Insights into the Early Epidemic Spread of Ebola in Sierra Leone Provided by Viral Sequence Data

·

Background and Methodology:
The current Ebola virus epidemic in West Africa has been spreading at least since December 2013. The first confirmed case of Ebola virus in Sierra Leone was identified on May 25. Based on viral genetic sequencing data from 72 individuals in Sierra Leone collected between the end of May and mid June, we utilize a range of phylodynamic methods to estimate the basic reproductive number (R0). We additionally estimate the expected lengths of the incubation and infectious periods of the virus. Finally, we use phylogenetic trees to examine the role played by population structure in the epidemic.

Results:
The median estimates of R0 based on sequencing data alone range between 1.65-2.18, with the most plausible model yielding a median R0 of 2.18 (95% HPD 1.24-3.55). Importantly, our results indicate that, at least until mid June, relief efforts in Sierra Leone were ineffective at lowering the effective reproductive number of the virus. We estimate the expected length of the infectious period to be 2.58 days (median; 95% HPD 1.24-6.98). The dataset appears to be too small in order to estimate the incubation period with high certainty (median expected incubation period 4.92 days; 95% HPD 2.11-23.20). While our estimates of the duration of infection tend to be smaller than previously reported, phylodynamic analyses support a previous estimate that 70% of cases were observed and included in the present dataset. The dataset is too small to show a particular population structure with high significance, however our preliminary analyses suggest that half the population is spreading the virus with an R0 well above 2, while the other half of the population is spreading with an R0 below 1.

Conclusions:
Overall we show that sequencing data can robustly infer key epidemiological parameters. Such estimates inform public health officials and help to coordinate effective public health efforts. Thus having more sequencing data available for the ongoing Ebola virus epidemic and at the start of new outbreaks will foster a quick understanding of the dynamics of the pathogen.

Commentary: Containing the Ebola Outbreak – the Potential and Challenge of Mobile Network Data

·

Commentary The ongoing Ebola outbreak is taking place in one of the most highly connected and densely populated regions of Africa (Figure 1A). Accurate information on population movements is valuable for monitoring the progression of the outbreak and predicting its future spread, facilitating the prioritization of interventions and designing surveillance and containment strategies. Vital questions […]

Temporal Variations in the Effective Reproduction Number of the 2014 West Africa Ebola Outbreak

·

Background
The rapidly evolving 2014 Ebola virus disease (EVD) outbreak in West Africa is the largest documented in history, both in terms of the number of people infected and in the geographic spread. The high morbidity and mortality have inspired response strategies to the outbreak at the individual, regional, and national levels. Methods to provide real-time assessment of changing transmission dynamics are critical to the understanding of how these adaptive intervention measures have affected the spread of the outbreak.

Methods
In this analysis, we use the time series of EVD cases in Guinea, Sierra Leone, and Liberia up to September 8, 2014, and employ novel methodology to estimate how the rate of exponential rise of new cases has changed over the outbreak using piecewise fits of exponential curves to the outbreak data.

Results
We find that for Liberia and Guinea, the effective reproduction number rose, rather than fell, around the time that the outbreak spread to densely populated cities, and enforced quarantine was imposed on several regions in the countries; this may indicate that enforced quarantine may not be an effective control measure.

Conclusions
If effective control measures are not put in place, and the current rate of exponential rise of new cases continues, we predict 4400 new Ebola cases in West Africa during the last half of the month of September, with an upper 95% confidence level of 6800 new cases.

Early Epidemic Dynamics of the West African 2014 Ebola Outbreak: Estimates Derived with a Simple Two-Parameter Model

·

The 2014 West African Ebola virus outbreak, now more correctly referred to as an epidemic, is the largest ever to occur. As of August 28, 2014, concerns have been raised that control efforts, particularly in Liberia, have been ineffective, as reported case counts continue to increase. Limited data are available on the epidemiology of the outbreak. However, reported cumulative incidence data as well as death counts are available for Guinea, Sierra Leone, Liberia and Nigeria. We utilized a simple, two parameter mathematical model of epidemic growth and control, to characterize epidemic growth patterns in West Africa, to evaluate the degree to which the epidemic is being controlled, and to assess the potential implications of growth patterns for epidemic size. Models demonstrated good fits to data. Overall basic reproductive number (R0) for the epidemic was estimated to be between 1.6 and 2.0, consistent with prior outbreaks. However, we identified only weak evidence for the occurrence of epidemic control in West Africa as a whole, and essentially no evidence for control in Liberia (though slowing of growth was seen in Guinea and Sierra Leone). It is projected that small reductions in transmission would prevent tens of thousands of future infections. These findings suggest that there is an extraordinary need for improved control measures for the 2014 Ebola epidemic, especially in Liberia, if catastrophe is to be averted.

