Evolution du système national d’information sanitaire de la république démocratique du Congo entre 2009 et 2015

Introduction: Lancé en 1987, le Système national d'information sanitaire (SNIS) de la République Démocratique du Congo (DR Congo) a été évalué en 2009 et 2015 moyennant l'outil HMN (Health metrics network). L'objectif de cette étude était d'estimer les progrès réalisés entre ces deux évaluations.Méthodes: Il s'agissait d'une analyse des données secondaires des évaluations du SNIS, qui a consisté à comparer le degré de satisfaction par rapport aux six composantes de cet outil entre 2009 et 2015, à savoir; les ressources, les indicateurs, les sources de données, la gestion des données, les produits de l'information, la diffusion et l'utilisation des données.Résultats: Entre 2009 et 2015, le degré de satisfaction des répondants a évolués de la manière suivante: 49% contre 61% pour les ressources; 73% vs 88% pour les indicateurs; 52% vs 61% pour les sources de données; 41% vs 45% pour la gestion des données; 74% contre 77% pour les produits de l'information et enfin 51% vs 51% pour la diffusion et l'utilisation des données. Dans l'ensemble, le score moyen est passé de 59% à 64% avec une mention « satisfaisante ».Conclusion: Notre étude a montré que le SNIS de la RD Congo n'a pas significativement évolué entre 2009 et 2015, et n'était pas en mesure de fournir en temps réel l'information sanitaire fiable pour la prise de décision et la planification des programmes de santé.Mots clés: Outil HMN, SNIS, RD CongoEnglish Title: Evolution of the National Health Information System in the Democratic Republic of the Congo between 2009 and 2015English AbstractIntroduction: Launched in 1987, the National Health Information System (NHIS) in the Democratic Republic of the Congo (DR Congo) was evaluated in 2009 and 2015 using the HMN (Health Metrics Network) assessment tool. This study aimed to estimate the progress made between these two evaluations.Methods: We performed an analysis of the secondary data from the evaluations of the NHIS, which was based on the comparison of the satisfaction level between the six components of this tool between 2009 and 2015, namely: resources, indicators, data sources, data management, information products, dissemination and use of data.Results: Between 2009 and 2015, respondents' satisfaction level changed as follow: resouces 49% vs 61%; indicators 73% vs 88%; data sources 52% vs 61%; data management 41% vs 45%; information products 74% vs 77%; dissemination and use of data 51% vs 51%. In general the average score increased from 59% to 64% with "satisfactory" mark.Conclusion: Our study shows that the NHIS in the DR Congo has not changed significantly between 2009 and 2015 and that it couldn't provide real-time reliable health information for decision-making and health program planning.Keywords: HMN tool, NHIS, DR Cong

Predictors of measles vaccination coverage among children 6-59 months of age in the Democratic Republic of the Congo.

BackgroundMeasles is a significant contributor to child mortality in the Democratic Republic of the Congo (DRC), despite routine immunization programs and supplementary immunization activities (SIA). Further, national immunization coverage levels may hide disparities among certain groups of children, making effective measles control even more challenging. This study describes measles vaccination coverage and reporting methods and identifies predictors of vaccination among children participating in the 2013-2014 DRC Demographic and Health Survey (DHS).MethodsWe examined vaccination coverage of 6947 children aged 6-59 months. A multivariate logistic regression model was used to identify predictors of vaccination among children reporting vaccination via dated card in order to identify least reached children. We also assessed spatial distribution of vaccination report type by rural versus urban residence.ResultsUrban children with educated mothers were more likely to be vaccinated (OR = 4.1, 95% CI: 1.6, 10.7) versus children of mothers with no education, as were children in wealthier rural families (OR = 2.9, 95% CI: 1.9, 4.4). At the provincial level, urban areas more frequently reported vaccination via dated card than rural areas.ConclusionsResults indicate that, while the overall coverage level of 70% is too low, socioeconomic and geographic disparities also exist which could make some children even less likely to be vaccinated. Dated records of measles vaccination must be increased, and groups of children with the greatest need should be targeted. As access to routine vaccination services is limited in DRC, identifying and targeting under-reached children should be a strategic means of increasing country-wide effective measles control

Conditional Cash Transfers Improve Retention in PMTCT Services by Mitigating the Negative Effect of Not Having Money to Come to the Clinic

To elucidate the mechanisms by which a cash incentive intervention increases retention in prevention of mother-to-child transmission (PMTCT) services

Conditional Cash Transfers to Increase Retention in PMTCT Care, Antiretroviral Adherence, and Postpartum Virological Suppression: A Randomized Controlled Trial

Novel strategies are needed to increase retention in prevention of mother-to-child HIV transmission (PMTCT) services. We have recently shown that small, incremental cash transfers conditional on attending clinic resulted in increased retention along the PMTCT cascade. However, whether women who receive incentives to attend clinic visits are as adherent to antiretrovirals (ARV) as those who do not was unknown

Projections of epidemic transmission and estimation of vaccination impact during an ongoing Ebola virus disease outbreak in Northeastern Democratic Republic of Congo, as of Feb. 25, 2019.

