An Assessment on the Hidden Ecological Factors of the Incidence of Malaria

Babagana Modu; A. Taufiq Asyhari; Savas Konur; Yonghong Peng

doi:10.3390/is4si-2017-04001

An Assessment on the Hidden Ecological Factors of the Incidence of Malaria

Babagana Modu, A. Taufiq Asyhari, Savas Konur, Yonghong Peng

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Abstract

Confounding effects of climatic factors temporally contribute to the prevalence of malaria. In this study, we explore a new framework for assessment and identification of hidden ecological factors to the incidence of malaria. A statistical technique, partial least squares path modeling and exploratory factor analysis, is employed to identify hidden ecological factors. Three hidden factors are identified: Factor I is related to minimum temperature and relative humidity, Factor II is related to maximum temperature and solar radiation and Factor III is related to precipitation and wind speed, respectively. Factor I is identified as the most influential hidden ecological factor of malaria incidence in the study area, as evaluated by communality and Dillon-Goldstein’s indices.

Original language	English
Article number	131
Number of pages	2
Journal	Proceedings
Volume	1
Issue number	3
DOIs	https://doi.org/10.3390/is4si-2017-04001
Publication status	Published - 9 Jun 2017
Event	IS4SI 2017 Summit Digitalisation for a Sustainable Society - Gothenburg, Sweden Duration: 12 Jun 2017 → 16 Jun 2019

Bibliographical note

This article belongs to the Proceedings of the IS4SI 2017 Summit DIGITALISATION FOR A SUSTAINABLE SOCIETY)

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Keywords

malaria incidence
climatic factors
structural equation modeling
partial least square model and hidden factors

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3390/is4si-2017-04001Licence: CC BY

PublishedFinal published version, 564 KBLicence: CC BY

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title = "An Assessment on the Hidden Ecological Factors of the Incidence of Malaria",

abstract = "Confounding effects of climatic factors temporally contribute to the prevalence of malaria. In this study, we explore a new framework for assessment and identification of hidden ecological factors to the incidence of malaria. A statistical technique, partial least squares path modeling and exploratory factor analysis, is employed to identify hidden ecological factors. Three hidden factors are identified: Factor I is related to minimum temperature and relative humidity, Factor II is related to maximum temperature and solar radiation and Factor III is related to precipitation and wind speed, respectively. Factor I is identified as the most influential hidden ecological factor of malaria incidence in the study area, as evaluated by communality and Dillon-Goldstein{\textquoteright}s indices.",

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author = "Babagana Modu and Asyhari, {A. Taufiq} and Savas Konur and Yonghong Peng",

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AU - Asyhari, A. Taufiq

AU - Konur, Savas

AU - Peng, Yonghong

N1 - This article belongs to the Proceedings of the IS4SI 2017 Summit DIGITALISATION FOR A SUSTAINABLE SOCIETY) © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

PY - 2017/6/9

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N2 - Confounding effects of climatic factors temporally contribute to the prevalence of malaria. In this study, we explore a new framework for assessment and identification of hidden ecological factors to the incidence of malaria. A statistical technique, partial least squares path modeling and exploratory factor analysis, is employed to identify hidden ecological factors. Three hidden factors are identified: Factor I is related to minimum temperature and relative humidity, Factor II is related to maximum temperature and solar radiation and Factor III is related to precipitation and wind speed, respectively. Factor I is identified as the most influential hidden ecological factor of malaria incidence in the study area, as evaluated by communality and Dillon-Goldstein’s indices.

AB - Confounding effects of climatic factors temporally contribute to the prevalence of malaria. In this study, we explore a new framework for assessment and identification of hidden ecological factors to the incidence of malaria. A statistical technique, partial least squares path modeling and exploratory factor analysis, is employed to identify hidden ecological factors. Three hidden factors are identified: Factor I is related to minimum temperature and relative humidity, Factor II is related to maximum temperature and solar radiation and Factor III is related to precipitation and wind speed, respectively. Factor I is identified as the most influential hidden ecological factor of malaria incidence in the study area, as evaluated by communality and Dillon-Goldstein’s indices.

KW - malaria incidence

KW - climatic factors

KW - structural equation modeling

KW - partial least square model and hidden factors

UR - http://www.mendeley.com/research/assessment-hidden-ecological-factors-incidence-malaria

U2 - 10.3390/is4si-2017-04001

DO - 10.3390/is4si-2017-04001

M3 - Conference article

SN - 2504-3900

VL - 1

JO - Proceedings

JF - Proceedings

IS - 3

M1 - 131

T2 - IS4SI 2017 Summit Digitalisation for a Sustainable Society

Y2 - 12 June 2017 through 16 June 2019

ER -

An Assessment on the Hidden Ecological Factors of the Incidence of Malaria

Abstract

Bibliographical note

Keywords

UN SDGs

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