Jorge E Salazar Flórez, Berta N Restrepo, Laís Picinini Freitas, Mabel Carabali, Gloria I Jaramillo Ramírez, Cesar Garcia Balaguera, Brayan S Avila Monsalve, Kate Zinszer
{"title":"2013 - 2021年哥伦比亚Medellín登革热、基孔肯雅热和寨卡病毒分布与共传播的时空分析","authors":"Jorge E Salazar Flórez, Berta N Restrepo, Laís Picinini Freitas, Mabel Carabali, Gloria I Jaramillo Ramírez, Cesar Garcia Balaguera, Brayan S Avila Monsalve, Kate Zinszer","doi":"10.1371/journal.pntd.0013470","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Dengue, chikungunya, and Zika present significant public health challenges in Colombia. Spatial studies help clarify the distribution and progression of these diseases over time and location. Objective to describe the spatio-temporal distribution and clustering patterns of dengue, chikungunya, and Zika in Medellín, Colombia, between 2013 and 2021, with the aim of providing baseline spatial intelligence to support future epidemiological and policy-oriented analyses.</p><p><strong>Methods: </strong>We analyzed dengue, chikungunya, and Zika cases in Medellín from 2013 to 2021, using weekly data from 27,459 geocoded cases across 265 neighborhoods. Cases were geocoded by neighborhood based on residential addresses in the national surveillance system (SIVIGILA). Spatio-temporal analysis identified high-risk clusters and examined the co-circulation of the diseases through multivariate analysis. We used scan statistics with a discrete Poisson model to detect high-risk clusters.</p><p><strong>Results: </strong>From 2013 to 2021, 26,350 dengue cases probable and confirmed were reported, with an annual incidence of 137.3 per 100,000 residents. Chikungunya and Zika emerged in 2014 and 2015, with 574 and 515 cases reported, resulting in incidences of 5.1 and 3.8 per 100,000 residents, respectively. We identified five dengue clusters and four clusters each for Zika and chikungunya, mainly in Medellín's northeast. Multivariate analysis revealed six clusters, with four exhibiting high risk for all three diseases. Co-circulation of dengue, chikungunya, and Zika occurred between September 2015 and February 2017. Dengue clusters peaked between 2015 and 2016, while chikungunya and Zika peaks occurred in 2015 and 2016, respectively.</p><p><strong>Conclusions: </strong>This study advances understanding of spatio-temporal dynamics in arbovirus transmission in Medellín, highlighting high-risk clusters for dengue, chikungunya, and Zika and their collective presence. Our findings support targeted public health interventions to mitigate these diseases.</p>","PeriodicalId":49000,"journal":{"name":"PLoS Neglected Tropical Diseases","volume":"19 9","pages":"e0013470"},"PeriodicalIF":3.4000,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12425392/pdf/","citationCount":"0","resultStr":"{\"title\":\"Spatio-temporal analysis of the distribution and co-circulation of dengue, chikungunya, and Zika in Medellín, Colombia, from 2013 to 2021.\",\"authors\":\"Jorge E Salazar Flórez, Berta N Restrepo, Laís Picinini Freitas, Mabel Carabali, Gloria I Jaramillo Ramírez, Cesar Garcia Balaguera, Brayan S Avila Monsalve, Kate Zinszer\",\"doi\":\"10.1371/journal.pntd.0013470\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Dengue, chikungunya, and Zika present significant public health challenges in Colombia. Spatial studies help clarify the distribution and progression of these diseases over time and location. Objective to describe the spatio-temporal distribution and clustering patterns of dengue, chikungunya, and Zika in Medellín, Colombia, between 2013 and 2021, with the aim of providing baseline spatial intelligence to support future epidemiological and policy-oriented analyses.</p><p><strong>Methods: </strong>We analyzed dengue, chikungunya, and Zika cases in Medellín from 2013 to 2021, using weekly data from 27,459 geocoded cases across 265 neighborhoods. Cases were geocoded by neighborhood based on residential addresses in the national surveillance system (SIVIGILA). Spatio-temporal analysis identified high-risk clusters and examined the co-circulation of the diseases through multivariate analysis. We used scan statistics with a discrete Poisson model to detect high-risk clusters.