ABSTRACT
The aim of this study was to analyze the spatio-temporal distribution and determinants of the 2017 dengue epidemic in Burkina Faso. A principal component analysis of meteorological and environmental factors was performed to reduce dimensions and avoid collinearities. An initial generalized additive model assessed the impact of the components derived from this analysis on dengue incidence. Dengue incidence increased mainly with relative humidity, precipitation, normalized difference vegetation index and minimum temperature with an 8-week lag. A Kulldoff Satscan scan was used to identify high-risk dengue clusters, and a second generalized additive model assessed the risk of a health area being at high risk according to land-use factors. The spatio-temporal distribution of dengue fever was heterogeneous and strongly correlated with meteorological factors. The rural communes of Sabaa and Koubri were the areas most at risk. This study provides useful information for planning targeted dengue control strategies in Burkina Faso.
ABSTRACT
Dengue is now a major health concern in sub-Saharan Africa. Understanding the influence of local meteorological factors on the incidence of dengue is an important element for better prediction and control of this disease. This study aims to assess the impact of meteorological factors on dengue transmission in the central region of Burkina Faso. We analyzed the lagged effects of meteorological factors on the weekly incidence of dengue from 2017 to 2019 in the central region of Burkina Faso using a General Additive Model. The results show that maximum and minimum temperature, relative humidity, and wind speed have a significant non-linear effect on dengue cases in the region with 83% of case variance explained. The optimal temperature that increases dengue cases was 27°C to 32°C for the maximum temperature and 18°C to 20°C for the minimum temperature with a decrease beyond that. The maximum temperature shifted by six weeks had the best correlation with dengue incidence. The estimated number of dengue cases increases as the maximum relative humidity increases from 15 to 45% and then from 60 to 70%. In general, an increase in daily wind speed is estimated to decrease the number of daily dengue cases. The relationship between rainfall and dengue cases was not significant. This study provides local information about the effect of meteorological factors on dengue that should help improve predictive models of dengue cases in Burkina Faso and contribute to the control of this disease.
ABSTRACT
BACKGROUND: Burkina Faso experienced an epidemic resurgence of dengue in 2016, which led to the implementation of several control strategies. In order to allow a better adaptation of these strategies, we studied the spatio-temporal distribution of dengue. METHODS: Monthly dengue cases from 2016 to 2019, aggregated at the health district level, were used to map the crude incidence, excess risk, and smoothed incidence of dengue in Burkina Faso with GeoDa software. A Kulldoff scan on Satscan software was then used to identify spatio-temporal clustering of cases. RESULTS: The results show that the distribution of dengue fever across the health districts of Burkina Faso is heterogeneous. Dengue was considered non-endemic in 9 out of the 70 health districts, minimally endemic in 45 districts (< 10 incidences), moderately endemic (10-100 incidences) in 12 districts, and highly endemic (> 100 incidences) in 4 districts. The main cluster covered the health districts of Baskuy, Nongr-massom, Sig-noghin, Boulmiougou, and Bogodogo. The months of October and November corresponded to the peak of cases and a significant temporal cluster in 2017. CONCLUSION: This study identified the spatial and temporal clustering of dengue cases in Burkina Faso. These results may help to develop better preventive strategies.
