Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions

Background Since 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach. Methods This study used individual and household-level data from the 2015 and 2018 annual malaria indicator surveys on Bioko Island, as well as remotely-sensed environmental data in multilevel logistic regression models to quantify the odds of malaria infection. The analyses were stratified by urban and rural settings and by survey year. Results Malaria prevalence was higher in 10–14-year-old children and similar between female and male individuals. After adjusting for demographic factors and other covariates, many of the variables investigated showed no significant association with malaria infection. The factor most strongly associated was history of travel to mainland Equatorial Guinea (mEG), which increased the odds significantly both in urban and rural settings (people who travelled had 4 times the odds of infection). Sleeping under a long-lasting insecticidal net decreased significantly the odds of malaria across urban and rural settings and survey years (net users had around 30% less odds of infection), highlighting their contribution to malaria control on the Island. Improved housing conditions indicated some protection, though this was not consistent across settings and survey year. Conclusions Malaria risk on Bioko Island is heterogeneous and determined by a combination of factors interacting with local mosquito ecology. These interactions grant further investigation in order to better adapt control according to need. The single most important risk factor identified was travel to mEG, in line with previous investigations, and represents a great challenge for the success of malaria control on the Island. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	García, Guillermo A. [verfasserIn] Janko, Mark Hergott, Dianna E. B. Donfack, Olivier T. Smith, Jordan M. Mba Eyono, Jeremías Nzamío DeBoer, Kylie R. Nguema Avue, Restituto Mba Phiri, Wonder P. Aldrich, Edward M. Schwabe, Christopher Stabler, Thomas C. Rivas, Matilde Riloha Cameron, Ewan Guerra, Carlos A. Cook, Jackie Kleinschmidt, Immo Bradley, John

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Malaria Targeted interventions Importation Vector control Risk factors

Anmerkung:	© The Author(s) 2023

Übergeordnetes Werk:	Enthalten in: Malaria journal - London : BioMed Central, 2002, 22(2023), 1 vom: 01. März
Übergeordnetes Werk:	volume:22 ; year:2023 ; number:1 ; day:01 ; month:03

Links:	Volltext

DOI / URN:	10.1186/s12936-023-04504-7

Katalog-ID:	SPR051517000

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100	1		\|a García, Guillermo A. \|e verfasserin \|4 aut
245	1	0	\|a Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions
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520			\|a Background Since 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach. Methods This study used individual and household-level data from the 2015 and 2018 annual malaria indicator surveys on Bioko Island, as well as remotely-sensed environmental data in multilevel logistic regression models to quantify the odds of malaria infection. The analyses were stratified by urban and rural settings and by survey year. Results Malaria prevalence was higher in 10–14-year-old children and similar between female and male individuals. After adjusting for demographic factors and other covariates, many of the variables investigated showed no significant association with malaria infection. The factor most strongly associated was history of travel to mainland Equatorial Guinea (mEG), which increased the odds significantly both in urban and rural settings (people who travelled had 4 times the odds of infection). Sleeping under a long-lasting insecticidal net decreased significantly the odds of malaria across urban and rural settings and survey years (net users had around 30% less odds of infection), highlighting their contribution to malaria control on the Island. Improved housing conditions indicated some protection, though this was not consistent across settings and survey year. Conclusions Malaria risk on Bioko Island is heterogeneous and determined by a combination of factors interacting with local mosquito ecology. These interactions grant further investigation in order to better adapt control according to need. The single most important risk factor identified was travel to mEG, in line with previous investigations, and represents a great challenge for the success of malaria control on the Island.
