No Arabic abstract
Radio refractivity, which is the bending of radio signal as it propagates through media, is very important in works involving terrestrial atmospheric electromagnetic propagation such as point-to-point microwave communication, terrestrial radio and television broadcast, mobile communication system, and so on. This study has focused on the West African region where it was found that the region has a refractivity which varies exponentially with height and from the coast towards the desert. Generally, refractivity gradient was found to range between -46.48 and -29.51 N-units/km (k-factor value of between 1.23 and 1.42) across the region, splitting the between sub- and super-refraction. The variation in refraction type was found to follow seasonal pattern across the West African region, with sub-refraction dominating during dry season and super-refraction dominating most part in the coastal area during the wet season.
Drought poses a significant threat to the delicate economies in subsaharan Africa. This study investigates the influence of large scale ocean oscillation on drought in West Africa. Standardized Precipitation Index for the region was computed using monthly precipitation data from the Climate Research Unit during the period 1961 -1990. The impact of three ocean oscillation indices - Southern Ocean Index (SOI), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO) on drought over West Africa was investigated using linear correlation, co-integration test, mutual information and nonlinear synchronization methods. SOI showed predominantly positive correlation with drought over the region while PDO and NAO showed negative correlation. This was confirmed by the co-integration tests. The nonlinear test revealed more complex relationship between the indices and drought. PDO has lesser influence or contribute less to the drought in the coastal region compared to the Sahel region of West Africa.
We use a multivariate formulation of sequential Monte Carlo filter that utilizes mechanistic models for Ebola virus propagation and available incidence data to simultaneously estimate the disease progression states and the model parameters. This method has the advantage of performing the inference online as the new data becomes available and estimates the evolution of basic reproductive ratio $R_0(t)$ of the Ebola outbreak through time. Our analysis identifies a peak in the basic reproductive ratio close to the time when Ebola cases were reported in Europe and the USA.
The history of southern Africa involved interactions between indigenous hunter-gatherers and a range of populations that moved into the region. Here we use genome-wide genetic data to show that there are at least two admixture events in the history of Khoisan populations (southern African hunter-gatherers and pastoralists who speak non-Bantu languages with click consonants). One involved populations related to Niger-Congo-speaking African populations, and the other introduced ancestry most closely related to west Eurasian (European or Middle Eastern) populations. We date this latter admixture event to approximately 900-1,800 years ago, and show that it had the largest demographic impact in Khoisan populations that speak Khoe-Kwadi languages. A similar signal of west Eurasian ancestry is present throughout eastern Africa. In particular, we also find evidence for two admixture events in the history of Kenyan, Tanzanian, and Ethiopian populations, the earlier of which involved populations related to west Eurasians and which we date to approximately 2,700 - 3,300 years ago. We reconstruct the allele frequencies of the putative west Eurasian population in eastern Africa, and show that this population is a good proxy for the west Eurasian ancestry in southern Africa. The most parsimonious explanation for these findings is that west Eurasian ancestry entered southern Africa indirectly through eastern Africa.
The Ebola virus in West Africa has infected almost 30,000 and killed over 11,000 people. Recent models of Ebola Virus Disease (EVD) have often made assumptions about how the disease spreads, such as uniform transmissibility and homogeneous mixing within a population. In this paper, we test whether these assumptions are necessarily correct, and offer simple solutions that may improve disease model accuracy. First, we use data and models of West African migration to show that EVD does not homogeneously mix, but spreads in a predictable manner. Next, we estimate the initial growth rate of EVD within country administrative divisions and find that it significantly decreases with population density. Finally, we test whether EVD strains have uniform transmissibility through a novel statistical test, and find that certain strains appear more often than expected by chance.
We introduce a data assimilation method to estimate model parameters with observations of passive tracers by directly assimilating Lagrangian Coherent Structures. Our approach differs from the usual Lagrangian Data Assimilation approach, where parameters are estimated based on tracer trajectories. We employ the Approximate Bayesian Computation (ABC) framework to avoid computing the likelihood function of the coherent structure, which is usually unavailable. We solve the ABC by a Sequential Monte Carlo (SMC) method, and use Principal Component Analysis (PCA) to identify the coherent patterns from tracer trajectory data. Our new method shows remarkably improved results compared to the bootstrap particle filter when the physical model exhibits chaotic advection.