Ebola Virus Epidemiology, Transmission, and Evolution during Seven Months in Sierra Leone.

The 2013-2015 Ebola virus disease (EVD) epidemic is caused by the Makona variant of Ebola virus (EBOV). Early in the epidemic, genome sequencing provided insights into virus evolution and transmission and offered important information for outbreak response. Here, we analyze sequences from 232 patients sampled over 7 months in Sierra Leone, along with 86 previously released genomes from earlier in the epidemic. We confirm sustained human-to-human transmission within Sierra Leone and find no evidence for import or export of EBOV across national borders after its initial introduction. Using high-depth replicate sequencing, we observe both host-to-host transmission and recurrent emergence of intrahost genetic variants. We trace the increasing impact of purifying selection in suppressing the accumulation of nonsynonymous mutations over time. Finally, we note changes in the mucin-like domain of EBOV glycoprotein that merit further investigation. These findings clarify the movement of EBOV within the region and describe viral evolution during prolonged human-to-human transmission.

Genetic diversity and evolutionary dynamics of Ebola virus in Sierra Leone.

A novel Ebola virus (EBOV) first identified in March 2014 has infected more than 25,000 people in West Africa, resulting in more than 10,000 deaths. Preliminary analyses of genome sequences of 81 EBOV collected from March to June 2014 from Guinea and Sierra Leone suggest that the 2014 EBOV originated from an independent transmission event from its natural reservoir followed by sustained human-to-human infections. It has been reported that the EBOV genome variation might have an effect on the efficacy of sequence-based virus detection and candidate therapeutics. However, only limited viral information has been available since July 2014, when the outbreak entered a rapid growth phase. Here we describe 175 full-length EBOV genome sequences from five severely stricken districts in Sierra Leone from 28 September to 11 November 2014. We found that the 2014 EBOV has become more phylogenetically and genetically diverse from July to November 2014, characterized by the emergence of multiple novel lineages. The substitution rate for the 2014 EBOV was estimated to be 1.23 × 10(-3) substitutions per site per year (95% highest posterior density interval, 1.04 × 10(-3) to 1.41 × 10(-3) substitutions per site per year), approximating to that observed between previous EBOV outbreaks. The sharp increase in genetic diversity of the 2014 EBOV warrants extensive EBOV surveillance in Sierra Leone, Guinea and Liberia to better understand the viral evolution and transmission dynamics of the ongoing outbreak. These data will facilitate the international efforts to develop vaccines and therapeutics.

Transmission dynamics of Ebola virus disease and intervention effectiveness in Sierra Leone.

Sierra Leone is the most severely affected country by an unprecedented outbreak of Ebola virus disease (EVD) in West Africa. Although successfully contained, the transmission dynamics of EVD and the impact of interventions in the country remain unclear. We established a database of confirmed and suspected EVD cases from May 2014 to September 2015 in Sierra Leone and mapped the spatiotemporal distribution of cases at the chiefdom level. A Poisson transmission model revealed that the transmissibility at the chiefdom level, estimated as the average number of secondary infections caused by a patient per week, was reduced by 43% [95% confidence interval (CI): 30%, 52%] after October 2014, when the strategic plan of the United Nations Mission for Emergency Ebola Response was initiated, and by 65% (95% CI: 57%, 71%) after the end of December 2014, when 100% case isolation and safe burials were essentially achieved, both compared with before October 2014. Population density, proximity to Ebola treatment centers, cropland coverage, and atmospheric temperature were associated with EVD transmission. The household secondary attack rate (SAR) was estimated to be 0.059 (95% CI: 0.050, 0.070) for the overall outbreak. The household SAR was reduced by 82%, from 0.093 to 0.017, after the nationwide campaign to achieve 100% case isolation and safe burials had been conducted. This study provides a complete overview of the transmission dynamics of the 2014-2015 EVD outbreak in Sierra Leone at both chiefdom and household levels. The interventions implemented in Sierra Leone seem effective in containing the epidemic, particularly in interrupting household transmission.

Development, Use, and Impact of a Global Laboratory Database During the 2014 Ebola Outbreak in West Africa.

