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Spatial analysis to evaluate risk of malaria in Northern Sumatera, Indonesia
BACKGROUND: As Indonesia aims for malaria elimination by 2030, provisional malaria epidemiology and risk factors evaluation are important in pursue of this national goal. Therefore, this study aimed to understand the risk factor of malaria in Northern Sumatera. METHODS: Malaria cases from 2019 to 20...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392258/ https://www.ncbi.nlm.nih.gov/pubmed/35987665 http://dx.doi.org/10.1186/s12936-022-04262-y |
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author | Fahmi, Fahmi Pasaribu, Ayodhia Pitaloka Theodora, Minerva Wangdi, Kinley |
author_facet | Fahmi, Fahmi Pasaribu, Ayodhia Pitaloka Theodora, Minerva Wangdi, Kinley |
author_sort | Fahmi, Fahmi |
collection | PubMed |
description | BACKGROUND: As Indonesia aims for malaria elimination by 2030, provisional malaria epidemiology and risk factors evaluation are important in pursue of this national goal. Therefore, this study aimed to understand the risk factor of malaria in Northern Sumatera. METHODS: Malaria cases from 2019 to 2020 were obtained from the Indonesian Ministry of Health Electronic Database. Climatic variables were provided by the Center for Meteorology and Geophysics Medan branch office. Multivariable logistic regression was undertaken to understand the risk factors of imported malaria. A zero-inflated Poisson multivariable regression model was used to study the climatic drivers of indigenous malaria. RESULTS: A total of 2208 (indigenous: 76.0% [1679] and imported: 17.8% [392]) were reported during the study period. Risk factors of imported malaria were: ages 19–30 (adjusted odds ratio [AOR] = 3.31; 95% confidence interval [CI] 1.67, 2.56), 31–45 (AOR = 5.69; 95% CI 2.65, 12.20), and > 45 years (AOR = 5.11; 95% CI 2.41, 10.84). Military personnel and forest workers and miners were 1,154 times (AOR = 197.03; 95% CI 145.93, 9,131.56) and 44 times (AOR = 44.16; 95% CI 4.08, 477,93) more likely to be imported cases as compared to those working as employees and traders. Indigenous Plasmodium falciparum increased by 12.1% (95% CrI 5.1%, 20.1%) for 1% increase in relative humidity and by 21.0% (95% CrI 9.0%, 36.2%) for 1 °C increase in maximum temperature. Plasmodium vivax decreased by 0.8% (95% CrI 0.2%, 1.3%) and 16.7% (95% CrI 13.7%, 19.9%) for one meter and 1 °C increase of altitude and minimum temperature. Indigenous hotspot was reported by Kota Tanjung Balai city and Asahan regency, respectively. Imported malaria hotspots were reported in Batu Bara, Kota Tebing Tinggi, Serdang Bedagai and Simalungun. CONCLUSION: Both indigenous and imported malaria is limited to a few regencies and cities in Northern Sumatera. The control measures should focus on these risk factors to achieve elimination in Indonesia. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12936-022-04262-y. |
format | Online Article Text |
id | pubmed-9392258 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-93922582022-08-21 Spatial analysis to evaluate risk of malaria in Northern Sumatera, Indonesia Fahmi, Fahmi Pasaribu, Ayodhia Pitaloka Theodora, Minerva Wangdi, Kinley Malar J Research BACKGROUND: As Indonesia aims for malaria elimination by 2030, provisional malaria epidemiology and risk factors evaluation are important in pursue of this national goal. Therefore, this study aimed to understand the risk factor of malaria in Northern Sumatera. METHODS: Malaria cases from 2019 to 2020 were obtained from the Indonesian Ministry of Health Electronic Database. Climatic variables were provided by the Center for Meteorology and Geophysics Medan branch office. Multivariable logistic regression was undertaken to understand the risk factors of imported malaria. A zero-inflated Poisson multivariable regression model was used to study the climatic drivers of indigenous malaria. RESULTS: A total of 2208 (indigenous: 76.0% [1679] and imported: 17.8% [392]) were reported during the study period. Risk factors of imported malaria were: ages 19–30 (adjusted odds ratio [AOR] = 3.31; 95% confidence interval [CI] 1.67, 2.56), 31–45 (AOR = 5.69; 95% CI 2.65, 12.20), and > 45 years (AOR = 5.11; 95% CI 2.41, 10.84). Military personnel and forest workers and miners were 1,154 times (AOR = 197.03; 95% CI 145.93, 9,131.56) and 44 times (AOR = 44.16; 95% CI 4.08, 477,93) more likely to be imported cases as compared to those working as employees and traders. Indigenous Plasmodium falciparum increased by 12.1% (95% CrI 5.1%, 20.1%) for 1% increase in relative humidity and by 21.0% (95% CrI 9.0%, 36.2%) for 1 °C increase in maximum temperature. Plasmodium vivax decreased by 0.8% (95% CrI 0.2%, 1.3%) and 16.7% (95% CrI 13.7%, 19.9%) for one meter and 1 °C increase of altitude and minimum temperature. Indigenous hotspot was reported by Kota Tanjung Balai city and Asahan regency, respectively. Imported malaria hotspots were reported in Batu Bara, Kota Tebing Tinggi, Serdang Bedagai and Simalungun. CONCLUSION: Both indigenous and imported malaria is limited to a few regencies and cities in Northern Sumatera. The control measures should focus on these risk factors to achieve elimination in Indonesia. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12936-022-04262-y. BioMed Central 2022-08-20 /pmc/articles/PMC9392258/ /pubmed/35987665 http://dx.doi.org/10.1186/s12936-022-04262-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Fahmi, Fahmi Pasaribu, Ayodhia Pitaloka Theodora, Minerva Wangdi, Kinley Spatial analysis to evaluate risk of malaria in Northern Sumatera, Indonesia |
title | Spatial analysis to evaluate risk of malaria in Northern Sumatera, Indonesia |
title_full | Spatial analysis to evaluate risk of malaria in Northern Sumatera, Indonesia |
title_fullStr | Spatial analysis to evaluate risk of malaria in Northern Sumatera, Indonesia |
title_full_unstemmed | Spatial analysis to evaluate risk of malaria in Northern Sumatera, Indonesia |
title_short | Spatial analysis to evaluate risk of malaria in Northern Sumatera, Indonesia |
title_sort | spatial analysis to evaluate risk of malaria in northern sumatera, indonesia |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392258/ https://www.ncbi.nlm.nih.gov/pubmed/35987665 http://dx.doi.org/10.1186/s12936-022-04262-y |
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