Assessing the preparedness of primary healthcare facilities during a cholera outbreak in Kinshasa, Democratic Republic of the Congo, 2018.

OBJECTIVE: During the 2017-2018 cholera outbreak in Kinshasa, many patients initially reported to primary healthcare centers (HCs) before being transferred to the nearest cholera treatment centers. This study aims to assess the level of preparedness of HCs in responding to cholera outbreaks. STUDY DESIGN: Descriptive cross-sectional survey. METHODS: We conducted a descriptive cross-sectional survey in 180 of 374 primary HCs in Kinshasa. We collected data on 14 cholera preparedness criteria and described their prevalence among HCs. We used logistic regression to assess the association between each preparedness criteria and previous reporting of cholera cases by HCs. RESULTS: The median number of preparedness criteria met by HCs was 5 [range: 0-11]. Five percent (n = 9) of HCs [95% confidence interval (CI): 2.3%-9.3%] met at least 10 criteria. HCs that previously reported ≥3 cholera cases were less likely to meet the criteria for 'presence of an isolation unit' (adjusted odds ratio [aOR]: 0.12; 95% CI [0.03-0.61]) and 'availability of sufficient quantity of chlorine' (aOR: 0.13; 95% CI [0.02-0.64]). CONCLUSIONS: Despite past experience of cholera cases, health facilities in Kinshasa exhibit a low level of cholera preparedness. There is a need to prioritize the reinforcement of the preparedness of primary HCs to prevent future cholera outbreaks.

Environmental and anthropogenic factors associated with increased malaria incidence in South-Kivu Province, Democratic Republic of the Congo.

OBJECTIVE: To examine environmental and human factors that affect the spatial and temporal dynamism of malaria in DRC's South-Kivu province. METHODS: In a cross-sectional study conducted between 1 January 2010 and 31 December 2015, spatial distribution was determined through thematic maps of malaria attack rate. SatScan ™ software and Monte Carlo test were used to identify spatial risk clusters. Temporal evolutions were analysed using the Cleveland algorithm. Generalized Additive Models for Location Scale and Shape and negative binomial regression were used to assess the independent human and environmental factors associated with incident malaria. RESULTS: The cumulative annual incidence of malaria increased from 10 968/100 000 in 2013 to 15 501/100 000 in 2015 (P for trend ˂0.001); malaria lethality increased from 0.1% in 2013 to 0.3% in 2015 (P for trend = 0.62). Between 2010 and 2015, 18 of 34 health zones consistently reported the highest attack rates, which ranged from 25 000 to 50 000/100 000. Four risk clusters areas were identified, with relative risk (RR) of 1.2 to 3.0, from which malaria was reported continuously during each year. Factors significantly associated with malaria cases were agro-pisciculture practices (Incidence Risk Ratio [IRR]: 1.96; 95% CI: 1.23-3.13) and the presence of a lake in the health zone (IRR: 2.48, 95% CI: 1.51-4.42). CONCLUSIONS: Malaria control in this setting must be intensified in peri-lacustrine areas and those in which the population is intensively engaged in standing water-associated activities.

OBJECTIF: Examiner les facteurs environnementaux et humains qui affectent le dynamisme spatial et temporel du paludisme dans la province du Sud-Kivu en RDC. MÉTHODES: Dans une étude transversale menée entre le 1er janvier 2010 et le 31 décembre 2015, la distribution spatiale a été déterminée à l'aide de cartes thématiques du taux de cas de paludisme. Le logiciel SatScan™ et le test Monte Carlo ont été utilisés pour identifier les grappes de risques spatiaux. Les évolutions temporelles ont été analysées à l'aide de l'algorithme de Cleveland. Des modèles additifs généralisés pour l'échelle et la forme de l'emplacement et la régression binomiale négative ont été utilisés pour évaluer les facteurs humains et environnementaux indépendants associés à l'incidence du paludisme. RÉSULTATS: L'incidence annuelle cumulée du paludisme est passée de 10.968/100 000 en 2013 à 15.501/100 000 en 2015 (p pour la tendance ˂0,001); la létalité du paludisme est passée de 0,1% en 2013 à 0,3% en 2015 (p pour tendance = 0,62). Entre 2010 et 2015, 18 des 34 zones de santé ont constamment rapporté des taux de cas les plus élevés, qui variaient de 25.000 à 50.000/100 000. Quatre zones de risques de grappes ont été identifiées, avec un risque relatif (RR) de 1,2 à 3,0 à partir desquelles le paludisme a été rapporté en continu chaque année. Les facteurs significativement associés aux cas de paludisme étaient: les pratiques agro-piscicoles (Ratio d'Incidence de Risque [IRR]: 1,96 ; IC95%: 1,23-3,13) et la présence d'un lac dans la zone de santé (TRI: 2,48 ; IC95%: 1,51-4,42). CONCLUSIONS: La lutte contre le paludisme dans ce contexte doit être intensifiée dans les zones péri-lacustres et celles dans lesquelles la population est intensément engagée dans des activités liées à l'eau stagnante.