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.