A meta-analysis of serological response associated with yellow fever vaccination

Despite previous evidence of high level of efficacy, no synthetic metric of yellow fever (YF) vaccine efficacy is currently available. Based on the studies identified in a recent systematic review, we conducted a random-effects meta-analysis of the serological response associated with YF vaccination. Eleven studies conducted between 1965 and 2011 representing 4,868 individual observations were included in the meta-analysis. The pooled estimate of serological response was 97.5% (95% confidence interval [CI] = 82.9–99.7%). There was evidence of between-study heterogeneity (I2 = 89.1%), but this heterogeneity did not appear to be related to study size, study design, seroconversion measurement, or definition. Pooled estimates were significantly higher (P & 0.0001) among studies conducted in nonendemic settings (98.9%, 95% CI = 98.2–99.4%) than among those conducted in endemic settings (94.2%, 95% CI = 83.8–98.1%). These results provide background information against which to evaluate the efficacy of fractional doses of YF vaccine that may be used in outbreak situations

Mapping the baseline prevalence of lymphatic filariasis across Nigeria

Introduction: The baseline endemicity profile of lymphatic filariasis (LF) is a keybenchmark for planning control programmes, monitoring their impact on transmissionand assessing the feasibility of achieving elimination. Presented in this work is themodelled serological and parasitological prevalence of LF prior to the scale-up of massdrug administration (MDA) in Nigeria using a machine learning based approach.Methods: LF prevalence data generated by the Nigeria Lymphatic Filariasis ControlProgramme during country-wide mapping surveys conducted between 2000 and 2013were used to build the models. The dataset comprised of 1103 community-levelsurveys based on the detection of filarial antigenaemia using rapidimmunochromatographic card tests (ICT) and 184 prevalence surveys testing for thepresence of microfilaria (Mf) in blood. Using a suite of climate and environmentalcontinuous gridded variables and compiled site-level prevalence data, a quantileregression forest (QRF) model was fitted for both antigenaemia and microfilaraemia LFprevalence. Model predictions were projected across a continuous 5 × 5 km griddedmap of Nigeria. The number of individuals potentially infected by LF prior to MDAinterventions was subsequently estimated.Results: Maps presented predict a heterogeneous distribution of LF antigenaemia andmicrofilaraemia in Nigeria. The North-Central, North-West, and South-East regionsdisplayed the highest predicted LF seroprevalence, whereas predicted Mf prevalencewas highest in the southern regions. Overall, 8.7 million and 3.3 million infections werepredicted for ICT and Mf, respectively.Conclusions: QRF is a machine learning-based algorithm capable of handling high-dimensional data and fitting complex relationships between response and predictorvariables. Our models provide a benchmark through which the progress of ongoing LF control efforts can be monitored

Boundary Layer Transition Flight Experiment Overview and In-Situ Measurements

In support of the Boundary Layer Transition Flight Experiment (BLTFE) Project, a manufactured protuberance tile was installed on the port wing of Space Shuttle Orbiter Discovery for the flights of STS-119 and STS-128. Additional instrumentation was also installed in order to obtain more spatially resolved measurements downstream of the protuberance. This paper provides an overview of the BLTFE Project, including the project history, organizations involved, and motivations for the flight experiment. Significant efforts were made to place the protuberance at an appropriate location on the Orbiter and to design the protuberance to withstand the expected environments. Efforts were also extended to understand the as-fabricated shape of the protuberance and the thermal protection system tile configuration surrounding the protuberance. A high-level overview of the in-situ flight data is presented, along with a summary of the comparisons between pre- and post-flight analysis predictions and flight data. Comparisons show that predictions for boundary layer transition onset time closely match the flight data, while predicted temperatures were significantly higher than observed flight temperatures

Robustness and epistasis in mutation-selection models

We investigate the fitness advantage associated with the robustness of a phenotype against deleterious mutations using deterministic mutation-selection models of quasispecies type equipped with a mesa shaped fitness landscape. We obtain analytic results for the robustness effect which become exact in the limit of infinite sequence length. Thereby, we are able to clarify a seeming contradiction between recent rigorous work and an earlier heuristic treatment based on a mapping to a Schr\"odinger equation. We exploit the quantum mechanical analogy to calculate a correction term for finite sequence lengths and verify our analytic results by numerical studies. In addition, we investigate the occurrence of an error threshold for a general class of epistatic landscape and show that diminishing epistasis is a necessary but not sufficient condition for error threshold behavior.Comment: 20 pages, 14 figure

