Australian Mathematical Society expresses concerns about the proposed new mathematics curriculum

The Australian Curriculum, Assessment and Reporting Authority (ACARA) is currently developing a new national school curriculum, including for mathematics. The public consultation period is drawing to a close, finishing on the 8th July.

On the 2nd of July the President of the AustMS, Prof. Ole Warnaar, contacted David de Carvalho, CEO of ACARA, asking for an extension of the consultation period, and further details about the design process and evidence base for the proposed mathematics curriculum. This letter, along with Mr de Carvalho’s response, can be seen at this page.

The exchange of letters was followed up with a meeting on the 5th of July between Mr de Carvalho, Prof. Warnaar, and Prof. Geoff Prince, Vice-President of AustMS. One result is that “The meeting confirmed that mathematical scientists were not involved in any official capacity in the preparation of the revised curriculum.”

It is deeply concerning that the mathematics profession has been left out of the revision process and design of the new National Curriculum in Mathematics.

Prof Ole Warnaar

Prof. Warnaar’s full summary of the situation can also be seen at the letter page. At the time of posting there is to be no change to the consultation timeline.

Lecturer/Senior Lecturer in Statistics, Data Science, Stochastic Modelling

School of Mathematical Sciences
University of Adelaide

Closing date: 1st August 2021

(Level B, Lecturer) $100,933 to $119,391 or (Level C, Senior Lecturer) $123,075 to $141,537 per annum plus an employer contribution of up to 17% superannuation may apply. 

Three-year fixed term position available from December 2021.  On conclusion of the three-year term, the position may be converted to a continuing position under the provisions of the University’s Enterprise Agreement.  

Two full-time positions are available.

The University of Adelaide is seeking to grow the statistics, data science, and stochastic modelling team in the School of Mathematical Sciences. This is an opportunity for a highly motivated researcher and committed educator to join a School that is a leader in pedagogical innovation and received the highest possible rating of research quality in the mathematical sciences overall and in each of its disciplines in the two most recent ERA assessments.

The School has identified data science, broadly construed, as one of its strategic priorities. We are seeking an enthusiastic colleague to work with us to expand our research and educational offerings in statistics, data science, and stochastic modelling. Willingness to engage with industry would be an asset. 

The School is strongly committed to increasing the diversity of its staff and students. These two available positions are directed at applicants who are able to contribute to the diversity of the School community.

For more information and to apply, click here.

Contribution of mathematical modelling to COVID-19 response strategies in regional and remote Australian Aboriginal and Torres Strait Islander communities

(This is a guest post by Dr Rebecca Chisholm, Dr Ben Hui and Associate Professor David Regan as part of our miniseries of articles/essays by Australian mathematicians involved in the pandemic response. A pdf version of this article is available here.)

The health and science communities recognised early on in the SARS-CoV-2 pandemic that Aboriginal and Torres Strait Islander Australians were likely to be at high risk of COVID-19 infection and severe outcomes, due to high rates of comorbidities associated with severe outcomes [1,2], and multiple factors predisposing to increased SARS-CoV-2 transmission [2,3,4].  In March 2020, the Australian Government convened the Aboriginal and Torres Strait Islander Advisory Group on COVID-19 (IAG), co-chaired by the Department of Health and the National Aboriginal Community Controlled Health Organisation. The role of the IAG was to develop and deliver a National Management Plan to protect Aboriginal and Torres Strait Islander communities.  Our research groups—located at the Doherty Institute, the Kirby Institute and La Trobe University—were commissioned to carry out modelling, under the guidance of the IAG, to help inform aspects of this plan related to regional and remote communities.  

Our prior research and existing modelling frameworks enabled us to quickly begin the process of responding to the questions of interest to the IAG which included:

  • How important is a timely response to the first identified case of COVID-19? 
  • Who should be quarantined and/or tested in communities?
  • How important is it to test people when they are in quarantine and prior to exit from quarantine?
  • Is there a role for community-wide lockdown in initial containment? 