Assessing the International Spreading Risk Associated with the 2014 West African Ebola Outbreak

·

Background: The 2014 West African Ebola Outbreak is so far the largest and deadliest recorded in history. The affected countries, Sierra Leone, Guinea, Liberia, and Nigeria, have been struggling to contain and to mitigate the outbreak. The ongoing rise in confirmed and suspected cases, 2615 as of 20 August 2014, is considered to increase the risk of international dissemination, especially because the epidemic is now affecting cities with major commercial airports.

Method: We use the Global Epidemic and Mobility Model to generate stochastic, individual based simulations of epidemic spread worldwide, yielding, among other measures, the incidence and seeding events at a daily resolution for 3,362 subpopulations in 220 countries. The mobility model integrates daily airline passenger traffic worldwide and the disease model includes the community, hospital, and burial transmission dynamic. We use a multimodel inference approach calibrated on data from 6 July to the date of 9 August 2014. The estimates obtained were used to generate a 3-month ensemble forecast that provides quantitative estimates of the local transmission of Ebola virus disease in West Africa and the probability of international spread if the containment measures are not successful at curtailing the outbreak.

Results: We model the short-term growth rate of the disease in the affected West African countries and estimate the basic reproductive number to be in the range 1.5 − 2.0 (interval at the 1/10 relative likelihood). We simulated the international spreading of the outbreak and provide the estimate for the probability of Ebola virus disease case importation in countries across the world. Results indicate that the short-term (3 and 6 weeks) probability of international spread outside the African region is small, but not negligible. The extension of the outbreak is more likely occurring in African countries, increasing the risk of international dissemination on a longer time scale.

Estimating the Reproduction Number of Ebola Virus (EBOV) During the 2014 Outbreak in West Africa

·

The 2014 Ebola virus (EBOV) outbreak in West Africa is the largest outbreak of the genus Ebolavirus to date. To better understand the spread of infection in the affected countries, it is crucial to know the number of secondary cases generated by an infected index case in the absence and presence of control measures, i.e., the basic and effective reproduction number. In this study, I describe the EBOV epidemic using an SEIR (susceptible-exposed-infectious-recovered) model and fit the model to the most recent reported data of infected cases and deaths in Guinea, Sierra Leone and Liberia. The maximum likelihood estimates of the basic reproduction number are 1.51 (95% confidence interval [CI]: 1.50-1.52) for Guinea, 2.53 (95% CI: 2.41-2.67) for Sierra Leone and 1.59 (95% CI: 1.57-1.60) for Liberia. The model indicates that in Guinea and Sierra Leone the effective reproduction number might have dropped to around unity by the end of May and July 2014, respectively. In Liberia, however, the model estimates no decline in the effective reproduction number by end-August 2014. This suggests that control efforts in Liberia need to be improved substantially in order to stop the current outbreak.

Clock Rooting Further Demonstrates that Guinea 2014 EBOV is a Member of the Zaïre Lineage

·

While initial phylogenetic analyses concluded to Guinea 2014 EBOV falling outside the Zaïre lineage (ZEBOV), a recent re-analysis of the same dataset by Dudas and Rambaut (2014) suggested that Guinea 2014 EBOV actually is ZEBOV. Under the same hypothesis as used by these authors (the molecular clock hypothesis), we reinforce their conclusion by providing a statistical assessment of the location of the root of the Zaïre lineage. Our analysis unambiguously supports Guinea 2014 EBOV as a member of the Zaïre lineage. In addition, we also show that some uncertainty exists so as to the location of the root of the genus Ebolavirus. We release the software we used for these re-analyses. RootAnnotator allows for the easy determination of branch root posterior probability from any posterior sample of clocked trees and is freely available at http://sourceforge.net/projects/rootannotator/.

Phylogenetic Analysis of Guinea 2014 EBOV Ebolavirus Outbreak

·

Members of the genus Ebolavirus have caused outbreaks of haemorrhagic fever in humans in Africa. The most recent outbreak in Guinea, which began in February of 2014, is still ongoing. Recently published analyses of sequences from this outbreak suggest that the outbreak in Guinea is caused by a divergent lineage of Zaire ebolavirus. We report evidence that points to the same Zaire ebolavirus lineage that has previously caused outbreaks in the Democratic Republic of Congo, the Republic of Congo and Gabon as the culprit behind the outbreak in Guinea.