Background: The international impact, rapid widespread transmission, and reporting delays during the 2014 Ebola outbreak in West Africa highlighted the need for a global, centralized database to inform outbreak response. The World Health Organization and Emerging and Dangerous Pathogens Laboratory Network addressed this need by supporting the development of a global laboratory database. Methods: Specimens were collected in the affected countries from patients and dead bodies meeting the case definitions for Ebola virus disease. Test results were entered in nationally standardized spreadsheets and consolidated onto a central server. Results: From March 2014 through August 2016, 256343 specimens tested for Ebola virus disease were captured in the database. Thirty-one specimen types were collected, and a variety of diagnostic tests were performed. Regular analysis of data described the functionality of laboratory and response systems, positivity rates, and the geographic distribution of specimens. Conclusion: With data standardization and end user buy-in, the collection and analysis of large amounts of data with multiple stakeholders and collaborators across various user-access levels was made possible and contributed to outbreak response needs. The usefulness and value of a multifunctional global laboratory database is far reaching, with uses including virtual biobanking, disease forecasting, and adaption to other disease outbreaks.

Features of Ebola Virus Disease at the Late Outbreak Stage in Sierra Leone: Clinical, Virological, Immunological, and Evolutionary Analyses.

We performed Ebola virus disease diagnosis and viral load estimation for Ebola cases in Sierra Leone during the late stage of the 2014-2015 outbreak (January-March 2015) and analyzed antibody and cytokine levels and the viral genome sequences. Ebola virus disease was confirmed in 86 of 1001 (9.7%) patients, with an overall case fatality rate of 46.8%. Fatal cases exhibited significantly higher levels of viral loads, cytokines, and chemokines at late stages of infection versus early stage compared with survivors. The viruses converged in a new clade within sublineage 3.2.4, which had a significantly lower case fatality rate.

Clinical illness and outcomes in patients with Ebola in Sierra Leone.

BACKGROUND: Limited clinical and laboratory data are available on patients with Ebola virus disease (EVD). The Kenema Government Hospital in Sierra Leone, which had an existing infrastructure for research regarding viral hemorrhagic fever, has received and cared for patients with EVD since the beginning of the outbreak in Sierra Leone in May 2014. METHODS: We reviewed available epidemiologic, clinical, and laboratory records of patients in whom EVD was diagnosed between May 25 and June 18, 2014. We used quantitative reverse-transcriptase-polymerase-chain-reaction assays to assess the load of Ebola virus (EBOV, Zaire species) in a subgroup of patients. RESULTS: Of 106 patients in whom EVD was diagnosed, 87 had a known outcome, and 44 had detailed clinical information available. The incubation period was estimated to be 6 to 12 days, and the case fatality rate was 74%. Common findings at presentation included fever (in 89% of the patients), headache (in 80%), weakness (in 66%), dizziness (in 60%), diarrhea (in 51%), abdominal pain (in 40%), and vomiting (in 34%). Clinical and laboratory factors at presentation that were associated with a fatal outcome included fever, weakness, dizziness, diarrhea, and elevated levels of blood urea nitrogen, aspartate aminotransferase, and creatinine. Exploratory analyses indicated that patients under the age of 21 years had a lower case fatality rate than those over the age of 45 years (57% vs. 94%, P=0.03), and patients presenting with fewer than 100,000 EBOV copies per milliliter had a lower case fatality rate than those with 10 million EBOV copies per milliliter or more (33% vs. 94%, P=0.003). Bleeding occurred in only 1 patient. CONCLUSIONS: The incubation period and case fatality rate among patients with EVD in Sierra Leone are similar to those observed elsewhere in the 2014 outbreak and in previous outbreaks. Although bleeding was an infrequent finding, diarrhea and other gastrointestinal manifestations were common. (Funded by the National Institutes of Health and others.).

An Outbreak of Ebola Virus Disease in the Lassa Fever Zone.

BACKGROUND: Kenema Government Hospital (KGH) has developed an advanced clinical and laboratory research capacity to manage the threat of Lassa fever, a viral hemorrhagic fever (VHF). The 2013-2016 Ebola virus (EBOV) disease (EVD) outbreak is the first to have occurred in an area close to a facility with established clinical and laboratory capacity for study of VHFs. METHODS: Because of its proximity to the epicenter of the EVD outbreak, which began in Guinea in March 2014, the KGH Lassa fever Team mobilized to establish EBOV surveillance and diagnostic capabilities. RESULTS: Augustine Goba, director of the KGH Lassa laboratory, diagnosed the first documented case of EVD in Sierra Leone, on 25 May 2014. Thereafter, KGH received and cared for numbers of patients with EVD that quickly overwhelmed the capacity for safe management. Numerous healthcare workers contracted and lost their lives to EVD. The vast majority of subsequent EVD cases in West Africa can be traced back to a single transmission chain that includes this first diagnosed case. CONCLUSIONS: Responding to the challenges of confronting 2 hemorrhagic fever viruses will require continued investments in the development of countermeasures (vaccines, therapeutic agents, and diagnostic assays), infrastructure, and human resources.

