126 research outputs found

    Forty-four years of land use changes in a Sardinian cork oak agro-silvopastoral system: a qualitative analysis

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    The island of Sardinia is the biggest producer of natural cork in Italy. In this study, cork oak cover change is investigated in a typical agro-silvopastoral system where the main activities are cereal fodder and wheat cultivation, sheep rearing and cork exploitation. The research method is based on the comparison of two land use maps produced by photo-interpretation of digitised aerial photographs taken in 1954 and 1998, combined with interviews with local farmers, field surveys, and data collected from literature, administrative documentation and decadal censuses (at council level). The results show that the cork oak woodland surface decreased (-29%). It was substituted by other forest, ploughed land, and mixed grassland and shrubland. Apart from the transformation of the cork oak woodland to other forest, other changes have happened probably because of an increase in agricultural and pastoral activities as described by the documental material available for the same area

    Performance di recenti imboschimenti con quercia da sughero in ex-coltivi

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    Growth performance of cork oak plantations recently established on farmlands in Sardinia, Italy. Recently, significant forestry activities have taken place in Sardinia thanks to EU Regulation 2080/92 funds. Some 80% of the afforestated surface has been planted with holm oak and cork oak. The latter also characterizes 89% of the reforestation area. Given the funding source, plantations have been established on farmlands. Growth performances of these recent cork oak stands have been quantitatively evaluated and compared with the performances of two experimental plots. In Gallura (north-east of Sardinia), that is the traditional cork production area and still is economically the most important cork district of the island, these new cork oak plantations have an average size of 28 ha. They have been established on lands that, before plantation, were either pastures (30%) or arable lands (70%). Plantation failures are limited to 8.8% of the total (in term of mass) and seem independent of environmental factors or plantations species composition (conifers have been frequently used as secondary species). Average growth of the stem, measured above cork at collar height, is in the range 4 to 8mm/year with a mean value of 5.5mm/year. No correlation appears with either environmental conditions or species composition of the plantations. In the first experimental plot, soil management practices (natural vegetation removal vs its cutting and mulching) does not differentiate young plants growth trends. In the control subplots (no removal) stem collar diameter is 20% smaller. Localized manual hoeing around trunk base increased the diameters by 13% but reduced cork thickness by 21%. The second experimental plot allows comparisons among 27 Mediterranean proveniences of cork oak. The trial exhibits reduced genetic influence: diameters and heights growth are significantly different only among extreme groups. In conclusion, reduced growth performances of the plantations established in farmlands is due, to some extent, to the limitations inherent with private land management (constrained to costs minimization) and, on the other hand, to the generally very limited thickness of Gallura soils. Demand for good quality commercial cork is steadily raising. To sustain the request, in the short term, it would be necessary to extend financial support for plantations care, from 5 to 10 years, or even up to the first stripping (virgin cork)

    A geostatistical analysis of the association between armed conflicts and P. falciparum malaria in Africa 1997-2010

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    Background The absence of conflict in a country has been cited as a crucial factor affecting the operational feasibility of achieving malaria control and elimination, yet mixed evidence exists on the influence that conflicts have had on malaria transmission. Over the past two decades, Africa has seen substantial numbers of armed conflicts of varying length and scale, creating conditions that can disrupt control efforts and impact malaria transmission. However, very few studies have quantitatively assessed the associations between conflicts and malaria transmission, particularly in a consistent way across multiple countries. Methods In this analysis an explicit geostatistical, autoregressive, mixed model is employed to quantitatively assess the association between conflicts and variations in Plasmodium falciparum parasite prevalence across a 13-year period in sub-Saharan Africa. Results Analyses of geolocated, malaria prevalence survey variations against armed conflict data in general showed a wide, but short-lived impact of conflict events geographically. The number of countries with decreased P. falciparum parasite prevalence (17) is larger than the number of countries with increased transmission (12), and notably, some of the countries with the highest transmission pre-conflict were still found with lower transmission post-conflict. For four countries, there were no significant changes in parasite prevalence. Finally, distance from conflicts, duration of conflicts, violence of conflict, and number of conflicts were significant components in the model explaining the changes in P. falciparum parasite rate. Conclusions The results suggest that the maintenance of intervention coverage and provision of healthcare in conflict situations to protect vulnerable populations can maintain gains in even the most difficult of circumstances, and that conflict does not represent a substantial barrier to elimination goals

    Development and deployment of an improved Anopheles gambiae s.l. field surveillance by adaptive spatial sampling design