BackgroundAs of February 25, 2019, 875 cases of Ebola virus disease (EVD) were reported in North Kivu and Ituri Provinces, Democratic Republic of Congo. Since the beginning of October 2018, the outbreak has largely shifted into regions in which active armed conflict has occurred, and in which EVD cases and their contacts have been difficult for health workers to reach. We used available data on the current outbreak, with case-count time series from prior outbreaks, to project the short-term and long-term course of the outbreak.MethodsFor short- and long-term projections, we modeled Ebola virus transmission using a stochastic branching process that assumes gradually quenching transmission rates estimated from past EVD outbreaks, with outbreak trajectories conditioned on agreement with the course of the current outbreak, and with multiple levels of vaccination coverage. We used two regression models to estimate similar projection periods. Short- and long-term projections were estimated using negative binomial autoregression and Theil-Sen regression, respectively. We also used Gott's rule to estimate a baseline minimum-information projection. We then constructed an ensemble of forecasts to be compared and recorded for future evaluation against final outcomes. From August 20, 2018 to February 25, 2019, short-term model projections were validated against known case counts.ResultsDuring validation of short-term projections, from one week to four weeks, we found models consistently scored higher on shorter-term forecasts. Based on case counts as of February 25, the stochastic model projected a median case count of 933 cases by February 18 (95% prediction interval: 872-1054) and 955 cases by March 4 (95% prediction interval: 874-1105), while the auto-regression model projects median case counts of 889 (95% prediction interval: 876-933) and 898 (95% prediction interval: 877-983) cases for those dates, respectively. Projected median final counts range from 953 to 1,749. Although the outbreak is already larger than all past Ebola outbreaks other than the 2013-2016 outbreak of over 26,000 cases, our models do not project that it is likely to grow to that scale. The stochastic model estimates that vaccination coverage in this outbreak is lower than reported in its trial setting in Sierra Leone.ConclusionsOur projections are concentrated in a range up to about 300 cases beyond those already reported. While a catastrophic outbreak is not projected, it is not ruled out, and prevention and vigilance are warranted. Prospective validation of our models in real time allowed us to generate more accurate short-term forecasts, and this process may prove useful for future real-time short-term forecasting. We estimate that transmission rates are higher than would be seen under target levels of 62% coverage due to contact tracing and vaccination, and this model estimate may offer a surrogate indicator for the outbreak response challenges

Continuous quality improvement interventions to improve long-term outcomes of antiretroviral therapy in women who initiated therapy during pregnancy or breastfeeding in the Democratic Republic of Congo: design of an open-label, parallel, group randomized trial

Abstract Background Despite the rapid adoption of the World Health Organization’s 2013 guidelines, children continue to be infected with HIV perinatally because of sub-optimal adherence to the continuum of HIV care in maternal and child health (MCH) clinics. To achieve the UNAIDS goal of eliminating mother-to-child HIV transmission, multiple, adaptive interventions need to be implemented to improve adherence to the HIV continuum. Methods The aim of this open label, parallel, group randomized trial is to evaluate the effectiveness of Continuous Quality Improvement (CQI) interventions implemented at facility and health district levels to improve retention in care and virological suppression through 24 months postpartum among pregnant and breastfeeding women receiving ART in MCH clinics in Kinshasa, Democratic Republic of Congo. Prior to randomization, the current monitoring and evaluation system will be strengthened to enable collection of high quality individual patient-level data necessary for timely indicators production and program outcomes monitoring to inform CQI interventions. Following randomization, in health districts randomized to CQI, quality improvement (QI) teams will be established at the district level and at MCH clinics level. For 18 months, QI teams will be brought together quarterly to identify key bottlenecks in the care delivery system using data from the monitoring system, develop an action plan to address those bottlenecks, and implement the action plan at the level of their district or clinics. Discussion If proven to be effective, CQI as designed here, could be scaled up rapidly in resource-scarce settings to accelerate progress towards the goal of an AIDS free generation. Trial registration The protocol was retrospectively registered on February 7, 2017. ClinicalTrials.gov Identifier: NCT03048669

Association of Previous Measles Infection With Markers of Acute Infectious Disease Among 9- to 59-Month-Old Children in the Democratic Republic of the Congo.