Together, we repurposed a stochastic, individual-based modelling framework which had previously been developed at the Kirby Institute to examine the dynamics of sexually transmitted infections in remote communities [5].  Within this framework, we incorporated a model of population mobility and household structure relevant to disease spread via close contact in remote communities. This model was originally developed at La Trobe University and the Doherty Institute as part of a research program focused on understanding the drivers of high prevalence of Group A Streptococcus disease in these communities [4].  We also integrated a COVID-19-specific disease transmission model and the effects of various public health responses.  Throughout this model building process, we regularly engaged with the IAG and representatives from other peak bodies and public health units to iteratively refine details and assumptions (described in Box 1 and Figure 1).  

To address the questions of interest to the IAG, we used the model to simulate and analyse a number of outbreak response scenarios. We designed the scenarios in consultation with public health service providers working closely with communities (with options varying by jurisdiction and community). These included:

  • Case isolation, with or without an exit test, and with various expected delays between case identification and response;
  • Case isolation and quarantining the contacts of a case (based on different definitions of contacts), with or without exit tests, and with or without tests on entry to quarantine;
  • Case isolation and population lockdown (entire community quarantined), with or without exit tests, and with various levels of assumed compliance to lockdown.

Box 1. Brief model summary. The individual-based, computational model we designed simulated the “silent” introduction of SARS-CoV-2 into a remote community of either 100, 500, 1000 or 3500 people, the subsequent transmission of SARS-CoV-2 within the community, and the public health response. The model explicitly represented the infection status of each community member, as well as their age and place of residence within the community, which were tracked and updated daily.  Community members were assumed to have close family connections across multiple dwellings in the community (their so-called “extended household”), between which their time at home was distributed, and within which they were at higher transmission risk compared to individuals staying in different dwellings (Figure 1a).  Infected community members were further classified according to whether or not they would present to healthcare services for testing (if symptoms developed and were recognized, and fear/stigma did not prevent individuals from presenting, Figure 1b). At the time we developed our model, there had been no  SARS-CoV-2 transmission in Australian Aboriginal and Torres Strait Islander communities.  Therefore, our model was parameterized based on the experience of SARS-CoV-2 in other populations [6], but accounting for the expected increase in transmission due to enhanced mixing anticipated in interconnected and overcrowded households [2,3].  

Two images: a) graphic showing population model with infectious and not infections people in various types of households in the community
b) flowchart with details on internal state of the disease model in the Infected phase
Figure 1. Schematic representation of the individual-based model. The model simulates the “silent” introduction of SARS-CoV-2 into a remote community, the subsequent transmission of SARS-CoV-2, and the public health response.  Here we illustrate the structure of the (a) population model; and (b) disease model.

To gain an understanding of the range of possible epidemic outcomes, we used our model to run 100 simulations of each outbreak response scenario  (defined by a set of parameters controlling the transmission of SARS-CoV-2, the public health response, and the assumed response of community members to the response).  For different response scenarios, we compared and reported the median and interquartile range of several model outputs of interest, including the percentage of the community who were infected at the peak of the outbreak (peak infection prevalence) and by the end of the outbreak (the attack rate), the number of cases identified versus the number of cumulative infections over time, the total number of person-days community members were in quarantine for, and the number of tests performed.  

We sought regular feedback on the response scenarios considered, and our interpretation and communication of model outputs.  This ensured we were always addressing relevant questions and faithfully relaying our findings (summarised in Box 2 and Figure 2). 

Our work informed both the CDNA National Guidance for remote Aboriginal and Torres Strait Islander Communities for COVID-19 [7] and the Australian Health Sector Emergency Response Plan for Novel Coronavirus (COVID-19) [8].  We have since submitted a publication for peer-review describing our work, currently available as a pre-print [9].  We also worked together with the IAG to develop a plain-language document containing key messages for health services [10], and a plain-language presentation [11] containing key messages for Health service decision makers and community leaders to consider when deciding how a remote community will respond to a COVID‐19 outbreak.   

To date, efforts to protect Australian Aboriginal and Torres Strait Islander peoples from COVID-19 are working – there have been no incursions of SARS-CoV-2 into remote Australian Aboriginal and Torres Strait Islander communities, and the incidence of locally-acquired cases among all Australian Aboriginal and Torres Strait Islander peoples is six-times lower than the Australia-wide incidence [12].  