Clinical and Virological Characteristics of Ebola Virus Disease Patients Treated With Favipiravir (T-705)-Sierra Leone, 2014.

BACKGROUND: During 2014-2015, an outbreak of Ebola virus disease (EVD) swept across parts of West Africa. No approved antiviral drugs are available for Ebola treatment currently. METHODS: A retrospective clinical case series was performed for EVD patients in Sierra Leone-China Friendship Hospital. Patients with confirmed EVD were sequentially enrolled and treated with either World Health Organization (WHO)-recommended supportive therapy (control group) from 10 to 30 October, or treated with WHO-recommended therapy plus favipiravir (T-705) from 1 to 10 November 2014. Survival and virological characteristics were observed for 85 patients in the control group and 39 in the T-705 treatment group. RESULTS: The overall survival rate in the T-705 treatment group was higher than that of the control group (56.4% [22/39] vs 35.3% [30/85]; P = .027). Among the 35 patients who finished all designed endpoint observations, the survival rate in the T-705 treatment group (64.8% [11/17]) was higher than that of the control group (27.8% [5/18]). Furthermore, the average survival time of the treatment group (46.9 ± 5.6 days) was longer than that of the control group (28.9 ± 4.7 days). Most symptoms of patients in the treatment group improved significantly. Additionally, 52.9% of patients who received T-705 had a >100-fold viral load reduction, compared with only 16.7% of patients in the control group. CONCLUSIONS: Treatment of EVD with T-705 was associated with prolonged survival and markedly reduced viral load, which makes a compelling case for further randomized controlled trials of T-705 for treating EVD.

Exposure Patterns Driving Ebola Transmission in West Africa: A Retrospective Observational Study.

BACKGROUND: The ongoing West African Ebola epidemic began in December 2013 in Guinea, probably from a single zoonotic introduction. As a result of ineffective initial control efforts, an Ebola outbreak of unprecedented scale emerged. As of 4 May 2015, it had resulted in more than 19,000 probable and confirmed Ebola cases, mainly in Guinea (3,529), Liberia (5,343), and Sierra Leone (10,746). Here, we present analyses of data collected during the outbreak identifying drivers of transmission and highlighting areas where control could be improved. METHODS AND FINDINGS: Over 19,000 confirmed and probable Ebola cases were reported in West Africa by 4 May 2015. Individuals with confirmed or probable Ebola ("cases") were asked if they had exposure to other potential Ebola cases ("potential source contacts") in a funeral or non-funeral context prior to becoming ill. We performed retrospective analyses of a case line-list, collated from national databases of case investigation forms that have been reported to WHO. These analyses were initially performed to assist WHO's response during the epidemic, and have been updated for publication. We analysed data from 3,529 cases in Guinea, 5,343 in Liberia, and 10,746 in Sierra Leone; exposures were reported by 33% of cases. The proportion of cases reporting a funeral exposure decreased over time. We found a positive correlation (r = 0.35, p < 0.001) between this proportion in a given district for a given month and the within-district transmission intensity, quantified by the estimated reproduction number (R). We also found a negative correlation (r = -0.37, p < 0.001) between R and the district proportion of hospitalised cases admitted within ≤4 days of symptom onset. These two proportions were not correlated, suggesting that reduced funeral attendance and faster hospitalisation independently influenced local transmission intensity. We were able to identify 14% of potential source contacts as cases in the case line-list. Linking cases to the contacts who potentially infected them provided information on the transmission network. This revealed a high degree of heterogeneity in inferred transmissions, with only 20% of cases accounting for at least 73% of new infections, a phenomenon often called super-spreading. Multivariable regression models allowed us to identify predictors of being named as a potential source contact. These were similar for funeral and non-funeral contacts: severe symptoms, death, non-hospitalisation, older age, and travelling prior to symptom onset. Non-funeral exposures were strongly peaked around the death of the contact. There was evidence that hospitalisation reduced but did not eliminate onward exposures. We found that Ebola treatment units were better than other health care facilities at preventing exposure from hospitalised and deceased individuals. The principal limitation of our analysis is limited data quality, with cases not being entered into the database, cases not reporting exposures, or data being entered incorrectly (especially dates, and possible misclassifications). CONCLUSIONS: Achieving elimination of Ebola is challenging, partly because of super-spreading. Safe funeral practices and fast hospitalisation contributed to the containment of this Ebola epidemic. Continued real-time data capture, reporting, and analysis are vital to track transmission patterns, inform resource deployment, and thus hasten and maintain elimination of the virus from the human population.

