Pandemic (H1N1) 2009 influenza community transmission was established in one Australian state when the virus was first identified in North America

BACKGROUND In mid-June 2009 the State of Victoria in Australia appeared to have the highest notification rate of pandemic (H1N1) 2009 influenza in the world. We hypothesise that this was because community transmission of pandemic influenza was already well established in Victoria at the time testing for the novel virus commenced. In contrast, this was not true for the pandemic in other parts of Australia, including Western Australia (WA). METHODS We used data from detailed case follow-up of patients with confirmed infection in Victoria and WA to demonstrate the difference in the pandemic curve in two Australian states on opposite sides of the continent. We modelled the pandemic in both states, using a susceptible-infected-removed model with Bayesian inference accounting for imported cases. RESULTS Epidemic transmission occurred earlier in Victoria and later in WA. Only 5% of the first 100 Victorian cases were not locally acquired and three of these were brothers in one family. By contrast, 53% of the first 102 cases in WA were associated with importation from Victoria. Using plausible model input data, estimation of the effective reproductive number for the Victorian epidemic required us to invoke an earlier date for commencement of transmission to explain the observed data. This was not required in modelling the epidemic in WA. CONCLUSION Strong circumstantial evidence, supported by modelling, suggests community transmission of pandemic influenza was well established in Victoria, but not in WA, at the time testing for the novel virus commenced in Australia. The virus is likely to have entered Victoria and already become established around the time it was first identified in the US and Mexico

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

A springs and masses model for determining the lowest risk path in a threat environment

Finding the safest path through a threat environment is paramount for the military. This work investigates the use of a springs and masses model for battlefield applications. In particular, we examine the use of this model in scenarios when the locations of the threat environment are not necessarily known, that is, `pop-up' threats. The strengths and weaknesses of this approach are discussed including the potential for using this model to solve safe path problems in real-time, which would allow it to be used as a decision making tool for both field and onboard system applications. References The MathWorks. MATLAB central. http://www.mathworks.com/matlabcentral/. The MathWorks. MATLAB documentation. http://www.mathworks.com/access/helpdesk/help/techdoc/index.html?/access/helpdesk/help/techdoc/math/f1-662913.html. T. W. Mclain and R. W. Beard. Trajectory planning for coordinated rendezvous of unmanned air vehicles. In Proceedings of the AIAA Guidance, Navigation, and Control Conference, pages 1247--1254, 2000. http://citeseer.ist.psu.edu/306568.html. G. N. Mercer and H. S. Sidhu. Two continuous methods for determining a minimal risk path through a minefield. In W Read and A J Roberts, editors, Proceedings of the 13th Biennial Computational Techniques and Applications Conference, volume 48, pages C293--C306, July 2007. http://anziamj.austms.org.au/ojs/index.php/ANZIAMJ/article/view/56. R. Murphy, S. Uryasev, and M. Zabarankin. Trajectory optimization in a threat environment. Research report 9, Department of Industrial and Systems Engineering, University of Florida, July 2003. http://www.ise.ufl.edu/uryasev/Trajectory_optimization.pdf. M. C. Novy. Air vehicle optimal trajectories for minimization of radar exposure. Master's thesis, Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio, USA, March 2001. http://handle.dtic.mil/100.2/ADA390154. H. S. Sidhu, G. N. Mercer, M. J. Sexton, N. A. Ansari, and Z. Jovanoski. Optimal path trajectories in a threat environment. Journal of Battlefield Technology, 9(3):33--39, November 2006. http://www.argospress.com/jbt/. M. Zabarankin, S. Uryasev, and P. Pardalos. Optimal path risk algorithms. In R Murphey and P Pardalos, editors, Cooperative Control and Optimization, chapter 13, pages 273--298. Kluwer Academic Publisher, 2002. doi:10.1007/0-306-47536-7-13. R. W. Beard, T. W. McLain, M. Goodrich, and E. P. Anderson. Coordinated target assignment and intercept for unmanned air vehicles. IEEE Transactions on Robotics and Automation, 18:911--922, 2002. http://ieeexplore.ieee.org/iel5/70/25967/01159009.pdf. S. A. Bortoff. Path planning for {UAV}s. In Proceedings of the American Control Conference, number 6, pages 364--368, Sep 2000. doi:10.1109/ACC.2000.878915. M. Jun and R. D'Andrea. Path planning for unmanned aerial vehicles in uncertain and adversarial environments. In S Butenko, R Murphey, and P Paralos, editors, Cooperative Control: Models, Applications and Algorithms, chapter 6, pages 95--110. Kluwer Academic Publisher, 2003. http://www.seas.ucla.edu/coopcontrol/papers/02cn04.pdf. J. J. Leary. Search for a stealthy flight path through a hostile radar defense network. Master's thesis, Naval Postgraduate School, Monterey, CA, USA, March 1995. http://handle.dtic.mil/100.2/ADA297669