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700	1		\|a Janko, Mark \|4 aut
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700	1		\|a Donfack, Olivier T. \|4 aut
700	1		\|a Smith, Jordan M. \|4 aut
700	1		\|a Mba Eyono, Jeremías Nzamío \|4 aut
700	1		\|a DeBoer, Kylie R. \|4 aut
700	1		\|a Nguema Avue, Restituto Mba \|4 aut
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700	1		\|a Aldrich, Edward M. \|4 aut
700	1		\|a Schwabe, Christopher \|4 aut
700	1		\|a Stabler, Thomas C. \|4 aut
700	1		\|a Rivas, Matilde Riloha \|4 aut
700	1		\|a Cameron, Ewan \|4 aut
700	1		\|a Guerra, Carlos A. \|4 aut
700	1		\|a Cook, Jackie \|4 aut
700	1		\|a Kleinschmidt, Immo \|4 aut
700	1		\|a Bradley, John \|4 aut
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allfields	10.1186/s12936-023-04504-7 doi (DE-627)SPR051517000 (SPR)s12936-023-04504-7-e DE-627 ger DE-627 rakwb eng García, Guillermo A. verfasserin aut Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Background Since 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach. Methods This study used individual and household-level data from the 2015 and 2018 annual malaria indicator surveys on Bioko Island, as well as remotely-sensed environmental data in multilevel logistic regression models to quantify the odds of malaria infection. The analyses were stratified by urban and rural settings and by survey year. Results Malaria prevalence was higher in 10–14-year-old children and similar between female and male individuals. After adjusting for demographic factors and other covariates, many of the variables investigated showed no significant association with malaria infection. The factor most strongly associated was history of travel to mainland Equatorial Guinea (mEG), which increased the odds significantly both in urban and rural settings (people who travelled had 4 times the odds of infection). Sleeping under a long-lasting insecticidal net decreased significantly the odds of malaria across urban and rural settings and survey years (net users had around 30% less odds of infection), highlighting their contribution to malaria control on the Island. Improved housing conditions indicated some protection, though this was not consistent across settings and survey year. Conclusions Malaria risk on Bioko Island is heterogeneous and determined by a combination of factors interacting with local mosquito ecology. These interactions grant further investigation in order to better adapt control according to need. The single most important risk factor identified was travel to mEG, in line with previous investigations, and represents a great challenge for the success of malaria control on the Island. Malaria (dpeaa)DE-He213 Targeted interventions (dpeaa)DE-He213 Importation (dpeaa)DE-He213 Vector control (dpeaa)DE-He213 Risk factors (dpeaa)DE-He213 Janko, Mark aut Hergott, Dianna E. B. aut Donfack, Olivier T. aut Smith, Jordan M. aut Mba Eyono, Jeremías Nzamío aut DeBoer, Kylie R. aut Nguema Avue, Restituto Mba aut Phiri, Wonder P. aut Aldrich, Edward M. aut Schwabe, Christopher aut Stabler, Thomas C. aut Rivas, Matilde Riloha aut Cameron, Ewan aut Guerra, Carlos A. aut Cook, Jackie aut Kleinschmidt, Immo aut Bradley, John aut Enthalten in Malaria journal London : BioMed Central, 2002 22(2023), 1 vom: 01. März (DE-627)355986582 (DE-600)2091229-8 1475-2875 nnns volume:22 year:2023 number:1 day:01 month:03 https://dx.doi.org/10.1186/s12936-023-04504-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2023 1 01 03
spelling	10.1186/s12936-023-04504-7 doi (DE-627)SPR051517000 (SPR)s12936-023-04504-7-e DE-627 ger DE-627 rakwb eng García, Guillermo A. verfasserin aut Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Background Since 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach. Methods This study used individual and household-level data from the 2015 and 2018 annual malaria indicator surveys on Bioko Island, as well as remotely-sensed environmental data in multilevel logistic regression models to quantify the odds of malaria infection. The analyses were stratified by urban and rural settings and by survey year. Results Malaria prevalence was higher in 10–14-year-old children and similar between female and male individuals. After adjusting for demographic factors and other covariates, many of the variables investigated showed no significant association with malaria infection. The factor most strongly associated was history of travel to mainland Equatorial Guinea (mEG), which increased the odds significantly both in urban and rural settings (people who travelled had 4 times the odds of infection). Sleeping under a long-lasting insecticidal net decreased significantly the odds of malaria across urban and rural settings and survey years (net users had around 30% less odds of infection), highlighting their contribution to malaria control on the Island. Improved housing conditions indicated some protection, though this was not consistent across settings and survey year. Conclusions Malaria risk on Bioko Island is heterogeneous and determined by a combination of factors interacting with local mosquito ecology. These interactions grant further investigation in order to better adapt control according to need. The single most important risk factor identified was travel to mEG, in line with previous investigations, and represents a great challenge