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Spatiotemporal variation in risk of Shigella infection in childhood: a global risk mapping and prediction model using individual participant data

BACKGROUND: Diarrhoeal disease is a leading cause of childhood illness and death globally, and Shigella is a major aetiological contributor for which a vaccine might soon be available. The primary objective of this study was to model the spatiotemporal variation in paediatric Shigella infection and...

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Autores principales: Badr, Hamada S, Colston, Josh M, Nguyen, Nhat-Lan H, Chen, Yen Ting, Burnett, Eleanor, Ali, Syed Asad, Rayamajhi, Ajit, Satter, Syed M, Van Trang, Nguyen, Eibach, Daniel, Krumkamp, Ralf, May, Jürgen, Adegnika, Ayola Akim, Manouana, Gédéon Prince, Kremsner, Peter Gottfried, Chilengi, Roma, Hatyoka, Luiza, Debes, Amanda K, Ateudjieu, Jerome, Faruque, Abu S G, Hossain, M Jahangir, Kanungo, Suman, Kotloff, Karen L, Mandomando, Inácio, Nisar, M Imran, Omore, Richard, Sow, Samba O, Zaidi, Anita K M, Lambrecht, Nathalie, Adu, Bright, Page, Nicola, Platts-Mills, James A, Mavacala Freitas, Cesar, Pelkonen, Tuula, Ashorn, Per, Maleta, Kenneth, Ahmed, Tahmeed, Bessong, Pascal, Bhutta, Zulfiqar A, Mason, Carl, Mduma, Estomih, Olortegui, Maribel P, Peñataro Yori, Pablo, Lima, Aldo A M, Kang, Gagandeep, Humphrey, Jean, Ntozini, Robert, Prendergast, Andrew J, Okada, Kazuhisa, Wongboot, Warawan, Langeland, Nina, Moyo, Sabrina J, Gaensbauer, James, Melgar, Mario, Freeman, Matthew, Chard, Anna N, Thongpaseuth, Vonethalom, Houpt, Eric, Zaitchik, Benjamin F, Kosek, Margaret N
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10020138/
https://www.ncbi.nlm.nih.gov/pubmed/36796984
http://dx.doi.org/10.1016/S2214-109X(22)00549-6
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author Badr, Hamada S
Colston, Josh M
Nguyen, Nhat-Lan H
Chen, Yen Ting
Burnett, Eleanor
Ali, Syed Asad
Rayamajhi, Ajit
Satter, Syed M
Van Trang, Nguyen
Eibach, Daniel
Krumkamp, Ralf
May, Jürgen
Adegnika, Ayola Akim
Manouana, Gédéon Prince
Kremsner, Peter Gottfried
Chilengi, Roma
Hatyoka, Luiza
Debes, Amanda K
Ateudjieu, Jerome
Faruque, Abu S G
Hossain, M Jahangir
Kanungo, Suman
Kotloff, Karen L
Mandomando, Inácio
Nisar, M Imran
Omore, Richard
Sow, Samba O
Zaidi, Anita K M
Lambrecht, Nathalie
Adu, Bright
Page, Nicola
Platts-Mills, James A
Mavacala Freitas, Cesar
Pelkonen, Tuula
Ashorn, Per
Maleta, Kenneth
Ahmed, Tahmeed
Bessong, Pascal
Bhutta, Zulfiqar A
Mason, Carl
Mduma, Estomih
Olortegui, Maribel P
Peñataro Yori, Pablo
Lima, Aldo A M
Kang, Gagandeep
Humphrey, Jean
Ntozini, Robert
Prendergast, Andrew J
Okada, Kazuhisa
Wongboot, Warawan
Langeland, Nina
Moyo, Sabrina J
Gaensbauer, James
Melgar, Mario
Freeman, Matthew
Chard, Anna N
Thongpaseuth, Vonethalom
Houpt, Eric
Zaitchik, Benjamin F
Kosek, Margaret N
author_facet Badr, Hamada S
Colston, Josh M
Nguyen, Nhat-Lan H
Chen, Yen Ting
Burnett, Eleanor
Ali, Syed Asad
Rayamajhi, Ajit
Satter, Syed M
Van Trang, Nguyen
Eibach, Daniel
Krumkamp, Ralf
May, Jürgen
Adegnika, Ayola Akim
Manouana, Gédéon Prince
Kremsner, Peter Gottfried
Chilengi, Roma
Hatyoka, Luiza
Debes, Amanda K
Ateudjieu, Jerome
Faruque, Abu S G
Hossain, M Jahangir
Kanungo, Suman
Kotloff, Karen L
Mandomando, Inácio
Nisar, M Imran
Omore, Richard
Sow, Samba O
Zaidi, Anita K M
Lambrecht, Nathalie
Adu, Bright
Page, Nicola
Platts-Mills, James A
Mavacala Freitas, Cesar
Pelkonen, Tuula
Ashorn, Per
Maleta, Kenneth
Ahmed, Tahmeed
Bessong, Pascal
Bhutta, Zulfiqar A
Mason, Carl
Mduma, Estomih
Olortegui, Maribel P
Peñataro Yori, Pablo
Lima, Aldo A M
Kang, Gagandeep
Humphrey, Jean
Ntozini, Robert
Prendergast, Andrew J
Okada, Kazuhisa
Wongboot, Warawan
Langeland, Nina
Moyo, Sabrina J
Gaensbauer, James
Melgar, Mario
Freeman, Matthew
Chard, Anna N
Thongpaseuth, Vonethalom
Houpt, Eric
Zaitchik, Benjamin F
Kosek, Margaret N
author_sort Badr, Hamada S
collection PubMed
