Vaccine preventable diseases

Vaccination is one of the most significant public health interventions in history. In this thesis, I present work conducted as an Master of Applied Epidemiology (MAE) Scholar whilst placed at the National Centre for Immunisation Research and Surveillance (NCIRS) in 2012-2013. During my placement, I was involved in examining the epidemiology of a number of vaccine preventable diseases and also adverse events following immunisation (AEFI). A key requirement of the MAE is the analysis of a public health dataset; of which I present two analyses. Firstly, the impact of the human papillomavirus vaccine on high grade cervical abnormalities (HGAs) in Australia using screening data; the analysis found a significant reduction in HGAs in females under 20 years post-vaccine compared to the pre-vaccine era, suggesting that the vaccine may have contributed to the decline in HGAs.Secondly, the epi-review on passive AEFI surveillance in children less than 18 years of age in 2000-2011 highlighted major events that occurred during this period. I also present two projects conducted as part of the measles outbreak in New South Wales (NSW) during 2012. The first was using a non-validated algorithm to identify an index case following four measles notifications that were linked by time and place to a paediatric hospital. The algorithm was unsuccessful in identifying an index case, however, may serve as a model that can be adapted and possibly validated for use in similar investigations in the future. The second was examining the epidemiology of healthcare transmissions during the outbreak. This study identified the importance of raising awareness of measles among clinicians during outbreaks and that measles control strategies may need a more targeted approach, particularly with limited resources. As part of my epidemiological study, I conducted an epi-review of measles in Australia. Since 1993, there was a considerable decline in measles notifications and hospitalisations; however; between 2000 and 2011, notifications have fluctuated with a notable increase in 2011. National notification data (2009-2011) were also used to estimate the reproduction number (R) for measles. The three methods to estimate R were below one for all years suggesting that measles elimination had been sustained in Australia. I also calculated a measles discard rate in NSW; an indicator of high quality surveillance. This study further supported sustained measles elimination achieving the minimum standard of more than 2 non-measles cases per 100,000 population suggesting that in NSW, endemic measles would be detected if wild virus was re-established. I also present another MAE requirement, evaluating the passive surveillance system for varicella-zoster virus nationally, as part of the National Notifiable Disease Surveillance System. I found that the sensitivity of the system in detecting the incidence of disease was poor; however, it was sensitive in detecting disease trends when compared to other data sources. Additionally, more consistency in reporting by jurisdictions is necessary to improve the validity of the data. This thesis provides documentation of my MAE activities at NCIRS and includes how these activities have contributed to public health in Australia

Life cycle inventory of the commercial production of compost from oil palm biomass: a case study

This paper compared the life cycle inventory (LCI) obtained from three commercial oil palm biomass composting projects in Malaysia which use the open windrow composting system. The LCI was obtained and calculated based on the functional unit of 1 t of compost produced. The input of the inventory are the feed materials such as empty fruit bunches (EFB) and palm oil mill effluent (POME); and utilities which include electricity generated at palm oil mill and diesel used. Composting 2.0–2.5 t of EFB and 5.0–7.5 t of POME required diesel from 218.7 to 270.2 MJ and electricity from 0 to 6.8 MJ. It is estimated that the composting emitted from 0.01 to 0.02 t CO2eq/tcompost mainly from diesel used to operate machineries. Composting saved 65 % of time required for a complete degradation of POME when compared to ponding system, and 89 % of time required for a complete degradation of EFB compared to mulching. In terms of land required, it required 36 % less land as compared to ponding for POME and 99 % less land as compared to mulching for EFB. Based on the case study, diesel was found to be the main contributor to the environmental impact. There is a potential of upgrading the process to be more economical and environmental friendly. Using electricity as the source of energy has a lower footprint for the composting process. Instead of using raw POME, studies had reported that using treated POME either from anaerobic ponding or digested tank can accelerate the composting process

Phishing Email Detection Technique by using Hybrid Features

Phishing emails is growing at an alarming rate in this few years. It has caused tremendous financial losses to internet users. Phishing techniques getting more advance everyday and this has created great challenge to the existing anti-phishing techniques. Hence, in this paper, we proposed to detect phishing emails through hybrids features. The hybrid features consist of content-based, URL-based, and behaviorbased features. Based on a set of 500 phishing emails and 500 legitimate emails, the proposed method achieved overall accuracy of 97.25% and error rate of 2.75%. This promising result verify the effectiveness of the proposed hybrid features in detecting phishing email

Composting of oil palm biomass: Fourier transform-infrared and thermogravimetry analyses

This study investigates the effects of composting conditions on the chemical characteristics of compost from oil palm biomass. Three samples each of empty fruit bunches (EFB), palm oil mill effluent (POME) and compost were collected from three compost plants in Malaysia. The plants employed open windrow composting system. The Fourier transform-infrared spectra and thermogravimetry analysis were used to analyse the samples. It was found that composting resulted in the loss of aliphatic structures by formation of aromatic structures. This led to a stronger intramolecular bond and subsequently increased the stability of compost. The results of the study showed that the use of shredded EFB for composting is the most efficient way to produce compost. It required 55% less amount of time as compared to untreated EFB and 60% less amount of time as compared to treatment without addition of microbes

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC

Polygenic Risk Modelling for Prediction of Epithelial Ovarian Cancer Risk

Funder: Funding details are provided in the Supplementary MaterialAbstractPolygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally-efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestry; 7,669 women of East Asian ancestry; 1,072 women of African ancestry, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestry. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38(95%CI:1.28–1.48,AUC:0.588) per unit standard deviation, in women of European ancestry; 1.14(95%CI:1.08–1.19,AUC:0.538) in women of East Asian ancestry; 1.38(95%CI:1.21-1.58,AUC:0.593) in women of African ancestry; hazard ratios of 1.37(95%CI:1.30–1.44,AUC:0.592) in BRCA1 pathogenic variant carriers and 1.51(95%CI:1.36-1.67,AUC:0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.</jats:p

Longitudinally extensive transverse myelopathy in spinal cord infarction

Abstract Spinal cord infarction may present as longitudinally extensive myelopathy, similar to inflammatory myelitis such as neuromyelitis optica. Magnetic resonance imaging features such as diffusion‐weighted imaging/apparent diffusion coefficient showing restricted diffusion and lack of contrast enhancement are helpful in the diagnosis of spinal cord infarction and differentiating them from inflammatory myelitis

Epidemiological update on the dengue situation in the Western Pacific Region, 2012

Dengue has caused a substantial public health burden in the Western Pacific Region. To assess this burden and regional trends, data were collated and summarized from indicator-based surveillance systems on dengue cases and deaths from countries and areas in the Western Pacific Region. In 2012, dengue notifications continued to increase with 356 838 dengue cases reported in the Region (relative to 244 855 cases reported in 2011) of which 1248 died. In the Asia subregion, the notification rate was highest in Cambodia, the Philippines and the Lao People’s Democratic Republic (316.2, 198.9 and 162.4 per 100 000 population, respectively), and in the Pacific island countries and areas, the notification rate was highest in Niue, the Marshall Islands and the Federated States of Micronesia (8556.0, 337.0 and 265.1 per 100 000 population, respectively). All four serotypes were circulating in the Region in 2012 with considerable variabilitiy in distribution. Regional surveillance provides important information to enhance situational awareness, conduct risk assessments and improve preparedness activities