scholarly journals Multi-model forecasts of the ongoing Ebola epidemic in the Democratic Republic of Congo, March – October 2019

2020 ◽  
Author(s):  
Kimberlyn Roosa ◽  
Amna Tariq ◽  
Ping Yan ◽  
James M. Hyman ◽  
Gerardo Chowell
Keyword(s):  
Real Time ◽  
Dynamic Models ◽  
Democratic Republic ◽  
Democratic Republic Of Congo ◽  
Epidemiological Data ◽  
World Health ◽  
Logistic Growth ◽  
Richards Model ◽  
Wide Range ◽  
Model Approach

AbstractThe 2018-20 Ebola outbreak in the Democratic Republic of the Congo is the first to occur in an armed conflict zone. The resulting impact on population movement, treatment centers, and surveillance has created an unprecedented challenge for real-time epidemic forecasting. Most standard mathematical models cannot capture the observed incidence trajectory when it deviates from a traditional epidemic logistic curve. We fit seven dynamic models of increasing complexity to the incidence data published in the World Health Organization Situation Reports, after adjusting for reporting delays. These models include a simple logistic model, a Richards model, an endemic Richards model, a double logistic growth model, a multi-model approach, and two sub-epidemic models. We analyze model fit to the data and compare real-time forecasts throughout the ongoing epidemic across 29 weeks from March 11 to September 23, 2019. We observe that the modest extensions presented allow for capturing a wide range of epidemic behavior. The multi-model approach yields the most reliable forecasts on average for this application, and the presented extensions improve model flexibility and forecasting accuracy, even in the context of limited epidemiological data.

scholarly journals Multi-model forecasts of the ongoing Ebola epidemic in the Democratic Republic of Congo, March–October 2019

2020 ◽  
Vol 17 (169) ◽  
pp. 20200447
Author(s):  
Kimberlyn Roosa ◽  
Amna Tariq ◽  
Ping Yan ◽  
James M. Hyman ◽  
Gerardo Chowell
Keyword(s):  
Real Time ◽  
Dynamic Models ◽  
Democratic Republic ◽  
Democratic Republic Of Congo ◽  
Epidemiological Data ◽  
World Health ◽  
Logistic Growth ◽  
Richards Model ◽  
Wide Range ◽  
Model Approach

The 2018–2020 Ebola outbreak in the Democratic Republic of the Congo is the first to occur in an armed conflict zone. The resulting impact on population movement, treatment centres and surveillance has created an unprecedented challenge for real-time epidemic forecasting. Most standard mathematical models cannot capture the observed incidence trajectory when it deviates from a traditional epidemic logistic curve. We fit seven dynamic models of increasing complexity to the incidence data published in the World Health Organization Situation Reports, after adjusting for reporting delays. These models include a simple logistic model, a Richards model, an endemic Richards model, a double logistic growth model, a multi-model approach and two sub-epidemic models. We analyse model fit to the data and compare real-time forecasts throughout the ongoing epidemic across 29 weeks from 11 March to 23 September 2019. We observe that the modest extensions presented allow for capturing a wide range of epidemic behaviour. The multi-model approach yields the most reliable forecasts on average for this application, and the presented extensions improve model flexibility and forecasting accuracy, even in the context of limited epidemiological data.

scholarly journals Minimum acceptable diet among children aged 6–23 months in South Kivu, Democratic Republic of Congo: a community-based cross-sectional study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Richard Mbusa Kambale ◽  
Gaylord Amani Ngaboyeka ◽  
Joe Bwija Kasengi ◽  
Sarah Niyitegeka ◽  
Boss Rutakaza Cinkenye ◽  
...  
Keyword(s):  
Democratic Republic ◽  
Democratic Republic Of Congo ◽  
Feeding Practices ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Community Based ◽  
Cross Sectional ◽  
Republic Of Congo ◽  
Wide Range ◽  
South Kivu