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    Introduction: Accurate assessments of vector occurrence and abundance, particularly in widespread vector-borne diseases such as malaria, are crucial for the efficient deployment of disease surveillance and control interventions. Although previous studies have explored the benefits of adaptive sampling for identifying disease hotspots (mostly through simulations), limited research has been conducted on field surveillance of malaria vectors. Methods: We developed and implemented an adaptive spatial sampling design in southwestern Benin, specifically targeting potential and uncertain Anopheles gambiae hotspots, a major malaria vector in sub-Saharan Africa. The first phase of our proposed design involved delineating ecological zones and employing a proportional lattice with close pairs sampling design to maximize spatial coverage, representativeness of ecological zones, and account for spatial dependence in mosquito counts. In the second phase, we employed a spatial adaptive sampling design focusing on high-risk areas with the greatest uncertainty. Results: The adaptive spatial sampling design resulted in a reduced sample size from the first phase, leading to improved predictions for both out-of-sample and training data. Collections of Anopheles gambiae in high-risk and low-uncertainty areas were nearly tripled compared to those in high-risk and high-uncertainty areas. However, the overall model uncertainty increased. Discussion: While the adaptive sampling design allowed for increased collections of Anopheles gambiae mosquitoes with a reduced sample size, it also led to a general increase in uncertainty, highlighting the potential trade-offs in multi-criteria adaptive sampling designs. It is imperative that future research focuses on understanding these trade-offs to expedite effective malaria control and elimination efforts

    Nontuberculous mycobacterial disease in children :epidemiology, diagnosis and management at a tertiary center

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    Background There are limited data on the epidemiology, diagnosis and optimal management of nontuberculous mycobacterial (NTM) disease in children. Methods Retrospective cohort study of NTM cases over a 10-year-period at a tertiary referral hospital in Australia. Results A total of 140 children with NTM disease, including 107 with lymphadenitis and 25 with skin and soft tissue infections (SSTIs), were identified. The estimated incidence of NTM disease was 0.6–1.6 cases / 100,000 children / year; no increasing trend was observed over the study period. Temporal analyses revealed a seasonal incidence cycle around 12 months, with peaks in late winter/spring and troughs in autumn. Mycobacterium-avium-complex accounted for most cases (77.8%), followed by Mycobacterium ulcerans (14.4%) and Mycobacterium marinum (3.3%). Polymerase chain reaction testing had higher sensitivity than culture and microscopy for acid-fast bacilli (92.0%, 67.2% and 35.7%, respectively). The majority of lymphadenitis cases underwent surgical excision (97.2%); multiple recurrences in this group were less common in cases treated with clarithromycin and rifampicin compared with clarithromycin alone or no anti-mycobacterial drugs (0% versus 7.1%; OR:0.73). SSTI recurrences were also less common in cases treated with two anti-mycobacterial drugs compared with one or none (10.5% versus 33.3%; OR:0.23). Conclusions There was seasonal variation in the incidence of NTM disease, analogous to recently published observations in tuberculosis, which have been linked to seasonal variation in vitamin D. Our finding that anti-mycobacterial combination therapy was associated with a reduced risk of recurrences in patients with NTM lymphadenitis or SSTI requires further confirmation in prospective trials

    Joint spatial modelling of malaria incidence and vector's abundance shows heterogeneity in malaria‐vector geographical relationships

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    Limited attention from the modelling community has been given to ecological approaches which aim to predict geographical patterns of malaria by accounting for the joint effects of different vectors and environmental drivers. A hierarchical multivariate joint spatial Gaussian generalised linear model was developed to provide joint parameters inference and mapping of counts of Anopheles gambiae, An. funestus, An. nili and malaria incidence collected in an area of Cote d'Ivoire. Variable‐selection methods were applied to select important predictors for each mosquito species and malaria incidence. The proposed joint model led to a general reduction of the variance in the estimates compared to independent modelling. There was high variability in the composition of Anopheles mosquito species in the villages with each species suitability only partly overlapping geographically. Abundances of An. gambiae, An. funestus and An. nili were primarily determined by temperature. None of the species were found as a significant predictor for the others. Anopheles gambiae was the predominant species and only An. gambiae female abundance was an important variable (linear predictor) for malaria incidence. However, the geographic correlation analyses show that the rest of Anopheles species are likely playing a role in malaria suitability. Residuals from the models of mosquito abundance and malaria cases are also correlated with each other and overlapping but in geographic patches, meaning that local drivers of vector‐malaria suitability are still present and not represented by the predictors used in the model. Synthesis and applications: Joint modelling improve predictive estimation compared to individual modelling. The accurate predictions highlighted high diversity in the association between malaria and vector species, with most of the area having more than one species suitability correlated with malaria suitability. These zones are unlikely to benefit from species‐specific interventions. Areas with correlated malaria and vector species suitability residuals contain local information, not included in the model, that requires further investigation. This will identify additional communal malaria and vectors factors that need to be considered for optimal malaria control and elimination strategies since these factors are expected to be linked to the local malaria transmission