Ebola Virus Outbreak Investigation, Sierra Leone, September 28-November 11, 2014.

During 2014-2015, an outbreak of Ebola virus disease (EVD) swept across parts of West Africa. The China Mobile Laboratory Testing Team was dispatched to support response efforts; during September 28-November 11, 2014, they conducted PCR testing on samples from 1,635 suspected EVD patients. Of those patients, 50.4% were positive, of whom 84.6% lived within a 3-km zone along main roads connecting rural towns and densely populated cities. The median time from symptom onset to testing was 5 days. At testing, 75.7% of the confirmed patients had fever, and 94.1% reported at least 1 gastrointestinal symptom; all symptoms, except rash and hemorrhage, were more frequent in confirmed than nonconfirmed patients. Virus loads were significantly higher in EVD patients with fever, diarrhea, fatigue, or headache. The case-fatality rate was lower among patients 15-44 years of age and with virus loads of <100,000 RNA copies/mL. These findings are key for optimizing EVD control and treatment measures.

Genotypic anomaly in Ebola virus strains circulating in Magazine Wharf area, Freetown, Sierra Leone, 2015.

The Magazine Wharf area, Freetown, Sierra Leone was a focus of ongoing Ebola virus transmission from late June 2015. Viral genomes linked to this area contain a series of 13 T to C substitutions in a 150 base pair intergenic region downstream of viral protein 40 open reading frame, similar to the Ebolavirus/H.sapiens-wt/SLE/2014/Makona-J0169 strain (J0169) detected in the same town in November 2014. This suggests that recently circulating viruses from Freetown descend from a J0169-like virus.

Determinants of low birth weight deliveries at five referral hospitals in Western Area Urban district, Sierra Leone.

BACKGROUND: Low birth weight (LBW) contributes significantly to infant and child mortality. Each year, about 20 1million deliveries are LBW with 96.5% occurring in developing countries. Whiles the incidence of LBW is reducing in other districts of Sierra Leone, it has been reported to be increasing in the Western Area Urban district. Determining the risk factors in a specific geographic area is important for identifying mothers at risk and thereby for planning and taking appropriate action. The current study sought to identify factors associated with LBW deliveries in the Western Area Urban district of Sierra Leone. METHODS: A hospital-based unmatched 1:2 case-control study was conducted among mothers who delivered live singleton babies from November, 2019 to February, 2020 in five referral health facilities. Mothers were conveniently sampled and sequentially enrolled into the study after delivery. Their antenatal care cards were reviewed and a pre-tested questionnaire administered to the mothers. Data analysis was done using Stata 15.0 and association between maternal socio-demographic, socio-economic, obstetric and lifestyle factors and LBW assessed using bivariable and multivariable logistic regression analyses. RESULTS: A total of 438 mothers (146 cases and 292 controls), mean age: 24.2 (±5.8) and 26.1 (±5.5) years for cases and controls respectively participated in the study. Multivariable analysis revealed that being unemployed (AoR = 2.52, 95% CI 1.16-5.49, p = 0.020), having anaemia during pregnancy (AoR = 3.88, 95% CI 1.90-7.90, p <  0.001), having less than 2 years inter-pregnancy interval (AoR = 2.53, 95% CI 1.11-5.73, p = 0.026), and smoking cigarettes during pregnancy (AoR = 4.36, 95% CI 1.94-9.80, p <  0.001) were significantly associated with having LBW babies. CONCLUSION: Factors associated with LBW identified were unemployment, anaemia during pregnancy, < 2 years inter-pregnancy interval and cigarette smoking during pregnancy. Health care providers should screen and sensitize mothers on the risk factors of LBW during antenatal sessions.

Natural gas plays in the Marcellus Shale: challenges and potential opportunities.

Tapping the lucrative Marcellus Shale natural gas deposits may have a host of environmental concerns.

Implementing Nationwide Facility-based Electronic Disease Surveillance in Sierra Leone: Lessons Learned.