Abstract Background Suboptimal child nutrition remains the main factor underlying child undernutrition in Democratic Republic of Congo (DRC). This study aimed to assess the prevalence of minimum acceptable diet and associated factors among children aged 6–23 months old. Methods Community-based cross-sectional study including 742 mothers with children aged 6–23 months old was conducted in 2 Health Zones of South Kivu, Eastern DRC. WHO indicators of Infant and Young Child Feeding (IYCF) regarding complementary feeding practices were used. Logistic regression analysis was used to quantify the association between sociodemographic indicators and adequate minimum acceptable diet for both univariate and multivariate analysis. Results Overall, 33% of infants had minimum acceptable diet. After controlling for a wide range of covariates, residence urban area (AOR 2.39; 95% CI 1.43, 3.85), attendance postnatal care (AOR 1.68; 95% CI 1.12, 2.97), education status of mother (AOR 1.83; 95% CI 1.20, 2.77) and household socioeconomic status (AOR 1.72; 95% CI 1.14, 2.59) were factors positively associated with minimum acceptable diet. Conclusion Actions targeting these factors are expected to improve infant feeding practices in South Kivu.

scholarly journals Predicting the Epidemiological Outbreak of the Coronavirus Disease 2019 (COVID-19) in Saudi Arabia

2020 ◽  
Vol 17 (12) ◽  
pp. 4568 ◽  
Author(s):  
Dabiah Alboaneen ◽  
Bernardi Pranggono ◽  
Dhahi Alshammari ◽  
Nourah Alqahtani ◽  
Raja Alyaffer
Keyword(s):  
Saudi Arabia ◽  
Real Time ◽  
World Health ◽  
Logistic Growth ◽  
Final Phase ◽  
Time Data ◽  
Local Prediction ◽  
The World ◽  
Real Time Data ◽  
Health Organization

The coronavirus diseases 2019 (COVID-19) outbreak continues to spread rapidly across the world and has been declared as pandemic by World Health Organization (WHO). Saudi Arabia was among the countries that was affected by the deadly and contagious virus. Using a real-time data from 2 March 2020 to 15 May 2020 collected from Saudi Ministry of Health, we aimed to give a local prediction of the epidemic in Saudi Arabia. We used two models: the Logistic Growth and the Susceptible-Infected-Recovered for real-time forecasting the confirmed cases of COVID-19 across Saudi Arabia. Our models predicted that the epidemics of COVID-19 will have total cases of 69,000 to 79,000 cases. The simulations also predicted that the outbreak will entering the final-phase by end of June 2020.

scholarly journals Quantifying epidemiological drivers of gambiense human African Trypanosomiasis across the Democratic Republic of Congo

2020 ◽  
Author(s):  
Ronald E Crump ◽  
Ching-I Huang ◽  
Ed Knock ◽  
Simon E F Spencer ◽  
Paul Brown ◽  
...  
Keyword(s):  
Human African Trypanosomiasis ◽  
Democratic Republic ◽  
Democratic Republic Of Congo ◽  
Model Fitting ◽  
Case Finding ◽  
World Health ◽  
Model Parameters ◽  
African Trypanosomiasis ◽  
Republic Of Congo ◽  
Case Data

