Viewpoint: filovirus haemorrhagic fever outbreaks: much ado about nothing?

The recent outbreak of Marburg haemorrhagic fever in the Democratic Republic of Congo has put the filovirus threat back on the international health agenda. This paper gives an overview of Marburg and Ebola outbreaks so far observed and puts them in a public health perspective. Damage on the local level has been devastating at times, but was marginal on the international level despite the considerable media attention these outbreaks received. The potential hazard of outbreaks, however, after export of filovirus from its natural environment into metropolitan areas, is argued to be considerable. Some avenues for future research and intervention are explored. Beyond the obvious need to find the reservoir and study the natural history, public health strategies for a more timely and efficient response are urgently needed

Organisation of Health Care During an Outbreak of Marburg Haemorrhagic Fever in the Democratic Republic of Congo, 1999.

Organising health care was one of the tasks of the International Scientific and Technical Committee during the 1998-1999 outbreak in Durba/Watsa, in the north-eastern province (Province Orientale), Democratic Republic of Congo. With the logistical support of Médecins sans Frontières (MSF), two isolation units were created: one at the Durba Reference Health Centre and the other at the Okimo Hospital in Watsa. Between May 6th, the day the isolation unit was installed and May 19th, 15 patients were admitted to the Durba Health Centre. In only four of them were the diagnosis of Marburg haemorrhagic fever (MHF) confirmed by laboratory examination. Protective equipment was distributed to health care workers and family members caring for patients. Information about MHF, modes of transmission and the use of barrier nursing techniques was provided to health care workers and sterilisation procedures were reviewed. In contrast to Ebola outbreaks, there was little panic among health care workers and the general public in Durba and all health services remained operational

Projections of epidemic transmission and estimation of vaccination impact during an ongoing Ebola virus disease outbreak in Northeastern Democratic Republic of Congo, as of Feb. 25, 2019.

BackgroundAs of February 25, 2019, 875 cases of Ebola virus disease (EVD) were reported in North Kivu and Ituri Provinces, Democratic Republic of Congo. Since the beginning of October 2018, the outbreak has largely shifted into regions in which active armed conflict has occurred, and in which EVD cases and their contacts have been difficult for health workers to reach. We used available data on the current outbreak, with case-count time series from prior outbreaks, to project the short-term and long-term course of the outbreak.MethodsFor short- and long-term projections, we modeled Ebola virus transmission using a stochastic branching process that assumes gradually quenching transmission rates estimated from past EVD outbreaks, with outbreak trajectories conditioned on agreement with the course of the current outbreak, and with multiple levels of vaccination coverage. We used two regression models to estimate similar projection periods. Short- and long-term projections were estimated using negative binomial autoregression and Theil-Sen regression, respectively. We also used Gott's rule to estimate a baseline minimum-information projection. We then constructed an ensemble of forecasts to be compared and recorded for future evaluation against final outcomes. From August 20, 2018 to February 25, 2019, short-term model projections were validated against known case counts.ResultsDuring validation of short-term projections, from one week to four weeks, we found models consistently scored higher on shorter-term forecasts. Based on case counts as of February 25, the stochastic model projected a median case count of 933 cases by February 18 (95% prediction interval: 872-1054) and 955 cases by March 4 (95% prediction interval: 874-1105), while the auto-regression model projects median case counts of 889 (95% prediction interval: 876-933) and 898 (95% prediction interval: 877-983) cases for those dates, respectively. Projected median final counts range from 953 to 1,749. Although the outbreak is already larger than all past Ebola outbreaks other than the 2013-2016 outbreak of over 26,000 cases, our models do not project that it is likely to grow to that scale. The stochastic model estimates that vaccination coverage in this outbreak is lower than reported in its trial setting in Sierra Leone.ConclusionsOur projections are concentrated in a range up to about 300 cases beyond those already reported. While a catastrophic outbreak is not projected, it is not ruled out, and prevention and vigilance are warranted. Prospective validation of our models in real time allowed us to generate more accurate short-term forecasts, and this process may prove useful for future real-time short-term forecasting. We estimate that transmission rates are higher than would be seen under target levels of 62% coverage due to contact tracing and vaccination, and this model estimate may offer a surrogate indicator for the outbreak response challenges

Neurological, Cognitive, and Psychological Findings Among Survivors of Ebola Virus Disease From the 1995 Ebola Outbreak in Kikwit, Democratic Republic of Congo: A Cross-sectional Study.

