Cargando…
Malaria risk factor assessment using active and passive surveillance data from Aceh Besar, Indonesia, a low endemic, malaria elimination setting with Plasmodium knowlesi, Plasmodium vivax, and Plasmodium falciparum
BACKGROUND: As malaria transmission declines, it becomes more geographically focused and more likely due to asymptomatic and non-falciparum infections. To inform malaria elimination planning in the context of this changing epidemiology, local assessments on the risk factors for malaria infection are...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5020529/ https://www.ncbi.nlm.nih.gov/pubmed/27619000 http://dx.doi.org/10.1186/s12936-016-1523-z |
_version_ | 1782453220870717440 |
---|---|
author | Herdiana, Herdiana Cotter, Chris Coutrier, Farah N. Zarlinda, Iska Zelman, Brittany W. Tirta, Yusrifar Kharisma Greenhouse, Bryan Gosling, Roly D. Baker, Peter Whittaker, Maxine Hsiang, Michelle S. |
author_facet | Herdiana, Herdiana Cotter, Chris Coutrier, Farah N. Zarlinda, Iska Zelman, Brittany W. Tirta, Yusrifar Kharisma Greenhouse, Bryan Gosling, Roly D. Baker, Peter Whittaker, Maxine Hsiang, Michelle S. |
author_sort | Herdiana, Herdiana |
collection | PubMed |
description | BACKGROUND: As malaria transmission declines, it becomes more geographically focused and more likely due to asymptomatic and non-falciparum infections. To inform malaria elimination planning in the context of this changing epidemiology, local assessments on the risk factors for malaria infection are necessary, yet challenging due to the low number of malaria cases. METHODS: A population-based, cross-sectional study was performed using passive and active surveillance data collected in Aceh Besar District, Indonesia from 2014 to 2015. Malaria infection was defined as symptomatic polymerase chain reaction (PCR)-confirmed infection in index cases reported from health facilities, and asymptomatic or symptomatic PCR-confirmed infection identified in reactive case detection (RACD). Potential risk factors for any infection, species-specific infection, or secondary-case detection in RACD were assessed through questionnaires and evaluated for associations. RESULTS: Nineteen Plasmodium knowlesi, 12 Plasmodium vivax and six Plasmodium falciparum cases were identified passively, and 1495 community members screened in RACD, of which six secondary cases were detected (one P. knowlesi, three P. vivax, and two P. falciparum, with four being asymptomatic). Compared to non-infected subjects screened in RACD, cases identified through passive or active surveillance were more likely to be male (AOR 12.5, 95 % CI 3.0–52.1), adult (AOR 14.0, 95 % CI 2.2–89.6 for age 16–45 years compared to <15 years), have visited the forest in the previous month for any reason (AOR 5.6, 95 % CI 1.3–24.2), and have a workplace near or in the forest and requiring overnight stays (AOR 7.9, 95 % CI 1.6–39.7 compared to workplace not near or in the forest). Comparing subjects with infections of different species, differences were observed in sub-district of residence and other demographic and behavioural factors. Among subjects screened in RACD, cases compared to non-cases were more likely to be febrile and reside within 100 m of the index case. CONCLUSION: In this setting, risk of malaria infection in index and RACD identified cases was associated with forest exposure, particularly overnights in the forest for work. In low-transmission settings, utilization of data available through routine passive and active surveillance can support efforts to target individuals at high risk. |
format | Online Article Text |
id | pubmed-5020529 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-50205292016-09-14 Malaria risk factor assessment using active and passive surveillance data from Aceh Besar, Indonesia, a low endemic, malaria elimination setting with Plasmodium knowlesi, Plasmodium vivax, and Plasmodium falciparum Herdiana, Herdiana Cotter, Chris Coutrier, Farah N. Zarlinda, Iska Zelman, Brittany W. Tirta, Yusrifar Kharisma Greenhouse, Bryan Gosling, Roly D. Baker, Peter Whittaker, Maxine Hsiang, Michelle S. Malar J Research BACKGROUND: As malaria transmission declines, it becomes more geographically focused and more likely due to asymptomatic and non-falciparum infections. To inform malaria elimination planning in the context of this changing epidemiology, local assessments on the risk factors for malaria infection are necessary, yet challenging due to the low number of malaria cases. METHODS: A population-based, cross-sectional study was performed using passive and active surveillance data collected in Aceh Besar District, Indonesia from 2014 to 2015. Malaria infection was defined as symptomatic polymerase chain reaction (PCR)-confirmed infection in index cases reported from health facilities, and asymptomatic or symptomatic PCR-confirmed infection identified in reactive case detection (RACD). Potential risk factors for any infection, species-specific infection, or secondary-case detection in RACD were assessed through questionnaires and evaluated for associations. RESULTS: Nineteen Plasmodium knowlesi, 12 Plasmodium vivax and six Plasmodium falciparum cases were identified passively, and 1495 community members screened in RACD, of which six secondary cases were detected (one P. knowlesi, three P. vivax, and two P. falciparum, with four being asymptomatic). Compared to non-infected subjects