BackgroundTransient immunosuppression and increased susceptibility to other infections after measles infection is well known, but recent studies have suggested the occurrence of an "immune amnesia" that could have long-term immunosuppressive effects.MethodsWe examined the association between past measles infection and acute episodes of fever, cough, and diarrhea among 2350 children aged 9 to 59 months whose mothers were selected for interview in the 2013-2014 Democratic Republic of the Congo (DRC) Demographic and Health Survey (DHS). Classification of children who had had measles was completed using maternal recall and measles immunoglobulin G serostatus obtained via dried-blood-spot analysis with a multiplex immunoassay. The association with time since measles infection and fever, cough, and diarrhea outcomes was also examined.ResultsThe odds of fever in the previous 2 weeks were 1.80 (95% confidence interval [CI], 1.25-2.60) among children for whom measles was reported compared to children with no history of measles. Measles vaccination demonstrated a protective association against selected clinical markers of acute infectious diseases.ConclusionOur results suggest that measles might have a long-term effect on selected clinical markers of acute infectious diseases among children aged 9 to 59 months in the DRC. These findings support the immune-amnesia hypothesis suggested by others and underscore the need for continued evaluation and improvement of the DRC's measles vaccination program

Neurological, Cognitive, and Psychological Findings Among Survivors of Ebola Virus Disease From the 1995 Ebola Outbreak in Kikwit, Democratic Republic of Congo: A Cross-sectional Study.

BackgroundClinical sequelae of Ebola virus disease (EVD) have not been described more than 3 years postoutbreak. We examined survivors and close contacts from the 1995 Ebola outbreak in Kikwit, Democratic Republic of Congo (DRC), and determined prevalence of abnormal neurological, cognitive, and psychological findings and their association with EVD survivorship.MethodsFrom August to September 2017, we conducted a cross-sectional study in Kikwit, DRC. Over 2 decades after the EVD outbreak, we recruited EVD survivors and close contacts from the outbreak to undergo physical examination and culturally adapted versions of the Folstein mini-mental status exam (MMSE) and Goldberg anxiety and depression scale (GADS). We estimated the strength of relationships between EVD survivorship and health outcomes using linear regression models by comparing survivors versus close contacts, adjusting for age, sex, educational level, marital status, and healthcare worker status.ResultsWe enrolled 20 EVD survivors and 187 close contacts. Among the 20 EVD survivors, 4 (20%) reported at least 1 abnormal neurological symptom, and 3 (15%) had an abnormal neurological examination. Among the 187 close contacts, 14 (11%) reported at least 1 abnormal neurologic symptom, and 9 (5%) had an abnormal neurological examination. EVD survivors had lower mean MMSE and higher mean GADS scores as compared to close contacts (MMSE: adjusted coefficient: -1.85; 95% confidence interval [CI]: -3.63, -0.07; GADS: adjusted coefficient: 3.91; 95% CI: 1.76, 6.04).ConclusionsEVD survivors can have lower cognitive scores and more symptoms of depression and anxiety than close contacts more than 2 decades after Ebola virus outbreaks

Projections of Ebola outbreak size and duration with and without vaccine use in Équateur, Democratic Republic of Congo, as of May 27, 2018.

As of May 27, 2018, 6 suspected, 13 probable and 35 confirmed cases of Ebola virus disease (EVD) had been reported in Équateur Province, Democratic Republic of Congo. We used reported case counts and time series from prior outbreaks to estimate the total outbreak size and duration with and without vaccine use. We modeled Ebola virus transmission using a stochastic branching process model that included reproduction numbers from past Ebola outbreaks and a particle filtering method to generate a probabilistic projection of the outbreak size and duration conditioned on its reported trajectory to date; modeled using high (62%), low (44%), and zero (0%) estimates of vaccination coverage (after deployment). Additionally, we used the time series for 18 prior Ebola outbreaks from 1976 to 2016 to parameterize the Thiel-Sen regression model predicting the outbreak size from the number of observed cases from April 4 to May 27. We used these techniques on probable and confirmed case counts with and without inclusion of suspected cases. Probabilistic projections were scored against the actual outbreak size of 54 EVD cases, using a log-likelihood score. With the stochastic model, using high, low, and zero estimates of vaccination coverage, the median outbreak sizes for probable and confirmed cases were 82 cases (95% prediction interval [PI]: 55, 156), 104 cases (95% PI: 58, 271), and 213 cases (95% PI: 64, 1450), respectively. With the Thiel-Sen regression model, the median outbreak size was estimated to be 65.0 probable and confirmed cases (95% PI: 48.8, 119.7). Among our three mathematical models, the stochastic model with suspected cases and high vaccine coverage predicted total outbreak sizes closest to the true outcome. Relatively simple mathematical models updated in real time may inform outbreak response teams with projections of total outbreak size and duration