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Spatial epidemiology and climatic predictors of paediatric dengue infections captured via sentinel site surveillance, Phnom Penh Cambodia 2011–2012
BMC Public Health (2014)
  • Andrew A. Lover, University of Massachusetts Amherst
  • Philippe Buchy, Institut Pasteur in Cambodia
  • Anne Rachline, Formerly- Regional Emerging Diseases Intervention (REDI) Centre
  • Duch Moniboth, National Paediatric Hospital
  • Rekol Huy, National Dengue Control Program (NDCP), National Center for Parasitological, Entomology and Malaria Control
  • Chour Y Meng, Ministry of Health
  • Yee Sin Leo, Centers for Disease Control
  • Kdan Yuvatha, National Paediatric Hospital
  • Ung Sophal, National Paediatric Hospital
  • Ngan Chantha, National Dengue Control Program (NDCP), National Center for Parasitological, Entomology and Malaria Control
  • Bunthin Y, Institut Pasteur in Cambodia
  • Veasna Duong, Institut Pasteur in Cambodia
  • Sophie Goyet, Formerly- Regional Emerging Diseases Intervention (REDI) Centre
  • Jeremy Brett, Sanofi Pasteur
  • Arnaud Tarantola, Institut Pasteur in Cambodia
  • Philippe Cavailler, Institut Pasteur in Cambodia
Abstract
Background
Dengue is a major contributor to morbidity in children aged twelve and below throughout Cambodia; the 2012 epidemic season was the most severe in the country since 2007, with more than 42,000 reported (suspect or confirmed) cases.
Methods
We report basic epidemiological characteristics in a series of 701 patients at the National Paediatric Hospital in Cambodia, recruited during a prospective clinical study (2011–2012). To more fully explore this cohort, we examined climatic factors using multivariate negative binomial models and spatial clustering of cases using spatial scan statistics to place the clinical study within a larger epidemiological framework.
Results
We identify statistically significant spatial clusters at the urban village scale, and find that the key climatic predictors of increasing cases are weekly minimum temperature, median relative humidity, but find a negative association with rainfall maximum, all at lag times of 1–6 weeks, with significant effects extending to 10 weeks.
Conclusions
Our results identify clustering of infections at the neighbourhood scale, suggesting points for targeted interventions, and we find that the complex interactions of vectors and climatic conditions in this setting may be best captured by rising minimum temperature, and median (as opposed to mean) relative humidity, with complex and limited effects from rainfall. These results suggest that real-time cluster detection during epidemics should be considered in Cambodia, and that improvements in weather data reporting could benefit national control programs by allow greater prioritization of limited health resources to both vulnerable populations and time periods of greatest risk. Finally, these results add to the increasing body of knowledge suggesting complex interactions between climate and dengue cases that require further targeted research.
Disciplines
Publication Date
2014
DOI
https://doi.org/10.1186/1471-2458-14-658
Citation Information
Andrew A. Lover, Philippe Buchy, Anne Rachline, Duch Moniboth, et al.. "Spatial epidemiology and climatic predictors of paediatric dengue infections captured via sentinel site surveillance, Phnom Penh Cambodia 2011–2012" BMC Public Health (2014)
Available at: http://works.bepress.com/andrew-lover/7/
Creative Commons license
Creative Commons License
This work is licensed under a Creative Commons CC_BY International License.