for the success of malaria control on the Island. Malaria (dpeaa)DE-He213 Targeted interventions (dpeaa)DE-He213 Importation (dpeaa)DE-He213 Vector control (dpeaa)DE-He213 Risk factors (dpeaa)DE-He213 Janko, Mark aut Hergott, Dianna E. B. aut Donfack, Olivier T. aut Smith, Jordan M. aut Mba Eyono, Jeremías Nzamío aut DeBoer, Kylie R. aut Nguema Avue, Restituto Mba aut Phiri, Wonder P. aut Aldrich, Edward M. aut Schwabe, Christopher aut Stabler, Thomas C. aut Rivas, Matilde Riloha aut Cameron, Ewan aut Guerra, Carlos A. aut Cook, Jackie aut Kleinschmidt, Immo aut Bradley, John aut Enthalten in Malaria journal London : BioMed Central, 2002 22(2023), 1 vom: 01. März (DE-627)355986582 (DE-600)2091229-8 1475-2875 nnns volume:22 year:2023 number:1 day:01 month:03 https://dx.doi.org/10.1186/s12936-023-04504-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2023 1 01 03
allfields_unstemmed	10.1186/s12936-023-04504-7 doi (DE-627)SPR051517000 (SPR)s12936-023-04504-7-e DE-627 ger DE-627 rakwb eng García, Guillermo A. verfasserin aut Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Background Since 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach. Methods This study used individual and household-level data from the 2015 and 2018 annual malaria indicator surveys on Bioko Island, as well as remotely-sensed environmental data in multilevel logistic regression models to quantify the odds of malaria infection. The analyses were stratified by urban and rural settings and by survey year. Results Malaria prevalence was higher in 10–14-year-old children and similar between female and male individuals. After adjusting for demographic factors and other covariates, many of the variables investigated showed no significant association with malaria infection. The factor most strongly associated was history of travel to mainland Equatorial Guinea (mEG), which increased the odds significantly both in urban and rural settings (people who travelled had 4 times the odds of infection). Sleeping under a long-lasting insecticidal net decreased significantly the odds of malaria across urban and rural settings and survey years (net users had around 30% less odds of infection), highlighting their contribution to malaria control on the Island. Improved housing conditions indicated some protection, though this was not consistent across settings and survey year. Conclusions Malaria risk on Bioko Island is heterogeneous and determined by a combination of factors interacting with local mosquito ecology. These interactions grant further investigation in order to better adapt control according to need. The single most important risk factor identified was travel to mEG, in line with previous investigations, and represents a great challenge for the success of malaria control on the Island. Malaria (dpeaa)DE-He213 Targeted interventions (dpeaa)DE-He213 Importation (dpeaa)DE-He213 Vector control (dpeaa)DE-He213 Risk factors (dpeaa)DE-He213 Janko, Mark aut Hergott, Dianna E. B. aut Donfack, Olivier T. aut Smith, Jordan M. aut Mba Eyono, Jeremías Nzamío aut DeBoer, Kylie R. aut Nguema Avue, Restituto Mba aut Phiri, Wonder P. aut Aldrich, Edward M. aut Schwabe, Christopher aut Stabler, Thomas C. aut Rivas, Matilde Riloha aut Cameron, Ewan aut Guerra, Carlos A. aut Cook, Jackie aut Kleinschmidt, Immo aut Bradley, John aut Enthalten in Malaria journal London : BioMed Central, 2002 22(2023), 1 vom: 01. März (DE-627)355986582 (DE-600)2091229-8 1475-2875 nnns volume:22 year:2023 number:1 day:01 month:03 https://dx.doi.org/10.1186/s12936-023-04504-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2023 1 01 03
allfieldsGer	10.1186/s12936-023-04504-7 doi (DE-627)SPR051517000 (SPR)s12936-023-04504-7-e DE-627 ger DE-627 rakwb eng García, Guillermo A. verfasserin aut Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Background Since 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach. Methods This study used individual and household-level data from the 2015 and 2018 annual malaria indicator surveys on Bioko Island, as well as remotely-sensed environmental data in multilevel logistic regression models to quantify the odds of malaria infection. The analyses were stratified by urban and rural settings and by survey year. Results Malaria prevalence was higher in 10–14-year-old children and similar between female and male individuals. After adjusting for demographic factors and other covariates, many of the variables investigated showed no significant association with malaria infection. The factor most strongly associated was history of travel to mainland Equatorial Guinea (mEG), which increased the odds significantly both in urban and rural settings (people who travelled had 4 times the odds of infection). Sleeping under a long-lasting insecticidal net decreased significantly the odds of malaria across urban and rural settings and survey years (net users had around 30% less odds of infection), highlighting their contribution to malaria control on the Island. Improved housing conditions indicated some protection, though this was not consistent across settings and survey year. Conclusions Malaria risk on Bioko Island is heterogeneous and determined by a combination of factors interacting with local mosquito ecology. These interactions grant further investigation in order to better adapt control according to need. The single most important