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Spatial Association Between Dengue Incidence and Larvae-Free Index: A Bivariate Spatial Autocorrelation Analysis in Surabaya, Indonesia

JURNAL KESEHATAN LINGKUNGAN (Journal of Environmental Health) · Vol. 18 No. 4 (2026) · hlm. 366–379

DOI
10.20473/jkl.v18i4.2026.366-379
ISSN
2540-881X, 1829-7285
Terbit
2026-10-18
Penerbit
Universitas Airlangga
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-nc-sa/4.0

Abstrak

Introduction: Dengue transmission in Surabaya, Indonesia, varies across urban villages, but its spatial relationship with vector-control performance remains insufficiently understood. This study examined dengue incidence, the Larvae-Free Index (LFI), and their bivariate spatial association. Methods: This spatial ecological study analysed annual confirmed dengue cases and LFI data from all 154 urban villages in Surabaya during 2020–2025, obtained from the Surabaya City Health Office. Incidence was calculated per 10,000 population. Multiplicative seasonal decomposition characterised monthly case patterns. Global Moran’s I and Local Indicators of Spatial Association (LISA) assessed spatial clustering, while Bivariate Moran’s I and Bivariate LISA (BiLISA) examined associations between local dengue incidence and neighbouring LFI values. Results and Discussion: Dengue incidence clustered significantly in five of six years (I = 0.0784–0.2727), except 2024 (I = 0.0280; p = 0.222). LFI clustered significantly every year (I = 0.2190–0.3087; p = 0.001). Bivariate Moran’s I was negative in five years and significant in 2020 (−0.0805; p = 0.022), 2021 (−0.0875; p = 0.019), and 2025 (−0.1046; p = 0.003), indicating spatial associations between higher incidence and lower neighbouring LFI. In 2025, LISA identified 10 High–High and 15 Low–Low dengue clusters. BiLISA identified High–Low villages annually, with Ujung and Pegirian recurring most frequently. Conclusion: Dengue incidence and LFI exhibited spatial clustering, with significant inverse spatial associations in three years. LFI should complement, rather than replace, dengue surveillance when identifying priority areas for targeted vector control.

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  • Universitas Airlangga
  • Universitas Halu Oleo
  • Universitas Jember
  • Universitas Negeri Surabaya
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Rekan penulisOrganisasiArtikel bersama
R AzizahAfiliasi tidak diketahui10
Zainul Amiruddin ZakariaAfiliasi tidak diketahui8
Juhairiyah JuhairiyahAfiliasi tidak diketahui5
Triwibowo Ambar GarjitoAfiliasi tidak diketahui5
Rania Ichwana WicaksonoAfiliasi tidak diketahui5
Soedjajadi KemanAfiliasi tidak diketahui5
Shamsul Bahari ShamsudinAfiliasi tidak diketahui5
Wanti WantiUniversitas Halu Oleo4
Dicky AndiarsaAfiliasi tidak diketahui4
Retno AdriyaniAfiliasi tidak diketahui4
Liestiana IndriyatiAfiliasi tidak diketahui4
Renaningtyas NityasaniAfiliasi tidak diketahui4
Isnawati -Universitas Negeri Surabaya4
Edza Aria WikurendraAfiliasi tidak diketahui4
Kuntoro KuntoroAfiliasi tidak diketahui3
Sri SubektiAfiliasi tidak diketahui3
Juliana Binti JalaludinAfiliasi tidak diketahui3
Azmi Nur FadlillahUniversitas Airlangga2
Rachmah IndawatiAfiliasi tidak diketahui2
Farapti FaraptiUniversitas Airlangga2
Globila NurikaUniversitas Jember2
Endah Nurul KumarijatiAfiliasi tidak diketahui2
Nahdhiah Khoirun NisaUniversitas Airlangga2
I Gde Raju Sathya MurtiUniversitas Airlangga2
Asriani MuflihahUniversitas Airlangga2
Atik Choirul HidajahAfiliasi tidak diketahui2
Corie Indria PrasastiAfiliasi tidak diketahui2
Sarva Mangala PraveenaAfiliasi tidak diketahui2

