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Real-time predictions of the 2018-2019 Ebola virus disease outbreak in the Democratic Republic of the Congo using Hawkes point process models.

ABSTRACT: As of June 16, 2019, an Ebola virus disease (EVD) outbreak has led to 2136 reported cases in the northeastern region of the Democratic Republic of the Congo (DRC). As this outbreak continues to threaten the lives and livelihoods of people already suffering from civil strife and armed conflict, relatively simple mathematical models and their short-term predictions have the potential to inform Ebola response efforts in real time. We applied recently developed non-parametrically estimated Hawkes point processes to model the expected cumulative case count using daily case counts from May 3, 2018, to June 16, 2019, initially reported by the Ministry of Health of DRC and later confirmed in World Health Organization situation reports. We generated probabilistic estimates of the ongoing EVD outbreak in DRC extending both before and after June 16, 2019, and evaluated their accuracy by comparing forecasted vs. actual outbreak sizes, out-of-sample log-likelihood scores and the error per day in the median forecast. The median estimated outbreak sizes for the prospective thee-, six-, and nine-week projections made using data up to June 16, 2019, were, respectively, 2317 (95% PI: 2222, 2464); 2440 (95% PI: 2250, 2790); and 2544 (95% PI: 2273, 3205). The nine-week projection experienced some degradation with a daily error in the median forecast of 6.73 cases, while the six- and three-week projections were more reliable, with corresponding errors of 4.96 and 4.85 cases per day, respectively. Our findings suggest the Hawkes point process may serve as an easily-applied statistical model to predict EVD outbreak trajectories in near real-time to better inform decision-making and resource allocation during Ebola response efforts.

SUBMITTER: Kelly JD

PROVIDER: S-EPMC7358183 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Real-time predictions of the 2018-2019 Ebola virus disease outbreak in the Democratic Republic of the Congo using Hawkes point process models.

Kelly J Daniel JD Park Junhyung J Harrigan Ryan J RJ Hoff Nicole A NA Lee Sarita D SD Wannier Rae R Selo Bernice B Mossoko Mathias M Njoloko Bathe B Okitolonda-Wemakoy Emile E Mbala-Kingebeni Placide P Rutherford George W GW Smith Thomas B TB Ahuka-Mundeke Steve S Muyembe-Tamfum Jean Jacques JJ Rimoin Anne W AW Schoenberg Frederic Paik FP

Epidemics 20190723

As of June 16, 2019, an Ebola virus disease (EVD) outbreak has led to 2136 reported cases in the northeastern region of the Democratic Republic of the Congo (DRC). As this outbreak continues to threaten the lives and livelihoods of people already suffering from civil strife and armed conflict, relatively simple mathematical models and their short-term predictions have the potential to inform Ebola response efforts in real time. We applied recently developed non-parametrically estimated Hawkes po ...[more]

PMID: 31395373

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Project description:BackgroundThe 2018-2019 Ebola virus disease (EVD) outbreak in North Kivu and Ituri provinces in the Democratic Republic of the Congo (DRC) is the largest ever recorded in the DRC. It has been declared a Public Health Emergency of International Concern. The outbreak emerged in a region of chronic conflict and insecurity, and directed attacks against health care workers may have interfered with disease response activities. Our study characterizes and quantifies the broader conflict dynamics over the course of the outbreak by pairing epidemiological and all available spatial conflict data.MethodsWe build a set of conflict variables by mapping the spatial locations of all conflict events and their associated deaths in each of the affected health zones in North Kivu and Ituri, eastern DRC, before and during the outbreak. Using these data, we compare patterns of conflict before and during the outbreak in affected health zones and those not affected. We then test whether conflict is correlated with increased EVD transmission at the health zone level.FindingsThe incidence of conflict events per capita is ~ 600 times more likely in Ituri and North Kivu than for the rest of the DRC. We identified 15 time periods of substantial uninterrupted transmission across 11 health zones and a total of 120 bi-weeks. We do not find significant short-term associations between the bi-week reproduction numbers and the number of conflicts. However, we do find that the incidence of conflict per capita was correlated with the incidence of EVD per capita at the health zone level for the entire outbreak (Pearson's r = 0.33, 95% CI 0.05-0.57). In the two provinces, the monthly number of conflict events also increased by a factor of 2.7 in Ebola-affected health zones (p value < 0.05) compared to 2.0 where no transmission was reported and 1.3 in the rest of the DRC, in the period between February 2019 and July 2019.ConclusionWe characterized the association between variables documenting broad conflict levels and EVD transmission. Such assessment is important to understand if and how such conflict variables could be used to inform the outbreak response. We found that while these variables can help characterize long-term challenges and susceptibilities of the different regions they provide little insight on the short-term dynamics of EVD transmission.