risk factor identified was travel to mEG, in line with previous investigations, and represents a great challenge for the success of malaria control on the Island. Malaria (dpeaa)DE-He213 Targeted interventions (dpeaa)DE-He213 Importation (dpeaa)DE-He213 Vector control (dpeaa)DE-He213 Risk factors (dpeaa)DE-He213 Janko, Mark aut Hergott, Dianna E. B. aut Donfack, Olivier T. aut Smith, Jordan M. aut Mba Eyono, Jeremías Nzamío aut DeBoer, Kylie R. aut Nguema Avue, Restituto Mba aut Phiri, Wonder P. aut Aldrich, Edward M. aut Schwabe, Christopher aut Stabler, Thomas C. aut Rivas, Matilde Riloha aut Cameron, Ewan aut Guerra, Carlos A. aut Cook, Jackie aut Kleinschmidt, Immo aut Bradley, John aut Enthalten in Malaria journal London : BioMed Central, 2002 22(2023), 1 vom: 01. März (DE-627)355986582 (DE-600)2091229-8 1475-2875 nnns volume:22 year:2023 number:1 day:01 month:03 https://dx.doi.org/10.1186/s12936-023-04504-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2023 1 01 03
allfieldsSound	10.1186/s12936-023-04504-7 doi (DE-627)SPR051517000 (SPR)s12936-023-04504-7-e DE-627 ger DE-627 rakwb eng García, Guillermo A. verfasserin aut Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Background Since 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach. Methods This study used individual and household-level data from the 2015 and 2018 annual malaria indicator surveys on Bioko Island, as well as remotely-sensed environmental data in multilevel logistic regression models to quantify the odds of malaria infection. The analyses were stratified by urban and rural settings and by survey year. Results Malaria prevalence was higher in 10–14-year-old children and similar between female and male individuals. After adjusting for demographic factors and other covariates, many of the variables investigated showed no significant association with malaria infection. The factor most strongly associated was history of travel to mainland Equatorial Guinea (mEG), which increased the odds significantly both in urban and rural settings (people who travelled had 4 times the odds of infection). Sleeping under a long-lasting insecticidal net decreased significantly the odds of malaria across urban and rural settings and survey years (net users had around 30% less odds of infection), highlighting their contribution to malaria control on the Island. Improved housing conditions indicated some protection, though this was not consistent across settings and survey year. Conclusions Malaria risk on Bioko Island is heterogeneous and determined by a combination of factors interacting with local mosquito ecology. These interactions grant further investigation in order to better adapt control according to need. The single most important risk factor identified was travel to mEG, in line with previous investigations, and represents a great challenge for the success of malaria control on the Island. Malaria (dpeaa)DE-He213 Targeted interventions (dpeaa)DE-He213 Importation (dpeaa)DE-He213 Vector control (dpeaa)DE-He213 Risk factors (dpeaa)DE-He213 Janko, Mark aut Hergott, Dianna E. B. aut Donfack, Olivier T. aut Smith, Jordan M. aut Mba Eyono, Jeremías Nzamío aut DeBoer, Kylie R. aut Nguema Avue, Restituto Mba aut Phiri, Wonder P. aut Aldrich, Edward M. aut Schwabe, Christopher aut Stabler, Thomas C. aut Rivas, Matilde Riloha aut Cameron, Ewan aut Guerra, Carlos A. aut Cook, Jackie aut Kleinschmidt, Immo aut Bradley, John aut Enthalten in Malaria journal London : BioMed Central, 2002 22(2023), 1 vom: 01. März (DE-627)355986582 (DE-600)2091229-8 1475-2875 nnns volume:22 year:2023 number:1 day:01 month:03 https://dx.doi.org/10.1186/s12936-023-04504-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2023 1 01 03
language	English
source	Enthalten in Malaria journal 22(2023), 1 vom: 01. März volume:22 year:2023 number:1 day:01 month:03
sourceStr	Enthalten in Malaria journal 22(2023), 1 vom: 01. März volume:22 year:2023 number:1 day:01 month:03
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Malaria Targeted interventions Importation Vector control Risk factors
isfreeaccess_bool	true
container_title	Malaria journal
authorswithroles_txt_mv	García, Guillermo A. @@aut@@ Janko, Mark @@aut@@ Hergott, Dianna E. B. @@aut@@ Donfack, Olivier T. @@aut@@ Smith, Jordan M. @@aut@@ Mba Eyono, Jeremías Nzamío @@aut@@ DeBoer, Kylie R. @@aut@@ Nguema Avue, Restituto Mba @@aut@@ Phiri, Wonder P. @@aut@@ Aldrich, Edward M. @@aut@@ Schwabe, Christopher @@aut@@ Stabler, Thomas C. @@aut@@ Rivas, Matilde Riloha @@aut@@ Cameron, Ewan @@aut@@ Guerra, Carlos A. @@aut@@ Cook, Jackie @@aut@@ Kleinschmidt, Immo @@aut@@ Bradley, John @@aut@@
publishDateDaySort_date	2023-03-01T00:00:00Z
hierarchy_top_id	355986582
id	SPR051517000
