Malaria prevalence in Bata district, Equatorial Guinea: a cross-sectional study

BACKGROUND: Malaria has traditionally been a leading public health problem in Equatorial Guinea. After completion, in September 2011, of the integrated set of interventions against malaria launched by the Global Fund Malaria Programme in the mainland area, the epidemiological situation of malaria remains unknown. The aim of this study was to investigate the prevalence rate of malaria and associated factors based on the rapid diagnosis test (RDT) in Bata district, in order to provide evidence that will reinforce the National Malaria Control Programme. METHODS: From June to August 2013, a representative cross sectional survey using a multistage, stratified, cluster-selected sample was carried out in urban zones and rural villages from Bata district. Data on socio-demographic, health status and malaria-related behaviours was collected. Malaria diagnosis was performed by RDT. Bivariate and multivariable statistical methods were employed to assess malaria prevalence and its association with different factors. RESULTS: Prevalence of malaria was higher in rural settings (58.9 %; CI 95 % 55.2-62.5 %) than in the sampled urban communities (33.9 %; CI 95 % 31.1-36.9 %). Presence of anaemia was also high, especially in rural sites (89.6 vs. 82.8 %, p < 0.001). The analyses show that a positive RDT result was significantly associated with age group, the most affected age range being 13 months-14 years old. Other significant covariates were ethnic group (only in urban sites), number of adults living in the house (only in rural villages) previous history of fever, anaemia (only in urban sites) and sleeping under a bed net. Moreover, those who never slept under a bed net were two times more likely to have malaria. CONCLUSION: The prevalence of malaria was high in Bata district, especially in rural villages. The National Programme to fight malaria in Equatorial Guinea should take into account the differences found between rural and urban communities and age groups to target appropriately those worst affected. The findings of this study will assist in planning and undertaking regional policy and other preventive initiatives.We thank the study participants for volunteering to participate in the study; the data collectors for performing field work; the Centro de Referencia de Control de Endemias (CRCE) from the Health Institute Carlos III (ISCIII) for providing logistic and technical support, and the Ministry of Health and Social Welfare from Equatorial Guinea for creating a conducive environment during the field work. Special thanks to the Spanish Agency for International Development Cooperation (AECID) and the Network Biomedical Research on Tropical Diseases (RICET in Spanish) for the financial support that enabled us to carry out this study. Corresponding author’s affiliation centre belongs to the Network Biomedical Research on Tropical Diseases (RICET in Spanish): RD12/0018/0001.S

Spatial clustering and risk factors of malaria infections in Bata district, Equatorial Guinea

Abstract Background The transmission of malaria is intense in the majority of the countries of sub-Saharan Africa, particularly in those that are located along the Equatorial strip. The present study aimed to describe the current distribution of malaria prevalence among children and its environment-related factors as well as to detect malaria spatial clusters in the district of Bata, in Equatorial Guinea. Methods From June to August 2013 a representative cross-sectional survey using a multistage, stratified, cluster-selected sample was carried out of children in urban and rural areas of Bata District. All children were tested for malaria using rapid diagnostic tests (RDTs). Results were linked to each household by global position system data. Two cluster analysis methods were used: hot spot analysis using the Getis-Ord Gi statistic, and the SaTScan™ spatial statistic estimates, based on the assumption of a Poisson distribution to detect spatial clusters. In addition, univariate associations and Poisson regression model were used to explore the association between malaria prevalence at household level with different environmental factors. Results A total of 1416 children aged 2 months to 15 years living in 417 households were included in this study. Malaria prevalence by RDTs was 47.53%, being highest in the age group 6–15 years (63.24%, p < 0.001). Those children living in rural areas were there malaria risk is greater (65.81%) (p < 0.001). Malaria prevalence was higher in those houses located <1 km from a river and <3 km to a forest (IRR: 1.31; 95% CI 1.13–1.51 and IRR: 1.44; 95% CI 1.25–1.66, respectively). Poisson regression analysis also showed a decrease in malaria prevalence with altitude (IRR: 0.73; 95% CI 0.62–0.86). A significant cluster inland of the district, in rural areas has been found. Conclusions This study reveals a high prevalence of RDT-based malaria among children in Bata district. Those households situated in inland rural areas, near to a river, a green area and/or at low altitude were a risk factor for malaria. Spatial tools can help policy makers to promote new recommendations for malaria control