Serum troponin is often elevated in patients with acute stroke and its mechanism is unknown. In a retrospective single-center cohort study, we evaluated the association between stroke severity and serum troponin in 187 patients with acute stroke using multivariable modified Poisson models. A one-point increase in the National Institutes of Health Stroke Scale (measure of stroke severity) was associated with a marginally higher serum troponin level in adjusted models (aIRR 1.03; 1.01–1.05, P = 0.001). The modest, yet potentially independent, association between stroke severity and serum troponins could suggest a neurogenic basis for a cardiac injury in patients with acute stroke.

Actuarial risk classification studies are typically confined to univariate, policy-based analyses: Individual claim frequencies are modelled for a single product, without accounting for the interactions between the different coverages bought by the members of the same household. Now that large amounts of data are available and that the customer's value is at the heart of insurers' strategies, it becomes essential to develop multivariate risk models combining all the products subscribed by the members of the household in order to capture the correlation effects. This paper aims to supplement the standard actuarial policy-based approach with a household-based approach. This makes the actuarial model more complex but also increases the volume of available information which eases and refines forecasting. Possible cross-selling opportunities can also be identified.

Spatial distribution of broadleaf weeds within 14 North Carolina soybean fields was characterized by fitting negative binomial distributions to frequency distributions of weed counts in each field. In most cases, the data could be represented by a negative binomial distribution. Estimated values of the parameter K of this distribution were small, often less than one, indicating a high degree of patchiness. The data also indicated that the population as a whole was patchy. Counts of individual species were positively correlated with each other in some fields and total weed count could be represented by a negative binomial for 12 of the 14 fields.

Field experiments were conducted in 1992 and 1993 to characterize the weed seed bank, to determine the influence of moldboard plowing and secondary soil disturbance on the emergence pattern of weeds, and to measure weed seed bank depletion by emergence in a long-term moldboard plow corn cropping system. Viable seeds of common lambsquarters, redroot pigweed, and each of 10 other species accounted for about 85, about 9, and less than 1%, respectively, of the total weed species in the seed bank. A negative binomial distribution described the spatial distribution of viable seeds of 10 species, but not of common lambsquarters or of redroot pigweed. Decreased density of seeds among species was associated with increased aggregation. Secondary soil disturbance increased the rate and magnitude of common lambs quarters emergence in 1992 but did not influence emergence in 1993. Secondary soil disturbance did not influence the magnitude and rate of emergence of redroot pigweed or velvetleaf. Whereas cumulative growing degree days from April through July were similar between years, the amount of rainfall was about 50% less in 1992 than in 1993. Secondary soil disturbance may have increased common lambsquarters emergence by increasing the availability of soil moisture and improving conditions for seed germination during the dry year. Even though seed bank depletion by seedling emergence was relatively low for all species, secondary soil disturbance in creased seed bank depletion of common lambsquarters and redroot pigweed about 7- and 3-fold, respectively, in 1992. Seasonal variation in the amount of rainfall may have influenced the effect of soil disturbance on emergence and seed bank depletion of common lambsquarters, which is the most abundant species in the weed community.

The influence of secondary soil disturbance on the emergence pattern and seed bank depletion of an annual weed community in a long-term, no-tillage corn cropping system was determined in 1992 and 1993. As a component of this research, the seed bank was characterized prior to implementation of soil disturbance treatments. The seed bank was initially composed of common lambsquarters, redroot pigweed, and giant foxtail, with approximately 55, 36, and 8% of the total viable seeds, respectively. The remaining 1% was comprised of five other species in 1992 and eight in 1993. The spatial distribution of viable seeds of each species, except common lambsquarters and redroot pigweed, was described by a negative binomial distribution. Three dispersion indices indicated that seeds of individual and total weed species were aggregated and that the level of aggregation of viable seeds of a species was associated with seed density; at lower seed densities, the level of aggregation was greater. Soil disturbance increased common lambsquarters emergence 6-fold in 1992 relative to nondisturbed soil, but did not influence emergence in 1993. Rainfall was about 50% less in 1993. In contrast, soil disturbance increased giant foxtail and redroot pigweed emergence approximately 6- and 3-fold in 1992 and 1993, respectively. Seedling emergence associated with soil disturbance, relative to nondisturbed soil, increased seed bank depletion of common lambsquarters 16-fold in 1992, and giant foxtail and redroot pigweed and average of 6- and 3-fold in 1992 and 1993, respectively. These results indicated that soil disturbance increased seedling emergence and seed bank depletion of the predominant species in the weed community of a long-term, no-tillage system, but that this response was dependent on rainfall for common lambsquarters.

Three methods of predicting the impact of weed interference on crop yield and expected economic return were compared to evaluate the economic importance of weed spatial heterogeneity. Density of three weed species was obtained using a grid sampling scheme in 11 corn and 11 soybean fields. Crop yield loss was predicted assuming densities were homogeneous, aggregated following a negative binomial with known population mean and k, or aggregated with weed densities spatially mapped. Predicted crop loss was lowest and expected returns highest when spatial location of weed density was utilized to decide whether control was justified. Location-specific weed management resulted in economic gain as well as a reduction in the quantity of herbicide applied.

