Amanda Tiffany

Emergence of Zaire Ebola Virus Disease in Guinea

In March 2014, the World Health Organization was notified of an outbreak of a communicable disease characterized by fever, severe diarrhea, vomiting, and a high fatality rate in Guinea. Virologic investigation identified Zaire ebolavirus (EBOV) as the causative agent. Full-length genome sequencing and phylogenetic analysis showed that EBOV from Guinea forms a separate clade in relationship to the known EBOV strains from the Democratic Republic of Congo and Gabon. Epidemiologic investigation linked the laboratory-confirmed cases with the presumed first fatality of the outbreak in December 2013. This study demonstrates the emergence of a new EBOV strain in Guinea.

Temporal Changes in Ebola Transmission in Sierra Leone and Implications for Control Requirements: a Real-time Modelling Study

Background: Between August and November 2014, the incidence of Ebola virus disease (EVD) rose dramatically in several districts of Sierra Leone. As a result, the number of cases exceeded the capacity of Ebola holding and treatment centres. During December, additional beds were introduced, and incidence declined in many areas. We aimed to measure patterns of transmission in different regions, and evaluate whether bed capacity is now sufficient to meet future demand. Methods: We used a mathematical model of EVD infection to estimate how the extent of transmission in the nine worst affected districts of Sierra Leone changed between 10th August 2014 and 18th January 2015. Using the model, we forecast the number of cases that could occur until the end of March 2015, and compared bed requirements with expected future capacity. Results: We found that the reproduction number, R, defined as the average number of secondary cases generated by a typical infectious individual, declined between August and December in all districts. We estimated that R was near the crucial control threshold value of 1 in December. We further estimated that bed capacity has lagged behind demand between August and December for most districts, but as a consequence of the decline in transmission, control measures caught up with the epidemic in early 2015. Conclusions: EVD incidence has exhibited substantial temporal and geographical variation in Sierra Leone, but our results suggest that the epidemic may have now peaked in Sierra Leone, and that current bed capacity appears to be sufficient to keep the epidemic under-control in most districts.

Ebola Virus Disease Complications as Experienced by Survivors in Sierra Leone

The main complications experienced by Ebola virus disease (EVD) survivors in our clinic were arthralgia and uveitis as described earlier. Treatment of EVD complications should be systematic and initiated as soon as possible to prevent severe disabilities such as blindness.

Effect of Artesunate-Amodiaquine on Mortality Related to Ebola Virus Disease.

BACKGROUND Malaria treatment is recommended for patients with suspected Ebola virus disease (EVD) in West Africa, whether systeomatically or based on confirmed malaria diagnosis. At the Ebola treatment center in Foya, Lofa County, Liberia, the supply of artemether-lumefantrine, a first-line antimalarial combination drug, ran out for a 12-day period in August 2014. During this time, patients received the combination drug artesunate-amodiaquine; amodiaquine is a compound with anti-Ebola virus activity in vitro. No other obvious change in the care of patients occurred during this period. METHODS We fit unadjusted and adjusted regression models to standardized patient-level data to estimate the risk ratio for death among patients with confirmed EVD who were prescribed artesunate-amodiaquine (artesunate-amodiaquine group), as compared with those who were prescribed artemether-lumefantrine (artemether-lumefantrine group) and those who were not prescribed any antimalarial drug (no-antimalarial group). RESULTS Between June 5 and October 24, 2014, a total of 382 patients with confirmed EVD were admitted to the Ebola treatment center in Foya. At admission, 194 patients were prescribed artemether-lumefantrine and 71 were prescribed artesunate-amodiaquine. The characteristics of the patients in the artesunate-amodiaquine group were similar to those in the artemether-lumefantrine group and those in the no-antimalarial group. A total of 125 of the 194 patients in the artemether-lumefantrine group (64.4%) died, as compared with 36 of the 71 patients in the artesunate-amodiaquine group (50.7%). In adjusted analyses, the artesunate-amodiaquine group had a 31% lower risk of death than the artemether-lumefantrine group (risk ratio, 0.69; 95% confidence interval, 0.54 to 0.89), with a stronger effect observed among patients without malaria. CONCLUSIONS Patients who were prescribed artesunate-amodiaquine had a lower risk of death from EVD than did patients who were prescribed artemether-lumefantrine. However, our analyses cannot exclude the possibility that artemether-lumefantrine is associated with an increased risk of death or that the use of artesunate-amodiaquine was associated with unmeasured patient characteristics that directly altered the risk of death.