description BACKGROUND: Diarrhoeal disease is a leading cause of childhood illness and death globally, and Shigella is a major aetiological contributor for which a vaccine might soon be available. The primary objective of this study was to model the spatiotemporal variation in paediatric Shigella infection and map its predicted prevalence across low-income and middle-income countries (LMICs). METHODS: Individual participant data for Shigella positivity in stool samples were sourced from multiple LMIC-based studies of children aged 59 months or younger. Covariates included household-level and participant-level factors ascertained by study investigators and environmental and hydrometeorological variables extracted from various data products at georeferenced child locations. Multivariate models were fitted and prevalence predictions obtained by syndrome and age stratum. FINDINGS: 20 studies from 23 countries (including locations in Central America and South America, sub-Saharan Africa, and south and southeast Asia) contributed 66 563 sample results. Age, symptom status, and study design contributed most to model performance followed by temperature, wind speed, relative humidity, and soil moisture. Probability of Shigella infection exceeded 20% when both precipitation and soil moisture were above average and had a 43% peak in uncomplicated diarrhoea cases at 33°C temperatures, above which it decreased. Compared with unimproved sanitation, improved sanitation decreased the odds of Shigella infection by 19% (odds ratio [OR]=0·81 [95% CI 0·76–0·86]) and open defecation decreased them by 18% (OR=0·82 [0·76–0·88]). INTERPRETATION: The distribution of Shigella is more sensitive to climatological factors, such as temperature, than previously recognised. Conditions in much of sub-Saharan Africa are particularly propitious for Shigella transmission, although hotspots also occur in South America and Central America, the Ganges–Brahmaputra Delta, and the island of New Guinea. These findings can inform prioritisation of populations for future vaccine trials and campaigns. FUNDING: NASA, National Institutes of Health–The National Institute of Allergy and Infectious Diseases, and Bill & Melinda Gates Foundation.
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spelling pubmed-100201382023-03-18 Spatiotemporal variation in risk of Shigella infection in childhood: a global risk mapping and prediction model using individual participant data Badr, Hamada S Colston, Josh M Nguyen, Nhat-Lan H Chen, Yen Ting Burnett, Eleanor Ali, Syed Asad Rayamajhi, Ajit Satter, Syed M Van Trang, Nguyen Eibach, Daniel Krumkamp, Ralf May, Jürgen Adegnika, Ayola Akim Manouana, Gédéon Prince Kremsner, Peter Gottfried Chilengi, Roma Hatyoka, Luiza Debes, Amanda K Ateudjieu, Jerome Faruque, Abu S G Hossain, M Jahangir Kanungo, Suman Kotloff, Karen L Mandomando, Inácio Nisar, M Imran Omore, Richard Sow, Samba O Zaidi, Anita K M Lambrecht, Nathalie Adu, Bright Page, Nicola Platts-Mills, James A Mavacala Freitas, Cesar Pelkonen, Tuula Ashorn, Per Maleta, Kenneth Ahmed, Tahmeed Bessong, Pascal Bhutta, Zulfiqar A Mason, Carl Mduma, Estomih Olortegui, Maribel P Peñataro Yori, Pablo Lima, Aldo A M Kang, Gagandeep Humphrey, Jean Ntozini, Robert Prendergast, Andrew J Okada, Kazuhisa Wongboot, Warawan Langeland, Nina Moyo, Sabrina J Gaensbauer, James Melgar, Mario Freeman, Matthew Chard, Anna N Thongpaseuth, Vonethalom Houpt, Eric Zaitchik, Benjamin F Kosek, Margaret N Lancet Glob Health Articles BACKGROUND: Diarrhoeal disease is a leading cause of childhood illness and death globally, and Shigella is a major aetiological contributor for which a vaccine might soon be available. The primary objective of this study was to model the spatiotemporal variation in paediatric Shigella infection and map its predicted prevalence across low-income and middle-income countries (LMICs). METHODS: Individual participant data for Shigella positivity in stool samples were sourced from multiple LMIC-based studies of children aged 59 months or younger. Covariates included household-level and participant-level factors ascertained by study investigators and environmental