Project description:ImportanceIn 2018 to 2020, the Democratic Republic of the Congo experienced the world's second largest Ebola virus disease (EVD) outbreak, killing 2290 individuals; women were disproportionately infected (57% of all cases) despite no evidence of differential biological EVD risk. Understanding how gender norms may influence exposure to EVD, intensity, and prognosis as well as personal protective behaviors against the virus is important to disease risk reduction and control interventions.ObjectiveTo assess whether men and women differ in personal protective behaviors (vaccine acceptance, health-seeking behaviors, physical distancing) and the mediating role of EVD information and knowledge, perceived disease risk, and social relations.Design, setting, and participantsThis cross-sectional, multistage cluster survey study of 1395 randomly selected adults was conducted in the Ebola-affected regions of North Kivu from April 20, 2019, to May 10, 2019. Path analyses were conducted using structural equation modeling to examine associations among study variables. Statistical analysis was conducted from August 2019 to May 2020.Main outcomes and measuresThe main behavioral outcomes of interest were (1) vaccine acceptance, (2) formal health care seeking, and (3) self-protective behaviors. The primary factor of interest was self-reported gender identity. We also assessed sociodemographic factors.ResultsAmong the study's 1395 participants, 1286 (93%) had Nande ethnicity and 698 (50%) were women; the mean (SD) age was 34.5 (13.1) years. Compared with female participants, male participants reported significantly higher levels of education, wealth, and mobile phone access. There were associations found between gender and all EVD preventive behavioral outcomes, with evidence for mediation through EVD knowledge and belief in rumors. Men reported greater EVD knowledge accuracy compared with women (mean [SE] score for men: 12.06 [0.13] vs women: 11.08 [0.16]; P < .001), and greater knowledge accuracy was associated with increases in vaccine acceptance (β = 0.37; P < .001), formal care seeking (β = 0.39; P < .001), and self-protective behaviors (β = 0.35; P < .001). Lower belief in rumors was associated with greater vaccine acceptance (β = -0.30; P < .001), and greater EVD information awareness was associated with increased adoption of self-protective behaviors (β = 0.23; P < .001).Conclusions and relevanceThis survey study found gender differences in adopting preventive protective behaviors against EVD. These findings suggest that it is critical to design gender-sensitive communication and vaccination strategies, while engaging women and their community as a whole in any response to infectious disease outbreaks. Research on the potential link between gender and sociodemographics factors associated with disease risk and outcomes is needed.

Project description:BackgroundThe second largest Ebola virus disease (EVD) outbreak began in the Democratic Republic of Congo in July 2018 in North Kivu Province. Data suggest the outbreak is not epidemiologically linked to the 2018 outbreak in Equateur Province, and that independent introduction of Ebola virus (EBOV) into humans occurred. We tested for antibodies to ebolaviruses in febrile patients seeking care in North Kivu Province prior to the EVD outbreak.MethodsPatients were enrolled between May 2017 and April 2018, before the declared start of the outbreak in eastern DRC. Questionnaires were administered to collect demographic and behavioural information to identify risk factors for exposure. Biological samples were evaluated for ebolavirus nucleic acid, and for antibodies to ebolaviruses. Prevalence of exposure was calculated, and demographic factors evaluated for associations with ebolavirus serostatus.ResultsSamples were collected and tested from 272 people seeking care in the Rutshuru Health Zone in North Kivu Province. All patients were negative for filoviruses by PCR. Intial screening by indirect ELISA found that 30 people were reactive to EBOV-rGP. Results were supported by detection of ebolavirus reactive linear peptides using the Serochip platform. Differential screening of all reactive serum samples against the rGP of all six ebolaviruses and Marburg virus (MARV) showed that 29 people exhibited the strongest reactivity to EBOV and one to Bombali virus (BOMV), and western blotting confirmed results. Titers ranged from 1:100 to 1:12,800. Although both sexes and all ages tested positive for antibodies, women were significantly more likely to be positive and the majority of positives were in February 2018.ConclusionsWe provide the first documented evidence of exposure to Ebola virus in people in eastern DRC. We detected antibodies to EBOV in 10% of febrile patients seeking healthcare prior to the declaration of the 2018-2020 outbreak, suggesting early cases may have been missed or exposure ocurred without associated illness. We also report the first known detection of antibodies to BOMV, previously detected in bats in West and East Africa, and show that human exposure to BOMV has occurred. Our data suggest human exposure to ebolaviruses may be more frequent and geographically widespread.

Project description:BackgroundAn Ebola Virus Disease (EVD) outbreak occurred in North Kivu between 2018 and 2020. This eastern province of the Democratic Republic of Congo was also grappling with insecurity caused by several armed groups. This study aimed to explore the barriers and facilitators to utilizing Healthcare Facilities (HCFs) by non-Ebola patients during the crisis.MethodsA qualitative case study was conducted in Beni and Butembo with 24 relatives of 15 deceased non-EVD patients, 47 key informants from healthcare workers (HCWs), as well as community leaders. Semi-structured interviews were conducted to explore three key areas: (i) the participants' illness history, care pathway, care, and social support; (ii) their perceptions of how EVD affected the care outcome; and (iii) their opinions on the preparedness, supply, use, and quality of healthcare before and during the outbreak. All interviews were recorded, transcribed verbatim, and thematically analysed using Atlas-ti 8.0.ResultsNine of the 15 deaths were female and their ages ranged from 7 to 79 years. The causes of death were non-communicable (13) or infectious (2) diseases. Conspiracy theories, failure to establish security, and the concept of the ''Ebola business'' were associated with misinformation and lower levels of trust in government and HCFs. The negative perceptions, fear of being identified as an Ebola case, apprehension about the triage unit, and inadequacy of personal protective equipment resulted in a preference for private or informal HCFs. For half of the deceased's relatives, the Ebola outbreak hastened their death. Conversely, community involvement, employing familiar, neutral, and credible HCWs, and implementing a free care policy increased the number of visits. These results were observable despite a lack of funds, overstretched HCWs, and long waiting time.ConclusionsOur findings can inform policies before and during future outbreaks to enhance the resilience of routine HCFs by maintaining dialogue between HCWs and patients, and rebuilding confidence in HCFs. Quantitative studies including context analysis are essential to identify the determinants of care-seeking during such a crisis.

Dataset Information

Real-time predictions of the 2018-2019 Ebola virus disease outbreak in the Democratic Republic of the Congo using Hawkes point process models.

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Real-time predictions of the 2018-2019 Ebola virus disease outbreak in the Democratic Republic of the Congo using Hawkes point process models.

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