teacher training courses; a longitudinal survey at the commencement and completion of courses to capture trainees' knowledge, skills and attitudes towards health and their role in health promotion; and mapping curriculum content against qualified teacher standards and public health competencies. Findings: Training about health varies largely between institutions. Trainees' knowledge levels remained low after training; ranked importance of key health topics--nutrition, alcohol, smoking,--decreased significantly; a majority thought that teachers and schools play an important role in health promotion, but significant increases were also noted in the minority who thought health promotion is not part of their remit (Phase 2). Originality/value: To the best of one's knowledge, similar work has not so far been reported. While teachers are in a prime position to influence child health, trainees require knowledge and skills to realise their public health potential. (Contains 5 tables and 1 figure.)

Published
2010
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38. Suicide numbers during the first 9-15 months of the COVID-19 pandemic compared with pre-existing trends:An interrupted time series analysis in 33 countries

Author

Pirkis, Jane, Gunnell, David, Shin, Sangsoo, Del Pozo-Banos, Marcos, Arya, Vikas, Aguilar, Pablo Analuisa, Appleby, Louis, Arafat, S. M. Yasir, Arensman, Ella, Ayuso-Mateos, Jose Luis, Balhara, Yatan Pal Singh, Bantjes, Jason, Baran, Anna, Behera, Chittaranjan, Bertolote, Jose, Borges, Guilherme, Bray, Michael, Brečić, Petrana, Caine, Eric, Calati, Raffaella, Carli, Vladimir, Castelpietra, Giulio, Chan, Lai Fong, Chang, Shu-Sen, Colchester, David, Coss-Guzmán, Maria, Crompton, David, Ćurković, Marko, Dandona, Rakhi, De Jaegere, Eva, De Leo, Diego, Deisenhammer, Eberhard A., Dwyer, Jeremy, Erlangsen, Annette, Faust, Jeremy S., Fornaro, Michele, Fortune, Sarah, Garrett, Andrew, Gentile, Guendalina, Gerstner, Rebekka, Gilissen, Renske, Gould, Madelyn, Gupta, Sudhir Kumar, Hawton, Keith, Holz, Franziska, Kamenshchikov, Iurii, Kapur, Navneet, Kasal, Alexandr, Khan, Murad, Kirtley, Olivia J., Knipe, Duleeka, Kõlves, Kairi, Kölzer, Sarah C., Krivda, Hryhorii, Leske, Stuart, Madeddu, Fabio, Marshall, Andrew, Memon, Anjum, Mittendorfer-Rutz, Ellenor, Nestadt, Paul, Neznanov, Nikolay, Niederkrotenthaler, Thomas, Nielsen, Emma, Nordentoft, Merete, Oberlerchner, Herwig, O'Connor, Rory C., Papsdorf, Rainer, Partonen, Timo, Phillips, Michael R, Platt, Steve, Portzky, Gwendolyn, Psota, Georg, Qin, Ping, Radeloff, Daniel, Reif, Andreas, Reif-Leonhard, Christine, Rezaeian, Mohsen, Román-Vázquez, Nayda, Roskar, Saska, Rozanov, Vsevolod, Sara, Grant, Scavacini, Karen, Schneider, Barbara, Semenova, Natalia, Sinyor, Mark, Tambuzzi, Stefano, Townsend, Ellen, Ueda, Michiko, Wasserman, Danuta, Webb, Roger T, Winkler, Petr, Yip, Paul S. F., Zalsman, Gil, Zoja, Riccardo, John, Ann, Spittal, Matthew J., Pirkis, Jane, Gunnell, David, Shin, Sangsoo, Del Pozo-Banos, Marcos, Arya, Vikas, Aguilar, Pablo Analuisa, Appleby, Louis, Arafat, S. M. Yasir, Arensman, Ella, Ayuso-Mateos, Jose Luis, Balhara, Yatan Pal Singh, Bantjes, Jason, Baran, Anna, Behera, Chittaranjan, Bertolote, Jose, Borges, Guilherme, Bray, Michael, Brečić, Petrana, Caine, Eric, Calati, Raffaella, Carli, Vladimir, Castelpietra, Giulio, Chan, Lai Fong, Chang, Shu-Sen, Colchester, David, Coss-Guzmán, Maria, Crompton, David, Ćurković, Marko, Dandona, Rakhi, De Jaegere, Eva, De Leo, Diego, Deisenhammer, Eberhard A., Dwyer, Jeremy, Erlangsen, Annette, Faust, Jeremy S., Fornaro, Michele, Fortune, Sarah, Garrett, Andrew, Gentile, Guendalina, Gerstner, Rebekka, Gilissen, Renske, Gould, Madelyn, Gupta, Sudhir Kumar, Hawton, Keith, Holz, Franziska, Kamenshchikov, Iurii, Kapur, Navneet, Kasal, Alexandr, Khan, Murad, Kirtley, Olivia J., Knipe, Duleeka, Kõlves, Kairi, Kölzer, Sarah C., Krivda, Hryhorii, Leske, Stuart, Madeddu, Fabio, Marshall, Andrew, Memon, Anjum, Mittendorfer-Rutz, Ellenor, Nestadt, Paul, Neznanov, Nikolay, Niederkrotenthaler, Thomas, Nielsen, Emma, Nordentoft, Merete, Oberlerchner, Herwig, O'Connor, Rory C., Papsdorf, Rainer, Partonen, Timo, Phillips, Michael R, Platt, Steve, Portzky, Gwendolyn, Psota, Georg, Qin, Ping, Radeloff, Daniel, Reif, Andreas, Reif-Leonhard, Christine, Rezaeian, Mohsen, Román-Vázquez, Nayda, Roskar, Saska, Rozanov, Vsevolod, Sara, Grant, Scavacini, Karen, Schneider, Barbara, Semenova, Natalia, Sinyor, Mark, Tambuzzi, Stefano, Townsend, Ellen, Ueda, Michiko, Wasserman, Danuta, Webb, Roger T, Winkler, Petr, Yip, Paul S. F., Zalsman, Gil, Zoja, Riccardo, John, Ann, and Spittal, Matthew J.

