Temporal changes in land cover types and the incidence of malaria in Mangalore, India

Mohan, Venkata Raghava; Naumova, Elena N.

doi:10.7439/ijbr.v5i8.719

Cited by 8 publications

(3 citation statements)

References 21 publications

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“…Presence of malaria's vector also influenced by environment factor that affected their ability to live and growth. The variation and degree of environment's influence is large, not only through abiotic factors such as rain and temperature which affect mosquito density and parasite growth inside the vector, but also biotic factors such as deforestation, agriculture, house construction, human population and urbanization (Mohan & Naumova, 2014;Caminade et al, 2014). The impact of deforestation on temperature, rain, and humidity interacts with each other in affecting macro and micro climate in mosquito's habitat (Duarsa, 2008).…”

Section: Resultsmentioning

confidence: 99%

Climatology Influence on Malaria Cases in Alusi Community Health Center, West Southeast Maluku Regency

Sandy¹,

Ayomi²

2018

Kemas

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The west Southeast Maluku regency is a malaria endemic area with API of 29.99 / 1000 in 2014. Malaria is affected by climatology, therefore climatological changes can be used to predict increase in malaria cases. We used times series study research method of the climatology influence on malaria cases in Alusi Community Health Center. We used secondary data of malaria cases from Alusi Community Health Center and climatologic data (rainfall, wind speed, humidity temperature) from Saumlaki Meteorological, Climatology, and Geophysical Agency. The research was conducted in March-April 2016 in West Southeast Maluku Regency. The data was analysed by linear regression. The proportion of malaria cases was 38.3%; most infection occured in patients over 15 years old (71 cases). The linear regression analysis of climatological influence on malaria cases were as follows: humidity was r = 0.382; R2 = 0.146; p = 0.220, r = 0.172 temperature was; R2 = 0.03; p = 0.592, r = 0.345, rainfall was; R2 = 0.119; p = 0.272, and wind velocity was r = 0.07; R2 = 0.005; p = 0.828. We could concluded that climatology parameters showed positive correlation, but statistically insignificant relationship with malaria cases (p <0.05).

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Section: Resultsmentioning

confidence: 99%

Climatology Influence on Malaria Cases in Alusi Community Health Center, West Southeast Maluku Regency

Sandy¹,

Ayomi²

2018

Kemas

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“…A total of 2,333 finger-pricked blood samples were collected from 11 different collection sites from a period of 2012 to 2015 ( Table 1 ). The sample collection sites were selected based on previous report on the malaria endemicity in that particular Indian state and locations, such as; Delhi [ 22 ], Diphu and Guwahati from Assam [ 23 ], Shankargarh from Uttar Pradesh [ 24 ], Nadiad from Gujarat [ 17 ], Betul from Madhya Pradesh [ 25 ], Kendujhar [ 26 ] and Rourkela [ 27 ] from Odisha, Gadchiroli from Maharashtra [ 28 ], Chennai from Tamil Nadu [ 29 ] and Mangaluru from Karnataka [ 30 ]. In particular, due care has been taken to sample from areas reportedly dominated by either P .…”

Section: Methodsmentioning

confidence: 99%

Malaria diagnosis by PCR revealed differential distribution of mono and mixed species infections by Plasmodium falciparum and P. vivax in India

et al. 2018

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Malaria is a vector-borne infectious disease, caused by five different species of the genus Plasmodium, and is endemic to many tropical and sub-tropical countries of the globe. At present, malaria diagnosis at the primary health care level in India is conducted by either microscopy or rapid diagnostic test (RDT). In recent years, molecular diagnosis (by PCR assay), has emerged as the most sensitive method for malaria diagnosis. India is highly endemic to malaria and shoulders the burden of two major malaria parasites, Plasmodium falciparum and P. vivax. Previous studies using PCR diagnostic assay had unraveled several interesting facts on distribution of malaria parasites in India. However, these studies had several limitations from small sample size to limited geographical areas of sampling. In order to mitigate these limitations, we have collected finger-prick blood samples from 2,333 malaria symptomatic individuals in nine states from 11 geographic locations, covering almost the entire malaria endemic regions of India and performed all the three diagnostic tests (microscopy, RDT and PCR assay) and also have conducted comparative assessment on the performance of the three diagnostic tests. Since PCR assay turned out to be highly sensitive (827 malaria positive cases) among the three types of tests, we have utilized data from PCR diagnostic assay for analyses and inferences. The results indicate varied distributional prevalence of P. vivax and P. falciparum according to locations in India, and also the mixed species infection due to these two species. The proportion of P. falciparum to P. vivax was found to be 49:51, and percentage of mixed species infections due to these two parasites was found to be 13% of total infections. Considering India is set for malaria elimination by 2030, the present malaria epidemiological information is of high importance.