Osmotic pressure modulates single cell cycle dynamics inducing reversible growth arrest and reactivation of human metastatic cells

Biophysical cues such as osmotic pressure modulate proliferation and growth arrest of bacteria, yeast cells and seeds. In tissues, osmotic regulation takes place through blood and lymphatic capillaries and, at a single cell level, water and osmoregulation play a critical role. However, the effect of osmotic pressure on single cell cycle dynamics remains poorly understood. Here, we investigate the effect of osmotic pressure on single cell cycle dynamics, nuclear growth, proliferation, migration and protein expression, by quantitative time-lapse imaging of single cells genetically modified with fluorescent ubiquitination-based cell cycle indicator 2 (FUCCI2). Single cell data reveals that under hyperosmotic stress, distinct cell subpopulations emerge with impaired nuclear growth, delayed or growth arrested cell cycle and reduced migration. This state is reversible for mild hyperosmotic stress, where cells return to regular cell cycle dynamics, proliferation and migration. Thus, osmotic pressure can modulate the reversible growth arrest and reactivation of human metastatic cells

Estimating the potential public health impact of seasonal malaria chemoprevention in African children

Seasonal malaria chemoprevention, previously known as intermittent preventive treatment in children, is highly effective in areas with a short malaria transmission season. Here we assess seasonality in malaria incidence data and define a predictor of seasonality based on rainfall. We then use spatial rainfall, malaria endemicity and population data to identify areas likely to have highly seasonal malaria incidence, and estimate the population at risk and malaria burden in areas where seasonal malaria chemoprevention would be appropriate. We estimate that in areas suitable for seasonal malaria chemoprevention, there are 39 million children under 5 years of age, who experience 33.7 million malaria episodes and 152,000 childhood deaths from malaria each year. The majority of this burden occurs in the Sahelian or sub-Sahelian regions of Africa. Our data suggest that seasonal malaria chemoprevention has the potential to avert several million malaria cases and tens of thousands of childhood deaths each year if successfully delivered to the populations at risk

Outbreak of Ebola virus disease in the Democratic Republic of the Congo, April–May, 2018: an epidemiological study

Background On May 8, 2018, the Government of the Democratic Republic of the Congo reported an outbreak of Ebola virus disease in Équateur Province in the northwest of the country. The remoteness of most affected communities and the involvement of an urban centre connected to the capital city and neighbouring countries makes this outbreak the most complex and high risk ever experienced by the Democratic Republic of the Congo. We provide early epidemiological information arising from the ongoing investigation of this outbreak. Methods We classified cases as suspected, probable, or confirmed using national case definitions of the Democratic Republic of the Congo Ministère de la Santé Publique. We investigated all cases to obtain demographic characteristics, determine possible exposures, describe signs and symptoms, and identify contacts to be followed up for 21 days. We also estimated the reproduction number and projected number of cases for the 4-week period from May 25, to June 21, 2018. Findings As of May 30, 2018, 50 cases (37 confirmed, 13 probable) of Zaire ebolavirus were reported in the Democratic Republic of the Congo. 21 (42%) were reported in Bikoro, 25 (50%) in Iboko, and four (8%) in Wangata health zones. Wangata is part of Mbandaka, the urban capital of Équateur Province, which is connected to major national and international transport routes. By May 30, 2018, 25 deaths from Ebola virus disease had been reported, with a case fatality ratio of 56% (95% CI 39–72) after adjustment for censoring. This case fatality ratio is consistent with estimates for the 2014–16 west African Ebola virus disease epidemic (p=0·427). The median age of people with confirmed or probable infection was 40 years (range 8–80) and 30 (60%) were male. The most commonly reported signs and symptoms in people with confirmed or probable Ebola virus disease were fever (40 [95%] of 42 cases), intense general fatigue (37 [90%] of 41 cases), and loss of appetite (37 [90%] of 41 cases). Gastrointestinal symptoms were frequently reported, and 14 (33%) of 43 people reported haemorrhagic signs. Time from illness onset and hospitalisation to sample testing decreased over time. By May 30, 2018, 1458 contacts had been identified, of which 746 (51%) remained under active follow-up. The estimated reproduction number was 1·03 (95% credible interval 0·83–1·37) and the cumulative case incidence for the outbreak by June 21, 2018, is projected to be 78 confirmed cases (37–281), assuming heterogeneous transmissibility. Interpretation The ongoing Ebola virus outbreak in the Democratic Republic of the Congo has similar epidemiological features to previous Ebola virus disease outbreaks. Early detection, rapid patient isolation, contact tracing, and the ongoing vaccination programme should sufficiently control the outbreak. The forecast of the number of cases does not exceed the current capacity to respond if the epidemiological situation does not change. The information presented, although preliminary, has been essential in guiding the ongoing investigation and response to this outbreak

