Spatial analysis to evaluate risk of malaria in Northern Sumatera, Indonesia
Abstract 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 201...
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ftdoajarticles:oai:doaj.org/article:7d26a2eacb134071ae7c10ed182e1224 2023-05-15T15:16:01+02:00 Spatial analysis to evaluate risk of malaria in Northern Sumatera, Indonesia Fahmi Fahmi Ayodhia Pitaloka Pasaribu Minerva Theodora Kinley Wangdi 2022-08-01T00:00:00Z https://doi.org/10.1186/s12936-022-04262-y https://doaj.org/article/7d26a2eacb134071ae7c10ed182e1224 EN eng BMC https://doi.org/10.1186/s12936-022-04262-y https://doaj.org/toc/1475-2875 doi:10.1186/s12936-022-04262-y 1475-2875 https://doaj.org/article/7d26a2eacb134071ae7c10ed182e1224 Malaria Journal, Vol 21, Iss 1, Pp 1-12 (2022) Bayesian analysis Elimination Indigenous Indonesia Imported Malaria Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2022 ftdoajarticles https://doi.org/10.1186/s12936-022-04262-y 2022-12-30T23:10:23Z Abstract 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. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Malaria Journal 21 1 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
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English |
topic |
Bayesian analysis Elimination Indigenous Indonesia Imported Malaria Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
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Bayesian analysis Elimination Indigenous Indonesia Imported Malaria Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 Fahmi Fahmi Ayodhia Pitaloka Pasaribu Minerva Theodora Kinley Wangdi Spatial analysis to evaluate risk of malaria in Northern Sumatera, Indonesia |
topic_facet |
Bayesian analysis Elimination Indigenous Indonesia Imported Malaria Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
description |
Abstract 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. |
format |
Article in Journal/Newspaper |
author |
Fahmi Fahmi Ayodhia Pitaloka Pasaribu Minerva Theodora Kinley Wangdi |
author_facet |
Fahmi Fahmi Ayodhia Pitaloka Pasaribu Minerva Theodora Kinley Wangdi |
author_sort |
Fahmi Fahmi |
title |
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_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_sort |
spatial analysis to evaluate risk of malaria in northern sumatera, indonesia |
publisher |
BMC |
publishDate |
2022 |
url |
https://doi.org/10.1186/s12936-022-04262-y https://doaj.org/article/7d26a2eacb134071ae7c10ed182e1224 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Malaria Journal, Vol 21, Iss 1, Pp 1-12 (2022) |
op_relation |
https://doi.org/10.1186/s12936-022-04262-y https://doaj.org/toc/1475-2875 doi:10.1186/s12936-022-04262-y 1475-2875 https://doaj.org/article/7d26a2eacb134071ae7c10ed182e1224 |
op_doi |
https://doi.org/10.1186/s12936-022-04262-y |
container_title |
Malaria Journal |
container_volume |
21 |
container_issue |
1 |
_version_ |
1766346327120150528 |