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“…Menurut Hanafi-Bojd (2012), area sungai memiliki bobot 30% dari total 6 variabel yang digunakan dalam penelitiannya. Keberadaan tubuh air diperlukan nyamuk Anopheles betina untuk memenuhi life cycle (Mohan, 2014). Data buffer sungai kemudian digabungkan dengan data penutup lahan sehingga mengasilkan peta penutup lahan dengan sungai yang sudah di buffer.…”

Section: Peta Penutup Lahanunclassified

Penerapan Data Spasial Kebijakan Satu Peta untuk Pemodelan Kerawanan Malaria Terintegrasi, Kasus Malaria Perbukitan Menoreh

Widartono

Suharyadi

Satoto

et al. 2022

MGI

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Abstrak. Kebijakan Satu Peta (KSP) atau One Map Policy (OMP) merupakan salah satu program prioritas pemerintah dalam pelaksanaan Nawa Cita. Implementasi KSP diharapkan dapat membantu percepatan pelaksanaan pembangunan nasional di berbagai bidang, yang diantaranya adalah di bidang kesehatan. Salah satu program di bidang kesehatan yang dipandang relevan dengan implementasi KSP adalah program pengendalian malaria. Penelitian ini bertujuan untuk mengeksplorasi dan mengidentifikasi data KSP yang dapat digunakan untuk memetakan kerawanan malaria. Eksplorasi dan identifikasi data KSP dilakukan dengan menggunakan pendekatan spasial ekologis yaitu habitat nyamuk vektor malaria. Menggunakan metode Spatial Multi Criteria Analysis (SMCA) yang diintegrasikan dengan SIG. Data KSP terpilih yang digunakan adalah pada kelompok tematik batas wilayah serta sumberdaya alam dan lingkungan yaitu diantaranya batas wilayah administrasi, sistem lahan, geologi, dan penutup lahan, ditambah dengan data kerapatan vegetasi yang di ekstraksi dari citra Landsat. Pemetaan dilakukan di daerah reseptif malaria di Perbukitan Menoreh. Peta kerawanan malaria yang dihasilkan dari implementasi KSP secara umum selaras dengan kondisi kejadian malaria yang terjadi sehingga nantinya dapat digunakan sebagai bahan kajian untuk informasi spasial terpadu. Abstract. One Map Policy (OMP) is a priority government program in the implementation of Nawa Cita. One Map Policy implementation can help national acceleration development in every sector, such as health. One of the programs in the health sector that is relevant to OMP implementation is the malaria control program. The purposes of this research are to explore and identify OMP data that can be used to map the malaria hazard. Exploration and identification of OMP data was carried out using a spatial ecology approach that is the habitat of the malaria vector mosquito. This research uses the spatial multicriteria analysis (SMCA) method which is integrated with a geographic information system (GIS). The selected OMP data are boundary and natural resources and environment thematics groups, such as administrative boundaries, land system, geology, land cover, and vegetation density extracted from Landsat imagery. This mapping is located in an endemic malaria area, Menoreh Hills. The resulting malaria hazard map from OMP implementation is generally in line with the conditions of malaria incidence that occur so that it can be used as a study for spatial integrated information.

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Temporal changes in land cover types and the incidence of malaria in Mangalore, India

Cited by 8 publications

References 21 publications

Climatology Influence on Malaria Cases in Alusi Community Health Center, West Southeast Maluku Regency

Climatology Influence on Malaria Cases in Alusi Community Health Center, West Southeast Maluku Regency

Malaria diagnosis by PCR revealed differential distribution of mono and mixed species infections by Plasmodium falciparum and P. vivax in India

Penerapan Data Spasial Kebijakan Satu Peta untuk Pemodelan Kerawanan Malaria Terintegrasi, Kasus Malaria Perbukitan Menoreh

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