    Education and Socio‑economic status are key factors influencing use of insecticides and malaria knowledge in rural farmers in Southern Cîte d’Ivoire

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    Background Insecticides play a key role in rural farming; however, their over- or misuse has been linked with a negative impact on malaria vector control policies. This study was conducted amongst agricultural communities in Southern Cîte d’Ivoire to identify which insecticides are used by local farmers and how it relates to the perception of farmers on malaria. Understanding the use of insecticides may help in designing awareness programme on mosquito control and pesticides management. Methods A questionnaire was administered to 1399 farming households across ten villages. Farmers were interviewed on their education, farming practices (e.g. crops cultivated, insecticides use), perception of malaria, and the different domestic strategies of mosquito control they use. Based on some pre-defined household assets, the socioeconomic status (SES) of each household was estimated. Statistical associations were calculated between different variables, showing significant risk factors. Results The educational level of farmers was significantly associated with their SES (p < 0.0001). Most of the householders (88.82%) identified mosquitoes as the principal cause of malaria, with good knowledge of malaria resulting as positively related to high educational level (OR = 2.04; 95%CI: 1.35, 3.10). The use of indoor chemical compounds was strongly associated to the SES of the households, their education level, their use of ITNs and insecticide in agricultural (p < 0.0001). Indoor application of pyrethroid insecticides was found to be widespread among farmers as well as the use of such insecticide for crops protection. Conclusion Our study shows that the education level remains the key factor influencing the use of insecticides by farmers and their awareness of malaria control. We suggest that better communication tailored to education level and including SES, controlled availability and access to chemical products, should be considered when designing campaigns on use of pesticides and vector borne disease control for local communities

    Rapid mechanosensitive migration and dispersal of newly divided mesenchymal cells aid their recruitment into dermal condensates

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    Embryonic mesenchymal cells are dispersed within an extracellular matrix but can coalesce to form condensates with key developmental roles. Cells within condensates undergo fate and morphological changes and induce cell fate changes in nearby epithelia to produce structures including hair follicles, feathers, or intestinal villi. Here, by imaging mouse and chicken embryonic skin, we find that mesenchymal cells undergo much of their dispersal in early interphase, in a stereotyped process of displacement driven by 3 hours of rapid and persistent migration followed by a long period of low motility. The cell division plane and the elevated migration speed and persistence of newly born mesenchymal cells are mechanosensitive, aligning with tissue tension, and are reliant on active WNT secretion. This behaviour disperses mesenchymal cells and allows daughters of recent divisions to travel long distances to enter dermal condensates, demonstrating an unanticipated effect of cell cycle subphase on core mesenchymal behaviour

    Bluetongue risk map for vaccination and surveillance strategies in India

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    Bluetongue virus (BTV, Sedoreoviridae: Orbivirus) causes an economically important disease, namely, bluetongue (BT), in domestic and wild ruminants worldwide. BTV is endemic to South India and has occurred with varying severity every year since the virus was first reported in 1963. BT can cause high morbidity and mortality to sheep flocks in this region, resulting in serious economic losses to subsistence farmers, with impacts on food security. The epidemiology of BTV in South India is complex, characterized by an unusually wide diversity of susceptible ruminant hosts, multiple vector species biting midges (Culicoides spp., Diptera: Ceratopogonidae), which have been implicated in the transmission of BTV and numerous co-circulating virus serotypes and strains. BT presence data (1997–2011) for South India were obtained from multiple sources to develop a presence/absence model for the disease. A non-linear discriminant analysis (NLDA) was carried out using temporal Fourier transformed variables that were remotely sensed as potential predictors of BT distribution. Predictive performance was then characterized using a range of different accuracy statistics (sensitivity, specificity, and Kappa). The top ten variables selected to explain BT distribution were primarily thermal metrics (land surface temperature, i.e., LST, and middle infrared, i.e., MIR) and a measure of plant photosynthetic activity (the Normalized Difference Vegetation Index, i.e., NDVI). A model that used pseudo-absence points, with three presence and absence clusters each, outperformed the model that used only the recorded absence points and showed high correspondence with past BTV outbreaks. The resulting risk maps may be suitable for informing disease managers concerned with vaccination, prevention, and control of BT in high-risk areas and for planning future state-wide vector and virus surveillance activities
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