Concept: Economic Community of West African States
In its largest outbreak, Ebola virus disease is spreading through Guinea, Liberia, Sierra Leone, and Nigeria. We sequenced 99 Ebola virus genomes from 78 patients in Sierra Leone to ~2000× coverage. We observed a rapid accumulation of interhost and intrahost genetic variation, allowing us to characterize patterns of viral transmission over the initial weeks of the epidemic. This West African variant likely diverged from central African lineages around 2004, crossed from Guinea to Sierra Leone in May 2014, and has exhibited sustained human-to-human transmission subsequently, with no evidence of additional zoonotic sources. Because many of the mutations alter protein sequences and other biologically meaningful targets, they should be monitored for impact on diagnostics, vaccines, and therapies critical to outbreak response.
Background On March 23, 2014, the World Health Organization (WHO) was notified of an outbreak of Ebola virus disease (EVD) in Guinea. On August 8, the WHO declared the epidemic to be a “public health emergency of international concern.” Methods By September 14, 2014, a total of 4507 probable and confirmed cases, including 2296 deaths from EVD (Zaire species) had been reported from five countries in West Africa - Guinea, Liberia, Nigeria, Senegal, and Sierra Leone. We analyzed a detailed subset of data on 3343 confirmed and 667 probable Ebola cases collected in Guinea, Liberia, Nigeria, and Sierra Leone as of September 14. Results The majority of patients are 15 to 44 years of age (49.9% male), and we estimate that the case fatality rate is 70.8% (95% confidence interval [CI], 69 to 73) among persons with known clinical outcome of infection. The course of infection, including signs and symptoms, incubation period (11.4 days), and serial interval (15.3 days), is similar to that reported in previous outbreaks of EVD. On the basis of the initial periods of exponential growth, the estimated basic reproduction numbers (R0 ) are 1.71 (95% CI, 1.44 to 2.01) for Guinea, 1.83 (95% CI, 1.72 to 1.94) for Liberia, and 2.02 (95% CI, 1.79 to 2.26) for Sierra Leone. The estimated current reproduction numbers ® are 1.81 (95% CI, 1.60 to 2.03) for Guinea, 1.51 (95% CI, 1.41 to 1.60) for Liberia, and 1.38 (95% CI, 1.27 to 1.51) for Sierra Leone; the corresponding doubling times are 15.7 days (95% CI, 12.9 to 20.3) for Guinea, 23.6 days (95% CI, 20.2 to 28.2) for Liberia, and 30.2 days (95% CI, 23.6 to 42.3) for Sierra Leone. Assuming no change in the control measures for this epidemic, by November 2, 2014, the cumulative reported numbers of confirmed and probable cases are predicted to be 5740 in Guinea, 9890 in Liberia, and 5000 in Sierra Leone, exceeding 20,000 in total. Conclusions These data indicate that without drastic improvements in control measures, the numbers of cases of and deaths from EVD are expected to continue increasing from hundreds to thousands per week in the coming months.
The West African cocoa belt, reaching from Sierra Leone to southern Cameroon, is the origin of about 70% of the world’s cocoa (Theobroma cacao), which in turn is the basis of the livelihoods of about two million farmers. We analyze cocoa’s vulnerability to climate change in the West African cocoa belt, based on climate projections for the 2050s of 19 Global Circulation Models under the Intergovernmental Panel on Climate Change intermediate emissions scenario RCP 6.0. We use a combination of a statistical model of climatic suitability (Maxent) and the analysis of individual, potentially limiting climate variables. We find that: 1) contrary to expectation, maximum dry season temperatures are projected to become as or more limiting for cocoa as dry season water availability; 2) to reduce the vulnerability of cocoa to excessive dry season temperatures, the systematic use of adaptation strategies like shade trees in cocoa farms will be necessary, in reversal of the current trend of shade reduction; 3) there is a strong differentiation of climate vulnerability within the cocoa belt, with the most vulnerable areas near the forest-savanna transition in Nigeria and eastern Côte d'Ivoire, and the least vulnerable areas in the southern parts of Cameroon, Ghana, Côte d'Ivoire and Liberia; 4) this spatial differentiation of climate vulnerability may lead to future shifts in cocoa production within the region, with the opportunity of partially compensating losses and gains, but also the risk of local production expansion leading to new deforestation. We conclude that adaptation strategies for cocoa in West Africa need to focus at several levels, from the consideration of tolerance to high temperatures in cocoa breeding programs, the promotion of shade trees in cocoa farms, to policies incentivizing the intensification of cocoa production on existing farms where future climate conditions permit and the establishment of new farms in already deforested areas.
