17 research outputs found

    Spatial distribution, work patterns, and perception towards malaria interventions among temporary mobile/migrant workers in artemisinin resistance containment zone

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    BACKGROUND: Mobile populations are at a high risk of malaria infection and suspected to carry and spread resistant parasites. The Myanmar National Malaria Control Programme focuses on preventive interventions and vector control measures for the temporary mobile/migrant workers in Myanmar Artemisinin Resistance Containment Zones. METHODS: A prospective cross-sectional study was conducted in 2012 in Kawthaung and Bokepyin townships of Tanintharyi Region, Myanmar, covering 192 mobile/migrant aggregates. The objectives were to identify the spatial distribution of the mobile/migrant populations, and to assess knowledge, attitudes, perceptions, and practices concerning malaria prevention and control, and their preferred methods of interventions. The structure of the192 migrant aggregates was investigated using a migrant mapping tool. Individual and household information was collected by structured interviews of 408 respondents from 39 aggregates, supplemented by 12 in-depth interviews of health care providers, authorities, volunteers, and employers. Data were analyzed by triangulating quantitative and qualitative data. RESULTS: The primary reasons for the limitation in access to formal health services for suspected malaria within 24 hours were identified to be scattered distribution of migrant aggregates, variable working hours and the lack of transportation. Only 19.6% of respondents reported working at night from dusk to dawn. Among study populations, 73% reported a perceived risk of contracting malaria and 60% reported to know how to confirm a suspected case of malaria. Moreover, only 15% was able to cite correct antimalarial drugs, and less than 10% believed that non-compliance with antimalarial treatment may be related to the risk of drug resistance. About 50% of study population reported to seeking health care from the public sector, and to sleep under ITNs/LLINs the night before the survey. There was a gap in willingness to buy ITNs/LLINs and affordability (88.5% vs. 60.2%) which may affect their sustained and consistent use. Only 32.4% across all aggregates realized the importance of community participation in effective malaria prevention and control. CONCLUSIONS: Community-based innovative approaches through strong collaboration and coordination of multi-stakeholders are desirable for relaying information on ITNs/LLINs, rapid diagnostic test, and artemisinin combination therapy and drug resistance successfully across the social and economic diversity of mobile/migrant aggregates in Myanmar

    Preparation and Characterization of TiO2 Electrospun Nano Fibres

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    Titanium dioxide nanofibres were fabricated by home-made horizontal and vertical experimental electrospinning set-ups. Electrospun titanium dioxide (TiO2) nanofibres were prepared by calcined titanium isopropoxide (TiP) and 2-Methoxyethanol (CH3OCH2CH2OH) with different molar ratios and it was formed on Al-foil substrate by different spinning time. TiO2 sol solution (Sol-gel) was characterized by TG-DTA, XRD and SEM analyses. SEM images revealed that Anatase TiO2 as-spun fibres on the Al foils were found to be between 120-250nm in diameters before and after calcinations with horizontal set-up for 30 minutes and vertical set-up for 40 minutes spinning time

    A Deep Learning Model Generation Framework for Virtualized Multi-Access Edge Cache Management

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    To reduce the network traffic and service delay in next-generation networks, popular contents (videos and music) are proposed to be temporarily stored in the cache located at the edge nodes such as base stations. The challenging issue in the caching process is to correctly predict the popular contents to store, since the more popular the contents, the more reduction in the network traffic and the service delay occurs. Furthermore, network virtualization proposes an existing cellular network to decouple into infrastructure providers (InPs) and mobile virtual network operators (MVNOs) to reduce capital and operation costs. In this architecture, MVNOs lease the physical resources (network capacity and cache storage) from InPs, the owner of the resources, to provide services to their users. On the one hand, if an MVNO leases more resources than necessary, they will be wasted. On the other hand, if an MVNO leases fewer resources than necessary, the traffic and service delay will increase. Our objective is to lease enough resources without going under or over the required amount and store the most popular contents. Thus, we propose a deep learning-based prediction scheme to intelligently manage the resource leasing and caching process to improve MVNO's profit. The main challenging issue in utilizing the deep-learning is searching for the problem specific best-suited prediction model. Hence, we also propose a reinforcement learning-based model searching scheme to find the best suited deep-learning model. We implement the prediction models using the Keras and Tensorflow libraries and the performance of the cache leasing and caching schemes are tested with a Python-based simulator. In terms of utility, simulation results present that the proposed scheme outperforms 46% compared with the randomized caching with optimal cache leasing scheme.</p

