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

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  • Sokhna Dieng

    (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)

  • Pierre Michel

    (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)

  • Abdoulaye Guindo

    (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
    Mère et Enfant face aux Infections Tropicales (MERIT), Institut de Recherche pour le Développement (IRD), Université Paris 5, 75006 Paris, France)

  • Kankoe Sallah

    (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
    Unité de Recherche Clinique Paris Nord Val de Seine (PNVS), Hôpital Bichat, Assistance Publique—Hôpitaux de Paris (AP-HP), 75018 Paris, France)

  • El-Hadj Ba

    (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)

  • Badara Cissé

    (Institut de Recherche en Santé, de Surveillance Épidémiologique et de Formation (IRESSEF) Diamniadio, Dakar BP 7325, Senegal)

  • Maria Patrizia Carrieri

    (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)

  • Cheikh Sokhna

    (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)

  • Paul Milligan

    (London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK)

  • Jean Gaudart

    (Aix Marseille Université, Assistance Publique—Hôpitaux de Marseille(APHM), INSERM, IRD, SESSTIM, Hop Timone, BioSTIC, Biostatistic and ICT, 13005 Marseille, France)

Abstract

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.

Suggested Citation

  • Sokhna Dieng & Pierre Michel & Abdoulaye Guindo & Kankoe Sallah & El-Hadj Ba & Badara Cissé & Maria Patrizia Carrieri & Cheikh Sokhna & Paul Milligan & Jean Gaudart, 2020. "Application of Functional Data Analysis to Identify Patterns of Malaria Incidence, to Guide Targeted Control Strategies," IJERPH, MDPI, vol. 17(11), pages 1-23, June.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:11:p:4168-:d:370217
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    References listed on IDEAS

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    1. Febrero-Bande, Manuel & de la Fuente, Manuel Oviedo, 2012. "Statistical Computing in Functional Data Analysis: The R Package fda.usc," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 51(i04).
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    3. Fionn Murtagh & Pierre Legendre, 2014. "Ward’s Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward’s Criterion?," Journal of Classification, Springer;The Classification Society, vol. 31(3), pages 274-295, October.
    4. Montero, Pablo & Vilar, José A., 2014. "TSclust: An R Package for Time Series Clustering," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 62(i01).
    5. Gaudart, Jean & Graffeo, Nathalie & Coulibaly, Drissa & Barbet, Guillaume & Rebaudet, Stanilas & Dessay, Nadine & Doumbo, Ogobara K. & Giorgi, Roch, 2015. "SPODT: An R Package to Perform Spatial Partitioning," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i16).
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    Cited by:

    1. Weiwei Wang & Futian Weng & Jianping Zhu & Qiyuan Li & Xiaolong Wu, 2023. "An Analytical Approach for Temporal Infection Mapping and Composite Index Development," Mathematics, MDPI, vol. 11(20), pages 1-16, October.

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