Evidence map›Paper›PMID 32370941›Full record

ArticleSpatial and spatio-temporal epidemiology2020

Severe-malaria infection and its outcomes among pregnant women in Burkina Faso health-districts: Hierarchical Bayesian space-time models applied to routinely-collected data from 2013 to 2018.

Toussaint Rouamba, Sekou Samadoulougou, Halidou Tinto, Victor A Alegana, Fati Kirakoya-Samadoulougou

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Spatial and spatio-temporal epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 13% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Geographical Detector-Based Spatial Modeling of the COVID-19 Mortality Rate in the Continental United States.International journal of environmental research and public health · 2021
    Article
  5. Article
  6. Article
  7. Article
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

5 authors at 4 institutions in 5 countries.

Toussaint RouambaClinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Santé, 42, Avenue Kumda-Yonre, Centre National de la Recherche Scientifique et Technologique, 11 BP 218 Ouaga CMS 11, Ouagadougou, Burkina Faso; Centre d'Epidémiologie, Biostatistique et Recherche Clinique, Ecole de Santé Publique, Université Libre de Bruxelles (ULB), Route de Lennik, 808 B-1070, Bruxelles, Belgique. Electronic address: rouambatoussaint@gmail.com.
Sekou SamadoulougouEvaluation Platform on Obesity Prevention, Quebec Heart and Lung Institute Research Center, Quebec City, QC G1V 4G5, Canada; Centre for Research on Planning and Development (CRAD), Laval University, Quebec, G1V 0A6, Canada. Electronic address: sekou-ouindpanga.samadoulougou@criucpq.ulaval.ca.
Halidou TintoClinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Santé, 42, Avenue Kumda-Yonre, Centre National de la Recherche Scientifique et Technologique, 11 BP 218 Ouaga CMS 11, Ouagadougou, Burkina Faso.
Victor A AleganaPopulation Health Theme, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya; Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK.
Fati Kirakoya-SamadoulougouCentre d'Epidémiologie, Biostatistique et Recherche Clinique, Ecole de Santé Publique, Université Libre de Bruxelles (ULB), Route de Lennik, 808 B-1070, Bruxelles, Belgique. Electronic address: fkirakoy@ulb.ac.be.
Centre National de la Recherche Scientifique et Technologique · BFMontreal Heart Institute · CAUniversité Libre de Bruxelles · BEUniversity of Southampton · GB

Funding

Wellcome Trust 203077Wellcome Trust 211208/Z/18/Z
6 · The paper itself

Abstract

Fine-scale hotspots detection is crucial for optimum delivery of essential health-services for reducing severe malaria in pregnancy (MiP) and death cases in Burkina Faso. This study used hierarchical-Bayesian Spatio-temporal modeling to explore space-time patterns and pinpoint health-districts with an exceedance probability of severe MiP incidence and fatality rate. Study also assessed effect of health-district service delivery (readiness) on severe-MiP outcomes. Severe-MiP fatality rate declined considerably while its incidence rate remained unchanged between January-2013 and December-2018. Severe-MiP cases persisted throughout the year with peaks between August and November. These peaks increased 2.5-fold the fatality rate. Furthermore, severe-MiP fatality was higher in health-districts classified as low-readiness (IRR = 2.469, 95%CrI: 1.632-3.738). However, the fatality rate decreased significantly with proper coverage with three doses for intermittent-preventive-treatment with sulphadoxine-pyrimethamine. Severe-MiP burden was heterogeneous spatially and temporally. The study suggested that health-programs should increase health-districts readiness and optimize resource allocation in high burden areas and months.

Indexed as

Spatial AnalysisAdultAntimalarialsBayes TheoremBurkina FasoDrug CombinationsFemaleHumansIncidenceMalariaPregnancyPregnancy Complications, ParasiticPyrimethamineSeverity of Illness IndexSulfadoxineTreatment OutcomeAntimalarialsDrug Combinationsfanasil, pyrimethamine drug combinationPyrimethamineSulfadoxineBurkina-FasoDeathsPregnancyReadinessSevere-malariaSpatio-temporal

Identifiers

PMID32370941
PMCPMC7613547
OpenAlexW3005748517

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.