Flesh, Blood, Sex and Consumption: Applied Epidemiology in Victoria

In this thesis I present the key projects and activities that I completed as part of the Australian National University's Master of Philosophy in Applied Epidemiology (MAE) program during 2018-2019. During this time I was based in the Communicable Disease Epidemiology and Surveillance (CDES) unit at the Victorian Department of Health and Human Services (DHHS), and the Surveillance and Evaluation section of the Burnet Institute in Melbourne, Victoria. I completed four major projects across these two organisations, as well as being involved with a range of other infectious disease surveillance and research activities. At DHHS, I investigated a cluster of tuberculosis cases in a cultural community. This three-year investigation was one of the largest tuberculosis cluster investigations ever undertaken by the Department of Health and Human Services and the Victorian Tuberculosis Program. The epidemiological side of the investigation in which I was involved utilised epidemiological, social-location and genomic data to better understand transmission within the cluster. I also conducted an epidemiological study of delays in patient presentation and diagnosis for Buruli ulcer in Victoria. Given the current lack of effective interventions to reduce disease transmission in Victoria, prompt diagnosis and treatment are critical to minimise the impact of the disease. The study aimed to characterise and identify factors influencing presentation and diagnosis delays in patients notified to DHHS between 2011 and 2017 to better inform public health messaging for the public and medical practitioners. The study was published in the Tropical Medicine and Infectious Diseases journal in July 2019. At the Burnet Institute I completed a program evaluation of the ACCESS project, a sentinel surveillance system for STIs and BBVs that was funded by the Australian Government Department of Health to expand nationally during 2016-2019. Based on the outcomes of the evaluation, I made several recommendations to improve the operation of the ACCESS project during the next potential funding period. My data analysis project at the Burnet Institute examined the epidemiology and subtype diversity of HIV-1 in newly-arrived Asian-born and Australian-born men who have sex with men (MSM) populations using routinely-collected surveillance and subtyping data. Understanding and addressing HIV transmission in the newly-arrived Asian-born MSM population is increasingly important in Victoria, with both the population and the proportion of HIV notifications from the population increasing in recent years. The appendices to the thesis include summaries of other program requirements outside these four main projects. I developed public health communications materials for a non-scientific audience in the form of participant information for the NHMRC-funded Beating Buruli in Victoria case-control study. I completed three teaching activities; a lecture on data visualisation, a session on the basics of social network analysis for infectious diseases, and a "lesson from the field" on tuberculosis cluster and outbreak investigations. Finally, I present a short summary of my involvement as a team leader in the SaMELFS Samoa mosquito survey and molecular xenomonitoring study, for which I travelled to Samoa in June 2019. Through the completion of these projects and activities I have clearly demonstrated the core field epidemiology training program competencies and accumulated knowledge and experience that will no doubt serve me well in the future

Deep learning for robotic strawberry harvesting

Abstract—We develop a novel machine learning based robotic strawberry harvesting system for fruit counting, sizing/weighting, and yield prediction

Black-grass (Alopecurus myosuroides) in cereal multispectral detection by UAV

Site-specific weed management (on the scale of a few meters or less) has the potential to greatly reduce pesticide use and its associated environmental and economic costs. A prerequisite for site-specific weed management is the availability of accurate maps of the weed population that can be generated quickly and cheaply. Improvements and cost reductions in unmanned aerial vehicles (UAVs) and camera technology mean these tools are now readily available for agricultural use. We used UAVs to collect aerial images captured in both RGB and multispectral formats of 12 cereal fields (wheat [Triticum aestivum L.] and barley [Hordeum vulgare L.]) across eastern England. These data were used to train machine learning models to generate prediction maps of locations of black-grass (Alopecurus myosuroides Huds.), a prolific weed in UK cereal fields. We tested machine learning and data set resampling methods to obtain the most accurate system for predicting the presence and absence of weeds in new out-of-sample fields. The accuracy of the system in predicting the absence of A. myosuroides is 69% and its presence above 5 g in weight with 77% accuracy in new out-of-sample fields. This system generates prediction maps that can be used by either agricultural machinery or autonomous robotic platforms for precision weed management. Improvements to the accuracy can be made by increasing the number of fields and samples in the data set and the length of time over which data are collected to gather data across the entire growing season

