Identifying Paucisymptomatic or Asymptomatic and Unrecognized Ebola Virus Disease Among Close Contacts Based on Exposure Risk Assessments and Screening Algorithms.

BACKGROUND: There is limited evidence to evaluate screening algorithms with rapid antigen testing and exposure assessments as identification strategies for paucisymptomatic or asymptomatic Ebola virus (EBOV) infection and unrecognized EBOV disease (EVD). METHODS: We used serostatus and self-reported postexposure symptoms from a cohort study to classify contact-participants as having no infection, paucisymptomatic or asymptomatic infection, or unrecognized EVD. Exposure risk was categorized as low, intermediate, or high. We created hypothetical scenarios to evaluate the World Health Organization (WHO) case definition with or without rapid diagnostic testing (RDT) or exposure assessments. RESULTS: This analysis included 990 EVD survivors and 1909 contacts, of whom 115 (6%) had paucisymptomatic or asymptomatic EBOV infection, 107 (6%) had unrecognized EVD, and 1687 (88%) were uninfected. High-risk exposures were drivers of unrecognized EVD (adjusted odds ratio, 3.5 [95% confidence interval, 2.4-4.9]). To identify contacts with unrecognized EVD who test negative by the WHO case definition, the sensitivity was 96% with RDT (95% confidence interval, 91%-99%), 87% with high-risk exposure (82%-92%), and 97% with intermediate- to high-risk exposures (93%-99%). The proportion of false-positives was 2% with RDT and 53%-93% with intermediate- and/or high-risk exposures. CONCLUSION: We demonstrated the utility and trade-offs of sequential screening algorithms with RDT or exposure risk assessments as identification strategies for contacts with unrecognized EVD.

Simplifying the estimation of diagnostic testing accuracy over time for high specificity tests in the absence of a gold standard.

Many different methods for evaluating diagnostic test results in the absence of a gold standard have been proposed. In this paper, we discuss how one common method, a maximum likelihood estimate for a latent class model found via the Expectation-Maximization (EM) algorithm can be applied to longitudinal data where test sensitivity changes over time. We also propose two simplified and nonparametric methods which use data-based indicator variables for disease status and compare their accuracy to the maximum likelihood estimation (MLE) results. We find that with high specificity tests, the performance of simpler approximations may be just as high as the MLE.

Feasibility of digital contact tracing in low-income settings - pilot trial for a location-based DCT app.

BACKGROUND: Data about the effectiveness of digital contact tracing are based on studies conducted in countries with predominantly high- or middle-income settings. Up to now, little research is done to identify specific problems for the implementation of such technique in low-income countries. METHODS: A Bluetooth-assisted GPS location-based digital contact tracing (DCT) app was tested by 141 participants during 14 days in a hospital in Monrovia, Liberia in February 2020. The DCT app was compared to a paper-based reference system. Hits between participants and 10 designated infected participants were recorded simultaneously by both methods. Additional data about GPS and Bluetooth adherence were gathered and surveys to estimate battery consumption and app adherence were conducted. DCT apps accuracy was evaluated in different settings. RESULTS: GPS coordinates from 101/141 (71.6%) participants were received. The number of hours recorded by the participants during the study period, true Hours Recorded (tHR), was 496.3 h (1.1% of maximum Hours recordable) during the study period. With the paper-based method 1075 hits and with the DCT app five hits of designated infected participants with other participants have been listed. Differences between true and maximum recording times were due to failed permission settings (45%), data transmission issues (11.3%), of the participants 10.1% switched off GPS and 32.5% experienced other technical or compliance problems. In buildings, use of Bluetooth increased the accuracy of the DCT app (GPS + BT 22.9 m ± 21.6 SD vs. GPS 60.9 m ± 34.7 SD; p = 0.004). GPS accuracy in public transportation was 10.3 m ± 10.05 SD with a significant (p = 0.007) correlation between precision and phone brand. GPS resolution outdoors was 10.4 m ± 4.2 SD. CONCLUSION: In our study several limitations of the DCT together with the impairment of GPS accuracy in urban settings impede the solely use of a DCT app. It could be feasible as a supplement to traditional manual contact tracing. DKRS, DRKS00029327 . Registered 20 June 2020 - Retrospectively registered.

A Longitudinal Study of Ebola Sequelae in Liberia.