Malaria and leishmaniasis are among the two most important health problems of many developing countries especially in the Middle East and North Africa. It is common for vector-borne infectious diseases to have similar hotspots which may be attributed to the overlapping ecological distribution of the vector. Hotspot analyses were conducted to simultaneously detect the location of local hotspots and test their statistical significance. Spatial scan statistics were used to detect and test hotspots of malaria and cutaneous leishmaniasis (CL) in Afghanistan in 2009. A multivariate negative binomial model was used to simultaneously assess the effects of environmental variables on malaria and CL. In addition to the dependency between malaria and CL disease counts, spatial and temporal information were also incorporated in the model. Results indicated that malaria and CL incidence peaked at the same periods. Two hotspots were detected for malaria and three for CL. The findings in the current study show an association between the incidence of malaria and CL in the studied areas of Afghanistan. The incidence of CL disease in a given month is linked with the incidence of malaria in the previous month. Co-existence of malaria and CL within the same geographical area was supported by this study, highlighting the presence and effects of environmental variables such as temperature and precipitation. People living in areas with malaria are at increased risk for leishmaniasis infection. Local healthcare authorities should consider the co-infection problem by recommending systematic malaria screening for all CL patients.

This paper explores the influence of demographic and spatial variables on individual participation and consumption of wildland area recreation. Data from the National Survey on Recreation and the Environment are combined with geographical information system-based distance measures to develop nonlinear regression models used to predict both participation and the number of days of participation in wilderness and primitive area recreation. The estimated models corroborate previous findings indicating that race (black), ethnicity (Hispanic), immigrant status, age, and urban dwelling are negatively correlated with wildland visitation, while income, gender (male), and education positively affect wild-land recreation participation and use. The presence of a distance or proximity factor mitigates some of the influence of race and ethnicity. The results of the cross-sectional models are combined with U.S. Census projections of total population, changes in population characteristics, and estimates of current National Forest Wilderness visitation estimates to give some insight into pressure that might be expected on the nation's designated wilderness during the next half century. Results generally indicate that per-capita participation and visitation rates will decline over time as society changes. Total wilderness participation and visitation will, however, increase, but at a rate less than population growth.

In this paper we consider point processes Nf (t), t > 0, with independent increments and integer-valued jumps whose distribution is expressed in terms of Bernštein functions f with Lévy measure v. We obtain the general expression of the probability generating functions Gf of Nf, the equations governing the state probabilities pkf of Nf, and their corresponding explicit forms. We also give the distribution of the first-passage times Tkf of Nf, and the related governing equation. We study in detail the cases of the fractional Poisson process, the relativistic Poisson process, and the gamma-Poisson process whose state probabilities have the form of a negative binomial. The distribution of the times of jumps with height lj () under the condition N(t) = k for all these special processes is investigated in detail.

We discuss a class of counting distributions motivated by a problem in discrete surplus analysis, and special cases of which have applications in stop-loss, discrete Tail value at risk (TVaR) and claim count modelling. Explicit formulas are developed, and the mixed Poisson case is considered in some detail. Simplifications occur for some underlying negative binomial and related models, where in some cases compound geometric distributions arise naturally. Applications to claim count and aggregate claims models are then given.

This study quantifies the rate and intensity of re-infection with human hookworm and Schistosoma mansoni infection 12 months following successful treatment, and investigates the influence of socio-economic, geographical and environmental factors. A longitudinal study of 642 individuals aged over 5 years was conducted in Minas Gerais State, Brazil from June 2004 to March 2006. Risk factors were assessed using interval censored regression for the rate and negative binomial regression for intensity. The crude rate and intensity of hookworm re-infection was 0·21 per year (95% confidence interval (CI) 0·15–0·29) and 70·9 epg (95% CI 47·2–106·6). For S. mansoni the rate was 0·06 per year (95% CI 0·03–0·10) and intensity 6·51 epg (95% CI 3·82–11·11). Rate and intensity of re-infection with hookworm were highest among males and positively associated with previous infection status, absence of a toilet and house structure. Rate and intensity of S. mansoni re-infection were associated with previous infection status as well as geographical, environmental and socio-economic factors. The implications of findings for the design of anti-helminth vaccine trials are discussed.

The spatial distribution of Bactrocera fruit flies in the Goa region (west coast of India) was studied using several dispersion parameters between April 2006 and March 2008 in three ecological zones, viz. coastal, midland and upland. These zones are 10, 25 and 50 km to the east from the coastline of the Arabian Sea at an elevation of 15, 70 and 100 m above mean sea level, respectively. The dispersion parameters revealed that the population of all the fruit fly species attracted to methyl eugenol-baited traps, viz. Bactrocera dorsalis, Bactrocera caryeae, Bactrocera zonata, Bactrocera affinis and Bactrocera correcta, followed the negative binomial distribution pattern and was highly aggregated or clumped.