Mutation, selection, and ancestry in branching models: a variational approach

We consider the evolution of populations under the joint action of mutation and differential reproduction, or selection. The population is modelled as a finite-type Markov branching process in continuous time, and the associated genealogical tree is viewed both in the forward and the backward direction of time. The stationary type distribution of the reversed process, the so-called ancestral distribution, turns out as a key for the study of mutation-selection balance. This balance can be expressed in the form of a variational principle that quantifies the respective roles of reproduction and mutation for any possible type distribution. It shows that the mean growth rate of the population results from a competition for a maximal long-term growth rate, as given by the difference between the current mean reproduction rate, and an asymptotic decay rate related to the mutation process; this tradeoff is won by the ancestral distribution. Our main application is the quasispecies model of sequence evolution with mutation coupled to reproduction but independent across sites, and a fitness function that is invariant under permutation of sites. Here, the variational principle is worked out in detail and yields a simple, explicit result.Comment: 45 pages,8 figure

Yellow Fever in Africa: Estimating the Burden of Disease and Impact of Mass Vaccination from Outbreak and Serological Data

Background:Yellow fever is a vector-borne disease affecting humans and non-human primates in tropical areas of Africa and South America. While eradication is not feasible due to the wildlife reservoir, large scale vaccination activities in Africa during the 1940s to 1960s reduced yellow fever incidence for several decades. However, after a period of low vaccination coverage, yellow fever has resurged in the continent. Since 2006 there has been substantial funding for large preventive mass vaccination campaigns in the most affected countries in Africa to curb the rising burden of disease and control future outbreaks. Contemporary estimates of the yellow fever disease burden are lacking, and the present study aimed to update the previous estimates on the basis of more recent yellow fever occurrence data and improved estimation methods.Methods and Findings:Generalised linear regression models were fitted to a dataset of the locations of yellow fever outbreaks within the last 25 years to estimate the probability of outbreak reports across the endemic zone. Environmental variables and indicators for the surveillance quality in the affected countries were used as covariates. By comparing probabilities of outbreak reports estimated in the regression with the force of infection estimated for a limited set of locations for which serological surveys were available, the detection probability per case and the force of infection were estimated across the endemic zone.The yellow fever burden in Africa was estimated for the year 2013 as 130,000 (95% CI 51,000-380,000) cases with fever and jaundice or haemorrhage including 78,000 (95% CI 19,000-180,000) deaths, taking into account the current level of vaccination coverage. The impact of the recent mass vaccination campaigns was assessed by evaluating the difference between the estimates obtained for the current vaccination coverage and for a hypothetical scenario excluding these vaccination campaigns. Vaccination campaigns were estimated to have reduced the number of cases and deaths by 27% (95% CI 22%-31%) across the region, achieving up to an 82% reduction in countries targeted by these campaigns. A limitation of our study is the high level of uncertainty in our estimates arising from the sparseness of data available from both surveillance and serological surveys.Conclusions:With the estimation method presented here, spatial estimates of transmission intensity can be combined with vaccination coverage levels to evaluate the impact of past or proposed vaccination campaigns, thereby helping to allocate resources efficiently for yellow fever control. This method has been used by the Global Alliance for Vaccines and Immunization (GAVI Alliance) to estimate the potential impact of future vaccination campaigns.Please see later in the article for the Editors' Summary