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Sumber metadata: OAI-PMH (metadata jurnal) https://e-journal.unair.ac.id/JKL/oai, pertama di-harvest 9 Nov 2026, terakhir terlihat 9 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Spatial Association Between Dengue Incidence and Larvae-Free Index: A Bivariate Spatial Autocorrelation Analysis in Surabaya, Indonesia</dc:title>
	<dc:creator>Khuliyah Candraning Diyanah</dc:creator>
	<dc:creator>Ririh Yudhastuti</dc:creator>
	<dc:creator>Lilis Sulistyorini</dc:creator>
	<dc:creator>Hari Basuki Notobroto</dc:creator>
	<dc:creator>Zida Husnina</dc:creator>
	<dc:creator>Muhammad Rasyid Ridha</dc:creator>
	<dc:creator>Babucarr Jassey</dc:creator>
	<dc:creator>Aditya Sukma Pawitra</dc:creator>
	<dc:creator>Diva Alishya Shafwah</dc:creator>
	<dc:creator>Rahmat Dapari</dc:creator>
	<dc:creator>Nafi'atul Irbah</dc:creator>
	<dc:creator>Wira Satya Nugraha Wicaksono</dc:creator>
	<dc:subject xml:lang="en-US">Aedes aegypti</dc:subject>
	<dc:subject xml:lang="en-US">Dengue</dc:subject>
	<dc:subject xml:lang="en-US">Larvae-Free Index</dc:subject>
	<dc:subject xml:lang="en-US">Spatial Analysis</dc:subject>
	<dc:subject xml:lang="en-US">Urbanisation</dc:subject>
	<dc:description xml:lang="en-US">Introduction: Dengue transmission in Surabaya, Indonesia, varies across urban villages, but its spatial relationship with vector-control performance remains insufficiently understood. This study examined dengue incidence, the Larvae-Free Index (LFI), and their bivariate spatial association. Methods: This spatial ecological study analysed annual confirmed dengue cases and LFI data from all 154 urban villages in Surabaya during 2020–2025, obtained from the Surabaya City Health Office. Incidence was calculated per 10,000 population. Multiplicative seasonal decomposition characterised monthly case patterns. Global Moran’s I and Local Indicators of Spatial Association (LISA) assessed spatial clustering, while Bivariate Moran’s I and Bivariate LISA (BiLISA) examined associations between local dengue incidence and neighbouring LFI values. Results and Discussion: Dengue incidence clustered significantly in five of six years (I = 0.0784–0.2727), except 2024 (I = 0.0280; p = 0.222). LFI clustered significantly every year (I = 0.2190–0.3087; p = 0.001). Bivariate Moran’s I was negative in five years and significant in 2020 (−0.0805; p = 0.022), 2021 (−0.0875; p = 0.019), and 2025 (−0.1046; p = 0.003), indicating spatial associations between higher incidence and lower neighbouring LFI. In 2025, LISA identified 10 High–High and 15 Low–Low dengue clusters. BiLISA identified High–Low villages annually, with Ujung and Pegirian recurring most frequently. Conclusion: Dengue incidence and LFI exhibited spatial clustering, with significant inverse spatial associations in three years. LFI should complement, rather than replace, dengue surveillance when identifying priority areas for targeted vector control.</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Airlangga</dc:publisher>
	<dc:date>2026-10-18</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:format>text/xml</dc:format>
	<dc:identifier>https://e-journal.unair.ac.id/JKL/article/view/97307</dc:identifier>
	<dc:identifier>10.20473/jkl.v18i4.2026.366-379</dc:identifier>
	<dc:source xml:lang="en-US">JURNAL KESEHATAN LINGKUNGAN ; Vol. 18 No. 4 (2026): JURNAL KESEHATAN LINGKUNGAN ; 366-379</dc:source>
	<dc:source>2540-881X</dc:source>
	<dc:source>1829-7285</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://e-journal.unair.ac.id/JKL/article/view/97307/41539</dc:relation>
	<dc:relation>https://e-journal.unair.ac.id/JKL/article/view/97307/41563</dc:relation>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-nc-sa/4.0</dc:rights>
</oai_dc:dc>