Box 2. Brief summary of findings. Our analysis indicated that without an effective public health response, an introduction of SARS-CoV-2 into a regional or remote Australian Aboriginal and Torres Strait Islander community would likely result in rapid spread.  Furthermore, multiple secondary cases would likely be present in a community by the time the first case is identified, indicating that capacity for early case detection and a prompt response would be crucial in constraining an outbreak.  A response involving case isolation and quarantining of close contacts of cases defined by extended household membership was found to significantly reduce peak infection prevalence compared to the non-response scenario, but subsequent waves of infection consistently led to unacceptably high attack rates in excess of 80% in modelled scenarios.  Rapidly initiating an additional 14-day, community-wide lockdown of non-quarantined households could reduce the attack rate to less than 10%, but only if compliance with the lockdown was at least 80% (Figure 2).

Chart showing comparisons of epidemic curves based on different model assumptions
Figure 2. Impact of initiating a 14-day lockdown in addition to case isolation and quarantining of contacts with entry and exit testing on epidemic control. Epidemic curves for a community of 1000 individuals with various levels of individual compliance with community lockdown [9]

References

[1] Chen T, Wu D, Chen H, Yan W, Yang D, Chen G, Ma K, Xu D, Yu H, Wang H: Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study. Bmj 2020, 368. https://doi.org/10.1136/bmj.m1295

[2] Australian Institute of Health and Welfare: The health and welfare of Australia’s Aboriginal and Torres Strait Islander peoples: 2015. In. Canberra: AIHW; 2015. https://doi.org/10.25816/5ebcbd26fa7e4

[3] Koh D: Migrant workers and COVID-19. Occupational and Environmental Medicine 2020:oemed-2020-106626. https://doi.org/10.1136/oemed-2020-106626

[4] Chisholm RH, Crammond B, Wu Y, Bowen A, Campbell PT, Tong SY, McVernon J, Geard N: A model of population dynamics with complex household structure and mobility: implications for transmission and control of communicable diseases. PeerJ 2020, 8:e10203. https://doi.org/10.7717/peerj.10203

[5] Hui BB, Gray RT, Wilson DP, Ward JS, Smith AMA, Philp DJ, Law MG, Hocking JS, Regan DG: Population movement can sustain STI prevalence in remote Australian indigenous communities. BMC Infectious Diseases 2013, 13:188. https://doi.org/10.1186/1471-2334-13-188

[6] Sanche S, Lin YT, Xu C, Romero-Severson E, Hengartner N, Ke R: High Contagiousness and Rapid Spread of Severe Acute Respiratory Syndrome Coronavirus 2. Emerg Infect Dis 2020, 26(7). https://doi.org/10.3201/eid2607.200282

[7] Communicable Disease Network Australia: National Guidance for remote Aboriginal and Torres Strait Islander Communities for COVID-19. 2020, Department of Health, Commonwealth of Australia [https://www.health.gov.au/resources/publications/cdna-national-guidance-for-remote-aboriginal-and-torres-strait-islander-communities-for-covid-19]

[8] Department of Health, Commonwealth of Australia. Australian Health Sector Emergency Response Plan for Novel Coronavirus (COVID-19). 2020, Department of Health, Commonwealth of Australia [https://www.health.gov.au/resources/publications/australian-health-sector-emergency-response-plan-for-novel-coronavirus-covid-19]

[9] Hui BB, Brown D, Chisholm RH, Geard N, McVernon J, Regan DG: Modelling testing and response strategies for COVID-19 outbreaks in remote Australian Aboriginal communities. medRxiv 2020, 2020.10.07.20208819. https://doi.org/10.1101/2020.10.07.20208819

[10] Department of Health, Commonwealth of Australia. COVID-19 Testing and Response Strategies in Regional and Remote Indigenous Communities: Key Messages for Health Services. 2020, Department of Health, Commonwealth of Australia [https://www.health.gov.au/resources/publications/covid-19-testing-and-response-strategies-in-regional-and-remote-indigenous-communities-key-messages-for-health-services]