BACKGROUND: Multiple health problems have been reported in survivors of Ebola virus disease (EVD). Attribution of these problems to the disease without a control group for analysis is difficult. METHODS: We enrolled a cohort of EVD survivors and their close contacts and prospectively collected data on symptoms, physical examination findings, and laboratory results. A subset of participants underwent ophthalmologic examinations. Persistence of Ebola virus (EBOV) RNA in semen samples from survivors was determined. RESULTS: A total of 966 EBOV antibody-positive survivors and 2350 antibody-negative close contacts (controls) were enrolled, and 90% of these participants were followed for 12 months. At enrollment (median time to baseline visit, 358 days after symptom onset), six symptoms were reported significantly more often among survivors than among controls: urinary frequency (14.7% vs. 3.4%), headache (47.6% vs. 35.6%), fatigue (18.4% vs. 6.3%), muscle pain (23.1% vs. 10.1%), memory loss (29.2% vs. 4.8%), and joint pain (47.5% vs. 17.5%). On examination, more survivors than controls had abnormal abdominal, chest, neurologic, and musculoskeletal findings and uveitis. Other than uveitis (prevalence at enrollment, 26.4% vs. 12.1%; at year 1, 33.3% vs. 15.4%), the prevalence of these conditions declined during follow-up in both groups. The incidence of most symptoms, neurologic findings, and uveitis was greater among survivors than among controls. EBOV RNA was detected in semen samples from 30% of the survivors tested, with a maximum time from illness to detection of 40 months. CONCLUSIONS: A relatively high burden of symptoms was seen in all participants, but certain symptoms and examination findings were more common among survivors. With the exception of uveitis, these conditions declined in prevalence during follow-up in both groups. Viral RNA in semen persisted for a maximum of 40 months. (Funded by the National Institute of Allergy and Infectious Diseases and the National Eye Institute; PREVAIL III ClinicalTrials.gov number, NCT02431923.).

Increased Likelihood of Detecting Ebola Virus RNA in Semen by Using Sample Pelleting.

Ebola virus RNA can reside for months or years in semen of survivors of Ebola virus disease and is probably associated with increased risk for cryptic sexual transmission of the virus. A modified protocol resulted in increased detection of Ebola virus RNA in semen and improved disease surveillance.

PREVAIL I Cluster Vaccination Study With rVSVΔG-ZEBOV-GP as Part of a Public Health Response in Liberia.

OBJECTIVE: In November 2015, a 15-year-old boy received a diagnosis of Ebola virus disease (EVD) at the John F. Kennedy Medical Center in Monrovia, Liberia. Two additional family members received a diagnosis of EVD. The protocol for a phase 2 placebo-controlled trial of 2 Ebola vaccines was amended and approved; in 4 days, a single-arm cluster vaccination trial using the Merck rVSVΔG-ZEBOV-GP vaccine was initiated. Here, we evaluate the safety and immunogenicity of the vaccine and discuss challenges for its implementation in a small Ebola outbreak. METHOD: We conducted a ring vaccination study among contacts and contacts of close contacts of EVD cases a in Monrovia. Participants were evaluated 1 and 6 months after vaccination. RESULTS: Among 650 close contacts and contacts of close contacts of EVD cases, 210 (32%) consented and were vaccinated with rVSVΔG-ZEBOV-GP. Of those vaccinated, 189 (90%) attended the month 1 follow-up visit; 166 (79%) attended the month 6 visit. No serious adverse events were reported. Among 88 participants without an elevated antibody level at baseline, 77.3% (95% confidence interval, 68.5-86.1) had an antibody response at 1 month. CONCLUSIONS: The Merck rVSVΔG-ZEBOV-GP vaccine appeared to be safe and immunogenic among the vaccinated individuals. However, fewer than one third of eligible individuals consented to vaccination. These data may help guide implementation decisions for of cluster vaccination programs in an Ebola cluster outbreak response situation.

Assessment and Optimization of the GeneXpert Diagnostic Platform for Detection of Ebola Virus RNA in Seminal Fluid.

Recent studies have suggested that Ebola virus (EBOV) ribonucleic acid (RNA) potentially present in the semen of a large number of survivors of Ebola virus disease (EVD) in Western Africa may contribute to sexual transmission of EVD and generate new clusters of cases in regions previously declared EVD-free. These findings drive the immediate need for a reliable, rapid, user-friendly assay for detection of EBOV RNA in semen that is deployable to multiple sites across Western Africa. In this study, we optimized the Xpert EBOV assay for semen samples by adding dithiothreitol. Compared to the assays currently in use in Liberia (including Ebola Zaire Target 1, major groove binder real-time-polymerase chain reaction assays, and original Xpert EBOV assay), the modified Xpert EBOV assay demonstrated greater sensitivity than the comparator assays. Thus, the modified Xpert EBOV assay is optimal for large-scale monitoring of EBOV RNA persistence in male survivors.