and hydrometeorological variables extracted from various data products at georeferenced child locations. Multivariate models were fitted and prevalence predictions obtained by syndrome and age stratum. FINDINGS: 20 studies from 23 countries (including locations in Central America and South America, sub-Saharan Africa, and south and southeast Asia) contributed 66 563 sample results. Age, symptom status, and study design contributed most to model performance followed by temperature, wind speed, relative humidity, and soil moisture. Probability of Shigella infection exceeded 20% when both precipitation and soil moisture were above average and had a 43% peak in uncomplicated diarrhoea cases at 33°C temperatures, above which it decreased. Compared with unimproved sanitation, improved sanitation decreased the odds of Shigella infection by 19% (odds ratio [OR]=0·81 [95% CI 0·76–0·86]) and open defecation decreased them by 18% (OR=0·82 [0·76–0·88]). INTERPRETATION: The distribution of Shigella is more sensitive to climatological factors, such as temperature, than previously recognised. Conditions in much of sub-Saharan Africa are particularly propitious for Shigella transmission, although hotspots also occur in South America and Central America, the Ganges–Brahmaputra Delta, and the island of New Guinea. These findings can inform prioritisation of populations for future vaccine trials and campaigns. FUNDING: NASA, National Institutes of Health–The National Institute of Allergy and Infectious Diseases, and Bill & Melinda Gates Foundation. Elsevier Ltd 2023-02-14 /pmc/articles/PMC10020138/ /pubmed/36796984 http://dx.doi.org/10.1016/S2214-109X(22)00549-6 Text en © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Articles
Badr, Hamada S
Colston, Josh M
Nguyen, Nhat-Lan H
Chen, Yen Ting
Burnett, Eleanor
Ali, Syed Asad
Rayamajhi, Ajit
Satter, Syed M
Van Trang, Nguyen
Eibach, Daniel
Krumkamp, Ralf
May, Jürgen
Adegnika, Ayola Akim
Manouana, Gédéon Prince
Kremsner, Peter Gottfried
Chilengi, Roma
Hatyoka, Luiza
Debes, Amanda K
Ateudjieu, Jerome
Faruque, Abu S G
Hossain, M Jahangir
Kanungo, Suman
Kotloff, Karen L
Mandomando, Inácio
Nisar, M Imran
Omore, Richard
Sow, Samba O
Zaidi, Anita K M
Lambrecht, Nathalie
Adu, Bright
Page, Nicola
Platts-Mills, James A
Mavacala Freitas, Cesar
Pelkonen, Tuula
Ashorn, Per
Maleta, Kenneth
Ahmed, Tahmeed
Bessong, Pascal
Bhutta, Zulfiqar A
Mason, Carl
Mduma, Estomih
Olortegui, Maribel P
Peñataro Yori, Pablo
Lima, Aldo A M
Kang, Gagandeep
Humphrey, Jean
Ntozini, Robert
Prendergast, Andrew J
Okada, Kazuhisa
Wongboot, Warawan
Langeland, Nina
Moyo, Sabrina J
Gaensbauer, James
Melgar, Mario
Freeman, Matthew
Chard, Anna N
Thongpaseuth, Vonethalom
Houpt, Eric
Zaitchik, Benjamin F
Kosek, Margaret N
Spatiotemporal variation in risk of Shigella infection in childhood: a global risk mapping and prediction model using individual participant data
title Spatiotemporal variation in risk of Shigella infection in childhood: a global risk mapping and prediction model using individual participant data
title_full Spatiotemporal variation in risk of Shigella infection in childhood: a global risk mapping and prediction model using individual participant data
title_fullStr Spatiotemporal variation in risk of Shigella infection in childhood: a global risk mapping and prediction model using individual participant data
title_full_unstemmed Spatiotemporal variation in risk of Shigella infection in childhood: a global risk mapping and prediction model using individual participant data
title_short Spatiotemporal variation in risk of Shigella infection in childhood: a global risk mapping and prediction model using individual participant data
title_sort spatiotemporal variation in risk of shigella infection in childhood: a global risk mapping and prediction model using individual participant data
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10020138/
https://www.ncbi.nlm.nih.gov/pubmed/36796984
http://dx.doi.org/10.1016/S2214-109X(22)00549-6
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