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR051517000</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230510064443.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230510s2023 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1186/s12936-023-04504-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR051517000</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s12936-023-04504-7-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">García, Guillermo A.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s) 2023</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Background Since 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach. Methods This study used individual and household-level data from the 2015 and 2018 annual malaria indicator surveys on Bioko Island, as well as remotely-sensed environmental data in multilevel logistic regression models to quantify the odds of malaria infection. The analyses were stratified by urban and rural settings and by survey year. Results Malaria prevalence was higher in 10–14-year-old children and similar between female and male individuals. After adjusting for demographic factors and other covariates, many of the variables investigated showed no significant association with malaria infection. The factor most strongly associated was history of travel to mainland Equatorial Guinea (mEG), which increased the odds significantly both in urban and rural settings (people who travelled had 4 times the odds of infection). Sleeping under a long-lasting insecticidal net decreased significantly the odds of malaria across urban and rural settings and survey years (net users had around 30% less odds of infection), highlighting their contribution to malaria control on the Island. Improved housing conditions indicated some protection, though this was not consistent across settings and survey year. Conclusions Malaria risk on Bioko Island is heterogeneous and determined by a combination of factors interacting with local mosquito ecology. These interactions grant further investigation in order to better adapt control according to need. 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author	García, Guillermo A.
spellingShingle	García, Guillermo A. misc Malaria misc Targeted interventions misc Importation misc Vector control misc Risk factors Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions
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topic_title	Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions Malaria (dpeaa)DE-He213 Targeted interventions (dpeaa)DE-He213 Importation (dpeaa)DE-He213 Vector control (dpeaa)DE-He213 Risk factors (dpeaa)DE-He213
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title	Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions
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title_full	Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions
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author_browse	García, Guillermo A. Janko, Mark Hergott, Dianna E. B. Donfack, Olivier T. Smith, Jordan M. Mba Eyono, Jeremías Nzamío DeBoer, Kylie R. Nguema Avue, Restituto Mba Phiri, Wonder P. Aldrich, Edward M. Schwabe, Christopher Stabler, Thomas C. Rivas, Matilde Riloha Cameron, Ewan Guerra, Carlos A. Cook, Jackie Kleinschmidt, Immo Bradley, John
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title_sort	identifying individual, household and environmental risk factors for malaria infection on bioko island to inform interventions
title_auth	Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions
abstract	Background Since 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach. Methods This study used individual and household-level data from the 2015 and 2018 annual malaria indicator surveys on Bioko Island, as well as remotely-sensed environmental data in multilevel logistic regression models to quantify the odds of malaria infection. The analyses were stratified by urban and rural settings and by survey year. Results Malaria prevalence was higher in 10–14-year-old children and similar between female and male individuals. After adjusting for demographic factors and other covariates, many of the variables investigated showed no significant association with malaria infection. The factor most strongly associated was history of travel to mainland Equatorial Guinea (mEG), which increased the odds significantly both in urban and rural settings (people who travelled had 4 times the odds of infection). Sleeping under a long-lasting insecticidal net decreased significantly the odds of malaria across urban and rural settings and survey years (net users had around 30% less odds of infection), highlighting their contribution to malaria control on the Island. Improved housing conditions indicated some protection, though this was not consistent across settings and survey year. Conclusions Malaria risk on Bioko Island is heterogeneous and determined by a combination of factors interacting with local mosquito ecology. These interactions grant further investigation in order to better adapt control according to need. The single most important risk factor identified was travel to mEG, in line with previous investigations, and represents a great challenge for the success of malaria control on the Island. © The Author(s) 2023