screened in RACD, cases identified through passive or active surveillance were more likely to be male (AOR 12.5, 95 % CI 3.0–52.1), adult (AOR 14.0, 95 % CI 2.2–89.6 for age 16–45 years compared to <15 years), have visited the forest in the previous month for any reason (AOR 5.6, 95 % CI 1.3–24.2), and have a workplace near or in the forest and requiring overnight stays (AOR 7.9, 95 % CI 1.6–39.7 compared to workplace not near or in the forest). Comparing subjects with infections of different species, differences were observed in sub-district of residence and other demographic and behavioural factors. Among subjects screened in RACD, cases compared to non-cases were more likely to be febrile and reside within 100 m of the index case. CONCLUSION: In this setting, risk of malaria infection in index and RACD identified cases was associated with forest exposure, particularly overnights in the forest for work. In low-transmission settings, utilization of data available through routine passive and active surveillance can support efforts to target individuals at high risk. BioMed Central 2016-09-13 /pmc/articles/PMC5020529/ /pubmed/27619000 http://dx.doi.org/10.1186/s12936-016-1523-z Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Herdiana, Herdiana Cotter, Chris Coutrier, Farah N. Zarlinda, Iska Zelman, Brittany W. Tirta, Yusrifar Kharisma Greenhouse, Bryan Gosling, Roly D. Baker, Peter Whittaker, Maxine Hsiang, Michelle S. Malaria risk factor assessment using active and passive surveillance data from Aceh Besar, Indonesia, a low endemic, malaria elimination setting with Plasmodium knowlesi, Plasmodium vivax, and Plasmodium falciparum |
title | Malaria risk factor assessment using active and passive surveillance data from Aceh Besar, Indonesia, a low endemic, malaria elimination setting with Plasmodium knowlesi, Plasmodium vivax, and Plasmodium falciparum |
title_full | Malaria risk factor assessment using active and passive surveillance data from Aceh Besar, Indonesia, a low endemic, malaria elimination setting with Plasmodium knowlesi, Plasmodium vivax, and Plasmodium falciparum |
title_fullStr | Malaria risk factor assessment using active and passive surveillance data from Aceh Besar, Indonesia, a low endemic, malaria elimination setting with Plasmodium knowlesi, Plasmodium vivax, and Plasmodium falciparum |
title_full_unstemmed | Malaria risk factor assessment using active and passive surveillance data from Aceh Besar, Indonesia, a low endemic, malaria elimination setting with Plasmodium knowlesi, Plasmodium vivax, and Plasmodium falciparum |
title_short | Malaria risk factor assessment using active and passive surveillance data from Aceh Besar, Indonesia, a low endemic, malaria elimination setting with Plasmodium knowlesi, Plasmodium vivax, and Plasmodium falciparum |
title_sort | malaria risk factor assessment using active and passive surveillance data from aceh besar, indonesia, a low endemic, malaria elimination setting with plasmodium knowlesi, plasmodium vivax, and plasmodium falciparum |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5020529/ https://www.ncbi.nlm.nih.gov/pubmed/27619000 http://dx.doi.org/10.1186/s12936-016-1523-z |
work_keys_str_mv | AT herdianaherdiana malariariskfactorassessmentusingactiveandpassivesurveillancedatafromacehbesarindonesiaalowendemicmalariaeliminationsettingwithplasmodiumknowlesiplasmodiumvivaxandplasmodiumfalciparum AT cotterchris malariariskfactorassessmentusingactiveandpassivesurveillancedatafromacehbesarindonesiaalowendemicmalariaeliminationsettingwithplasmodiumknowlesiplasmodiumvivaxandplasmodiumfalciparum AT coutrierfarahn malariariskfactorassessmentusingactiveandpassivesurveillancedatafromacehbesarindonesiaalowendemicmalariaeliminationsettingwithplasmodiumknowlesiplasmodiumvivaxandplasmodiumfalciparum AT zarlindaiska malariariskfactorassessmentusingactiveandpassivesurveillancedatafromacehbesarindonesiaalowendemicmalariaeliminationsettingwithplasmodiumknowlesiplasmodiumvivaxandplasmodiumfalciparum AT zelmanbrittanyw malariariskfactorassessmentusingactiveandpassivesurveillancedatafromacehbesarindonesiaalowendemicmalariaeliminationsettingwithplasmodiumknowlesiplasmodiumvivaxandplasmodiumfalciparum AT tirtayusrifarkharisma malariariskfactorassessmentusingactiveandpassivesurveillancedatafromacehbesarindonesiaalowendemicmalariaeliminationsettingwithplasmodiumknowlesiplasmodiumvivaxandplasmodiumfalciparum AT greenhousebryan malariariskfactorassessmentusingactiveandpassivesurveillancedatafromacehbesarindonesiaalowendemicmalariaeliminationsettingwithplasmodiumknowlesiplasmodiumvivaxandplasmodiumfalciparum AT goslingrolyd malariariskfactorassessmentusingactiveandpassivesurveillancedatafromacehbesarindonesiaalowendemicmalariaeliminationsettingwithplasmodiumknowlesiplasmodiumvivaxandplasmodiumfalciparum AT bakerpeter malariariskfactorassessmentusingactiveandpassivesurveillancedatafromacehbesarindonesiaalowendemicmalariaeliminationsettingwithplasmodiumknowlesiplasmodiumvivaxandplasmodiumfalciparum AT whittakermaxine malariariskfactorassessmentusingactiveandpassivesurveillancedatafromacehbesarindonesiaalowendemicmalariaeliminationsettingwithplasmodiumknowlesiplasmodiumvivaxandplasmodiumfalciparum AT hsiangmichelles malariariskfactorassessmentusingactiveandpassivesurveillancedatafromacehbesarindonesiaalowendemicmalariaeliminationsettingwithplasmodiumknowlesiplasmodiumvivaxandplasmodiumfalciparum |