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Open AccessArticle

Application of Functional Data Analysis to Identify Patterns of Malaria Incidence, to Guide Targeted Control Strategies

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Sciences Economiques et Sociales de la Santé et Traitement de de l’Information Médicale (SESSTIM), Institut de Recherche pour le Développement (IRD), Institut National de la Santé et de la Recherche médicale (INSERM), Aix Marseille Université, 13005 Marseille, France
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Aix Marseille School of Economics (AMSE), Centrale Marseille, Ecoles des Hautes Etudes en Sciences Sociales (EHESS), Centre National de la Recherche Scientifique (CNRS), Aix Marseille Université, 13001 Marseille, France
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Mère et Enfant face aux Infections Tropicales (MERIT), Institut de Recherche pour le Développement (IRD), Université Paris 5, 75006 Paris, France
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Unité de Recherche Clinique Paris Nord Val de Seine (PNVS), Hôpital Bichat, Assistance Publique—Hôpitaux de Paris (AP-HP), 75018 Paris, France
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Unité Mixte de Recherche (UMR), Vecteurs-Infections Tropicales et Méditerranéennes (VITROME), Campus International Institut de Recherche pour le Développement-Université Cheikh Anta Diop (IRD-UCAD) de l’IRD, Dakar CP 18524, Senegal
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Institut de Recherche en Santé, de Surveillance Épidémiologique et de Formation (IRESSEF) Diamniadio, Dakar BP 7325, Senegal
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London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
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Aix Marseille Université, Assistance Publique—Hôpitaux de Marseille(APHM), INSERM, IRD, SESSTIM, Hop Timone, BioSTIC, Biostatistic and ICT, 13005 Marseille, France
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(11), 4168; https://doi.org/10.3390/ijerph17114168
Received: 29 April 2020 / Revised: 5 June 2020 / Accepted: 6 June 2020 / Published: 11 June 2020
(This article belongs to the Special Issue Geo-Epidemiology of Malaria)
We introduce an approach based on functional data analysis to identify patterns of malaria incidence to guide effective targeting of malaria control in a seasonal transmission area. Using functional data method, a smooth function (functional data or curve) was fitted from the time series of observed malaria incidence for each of 575 villages in west-central Senegal from 2008 to 2012. These 575 smooth functions were classified using hierarchical clustering (Ward’s method), and several different dissimilarity measures. Validity indices were used to determine the number of distinct temporal patterns of malaria incidence. Epidemiological indicators characterizing the resulting malaria incidence patterns were determined from the velocity and acceleration of their incidences over time. We identified three distinct patterns of malaria incidence: high-, intermediate-, and low-incidence patterns in respectively 2% (12/575), 17% (97/575), and 81% (466/575) of villages. Epidemiological indicators characterizing the fluctuations in malaria incidence showed that seasonal outbreaks started later, and ended earlier, in the low-incidence pattern. Functional data analysis can be used to identify patterns of malaria incidence, by considering their temporal dynamics. Epidemiological indicators derived from their velocities and accelerations, may guide to target control measures according to patterns. View Full-Text
Keywords: functional data analysis; time series clustering; malaria patterns; malaria dynamic functional data analysis; time series clustering; malaria patterns; malaria dynamic
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MDPI and ACS Style

Dieng, S.; Michel, P.; Guindo, A.; Sallah, K.; Ba, E.-H.; Cissé, B.; Carrieri, M.P.; Sokhna, C.; Milligan, P.; Gaudart, J. Application of Functional Data Analysis to Identify Patterns of Malaria Incidence, to Guide Targeted Control Strategies. Int. J. Environ. Res. Public Health 2020, 17, 4168. https://doi.org/10.3390/ijerph17114168

AMA Style

Dieng S, Michel P, Guindo A, Sallah K, Ba E-H, Cissé B, Carrieri MP, Sokhna C, Milligan P, Gaudart J. Application of Functional Data Analysis to Identify Patterns of Malaria Incidence, to Guide Targeted Control Strategies. International Journal of Environmental Research and Public Health. 2020; 17(11):4168. https://doi.org/10.3390/ijerph17114168

Chicago/Turabian Style

Dieng, Sokhna; Michel, Pierre; Guindo, Abdoulaye; Sallah, Kankoe; Ba, El-Hadj; Cissé, Badara; Carrieri, Maria P.; Sokhna, Cheikh; Milligan, Paul; Gaudart, Jean. 2020. "Application of Functional Data Analysis to Identify Patterns of Malaria Incidence, to Guide Targeted Control Strategies" Int. J. Environ. Res. Public Health 17, no. 11: 4168. https://doi.org/10.3390/ijerph17114168

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