Ouédraogo Jean Claude Romaric Pingdwindé, Ilboudo Sylvain, Tetteh Richard Joshua, Kyei Charles, Lougué Siaka, Ouédraogo Wendlasida Thomas, Ouédraogo Salfo, Dosoo David, Asante Kwaku Poku, Savadogo Léon Gueswendé Blaise
Laboratoire de Développement de Médicament (LADME), Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso.
Département de Médecine Traditionnelle, Pharmacopée et Pharmacie (MEPHATRA-Ph), Institut de Recherche en Sciences de la Santé (IRSS)/CNRST, Ouagadougou, Burkina Faso.
PLoS Negl Trop Dis. 2025 Jul 28;19(7):e0013356. doi: 10.1371/journal.pntd.0013356. eCollection 2025 Jul.
Dengue is endemic in Burkina Faso with sporadic outbreaks during the decade 2011-2021. Dengue control depends on the ability to predict future outbreaks. This study aimed to forecast dengue cases using historical data between 2016 and 2021.
The study covered the Central Region, Burkina Faso, with dengue monthly data from the National System of Health Information (SNIS) and environmental data from the National Agency of Meteorology (ANAM). The Autoregressive Distributed Lag (ARDL) model was performed to forecast dengue cases between 2022 and 2025.
Dengue cases increased gradually between 2016 and 2021, with seasonal spikes during the year. The 95 per cent confidence interval exceeds 5000 cases by 2023 and reaches about 10,000 cases by 2025. From the ARDL results, the lagged variable Dengue cases (-1) showed a strong positive association (coefficient = 0.76; p-value = 0.00) and the variable Dengue cases (-2) a negative association (coefficient = -0.47; p-value = 0.01). The Population statistically impacted dengue incidence (coefficient = 0.00; p-value of 0.01). Relative humidity (-1) and Relative humidity (-4) positively affected dengue cases (coefficient = 114.26; p-value = 0.00 and 90.84; p-value = 0.00 respectively). Furthermore, Rainfall (-4) had a negative influence on dengue incidence (Coefficient = -6.91; p-value = 0.00. D.Minimum temperature (-3) positively influenced dengue cases (Coefficient = 223.20; p-value = 0.01). D.Wind speed showed a negative relationship (Coefficient = -925.31; p-value = 0.02), while D. Wind speed (-3) had a positive relationship (Coefficient = 875.04; p-value = 0.02). In addition, the ARDL long-run results revealed a positive association between dengue cases and population size (p-value = 0.02), Relative humidity (p-value = 0.01), and D.Minimum temperature (p-value = 0.02), and a negative association with Rainfall (p-value = 0.04).
Dengue cases are forecasted to increase in the Central Region between 2022 and 2025. It is then crucial to develop long-term interventions against dengue, integrated with interventions for other neglected tropical diseases.
登革热在布基纳法索呈地方性流行,在2011年至2021年的十年间有零星疫情爆发。登革热防控依赖于预测未来疫情爆发的能力。本研究旨在利用2016年至2021年的历史数据预测登革热病例。
该研究覆盖布基纳法索中部地区,使用了国家卫生信息系统(SNIS)的登革热月度数据以及国家气象机构(ANAM)的环境数据。采用自回归分布滞后(ARDL)模型预测2022年至2025年的登革热病例。
2016年至2021年期间登革热病例逐渐增加,全年有季节性高峰。到2023年,95%置信区间超过5000例,到2025年达到约10000例。根据ARDL结果,滞后变量登革热病例(-1)显示出强正相关(系数 = 0.76;p值 = 0.00),变量登革热病例(-2)呈负相关(系数 = -0.47;p值 = 0.01)。人口数量对登革热发病率有统计学影响(系数 = 0.00;p值为0.01)。相对湿度(-1)和相对湿度(-4)对登革热病例有正向影响(系数分别为114.26;p值 = 0.00和90.84;p值 = 0.00)。此外,降雨量(-4)对登革热发病率有负面影响(系数 = -6.91;p值 = 0.00)。最低温度(-3)对登革热病例有正向影响(系数 = 223.20;p值 = 0.01)。风速显示出负相关(系数 = -925.31;p值 = 0.02),而风速(-3)呈正相关(系数 = 875.04;p值 = 0.02)。此外,ARDL长期结果显示登革热病例与人口规模(p值 = 0.02)、相对湿度(p值 = 0.01)和最低温度(p值 = 0.02)呈正相关,与降雨量(p值 = 0.04)呈负相关。
预计2022年至2025年布基纳法索中部地区登革热病例将增加。因此,制定针对登革热的长期干预措施并与其他被忽视热带病的干预措施相结合至关重要。