Utilizing general human movement models to predict the spread of emerging infectious diseases in resource poor settings.

Human mobility is an important driver of geographic spread of infectious pathogens. Detailed information about human movements during outbreaks are, however, difficult to obtain and may not be available during future epidemics. The Ebola virus disease (EVD) outbreak in West Africa between 2014-16 demonstrated how quickly pathogens can spread to large urban centers following one cross-species transmission event. Here we describe a flexible transmission model to test the utility of generalised human movement models in estimating EVD cases and spatial spread over the course of the outbreak. A transmission model that includes a general model of human mobility significantly improves prediction of EVD's incidence compared to models without this component. Human movement plays an important role not only to ignite the epidemic in locations previously disease free, but over the course of the entire epidemic. We also demonstrate important differences between countries in population mixing and the improved prediction attributable to movement metrics. Given their relative rareness, locally derived mobility data are unlikely to exist in advance of future epidemics or pandemics. Our findings show that transmission patterns derived from general human movement models can improve forecasts of spatio-temporal transmission patterns in places where local mobility data is unavailable.

A global map of travel time to cities to assess inequalities in accessibility in 2015.

The economic and man-made resources that sustain human wellbeing are not distributed evenly across the world, but are instead heavily concentrated in cities. Poor access to opportunities and services offered by urban centres (a function of distance, transport infrastructure, and the spatial distribution of cities) is a major barrier to improved livelihoods and overall development. Advancing accessibility worldwide underpins the equity agenda of 'leaving no one behind' established by the Sustainable Development Goals of the United Nations. This has renewed international efforts to accurately measure accessibility and generate a metric that can inform the design and implementation of development policies. The only previous attempt to reliably map accessibility worldwide, which was published nearly a decade ago, predated the baseline for the Sustainable Development Goals and excluded the recent expansion in infrastructure networks, particularly in lower-resource settings. In parallel, new data sources provided by Open Street Map and Google now capture transportation networks with unprecedented detail and precision. Here we develop and validate a map that quantifies travel time to cities for 2015 at a spatial resolution of approximately one by one kilometre by integrating ten global-scale surfaces that characterize factors affecting human movement rates and 13,840 high-density urban centres within an established geospatial-modelling framework. Our results highlight disparities in accessibility relative to wealth as 50.9% of individuals living in low-income settings (concentrated in sub-Saharan Africa) reside within an hour of a city compared to 90.7% of individuals in high-income settings. By further triangulating this map against socioeconomic datasets, we demonstrate how access to urban centres stratifies the economic, educational, and health status of humanity.

Inferences about spatiotemporal variation in dengue virus transmission are sensitive to assumptions about human mobility: a case study using geolocated tweets from Lahore, Pakistan.

Billions of users of mobile phones, social media platforms, and other technologies generate an increasingly large volume of data that has the potential to be leveraged towards solving public health challenges. These and other big data resources tend to be most successful in epidemiological applications when utilized within an appropriate conceptual framework. Here, we demonstrate the importance of assumptions about host mobility in a framework for dynamic modeling of infectious disease spread among districts within a large urban area. Our analysis focused on spatial and temporal variation in the transmission of dengue virus (DENV) during a series of large seasonal epidemics in Lahore, Pakistan during 2011-2014. Similar to many directly transmitted diseases, DENV transmission occurs primarily where people spend time during daytime hours, given that DENV is transmitted by a day-biting mosquito. We inferred spatiotemporal variation in DENV transmission under five different assumptions about mobility patterns among ten districts of Lahore: no movement among districts, movement following patterns of geo-located tweets, movement proportional to district population size, and movement following the commonly used gravity and radiation models. Overall, we found that inferences about spatiotemporal variation in DENV transmission were highly sensitive to this range of assumptions about intra-urban human mobility patterns, although the three assumptions that allowed for a modest degree of intra-urban mobility all performed similarly in key respects. Differing inferences about transmission patterns based on our analysis are significant from an epidemiological perspective, as they have different implications for where control efforts should be targeted and whether conditions for transmission became more or less favorable over time. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1140/epjds/s13688-018-0144-x) contains supplementary material.

Spontaneous Age-related Changes of Peripheral Nerves in Cattle: Morphological and Biochemical Studies.

Peripheral nerve function is significantly affected by ageing. During ageing process, multiple changes occur on tissue cells and extracellular matrix. The aim of this work was to study the ageing-associated changes of peripheral nerves in adult and old regularly slaughtered cattle compared with young calves, and correlate them to the features reported in humans and laboratory animals. Samples of axial dorsal metacarpal nerves from 44 cows were collected immediately after slaughtering. Each nerve was dissected and divided into two fragments: one used for morphological evaluation (n = 43) and the other one for biochemical analysis (n = 31). Axonal degeneration, demyelination, thickness of perineurium and endoneurium and increase of mast cells were the most important features detected. The mean amount of glycosaminoglycan quantitative content recorded in the samples increased with the age. Axonal degeneration, demyelination and thickness of endoneurium were positively and significantly correlated with biochemistry. The presence of changes affecting the different elements of the peripheral nerves, similar to that reported in humans and in laboratory species, the easy availability of the nerve tissue in this species, the considerable size of the samples and the life conditions more similar to humans than to laboratory animals, allows the authors to consider cattle as a potential good model for the comparative study of spontaneous ageing nerve lesions.

The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015.

Since the year 2000, a concerted campaign against malaria has led to unprecedented levels of intervention coverage across sub-Saharan Africa. Understanding the effect of this control effort is vital to inform future control planning. However, the effect of malaria interventions across the varied epidemiological settings of Africa remains poorly understood owing to the absence of reliable surveillance data and the simplistic approaches underlying current disease estimates. Here we link a large database of malaria field surveys with detailed reconstructions of changing intervention coverage to directly evaluate trends from 2000 to 2015, and quantify the attributable effect of malaria disease control efforts. We found that Plasmodium falciparum infection prevalence in endemic Africa halved and the incidence of clinical disease fell by 40% between 2000 and 2015. We estimate that interventions have averted 663 (542-753 credible interval) million clinical cases since 2000. Insecticide-treated nets, the most widespread intervention, were by far the largest contributor (68% of cases averted). Although still below target levels, current malaria interventions have substantially reduced malaria disease incidence across the continent. Increasing access to these interventions, and maintaining their effectiveness in the face of insecticide and drug resistance, should form a cornerstone of post-2015 control strategies.

Wild ungulates as sentinel of BTV-8 infection in piedmont areas.

Bluetongue caused by the genotype 8 virus (BTV-8) appeared for the first time in BTV free areas in northern Italy in 2008. The presence of domestic animals outbreaks, abundant wild ungulates populations, and ongoing regional BTV control plans, made this area interesting to evaluate the role of wild ruminants in BTV-8 epidemiology. We analyzed spleen samples from hunted red deer (Cervus elaphus), roe deer (Capreolus capreolus) and Alpine chamois (Rupicapra rupicapra) by quantitative RT-PCR. Samples were collected from 2008 to 2011 in two provinces of Piedmont region. BTV-8 was detected in all ungulate species, confirming their receptivity to the infection. However, the viral load in the positive specimens was low, and decreased from 2008 to 2011. These results, together with the extinction of the epidemic following a regional livestock vaccination campaign, lead to hypothesize that wild ungulates were an epiphenomenon and they had not an important role in the domestic transmission cycle of BTV-8 in this area. In spite of this, wild ruminants appear to be good sentinels of BTV circulation and their monitoring could be useful for surveillance in piedmont areas.