Bolstering Community Cooperation in Ebola Resurgence Protocols: Combining Field Blood Draw and Point-of-Care Diagnosis.

Alison Galvani and colleagues describe a community-based protocol to improve cooperation with Ebola testing as well as contact tracing, quarantining, and treatment.

Rapid Laboratory Identification of Neisseria meningitidis Serogroup C as the Cause of an Outbreak - Liberia, 2017.

On April 25, 2017, a cluster of unexplained illness and deaths among persons who had attended a funeral during April 21-22 was reported in Sinoe County, Liberia (1). Using a broad initial case definition, 31 cases were identified, including 13 (42%) deaths. Twenty-seven cases were from Sinoe County (1), and two cases each were from Grand Bassa and Monsterrado counties, respectively. On May 5, 2017, initial multipathogen testing of specimens from four fatal cases using the Taqman Array Card (TAC) assay identified Neisseria meningitidis in all specimens. Subsequent testing using direct real-time polymerase chain reaction (PCR) confirmed N. meningitidis in 14 (58%) of 24 patients with available specimens and identified N. meningitidis serogroup C (NmC) in 13 (54%) patients. N. meningitidis was detected in specimens from 11 of the 13 patients who died; no specimens were available from the other two fatal cases. On May 16, 2017, the National Public Health Institute of Liberia and the Ministry of Health of Liberia issued a press release confirming serogroup C meningococcal disease as the cause of this outbreak in Liberia.

The Opposite of Denial: Social Learning at the Onset of the Ebola Emergency in Liberia.

This study analyzes findings from a rapid-response community-based qualitative research initiative to study the content of Ebola-related communications and the transmission of Ebola-related behaviors and practices through mass media communications and social learning in Monrovia, Liberia during August-September 2014. Thirteen neighborhoods in the common Monrovia media market were studied to appraise the reach of health communications and outreach regarding Ebola prevention and response measures. A World Health Organization (WHO) research team collected data on social learning and Ebola knowledge, attitudes, and practices through focus group-based discussions and key informant interviews over a 14-day period to assess the spread of information during a period of rapidly escalating crisis. Findings show that during a 2-week period, Monrovia neighborhood residents demonstrated rapid changes in beliefs about the source of Ebola, modes of contagion, and infection prevention and control (IPC) practices, discarding incorrect information. Changes in practices tended to lag behind the acquisition of learning. Findings also show that many continued to support conspiracy theories even as correct information was acquired. The implications for community engagement are substantial: (1) Under conditions of accelerating mortality, communities rapidly assimilate health information and abandon incorrect information; (2) Behavior change is likely to lag behind changes in beliefs due to local physical, structural, sociocultural, and institutional constraints; (3) Reports of "resistance" in Monrovia during the Ebola response were overstated and based on a limited number of incidents, and failed to account for specific local conditions and constraints.

Ebola and Its Control in Liberia, 2014-2015.

The severe epidemic of Ebola virus disease in Liberia started in March 2014. On May 9, 2015, the World Health Organization declared Liberia free of Ebola, 42 days after safe burial of the last known case-patient. However, another 6 cases occurred during June-July; on September 3, 2015, the country was again declared free of Ebola. Liberia had by then reported 10,672 cases of Ebola and 4,808 deaths, 37.0% and 42.6%, respectively, of the 28,103 cases and 11,290 deaths reported from the 3 countries that were heavily affected at that time. Essential components of the response included government leadership and sense of urgency, coordinated international assistance, sound technical work, flexibility guided by epidemiologic data, transparency and effective communication, and efforts by communities themselves. Priorities after the epidemic include surveillance in case of resurgence, restoration of health services, infection control in healthcare settings, and strengthening of basic public health systems.

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.

Effect of Ebola progression on transmission and control in Liberia.