AbstractGambiense human African trypanosomiasis (gHAT) is a virulent disease declining in burden but still endemic in West and Central Africa. Although it is targeted for elimination of transmission by 2030, there remain numerous questions about the drivers of infection and how these vary geographically.In this study we focus on the Democratic Republic of Congo (DRC), which accounted for 84% of the global case burden in 2016, to explore changes in transmission across the country and elucidate factors which may have contributed to the persistence of disease or success of interventions in different regions. We present a Bayesian fitting methodology, applied to 168 endemic health zones (∼ 100,000 population size), which allows for calibration of mechanistic gHAT model to case data (from the World Health Organization HAT Atlas) in an adaptive and automated framework.It was found that the model needed to capture improvements in passive detection to match observed trends in the data within former Bandundu and Bas Congo provinces indicating these regions have substantially reduced time to detection. Health zones in these provinces generally had longer burn-in periods during fitting due to additional model parameters.Posterior probability distributions were found for a range of fitted parameters in each health zone; these included the basic reproduction number estimates for pre-1998 (R0) which was inferred to be between 1 and 1.19, in line with previous gHAT estimates, with higher median values typically in health zones with more case reporting in the 2000s.Previously, it was not clear whether a fall in active case finding in the period contributed to the declining case numbers. The modelling here accounts for variable screening and suggests that underlying transmission has also reduced greatly – on average 96% in former Equateur, 93% in former Bas Congo and 89% in former Bandundu – Equateur and Bandundu having had the highest case burdens in 2000. This analysis also sets out a framework to enable future predictions for the country.Author summaryGambiense human African trypanosomiasis (gHAT; sleeping sickness) is a deadly disease targeted for elimination by 2030, however there are still several unknowns about what factors influence continued transmission and how this changes with geographic location.In this study we focus on the Democratic Republic of Congo (DRC), which reported 84% of the global cases in 2016 to try and explain why some regions of the country have had more success than others in bringing down case burden. To achieve this we used a state-of-the-art statistical framework to match a mathematical gHAT model to reported case data for 168 regions with some case reporting during 2000–2016.The analysis indicates that two former provinces, Bandundu and Bas Congo had substantial improvements to case detection in fixed health facilities in the time period. Overall, all provinces were estimated to have reductions in (unobservable) transmission including ∼ 96% in former Equateur. This is reassuring as case finding effort has decreased in that region.The model fitting presented here will allow predictions of gHAT under future strategies to be performed in the future.

scholarly journals Melioidosis and sickle cell disease: Description of a rare association

2020 ◽  
Vol 3 (1) ◽  
pp. 57-62
Author(s):  
Mick Ya-Pongombo Shongo ◽  
◽  
Mimi Mujing Yav ◽  
Olivier Mukuku ◽  
Gaston Kankolongo ◽  
...  
Keyword(s):  
Sickle Cell Disease ◽  
Sickle Cell ◽  
Democratic Republic ◽  
Democratic Republic Of Congo ◽  
Central Africa ◽  
Cell Disease ◽  
Clinical Form ◽  
Rare Association ◽  
Wide Range ◽  
Clinical Cases

Melioidosis and its germ are increasingly reported on the African continent and particularly in Central Africa, probably due to the increased awareness of clinicians and microbiologists and the growing recognition of the organism. It is called "Great Mimicker" because it produces a wide range of clinical characteristics such as would be found in patients living with sickle cell disease (SCD) in particular. However, to date, no publication presents this association between melioidosis and SCD. The authors describe here 3 clinical cases presenting this very rare association between melioidosis and SCD. These are 3 children with SCD (homozygous SS) residing in Lubumbashi in Haut-Katanga province in the Democratic Republic of Congo. One patient presented with sepsis as a clinical form of the disease. All 3 had presented a pulmonary form. Only one patient was treated specifically after the diagnosis of melioidosis; for the other two, this diagnosis was confirmed after their death. Thus the death rate is 66.67%. This article describes, through these 3 clinical cases, a very rare first association between melioidosis and SCD. This association requires research to establish whether, like Thalassemia, SCD can be considered a risk factor for melioidosis. A screening of cases of melioidosis in the general population should allow us to focus on this.

scholarly journals Neonatal COVID-19: a clinical case report from the Democratic Republic of Congo (DRC)

2020 ◽  
Author(s):  
Serge ZIGABE ◽  
Etienne Kajibwami ◽  
Guy-Quesney Mateso ◽  
Benjamin Ntaligeza
Keyword(s):  
Case Report ◽  
World Health Organization ◽  
Clinical Case ◽  
Democratic Republic ◽  
Democratic Republic Of Congo ◽  
World Health ◽  
Wuhan City ◽  
Republic Of Congo ◽  
The World ◽  
Health Organization

Abstract COVID-19 started as a cluster of pneumonia cases in Wuhan City, the Province of Hubei, China, in December 2019. It spread to many regions of China, outside of China and was declared a pandemic by the World Health Organization (WHO) on March 11th, 2020. Initially Africa had no case and now the continent is reporting an increasing number of confirmed cases in an exponential manner (1,2).

scholarly journals Evaluation of the Influenza Sentinel Surveillance System in the Democratic Republic of Congo, 2012-2015