The Global Health Security Agenda aims to improve countries' ability to prevent, detect, and respond to infectious disease threats by building or strengthening core capacities required by the International Health Regulations (2005). One of those capacities is the development of surveillance systems to rapidly detect and respond to occurrences of diseases with epidemic potential. Since 2015, the US Centers for Disease Control and Prevention (CDC) has worked with partners in Sierra Leone to assist the Ministry of Health and Sanitation in developing an Integrated Disease Surveillance and Response (IDSR) system. Beginning in 2016, CDC, in collaboration with the World Health Organization and eHealth Africa, has supported the ministry in the development of Android device mobile data entry at the health facility for electronic IDSR (eIDSR), also known as health facility-based eIDSR. Health facility-based eIDSR was introduced via a pilot program in 1 district, and national rollout began in 2018. With more than 1,100 health facilities now reporting, the Sierra Leone eIDSR system is substantially larger than most mobile-device health (mHealth) projects found in the literature. Several technical innovations contributed to the success of health facility-based eIDSR in Sierra Leone. Among them were data compression and dual-mode (internet and text) message transmission to mitigate connectivity issues, user interface design tailored to local needs, and a continuous-feedback process to iteratively detect user or system issues and remediate challenges identified. The resultant system achieved high user acceptance and demonstrated the feasibility of an mHealth-based surveillance system implemented on a national scale.

Contact tracing performance during the Ebola virus disease outbreak in Kenema district, Sierra Leone.

Contact tracing in an Ebola virus disease (EVD) outbreak is the process of identifying individuals who may have been exposed to infected persons with the virus, followed by monitoring for 21 days (the maximum incubation period) from the date of the most recent exposure. The goal is to achieve early detection and isolation of any new cases in order to prevent further transmission. We performed a retrospective data analysis of 261 probable and confirmed EVD cases in the national EVD database and 2525 contacts in the Contact Line Lists in Kenema district, Sierra Leone between 27 April and 4 September 2014 to assess the performance of contact tracing during the initial stage of the outbreak. The completion rate of the 21-day monitoring period was 89% among the 2525 contacts. However, only 44% of the EVD cases had contacts registered in the Contact Line List and 6% of probable or confirmed cases had previously been identified as contacts. Touching the body fluids of the case and having direct physical contact with the body of the case conferred a 9- and 20-fold increased risk of EVD status, respectively. Our findings indicate that incompleteness of contact tracing led to considerable unmonitored transmission in the early months of the epidemic. To improve the performance of early outbreak contact tracing in resource poor settings, our results suggest the need for prioritized contact tracing after careful risk assessment and better alignment of Contact Line Listing with case ascertainment and investigation.This article is part of the themed issue 'The 2013-2016 West African Ebola epidemic: data, decision-making and disease control'.

Rapid deployment of a mobile biosafety level-3 laboratory in Sierra Leone during the 2014 Ebola virus epidemic.

BACKGROUND: Ebola virus emerged in West Africa in December 2013. The high population mobility and poor public health infrastructure in this region led to the development of the largest Ebola virus disease (EVD) outbreak to date. METHODOLOGY/PRINCIPAL FINDINGS: On September 26, 2014, China dispatched a Mobile Biosafety Level-3 Laboratory (MBSL-3 Lab) and a well-trained diagnostic team to Sierra Leone to assist in EVD diagnosis using quantitative real-time PCR, which allowed the diagnosis of suspected EVD cases in less than 4 hours from the time of sample receiving. This laboratory was composed of three container vehicles equipped with advanced ventilation system, communication system, electricity and gas supply system. We strictly applied multiple safety precautions to reduce exposure risks. Personnel, materials, water and air flow management were the key elements of the biosafety measures in the MBSL-3 Lab. Air samples were regularly collected from the MBSL-3 Lab, but no evidence of Ebola virus infectious aerosols was detected. Potentially contaminated objects were also tested by collecting swabs. On one occasion, a pipette tested positive for EVD. A total of 1,635 suspected EVD cases (824 positive [50.4%]) were tested from September 28 to November 11, 2014, and no member of the diagnostic team was infected with Ebola virus or other pathogens, including Lassa fever. The specimens tested included blood (69.2%) and oral swabs (30.8%) with positivity rates of 54.2% and 41.9%, respectively. The China mobile laboratory was thus instrumental in the EVD outbreak response by providing timely and reliable diagnostics. CONCLUSIONS/SIGNIFICANCE: The MBSL-3 Lab significantly contributed to establishing a suitable laboratory response capacity during the emergence of EVD in Sierra Leone.

Mapping the clinical outcomes and genetic evolution of Ebola virus in Sierra Leone.