Abstract

Background: Predicted increases in suicide were not generally observed in the early months of the COVID-19 pandemic. However, the picture may be changing and patterns might vary across demographic groups. We aimed to provide a timely, granular picture of the pandemic's impact on suicides globally. Methods: We identified suicide data from official public-sector sources for countries/areas-within-countries, searching websites and academic literature and contacting data custodians and authors as necessary. We sent our first data request on 22nd June 2021 and stopped collecting data on 31st October 2021. We used interrupted time series (ITS) analyses to model the association between the pandemic's emergence and total suicides and suicides by sex-, age- and sex-by-age in each country/area-within-country. We compared the observed and expected numbers of suicides in the pandemic's first nine and first 10-15 months and used meta-regression to explore sources of variation. Findings: We sourced data from 33 countries (24 high-income, six upper-middle-income, three lower-middle-income; 25 with whole-country data, 12 with data for area(s)-within-the-country, four with both). There was no evidence of greater-than-expected numbers of suicides in the majority of countries/areas-within-countries in any analysis; more commonly, there was evidence of lower-than-expected numbers. Certain sex, age and sex-by-age groups stood out as potentially concerning, but these were not consistent across countries/areas-within-countries. In the meta-regression, different patterns were not explained by countries’ COVID-19 mortality rate, stringency of public health response, economic support level, or presence of a national suicide prevention strategy. Nor were they explained by countries’ income level, although the meta-regression only included data from high-income and upper-middle-income countries, and there were suggestions from the ITS analyses that lower-middle-income countries fared less w

Published
2022

40. Global, regional, and national consumption of animal-source foods between 1990 and 2018: findings from the Global Dietary Database