Comparison of the pandemic H1N1 2009 experience in the Southern Hemisphere with pandemic expectations

Abstract Objective: To describe the epidemiological characteristics of the 2009 H1N1 pandemic virus (pH1N1) over the 2009 and 2010 influenza seasons in Australia and New Zealand (NZ) and compare them with expectations based on previous pandemics. Methods: Laboratory‐confirmed influenza and influenza‐like illness (ILI) data were collected from established general practitioner sentinel surveillance schemes in NZ, Victoria and Western Australia (WA) throughout the 2009 and 2010 winter influenza seasons. Respiratory swabs from a sample of ILI patients were tested for influenza type and subtype. ILI rates and laboratory‐confirmed influenza data were analysed by age group and over time. Morbidity, mortality and reproductive number data were collated from the published literature. Results: Peak ILI rates and the percentage of influenza‐positive swabs from ILI patients from all sentinel surveillance schemes were considerably lower in 2010 than 2009. Compared to the population, cases of ILI were over‐represented in the young. While the age distributions in NZ and WA remained consistent, ILI cases were significantly younger in Victoria in 2009 compared to 2010. In Victoria, laboratory‐confirmed pH1N1 comprised up to 97% of influenza‐positive swabs in 2009 but only 56–87% in 2010. Mortality and hospitalisations were lower in 2010. The effective reproduction number (R) for pH1N1 was estimated to be 1.2–1.5 in NZ and WA, similar to estimated R values for seasonal influenza. Data from the surveillance systems indicated differences in the epidemiology of pH1N1 compared to expectations based on previous pandemics. In particular, there was no evidence of a second pandemic wave associated with increased mortality, and complete influenza strain replacement did not occur. Implications: Pandemic planning needs to accommodate the potential for influenza viruses to produce pandemics of various infectiousness and degrees of severity

Pandemic (H1N1) 2009 influenza community transmission was established in one Australian state when the virus was first identified in North America

Background: In mid-June 2009 the State of Victoria in Australia appeared to have the highest notification rate of pandemic (H1N1) 2009 influenza in the world. We hypothesise that this was because community transmission of pandemic influenza was already well established in Victoria at the time testing for the novel virus commenced. In contrast, this was not true for the pandemic in other parts of Australia, including Western Australia (WA). Methods: We used data from detailed case follow-up of patients with confirmed infection in Victoria and WA to demonstrate the difference in the pandemic curve in two Australian states on opposite sides of the continent. We modelled the pandemic in both states, using a susceptible-infected-removed model with Bayesian inference accounting for imported cases. Results: Epidemic transmission occurred earlier in Victoria and later in WA. Only 5 % of the first 100 Victorian cases were not locally acquired and three of these were brothers in one family. By contrast, 53 % of the first 102 cases in WA were associated with importation from Victoria. Using plausible model input data, estimation of the effective reproductive number for the Victorian epidemic required us to invoke an earlier date for commencement of transmission to explain the observed data. This was not required in modelling the epidemic in WA. Conclusion: Strong circumstantial evidence, supported by modelling, suggests community transmission of pandemi

Case notification and estimated reproductive number by date using a serial interval of 2.8 days, Western Australia 2009.

<p>Case notification and estimated reproductive number by date using a serial interval of 2.8 days, Western Australia 2009.</p

Actual and simulated cases and calculated R, Victoria, 25 April to 29 May 2009.

<p>An example of simulated data, calculated with an effective reproductive number (R) of 1.4 and a mean serial interval of 2.8 days, compared with observed data 25 April to 29 May, Victoria 2009. Also shown is R calculated from the observed data using a serial interval of 2.8 days.</p

Notified cases by onset date and source and dates of significant events, Victoria 2009.

<p>All cases notified to the department until 4 June inclusive were included in the analysis as they were assumed to be tested during the Delay or Contain phases. Due to the delay between symptoms onset and notification, the number of cases in this chart decreases in the days prior to 4 June.</p

Notified cases by onset date and importation source, Western Australia 2009.

