Healthcare network operation in Iquique after the 2014, Pisagua earthquake

On April 1st, 2014, the 8.2 Mw Pisagua earthquake affected the population in the north of Chile and generated disruption of services in the region. The largest effects of the earthquake were observed in the city of Iquique, capital of the Tarapaca Region, where more than 80% of the population of the region lives. This research describes the response of the public healthcare network of Iquique after the earthquake, and aims to identify the principal factors contributing to the network resilience during the early response and recovery phase after the earthquake. Despite the large magnitude of the earthquake, the observed structural damage was minor in the five healthcare centers considered (i.e., the regional hospital and 4 Primary Healthcare Attention Centers, PHACs). However, disruption of services in the healthcare network was large and due mainly to the collapse of non-structural components. Overall, the proper response of the healthcare network of Iquique was heavily supported by the PHACs, which largely provided first-aid, containment, and low-complexity attention to the population, allowing the hospital to focus on more complex procedures. The findings of this study suggest that the resilience of the healthcare network system, besides the robustness of the network’s facilities and their critical units, is also highly dependent on the interrelations and interactions between them in early post-earthquake recovery phases

Impact on Chilean hospitals following the 2015 Illapel earthquake

In a post-disaster environment, hospitals play a critical role in healthcare services continuities to the population while effectively coping with eventual losses of functionality. These losses come from physical damage to the facility, loss of utility lifelines, failure in supply chains, and reduction of personnel. However, data describing the detailed performance of hospitals during past earthquakes are scarce. Consequently, following the 2015 Mw 8.3 Illapel earthquake in central Chile, an exhaustive field campaign was carried out in the Coquimbo region to collect substantial perishable data to describe physical damage to hospitals and functionality losses. This study presents first the baseline information obtained in nine surveyed government hospitals, including size, location and type of infrastructure. Then, the seismic impact was analyzed and classified to show the main physical structural and non-structural damage, lifeline interruptions, losses in hospital units, and variations in flow of patients and staff. Transfers, discharges and evacuations of patients that occurred after the event were also reported. We found that the earthquake did not affect strongly the healthcare service despite the fact that most of the structural and non-structural damage was localized in the largest regional hospital. The archival nature of the data collected may deepen our understanding of the post-earthquake healthcare system performance, which is very useful in improving disaster preparation and overall resilience

Spatially clustered count data provide more efficient search strategies in invasion biology and disease control.

Geographic profiling, a mathematical model originally developed in criminology, is increasingly being used in ecology and epidemiology. Geographic profiling boasts a wide range of applications, such as finding source populations of invasive species or breeding sites of vectors of infectious disease. The model provides a cost-effective approach for prioritising search strategies for source locations and does so via simple data in the form of the positions of each observation, such as individual sightings of invasive species or cases of a disease. In doing so, however, classic geographic profiling approaches fail to make the distinction between those areas containing observed absences and those areas where no data were recorded. Absence data are generated via spatial sampling protocols but are often discarded during the inference process. Here we construct a geographic profiling model that resolves these issues by making inferences via count data - analysing a set of discrete sentinel locations at which the number of encounters has been recorded. Crucially, in our model this number can be zero. We verify the ability of this new model to estimate source locations and other parameters of practical interest via a Bayesian power analysis. We also measure model performance via real-world data in which the model infers breeding locations of mosquitoes in bromeliads in Miami-Dade County, Florida. In both cases, our novel model produces more efficient search strategies by shifting focus from those areas containing observed absences to those with no data, an improvement over existing models that treat these areas equally. Our model makes important improvements upon classic geographic profiling methods, which will significantly enhance real-world efforts to develop conservation management plans and targeted interventions

Economic Impact of Cystic Echinococcosis in Peru

Cystic echinococcosis (CE), caused by infection with the larval stage of the cestode Echinococcus granulosus, constitutes an important public health problem in Peru. Despite its high prevalence in endemic communities no studies have attempted to estimate the economic impact of CE in Peruvian society. We used official and published sources of epidemiological and economic information to estimate direct and indirect costs associated with livestock production losses and human disease. We also used disability adjusted life years (DALYs) which is an overall measure of disease burden, expressed as number of years lost due to ill-health, disability or early death due to CE. We found that the total estimated cost of human CE in Peru was U.S.$2,420,348 per year. Total estimated livestock-associated costs due to CE ranged from U.S.$196,681 to U.S.$3,846,754. An estimated 1,139 DALYs were also lost due to surgical cases of CE which is comparable to DALY losses from Amebiasis or Malaria in Peru. This conservative assessment found significant economic losses caused by this CE in Peruvian society. The findings of this study are important as these data can serve to prioritize those areas that may need to be targeted in a control program

Stimulus-dependent maximum entropy models of neural population codes

Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. To be able to infer a model for this distribution from large-scale neural recordings, we introduce a stimulus-dependent maximum entropy (SDME) model---a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. The model is able to capture the single-cell response properties as well as the correlations in neural spiking due to shared stimulus and due to effective neuron-to-neuron connections. Here we show that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. As a result, the SDME model gives a more accurate account of single cell responses and in particular outperforms uncoupled models in reproducing the distributions of codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like surprise and information transmission in a neural population.Comment: 11 pages, 7 figure

Nut production in Bertholletia excelsa across a logged forest mosaic: implications for multiple forest use

