Routes of Hendra Virus Excretion in Naturally-Infected Flying-Foxes: Implications for Viral Transmission and Spillover Risk

Pteropid bats or flying-foxes (Chiroptera: Pteropodidae) are the natural host of Hendra virus (HeV) which sporadically causes fatal disease in horses and humans in eastern Australia. While there is strong evidence that urine is an important infectious medium that likely drives bat to bat transmission and bat to horse transmission, there is uncertainty about the relative importance of alternative routes of excretion such as nasal and oral secretions, and faeces. Identifying the potential routes of HeV excretion in flying-foxes is important to effectively mitigate equine exposure risk at the bat-horse interface, and in determining transmission rates in host-pathogen models. The aim of this study was to identify the major routes of HeV excretion in naturally infected flying-foxes, and secondarily, to identify between-species variation in excretion prevalence. A total of 2840 flying-foxes from three of the four Australian mainland species (Pteropus alecto, P. poliocephalus and P. scapulatus) were captured and sampled at multiple roost locations in the eastern states of Queensland and New South Wales between 2012 and 2014. A range of biological samples (urine and serum, and urogenital, nasal, oral and rectal swabs) were collected from anaesthetized bats, and tested for HeV RNA using a qRT-PCR assay targeting the M gene. Forty-two P. alecto (n = 1410) had HeV RNA detected in at least one sample, and yielded a total of 78 positive samples, at an overall detection rate of 1.76% across all samples tested in this species (78/4436). The rate of detection, and the amount of viral RNA, was highest in urine samples (>serum, packed haemocytes >faecal >nasal >oral), identifying urine as the most plausible source of infection for flying-foxes and for horses. Detection in a urine sample was more efficient than detection in urogenital swabs, identifying the former as the preferred diagnostic sample. The detection of HeV RNA in serum is consistent with haematogenous spread, and with hypothesised latency and recrudesence in flying-foxes. There were no detections in P. poliocephalus (n = 1168 animals; n = 2958 samples) or P. scapulatus (n = 262 animals; n = 985 samples), suggesting (consistent with other recent studies) that these species are epidemiologically less important than P. alecto in HeV infection dynamics. The study is unprecedented in terms of the individual animal approach, the large sample size, and the use of a molecular assay to directly determine infection status. These features provide a high level of confidence in the veracity of our findings, and a sound basis from which to more precisely target equine risk mitigation strategies.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

Using Big Data to manage safety-related risk in the upstream oil and gas industry: A research agenda

Despite considerable effort and a broad range of new approaches to safety management over the years, the upstream oil & gas industry has been frustrated by the sector’s stubbornly high rate of injuries and fatalities. This short communication points out, however, that the industry may be in a position to make considerable progress by applying “Big Data” analytical tools to the large volumes of safety-related data that have been collected by these organizations. Toward making this case, we examine existing safety-related information management practices in the upstream oil & gas industry, and specifically note that data in this sector often tends to be highly customized, difficult to analyze using conventional quantitative tools, and frequently ignored. We then contend that the application of new Big Data kinds of analytical techniques could potentially reveal patterns and trends that have been hidden or unknown thus far, and argue that these tools could help the upstream oil & gas sector to improve its injury and fatality statistics. Finally, we offer a research agenda toward accelerating the rate at which Big Data and new analytical capabilities could play a material role in helping the industry to improve its health and safety performance.

Natural Hendra Virus Infection in Flying-Foxes - Tissue Tropism and Risk Factors

Hendra virus (HeV) is a lethal zoonotic agent that emerged in 1994 in Australia. Pteropid bats (flying-foxes) are the natural reservoir. To date, HeV has spilled over from flying-foxes to horses on 51 known occasions, and from infected horses to close-contact humans on seven occasions. We undertook screening of archived bat tissues for HeV by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Tissues were tested from 310 bats including 295 Pteropodiformes and 15 Vespertilioniformes. HeV was detected in 20 individual flying-foxes (6.4%) from various tissues including spleen, kidney, liver, lung, placenta and blood components. Detection was significantly higher in Pteropus Alecto and Pconspicillatus, identifying species as a risk factor for infection. Further, our findings indicate that HeV has a predilection for the spleen, suggesting this organ plays an important role in HeV infection. The lack of detections in the foetal tissues of HeV-positive females suggests that vertical transmission is not a regular mode of transmission in naturally infected flying-foxes, and that placental and foetal tissues are not a major source of infection for horses. A better understanding of HeV tissue tropism will strengthen management of the risk of spillover from flying-foxes to horses and ultimately humans.