</p><p><strong>Results: </strong>From 2013 to 2021, 26,350 dengue cases probable and confirmed were reported, with an annual incidence of 137.3 per 100,000 residents. Chikungunya and Zika emerged in 2014 and 2015, with 574 and 515 cases reported, resulting in incidences of 5.1 and 3.8 per 100,000 residents, respectively. We identified five dengue clusters and four clusters each for Zika and chikungunya, mainly in Medellín's northeast. Multivariate analysis revealed six clusters, with four exhibiting high risk for all three diseases. Co-circulation of dengue, chikungunya, and Zika occurred between September 2015 and February 2017. Dengue clusters peaked between 2015 and 2016, while chikungunya and Zika peaks occurred in 2015 and 2016, respectively.</p><p><strong>Conclusions: </strong>This study advances understanding of spatio-temporal dynamics in arbovirus transmission in Medellín, highlighting high-risk clusters for dengue, chikungunya, and Zika and their collective presence. 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Spatio-temporal analysis of the distribution and co-circulation of dengue, chikungunya, and Zika in Medellín, Colombia, from 2013 to 2021.
Background: Dengue, chikungunya, and Zika present significant public health challenges in Colombia. Spatial studies help clarify the distribution and progression of these diseases over time and location. Objective to describe the spatio-temporal distribution and clustering patterns of dengue, chikungunya, and Zika in Medellín, Colombia, between 2013 and 2021, with the aim of providing baseline spatial intelligence to support future epidemiological and policy-oriented analyses.
Methods: We analyzed dengue, chikungunya, and Zika cases in Medellín from 2013 to 2021, using weekly data from 27,459 geocoded cases across 265 neighborhoods. Cases were geocoded by neighborhood based on residential addresses in the national surveillance system (SIVIGILA). Spatio-temporal analysis identified high-risk clusters and examined the co-circulation of the diseases through multivariate analysis. We used scan statistics with a discrete Poisson model to detect high-risk clusters.
Results: From 2013 to 2021, 26,350 dengue cases probable and confirmed were reported, with an annual incidence of 137.3 per 100,000 residents. Chikungunya and Zika emerged in 2014 and 2015, with 574 and 515 cases reported, resulting in incidences of 5.1 and 3.8 per 100,000 residents, respectively. We identified five dengue clusters and four clusters each for Zika and chikungunya, mainly in Medellín's northeast. Multivariate analysis revealed six clusters, with four exhibiting high risk for all three diseases. Co-circulation of dengue, chikungunya, and Zika occurred between September 2015 and February 2017. Dengue clusters peaked between 2015 and 2016, while chikungunya and Zika peaks occurred in 2015 and 2016, respectively.
Conclusions: This study advances understanding of spatio-temporal dynamics in arbovirus transmission in Medellín, highlighting high-risk clusters for dengue, chikungunya, and Zika and their collective presence. Our findings support targeted public health interventions to mitigate these diseases.
期刊介绍：
PLOS Neglected Tropical Diseases publishes research devoted to the pathology, epidemiology, prevention, treatment and control of the neglected tropical diseases (NTDs), as well as relevant public policy.
The NTDs are defined as a group of poverty-promoting chronic infectious diseases, which primarily occur in rural areas and poor urban areas of low-income and middle-income countries. Their impact on child health and development, pregnancy, and worker productivity, as well as their stigmatizing features limit economic stability.
All aspects of these diseases are considered, including:
Pathogenesis
Clinical features
Pharmacology and treatment
Diagnosis
Epidemiology
Vector biology
Vaccinology and prevention
Demographic, ecological and social determinants
Public health and policy aspects (including cost-effectiveness analyses).
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