Malaria in an Internally Displaced Persons Camp in the Democratic Republic of the Congo
Notice bibliographique
Résumé
To the Editor— We read with interest your 2016 supplement “Malaria in Highly Endemic Areas,” in which several articles describe malaria control in 3 countries: Burkina Faso, Nigeria, and Uganda. Contributing an estimated 7, 8.5, and 61 million cases annually, respectively, to the global burden of malaria [1], these are worthy countries of focus. Conspicuously underrepresented, however, was the Democratic Republic of the Congo (DRC), with 19 million cases annually [1]. Data are scarce from the DRC because of challenges to research and public health interventions in remote zones affected by violent conflict [2, 3]. Thus, the DRC is considered the world’s least feasible country for malaria elimination [4] and may be overlooked in global control efforts. We wish to call attention to the burden of malaria in the DRC and its vulnerable population of internally displaced persons (IDPs), providing an illustrative snapshot of malaria in an IDP camp in war-torn DRC. Lushebere is the largest IDP camp in the region of Masisi, DRC, formed in 2013 when approximately 1100 IDPs arrived, fleeing nearby violent conflict, followed by a second wave of approximately 1500 IDPs in early 2014. We reviewed health records of IDPs presenting for treatment of febrile illness between January and July 2014 to the only health center in the area. All patients were tested for malaria using a histidine-rich protein 2 (HRP2)–based rapid diagnostic test (Paracheck-Pf). Ethics approval was obtained from Comité d’Éthique du Nord Kivu (Butembo, DRC) and the University of Alberta. Of 751 febrile patients, 323 (43%) tested positive for malaria, including 169 of 279 (61%) of children <5 years of age. Using camp census data to estimate number at risk, the incidence of medically attended malaria was at least 910 per 1000 children aged <5 per year (compared to 246/1000 at risk per year overall in the World Health Organization African region [1]). Of 323 malaria cases, 292 (90%) were uncomplicated and 31 (9.6%) were severe. Four deaths occurred, 2 in children <5 years of age. Patient characteristics are shown in Table 1. Free bed net distribution was implemented as a control measure, although coverage was incomplete, particularly among recent arrivals to the camp. Overall, 452 of 751 (60%) febrile patients lived in households that owned a bed net and of these, 269 of 452 (59%) reported sleeping under the net. Patients who slept under a bed net were less likely to test positive for malaria (24/269 [8.9%] vs 299/482 [62%]; P < .0001). In a multivariable logistic regression model, age <5 years (adjusted odds ratio [AOR], 2.97; 95% confidence interval [CI], 1.84–4.81), lack of bed net use (AOR, 15.63; 95% CI, 9.09–27.03), and recent arrival in the IDP camp (AOR, 18.18; 95% CI, 11.63–28.57) remained significant predictors of malaria. Characteristics of Patients From Internally Displaced Persons Camp Presenting to a Health Center for Management of Acute Febrile Illness, According to Malaria Rapid Diagnostic Test Status (N = 751) Data are presented as No. (%) unless otherwise indicated. Abbreviation: RDT, rapid diagnostic test. aLiteracy rates exclude individuals ≤14 years of age. Characteristics of Patients From Internally Displaced Persons Camp Presenting to a Health Center for Management of Acute Febrile Illness, According to Malaria Rapid Diagnostic Test Status (N = 751) Data are presented as No. (%) unless otherwise indicated. Abbreviation: RDT, rapid diagnostic test. aLiteracy rates exclude individuals ≤14 years of age. This case series from an IDP camp deep within the zone of insecurity in the DRC serves as a reminder of the malaria burden in complex, chronic humanitarian crises in the tropics [5–8]. Almost two-thirds of refugees and IDPs live in regions where malaria is endemic [9], including 1.5 million IDPs in the DRC alone [10]. Hard-to-reach populations affected by violent conflict should not be forgotten in global malaria control efforts. Potential conflicts of interest. All authors: No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,012 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,009 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».