scholarly journals A Syndrome Definition Validation Approach for Ebola Virus Disease

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Dino Rumoro ◽  
Shital Shah ◽  
Marilyn Hallock ◽  
Gillian Gibbs ◽  
Gordon Trenholme ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Surveillance System ◽  
Ebola Virus ◽  
Virus Disease ◽  
Ebola Virus Disease ◽  
Disease Identification ◽  
Development And Validation ◽  
The Guardian

Describes the development and validation of an Ebola virus disease syndrome definition within the GUARDIAN (Geographic Utilization of Artificial Intelligence in Real-Time for Disease Identification and Alert Notification) surveillance system.

JOINT ESTIMATION OF THE TRANSMISSIBILITY AND SEVERITY OF EBOLA VIRUS DISEASE IN REAL TIME

2017 ◽  
Vol 25 (04) ◽  
pp. 587-603 ◽  
Author(s):  
YUSUKE ASAI ◽  
HIROSHI NISHIURA
Keyword(s):  
Real Time ◽  
Ebola Virus ◽  
Virus Disease ◽  
Critical Role ◽  
Estimation Method ◽  
Case Fatality ◽  
Ascertainment Bias ◽  
Joint Estimation ◽  
Ebola Virus Disease ◽  
Strong Impact

The effective reproduction number [Formula: see text], the average number of secondary cases that are generated by a single primary case at calendar time [Formula: see text], plays a critical role in interpreting the temporal transmission dynamics of an infectious disease epidemic, while the case fatality risk (CFR) is an indispensable measure of the severity of disease. In many instances, [Formula: see text] is estimated using the reported number of cases (i.e., the incidence data), but such report often does not arrive on time, and moreover, the rate of diagnosis could change as a function of time, especially if we handle diseases that involve substantial number of asymptomatic and mild infections and large outbreaks that go beyond the local capacity of reporting. In addition, CFR is well known to be prone to ascertainment bias, often erroneously overestimated. In this paper, we propose a joint estimation method of [Formula: see text] and CFR of Ebola virus disease (EVD), analyzing the early epidemic data of EVD from March to October 2014 and addressing the ascertainment bias in real time. To assess the reliability of the proposed method, coverage probabilities were computed. When ascertainment effort plays a role in interpreting the epidemiological dynamics, it is useful to analyze not only reported (confirmed or suspected) cases, but also the temporal distribution of deceased individuals to avoid any strong impact of time dependent changes in diagnosis and reporting.

scholarly journals The Ebola virus disease outbreak in Tonkolili district, Sierra Leone: a retrospective analysis of the Viral Haemorrhagic Fever surveillance system, July 2014–June 2015

2019 ◽  
Vol 147 ◽  
Author(s):  
Alessandro Miglietta ◽  
Angelo Solimini ◽  
Ghyslaine Bruna Djeunang Dongho ◽  
Carla Montesano ◽  
Giovanni Rezza ◽  
...  
Keyword(s):  
Sierra Leone ◽  
Symptom Onset ◽  
Surveillance System ◽  
Ebola Virus ◽  
Virus Disease ◽  
Multivariable Analysis ◽  
Data Availability ◽  
Ebola Virus Disease ◽  
Haemorrhagic Fever ◽  
Viral Haemorrhagic Fever

AbstractIn Sierra Leone, the Ebola virus disease (EVD) outbreak occurred with substantial differences between districts with someone even not affected. To monitor the epidemic, a community event-based surveillance system was set up, collecting data into the Viral Haemorrhagic Fever (VHF) database. We analysed the VHF database of Tonkolili district to describe the epidemiology of the EVD outbreak during July 2014–June 2015 (data availability). Multivariable analysis was used to identify risk factors for EVD, fatal EVD and barriers to healthcare access, by comparing EVD-positive vs. EVD-negative cases. Key-performance indicators for EVD response were also measured. Overall, 454 EVD-positive cases were reported. At multivariable analysis, the odds of EVD was higher among those reporting contacts with an EVD-positive/suspected case (odds ratio (OR) 2.47; 95% confidence interval (CI) 2.44–2.50; P < 0.01) and those attending funeral (OR 1.02; 95% CI 1.01–1.04; P < 0.01). EVD cases from Kunike chiefdom had a lower odds of death (OR 0.22; 95% CI 0.08–0.44; P < 0.01) and were also more likely to be hospitalised (OR 2.34; 95% CI 1.23–4.57; P < 0.05). Only 25.1% of alerts were generated within 1 day from symptom onset. EVD preparedness and response plans for Tonkolili should include social-mobilisation activities targeting Ebola/knowledge-attitudes-practice during funeral attendance, to avoid contact with suspected cases and to increase awareness on EVD symptoms, in order to reduce delays between symptom onset to alert generation and consequently improve the outbreak-response promptness.