Spatial and temporal dynamics of superspreading events in the 2014-2015 West Africa Ebola epidemic

Significance For many infections, some infected individuals transmit to disproportionately more susceptibles than others, a phenomenon referred to as “superspreading.” Understanding superspreading can facilitate devising individually targeted control measures, which may outperform population-level measures. Superspreading has been described for a recent Ebola virus (EBOV) outbreak, but systematic characterizations of its spatiotemporal dynamics are still lacking. We introduce a statistical framework that allows us to identify core characteristics of EBOV superspreading. We find that the epidemic was largely driven and sustained by superspreadings that are ubiquitous throughout the outbreak and that age is an important demographic predictor for superspreading. Our results highlight the importance of control measures targeted at potential superspreaders and enhance understanding of causes and consequences of superspreading for EBOV. The unprecedented scale of the Ebola outbreak in Western Africa (2014–2015) has prompted an explosion of efforts to understand the transmission dynamics of the virus and to analyze the performance of possible containment strategies. Models have focused primarily on the reproductive numbers of the disease that represent the average number of secondary infections produced by a random infectious individual. However, these population-level estimates may conflate important systematic variation in the number of cases generated by infected individuals, particularly found in spatially localized transmission and superspreading events. Although superspreading features prominently in first-hand narratives of Ebola transmission, its dynamics have not been systematically characterized, hindering refinements of future epidemic predictions and explorations of targeted interventions. We used Bayesian model inference to integrate individual-level spatial information with other epidemiological data of community-based (undetected within clinical-care systems) cases and to explicitly infer distribution of the cases generated by each infected individual. Our results show that superspreaders play a key role in sustaining onward transmission of the epidemic, and they are responsible for a significant proportion (∼61%) of the infections. Our results also suggest age as a key demographic predictor for superspreading. We also show that community-based cases may have progressed more rapidly than those notified within clinical-care systems, and most transmission events occurred in a relatively short distance (with median value of 2.51 km). Our results stress the importance of characterizing superspreading of Ebola, enhance our current understanding of its spatiotemporal dynamics, and highlight the potential importance of targeted control measures.

Impact and Lessons Learned from Mass Drug Administrations of Malaria Chemoprevention during the Ebola Outbreak in Monrovia, Liberia, 2014

Background In October 2014, during the Ebola outbreak in Liberia healthcare services were limited while malaria transmission continued. Médecins Sans Frontières (MSF) implemented a mass drug administration (MDA) of malaria chemoprevention (CP) in Monrovia to reduce malaria-associated morbidity. In order to inform future interventions, we described the scale of the MDA, evaluated its acceptance and estimated the effectiveness. Methods MSF carried out two rounds of MDA with artesunate/amodiaquine (ASAQ) targeting four neighbourhoods of Monrovia (October to December 2014). We systematically selected households in the distribution area and administered standardized questionnaires. We calculated incidence ratios (IR) of side effects using poisson regression and compared self-reported fever risk differences (RD) pre- and post-MDA using a z-test. Findings In total, 1,259,699 courses of ASAQ-CP were distributed. All households surveyed (n = 222; 1233 household members) attended the MDA in round 1 (r1) and 96% in round 2 (r2) (212/222 households; 1,154 household members). 52% (643/1233) initiated ASAQ-CP in r1 and 22% (256/1154) in r2. Of those not initiating ASAQ-CP, 29% (172/590) saved it for later in r1, 47% (423/898) in r2. Experiencing side effects in r1 was not associated with ASAQ-CP initiation in r2 (IR 1.0, 95%CI 0.49–2.1). The incidence of self-reported fever decreased from 4.2% (52/1229) in the month prior to r1 to 1.5% (18/1229) after r1 (p<0.001) and decrease was larger among household members completing ASAQ-CP (RD = 4.9%) compared to those not initiating ASAQ-CP (RD = 0.6%) in r1 (p<0.001). Conclusions The reduction in self-reported fever cases following the intervention suggests that MDAs may be effective in reducing cases of fever during Ebola outbreaks. Despite high coverage, initiation of ASAQ-CP was low. Combining MDAs with longer term interventions to prevent malaria and to improve access to healthcare may reduce both the incidence of malaria and the proportion of respondents saving their treatment for future malaria episodes.

The impact of control strategies and behavioural changes on the elimination of Ebola from Lofa County, Liberia

The Ebola epidemic in West Africa was stopped by an enormous concerted effort of local communities and national and international organizations. It is not clear, however, how much the public health response and behavioural changes in affected communities, respectively, contributed to ending the outbreak. Here, we analyse the epidemic in Lofa County, Liberia, lasting from March to November 2014, by reporting a comprehensive time line of events and estimating the time-varying transmission intensity using a mathematical model of Ebola transmission. Model fits to the epidemic show an alternation of peaks and troughs in transmission, consistent with highly heterogeneous spread. This is combined with an overall decline in the reproduction number of Ebola transmission from early August, coinciding with an expansion of the local Ebola treatment centre. We estimate that healthcare seeking approximately doubled over the course of the outbreak, and that isolation of those seeking healthcare reduced their reproduction number by 62% (mean estimate, 95% credible interval (CI) 59–66). Both expansion of bed availability and improved healthcare seeking contributed to ending the epidemic, highlighting the importance of community engagement alongside clinical intervention. This article is part of the themed issue ‘The 2013–2016 West African Ebola epidemic: data, decision-making and disease control’.