2019 ◽  
Author(s):  
Pélagie Diambalula Babakazo ◽  
Joelle Kabamba-Tshilobo ◽  
Emile Okitolonda Wemakoy ◽  
Léopold Lubula ◽  
Léonie Kitoko Manya ◽  
...  
Keyword(s):  
Data Quality ◽  
Surveillance System ◽  
Democratic Republic ◽  
Democratic Republic Of Congo ◽  
Sentinel Surveillance ◽  
World Health ◽  
Influenza Surveillance ◽  
Surveillance Systems ◽  
Republic Of Congo ◽  
Sentinel Surveillance System

Abstract Background The World Health Organization recommends periodic evaluations of influenza surveillance systems to identify areas for improvement and provide evidence of data reliability for policymaking. However, data about the performance of established influenza surveillance systems are limited in Africa, including in the Democratic Republic of Congo (DRC). Methods We used the Centers for Disease Control and Prevention guidelines to evaluate the performance of the influenza sentinel surveillance system (ISSS) in DRC during 2012-2015. The performance of the system was evaluated using eight surveillance attributes: (i) data quality and completeness for key variables, (ii) timeliness, (iii) representativeness, (iv) flexibility, (v) simplicity, (vi) acceptability, (vii) stability and (viii) utility. For each attribute, specific indicators were developed and described using quantitative and qualitative methods. Scores for each indicator were as follows: <60% weak performance; 60-79% moderate performance; ≥80% good performance. Results During 2012-2015, we enrolled and tested 4,339 patients with influenza-like illness (ILI) and 2,869 patients with severe acute respiratory illness (SARI) from 11 sentinel sites situated in 5 of 11 provinces. Influenza viruses were detected in 446 (10.3%) samples from patients with ILI and in 151 (5.5%) samples from patients with SARI with higher detection during December-May. Data quality and completeness was >90% for all evaluated indicators. Other strengths of the system were timeliness, representativeness, simplicity, stability and utility that scored >70% each. Flexibility and acceptability had moderate to week performance. It was reported that the ISSS contributed to: (i) a better understanding of the epidemiology, circulating patterns and proportional contribution of influenza virus among patients with ILI or SARI; (ii) acquisition of new key competences related to influenza surveillance and diagnosis; and (iii) continuous education of surveillance staff and clinicians at sentinel sites about influenza. However, due to limited resources no actions were undertaken to mitigate the impact of seasonal influenza epidemics. Conclusions The system performed overall satisfactorily and provided reliable and timely data about influenza circulation in DRC. The simplicity of the system contributed to its stability. A better use of the available data could be made to inform and promote prevention interventions especially among the most vulnerable groups.

scholarly journals Integrating sexual and reproductive health into health system strengthening in humanitarian settings: a planning workshop toolkit to transition from minimum to comprehensive services in the Democratic Republic of Congo, Bangladesh, and Yemen

2020 ◽  
Author(s):  
Nguyen Toan Tran ◽  
Alison Greer ◽  
Brigitte Kini ◽  
Hassan Abdi ◽  
Kariman Rajeh ◽  
...  
Keyword(s):  
Reproductive Health ◽  
Health System ◽  
Sexual And Reproductive Health ◽  
Democratic Republic ◽  
Democratic Republic Of Congo ◽  
Health System Strengthening ◽  
World Health ◽  
Second Phase ◽  
Republic Of Congo ◽  
Humanitarian Settings

