Predicting Malaria Transmission Dynamics in Dangassa, Mali

A Novel Approach Using Functional Generalized Additive Models

Bibliographic Data

ID15464707
AuthorsFrançois Freddy Ateba (0000-0003-1171-7288, University of Buea), Manuel Febrero–Bande (0000-0002-9536-2973, Universidade de Santiago de Compostela), Manuel Febrero-Bande (Universidade de Santiago de Compostela), Issaka Sagara (0000-0002-8555-9983, Université des Sciences, des Techniques et des Technologies de Bamako), Nafomon Sogoba (0000-0003-2926-220X, Malaria Research and Training Center, Faculty of Medicine, Pharmacy and Dentistry, University of Sciences, Techniques and Technologies of Bamako, Bamako BP 1805, Mali), Mahamoudou Touré (0000-0001-6238-5063, Malaria Research and Training Center, Faculty of Medicine, Pharmacy and Dentistry, University of Sciences, Techniques and Technologies of Bamako, Bamako BP 1805, Mali), Daouda Sanogo (0009-0007-1152-5231, Malaria Research and Training Center, Faculty of Medicine, Pharmacy and Dentistry, University of Sciences, Techniques and Technologies of Bamako, Bamako BP 1805, Mali), Ayouba Diarra (Malaria Research and Training Center, Faculty of Medicine, Pharmacy and Dentistry, University of Sciences, Techniques and Technologies of Bamako, Bamako BP 1805, Mali), Andoh Magdalene Ngitah (University of Buea), Peter J Winch (0000-0001-8569-5507, Johns Hopkins University), Jeffrey Shaffer (Tulane University), Jeffrey G Shaffer (0000-0002-3941-3772, Tulane University), Donald J Krogstad (0000-0002-7972-9667, Tulane University), Hannah Fritz (0000-0002-1895-8132, Johns Hopkins University), Hannah C Marker (Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA), Jean Gaudart (0000-0001-9006-5729, Inserm), Seydou Doumbia (0000-0003-1637-5600, Université des Sciences, des Techniques et des Technologies de Bamako, corresponding author)
Year2020
Volume17
Issue17
Pages6339-6339
Publication date2020-08-31
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph17176339
PMID32878174
OpenAlexW3082503857
LanguageEN
References cited24

Mali aims to reach the pre-elimination stage of malaria by the next decade. This study used functional regression models to predict the incidence of malaria as a function of past meteorological patterns to better prevent and to act proactively against impending malaria outbreaks. All data were collected over a five-year period (2012-2017) from 1400 persons who sought treatment at Dangassa's community health center. Rainfall, temperature, humidity, and wind speed variables were collected. Functional Generalized Spectral Additive Model (FGSAM), Functional Generalized Linear Model (FGLM), and Functional Generalized Kernel Additive Model (FGKAM) were used to predict malaria incidence as a function of the pattern of meteorological indicators over a continuum of the 18 weeks preceding the week of interest. Their respective outcomes were compared in terms of predictive abilities. The results showed that (1) the highest malaria incidence rate occurred in the village 10 to 12 weeks after we observed a pattern of air humidity levels >65%, combined with two or more consecutive rain episodes and a mean wind speed <1.8 m/s; (2) among the three models, the FGLM obtained the best results in terms of prediction; and (3) FGSAM was shown to be a good compromise between FGLM and FGKAM in terms of flexibility and simplicity. The models showed that some meteorological conditions may provide a basis for detection of future outbreaks of malaria. The models developed in this paper are useful for implementing preventive strategies using past meteorological and past malaria incidence

Biological system · Biology · Dynamics (music · Generalized additive model · Malaria · Statistics · Telecommunications · Transmission (telecommunications · Computer Science · COVID-19 epidemiological studies · Malaria Research and Control · Mathematics · Mosquito-borne diseases and control · Psychology · Immunology

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