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Spatial and temporal distribution of reported dengue cases and hot spot identification in Quezon City, Philippines, 2010–2017
BACKGROUND: Dengue remains a major public health problem in the Philippines, particularly in urban areas of the National Capital Region. Thematic mapping using geographic information systems complemented by spatial analysis such as cluster analysis and hot spot detection can provide useful informati...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10208904/ https://www.ncbi.nlm.nih.gov/pubmed/37226211 http://dx.doi.org/10.1186/s41182-023-00523-x |
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author | Medina, John Robert C. Takeuchi, Rie Mercado, Chris Erwin G. de los Reyes, Calvin S. Cruz, Rolando V. Abrigo, Melvin D. R. Hernandez, Paul Michael R. Garcia, Fernando B. Salanguit, Mika Gregorio, Ernesto R. Kawamura, Shin’ya Hung, Khew Ee Kaneko, Masami Nonaka, Daisuke Maude, Richard J. Kobayashi, Jun |
author_facet | Medina, John Robert C. Takeuchi, Rie Mercado, Chris Erwin G. de los Reyes, Calvin S. Cruz, Rolando V. Abrigo, Melvin D. R. Hernandez, Paul Michael R. Garcia, Fernando B. Salanguit, Mika Gregorio, Ernesto R. Kawamura, Shin’ya Hung, Khew Ee Kaneko, Masami Nonaka, Daisuke Maude, Richard J. Kobayashi, Jun |
author_sort | Medina, John Robert C. |
collection | PubMed |
description | BACKGROUND: Dengue remains a major public health problem in the Philippines, particularly in urban areas of the National Capital Region. Thematic mapping using geographic information systems complemented by spatial analysis such as cluster analysis and hot spot detection can provide useful information to guide preventive measures and control strategies against dengue. Hence, this study was aimed to describe the spatiotemporal distribution of dengue incidence and identify dengue hot spots by barangay using reported cases from Quezon City, the Philippines from 2010 to 2017. METHODS: Reported dengue case data at barangay level from January 1, 2010 to December 31, 2017 were obtained from the Quezon City Epidemiology and Surveillance Unit. The annual incidence rate of dengue from 2010 to 2017, expressed as the total number of dengue cases per 10,000 population in each year, was calculated for each barangay. Thematic mapping, global cluster analysis, and hot spot analysis were performed using ArcGIS 10.3.1. RESULTS: The number of reported dengue cases and their spatial distribution varied highly between years. Local clusters were evident during the study period. Eighteen barangays were identified as hot spots. CONCLUSIONS: Considering the spatial heterogeneity and instability of hot spots in Quezon City across years, efforts towards the containment of dengue can be made more targeted, and efficient with the application of hot spot analysis in routine surveillance. This may be useful not only for the control of dengue but also for other diseases, and for public health planning, monitoring, and evaluation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41182-023-00523-x. |
format | Online Article Text |
id | pubmed-10208904 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-102089042023-05-26 Spatial and temporal distribution of reported dengue cases and hot spot identification in Quezon City, Philippines, 2010–2017 Medina, John Robert C. Takeuchi, Rie Mercado, Chris Erwin G. de los Reyes, Calvin S. Cruz, Rolando V. Abrigo, Melvin D. R. Hernandez, Paul Michael R. Garcia, Fernando B. Salanguit, Mika Gregorio, Ernesto R. Kawamura, Shin’ya Hung, Khew Ee Kaneko, Masami Nonaka, Daisuke Maude, Richard J. Kobayashi, Jun Trop Med Health Research BACKGROUND: Dengue remains a major public health problem in the Philippines, particularly in urban areas of the National Capital Region. Thematic mapping using geographic information systems complemented by spatial analysis such as cluster analysis and hot spot detection can provide useful information to guide preventive measures and control strategies against dengue. Hence, this study was aimed to describe the spatiotemporal distribution of dengue incidence and identify dengue hot spots by barangay using reported cases from Quezon City, the Philippines from 2010 to 2017. METHODS: Reported dengue case data at barangay level from January 1, 2010 to December 31, 2017 were obtained from the Quezon City Epidemiology and Surveillance Unit. The annual incidence rate of dengue from 2010 to 2017, expressed as the total number of dengue cases per 10,000 population in each year, was calculated for each barangay. Thematic mapping, global cluster analysis, and hot spot analysis were performed using ArcGIS 10.3.1. RESULTS: The number of reported dengue cases and their spatial distribution varied highly between years. Local clusters were evident during the study period. Eighteen barangays were identified as hot spots. CONCLUSIONS: Considering the spatial heterogeneity and instability of hot spots in Quezon City across years, efforts towards the containment of dengue can be made more targeted, and efficient with the application of hot spot analysis in routine surveillance. This may be useful not only for the control of dengue but also for other diseases, and for public health planning, monitoring, and evaluation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41182-023-00523-x. BioMed Central 2023-05-25 /pmc/articles/PMC10208904/ /pubmed/37226211 http://dx.doi.org/10.1186/s41182-023-00523-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Medina, John Robert C. Takeuchi, Rie Mercado, Chris Erwin G. de los Reyes, Calvin S. Cruz, Rolando V. Abrigo, Melvin D. R. Hernandez, Paul Michael R. Garcia, Fernando B. Salanguit, Mika Gregorio, Ernesto R. Kawamura, Shin’ya Hung, Khew Ee Kaneko, Masami Nonaka, Daisuke Maude, Richard J. Kobayashi, Jun Spatial and temporal distribution of reported dengue cases and hot spot identification in Quezon City, Philippines, 2010–2017 |
title | Spatial and temporal distribution of reported dengue cases and hot spot identification in Quezon City, Philippines, 2010–2017 |
title_full | Spatial and temporal distribution of reported dengue cases and hot spot identification in Quezon City, Philippines, 2010–2017 |
title_fullStr | Spatial and temporal distribution of reported dengue cases and hot spot identification in Quezon City, Philippines, 2010–2017 |
title_full_unstemmed | Spatial and temporal distribution of reported dengue cases and hot spot identification in Quezon City, Philippines, 2010–2017 |
title_short | Spatial and temporal distribution of reported dengue cases and hot spot identification in Quezon City, Philippines, 2010–2017 |
title_sort | spatial and temporal distribution of reported dengue cases and hot spot identification in quezon city, philippines, 2010–2017 |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10208904/ https://www.ncbi.nlm.nih.gov/pubmed/37226211 http://dx.doi.org/10.1186/s41182-023-00523-x |
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