Estimating the number of secondary Ebola cases resulting from an unsafe burial and risk factors for transmission during the West Africa Ebola epidemic

Background Safely burying Ebola infected individuals is acknowledged to be important for controlling Ebola epidemics and was a major component of the 2013–2016 West Africa Ebola response. Yet, in order to understand the impact of safe burial programs it is necessary to elucidate the role of unsafe burials in sustaining chains of Ebola transmission and how the risk posed by activities surrounding unsafe burials, including care provided at home prior to death, vary with human behavior and geography. Methodology/Principal findings Interviews with next of kin and community members were carried out for unsafe burials in Sierra Leone, Liberia and Guinea, in six districts where the Red Cross was responsible for safe and dignified burials (SDB). Districts were randomly selected from a district-specific sampling frame comprised of villages and neighborhoods that had experienced cases of Ebola. An average of 2.58 secondary cases were potentially generated per unsafe burial and varied by district (range: 0–20). Contact before and after death was reported for 142 (46%) contacts. Caregivers of a primary case were 2.63 to 5.92 times more likely to become EVD infected compared to those with post-mortem contact only. Using these estimates, the Red Cross SDB program potentially averted between 1,411 and 10,452 secondary EVD cases, reducing the epidemic by 4.9% to 36.5%. Conclusions/Significance SDB is a fundamental control measure that limits community transmission of Ebola; however, for those individuals having contact before and after death, it was impossible to ascertain the exposure that caused their infection. The number of infections prevented through SDB is significant, yet greater impact would be achieved by early hospitalization of the primary case during acute illness.

Mortality, Morbidity and Health-Seeking Behaviour during the Ebola Epidemic 2014-2015 in Monrovia Results from a Mobile Phone Survey

Between March 2014 and July 2015 at least 10,500 Ebola cases including more than 4,800 deaths occurred in Liberia, the majority in Monrovia. However, official numbers may have underestimated the size of the outbreak. Closure of health facilities and mistrust in existing structures may have additionally impacted on all-cause morbidity and mortality. To quantify mortality and morbidity and describe health-seeking behaviour in Monrovia, Médecins sans Frontières (MSF) conducted a mobile phone survey from December 2014 to March 2015. We drew a random sample of households in Monrovia and conducted structured mobile phone interviews, covering morbidity, mortality and health-seeking behaviour from 14 May 2014 until the day of the survey. We defined an Ebola-related death as any death meeting the Liberian Ebola case definition. We calculated all-cause and Ebola-specific mortality rates. The sample consisted of 6,813 household members in 905 households. We estimated a crude mortality rate (CMR) of 0.33/10,000 persons/day (95%CI:0.25–0.43) and an Ebola-specific mortality rate of 0.06/10,000 persons/day (95%-CI:0.03–0.11). During the recall period, 17 Ebola cases were reported including those who died. In the 30 days prior to the survey 277 household members were reported sick; malaria accounted for 54% (150/277). Of the sick household members, 43% (122/276) did not visit any health care facility. The mobile phone-based survey was found to be a feasible and acceptable alternative method when data collection in the community is impossible. CMR was estimated well below the emergency threshold of 1/10,000 persons/day. Non-Ebola-related mortality in Monrovia was not higher than previous national estimates of mortality for Liberia. However, excess mortality directly resulting from Ebola did occur in the population. Importantly, the small proportion of sick household members presenting to official health facilities when sick might pose a challenge for future outbreak detection and mitigation. Substantial reported health-seeking behaviour outside of health facilities may also suggest the need for adapted health messaging and improved access to health care.

Unreported cases in the 2014-2016 Ebola epidemic: Spatiotemporal variation, and implications for estimating transmission

In the recent 2014–2016 Ebola epidemic in West Africa, non-hospitalized cases were an important component of the chain of transmission. However, non-hospitalized cases are at increased risk of going unreported because of barriers to access to healthcare. Furthermore, underreporting rates may fluctuate over space and time, biasing estimates of disease transmission rates, which are important for understanding spread and planning control measures. We performed a retrospective analysis on community deaths during the recent Ebola epidemic in Sierra Leone to estimate the number of unreported non-hospitalized cases, and to quantify how Ebola reporting rates varied across locations and over time. We then tested if variation in reporting rates affected the estimates of disease transmission rates that were used in surveillance and response. We found significant variation in reporting rates among districts, and district-specific rates of increase in reporting over time. Correcting time series of numbers of cases for variable reporting rates led, in some instances, to different estimates of the time-varying reproduction number of the epidemic, particularly outside the capital. Future analyses that compare Ebola transmission rates over time and across locations may be improved by considering the impacts of differential reporting rates.