scholarly journals Ebola virus disease diagnosis by real-time RT-PCR: A comparative study of 11 different procedures

2016 ◽  
Vol 77 ◽  
pp. 9-14 ◽  
Author(s):  
Pascal Cherpillod ◽  
Manuel Schibler ◽  
Gaël Vieille ◽  
Samuel Cordey ◽  
Aline Mamin ◽  
...  
Keyword(s):  
Comparative Study ◽  
Real Time ◽  
Ebola Virus ◽  
Virus Disease ◽  
Disease Diagnosis ◽  
Ebola Virus Disease ◽  
Rt Pcr

scholarly journals Use of Peripheral Health Units in Low-Transmission Ebola Virus Disease Surveillance

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Alyssa J. Young ◽  
Allison Connolly ◽  
Adam Hoar ◽  
Brooke Mancuso ◽  
John Mark Esplana ◽  
...  
Keyword(s):  
Sierra Leone ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Ebola Virus ◽  
Virus Disease ◽  
Malaria Prevalence ◽  
Ebola Virus Disease ◽  
Alert System ◽  
Community Based

Surveillance strategies for Ebola Virus Disease (EVD) in Sierra Leone use a centralized "live alert" system to refer suspect cases from the community to specialized Ebola treatment centers. As EVD case burden declined in Port Loko District, Sierra Leone so did the number of reported alerts. Because EVD presents similarly to malaria, the number of alerts should remain consistent with malaria prevalence in malaria-endemic areas, irrespective of the reduction in true EVD cases. A community-based EVD surveillance system with improved symptom recording and follow-up of malaria-confirmed patients at PHUs was implemented in order to strengthen the sensitivity of EVD reporting.

scholarly journals Impact of the Ebola virus disease outbreak (2014-2016) on Tuberculosis Surveillance Activities in Guinea's National Tuberculosis Program: A Time Series Analysis

2019 ◽  
Author(s):  
Magassouba Aboubacar Sidiki ◽  
Boubacar Djelo Diallo ◽  
Lansana Mady Camara ◽  
Kadiatou Sow ◽  
Souleymane Camara ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Surveillance System ◽  
Cross Correlation ◽  
Ebola Virus ◽  
Virus Disease ◽  
Disease Outbreak ◽  
Ebola Virus Disease ◽  
World Health ◽  
Series Analysis

Abstract Background Tuberculosis (TB) is a major cause of disease and death worldwide. According to estimates published by WHO, Guinea is one of the countries with a high incidence of tuberculosis and tuberculosis / HIV co-infection. In March 2014, the World Health Organization (WHO) announced the Ebola virus disease outbreak in Guinea that caused a health system disruption. Our study aimed to assess the impact of the Ebola virus disease outbreak on the TB surveillance system through the main indicators of TB-related morbidity and mortality.Methods This is a retrospective cohort study by comparing TB trends through TB surveillance data from periods before (2011-2013), during (2014-2015) and after (2016-2018) the Ebola virus disease outbreak. A time-series analysis was conducted to investigate the link between the decrease in TB incidence and the Ebola virus disease through cross-correlation. We evaluated the surveillance system to compare its current status with that of the Ebola virus disease outbreak period.Results The reporting rate for TB cases has decreased from 120 cases per 100,000 people reported in 2011 to 100 cases in 2014. The cross-correlation test between TB and the Ebola virus disease incidents shows a significant lag of -0.6 (60%) this corresponds to the drop in TB incidence observed when Ebola virus disease was at its peak in 2014. Concerning the surveillance system, of the 13 standards, only five are reached in 2019 compared to 3 in 2015.Conclusion The Ebola virus disease outbreak has had a severe impact on TB surveillance in Guinea. The introduction of an early warning system would preserve the TB surveillance system; which could encourage the implementation of set stakes to ensure access to diagnosis, treatment for enhanced surveillance of tuberculosis.

scholarly journals Development and validation of a UHPLC-MS/MS method for quantification of the prodrug remdesivir and its metabolite GS-441524: a tool for clinical pharmacokinetics of SARS-CoV-2/COVID-19 and Ebola virus disease

