4,489 research outputs found

    Assessing infrequent large earthquakes using geomorphology and geodesy in the Malawi Rift

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    In regions with large, mature fault systems, a characteristic earthquake model may be more appropriate for modelling earthquake occurrence than extrapolating from a short history of small, instrumentally observed earthquakes using the Gutenberg–Richter scaling law. We illustrate how the geomorphology and geodesy of the Malawi Rift, a region with large seismogenic thicknesses, long fault scarps, and slow strain rates, can be used to assess hazard probability levels for large infrequent earthquakes. We estimate potential earthquake size using fault length and recurrence intervals from plate motion velocities and generate a synthetic catalogue of events. Since it is not possible to determine from the geomorphological information if a future rupture will be continuous (7.4 ≤ M W ≤ 8.3 with recurrence intervals of 1,000–4,300 years) or segmented (6.7 ≤ M W ≤ 7.7 with 300–1,900 years), we consider both alternatives separately and also produce a mixed catalogue. We carry out a probabilistic seismic hazard assessment to produce regional- and site-specific hazard estimates. At all return periods and vibration periods, inclusion of fault-derived parameters increases the predicted spectral acceleration above the level predicted from the instrumental catalogue alone, with the most significant changes being in close proximity to the fault systems and the effect being more significant at longer vibration periods. Importantly, the results indicate that standard probabilistic seismic hazard analysis (PSHA) methods using short instrumental records alone tend to underestimate the seismic hazard, especially for the most damaging, extreme magnitude events. For many developing countries in Africa and elsewhere, which are experiencing rapid economic growth and urbanisation, seismic hazard assessments incorporating characteristic earthquake models are critical

    Semi-automatic selection of summary statistics for ABC model choice

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    A central statistical goal is to choose between alternative explanatory models of data. In many modern applications, such as population genetics, it is not possible to apply standard methods based on evaluating the likelihood functions of the models, as these are numerically intractable. Approximate Bayesian computation (ABC) is a commonly used alternative for such situations. ABC simulates data x for many parameter values under each model, which is compared to the observed data xobs. More weight is placed on models under which S(x) is close to S(xobs), where S maps data to a vector of summary statistics. Previous work has shown the choice of S is crucial to the efficiency and accuracy of ABC. This paper provides a method to select good summary statistics for model choice. It uses a preliminary step, simulating many x values from all models and fitting regressions to this with the model as response. The resulting model weight estimators are used as S in an ABC analysis. Theoretical results are given to justify this as approximating low dimensional sufficient statistics. A substantive application is presented: choosing between competing coalescent models of demographic growth for Campylobacter jejuni in New Zealand using multi-locus sequence typing data

    Boothe v. DOTD

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    Village health volunteers: key issues facing agencies in Malawi

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    In March 1991 the International Eye Foundation and Adventist Development Be Relief Agency conducted a workshop on village health volunteers, bringing together representatives from Malawibased non-governmental organizations, the Ministry of Health, and USAID. The participants discussed recruitment, training, rewards, retention, and roles of village health volunteers. This paper presents background data on village health volunteers in Malawi and elsewhere and reviews the key issues facing health care providers in working with village health volunteers. A copy of the workshop report can be obtained from IEF or ADRA

    Partition Function Zeros of a Restricted Potts Model on Lattice Strips and Effects of Boundary Conditions

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    We calculate the partition function Z(G,Q,v)Z(G,Q,v) of the QQ-state Potts model exactly for strips of the square and triangular lattices of various widths LyL_y and arbitrarily great lengths LxL_x, with a variety of boundary conditions, and with QQ and vv restricted to satisfy conditions corresponding to the ferromagnetic phase transition on the associated two-dimensional lattices. From these calculations, in the limit Lx→∞L_x \to \infty, we determine the continuous accumulation loci B{\cal B} of the partition function zeros in the vv and QQ planes. Strips of the honeycomb lattice are also considered. We discuss some general features of these loci.Comment: 12 pages, 12 figure

    Evaluation of In-Hospital Management for Febrile Illness\ud in Northern Tanzania before and after 2010 World Health\ud Organization Guidelines for the Treatment of Malaria

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    In 2010, the World Health Organization (WHO) published updated guidelines emphasizing and expanding recommendations for a parasitological confirmation of malaria before treating with antimalarials. This study aimed to assess differences in historic (2007–2008) (cohort 1) and recent (2011–2012) (cohort 2) hospital cohorts in the diagnosis and treatment of febrile illness in a low malaria prevalence area of northern Tanzania. We analyzed data from two prospective cohort studies that enrolled febrile adolescents and adults aged $13 years. All patients received quality-controlled aerobic blood cultures and malaria smears. We compared patients’ discharge diagnoses, treatments, and outcomes to assess changes in the treatment of malaria and bacterial infections. In total, 595 febrile inpatients were enrolled from two referral hospitals in Moshi, Tanzania. Laboratory-confirmed malaria was detected in 13 (3.2%) of 402 patients in cohort 1 and 1 (0.5%) of 193 patients in cohort 2 (p = 0.041). Antimalarials were prescribed to 201 (51.7%) of 389 smear-negative patients in cohort 1 and 97 (50.5%) of 192 smearnegative patients in cohort 2 (p = 0.794). Bacteremia was diagnosed from standard blood culture in 58 (14.5%) of 401 patients in cohort 1 compared to 18 (9.5%) of 190 patients in cohort 2 (p = 0.091). In cohort 1, 40 (69.0%) of 58 patients with a positive blood culture received antibacterials compared to 16 (88.9%) of 18 patients in cohort 2 (p = 0.094). In cohort 1, 43 (10.8%) of the 399 patients with known outcomes died during hospitalization compared with 12 (6.2%) deaths among 193 patients in cohort 2 (p = 0.073). In a setting of low malaria transmission, a high proportion of smear-negative patients were diagnosed with malaria and treated with antimalarials despite updated WHO guidelines on malaria treatment. Improved laboratory diagnostics for non-malaria febrile illness might help to curb this practice.\u
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