Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study
Abstract Background Zika virus (ZIKV) infection is a pandemic and a public health emergency. It is transmitted by mosquitoes, primarily the Aedes genus. In light of no treatment currently, it is crucial to develop effective vector control programs to prevent the spread of ZIKV infection earlier when...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2018-04-01
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| Series: | BMC Infectious Diseases |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12879-018-3085-x |
| _version_ | 1818521306110361600 |
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| author | Lung-Chang Chien Ro-Ting Lin Yunqi Liao Francisco S. Sy Adriana Pérez |
| author_facet | Lung-Chang Chien Ro-Ting Lin Yunqi Liao Francisco S. Sy Adriana Pérez |
| author_sort | Lung-Chang Chien |
| collection | DOAJ |
| description | Abstract Background Zika virus (ZIKV) infection is a pandemic and a public health emergency. It is transmitted by mosquitoes, primarily the Aedes genus. In light of no treatment currently, it is crucial to develop effective vector control programs to prevent the spread of ZIKV infection earlier when observing possible risk factors, such as weather conditions enhancing mosquito breeding and surviving. Methods This study collected daily meteorological measurements and weekly ZIKV infectious cases among 32 departments of Colombia from January 2015–December 2016. This study applied the distributed lag nonlinear model to estimate the association between the number of ZIKA virus infection and meteorological measurements, controlling for spatial and temporal variations. We examined at most three meteorological factors with 20 lags in weeks in the model. Results Average humidity, total rainfall, and maximum temperature were more predictable of ZIKV infection outbreaks than other meteorological factors. Our models can detect significantly lagged effects of average humidity, total rainfall, and maximum temperature on outbreaks up to 15, 14, and 20 weeks, respectively. The spatial analysis identified 12 departments with a significant threat of ZIKV, and eight of those high-risk departments were located between the Equator and 6°N. The outbreak prediction also performed well in identified high-risk departments. Conclusion Our results demonstrate that meteorological factors could be used for predicting ZIKV epidemics. Building an early warning surveillance system is important for preventing ZIKV infection, particularly in endemic areas. |
| first_indexed | 2024-12-11T01:49:16Z |
| format | Article |
| id | doaj.art-01c300603bbb4512b0a7c4e5d3ba6c6d |
| institution | Directory Open Access Journal |
| issn | 1471-2334 |
| language | English |
| last_indexed | 2024-12-11T01:49:16Z |
| publishDate | 2018-04-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Infectious Diseases |
| spelling | doaj.art-01c300603bbb4512b0a7c4e5d3ba6c6d2022-12-22T01:24:47ZengBMCBMC Infectious Diseases1471-23342018-04-0118111110.1186/s12879-018-3085-xSurveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal studyLung-Chang Chien0Ro-Ting Lin1Yunqi Liao2Francisco S. Sy3Adriana Pérez4Department of Environmental and Occupational Health, School of Community Health Sciences, University of Nevada, Las VegasDepartment of Occupational Safety and Health, China Medical UniversityDepartment of Biostatistics and Data Science, School of Public Health, Houston Campus, The University of Texas Health Science Center at Houston-UTHealthDepartment of Environmental and Occupational Health, School of Community Health Sciences, University of Nevada, Las VegasDepartment of Biostatistics and Data Science, School of Public Health, Austin Campus, The University of Texas Health Science Center at Houston-UTHealthAbstract Background Zika virus (ZIKV) infection is a pandemic and a public health emergency. It is transmitted by mosquitoes, primarily the Aedes genus. In light of no treatment currently, it is crucial to develop effective vector control programs to prevent the spread of ZIKV infection earlier when observing possible risk factors, such as weather conditions enhancing mosquito breeding and surviving. Methods This study collected daily meteorological measurements and weekly ZIKV infectious cases among 32 departments of Colombia from January 2015–December 2016. This study applied the distributed lag nonlinear model to estimate the association between the number of ZIKA virus infection and meteorological measurements, controlling for spatial and temporal variations. We examined at most three meteorological factors with 20 lags in weeks in the model. Results Average humidity, total rainfall, and maximum temperature were more predictable of ZIKV infection outbreaks than other meteorological factors. Our models can detect significantly lagged effects of average humidity, total rainfall, and maximum temperature on outbreaks up to 15, 14, and 20 weeks, respectively. The spatial analysis identified 12 departments with a significant threat of ZIKV, and eight of those high-risk departments were located between the Equator and 6°N. The outbreak prediction also performed well in identified high-risk departments. Conclusion Our results demonstrate that meteorological factors could be used for predicting ZIKV epidemics. Building an early warning surveillance system is important for preventing ZIKV infection, particularly in endemic areas.http://link.springer.com/article/10.1186/s12879-018-3085-xZika virus infectionMeteorological factorNonlinear lagged effectSpatial analysis |
| spellingShingle | Lung-Chang Chien Ro-Ting Lin Yunqi Liao Francisco S. Sy Adriana Pérez Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study BMC Infectious Diseases Zika virus infection Meteorological factor Nonlinear lagged effect Spatial analysis |
| title | Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study |
| title_full | Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study |
| title_fullStr | Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study |
| title_full_unstemmed | Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study |
| title_short | Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study |
| title_sort | surveillance on the endemic of zika virus infection by meteorological factors in colombia a population based spatial and temporal study |
| topic | Zika virus infection Meteorological factor Nonlinear lagged effect Spatial analysis |
| url | http://link.springer.com/article/10.1186/s12879-018-3085-x |
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