Exploratory space-time analysis of dengue incidence in Trinidad: a retrospective study using travel hubs as dispersal points, 1998–2004
Abstract Background Dengue is an acute arboviral disease responsible for most of the illness and death in tropical and subtropical regions. Over the last 25 years there has been increase epidemic activity of the disease in the Caribbean, with the co-circulation of multiple serotypes. An understandin...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2014-07-01
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| Series: | Parasites & Vectors |
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| Online Access: | https://doi.org/10.1186/1756-3305-7-341 |
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| author | Karmesh D Sharma Ron S Mahabir Kevin M Curtin Joan M Sutherland John B Agard Dave D Chadee |
| author_facet | Karmesh D Sharma Ron S Mahabir Kevin M Curtin Joan M Sutherland John B Agard Dave D Chadee |
| author_sort | Karmesh D Sharma |
| collection | DOAJ |
| description | Abstract Background Dengue is an acute arboviral disease responsible for most of the illness and death in tropical and subtropical regions. Over the last 25 years there has been increase epidemic activity of the disease in the Caribbean, with the co-circulation of multiple serotypes. An understanding of the space and time dynamics of dengue could provide health agencies with important clues for reducing its impact. Methods Dengue Haemorrhagic Fever (DHF) cases observed for the period 1998–2004 were georeferenced using Geographic Information System software. Spatial clustering was calculated for individual years and for the entire study period using the Nearest Neighbor Index. Space and time interaction between DHF cases was determined using the Knox Test while the Nearest Neighbor Hierarchical method was used to extract DHF hot spots. All space and time distances calculated were validated using the Pearson r significance test. Results Results shows that (1) a decrease in mean distance between DHF cases correlates with activity leading up to an outbreak, (2) a decrease in temporal distance between DHF cases leads to increased geographic spread of the disease, with an outbreak occurrence about every 2 years, and (3) a general pattern in the movement of dengue incidents from more rural to urban settings leading up to an outbreak with hotspot areas associated with transportation hubs in Trinidad. Conclusion Considering only the spatial dimension of the disease, results suggest that DHF cases become more concentrated leading up to an outbreak. However, with the additional consideration of time, results suggest that when an outbreak occurs incidents occur more rapidly in time leading to a parallel increase in the rate of distribution of the disease across space. The results of this study can be used by public health officers to help visualize and understand the spatial and temporal patterns of dengue, and to prepare warnings for the public. Dengue space-time patterns and hotspot detection will provide useful information to support public health officers in their efforts to control and predict dengue spread over critical hotspots allowing better allocation of resources. |
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| institution | Directory Open Access Journal |
| issn | 1756-3305 |
| language | English |
| last_indexed | 2024-03-13T07:27:57Z |
| publishDate | 2014-07-01 |
| publisher | BMC |
| record_format | Article |
| series | Parasites & Vectors |
| spelling | doaj.art-f40b3db2279b4b2b98d11912a746eeb32023-06-04T11:16:55ZengBMCParasites & Vectors1756-33052014-07-017111110.1186/1756-3305-7-341Exploratory space-time analysis of dengue incidence in Trinidad: a retrospective study using travel hubs as dispersal points, 1998–2004Karmesh D Sharma0Ron S Mahabir1Kevin M Curtin2Joan M Sutherland3John B Agard4Dave D Chadee5Ministry of HealthDepartment of Geography and Geoinformation Science, George Mason UniversityDepartment of Geography and Geoinformation Science, George Mason UniversityDepartment of Life Sciences, The University of the West IndiesDepartment of Life Sciences, The University of the West IndiesDepartment of Life Sciences, The University of the West IndiesAbstract Background Dengue is an acute arboviral disease responsible for most of the illness and death in tropical and subtropical regions. Over the last 25 years there has been increase epidemic activity of the disease in the Caribbean, with the co-circulation of multiple serotypes. An understanding of the space and time dynamics of dengue could provide health agencies with important clues for reducing its impact. Methods Dengue Haemorrhagic Fever (DHF) cases observed for the period 1998–2004 were georeferenced using Geographic Information System software. Spatial clustering was calculated for individual years and for the entire study period using the Nearest Neighbor Index. Space and time interaction between DHF cases was determined using the Knox Test while the Nearest Neighbor Hierarchical method was used to extract DHF hot spots. All space and time distances calculated were validated using the Pearson r significance test. Results Results shows that (1) a decrease in mean distance between DHF cases correlates with activity leading up to an outbreak, (2) a decrease in temporal distance between DHF cases leads to increased geographic spread of the disease, with an outbreak occurrence about every 2 years, and (3) a general pattern in the movement of dengue incidents from more rural to urban settings leading up to an outbreak with hotspot areas associated with transportation hubs in Trinidad. Conclusion Considering only the spatial dimension of the disease, results suggest that DHF cases become more concentrated leading up to an outbreak. However, with the additional consideration of time, results suggest that when an outbreak occurs incidents occur more rapidly in time leading to a parallel increase in the rate of distribution of the disease across space. The results of this study can be used by public health officers to help visualize and understand the spatial and temporal patterns of dengue, and to prepare warnings for the public. Dengue space-time patterns and hotspot detection will provide useful information to support public health officers in their efforts to control and predict dengue spread over critical hotspots allowing better allocation of resources.https://doi.org/10.1186/1756-3305-7-341DengueSpace-time analysisTravel hubsHot spotsDengue epidemiologyCluster analysis |
| spellingShingle | Karmesh D Sharma Ron S Mahabir Kevin M Curtin Joan M Sutherland John B Agard Dave D Chadee Exploratory space-time analysis of dengue incidence in Trinidad: a retrospective study using travel hubs as dispersal points, 1998–2004 Parasites & Vectors Dengue Space-time analysis Travel hubs Hot spots Dengue epidemiology Cluster analysis |
| title | Exploratory space-time analysis of dengue incidence in Trinidad: a retrospective study using travel hubs as dispersal points, 1998–2004 |
| title_full | Exploratory space-time analysis of dengue incidence in Trinidad: a retrospective study using travel hubs as dispersal points, 1998–2004 |
| title_fullStr | Exploratory space-time analysis of dengue incidence in Trinidad: a retrospective study using travel hubs as dispersal points, 1998–2004 |
| title_full_unstemmed | Exploratory space-time analysis of dengue incidence in Trinidad: a retrospective study using travel hubs as dispersal points, 1998–2004 |
| title_short | Exploratory space-time analysis of dengue incidence in Trinidad: a retrospective study using travel hubs as dispersal points, 1998–2004 |
| title_sort | exploratory space time analysis of dengue incidence in trinidad a retrospective study using travel hubs as dispersal points 1998 2004 |
| topic | Dengue Space-time analysis Travel hubs Hot spots Dengue epidemiology Cluster analysis |
| url | https://doi.org/10.1186/1756-3305-7-341 |
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