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Geographically Weighted Regression Modeling of Spatial Clustering and Determinants of Focal Typhoid Fever Incidence

BACKGROUND: Typhoid is known to be heterogenous in time and space, with documented spatiotemporal clustering and hotspots associated with environmental factors. This analysis evaluated spatial clustering of typhoid and modeled incidence rates of typhoid from active surveillance at 4 sites with child...

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Autores principales: Mohan, Venkata Raghava, Srinivasan, Manikandan, Sinha, Bireshwar, Shrivastava, Ankita, Kanungo, Suman, Natarajan Sindhu, Kulandaipalayam, Ramanujam, Karthikeyan, Ganesan, Santhosh Kumar, Karthikeyan, Arun S, Kumar Jaganathan, Senthil, Gunasekaran, Annai, Arya, Alok, Bavdekar, Ashish, Rongsen-Chandola, Temsunaro, Dutta, Shanta, John, Jacob, Kang, Gagandeep
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8892548/
https://www.ncbi.nlm.nih.gov/pubmed/35238357
http://dx.doi.org/10.1093/infdis/jiab379
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author Mohan, Venkata Raghava
Srinivasan, Manikandan
Sinha, Bireshwar
Shrivastava, Ankita
Kanungo, Suman
Natarajan Sindhu, Kulandaipalayam
Ramanujam, Karthikeyan
Ganesan, Santhosh Kumar
Karthikeyan, Arun S
Kumar Jaganathan, Senthil
Gunasekaran, Annai
Arya, Alok
Bavdekar, Ashish
Rongsen-Chandola, Temsunaro
Dutta, Shanta
John, Jacob
Kang, Gagandeep
author_facet Mohan, Venkata Raghava
Srinivasan, Manikandan
Sinha, Bireshwar
Shrivastava, Ankita
Kanungo, Suman
Natarajan Sindhu, Kulandaipalayam
Ramanujam, Karthikeyan
Ganesan, Santhosh Kumar
Karthikeyan, Arun S
Kumar Jaganathan, Senthil
Gunasekaran, Annai
Arya, Alok
Bavdekar, Ashish
Rongsen-Chandola, Temsunaro
Dutta, Shanta
John, Jacob
Kang, Gagandeep
author_sort Mohan, Venkata Raghava
collection PubMed
description BACKGROUND: Typhoid is known to be heterogenous in time and space, with documented spatiotemporal clustering and hotspots associated with environmental factors. This analysis evaluated spatial clustering of typhoid and modeled incidence rates of typhoid from active surveillance at 4 sites with child cohorts in India. METHODS: Among approximately 24 000 children aged 0.5–15 years followed for 2 years, typhoid was confirmed by blood culture in all children with fever >3 days. Local hotspots for incident typhoid cases were assessed using SaTScan spatial cluster detection. Incidence of typhoid was modeled with sociodemographic and water, sanitation, and hygiene–related factors in smaller grids using nonspatial and spatial regression analyses. RESULTS: Hotspot households for typhoid were identified at Vellore and Kolkata. There were 4 significant SaTScan clusters (P < .05) for typhoid in Vellore. Mean incidence of typhoid was 0.004 per child-year with the highest incidence (0.526 per child-year) in Kolkata. Unsafe water and poor sanitation were positively associated with typhoid in Kolkata and Delhi, whereas drinking untreated water was significantly associated in Vellore (P = .0342) and Delhi (P = .0188). CONCLUSIONS: Despite decades of efforts to improve water and sanitation by the Indian government, environmental factors continue to influence the incidence of typhoid. Hence, administration of the conjugate vaccine may be essential even as efforts to improve water and sanitation continue.
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spelling pubmed-88925482022-03-04 Geographically Weighted Regression Modeling of Spatial Clustering and Determinants of Focal Typhoid Fever Incidence Mohan, Venkata Raghava Srinivasan, Manikandan Sinha, Bireshwar Shrivastava, Ankita Kanungo, Suman Natarajan Sindhu, Kulandaipalayam Ramanujam, Karthikeyan Ganesan, Santhosh Kumar Karthikeyan, Arun S Kumar Jaganathan, Senthil Gunasekaran, Annai Arya, Alok Bavdekar, Ashish Rongsen-Chandola, Temsunaro Dutta, Shanta John, Jacob Kang, Gagandeep J Infect Dis Supplement Articles BACKGROUND: Typhoid is known to be heterogenous in time and space, with documented spatiotemporal clustering and hotspots associated with environmental factors. This analysis evaluated spatial clustering of typhoid and modeled incidence rates of typhoid from active surveillance at 4 sites with child cohorts in India. METHODS: Among approximately 24 000 children aged 0.5–15 years followed for 2 years, typhoid was confirmed by blood culture in all children with fever >3 days. Local hotspots for incident typhoid cases were assessed using SaTScan spatial cluster detection. Incidence of typhoid was modeled with sociodemographic and water, sanitation, and hygiene–related factors in smaller grids using nonspatial and spatial regression analyses. RESULTS: Hotspot households for typhoid were identified at Vellore and Kolkata. There were 4 significant SaTScan clusters (P < .05) for typhoid in Vellore. Mean incidence of typhoid was 0.004 per child-year with the highest incidence (0.526 per child-year) in Kolkata. Unsafe water and poor sanitation were positively associated with typhoid in Kolkata and Delhi, whereas drinking untreated water was significantly associated in Vellore (P = .0342) and Delhi (P = .0188). CONCLUSIONS: Despite decades of efforts to improve water and sanitation by the Indian government, environmental factors continue to influence the incidence of typhoid. Hence, administration of the conjugate vaccine may be essential even as efforts to improve water and sanitation continue. Oxford University Press 2021-11-23 /pmc/articles/PMC8892548/ /pubmed/35238357 http://dx.doi.org/10.1093/infdis/jiab379 Text en © The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Supplement Articles
Mohan, Venkata Raghava
Srinivasan, Manikandan
Sinha, Bireshwar
Shrivastava, Ankita
Kanungo, Suman
Natarajan Sindhu, Kulandaipalayam
Ramanujam, Karthikeyan
Ganesan, Santhosh Kumar
Karthikeyan, Arun S
Kumar Jaganathan, Senthil
Gunasekaran, Annai
Arya, Alok
Bavdekar, Ashish
Rongsen-Chandola, Temsunaro
Dutta, Shanta
John, Jacob
Kang, Gagandeep
Geographically Weighted Regression Modeling of Spatial Clustering and Determinants of Focal Typhoid Fever Incidence
title Geographically Weighted Regression Modeling of Spatial Clustering and Determinants of Focal Typhoid Fever Incidence
title_full Geographically Weighted Regression Modeling of Spatial Clustering and Determinants of Focal Typhoid Fever Incidence
title_fullStr Geographically Weighted Regression Modeling of Spatial Clustering and Determinants of Focal Typhoid Fever Incidence
title_full_unstemmed Geographically Weighted Regression Modeling of Spatial Clustering and Determinants of Focal Typhoid Fever Incidence
title_short Geographically Weighted Regression Modeling of Spatial Clustering and Determinants of Focal Typhoid Fever Incidence
title_sort geographically weighted regression modeling of spatial clustering and determinants of focal typhoid fever incidence
topic Supplement Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8892548/
https://www.ncbi.nlm.nih.gov/pubmed/35238357
http://dx.doi.org/10.1093/infdis/jiab379
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