BackgroundClinical sequelae of Ebola virus disease (EVD) have not been described more than 3 years postoutbreak. We examined survivors and close contacts from the 1995 Ebola outbreak in Kikwit, Democratic Republic of Congo (DRC), and determined prevalence of abnormal neurological, cognitive, and psychological findings and their association with EVD survivorship.MethodsFrom August to September 2017, we conducted a cross-sectional study in Kikwit, DRC. Over 2 decades after the EVD outbreak, we recruited EVD survivors and close contacts from the outbreak to undergo physical examination and culturally adapted versions of the Folstein mini-mental status exam (MMSE) and Goldberg anxiety and depression scale (GADS). We estimated the strength of relationships between EVD survivorship and health outcomes using linear regression models by comparing survivors versus close contacts, adjusting for age, sex, educational level, marital status, and healthcare worker status.ResultsWe enrolled 20 EVD survivors and 187 close contacts. Among the 20 EVD survivors, 4 (20%) reported at least 1 abnormal neurological symptom, and 3 (15%) had an abnormal neurological examination. Among the 187 close contacts, 14 (11%) reported at least 1 abnormal neurologic symptom, and 9 (5%) had an abnormal neurological examination. EVD survivors had lower mean MMSE and higher mean GADS scores as compared to close contacts (MMSE: adjusted coefficient: -1.85; 95% confidence interval [CI]: -3.63, -0.07; GADS: adjusted coefficient: 3.91; 95% CI: 1.76, 6.04).ConclusionsEVD survivors can have lower cognitive scores and more symptoms of depression and anxiety than close contacts more than 2 decades after Ebola virus outbreaks

Projections of Ebola outbreak size and duration with and without vaccine use in Équateur, Democratic Republic of Congo, as of May 27, 2018.

As of May 27, 2018, 6 suspected, 13 probable and 35 confirmed cases of Ebola virus disease (EVD) had been reported in Équateur Province, Democratic Republic of Congo. We used reported case counts and time series from prior outbreaks to estimate the total outbreak size and duration with and without vaccine use. We modeled Ebola virus transmission using a stochastic branching process model that included reproduction numbers from past Ebola outbreaks and a particle filtering method to generate a probabilistic projection of the outbreak size and duration conditioned on its reported trajectory to date; modeled using high (62%), low (44%), and zero (0%) estimates of vaccination coverage (after deployment). Additionally, we used the time series for 18 prior Ebola outbreaks from 1976 to 2016 to parameterize the Thiel-Sen regression model predicting the outbreak size from the number of observed cases from April 4 to May 27. We used these techniques on probable and confirmed case counts with and without inclusion of suspected cases. Probabilistic projections were scored against the actual outbreak size of 54 EVD cases, using a log-likelihood score. With the stochastic model, using high, low, and zero estimates of vaccination coverage, the median outbreak sizes for probable and confirmed cases were 82 cases (95% prediction interval [PI]: 55, 156), 104 cases (95% PI: 58, 271), and 213 cases (95% PI: 64, 1450), respectively. With the Thiel-Sen regression model, the median outbreak size was estimated to be 65.0 probable and confirmed cases (95% PI: 48.8, 119.7). Among our three mathematical models, the stochastic model with suspected cases and high vaccine coverage predicted total outbreak sizes closest to the true outcome. Relatively simple mathematical models updated in real time may inform outbreak response teams with projections of total outbreak size and duration

Chloroquine and Hydroxychloroquine for the Prevention or Treatment of Novel Coronavirus Disease (COVID-19) in Africa: Caution for Inappropriate Off-Label Use in Healthcare Settings