Author

Miller, Victoria, primary, Reedy, Julia, additional, Cudhea, Frederick, additional, Zhang, Jianyi, additional, Shi, Peilin, additional, Erndt-Marino, Josh, additional, Coates, Jennifer, additional, Micha, Renata, additional, Webb, Patrick, additional, Mozaffarian, Dariush, additional, Abbott, Pamela, additional, Abdollahi, Morteza, additional, Abedi, Parvin, additional, Abumweis, Suhad, additional, Adair, Linda, additional, Al Nsour, Mohannad, additional, Al-Daghri, Nasser, additional, Al-Hamad, Nawal, additional, Al-Hooti, Suad, additional, Al-Zenki, Sameer, additional, Alam, Iftikhar, additional, Ali, Jemal H, additional, Alissa, Eman, additional, Anderson, Simon, additional, Anzid, Karim, additional, Arambepola, Carukshi, additional, Arici, Mustafa, additional, Arsenault, Joanne, additional, Asciak, Renzo, additional, Barbieri, Helene E, additional, Barengo, Noël, additional, Barquera, Simon, additional, Bas, Murat, additional, Becker, Wulf, additional, Beer-Borst, Sigrid, additional, Bergman, Per, additional, Biró, Lajos, additional, Boindala, Sesikeran, additional, Bovet, Pascal, additional, Bradshaw, Debbie, additional, Bukhary, Noriklil BI, additional, Bundhamcharoen, Kanitta, additional, Caballero, Mauricio, additional, Calleja, Neville, additional, Cao, Xia, additional, Capanzana, Mario, additional, Carmikle, Jan, additional, Castetbon, Katia, additional, Castro, Michelle, additional, Cerdena, Corazon, additional, Chang, Hsing-Yi, additional, Charlton, Karen, additional, Chen, Yu, additional, Chen, Mei F, additional, Chiplonkar, Shashi, additional, Cho, Yoonsu, additional, Chuah, Khun-Aik, additional, Costanzo, Simona, additional, Cowan, Melanie, additional, Damasceno, Albertino, additional, Dastgiri, Saeed, additional, De Henauw, Stefaan, additional, DeRidder, Karin, additional, Ding, Eric, additional, Dommarco, Rivera, additional, Don, Rokiah, additional, Duante, Charmaine, additional, Duleva, Vesselka, additional, Duran Aguero, Samuel, additional, Ekbote, Veena, additional, El Ati, Jalila, additional, El Hamdouchi, Asmaa, additional, El-kour, Tatyana, additional, Eldridge, Alison, additional, Elmadfa, Ibrahim, additional, Esteghamati, Alireza, additional, Etemad, Zohreh, additional, Fadzil, Fariza, additional, Farzadfar, Farshad, additional, Fernandez, Anne, additional, Fernando, Dulitha, additional, Fisberg, Regina, additional, Forsyth, Simon, additional, Gamboa-Delgado, Edna, additional, Garriguet, Didier, additional, Gaspoz, Jean-Michel, additional, Gauci, Dorothy, additional, Geleijnse, Marianne, additional, Ginnela, Brahmam, additional, Grosso, Giuseppe, additional, Guessous, Idris, additional, Gulliford, Martin, additional, Gunnarsdottir, Ingibjorg, additional, Hadden, Wilbur, additional, Hadziomeragic, Aida, additional, Haerpfer, Christian, additional, Hakeem, Rubina, additional, Haque, Aminul, additional, Hashemian, Maryam, additional, Hemalatha, Rajkumar, additional, Henjum, Sigrun, additional, Hinkov, Hristo, additional, Hjdaud, Zaiton, additional, Hoffman, Daniel, additional, Hopping, Beth, additional, Houshiar-rad, Anahita, additional, Hsieh, Yao-Te, additional, Hung, Shu-Yi, additional, Huybrechts, Inge, additional, Hwalla, Nahla C, additional, Ibrahim, Hajah M, additional, Ikeda, Nayu, additional, Illescas-Zarate, Daniel, additional, Inoue, Manami, additional, Janakiram, Chandrashekar, additional, Jayawardena, Ranil, additional, Jeewon, Rajesh, additional, Jitnarin, Nattinee, additional, Johansson, Lars, additional, Jonsdottir, Olof, additional, Jundishapur, Ahvaz, additional, Kally, Ola, additional, Kandiah, Mirnalini, additional, Karupaiah, Tilakavati, additional, Keinan-Boker, Lital, additional, Kelishadi, Roya, additional, Khadilkar, Anuradha, additional, Kim, Cho-il, additional, Koksal, Eda, additional, Konig, Jurgen, additional, Korkalo, Liisa, additional, Koster, Jeremy, additional, Kovalskys, Irina, additional, Krishnan, Anand, additional, Kruger, Herculina, additional, Kuriyan-Raj, Rebecca, additional, Kweon, Sanghui, additional, Lachat, Carl, additional, Lai, Yuen, additional, Lanerolle, Pulani, additional, Laxmaiah, Avula, additional, Leclercq, Catherine, additional, Lee, Meei-Shyuan, additional, Lee, Hae-Jeung, additional, Lemming, Eva