<p>Notified cases by onset date and importation source, Western Australia 2009.</p

Acalabrutinib in Combination with Rituximab, Cyclophosphamide, Doxorubicin, Vincristine and Prednisolone (R-CHOP) as first line therapy for patients with diffuse Large B-Cell Lymphoma (DLBCL): The Accept Phase Ib/II single arm study

Introduction: R‐CHOP remains the standard of care for DLBCL yet many patients (pts.) either fail to respond or relapse after having achieved an initial remission. Dysregulation of B Cell receptor (BCR) signalling is well recognised in some sub-types of DLBCL. In the phase III PHOENIX study (NCT01855750), the addition of the Bruton's tyrosine kinase inhibitor (BTKi) ibrutinib (I) to R‐CHOP (R‐CHOP‐I) did not improve the outcome of the study population with non‐germinal centre like DLBCL. However, R‐CHOP‐I treated pts. who were aged less than 60 years had a significantly improved progression free survival (PFS) and overall survival (OS) compared to those receiving R‐CHOP alone. In pts. aged over 60 years, the addition of I increased toxicity and compromised the delivery of R‐CHOP. Acalabrutinib (A) is a second generation BTKi, with enhanced kinase selectivity and potential for better efficacy and tolerability over first‐generation inhibitors. There is a strong rationale to combine A with R‐CHOP in untreated de novo DLBCL to understand its safety profile and efficacy.Methods: eligible pts. were treatment naive with histologically confirmed DLBCL. All pts. received 6 cycles of R‐CHOP therapy on a standard 21‐day schedule, with the addition of A in cycles 2‐6. A continuation phase of A only, for 2 cycles of 28 days was administered after R-CHOP. The primary objective of the phase Ib was to establish a recommended phase II dose (RP2D) of A in combination with R‐CHOP (modified classical 6+6 design). Phase II assessed the overall response rate (ORR) of the combination and ascertained additional safety information. Secondary endpoints included metabolic complete response rates (mCR), PFS and OS and their relation to the COO, pharmacokinetics and pharmacodynamics. Cell of origin (COO) was determined by HTG EdgeSeq. Recruitment of pts. over the age of 65 was suspended as an urgent safety measure (USM) following the abstract release of data from PHOENIX (Nov 2018). ACCEPT reopened to all ages after a comprehensive safety review by the Independent Data Monitoring Committee (Sep 2019). The trial was endorsed by CRUK (CRUKDE/16/006).Results: from May 2017 to Jan 2020, 38 pts. were enrolled (safety population: Pts. in receipt of any component of therapy). The median age was 64 years (range 24-80, 39% &gt;65 years old); 74% stage III/IV; 66%; raised LDH; 29% B symptoms; 32% bulk; 26% high IPI; 29% high-intermediate IPI; 16% High NCCN-IPI. Seven of the enrolled pts. were found to be ineligible (insufficient material for translational work, 2pts.; taking a proton pump inhibitor during therapy, 2 pts.; follicular histology, 1pt.; abnormal LFTs at baseline, 1pt.; age &gt;65 at time of USM, 1 pts). There were no dose-limiting toxicities and the maximum tolerated dose was not reached. The RP2D was chosen as 100mg bd acalabrutinib. The most common &gt;grade3 adverse events were neutropenia (26% of pts.), febrile neutropenia (13%) and diarrhoea (11%). The most frequently reported serious adverse event was febrile neutropenia (13% of pts.). Age did not compromise the delivery of full dose R-CHOP in combination with A. One patient in the first cohort (A 100mg od) progressed on therapy. Of the 24 eligible patients who received the RP2D (A 100mg bd) in either dose escalation or expansion, 22 responses have been reported (1 awaiting response assessment and 1 not assessed). Four pts. withdrew early from treatment (2 pts. subject withdrawal, 1 pt. investigator withdrawal and 1pt. due to toxicity) and are included in the efficacy analysis. The ORR was 95% with 82% of pts. achieving a mCR (3 pts. partial response (PR), 1pts. stable disease). One pt. with MYC/BCL2/BCL6 rearrangements and one pt. with MYC/BCL2 rearrangement achieved a mCR; neither have progressed. Ten of twelve ABC pts. (83%), 7/8 GCB pts (88%) and 1/2 unclassified pts. (50%) achieved a mCR. With a median follow-up of 15 months, the primary progressive patient from cohort 1 has died. PFS and OS at 12 months for those eligible pts. in receipt of the RP2D is 100%. Two of the RP2D pts. not achieving mCR have however received additional therapy (1 radiotherapy, 1 chemotherapy) prior to progression. R-CHOP did not affect the pharmacokinetics of A. Additional translational data will be presented.Conclusions: Acalabrutinib is well tolerated when given in combination with R-CHOP chemotherapy and may be associated with improved efficacy that should be explored in future randomised trials