Open-pit block sequencing optimization: A mathematical model and solution technique

This study presents a comprehensive mathematical formulation model for a short-term open-pit mine block sequencing problem, which considers nearly all relevant technical aspects in open-pit mining. The proposed model aims to obtain the optimum extraction sequences of the original-size (smallest) blocks over short time intervals and in the presence of real-life constraints, including precedence relationship, machine capacity, grade requirements, processing demands and stockpile management. A hybrid branch-and-bound and simulated annealing algorithm is developed to solve the problem. Computational experiments show that the proposed methodology is a promising way to provide quantitative recommendations for mine planning and scheduling engineers.

Evaluation of tomato production systems at Bowen in mitigating the risk of fruit fly infestation: a systems approach for market access

Queensland fruit flies Bactrocera tryoni and B. neohumeralis are considered major quarantine pests of tomato, a major crop in the horticultural production district around Bowen, North Queensland, Australia. Preharvest and/or postharvest treatments are required to meet the market access requirements of both domestic and international trading partners. The suspension from use of dimethoate and fenthion, the two insecticides used for fruit fly control, has resulted in the loss of both pre and postharvest uses in fresh tomato. Research undertaken quantitatively at Bowen evaluated the effectiveness of pre-harvest production systems without specific fruit fly controls and postharvest mitigation measures in reducing the risk of fruit fly infestation in tomato. A district-wide trapping using cue-lure baited traps was undertaken to determine fruit fly seasonal patterns in relation to the cropping seasons. A total of 17,626 field-harvested and 11,755 pack-house tomatoes were sampled from ten farms over three cropping seasons (2006-2009). The fruit were incubated and examined for fruit fly infestation. No fruit fly infested fruit were recorded over the three seasons in either the field or the pack-house samples. Statistical analyses showed that upper infestation levels were extremely low (between 0.025 and 0.062%) at the 95% confidence level. The trap catches showed a seasonal pattern in fruit fly activity, with low numbers during the autumn and winter months, rising slightly in spring and peaking in summer. This seasonal pattern was similar over the four seasons. The main two species of fruit fly caught were B. tryoni and B. neohumeralis. Based on the results, it is clear that the risk of fruit fly infestation is extremely low under the current production systems in the Bowen region.

Ambient temperature and risk of cardiovascular hospitalization: An updated systematic review and meta-analysis

The association between temperatures and risk of cardiovascular mortality has been recognized but the association drawn from previous meta-analysis was weak due to the lack of sufficient studies. This paper presented a review with updated reports in the literature about the risk of cardiovascular hospitalization in relation to different temperature exposures and examined the dose–response relationship of temperature-cardiovascular hospitalization by change in units of temperature, latitudes, and lag days. The pooled effect sizes were calculated for cold, heat, heatwave, and diurnal variation using random-effects meta-analysis, and the dose–response relationship of temperature-cardiovascular admission was modelled using random-effect meta-regression. The Cochrane Q-test and index of heterogeneity (I2) were used to evaluate heterogeneity, and Egger's test was used to evaluate publication bias. Sixty-four studies were included in meta-analysis. The pooled results suggest that for a change in temperature condition, the risk of cardiovascular hospitalization increased 2.8% (RR, 1.028; 95% CI, 1.021–1.035) for cold exposure, 2.2% (RR, 1.022; 95% CI, 1.006–1.039) for heatwave exposure, and 0.7% (RR, 1.007; 95% CI, 1.002–1.012) for an increase in diurnal temperature. However no association was observed for heat exposure. The significant dose–response relationship of temperature — cardiovascular admission was found with cold exposure and diurnal temperature. Increase in one-day lag caused a marginal reduction in risk of cardiovascular hospitalizations for cold exposure and diurnal variation, and increase in latitude was associated with a decrease in risk of cardiovascular hospitalizations for diurnal temperature only. There is a significant short-term effect of cold exposure, heatwave and diurnal variation on cardiovascular hospitalizations. Further research is needed to understand the temperature-cardiovascular relationship for different climate areas.