A finite element model for predicting impact-induced damage to a skin simulant.

A finite element model was developed for assessing the efficacy of rugby body padding in reducing the risk of sustaining cuts and abrasions. The model was developed to predict the onset of damage to a soft tissue simulant from concentrated impact loading (i.e., stud impact) and compared against a corresponding experiment. The damage modelling techniques involved defining an element deletion criterion, whereby those on the surface of the surrogate were deleted if their maximum principal stress reached a predefined value. Candidate maximum principal stress values for element deletion criteria were identified independently from puncture test simulations on the soft tissue simulant. Experimental impacts with a stud were carried out at three energies (2, 4 and 6 J), at three angular orientations (0°, 15° and 30°) and compared to corresponding simulations. Suitable maximum principal stress values for element deletion criteria settings were first identified for the 4 J impact, selecting the candidates that best matched the experimental results. The same element deletion settings were then applied in simulations at 2 and 6 J and the validity of the model was further assessed (difference < 15% for the force at tear and < 30% for time to tear). The damage modelling techniques presented here could be applied to other skin simulants to assess the onset of skin injuries and the ability of padding to prevent them.

Replicating superspreader dynamics with compartmental models.

Infectious disease outbreaks often exhibit superspreader dynamics, where most infected people generate no, or few secondary cases, and only a small fraction of individuals are responsible for a large proportion of transmission. Although capturing this heterogeneity is critical for estimating outbreak risk and the effectiveness of group-specific interventions, it is typically neglected in compartmental models of infectious disease transmission-which constitute the most common transmission dynamic modeling framework. In this study we propose different classes of compartmental epidemic models that incorporate transmission heterogeneity, fit them to a number of real outbreak datasets, and benchmark their performance against the canonical superspreader model (i.e., the negative binomial branching process model). We find that properly constructed compartmental models can capably reproduce observed superspreader dynamics and we provide the pathogen-specific parameter settings required to do so. As a consequence, we also show that compartmental models parameterized according to a binary clinical classification have limited support.

Epidemiology of soil-transmitted helminths using quantitative PCR and risk factors for hookworm and Necator americanus infection in school children in Dak Lak province, Vietnam.

BACKGROUND: Soil-transmitted helminth (STH) infection is driven by a complex interaction of demographic, socioeconomic and behavioural factors, including those related to water, sanitation and hygiene (WASH). Epidemiological studies that measure both infection and potential risk factors associated with infection help to understand the drivers of transmission in a population and therefore can provide information to optimise STH control programmes. METHODS: During October and November 2019, we conducted a cross-sectional survey of the prevalence and intensity of STH infection and associated risk factors among 7710 primary-school-age children from 64 primary schools across 13 districts in Dak Lak province, Vietnam. Quantitative PCR (qPCR) was used to detect and quantify STH infections. RESULTS: The predominant STH species was the hookworm Necator americanus (overall cluster-adjusted prevalence of 13.7%), and its prevalence was heterogeneously distributed across surveyed schools (0% to 56.3%). All other STH species had a prevalence of less than 1%. Using mixed-effects logistic regression, we found that the adjusted odds ratio (aOR) was significantly higher for both infection and moderate-to-heavy-intensity infection with N. americanus among children from multiple ethnic minority groups, compared to children from the majority group (Kinh). Adjusted odds of infection with N. americanus were also higher in children who reported practising open defecation at school (aOR 1.42, 95% CI 1.05, 1.93, P = 0.02) and in those who had an unimproved household water supply (aOR 1.28, 95% CI 1.04, 1.57, P = 0.02). Conversely, children with a flushing household toilet had a reduced risk of infection (aOR 0.58, 95% CI 0.47, 0.70, P < 0.01), as did those whose primary female carer attended secondary (aOR 0.65, 95% CI 0.51, 0.84, P < 0.01) or tertiary education (aOR 0.39, 95% CI 0.24, 0.63, P < 0.01). CONCLUSIONS: This study is the largest reported prevalence survey of STH infections conducted using qPCR as a diagnostic technique. The findings of higher adjusted odds of infection amongst ethnic minority children highlight that STH control programmes may not be reaching certain population groups and that additional culturally appropriate approaches may be required. Additionally, the associations between specific WASH factors and infection indicate potential programmatic targets to complement preventive chemotherapy programmes.

Factors associated with vanA VRE acquisition in Cardiothoracic Surgery patients during an acute outbreak.

