Spatial Modeling of Environmental Sanitation as the Distribution Determinant of Malaria Cases in Lahat Regency

Sunarsih, Elvi; Purba, Imelda Gernauli; Suheryanto,; Rosyada, Amrina; Septiawati, Dwi

doi:10.2991/ahsr.k.200612.023

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…Data analysis was carried out using spatial analysis and spatial patterns of research data [6], [7], [8]. Based on Figure 2, Moran index value is 0.263, indicating that there was a positive autocorrelation, which means that malaria cases in Muara Enim Regency in 2017 occurred in groups.…”

Section: Methodsmentioning

confidence: 99%

Spatial Pattern Analysis of Malaria Cases in Muara Enim Regency using Moran Index and Local Indicator Spatial Autocorrelation

Sunarsih

Zulkarnain

Hanum

et al. 2021

Open Access Maced J Med Sci

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BACKGROUND: Malaria is a disease which still becomes a global health issue, including in Indonesia, because of its potential vector which can infect and spread causing a wide impact. Until currently, malaria still becomes a serious threat to people living in tropical and subtropical areas. Muara Enim Regency is a malaria-endemic regency with the second highest positive case in South Sumatra Province, with an API value in 2019 was 0.18/1000 population. AIM: The current research was performed to identify and change the spatial pattern of malaria cases, environmental variability (rainfall), population density using Moran index and local indicator spatial autocorrelation (LISA), and habitat in Muara Enim Regency. METHODS: This research employed a quantitative research design with an analytical survey research method and a case–control approach. This research method was designed using a geographic information systems approach. RESULTS: The results of the study showed that malaria cases in Muara Enim Regency in 2017 occurred in groups with a Moran index of 0.263, indicating a positive autocorrelation. Meanwhile, based on the LISA index, it was found that there were three districts categorized as high-high (HH) (quadrant 1), those are Lawang Kidul District, Muara Enim District, and Gunung Megang District, while in the low-high (LH) category (quadrant 2), there was Benakat District. In 2018, it also occurred in groups where the Moran index was 0.129, indicating a positive autocorrelation, while the LISA index found that there was one district categorized as HH (quadrant 1) which is Lawang Kidul District, and district categorized as LH (quadrant 2) was Gunung Megang District. In 2019, it happened randomly or spread with a Moran index of −0.022 indicating a negative autocorrelation, while based on the LISA index, it was found that there was one subdistrict categorized as HH category (quadrant 1) which is Lawang Kidul District and two districts categorized as LH (quadrant 2) which are Semende Darat Laut and Rambang Niru. CONCLUSION: There was a change in the results of Moran index from a positive autocorrelation in 2017, 2018, to a negative autocorrelation in 2019 with the results of the LISA index for malaria cases in 2017–2019 in one subdistrict, namely, Lawang Kidul District categorized as a HH category (quadrant 1).

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Section: Methodsmentioning

confidence: 99%

Spatial Pattern Analysis of Malaria Cases in Muara Enim Regency using Moran Index and Local Indicator Spatial Autocorrelation

Sunarsih

Zulkarnain

Hanum

et al. 2021

Open Access Maced J Med Sci

Self Cite

View full text Add to dashboard Cite

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“…Screens in home ventilation are typically considered a preventive measure to protect against Anopheles mosquitoes, which can be malaria vectors. However, damage or holes in the screen, which allow mosquitoes to pass through the barrier, can still increase the risk of Anopheles mosquitoes entering the house (Saili et al, 2024;Sunarsih et al, 2020;Sutriyawan et al, 2021). The chances of mosquito entry can be increased by several factors, such as the size of the holes or damage to the screen, the activity of mosquitoes at night when they search for blood sources, and the attractiveness of humans as a source of blood meal (Sulistyawati et al, 2020;Tizifa et al, 2022).…”

Section: Figure 1 Data On Positive Cases Of Malaria In 2022 Based On ...mentioning

confidence: 99%

Investigating Malaria Susceptibility in Central Maluku District: A Focus on Anopheles Mosquito Habitats

Firmansyah,

Parulian,

Kristiawan

et al. 2024

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Malaria remains a formidable challenge to global public health, with an estimated 241 million cases reported across 85 endemic countries in 2020. Within this context, Indonesia, and particularly the Central Maluku Regency, has reported a notable burden of the disease, evidenced by 102 confirmed cases in 2022 as per the annual parasite incidence (API) data, highlighting indigenous transmissions in specific locales. This research was conducted to assess the susceptibility to malaria within the operational area of the Hila Perawatan Primary Healthcare Centre (Puskesmas), situated in the Leihitu sub-district of Ambon Island, through an examination of Anopheles mosquito breeding sites, larval densities, and habitat indices. Employing a descriptive research design, this cross-sectional observational study was carried out on October 26-27, 2023, to meticulously document the ecological footprint of the Anopheles mosquito, particularly Anopheles farauti. Findings reveal a habitat index (HI) of 33% in Kaitetu village with a larval density of 20%, indicating a significant presence of Anopheles farauti larvae. These findings suggest that environmental and behavioral factors within households, such as the use of gauze and ceilings, nocturnal activities, application of mosquito repellents, wearing of long-sleeved clothing, and utilization of mosquito nets, are pivotal in influencing malaria transmission dynamics. This study underscores the imperative of integrating environmental management with community engagement strategies to mitigate malaria transmission in endemic regions. The results not only provide a nuanced understanding of the Anopheles mosquito's breeding patterns and its implications for malaria transmission but also offer a foundational basis for tailoring targeted interventions aimed at reducing the malaria burden in the Central Maluku District.

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Spatial Modeling of Environmental Sanitation as the Distribution Determinant of Malaria Cases in Lahat Regency

Cited by 2 publications

References 8 publications

Spatial Pattern Analysis of Malaria Cases in Muara Enim Regency using Moran Index and Local Indicator Spatial Autocorrelation

Spatial Pattern Analysis of Malaria Cases in Muara Enim Regency using Moran Index and Local Indicator Spatial Autocorrelation

Investigating Malaria Susceptibility in Central Maluku District: A Focus on Anopheles Mosquito Habitats

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