Robotic crop row tracking around weeds using cereal-specific features

Crop row following is especially challenging in narrow row cereal crops, such as wheat. Separation between plants within a row disappears at an early growth stage, and canopy closure between rows, when leaves from different rows start to occlude each other, occurs three to four months after the crop emerges. Canopy closure makes it challenging to identify separate rows through computer vision as clear lanes become obscured. Cereal crops are grass species and so their leaves have a predictable shape and orientation. We introduce an image processing pipeline which exploits grass shape to identify and track rows. The key observation exploited is that leaf orientations tend to be vertical along rows and horizontal between rows due to the location of the stems within the rows. Adaptive mean-shift clustering on Hough line segments is then used to obtain lane centroids, and followed by a nearest neighbor data association creating lane line candidates in 2D space. Lane parameters are fit with linear regression and a Kalman filter is used for tracking lanes between frames. The method is achieves sub-50 mm accuracy which is sufficient for placing a typical agri-robot’s wheels between real-world, early-growth wheat crop rows to drive between them, as long as the crop is seeded in a wider spacing such as 180 mm row spacing for an 80 mm wheel width robot

Fine-scale spatial variation in fitness is comparable to disturbance-induced fluctuations in a fire-adapted species

The spatial scale at which demographic performance (e.g., net reproductive output) varies can profoundly influence landscape-level population growth and persistence, and many demographically pertinent processes such as species interactions and resource acquisition vary at fine scales. We compared the magnitude of demographic variation associated with fine-scale heterogeneity (1 ha) fluctuations associated with fire disturbance. We used a spatially explicit model within an IPM modeling framework to evaluate the demographic importance of fine-scale variation. We used a measure of expected lifetime fruit production, EF, that is assumed to be proportional to lifetime fitness. Demographic differences and their effects on EF were assessed in a population of the herbaceous perennial Hypericum cumulicola (~2,600 individuals), within a patch of Florida rosemary scrub (400 × 80 m). We compared demographic variation over fine spatial scales to demographic variation between years across 6 yr after a fire. Values of EF changed by orders of magnitude over <10 m. This variation in fitness over fine spatial scales (<10 m) is commensurate to postfire changes in fitness for this fire-adapted perennial. A life table response experiment indicated that fine-scale spatial variation in vital rates, especially survival, explains as much change in EF as demographic changes caused by time-since-fire, a key driver in this system. Our findings show that environmental changes over a few tens of meters can have ecologically meaningful implications for population growth and extinction

Prevalence and risk factors associated with lymphatic filariasis in American Samoa after mass drug administration

Background: In 2000, American Samoa had 16.5% prevalence of lymphatic filariasis (LF) antigenemia. Annual mass drug administration (MDA) was conducted using single-dose albendazole plus diethylcarbamazine from 2000 to 2006. This study presents the results of a 2007 population-based PacELF C-survey in all ages and compares the adult filarial antigenemia results of this survey to those of a subsequent 2010 survey in adults with the aim of improving understanding of LF transmission after MDA. Results: The 2007 C-survey used simple random sampling of households from a geolocated list. In 2007, the overall LF antigen prevalence by immunochromatographic card test (ICT) for all ages was 2.29% (95% CI 1.66–3.07). Microfilaremia prevalence was 0.27% (95% CI 0.09–0.62). Increasing age (OR 1.04 per year, 95% CI 1.02–1.05) was significantly associated with ICT positivity on multivariate analysis, while having ever taking MDA was protective (OR 0.39, 95% CI 0.16–0.96). The 2010 survey used a similar spatial sampling design. The overall adult filarial antigenemia prevalence remained relatively stable between the surveys at 3.32% (95% CI 2.44–4.51) by ICT in 2007 and 3.23 (95% CI 2.21–4.69) by Og4C3 antigen in 2010. However, there were changes in village-level prevalence. Eight village/village groupings had antigen-positive individuals identified in 2007 but not in 2010, while three villages/village groupings that had no antigen-positive individuals identified in 2007 had positive individuals identified in 2010. Conclusions: After 7 years of MDA, with four rounds achieving effective coverage, a representative household survey in 2007 showed a decline in prevalence from 16.5 to 2.3% in all ages. However, lack of further decline in adult prevalence by 2010 and fluctuation at the village level showed that overall antigenemia prevalence at a broader scale may not provide an accurate reflection of ongoing transmission at the village level.This publication was supported by a grant from the United States Agency for International Development (USAID) through NTD SC, a program of The Task Force for Global Health, Inc. Its contents are solely the responsibility of the authors and do not necessarily represent the views of The Task Force for Global Health, Inc., NTD SC or the USAID Funding for the 2007 survey was provided by the US Centers for Disease Prevention and Control. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. Funding for the 2010 serology was provided by James Cook University and Glaxo Smith Kline to the JCU WHO Collaborating Centre for Control of Lymphatic Filariasis, Soil-transmitted Helminths and other NTDs. CLL was supported by an Australian National Health and Medical Research Council (NHMRC) Fellowship (1109035). The funder had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript

Less favourable climates constrain demographic strategies in plants

Correlative species distribution models are based on the observed relationship between species’ occurrence and macroclimate or other environmental variables. In climates predicted less favourable populations are expected to decline, and in favourable climates they are expected to persist. However, little comparative empirical support exists for a relationship between predicted climate suitability and population performance. We found that the performance of 93 populations of 34 plant species worldwide – as measured by in situ population growth rate, its temporal variation and extinction risk – was not correlated with climate suitability. However, correlations of demographic processes underpinning population performance with climate suitability indicated both resistance and vulnerability pathways of population responses to climate: in less suitable climates, plants experienced greater retrogression (resistance pathway) and greater variability in some demographic rates (vulnerability pathway). While a range of demographic strategies occur within species’ climatic niches, demographic strategies are more constrained in climates predicted to be less suitable

Considering weed management as a social dilemma bridges individual and collective interests

Weeds pose severe threats to agricultural and natural landscapes worldwide. One major reason for the failure to effectively manage weeds at landscape scales is that current Best Management Practice guidelines, and research on how to improve such guidelines, focus too narrowly on property-level management decisions. Insufficiently considered are the aggregate effects of individual actions to determine landscape-scale outcomes, or whether there are collective practices that would improve weed management outcomes. Here, we frame landscape-scale weed management as a social dilemma, where trade-offs occur between individual and collective interests. We apply a transdisciplinary system approach—integrating the perspectives of ecologists, evolutionary biologists and agronomists into a social science theory of social dilemmas—to four landscape-scale weed management challenges: (i) achieving plant biosecurity, (ii) preventing weed seed contamination, (iii) maintaining herbicide susceptibility and (iv) sustainably using biological control. We describe how these four challenges exhibit characteristics of ‘public good problems’, wherein effective weed management requires the active contributions of multiple actors, while benefits are not restricted to these contributors. Adequate solutions to address these public good challenges often involve a subset of the eight design principles developed by Elinor Ostrom for ‘common pool social dilemmas’, together with design principles that reflect the public good nature of the problems. This paper is a call to action for scholars and practitioners to broaden our conceptualization and approaches to weed management problems. Such progress begins by evaluating the public good characteristics of specific weed management challenges and applying context-specific design principles to realize successful and sustainable weed management

A detailed quantification of differential ratings of perceived exertion during team-sport training

Objectives: To investigate the application of differential ratings of perceived exertion (dRPE) to team-sport training. Design: Single cohort, observational study. Methods:Twenty-nine professional rugby union players were monitored over a six-week intensified training period. Training sessions were classified as: high-intensity intervals, repeated high-intensity efforts, speed, skill-based conditioning, skills, whole-body resistance, or upper-body resistance. After each session, players recorded a session rating of perceived exertion (sRPE; CR100®), along with differential session ratings for breathlessness (sRPE-B), leg muscle exertion (sRPE-L), upper-body muscle exertion (sRPE-U), and cognitive/technical demands (sRPE-T). Each score was multiplied by the session duration to calculate session training loads. Data were analysed using mixed linear modelling and multiple linear regression, with magnitude-based inferences subsequently applied. Results: Between-session differences in dRPE scores ranged from very likely trivial to most likely extremely large and within-session differences amongst dRPE scores ranged from unclear to most likely very large. Differential RPE training loads combined to explain 66–91% of the variance in sRPE training loads, and the strongest associations with sRPE training load were with sRPE-L for high-intensity intervals (r = 0.67; 90% confidence limits ±0.22), sRPE-B for repeated high-intensity efforts (0.89; ±0.08) and skill-based conditioning (0.67; ±0.19), sRPE-T for Speed (0.63; ±0.17) and Skills (0.51; ±0.28), and sRPE-U for resistance training (whole-body: 0.61; ±0.21, upper-body: 0.92; ±0.07). Conclusions: Differential RPE can provide a detailed quantification of internal load during training activities commonplace in team sports. Knowledge of the relationships between dRPE and sRPE can isolate the specific perceptual demands of different training modes

Landscape scale spread of alien invasive plants: what are the key drivers and how can human behaviour affect it?