W, additional, Li, Yanping, additional, Lindström, Jaana, additional, Ling, Annie, additional, Liputo, Nur IL, additional, Lopez-Jaramillo, Patricio, additional, Luke, Amy, additional, Lukito, Widjaja, additional, Lupotto, Elisabette, additional, Ma, Yi, additional, Mahdy, Zaleha A, additional, Malekzadeh, Reza, additional, Manan, Wan, additional, Marchioni, Dirce, additional, Marques, Lydia L, additional, Marques-Vidal, Pedro, additional, Martin-Prevel,, Yves, additional, Mathee, Angie, additional, Matsumura, Yasuhiro, additional, Mazumdar, Paramita, additional, Memon, Anjum, additional, Mensink, Gert, additional, Meyer, Alexa, additional, Mirmiran, Parvin, additional, Mirzaei, Masoud, additional, Misra, Puneet, additional, Misra, Anoop, additional, Mitchell, Claudette, additional, Mohamed, Hamid JBJ, additional, Mohammadi-Nasrabadi, Fatemeh, additional, Mohammadifard, Noushin, additional, Moy, Foong M, additional, Musaiger, Abdulrahman, additional, Mwaniki, Elizabeth, additional, Myhre, Jannicke, additional, Nagalla, Balakrishna, additional, Naska, Androniki, additional, Ng, Swee A, additional, Ng, Shu W, additional, Ngoan, Le TN, additional, Noshad, Sina, additional, Ochoa, Angelica, additional, Ocke, Marga, additional, Odenkirk, Jillian, additional, Oh, Kyungwon, additional, Oleas, Mariana, additional, Olivares, Sonia, additional, Orfanos, Philippos, additional, Ortiz-Ulloa, Johana, additional, Otero, Johanna, additional, Ovaskainen, Marja-Leena, additional, Pakseresht, Mohammadreza, additional, Palacios, Cristina, additional, Palmer, Pam, additional, Pan, Wen-Harn, additional, Panagiotakos, Demosthenes, additional, Parajuli, Rajendra, additional, Park, Myungsook, additional, Pekcan, Gulden, additional, Petrova, Stefka, additional, Piaseu, Noppawan, additional, Pitsavos, Christos, additional, Polasa, Kalpagam, additional, Posada, Luz, additional, Pourfarzi, Farhad, additional, Preston, Alan M, additional, Rached, Ingrid, additional, Rahbar, Ali R, additional, Rehm, Colin, additional, Richter, Almut, additional, Riley, Leanne, additional, Salanave, Benoit, additional, Sánchez-Romero, Luz M, additional, Sarrafzadegan, Nizal, additional, Sawada, Norie, additional, Sekiyama, Makiko, additional, Selamat, Rusidah, additional, Shamsuddin, Khadijah, additional, Shariff, Zalilah M, additional, Sharma, Sangita, additional, Sibai, Abla M, additional, Sinkko, Harri, additional, Sioen, Isabelle, additional, Sisa, Ivan, additional, Skeaff, Sheila, additional, Steingrimsdottir, Laufey, additional, Strand, Tor, additional, Suarez-Ortegon, Milton F, additional, Swaminathan, Sumathi, additional, Swan, Gillian, additional, Sygnowska, Elzbieta, additional, Szabo, Maria, additional, Szponar, Lucjan, additional, Tan-Khouw, Ilse, additional, Tapanainen, Heli, additional, Tayyem, Reema, additional, Tedla, Bemnet, additional, Tedstone, Alison, additional, Templeton, Robert, additional, Termote, Celine, additional, Thanopoulou, Anastasia, additional, Thorgeirsdottir, Holmfridur, additional, Thorsdottir, Inga, additional, Trichopoulos, Dimitrios, additional, Trichopoulou, Antonia, additional, Tsugane, Shoichiro, additional, Turrini, Aida, additional, van Oosterhout, Coline, additional, Vartiainen, Erkki, additional, Veerman, J Lennert, additional, Virtanen, Suvi, additional, Vollenweider, Peter, additional, Vossenaar, Marieke, additional, Waidyatilaka, Indu, additional, Waskiewicz, Anna, additional, Waterham, Eveline, additional, Wieler, Lothar, additional, Wondwossen, Tizita, additional, Wu, Suh, additional, Yaakub, Roseyati, additional, Yap, Mabel, additional, Yusof, Safiah, additional, Zaghloul, Sahar, additional, Zajkás, Gábor, additional, Zapata, Maria, additional, Zarina, Khairul, additional, and Zohoori, Fatemeh V, additional

