Poverty is one of the most important determinants of adverse health outcomes globally, a major cause of societal instability and one of the largest causes of lost human potential. Traditional approaches to measuring and targeting poverty rely heavily on census data, which in most low- and middle-income countries (LMICs) are unavailable or out-of-date. Alternate measures are needed to complement and update estimates between censuses. This study demonstrates how public and private data sources that are commonly available for LMICs can be used to provide novel insight into the spatial distribution of poverty. We evaluate the relative value of modelling three traditional poverty measures using aggregate data from mobile operators and widely available geospatial data. Taken together, models combining these data sources provide the best predictive power (highest r2 = 0.78) and lowest error, but generally models employing mobile data only yield comparable results, offering the potential to measure poverty more frequently and at finer granularity. Stratifying models into urban and rural areas highlights the advantage of using mobile data in urban areas and different data in different contexts. The findings indicate the possibility to estimate and continually monitor poverty rates at high spatial resolution in countries with limited capacity to support traditional methods of data collection.
Understanding the introduction of farming and the adoption of Neolithic culture continues to be a major research objective in Europe. The authors make use of a new database of radiocarbon dates from Mesolithic and Neolithic sites to map the transition. While the overall effect is still a diffusion into Europe from the south-east, detailed spatial analysis reveals fascinating local variations: in some places change was rapid, and one population replaced another, in others it was gradual and owed to incoming ideas rather than people.
The long bones of the human upper limb usually show lateral asymmetries of length. This pattern can be attributed either to the mechanical consequences of handedness bias or to genetic or hormonal factors acting directly on longitudinal bone growth. Length data was obtained from the long bones of the upper limbs of a large skeletal assemblage from Wharram Percy, Yorkshire (England), predominantly deriving from the 1 lth-16th centuries A.D. The Wharram Percy adult skeletons had a population distribution of lateral asymmetries of length in the humerus and in the humerus-plus-radius (a proxy arm length index) which closely parallels the pattern of behavioural handedness found in modern populations. This pattern was developing in the skeletons from the infant and juvenile age ranges, but was absent in the neonates (of whom 12 out of 14 had longer left humeri). We argue that this supports the environmental hypothesis that the ontogeny of long bone length asymmetry is consequent to the earlier development of lateral bias in mechanical loading of the upper limbs.
It is reasonable to expect that the global dispersal of modern humans was influenced by habitat variation in space and time; but many simulation models average such variation into a single, homogeneous surface across which the dispersal process is modelled. We present a demographic simulation model in which rates of spatial range expansion can be modified by local habitat values. The broadscale vegetation cover of North America during the late last glacial is reconstructed and mapped at thousand-year intervals, 13,000-10,000 radiocarbon years BP. Results of the simulation of human dispersal into North America during the late last glacial are presented; output appears to match observed variation in occupancy of habitats during this period (as assessed from discard rates of diagnostic artefacts), if we assume that intrinsic population growth rates were fairly high and that local population densities varied as a function of environmental carrying capacity. Finally, a number of issues are raised relating to present limitations and possible future extensions of the simulation model.
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