Study of epidemiological behaviour of malaria and its control in the Purulia district of West Bengal, India (2016–2020)

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作者
Sayantan Pradhan
Samrat Hore
Suman Kumar Maji
Simi Manna
Abhijit Maity
Pratip Kumar Kundu
Krishna Maity
Stabak Roy
Saptarshi Mitra
Paulami Dam
Rittick Mondal
Suvankar Ghorai
Junaid Jibran Jawed
Subhadeep Dutta
Sandip Das
Sukhendu Mandal
Sanjib Mandal
Ahmet Kati
Sangram Sinha
Amit Bikram Maity
Tuphan Kanti Dolai
Amit Kumar Mandal
İkbal Agah İnce
机构
[1] Raiganj University,Chemical Biology Laboratory, Department of Sericulture
[2] Nil Ratan Sircar Medical College & Hospital,Hematology Department
[3] Tripura University,Department of Statistics
[4] Deben Mahata Government Medical College and Hospital,District Public Health Centre
[5] Vidyasagar University,Department of Bio
[6] Calcutta School of Tropical Medicine,Medical Laboratory Science & Management
[7] VisvaBharati University,Department of Statistics
[8] Tripura University,Department of Geography and Disaster Management
[9] Raiganj University,Department of Microbiology
[10] Presidency University – 2nd Campus,School of Biotechnology
[11] Netaji Subhas Open University,Department of Botany, School of Sciences, Durgapur Regional Centre
[12] University of Calcutta,Laboratory of Molecular Bacteriology, Department of Microbiology
[13] Raiganj University,Department of Economics
[14] University of Health Sciences,Department of Biotechnology, Institution of Health Sciences
[15] Vivekananda Mahavidyalaya,Department of Botany
[16] Deben Mahata Government Medical College and Hospital,Department of Otorhinolaryngology
[17] Raiganj University,Centre for Nanotechnology Sciences
[18] Acibadem Mehmet Ali Aydınlar University,Department of Medical Microbiology, School of Medicine
[19] Ataşehir,undefined
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摘要
Purulia is a malaria-prone district in West Bengal, India, with approximately half of the blocks defined as malaria endemic. We analyzed the malaria case in each block of the Purulia district from January 1, 2016, to December 31, 2020. As per the API, 20 blocks of Purulia were assigned to four different categories (0–3) and mapped using ArcGIS software. An exponential decay model was fitted to forecast the trend of malaria cases for each block of Purulia (2021–2025). There was a sharp decrease in total malaria cases and API from 2016 to 2020 due to the mass distribution of LLINs. The majority of cases (72.63%) were found in ≥ 15-year age group. Males were more prone to malaria (60.09%). Malaria was highly prevalent among Scheduled Tribes (48.44%). Six blocks were reported in Category 3 (high risk) and none in Category 0 (no risk) in 2016, while no blocks were determined to be in Category 3, and three blocks were in Category 0 in 2020. The exponential decay model prediction is oriented towards gaining malaria-free status in thirteen blocks of Purulia by 2025. This study will incite the government to uphold and strengthen the current efforts to meet the malaria elimination goals.
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