Malaria in Kenya during 2020: malaria indicator survey and suitability mapping for understanding spatial variations in prevalence, intervention and risk

C. Kioko; Justine Ianthe Blanford

doi:10.5194/agile-giss-4-31-2023

Malaria in Kenya during 2020: malaria indicator survey and suitability mapping for understanding spatial variations in prevalence, intervention and risk

C. Kioko^*, Justine Ianthe Blanford

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

Despite the availability of effective interventions malaria continues to be a major public health issue in Kenya, where young children and pregnant women are particularly vulnerable. In this study we examined the spatial distribution of malaria incidence and how this relates to the environmental conditions required for malaria in 2020. The Kenya Malaria Indicator Survey (N=11,549) for 2020 was used with the Local Indicators of Spatial Autocorrelation (LISA) method to determine spatial clusters of malaria and assess their significance as well as interventions in use. Climate data was used with a Fuzzy Overlay method to create malaria risk maps. The findings suggest that malaria incidence is not evenly distributed across Kenya, with some regions having higher rates of transmission and others having lower rates. High-rate clusters of malaria and high-risk areas of malaria transmission could benefit from increased vector control measures.

Original language	English
Title of host publication	26th AGILE Conference on Geographic Information Science
Subtitle of host publication	Spatial data for design
Editors	P. van Oosterom, H. Ploeger, A. Mansourian, S. Scheider, R. Lemmens, B. van Loenen
Publisher	Copernicus
Pages	1-5
Number of pages	5
Volume	4
DOIs	https://doi.org/10.5194/agile-giss-4-31-2023
Publication status	Published - 6 Jun 2023
Event	26th AGILE Conference on Geographic Information Science, AGILE 2023: Spatial data for design - Delft, Netherlands Duration: 13 Jun 2023 → 16 Jun 2023 Conference number: 26 https://agile-online.org/conference-2023

Publication series

Name	AGILE: GIScience Series
Publisher	Copernicus

Conference

Conference	26th AGILE Conference on Geographic Information Science, AGILE 2023
Abbreviated title	AGILE 2023
Country/Territory	Netherlands
City	Delft
Period	13/06/23 → 16/06/23
Internet address	https://agile-online.org/conference-2023

Keywords

Geo-health

UN SDGs

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

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10.5194/agile-giss-4-31-2023Licence: CC BY

ArticleFinal published version, 896 KBLicence: CC BY

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Kioko, C., & Blanford, J. I. (2023). Malaria in Kenya during 2020: malaria indicator survey and suitability mapping for understanding spatial variations in prevalence, intervention and risk. In P. van Oosterom, H. Ploeger, A. Mansourian, S. Scheider, R. Lemmens, & B. van Loenen (Eds.), 26th AGILE Conference on Geographic Information Science : Spatial data for design (Vol. 4, pp. 1-5). Article 31 (AGILE: GIScience Series). Copernicus. https://doi.org/10.5194/agile-giss-4-31-2023

Kioko, C. ; Blanford, Justine Ianthe. / Malaria in Kenya during 2020: malaria indicator survey and suitability mapping for understanding spatial variations in prevalence, intervention and risk. 26th AGILE Conference on Geographic Information Science : Spatial data for design. editor / P. van Oosterom ; H. Ploeger ; A. Mansourian ; S. Scheider ; R. Lemmens ; B. van Loenen. Vol. 4 Copernicus, 2023. pp. 1-5 (AGILE: GIScience Series).

