Evidence map›Paper›PMID 26573911›Full record

ArticleMalaria journal2015

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

Policarpo Ncogo, Zaida Herrador, Maria Romay-Barja, Emely García-Carrasco, Gloria Nseng, Pedro Berzosa, Maria A Santana-Morales, Matilde Riloha, Pilar Aparicio, Basilio Valladares and 1 more

Abstract read
In one paragraph

Article in Malaria journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

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  12. Comparing metapopulation dynamics of infectious diseases under different models of human movement.Proceedings of the National Academy of Sciences of the United States of America · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Policarpo NcogoReference Centre for Epidemics Control of Equatorial Guinea (CRCE), Ministry of Health and Social Welfare, Malabo, Equatorial Guinea. pncogo@crce-guinea.org.
Zaida HerradorNational Centre of Tropical Medicine, Instituto de Salud Carlos III (ISCIII) C/Sinesio Delgado, 6-Pabellón 13, 28029, Madrid, Spain. zherrador@isciii.es.
Maria Romay-BarjaNational Centre of Tropical Medicine, Instituto de Salud Carlos III (ISCIII) C/Sinesio Delgado, 6-Pabellón 13, 28029, Madrid, Spain. mromay@isciii.es.
Emely García-CarrascoDepartment of Preventive Medicine, University Hospital of Albacete, Albacete, Spain. mlycarrasco@gmail.com.
Gloria NsengMinistry of Health and Social Welfare, Malabo, Equatorial Guinea. glorianseng@yahoo.es.
Pedro BerzosaNational Centre of Tropical Medicine, Instituto de Salud Carlos III (ISCIII) C/Sinesio Delgado, 6-Pabellón 13, 28029, Madrid, Spain. pberzosa@isciii.es.
Maria A Santana-MoralesThe Spanish Tropical Diseases Research Network (RICET in Spanish), Madrid, Spain. msanmor@msn.com.
Matilde RilohaMinistry of Health and Social Welfare, Malabo, Equatorial Guinea. riloharivas@yahoo.es.
Pilar AparicioNational Centre of Tropical Medicine, Instituto de Salud Carlos III (ISCIII) C/Sinesio Delgado, 6-Pabellón 13, 28029, Madrid, Spain. paparicio@isciii.es.
Basilio ValladaresThe Spanish Tropical Diseases Research Network (RICET in Spanish), Madrid, Spain. bvallada@ull.es.
Agustín BenitoNational Centre of Tropical Medicine, Instituto de Salud Carlos III (ISCIII) C/Sinesio Delgado, 6-Pabellón 13, 28029, Madrid, Spain. abenito@isciii.es.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMalaria 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.

methodsFrom 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.

resultsPrevalence 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.

conclusionThe 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.

Indexed as

AdolescentAdultAgedAged, 80 and overAnimalsChildChild, PreschoolCross-Sectional StudiesEquatorial GuineaFemaleHumansInfantMalariaMaleMiddle AgedPrevalence

Identifiers

PMID26573911
PMCPMC4647797

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.