Sierra Leone was the most severely affected country in Western Africa during the 2013-2016 outbreak of Ebola virus disease (EVD). Previous genome surveillance studies have revealed the origin, diversity, and evolutionary dynamics of the Ebola virus (EBOV); however, the information regarding EBOV sequences is insufficient, especially the clinical outcomes, given that the correlation between the clinical outcomes and the genetic evolution of EBOV is still not clear. Here, we collected and curated a comprehensive data set that includes 514 EBOV genome sequences from patients with confirmed EVD (including 60 sequences not previously studied), >87.5% of which have residence information and definitive clinical outcomes. Phylogenetic reconstruction revealed 11 lineages of EBOV in Sierra Leone. The median-joining haplotype network showed that haplotypes that are associated with lethal outcomes tend to contribute more to the spread of the EBOV in Sierra Leone than those with live outcomes. Analyses of the spatial-temporal distribution unraveled the lineage-distinctive distribution patterns. Different viral lineages have different case fatality rates (CFRs) during the same stage of the outbreak, implying that several lineages featuring SNPs may correlate with increased/decreased CFRs. This study provides invaluable data sets of EBOV infection and highlights the potential SNPs for further in-depth investigation.

Epidemiology of Ebola Virus Disease in the Western Area Region of Sierra Leone, 2014-2015.

INTRODUCTION: Western Area (WA) of Sierra Leone including the capital, Freetown, experienced an unprecedented outbreak of Ebola from 2014 to 2015. At the onset of the epidemic, there was little information about the epidemiology, transmission dynamics, and risk factors in urban settings as previous outbreaks were limited to rural/semi-rural settings. This study, therefore, aimed to describe the epidemiology of the outbreak and the factors which had most impact on the transmission of the epidemic and whether there were different drivers from those previously described in rural settings. METHODS: We conducted a descriptive epidemiology study in WA, Sierra Leone using secondary data from the National Ebola outbreak database. We also reviewed the Ebola situation reports, response strategy documents, and other useful documents. RESULTS: A total of 4,955 Ebola cases were identified between June 2014 and November 2015, although there were reports of cases occurring in WA toward end of May. All wards were affected, and Waterloo Area I (Ward 330), the capital city of Western Area Rural District, recorded the highest numbers of cases (580) and deaths (236). Majority of cases (63.4%) and deaths (66.8%) were in WA Urban District (WAU); 44 cases were imported from other provinces. Only 20% of cases had a history of contact with an Ebola case, and more than 30% were death alerts. Equal numbers of males and females were infected, and very few cases (3.2%) were health workers. Overall, transmission was through contact with infected individuals, and intense transmission occurred at the community level. In WAU, transmission was mostly between neighbors and among inhabitants of shared accommodations. The drivers of transmission included high population movement to and from WA, overcrowding, fear and lack of trust in the response, and negative community behaviors. Transmission was mostly through contact and with limited transmission through sex and breast milk. CONCLUSION: The unprecedented outbreak in WA was attributed to delayed detection, inadequate preparedness and response, intense population movements, overcrowding, and unresponsive communities. Anticipation, strengthening preparedness for early detection, and swift and effective response remains critical in mitigating a potential urban explosion of similar future outbreaks.

Transmission network of the 2014-2015 Ebola epidemic in Sierra Leone.

Understanding the growth and spatial expansion of (re)emerging infectious disease outbreaks, such as Ebola and avian influenza, is critical for the effective planning of control measures; however, such efforts are often compromised by data insufficiencies and observational errors. Here, we develop a spatial-temporal inference methodology using a modified network model in conjunction with the ensemble adjustment Kalman filter, a Bayesian inference method equipped to handle observational errors. The combined method is capable of revealing the spatial-temporal progression of infectious disease, while requiring only limited, readily compiled data. We use this method to reconstruct the transmission network of the 2014-2015 Ebola epidemic in Sierra Leone and identify source and sink regions. Our inference suggests that, in Sierra Leone, transmission within the network introduced Ebola to neighbouring districts and initiated self-sustaining local epidemics; two of the more populous and connected districts, Kenema and Port Loko, facilitated two independent transmission pathways. Epidemic intensity differed by district, was highly correlated with population size (r = 0.76, p = 0.0015) and a critical window of opportunity for containing local Ebola epidemics at the source (ca one month) existed. This novel methodology can be used to help identify and contain the spatial expansion of future (re)emerging infectious disease outbreaks.