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

Urheber*innen

Badr,  Hamada S.
External Organizations;

Colston,  Josh M.
External Organizations;

Nguyen,  Nhat-Lan H.
External Organizations;

Chen,  Yen Ting
External Organizations;

Burnett,  Eleanor
External Organizations;

Ali,  Syed Asad
External Organizations;

Rayamajhi,  Ajit
External Organizations;

Satter,  Syed M.
External Organizations;

Van Trang,  Nguyen
External Organizations;

Eibach,  Daniel
External Organizations;

Krumkamp,  Ralf
External Organizations;

May,  Jürgen
External Organizations;

Adegnika,  Ayola Akim
External Organizations;

Manouana,  Gédéon Prince
External Organizations;

Kremsner,  Peter Gottfried
External Organizations;

Chilengi,  Roma
External Organizations;

Hatyoka,  Luiza
External Organizations;

Debes,  Amanda K.
External Organizations;

Ateudjieu,  Jerome
External Organizations;

Faruque,  Abu S. G.
External Organizations;

Hossain,  M Jahangir
External Organizations;

Kanungo,  Suman
External Organizations;

Kotloff,  Karen L.
External Organizations;

Mandomando,  Inácio
External Organizations;

Nisar,  M Imran
External Organizations;

Omore,  Richard
External Organizations;

Sow,  Samba O.
External Organizations;

Zaidi,  Anita K. M.
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/persons/resource/Nathalie.Lambrecht

Lambrecht,  Nathalie
Potsdam Institute for Climate Impact Research;

Adu,  Bright
External Organizations;

Page,  Nicola
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Platts-Mills,  James A.
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Mavacala Freitas,  Cesar
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Pelkonen,  Tuula
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Ashorn,  Per
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Maleta,  Kenneth
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Ahmed,  Tahmeed
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Bessong,  Pascal
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Bhutta,  Zulfiqar A.
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Mason,  Carl
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Mduma,  Estomih
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Olortegui,  Maribel P.
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Peñataro Yori,  Pablo
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Lima,  Aldo A. M.
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Kang,  Gagandeep
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Humphrey,  Jean
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Ntozini,  Robert
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Prendergast,  Andrew J.
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Okada,  Kazuhisa
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Wongboot,  Warawan
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Langeland,  Nina
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Moyo,  Sabrina J.
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Gaensbauer,  James
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Melgar,  Mario
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Freeman,  Matthew
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Chard,  Anna N.
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Thongpaseuth,  Vonethalom
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Houpt,  Eric
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Zaitchik,  Benjamin F.
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Kosek,  Margaret N.
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Zitation

Badr, H. S., Colston, J. M., Nguyen, N.-L.-H., Chen, Y. T., Burnett, E., Ali, S. A., Rayamajhi, A., Satter, S. M., Van Trang, N., Eibach, D., Krumkamp, R., May, J., Adegnika, A. A., Manouana, G. P., Kremsner, P. G., Chilengi, R., Hatyoka, L., Debes, A. K., Ateudjieu, J., Faruque, A. S. G., Hossain, M. J., Kanungo, S., Kotloff, K. L., Mandomando, I., Nisar, M. I., Omore, R., Sow, S. O., Zaidi, A. K. M., Lambrecht, N., Adu, B., Page, N., Platts-Mills, J. A., Mavacala Freitas, C., Pelkonen, T., Ashorn, P., Maleta, K., Ahmed, T., Bessong, P., Bhutta, Z. A., Mason, C., Mduma, E., Olortegui, M. P., Peñataro Yori, P., Lima, A. A. M., Kang, G., Humphrey, J., Ntozini, R., Prendergast, A. J., Okada, K., Wongboot, W., Langeland, N., Moyo, S. J., Gaensbauer, J., Melgar, M., Freeman, M., Chard, A. N., Thongpaseuth, V., Houpt, E., Zaitchik, B. F., Kosek, M. N. (2023): Spatiotemporal variation in risk of Shigella infection in childhood: a global risk mapping and prediction model using individual participant data. - The Lancet Global Health, 11, 3, e373-e384.
https://doi.org/10.1016/S2214-109X(22)00549-6


Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_28192
Zusammenfassung
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.