abstractGer	Background Since 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach. Methods This study used individual and household-level data from the 2015 and 2018 annual malaria indicator surveys on Bioko Island, as well as remotely-sensed environmental data in multilevel logistic regression models to quantify the odds of malaria infection. The analyses were stratified by urban and rural settings and by survey year. Results Malaria prevalence was higher in 10–14-year-old children and similar between female and male individuals. After adjusting for demographic factors and other covariates, many of the variables investigated showed no significant association with malaria infection. The factor most strongly associated was history of travel to mainland Equatorial Guinea (mEG), which increased the odds significantly both in urban and rural settings (people who travelled had 4 times the odds of infection). Sleeping under a long-lasting insecticidal net decreased significantly the odds of malaria across urban and rural settings and survey years (net users had around 30% less odds of infection), highlighting their contribution to malaria control on the Island. Improved housing conditions indicated some protection, though this was not consistent across settings and survey year. Conclusions Malaria risk on Bioko Island is heterogeneous and determined by a combination of factors interacting with local mosquito ecology. These interactions grant further investigation in order to better adapt control according to need. The single most important risk factor identified was travel to mEG, in line with previous investigations, and represents a great challenge for the success of malaria control on the Island. © The Author(s) 2023
abstract_unstemmed	Background Since 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach. Methods This study used individual and household-level data from the 2015 and 2018 annual malaria indicator surveys on Bioko Island, as well as remotely-sensed environmental data in multilevel logistic regression models to quantify the odds of malaria infection. The analyses were stratified by urban and rural settings and by survey year. Results Malaria prevalence was higher in 10–14-year-old children and similar between female and male individuals. After adjusting for demographic factors and other covariates, many of the variables investigated showed no significant association with malaria infection. The factor most strongly associated was history of travel to mainland Equatorial Guinea (mEG), which increased the odds significantly both in urban and rural settings (people who travelled had 4 times the odds of infection). Sleeping under a long-lasting insecticidal net decreased significantly the odds of malaria across urban and rural settings and survey years (net users had around 30% less odds of infection), highlighting their contribution to malaria control on the Island. Improved housing conditions indicated some protection, though this was not consistent across settings and survey year. Conclusions Malaria risk on Bioko Island is heterogeneous and determined by a combination of factors interacting with local mosquito ecology. These interactions grant further investigation in order to better adapt control according to need. The single most important risk factor identified was travel to mEG, in line with previous investigations, and represents a great challenge for the success of malaria control on the Island. © The Author(s) 2023
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title_short	Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions
url	https://dx.doi.org/10.1186/s12936-023-04504-7
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author2	Janko, Mark Hergott, Dianna E. B. Donfack, Olivier T. Smith, Jordan M. Mba Eyono, Jeremías Nzamío DeBoer, Kylie R. Nguema Avue, Restituto Mba Phiri, Wonder P. Aldrich, Edward M. Schwabe, Christopher Stabler, Thomas C. Rivas, Matilde Riloha Cameron, Ewan Guerra, Carlos A. Cook, Jackie Kleinschmidt, Immo Bradley, John
author2Str	Janko, Mark Hergott, Dianna E. B. Donfack, Olivier T. Smith, Jordan M. Mba Eyono, Jeremías Nzamío DeBoer, Kylie R. Nguema Avue, Restituto Mba Phiri, Wonder P. Aldrich, Edward M. Schwabe, Christopher Stabler, Thomas C. Rivas, Matilde Riloha Cameron, Ewan Guerra, Carlos A. Cook, Jackie Kleinschmidt, Immo Bradley, John
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The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach. Methods This study used individual and household-level data from the 2015 and 2018 annual malaria indicator surveys on Bioko Island, as well as remotely-sensed environmental data in multilevel logistic regression models to quantify the odds of malaria infection. The analyses were stratified by urban and rural settings and by survey year. Results Malaria prevalence was higher in 10–14-year-old children and similar between female and male individuals. After adjusting for demographic factors and other covariates, many of the variables investigated showed no significant association with malaria infection. The factor most strongly associated was history of travel to mainland Equatorial Guinea (mEG), which increased the odds significantly both in urban and rural settings (people who travelled had 4 times the odds of infection). Sleeping under a long-lasting insecticidal net decreased significantly the odds of malaria across urban and rural settings and survey years (net users had around 30% less odds of infection), highlighting their contribution to malaria control on the Island. Improved housing conditions indicated some protection, though this was not consistent across settings and survey year. Conclusions Malaria risk on Bioko Island is heterogeneous and determined by a combination of factors interacting with local mosquito ecology. These interactions grant further investigation in order to better adapt control according to need. 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Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions

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