Published
2022
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41. Did Suicide Numbers Diverge from Pre-Existing Trends During the First 9-15 Months of the COVID-19 Pandemic? Interrupted Time Series Analyses of Total and Sex- and Age-Specific Suicide Counts in 33 Countries

Author

Pirkis, Jane, primary, Gunnell, David, additional, Shin, Sangsoo, additional, DelPozo-Banos, Marcos, additional, Arya, Vikas, additional, Analuisa Aguilar, Pablo, additional, Appleby, Louis, additional, Arafat, S.M. Yasir, additional, Arensman, Ella, additional, Ayuso-Mateos, Jose Luis, additional, Balhara, Yatan Pal Singh, additional, Bantjes, Jason, additional, Baran, Anna, additional, Behera, Chittaranjan, additional, Bertolote, Jose, additional, Borges, Guilherme, additional, Bray, Michael, additional, Brečić, Petrana, additional, Caine, Eric D., additional, Calati, Raffaella, additional, Carli, Vladimir, additional, Castelpietra, Giulio, additional, Chan, Lai Fong, additional, Chang, Shu-Sen, additional, Colchester, David, additional, Coss-Guzmán, Maria, additional, Crompton, David, additional, Curkovic, Marko, additional, Dandona, Rakhi, additional, De Jaegere, Eva, additional, De Leo, Diego, additional, Deisenhammer, Eberhard, additional, Dwyer, Jeremy, additional, Erlangsen, Annette, additional, Faust, Jeremy, additional, Fornaro, Michele, additional, Fortune, Sarah, additional, Garrett, Andrew, additional, Gentile, Guendalina, additional, Gerstner, Rebekka, additional, Gilissen, Renske, additional, Gould, Madelyn, additional, Gupta, Sudhir Kumar, additional, Hawton, Keith, additional, Holz, Franziska, additional, Kamenshchikov, Iurii, additional, Kapur, Navneet, additional, Kasal, Alexandr, additional, Khan, Murad, additional, Kirtley, Olivia, additional, Knipe, Duleeka, additional, Kolves, Kairi, additional, Kölzer, Sarah, additional, Krivda, Hryhorii, additional, Leske, Stuart, additional, Madeddu, Fabio, additional, Marshall, Andrew, additional, Memon, Anjum, additional, Mittendorfer-Rutz, Ellenor, additional, Nestadt, Paul, additional, Neznanov, Nikolay, additional, Niederkrotenthaler, Thomas, additional, Nielsen, Emma, additional, Nordentoft, Merete, additional, Oberlerchner, Herwig, additional, O&apos;Connor, Rory, additional, Papsdorf, Rainer, additional, Partonen, Timo, additional, Michael, Phillips, additional, Platt, Steve, additional, Portzky, Gwendolyn, additional, Psota, Georg, additional, Qin, Ping, additional, Radeloff, Daniel, additional, Reif, Andreas, additional, Reif-Leonhard, Christine, additional, Rezaeian, Mohsen, additional, Román-Vázquez, Nayda, additional, Roskar, Saska, additional, Rozanov, Vsevolod, additional, Sara, Grant, additional, Scavacini, Karen, additional, Schneider, Barbara, additional, Semenova, Natalia, additional, Sinyor, Mark, additional, Tambuzzi, Stefano, additional, Townsend, Ellen, additional, Ueda, Michiko, additional, Wasserman, Danuta, additional, Webb, Roger T., additional, Winkler, Petr, additional, Yip, Paul S. F., additional, Zalsman, Gil, additional, Zoja, Riccardo, additional, John, Ann, additional, and Spittal, Matthew J., additional