[11] Department of Health, Commonwealth of Australia. Impact of COVID-19 in remote and regional settings. 2020, Department of Health, Commonwealth of Australia [https://www.health.gov.au/resources/publications/impact-of-covid-19-in-remote-and-regional-settings]

[12] Aboriginal and Torres Strait Islander Advisory Group on COVID-19. Aboriginal and Torres Strait Islander Advisory Group on COVID-19 Communique Update: 14 December 2020. Department of Health, Commonwealth of Australia [https://www.health.gov.au/resources/publications/aboriginal-and-torres-strait-islander-advisory-group-on-covid-19-communiques]

Postdoctoral Research Assistant 

Department of Statistics and the Wellcome Centre for Human Genetics
University of Oxford

Closing Date:30th July 2021

Grade 7: £32,817 – £40,322 p.a. 

We invite applications for a postdoctoral research assistant to develop predictive models for how DNA sequences impact regulatory networks, and apply these models to new single-cell datasets including for both gene expression, and chromatin accessibility (openness) during meiosis. The successful candidate will create new techniques integrating information from genomic DNA sequences, to perform mixture decomposition of sparse data matrices, and non-linear prediction, among other goals. We anticipate the resulting methods will be widely applicable to provide a technique for identifying the role of mutations, for example those identified in genome-wide association studies, in impacting gene expression in general. The postholder will work jointly at the Department of Statistics and the Wellcome Centre for Human Genetics. The post holder will join Oxford’s leading genomics research community, and the project may involve international collaboration and potential visits to collaborating groups.

The successful candidate will hold or be close to completion of a PhD/DPhil in a relevant quantitative scientific discipline, for example statistics, machine learning, mathematics, statistical or population genetics, or related disciplines. They also should have experience in developing and applying novel statistical methods, and low-level programming. Experience in analysing high-dimensional datasets, for example in computational statistics, machine learning, is highly desirable. They should have a strong interest in biological problems, genetics and/or genomics, but previous experience is not essential.

Queries about this post should be addressed to: Professor Simon Myers at myers@stats.ox.ac.uk.

This post is fixed-term until 10 September 2023.

Only applications received before 12.00 midday on 30 July 2021 will be considered. Interviews will be held on 25 August 2021.

For more information and to apply, click here.

Postdoctoral Research Assistant

Department of Statistics and the Wellcome Centre for Human Genetics
University of Oxford

Closing Date: 30th July 2021

Grade 7: £32,817 – £40,322 p.a 

We invite applications for a PDRA to develop statistical methods to study differences in healthy phenotypes and disease risks between human populations, and apply these to Biobank-scale datasets. This work aims to develop improved approaches to genetic prediction of disease risk by combining information among groups and/or modelling the evolution of traits through time.

The post holder will develop methods to understand whether strong differences in identified genetic predictors in different human populations, and lack of transferability of polygenic scores among human groups, reflect mainly genetic or environmental differences. They will also map the origins of disease-causing rare variants in time, and at fine geographic scales for example within regions of the UK, in order to understand the applicability of rare variant discoveries to other regions or populations. Leveraging genealogical approaches previously developed within the group represents a natural start-point for this project, but it will also be essential to integrate functional information and to leverage large-scale data on both phenotypes and variation, for datasets incorporating a range of ancestries. The UK Biobank and Genomics England data, in which we have ongoing work, provide two important examples.

This position is based jointly within the Department of Statistics and the Wellcome Centre for Human Genetics. The post holder will join Oxford’s leading genomics research community, and the project may involve international collaboration and potential visits to collaborating groups.

The successful candidate will hold or be close to completion of a PhD/DPhil in a relevant quantitative scientific discipline, for example statistics, machine learning, mathematics, statistical or population genetics, or related disciplines. They also should have experience in developing and applying novel statistical methods, and low-level programming. Experience in analysing high-dimensional datasets, for example in computational statistics, or machine learning, is highly desirable. They should have a strong interest in biological problems, genetics and/or genomics, but previous experience is not essential.

Queries about this post should be addressed to: Professor Simon Myers at myers@stats.ox.ac.uk.

This post is fixed-term until 10 September 2023. Only applications received before 12.00 midday on 30 July 2021 will be considered. Interviews will be held on 25 August 2021.

For more information and to apply, click here.