2020 ◽  
Vol 75 (7) ◽  
pp. 1772-1777 ◽  
Author(s):  
Valeria Avataneo ◽  
Amedeo de Nicolò ◽  
Jessica Cusato ◽  
Miriam Antonucci ◽  
Alessandra Manca ◽  
...  
Keyword(s):  
Ebola Virus ◽  
Thermal Inactivation ◽  
Virus Disease ◽  
Good Choice ◽  
Ebola Virus Disease ◽  
Nucleoside Triphosphate ◽  
Disease Treatment ◽  
Clinical Pharmacokinetics ◽  
Healthy Donors ◽  
Development And Validation

Abstract Background Remdesivir has received significant attention for its potential application in the treatment of COVID-19, caused by SARS-CoV-2. Remdesivir has already been tested for Ebola virus disease treatment and found to have activity against SARS and MERS coronaviruses. The remdesivir core contains GS-441524, which interferes with RNA-dependent RNA polymerases alone. In non-human primates, following IV administration, remdesivir is rapidly distributed into PBMCs and converted within 2 h to the active nucleoside triphosphate form, while GS-441524 is detectable in plasma for up to 24 h. Nevertheless, remdesivir pharmacokinetics and pharmacodynamics in humans are still unexplored, highlighting the need for a precise analytical method for remdesivir and GS-441524 quantification. Objectives The validation of a reliable UHPLC-MS/MS method for remdesivir and GS-441524 quantification in human plasma. Methods Remdesivir and GS-441524 standards and quality controls were prepared in plasma from healthy donors. Sample preparation consisted of protein precipitation, followed by dilution and injection into the QSight 220 UHPLC-MS/MS system. Chromatographic separation was obtained through an Acquity HSS T3 1.8 μm, 2.1 × 50 mm column, with a gradient of water and acetonitrile with 0.05% formic acid. The method was validated using EMA and FDA guidelines. Results Analyte stability has been evaluated and described in detail. The method successfully fulfilled the validation process and it was demonstrated that, when possible, sample thermal inactivation could be a good choice in order to improve biosafety. Conclusions This method represents a useful tool for studying remdesivir and GS-441524 clinical pharmacokinetics, particularly during the current COVID-19 outbreak.

scholarly journals Impact of the Ebola virus disease outbreak (2014-2016) on Tuberculosis Surveillance Activities in Guinea's National Tuberculosis Program: A Time Series Analysis

2020 ◽  
Author(s):  
Aboubacar Sidiki Magassouba ◽  
Boubacar Djelo Diallo ◽  
Lansana Mady Camara ◽  
Kadiatou Sow ◽  
Souleymane Camara ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Surveillance System ◽  
Cross Correlation ◽  
Ebola Virus ◽  
Virus Disease ◽  
Disease Outbreak ◽  
Ebola Virus Disease ◽  
Control Programs ◽  
National Tuberculosis

Abstract Background: Most countries in Subsaharan Africa have well-established National Tuberculosis Control Programs with relatively stable routine performances. However, major epidemiological events may result in significant disruptions. In March 2014, the World Health Organization announced the outbreak of Ebola virus disease in Guinea, a country with a high incidence of TB and HIV. Our study aims to assess the impact of the Ebola virus disease outbreak on TB notification, treatment and surveillance, using main indicators.Methods: This is a retrospective cohort study that compares TB trends using surveillance data from the periods before (2011-2013), during (2014-2016) and after (2017-2018) Ebola virus disease outbreak. A time series analysis is conducted to investigate the linkages between the decline in TB notification and the Ebola virus disease outbreak through cross-correlation. The lag in the cross-correlation test is evaluated using ANCOVA type II delayed variable dependent model. The surveillance system is assessed using TB surveillance standards and benchmarks and vital registration systems recommended by WHO, compared with those of 2015 during the Ebola virus disease.Results: The rate of reporting of TB declined from 120 cases per 100,000 in 2011 to 100 cases per 100,000 in 2014, at the peak of the Ebola virus disease outbreak. The time series cross-correlation test of all notified cases of TB and Ebola shows a significant lag of -0.4 (40%), reflecting a drop in the rate of notification (F-value=5.7 [95% CI: 0.2-21.3]). However, the Ebola virus disease had no negative impact on patient treatment outcomes (F-value=1.3 [95% CI: 0.002-8.8179]). Regarding the surveillance system, five out of 13 WHO standards and benchmarks were met following their evaluation in 2019, after the Ebola virus disease outbreak, compared to three in 2015.Conclusion: Major epidemics such as the Ebola virus disease outbreak may have a significant impact on well-established TB control programs as shown in the example of Guinea. On the other hand, it is noticed that, sudden disruptions of routine performance may lead programs to improve their surveillance system.