Although many examples of multiple-use forest management may be found in tropical smallholder systems, few studies provide empirical support for the integration of selective timber harvesting with non-timber forest product (NTFP) extraction. Brazil nut (Bertholletia excelsa, Lecythidaceae) is one of the world’s most economically-important NTFP species extracted almost entirely from natural forests across the Amazon Basin. An obligate out-crosser, Brazil nut flowers are pollinated by large-bodied bees, a process resulting in a hard round fruit that takes up to 14 months to mature. As many smallholders turn to the financial security provided by timber, Brazil nut fruits are increasingly being harvested in logged forests. We tested the influence of tree and stand-level covariates (distance to nearest cut stump and local logging intensity) on total nut production at the individual tree level in five recently logged Brazil nut concessions covering about 4000 ha of forest in Madre de Dios, Peru. Our field team accompanied Brazil nut harvesters during the traditional harvest period (January-April 2012 and January-April 2013) in order to collect data on fruit production. Three hundred and ninety-nine (approximately 80%) of the 499 trees included in this study were at least 100 m from the nearest cut stump, suggesting that concessionaires avoid logging near adult Brazil nut trees. Yet even for those trees on the edge of logging gaps, distance to nearest cut stump and local logging intensity did not have a statistically significant influence on Brazil nut production at the applied logging intensities (typically 1–2 timber trees removed per ha). In one concession where at least 4 trees ha-1 were removed, however, the logging intensity covariate resulted in a marginally significant (0.09) P value, highlighting a potential risk for a drop in nut production at higher intensities. While we do not suggest that logging activities should be completely avoided in Brazil nut rich forests, when a buffer zone cannot be observed, low logging intensities should be implemented. The sustainability of this integrated management system will ultimately depend on a complex series of socioeconomic and ecological interactions. Yet we submit that our study provides an important initial step in understanding the compatibility of timber harvesting with a high value NTFP, potentially allowing for diversification of forest use strategies in Amazonian Perù

Solving large 0–1 multidimensional knapsack problems by a new simplified binary artificial fish swarm algorithm

The artificial fish swarm algorithm has recently been emerged in continuous global optimization. It uses points of a population in space to identify the position of fish in the school. Many real-world optimization problems are described by 0-1 multidimensional knapsack problems that are NP-hard. In the last decades several exact as well as heuristic methods have been proposed for solving these problems. In this paper, a new simpli ed binary version of the artificial fish swarm algorithm is presented, where a point/ fish is represented by a binary string of 0/1 bits. Trial points are created by using crossover and mutation in the different fi sh behavior that are randomly selected by using two user de ned probability values. In order to make the points feasible the presented algorithm uses a random heuristic drop item procedure followed by an add item procedure aiming to increase the profit throughout the adding of more items in the knapsack. A cyclic reinitialization of 50% of the population, and a simple local search that allows the progress of a small percentage of points towards optimality and after that refines the best point in the population greatly improve the quality of the solutions. The presented method is tested on a set of benchmark instances and a comparison with other methods available in literature is shown. The comparison shows that the proposed method can be an alternative method for solving these problems.The authors wish to thank three anonymous referees for their comments and valuable suggestions to improve the paper. The first author acknowledges Ciˆencia 2007 of FCT (Foundation for Science and Technology) Portugal for the fellowship grant C2007-UMINHO-ALGORITMI-04. Financial support from FEDER COMPETE (Operational Programme Thematic Factors of Competitiveness) and FCT under project FCOMP-01-0124-FEDER-022674 is also acknowledged

Reversible Pulmonary Hypertension and Isolated Right-sided Heart Failure Associated with Hyperthyroidism

Hyperthyroidism may present with signs and symptoms related to dysfunction of a variety of organs. Cardiovascular pathology in hyperthyroidism is common. A few case reports describe isolated right heart failure, tricuspid regurgitation, and pulmonary hypertension as the prominent cardiovascular manifestations of hyperthyroidism. Although most textbooks do not mention hyperthyroidism as a cause of pulmonary hypertension and isolated right heart failure, the literature suggests that some hyperthyroid patients may develop reversible pulmonary hypertension and isolated right heart failure. We report a case of hyperthyroidism presenting with signs and symptoms of isolated right heart failure, tricuspid regurgitation, and pulmonary hypertension, which resolved with treatment of hyperthyroidism

ICBP90 belongs to a new family of proteins with an expression that is deregulated in cancer cells

International audienceICBP90 (Inverted CCAAT box Binding Protein of 90 kDa) is a recently identified nuclear protein that binds to one of the inverted CCAAT boxes of the topoisomerase IIalpha (TopoIIalpha) gene promoter. Here, we show that ICBP90 shares structural homology with several other proteins, including Np95, the human and mouse NIRF, suggesting the emergence of a new family of nuclear proteins. Towards elucidating the functions of this family, we analysed the expression of ICBP90 in various cancer or noncancer cell lines and in normal or breast carcinoma tissues. We found that cancer cell lines express higher levels of ICBP90 and TopoIIalpha than noncancer cell lines. By using cell-cycle phase-blocking drugs, we show that in primary cultured human lung fibroblasts, ICBP90 expression peaks at late G1 and during G2/M phases. In contrast, cancer cell lines such as HeLa, Jurkat and A549 show constant ICBP90 expression throughout the entire cell cycle. The effect of overexpression of E2F-1 is more efficient on ICBP90 and TopoIIalpha expression in noncancer cells (IMR90, WI38) than in cancer cells (U2OS, SaOs). Together, these results show that ICBP90 expression is altered in cancer cell lines and is upregulated by E2F-1 overexpression with an efficiency depending on the cancer status of the cell line