Outbreak of Ebola virus disease in the Democratic Republic of the Congo, April–May, 2018: an epidemiological study

Barry, Ahmadou; Ahuka‐Mundeke, Steve; Ahmed, Yahaya Ali; Allarangar, Y; Anoko, Julienne Ngoundoung; Archer, Brett N.; Abedi, Aaron Aruna; Bagaria, Jayshree; Belizaire, Marie Roseline Darnycka; Bhatia, Sangeeta; Bokenge, Théophile; Bruni, Emanuele; Cori, Anne; Dabire, Ernest; Diallo, Amadou Mouctar; Diallo, Boubacar; Donnelly, Christl A.; Dorigatti, Ilaria; Dorji, Tshewang; Waeber, Aura Rocio Escobar Corado; Fall, Ibrahima Socé; Ferguson, Neil; FitzJohn, Richard G.; Tengomo, Gervais Leon Folefack; Formenty, Pierre; Forna, Alpha; Fortin, Anne; Garske, Tini; Gaythorpe, Katy A. M.; Gurry, Céline; Hamblion, Esther; Djingarey, Mamoudou Harouna; Haskew, Christopher; Hugonnet, Stéphane; Imai, Natsuko; Impouma, Benido; Kabongo, Guylain; Kalenga, Oly Ilunga; Kibangou, Emerencienne; Lee, Theresa Min-Hyung; Lukoya, Charles Okot; Ly, Ousmane; Makiala-Mandanda, Sheila; Mamba, Augustin; Mbala-Kingebeni, Placide; Mboussou, Franck; Mlanda, Tamayi; Makuma, Vital Mondonge; Morgan, Oliver; Mulumba, Anastasie; Mukadi, Patrick; Mukadi-Bamuleka, Daniel; Muyembe, Jean J.; Bathé, Ndjoloko Tambwe; Ngamala, Patricia Ndumbi; Ngom, Roland; Ngoy, Guillaume; Nouvellet, Pierre; Nsio, Justus; Ousman, Kevin; Peron, Emilie; Polonsky, Jonathan; Ryan, Michael J.; Touré, Alhassane; Towner, Rodney; Tshapenda, Gaston; Weerdt, R Van de; Kerkhove, Maria Van; Wendland, Annika; Yao, N’da Konan Michel; Yoti, Zabulon; Yuma, Etienne; Kabamba, Guy Kalambayi; Mwati, Jean de Dieu Lukwesa; Mbuy, Gisele; Lubula, Leopold; Mutombo, Anny; Mavila, Oscar; Lay, Yyonne; Kitenge, Emma

doi:10.1016/s0140-6736(18)31387-4

Cited by 101 publications

(60 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Uptake of traditional control measures such as contact tracing and safe burials has varied with the community, even with the rapid deployment and widespread availability of experimental vaccines and therapeutics [3]. Our understanding of the impact of scientific advances on EVD transmission has been evolving; there has been an underlying, untested assumption that vaccination may reduce epidemic transmission [5]. Mathematical modeling of simulated EVD epidemics suggested that vaccination coverage as low as 40% in the general population and 95% in healthcare workers (HCWs) may avert another epidemic similar to size of the West African one [6].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

View full text Add to dashboard Cite

Background As 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. Methods For 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. Results During 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. Conclusions Our 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 c...

show abstract

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Integration of modeling with the public health response to epidemics of bovine spongiform encephalopathy and foot-and-mouth disease in the United Kingdom and the severe acute respiratory syndrome epidemic (68-73) has led to expectations for near real-time modeling studies during major outbreaks. In recent experience, models of the spread of pandemic influenza A H1N1 (74), cholera (75), Middle East respiratory syndrome (76), EBOV (77,78), Chikungunya virus (79), Zika virus (80,81), yellow fever (82), and plague (83) have all been published within weeks of the respective outbreak notifications.…”

Section: Model-data Integration For Emerging Diseasesmentioning

confidence: 99%

Emerging Challenges and Opportunities in Infectious Disease Epidemiology

Lewnard

Reingold

2019

American Journal of Epidemiology

View full text Add to dashboard Cite

Much of the intellectual tradition of modern epidemiology stems from efforts to understand and combat chronic diseases persisting through the 20th century epidemiologic transition of countries such as the United States and United Kingdom. After decades of relative obscurity, infectious disease epidemiology has undergone an intellectual rebirth in recent years amid increasing recognition of the threat posed by both new and familiar pathogens. Here, we review the emerging coalescence of infectious disease epidemiology around a core set of study designs and statistical methods bearing little resemblance to the chronic disease epidemiology toolkit. We offer our outlook on challenges and opportunities facing the field, including the integration of novel molecular and digital information sources into disease surveillance, the assimilation of such data into models of pathogen spread, and the increasing contribution of models to public health practice. We next consider emerging paradigms in causal inference for infectious diseases, ranging from approaches to evaluating vaccines and antimicrobial therapies to the task of ascribing clinical syndromes to etiologic microorganisms, an age-old problem transformed by our increasing ability to characterize human-associated microbiota. These areas represent an increasingly important component of epidemiology training programs for future generations of researchers and practitioners.

show abstract

“…For the three outbreaks, cases were alerted to the MOH of DRC by the referral health centre upon showing symptoms of acute haemorrhagic fever. The common symptoms for most of the early cases were high fever and intense fatigue [15,16,17]. No detailed description was given for any haemorrhagic symptom that accompanies fever (e.g.…”

Section: Clinical Featuresmentioning

confidence: 99%

“…The median age was 40 years (range 8-80) and 40% were females. 71% of confirmed cases had contact with infected patients, and 58% of confirmed cases attended funerals before the onset of disease [16].…”

Section: Demographics Of Casesmentioning

confidence: 99%

Ebola Outbreaks in the Democratic Republic of Congo (DRC), 2017-2019

Nguyen¹

2019

Global Biosecurity

View full text Add to dashboard Cite

Feedback from operational stakeholders who manage or respond to outbreaks is that they are often too busy to review literature or obtain relevant background information to assist them with acute response. Unlike a traditional analytical outbreak investigation report, Watching Briefs are intended as a rapid resource for public health or other first responders in the field on topical, serious or current outbreaks, and provide a digest of relevant information including key features of an outbreak, comparison with past outbreaks and a literature review. They can be completed by responders to an outbreak, or by anyone interested in or following an outbreak using public or open source data, including news reports.

show abstract

Outbreak of Ebola virus disease in the Democratic Republic of the Congo, April–May, 2018: an epidemiological study

Abstract: None.

Cited by 101 publications

References 17 publications

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

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

Emerging Challenges and Opportunities in Infectious Disease Epidemiology

Ebola Outbreaks in the Democratic Republic of Congo (DRC), 2017-2019

Contact Info

Product

Resources

About