Evidence map›Paper›PMID 29448965›Full record

ArticleInfectious diseases of poverty2018

Temporo-spatial dynamics and behavioural patterns of 2012 cholera epidemic in the African mega-city of Conakry, Guinea.

Alexandre Blake, Veronique Sarr Keita, Delphine Sauvageot, Mamadou Saliou, Berthe Marie Njanpop, Fode Sory, Bertrand Sudre, Koivogui Lamine, Martin Mengel, Bradford D Gessner and 1 more

Abstract read
In one paragraph

Article in Infectious diseases of poverty, 2018. 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
–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

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

  1. Pooled it
  2. Article
  3. Dissecting Water, Sanitation, and Hygiene (WaSH) to Assess Risk Factors for Cholera in Shashemene, Oromia Region, Ethiopia.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024
    Article
  4. Article
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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.

Alexandre BlakeAgence de Médecine Préventive, Paris, France. alexgeorges.blake@gmail.com.
Veronique Sarr KeitaDivision Prévention et Lutte contre la Maladie (DPLM), Ministère de la santé Publique et de l'Hygiène Publique Conakry, Conakry, Guinea.
Delphine SauvageotAgence de Médecine Préventive, Paris, France.
Mamadou SaliouInstitut National de Sante Publique (INSP), Conakry, Guinea.
Berthe Marie NjanpopAgence de Médecine Préventive, Paris, France.
Fode SoryDivision Prévention et Lutte contre la Maladie (DPLM), Ministère de la santé Publique et de l'Hygiène Publique Conakry, Conakry, Guinea.
Bertrand SudreFranche-Comté university (UMR 6249 chrono-environnement), Besançon, France.
Koivogui LamineInstitut National de Sante Publique (INSP), Conakry, Guinea.
Martin MengelAgence de Médecine Préventive, Paris, France.
Bradford D GessnerAgence de Médecine Préventive, Paris, France.
Keita SakobaDivision Prévention et Lutte contre la Maladie (DPLM), Ministère de la santé Publique et de l'Hygiène Publique Conakry, Conakry, Guinea.

Funding

Bill and Melinda Gates Foundation OPPGH5233
6 · The paper itself

Abstract

backgroundCholera is endemic in Guinea, having suffered consecutive outbreaks from 2004 to 2008 followed by a lull until the 2012 epidemic. Here we describe the temporal-spatial and behavioural characteristics of cholera cases in Conakry during a three-year period, including the large-scale 2012 epidemic.

methodsWe used the national and African Cholera Surveillance Network (Africhol) surveillance data collected from every cholera treatment centre in Conakry city from August 2011 to December 2013. The prevalence of suspect and confirmed cholera cases, the case fatality ratio (CFR), and the factors associated with suspected cholera were described according to three periods: pre-epidemic (A), epidemic 2012 (B) and post epidemic (C). Weekly attack rates and temporal-spatial clustering were calculated at municipality level for period B. Cholera was confirmed by culture at the cholera national reference laboratory.

resultsA total of 4559 suspect cases were reported: 66, 4437, and 66 suspect cases in periods A, B and C, respectively. Among the 204 suspect cases with culture results available, 6%, 60%, and 70% were confirmed in periods A, B, and C, respectively. With 0.3%, the CFR was significantly lower in period B than in periods A (7.6%) and C (7.1%). The overall attack rate was 0.28% in period B, ranging from 0.17% to 0.31% across municipalities. Concomitantly, a cluster of cases was identified in two districts in the northern part of Conakry. At 14%, rice water stools were less frequent in period A than in period B and C (78% and 84%). Dehydration (31% vs 94% and 89%) and coma (0.4% vs 3.1% and 2.9%) were lower during period B than in periods A and C. The treatment of drinking water was less frequent in period A, while there were more reports of recent travel in period C.

conclusionsThe epidemic dynamic and the sociological description of suspect cases before, during, and after the large-scale epidemic revealed that the Vibrio cholerae was already present before the epidemic. However, it appeared that infected individuals reacted differently in terms of disease severity as well as their access to treated water and travel habits. Such an in-depth description of cholera epidemics should be systematically carried out in cholera endemic settings in order to prioritize higher risk areas, identify transmission factors, and optimize preventive interventions.

Indexed as

AdultCholeraEpidemicsFemaleGuineaHumansMaleRisk FactorsSpatial AnalysisYoung AdultCholeraGuineaSpace-time clustering

Identifiers

PMID29448965
PMCPMC5815196

What OpenQuestion holds

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LicenceCC BY
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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.