At 6 a.m., our medical team arrives at the Ebola case-management center in the Kailahun district of Sierra Leone to take blood samples. At our 80-bed center here near the borders of Liberia and Guinea, 8 new patients were admitted yesterday, 9 need to have a repeat test 72 hours after their symptoms began, and some we hope to discharge today: at least 18 blood samples to obtain. The center currently houses 64 patients in all, 4 of them children less than 5 years of age. We have already seen 2 patients die today. I have been here for 7 . . .
Near the end of 2013, an outbreak of Zaire ebolavirus (EBOV) began in Guinea, subsequently spreading to neighboring Liberia and Sierra Leone. As this epidemic grew, important public health questions emerged about how and why this outbreak was so different from previous episodes. This review provides a synthetic synopsis of the 2014-15 outbreak, with the aim of understanding its unprecedented spread. We present a summary of the history of previous epidemics, describe the structure and genetics of the ebolavirus, and review our current understanding of viral vectors and the latest treatment practices. We conclude with an analysis of the public health challenges epidemic responders faced and some of the lessons that could be applied to future outbreaks of Ebola or other viruses.
Drug-resistant tuberculosis (TB) is a global public health problem. Adequate management requires baseline drug-resistance prevalence data. In West Africa, due to a poor laboratory infrastructure and inadequate capacity, such data are scarce. Therefore, the true extent of drug-resistant TB was hitherto undetermined. In 2008, a new research network, the West African Network of Excellence for Tuberculosis, AIDS and Malaria (WANETAM), was founded, comprising nine study sites from eight West African countries (Burkina Faso, The Gambia, Ghana, Guinea-Bissau, Mali, Nigeria, Senegal and Togo). The goal was to establish Good Clinical Laboratory Practice (GCLP) principles and build capacity in standardised smear microscopy and mycobacterial culture across partnering laboratories to generate the first comprehensive West African drug-resistance data.
An outbreak of Ebola virus disease (EVD) has jolted West Africa, claiming more than 1000 lives since the virus emerged in Guinea in early 2014 (see figure). The rapidly increasing numbers of cases in the African countries of Guinea, Liberia, and Sierra Leone have had public health authorities on high alert throughout the spring and summer. More recent events including the spread of EVD to Nigeria (Africa’s most populous country) and the recent evacuation to the United States of two American health care workers with EVD have captivated the world’s attention and concern. Health professionals and the general public are . . .
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.
Six-year-old Fatou was exposed to Ebola at her uncle’s funeral in Forécariah, a district along Guinea’s border with Sierra Leone where about 50% of all Guinea’s Ebola cases since February 2015 have occurred.(1) Fatou’s entire family was registered as contacts to be monitored for the next 21 days, during which the disease could develop. A contact tracer began making daily visits to check their temperatures and evaluate them for symptoms. For the first few days, everything seemed fine, but on the fifth day, Fatou was found to have fever and vomiting. A response team was dispatched to bring her to . . .
As of November 2015, the Ebola virus disease (EVD) epidemic that began in West Africa in late 2013 is waning. The human toll includes more than 28,000 Ebola virus disease (EVD) cases and 11,000 deaths in Guinea, Liberia, and Sierra Leone, the most heavily-affected countries. We reviewed 66 mathematical modeling studies of the EVD epidemic published in the peer-reviewed literature to assess the key uncertainties models addressed, data used for modeling, public sharing of data and results, and model performance. Based on the review, we suggest steps to improve the use of modeling in future public health emergencies.