BACKGROUND: There was an acute outbreak of vanA Enterococcus faecium (VREfm) in a tertiary Melbourne teaching hospital between 2015 and 2016 amongst Cardiothoracic Surgery (CTS) ward and Intensive Care Unit (ICU) patients. Prior to this outbreak vanB VRE had been the predominate genotype encountered. METHODS: A retrospective, matched (1:2), case-control study was conducted on CTS patients between 1 August 2015 and 31 May 2016 admitted to a hospital in Melbourne, during an outbreak of vanA VREfm to identify factors associated with colonisation or infection. Factors assessed included undergoing surgery and type of procedure, exposure to antibiotics and admission to ICU. RESULTS: During the outbreak, 56 new cases of vanA VREfm out of 802 CTS ward patients were identified. Of these new cases, 52 were included in the case-control analysis, all identified via rectal screening. Cases had significantly longer duration of stay in hospital (p < 0.001) than controls. Multivariable analysis identified exposure to ceftriaxone as an independent factor (OR 4.14, p = 0.018) associated with new vanA VREfm isolates. Other factors such as vancomycin exposure, specific CTS procedures or ICU admission were not identified as independent factors. Ceftriaxone was being used during the outbreak as surgical prophylaxis amongst CTS patients. CONCLUSION: Ceftriaxone use was associated with an increased risk of CTS patients acquiring vanA VREfm during an acute outbreak. This highlights the overall importance of antibiotic stewardship to minimise hospital-associated multi-drug resistant infections.

An outbreak of vanA vancomycin-resistant Enterococcus faecium in a hospital with endemic vanB VRE.

BACKGROUND: In Australia, vanB vancomycin-resistant Enterococcus faecium (VREfm) has been endemic for over 20 years, but vanA VREfm isolates have rarely been reported. METHODS: This outbreak report describes an outbreak of vanA VREfm in the intensive care unit (ICU) and cardiothoracic surgery (CTS) wards of a Melbourne hospital in 2015-2016. After the cluster was initially identified in the ICU ward, an active screening programme was implemented. VRE isolates were typed using in silico multi-locus sequence typing. In addition, to screening, enhanced environmental cleaning, chlorhexidine gluconate body washes, and standardisation of the surgical antibiotic prophylaxis regimen were implemented to control the outbreak. RESULTS: There were 83 new isolates of vanA VREfm recovered from patients in the ICU (n = 31) and CTS (n = 52) wards. Screening identified 78 (94%) of cases. Three patients required treatment for clinical infection with vanA VREfm during the outbreak. The outbreak was polyclonal with 5 different multilocus sequence types carrying the vanA gene (ST17, ST80, ST203, ST252 and ST1421) detected from a subset of isolates (N = 43). The ST17 isolates all carried both the vanA and vanB gene. The intervention bundle resulted in control of the outbreak after 10 months. CONCLUSION: Geographically, vanA VREfm has previously been uncommon in the region and this outbreak represents a change in local epidemiology. Few VRE outbreaks have been reported in CTS patients. The infection control responses controlled the outbreak within 10-months and may help guide future management of outbreaks.

A data science pipeline applied to Australia's 2022 COVID-19 Omicron waves.

The field of software engineering is advancing at astonishing speed, with packages now available to support many stages of data science pipelines. These packages can support infectious disease modelling to be more robust, efficient and transparent, which has been particularly important during the COVID-19 pandemic. We developed a package for the construction of infectious disease models, integrated it with several open-source libraries and applied this composite pipeline to multiple data sources that provided insights into Australia's 2022 COVID-19 epidemic. We aimed to identify the key processes relevant to COVID-19 transmission dynamics and thereby develop a model that could quantify relevant epidemiological parameters. The pipeline's advantages include markedly increased speed, an expressive application programming interface, the transparency of open-source development, easy access to a broad range of calibration and optimisation tools and consideration of the full workflow from input manipulation through to algorithmic generation of the publication materials. Extending the base model to include mobility effects slightly improved model fit to data, with this approach selected as the model configuration for further epidemiological inference. Under our assumption of widespread immunity against severe outcomes from recent vaccination, incorporating an additional effect of the main vaccination programs rolled out during 2022 on transmission did not further improve model fit. Our simulations suggested that one in every two to six COVID-19 episodes were detected, subsequently emerging Omicron subvariants escaped 30-60% of recently acquired natural immunity and that natural immunity lasted only one to eight months on average. We documented our analyses algorithmically and present our methods in conjunction with interactive online code notebooks and plots. We demonstrate the feasibility of integrating a flexible domain-specific syntax library with state-of-the-art packages in high performance computing, calibration, optimisation and visualisation to create an end-to-end pipeline for infectious disease modelling. We used the resulting platform to demonstrate key epidemiological characteristics of the transition from the emergency to the endemic phase of the COVID-19 pandemic.