Published
2022
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43. Parallel operated hybrid Arithmetic-Salp swarm optimizer for optimal allocation of multiple distributed generation units in distribution networks

Author

Zeeshan Memon Anjum, Dalila Mat Said, Mohammad Yusri Hassan, Zohaib Hussain Leghari, and Gul Sahar

Subjects
Multidisciplinary, Algorithms
Abstract

The installation of Distributed Generation (DG) units in the Radial Distribution Networks (RDNs) has significant potential to minimize active power losses in distribution networks. However, inaccurate size(s) and location(s) of DG units increase power losses and associated Annual Financial Losses (AFL). A comprehensive review of the literature reveals that existing analytical, metaheuristic and hybrid algorithms employed on DG allocation problems trap in local or global optima resulting in higher power losses. To address these limitations, this article develops a parallel hybrid Arithmetic Optimization Algorithm and Salp Swarm Algorithm (AOASSA) for the optimal sizing and placement of DGs in the RDNs. The proposed parallel hybrid AOASSA enables the mutual benefit of both algorithms, i.e., the exploration capability of the SSA and the exploitation capability of the AOA. The performance of the proposed algorithm has been analyzed against the hybrid Arithmetic Optimization Algorithm Particle Swarm Optimization (AOAPSO), Salp Swarm Algorithm Particle Swarm Optimization (SSAPSO), standard AOA, SSA, and Particle Swarm Optimization (PSO) algorithms. The results obtained reveals that the proposed algorithm produces quality solutions and minimum power losses in RDNs. The Power Loss Reduction (PLR) obtained with the proposed algorithm has also been validated against recent analytical, metaheuristic and hybrid optimization algorithms with the help of three cases based on the number of DG units allocated. Using the proposed algorithm, the PLR and associated AFL reduction of the 33-bus and 69-bus RDNs improved to 65.51% and 69.14%, respectively. This study will help the local distribution companies to minimize power losses and associated AFL in the long-term planning paradigm.

Published
2021

46. Predicting and forecasting the impact of local outbreaks of COVID-19: use of SEIR-D quantitative epidemiological modelling for healthcare demand and capacity

Author

Campillo-Funollet, Eduard, primary, Van Yperen, James, additional, Allman, Phil, additional, Bell, Michael, additional, Beresford, Warren, additional, Clay, Jacqueline, additional, Dorey, Matthew, additional, Evans, Graham, additional, Gilchrist, Kate, additional, Memon, Anjum, additional, Pannu, Gurprit, additional, Walkley, Ryan, additional, Watson, Mark, additional, and Madzvamuse, Anotida, additional

Published
2021
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48. Predicting and forecasting the impact of local outbreaks of COVID-19: use of SEIR-D quantitative epidemiological modelling for healthcare demand and capacity

Author

Campillo-Funollet, Eduard, Yperen, James Van, Allman, Phil, Bell, Michael, Beresford, Warren, Clay, Jacqueline, Dorey, Matthew, Evans, Graham, Gilchrist, Kate, Memon, Anjum, Pannu, Gurprit, Walkley, Ryan, Watson, Mark, Madzvamuse, Anotida, Campillo-Funollet, Eduard, Yperen, James Van, Allman, Phil, Bell, Michael, Beresford, Warren, Clay, Jacqueline, Dorey, Matthew, Evans, Graham, Gilchrist, Kate, Memon, Anjum, Pannu, Gurprit, Walkley, Ryan, Watson, Mark, and Madzvamuse, Anotida