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abstract = "Despite the availability of effective interventions malaria continues to be a major public health issue in Kenya, where young children and pregnant women are particularly vulnerable. In this study we examined the spatial distribution of malaria incidence and how this relates to the environmental conditions required for malaria in 2020. The Kenya Malaria Indicator Survey (N=11,549) for 2020 was used with the Local Indicators of Spatial Autocorrelation (LISA) method to determine spatial clusters of malaria and assess their significance as well as interventions in use. Climate data was used with a Fuzzy Overlay method to create malaria risk maps. The findings suggest that malaria incidence is not evenly distributed across Kenya, with some regions having higher rates of transmission and others having lower rates. High-rate clusters of malaria and high-risk areas of malaria transmission could benefit from increased vector control measures.",

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note = "26th AGILE Conference on Geographic Information Science, AGILE 2023 : Spatial data for design, AGILE 2023 ; Conference date: 13-06-2023 Through 16-06-2023",

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Kioko, C & Blanford, JI 2023, Malaria in Kenya during 2020: malaria indicator survey and suitability mapping for understanding spatial variations in prevalence, intervention and risk. in P van Oosterom, H Ploeger, A Mansourian, S Scheider, R Lemmens & B van Loenen (eds), 26th AGILE Conference on Geographic Information Science : Spatial data for design. vol. 4, 31, AGILE: GIScience Series, Copernicus, pp. 1-5, 26th AGILE Conference on Geographic Information Science, AGILE 2023, Delft, Netherlands, 13/06/23. https://doi.org/10.5194/agile-giss-4-31-2023

Malaria in Kenya during 2020: malaria indicator survey and suitability mapping for understanding spatial variations in prevalence, intervention and risk. / Kioko, C.; Blanford, Justine Ianthe.
26th AGILE Conference on Geographic Information Science : Spatial data for design. ed. / P. van Oosterom; H. Ploeger; A. Mansourian; S. Scheider; R. Lemmens; B. van Loenen. Vol. 4 Copernicus, 2023. p. 1-5 31 (AGILE: GIScience Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Blanford, Justine Ianthe

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Y1 - 2023/6/6

N2 - Despite the availability of effective interventions malaria continues to be a major public health issue in Kenya, where young children and pregnant women are particularly vulnerable. In this study we examined the spatial distribution of malaria incidence and how this relates to the environmental conditions required for malaria in 2020. The Kenya Malaria Indicator Survey (N=11,549) for 2020 was used with the Local Indicators of Spatial Autocorrelation (LISA) method to determine spatial clusters of malaria and assess their significance as well as interventions in use. Climate data was used with a Fuzzy Overlay method to create malaria risk maps. The findings suggest that malaria incidence is not evenly distributed across Kenya, with some regions having higher rates of transmission and others having lower rates. High-rate clusters of malaria and high-risk areas of malaria transmission could benefit from increased vector control measures.

AB - Despite the availability of effective interventions malaria continues to be a major public health issue in Kenya, where young children and pregnant women are particularly vulnerable. In this study we examined the spatial distribution of malaria incidence and how this relates to the environmental conditions required for malaria in 2020. The Kenya Malaria Indicator Survey (N=11,549) for 2020 was used with the Local Indicators of Spatial Autocorrelation (LISA) method to determine spatial clusters of malaria and assess their significance as well as interventions in use. Climate data was used with a Fuzzy Overlay method to create malaria risk maps. The findings suggest that malaria incidence is not evenly distributed across Kenya, with some regions having higher rates of transmission and others having lower rates. High-rate clusters of malaria and high-risk areas of malaria transmission could benefit from increased vector control measures.

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BT - 26th AGILE Conference on Geographic Information Science

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PB - Copernicus

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Kioko C , Blanford JI. Malaria in Kenya during 2020: malaria indicator survey and suitability mapping for understanding spatial variations in prevalence, intervention and risk. In van Oosterom P, Ploeger H, Mansourian A, Scheider S, Lemmens R, van Loenen B, editors, 26th AGILE Conference on Geographic Information Science : Spatial data for design. Vol. 4. Copernicus. 2023. p. 1-5. 31. (AGILE: GIScience Series). doi: 10.5194/agile-giss-4-31-2023

Malaria in Kenya during 2020: malaria indicator survey and suitability mapping for understanding spatial variations in prevalence, intervention and risk

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

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Cite this