scholarly journals Impact of the Ebola virus disease outbreak (2014-2016) on Tuberculosis Surveillance Activities in Guinea's National Tuberculosis Program: A Time Series Analysis

2019 ◽  
Author(s):  
Aboubacar Sidiki Magassouba ◽  
Boubacar Djelo Diallo ◽  
Lansana Mady Camara ◽  
Kadiatou Sow ◽  
Souleymane Camara ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Surveillance System ◽  
Cross Correlation ◽  
Ebola Virus ◽  
Virus Disease ◽  
Disease Outbreak ◽  
Ebola Virus Disease ◽  
P Value ◽  
Correlation Test

Abstract Background Tuberculosis (TB) is a major cause of disease and death worldwide. According to World Health Organization (WHO) estimates, Guinea is a country with a high incidence of tuberculosis (TB) and TB / HIV co-infection. In March 2014, the WHO announced the Ebola virus disease (EVD) outbreak in Guinea that caused a health system disruption. Our study aimed to assess the impact of the Ebola virus disease outbreak on the TB surveillance system through the main indicators of TB-related morbidity and mortality. Methods This is a retrospective cohort study comparing TB trends using TB surveillance data from periods before (2011-2013), during (2014-2016) and after (2017-2018) the Ebola virus disease outbreak. A time-series analysis was conducted to investigate the link between the decrease in TB incidence and the Ebola virus disease through cross-correlation. We evaluated the lag observed in the cross-correlation test using the ANCOVA type II delayed variable dependent model. The current status of the surveillance system was compared to that of 2015 during the EVD through the Standards and benchmarks for TB surveillance and vital registration systems established by WHO. Results The reporting rate of TB cases decreased from 120 cases per 100,000 in 2011 to 100 cases per 100,000 in 2014, while the EVD outbreak was at its peak. The cross-correlation test between the time series of incident cases of all forms of TB and Ebola shows a significant lag of -0.4 (40%), which corresponds to the decrease in the incidence of TB cases observed when the EVD was steep in 2014 (p-value=0.024). However, the EVD had no negative impact on patient treatment outcomes (p-value=0.258). Regarding the surveillance system, out of 13 WHO standards and benchmark, five were reached in 2019 compared to three in 2015. Conclusion The EVD outbreak had a severe impact on TB surveillance in Guinea, with a significant decline in TB reporting rates during the epidemic period. The introduction of an early warning system would preserve the TB surveillance system ; which could encourage the implementation of interventions to ensure access to diagnosis, and enhanced surveillance for the treatment of TB.

scholarly journals Field investigation with real-time virus genetic characterisation support of a cluster of Ebola virus disease cases in Dubréka, Guinea, April to June 2015

2018 ◽  
Vol 23 (12) ◽  
Author(s):  
Alessandro Pini ◽  
Delayo Zomahoun ◽  
Sophie Duraffour ◽  
Tarik Derrough ◽  
Myrna Charles ◽  
...  
Keyword(s):  
Real Time ◽  
Ebola Virus ◽  
Virus Disease ◽  
Field Investigation ◽  
Ebola Virus Disease ◽  
Sample Collection ◽  
Scarce Resources ◽  
Genetic Characterisation ◽  
Phylogenetic Cluster ◽  
Outbreak Investigations

On 11 May 2015, the Dubréka prefecture, Guinea, reported nine laboratory-confirmed cases of Ebola virus disease (EVD). None could be epidemiologically linked to cases previously reported in the prefecture. We describe the epidemiological and molecular investigations of this event. We used the Dubréka EVD registers and the Ebola treatment centre’s (ETC) records to characterise chains of transmission. Real-time field Ebola virus sequencing was employed to support epidemiological results. An epidemiological cluster of 32 cases was found, of which 27 were laboratory confirmed, 24 were isolated and 20 died. Real-time viral sequencing on 12 cases demonstrated SL3 lineage viruses with sequences differing by one to three nt inside a single phylogenetic cluster. For isolated cases, the average time between symptom onset and ETC referral was 2.8 days (interquartile range (IQR): 1–4). The average time between sample collection and molecular results’ availability was 3 days (IQR: 2–5). In an area with scarce resources, the genetic characterisation supported the outbreak investigations in real time, linking cases where epidemiological investigation was limited and reassuring that the responsible strain was already circulating in Guinea. We recommend coupling thorough epidemiological and genomic investigations to control EVD clusters.

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