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. 2023 Mar 1;22(1):72.
doi: 10.1186/s12936-023-04504-7.

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

Guillermo A García  1 , Mark Janko  2 , Dianna E B Hergott  3 , Olivier T Donfack  4 , Jordan M Smith  5 , Jeremías Nzamío Mba Eyono  4 , Kylie R DeBoer  5 , Restituto Mba Nguema Avue  4 , Wonder P Phiri  4 , Edward M Aldrich  6 , Christopher Schwabe  6 , Thomas C Stabler  7   8 , Matilde Riloha Rivas  9 , Ewan Cameron  10 , Carlos A Guerra  5 , Jackie Cook  11 , Immo Kleinschmidt  11   12 , John Bradley  11
Affiliations

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

Guillermo A García et al. Malar J. .

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.

Keywords: Importation; Malaria; Risk factors; Targeted interventions; Vector control.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Bioko Island and its location in the Gulf of Guinea. The continental territory of Equatorial Guinea is known as Río Muni. The color scale represents predicted PfPR in children, reconstructed from data produced by the Malaria Atlas Project, which are available for use under the Creative Commons Attribution 3.0 Unported License
Fig. 2
Fig. 2
Malaria prevalence in children 2–14 years old on Bioko Island, 2004–2021
Fig. 3
Fig. 3
Odds ratios estimated from regression models of all risk factors for malaria transmission on Bioko island and 95% confidence intervals, stratified by rural (left) and urban (right) settings and malaria annual indicator survey year, 2015 (blue) and 2018 (orange)
Fig. 4
Fig. 4
Malaria prevalence on Bioko Island in 2015 and 2018. Pixels represent 1 × 1 km inhabited areas. Raw PfPR data from each Malaria Indicator Survey (MIS) were interpolated using kernel smoothing
See this image and copyright information in PMC

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