    Effectiveness and safety of 3 and 5 day courses of artemether–lumefantrine for the treatment of uncomplicated falciparum malaria in an area of emerging artemisinin resistance in Myanmar

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    Abstract Background Artemisinin resistance in Plasmodium falciparum has emerged and spread in Southeast Asia. In areas where resistance is established longer courses of artemisinin-based combination therapy have improved cure rates. Methods The standard 3-day course of artemether–lumefantrine (AL) was compared with an extended 5-day regimen for the treatment of uncomplicated falciparum malaria in Kayin state in South-East Myanmar, an area of emerging artemisinin resistance. Late parasite clearance dynamics were described by microscopy and quantitative ultra-sensitive PCR. Patients were followed up for 42 days. Results Of 154 patients recruited (105 adults and 49 children < 14 years) 78 were randomized to 3 days and 76 to 5 days AL. Mutations in the P. falciparum kelch13 propeller gene (k13) were found in 46% (70/152) of infections, with F446I the most prevalent propeller mutation (29%; 20/70). Both regimens were well-tolerated. Parasite clearance profiles were biphasic with a slower submicroscopic phase which was similar in k13 wild-type and mutant infections. The cure rates were 100% (70/70) and 97% (68/70) in the 3- and 5-day arms respectively. Genotyping of the two recurrences was unsuccessful. Conclusion Despite a high prevalence of k13 mutations, the current first-line treatment, AL, was still highly effective in this area of South-East Myanmar. The extended 5 day regimen was very well tolerated, and would be an option to prolong the useful therapeutic life of AL. Trial registration NCT02020330. Registered 24 December 2013, https://clinicaltrials.gov/NCT0202033

    Flexible parametric survival model of potential determinants for attrition among study population (N = 5,718).

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    <p>CI: Confidence interval; BMI: Body mass index; PI: Protease inhibitor; WHO definition of Anaemia: Haemoglobin concentration <12 g/dL in women and <13 g/dL in men.</p><p>#- not significant in univariate models.</p><p>Note: Early enrolment (1 Sep 2005 to 31 Dec 2009), and Late enrolment (1 Jan 2010 to 20 Oct 2011).</p><p>Flexible parametric survival model of potential determinants for attrition among study population (N = 5,718).</p

    Malaria elimination in remote communities requires integration of malaria control activities into general health care: an observational study and interrupted time series analysis in Myanmar

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    Abstract Background Community health workers (CHWs) can provide diagnosis and treatment of malaria in remote rural areas and are therefore key to the elimination of malaria. However, as incidence declines, uptake of their services could be compromised if they only treat malaria. Methods We conducted a retrospective analysis of 571,286 malaria rapid diagnostic tests conducted between 2011 and 2016 by 1335 CHWs supported by Medical Action Myanmar. We assessed rates of decline in Plasmodium falciparum and Plasmodium vivax incidence and rapid diagnostic test (RDT) positivity rates using negative binomial mixed effects models. We investigated whether broadening the CHW remit to provide a basic health care (BHC) package was associated with a change in malaria blood examination rates. Results Communities with CHWs providing malaria diagnosis and treatment experienced declines in P. falciparum and P. vivax malaria incidence of 70% (95% CI 66–73%) and 64% (59–68%) respectively each year of operation. RDT positivity rates declined similarly with declines of 70% (95% CI 66–73%) for P. falciparum and 65% (95% CI 61–69%) for P. vivax with each year of CHW operation. In four cohorts studied, adding a BHC package was associated with an immediate and sustained increase in blood examination rates (step-change rate ratios 2.3 (95% CI 2.0–2.6), 5.4 (95% CI 4.0–7.3), 1.7 (95% CI 1.4–2.1), and 1.1 (95% CI 1.0.1.3)). Conclusions CHWs have overseen dramatic declines in P. falciparum and P. vivax malaria in rural Myanmar. Expanding their remit to general health care has sustained community uptake of malaria services. In similar settings, expanding health services offered by CHWs beyond malaria testing and treatment can improve rural health care while ensuring continued progress towards the elimination of malaria

    Prevalence percentages and odds ratios for primary outcome (death or loss-to-follow-up) from the logistic regression analysis.

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    <p>OR: Odds ratio; CI: Confidence interval; BMI: Body mass index; SD: Standard deviation; PI: Protease inhibitor; Anaemia: Haemoglobin concentration <12 g/dL in women and <13 g/dL in men.</p><p>Prevalence percentages and odds ratios for primary outcome (death or loss-to-follow-up) from the logistic regression analysis.</p
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