The novel severe acute respiratory syndrome-coronavirus-2 pandemic has spread to Africa, where nearly all countries have reported laboratory-confirmed cases of novel coronavirus disease (COVID-19). Although there are ongoing clinical trials of repurposed and investigational antiviral and immune-based therapies, there are as yet no scientifically proven, clinically effective pharmacological treatments for COVID-19. Among the repurposed drugs, the commonly used antimalarials chloroquine (CQ) and hydroxychloroquine (HCQ) have become the focus of global scientific, media, and political attention despite a lack of randomized clinical trials supporting their efficacy. Chloroquine has been used worldwide for about 75 years and is listed by the WHO as an essential medicine to treat malaria. Hydroxychloroquine is mainly used as a therapy for autoimmune diseases. However, the efficacy and safety of CQ/HCQ for the treatment of COVID-19 remains to be defined. Indiscriminate promotion and widespread use of CQ/HCQ have led to extensive shortages, self-treatment, and fatal overdoses. Shortages and increased market prices leave all countries vulnerable to substandard and falsified medical products, and safety issues are especially concerning for Africa because of its healthcare system limitations. Much needed in Africa is a cross-continental collaborative network for coordinated production, distribution, and post-marketing surveillance aligned to low-cost distribution of any approved COVID-19 drug; this would ideally be piggybacked on existing global aid efforts. Meanwhile, African countries should strongly consider implementing prescription monitoring schemes to ensure that any off-label CQ/HCQ use is appropriate and beneficial during this pandemic

Control of Ebola virus disease outbreaks: Comparison of health care worker-targeted and community vaccination strategies

Background Health care workers (HCW) are at risk of infection during Ebola virus disease outbreaks and therefore may be targeted for vaccination before or during outbreaks. The effect of these strategies depends on the role of HCW in transmission which is understudied. Methods To evaluate the effect of HCW-targeted or community vaccination strategies, we used a transmission model to explore the relative contribution of HCW and the community to transmission. We calibrated the model to data from multiple Ebola outbreaks. We quantified the impact of ahead-of-time HCW-targeted strategies, and reactive HCW and community vaccination. Results We found that for some outbreaks (we call “type 1″) HCW amplified transmission both to other HCW and the community, and in these outbreaks prophylactic vaccination of HCW decreased outbreak size. Reactive vaccination strategies had little effect because type 1 outbreaks ended quickly. However, in outbreaks with longer time courses (“type 2 outbreaks”), reactive community vaccination decreased the number of cases, with or without prophylactic HCW-targeted vaccination. For both outbreak types, we found that ahead-of-time HCW-targeted strategies had an impact at coverage of 30%. Conclusions The vaccine strategies tested had a different impact depending on the transmission dynamics and previous control measures. Although we will not know the characteristics of a new outbreak, ahead-of-time HCW-targeted vaccination can decrease the total outbreak size, even at low vaccine coverage

Artemisia Spp. Derivatives for COVID-19 Treatment: Anecdotal Use, Political Hype, Treatment Potential, Challenges, and Road Map to Randomized Clinical Trials

The world is currently facing a novel COVID-19 pandemic caused by SARS-CoV-2 that, as of July 12, 2020, has caused a reported 12,322,395 cases and 556,335 deaths. To date, only two treatments, remdesivir and dexamethasone, have demonstrated clinical efficacy through randomized controlled trials (RCTs) in seriously ill patients. The search for new or repurposed drugs for treatment of COVID-19 continues. We have witnessed anecdotal use of herbal medicines, including Artemisia spp. extracts, in low-income countries, and exaggerated claims of their efficacies that are not evidence based, with subsequent political controversy. These events highlight the urgent need for further research on herbal compounds to evaluate efficacy through RCTs, and, when efficacious compounds are identified, to establish the active ingredients, develop formulations and dosing, and define pharmacokinetics, toxicology, and safety to enable drug development. Derivatives from the herb Artemisia annua have been used as traditional medicine over centuries for the treatment of fevers, malaria, and respiratory tract infections. We review the bioactive compounds, pharmacological and immunological effects, and traditional uses for Artemisia spp. derivatives, and discuss the challenges and controversies surrounding current efforts and the scientific road map to advance them to prevent or treat COVID-19

Advancing detection and response capacities for emerging and re-emerging pathogens in Africa

Recurrent disease outbreaks caused by a range of emerging and resurging pathogens over the past decade reveal major gaps in public health preparedness, detection, and response systems in Africa. Underlying causes of recurrent disease outbreaks include inadequacies in the detection of new infectious disease outbreaks in the community, in rapid pathogen identification, and in proactive surveillance systems. In sub-Saharan Africa, where 70% of zoonotic outbreaks occur, there remains the perennial risk of outbreaks of new or re-emerging pathogens for which no vaccines or treatments are available. As the Ebola virus disease, COVID-19, and mpox (formerly known as monkeypox) outbreaks highlight, a major paradigm shift is required to establish an effective infrastructure and common frameworks for preparedness and to prompt national and regional public health responses to mitigate the effects of future pandemics in Africa