Abstract

BACKGROUND: The world is experiencing local/regional hotspots and spikes in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19 disease. We aimed to formulate an applicable epidemiological model to accurately predict and forecast the impact of local outbreaks of COVID-19 to guide the local healthcare demand and capacity, policy-making and public health decisions. METHODS: The model utilized the aggregated daily COVID-19 situation reports (including counts of daily admissions, discharges and bed occupancy) from the local National Health Service (NHS) hospitals and COVID-19-related weekly deaths in hospitals and other settings in Sussex (population 1.7 million), Southeast England. These data sets corresponded to the first wave of COVID-19 infections from 24 March to 15 June 2020. A novel epidemiological predictive and forecasting model was then derived based on the local/regional surveillance data. Through a rigorous inverse parameter inference approach, the model parameters were estimated by fitting the model to the data in an optimal sense and then subsequent validation. RESULTS: The inferred parameters were physically reasonable and matched up to the widely used parameter values derived from the national data sets by Biggerstaff M, Cowling BJ, Cucunubá ZM et al. (Early insights from statistical and mathematical modeling of key epidemiologic parameters of COVID-19, Emerging infectious diseases. 2020;26(11)). We validate the predictive power of our model by using a subset of the available data and comparing the model predictions for the next 10, 20 and 30 days. The model exhibits a high accuracy in the prediction, even when using only as few as 20 data points for the fitting. CONCLUSIONS: We have demonstrated that by using local/regional data, our predictive and forecasting model can be utilized to guide the local healthcare demand and capacity, policy-making and public health decisions to mitigate the impact of COVID-19 on the loc

Published
2021

49. Feasibility of a randomised controlled trial to evaluate home-based virtual reality therapy in children with cerebral palsy

Author

Farr, William J., Green, Dido, Bremner, Stephen, Male, Ian, Gage, Heather, Bailey, Sarah, Speller, Sandra, Colville, Valerie, Jackson, Mandy, Memon, Anjum, Morris, Christopher, Farr, William J., Green, Dido, Bremner, Stephen, Male, Ian, Gage, Heather, Bailey, Sarah, Speller, Sandra, Colville, Valerie, Jackson, Mandy, Memon, Anjum, and Morris, Christopher

Abstract

Purpose: Evidence is increasing for effective virtual reality therapy for motor rehabilitation for children with Cerebral Palsy. We assessed the feasibility of a virtual reality therapy mode of intervention, appropriateness of measures, and potential cost-effectiveness. Methods: A 12-week, 2-group, parallel-feasibility trial (ISRCT 17624388) using Nintendo Wii FitTM at home. Children aged 5–16, with ambulatory Cerebral Palsy, who were able to follow simple instructions were randomised to two groups; one supported by physiotherapists (individualised activity programme), the other unsupported with children having free choice (control). Children were assessed in clinic at baseline, week 6, and week 12 by blinded assessors. Feasibility of the intervention was assessed via recruitment, adherence, and usefulness of measurement tools. Results: Forty-four children were eligible (out of 48 approached): 31 consented, 30 were randomised, 21 completed the study; 10 in the supported group and 11 in the unsupported group. Nine children discontinued from tiredness, after-school activities, homework, surgery, technical difficulties or negative system feedback. The supported group completed 19 of 36 (IQR 5-35) possible sessions; the unsupported group 24 of 36 sessions (IQR 8-36). Gross Motor Function Measure scores varied by Cerebral Palsy severity after the intervention. There were no adverse events. Conclusion: Virtual reality therapy offers potential as a therapeutic adjunct for children with Cerebral Palsy, warranting substantive confirmatory study. Gross Motor Function Measure, with modifications to improve sensitivity, appeared appropriate as a primary measure, with Timed up and Go test secondary. The intervention was inexpensive costing £20 per child. An explanatory trial to evaluate the clinical/cost-effectiveness of commercial system virtual reality therapy is feasible with minor methodological adaptation. Implications for rehabilitation Home-based interactive computer gami

Published
2021
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