Invasive plants disrupt ecosystems from local to landscape scales, and there is a pressing need to predict spread rates accurately in order to inform management. Models of plant spread can aid management by identifying key population and dispersal processes to target, as well as areas at risk of invasion. This thesis aims to determine which vital rates drive spread under a variety of conditions for different types of species and how much biological detail is required to accurately model spread. This thesis also asks how control of invasive plants at local scales translates to landscape scale control when managers cannot access the entire invasive population. In chapter 2 the main drivers of spread, and thus potential targets for management, were identified using a spatially explicit simulation model tested on different life history categories in different spread and landscape scenarios. From our results we deduced four simple management guidelines: i) manage dispersal if possible as mean dispersal distance was important for spread under all conditions tested, ii) short bursts of rapid spread or more usual year on year spread can have different drivers, therefore managers need to decide what type of spread they want to slow, iii) efforts to manage spread will have variable outcomes due to interactions between, and non-linear responses to, key drivers of spread and iv) the most useful demographic rates to target depend on dispersal ability, life history and how spread is measured. Fecundity was found to be important for driving spread only when reduced to low levels. For longer lived species management should target survival or age of first seed production, especially when dispersal ability is limited. Chapter 3 describes a field study on the reproductive ecology of a population of Pinus nigra, an invasive pine species, at a site in New Zealand. We describe how cone production varied among trees using a negative binomial or mixed gamma-exponential distribution. Both of these distributions were right skewed and trees maintained fecundity hierarchies over time; suggesting that some trees in the population have much higher lifetime reproduction than others. We found that trees dropped significantly more seeds when conditions were dry and windy, potentially increasing the proportion of seeds that disperse mid to long distances. We also found taller neighbours reduced cone production much more than shorter neighbours; indicating shade was the primary mechanism by which neighbours reduced cone production. In chapter 4 the effect that individual level variation in fecundity has on spread rates was tested with an individual based simulation, parameterised with demographic data from chapter 3 and dispersal data from the same site. We found that including heterogeneity in fecundity lowered predicted spread rates, but the differences were small. However, the overestimation of spread rates caused by assuming homogeneous fecundity accumulated over time, leading to large differences in the extent of the invasion after 250 time steps. Thus, early in an invasion simpler models may be adequate to capture average spread rates, but over longer time spans heterogeneity in fecundity should be included for accurate prediction of extent and invasion impact. Given that current models of plant spread assuming homogeneous fecundity are commonly used for sensitivity analysis, an important finding was that sensitivities were similar under heterogeneous and homogeneous fecundity. In many situations control of damaging alien invasive plants is undertaken by multiple independent decision makers, each managing only a small part of the invader’s population. Using a spatially explicit agent based simulation we determined how individual manager behaviour, in concert with weed ecology, determined the prevalence of two invasive grass species in Australia, Nassella trichotoma and Eragrostis curvula (chapter 5). We expect damaging weeds with effective control strategies to be less prevalent because the majority of land managers will choose to control them. However, if there is long distance dispersal a small minority (ca. 10%) of land mangers reluctant to control can impact the whole landscape. The way decision makers react to the benefit of management can have a large effect on the extent of a weed. If all agents believed control was a good idea and acted on it, they tended to act synchronously, reducing the pool of infested agents available to spread the weed. The general findings of this thesis are as follows: i) characteristics of the dispersal kernel are the most influential factors driving spread rates, but demographic rates such as fecundity, establishment probability, age of first seed production and the frequency of high seed production years can all substantially influence spread rates, ii) individual level variation in fecundity did not greatly reduce spread rates and simpler models appear adequate to describe spread in many situations, iii) when there are multiple managers the translation of local control to landscape scale reductions in spread have the potential to be greatly influenced by human behaviour, especially if long distance dispersal is possible