Abstract BackgroundPlanning to transition from the Minimum Initial Service Package for Sexual and Reproductive Health (SRH) toward comprehensive SRH services has been a challenge in humanitarian settings. To bridge this gap, a workshop toolkit for SRH coordinators was designed to support effective planning. This article aims to describe the toolkit design, piloting, and final product.MethodsAnchored in the Health System Building Blocks Framework of the World Health Organization, the design entailed two complementary and participatory strategies. First, a collaborative design phase with iterative feedback loops involved global partners with extensive operational experience in the initial toolkit conception. The second phase engaged stakeholders from three major humanitarian crises to participate in pilot workshops to contextualize, evaluate, validate, and improve the toolkit using qualitative interviews and end-of-workshop evaluations. The aim of this two-phase design process was to finalize a planning toolkit that can be utilized in and adapted to diverse humanitarian contexts, and efficiently and effectively meet its objectives. Pilots occurred in the Democratic Republic of Congo for the Kasai region crisis, Bangladesh for the Rohingya humanitarian response in Cox’s Bazar, and Yemen for selected Governorates.ResultsResults suggest that the toolkit enabled facilitators to foster a systematic, participatory, interactive, and inclusive planning process among participants over a two-day workshop. The approach was reportedly effective and time-efficient in producing a joint work plan. The main planning priorities cutting across settings included improving comprehensive SRH services in general, healthcare workforce strengthening, such as midwifery capacity development, increasing community mobilization and engagement, focusing on adolescent SRH, and enhancing maternal and newborn health services in terms of quality, coverage, and referral pathways. Recommendations for improvement included a dedicated and adequately anticipated pre-workshop preparation to gather relevant data, encouraging participants to undertake preliminary study to equalize knowledge to partake fully in the workshop, and enlisting participants from marginalized and underserved populations.ConclusionCollaborative design and piloting efforts resulted in a workshop toolkit that could support a systematic and efficient identification of priority activities and services related to comprehensive SRH. Such priorities could help meet the SRH needs of communities emerging from acute humanitarian situations while strengthening the overall health system.

scholarly journals Integrating sexual and reproductive health into health system strengthening in humanitarian settings: a planning workshop toolkit to transition from minimum to comprehensive services in the Democratic Republic of Congo, Bangladesh, and Yemen

2020 ◽  
Vol 14 (1) ◽  
Author(s):  
Nguyen Toan Tran ◽  
Alison Greer ◽  
Brigitte Kini ◽  
Hassan Abdi ◽  
Kariman Rajeh ◽  
...  
Keyword(s):  
Reproductive Health ◽  
Health System ◽  
Collaborative Design ◽  
Sexual And Reproductive Health ◽  
Democratic Republic ◽  
Democratic Republic Of Congo ◽  
Health System Strengthening ◽  
World Health ◽  
Republic Of Congo ◽  
Humanitarian Settings

Abstract Background Planning to transition from the Minimum Initial Service Package for Sexual and Reproductive Health (SRH) toward comprehensive SRH services has been a challenge in humanitarian settings. To bridge this gap, a workshop toolkit for SRH coordinators was designed to support effective planning. This article aims to describe the toolkit design, piloting, and final product. Methods Anchored in the Health System Building Blocks Framework of the World Health Organization, the design entailed two complementary and participatory strategies. First, a collaborative design phase with iterative feedback loops involved global partners with extensive operational experience in the initial toolkit conception. The second phase engaged stakeholders from three major humanitarian crises to participate in pilot workshops to contextualize, evaluate, validate, and improve the toolkit using qualitative interviews and end-of-workshop evaluations. The aim of this two-phase design process was to finalize a planning toolkit that can be utilized in and adapted to diverse humanitarian contexts, and efficiently and effectively meet its objectives. Pilots occurred in the Democratic Republic of Congo for the Kasai region crisis, Bangladesh for the Rohingya humanitarian response in Cox’s Bazar, and Yemen for selected Governorates. Results Results suggest that the toolkit enabled facilitators to foster a systematic, participatory, interactive, and inclusive planning process among participants over a two-day workshop. The approach was reportedly effective and time-efficient in producing a joint work plan. The main planning priorities cutting across settings included improving comprehensive SRH services in general, healthcare workforce strengthening, such as midwifery capacity development, increasing community mobilization and engagement, focusing on adolescent SRH, and enhancing maternal and newborn health services in terms of quality, coverage, and referral pathways. Recommendations for improvement included a dedicated and adequately anticipated pre-workshop preparation to gather relevant data, encouraging participants to undertake preliminary study to equalize knowledge to partake fully in the workshop, and enlisting participants from marginalized and underserved populations. Conclusion Collaborative design and piloting efforts resulted in a workshop toolkit that could support a systematic and efficient identification of priority activities and services related to comprehensive SRH. Such priorities could help meet the SRH needs of communities emerging from acute humanitarian situations while strengthening the overall health system.

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