BACKGROUND: The Ebola outbreak that is sweeping across West Africa is the largest, most volatile, and deadliest Ebola epidemic ever recorded. Liberia is the most profoundly affected country, with more than 3500 infections and 2000 deaths recorded in the past 3 months. OBJECTIVE: To evaluate the contribution of disease progression and case fatality on transmission and to examine the potential for targeted interventions to eliminate the disease. DESIGN: Stochastic transmission model that integrates epidemiologic and clinical data on incidence and case fatality, daily viral load among survivors and nonsurvivors evaluated on the basis of the 2000-2001 outbreak in Uganda, and primary data on contacts of patients with Ebola in Liberia. SETTING: Montserrado County, Liberia, July to September 2014. MEASUREMENTS: Ebola incidence and case-fatality records from 2014 Liberian Ministry of Health and Social Welfare. RESULTS: The average number of secondary infections generated throughout the entire infectious period of a single infected case, R, was estimated as 1.73 (95% CI, 1.66 to 1.83). There was substantial stratification between survivors (RSurvivors), for whom the estimate was 0.66 (CI, 0.10 to 1.69), and nonsurvivors (RNonsurvivors), for whom the estimate was 2.36 (CI, 1.72 to 2.80). The nonsurvivors had the highest risk for transmitting the virus later in the course of disease progression. Consequently, the isolation of 75% of infected individuals in critical condition within 4 days from symptom onset has a high chance of eliminating the disease. LIMITATION: Projections are based on the initial dynamics of the epidemic, which may change as the outbreak and interventions evolve. CONCLUSION: These results underscore the importance of isolating the most severely ill patients with Ebola within the first few days of their symptomatic phase. PRIMARY FUNDING SOURCE: National Institutes of Health.

Elimination of Ebola Virus Transmission in Liberia - September 3, 2015.

Following 42 days since the last Ebola virus disease (Ebola) patient was discharged from a Liberian Ebola treatment unit (ETU), September 3, 2015, marks the second time in a 4-month period that the World Health Organization (WHO) has declared Liberia free of Ebola virus transmission (1). The first confirmed Ebola cases in West Africa were identified in southeastern Guinea on March 23, 2014, and within 1 week, cases were identified and confirmed in Liberia (1). Since then, Liberia has reported 5,036 confirmed and probable Ebola cases and 4,808 Ebola-related deaths. The epidemic in Liberia peaked in late summer and early fall of 2014, when more than 200 confirmed and probable cases were reported each week .

Controlling the last known cluster of Ebola virus disease - Liberia, January-February 2015.

As one of the three West African countries highly affected by the 2014-2015 Ebola virus disease (Ebola) epidemic, Liberia reported approximately 10,000 cases. The Ebola epidemic in Liberia was marked by intense urban transmission, multiple community outbreaks with source cases occurring in patients coming from the urban areas, and outbreaks in health care facilities (HCFs). This report, based on data from routine case investigations and contact tracing, describes efforts to stop the last known chain of Ebola transmission in Liberia. The index patient became ill on December 29, 2014, and the last of 21 associated cases was in a patient admitted into an Ebola treatment unit (ETU) on February 18, 2015. The chain of transmission was stopped because of early detection of new cases; identification, monitoring, and support of contacts in acceptable settings; effective triage within the health care system; and rapid isolation of symptomatic contacts. In addition, a "sector" approach, which divided Montserrado County into geographic units, facilitated the ability of response teams to rapidly respond to community needs. In the final stages of the outbreak, intensive coordination among partners and engagement of community leaders were needed to stop transmission in densely populated Montserrado County. A companion report describes the efforts to enhance infection prevention and control efforts in HCFs. After February 19, no additional clusters of Ebola cases have been detected in Liberia. On May 9, the World Health Organization declared the end of the Ebola outbreak in Liberia.

Initiation of a ring approach to infection prevention and control at non-Ebola health care facilities - Liberia, January-February 2015.

From mid-January to mid-February 2015, all confirmed Ebola virus disease (Ebola) cases that occurred in Liberia were epidemiologically linked to a single index patient from the St. Paul Bridge area of Montserrado County. Of the 22 confirmed patients in this cluster, eight (36%) sought and received care from at least one of 10 non-Ebola health care facilities (HCFs), including clinics and hospitals in Montserrado and Margibi counties, before admission to an Ebola treatment unit. After recognition that three patients in this emerging cluster had received care from a non-Ebola treatment unit, and in response to the risk for Ebola transmission in non-Ebola treatment unit health care settings, a focused infection prevention and control (IPC) rapid response effort for the immediate area was developed to target facilities at increased risk for exposure to a person with Ebola (Ring IPC). The Ring IPC approach, which provided rapid, intensive, and short-term IPC support to HCFs in areas of active Ebola transmission, was an addition to Liberia's proposed longer term national IPC strategy, which focused on providing a comprehensive package of IPC training and support to all HCFs in the country. This report describes possible health care worker exposures to the cluster's eight patients who sought care from an HCF and implementation of the Ring IPC approach. On May 9, 2015, the World Health Organization (WHO) declared the end of the Ebola outbreak in Liberia.