Week 8 Flashcards

1
Q

What are mathmatical models?

A

Using mean, median, mode etc
To model relationships and differences

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2
Q

What is the function of models?

A

To help us understand:
Past
Present
Future

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3
Q

What is an example of models for understanding the past?

A

Used to estimate the effects of non-phamaceutical interventions on COVID-19 in Europe?

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4
Q

What was the estimated effect of non-phamaceutical interventions on COVID-19 in Europe?

A

Lockdowns- ~80 reduction in transmissions
Reducing public events, school closure, self isolation and social distancing all around 5% reduction

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5
Q

What is an example of understanding the present?

A

Modelling Uk infections of COVID-19 showing fluctuations with a general decrease

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6
Q

What is an example of understanding the future?

A

Using models to predict the behaviour of COVID infections
Susceptible people –> Infected –> Resistant
Susceptible and resistant –> Escape variant –> resistant to new varient

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7
Q

What challenges does future modelling present?

A

spread available vaccines to more people in single doses?
or - complete two-dose regimes?

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8
Q

What are the effects of vaccinating more with a single dose?

A

decrease n infections circulating
reduce reproductive number of all variants (reduces S)
potentially increase probability of transmission

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9
Q

How does future modelling impact future policy?

A

Resistance after one vs two doses
Impact on the number of severe cases

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10
Q

What is needed to commicate models?

A

Trustworthiness - product of people, systems and processes within organisations that enable and support production of stats and data
Quality - stats fits their intended uses are based on appropriate data and methods, and are materially misleading
Value - statistics and data are useful, easy to access, remain relevant and support understanding of important issues

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11
Q

How do real-world social networks influence measures used to combat the spread of the SARS-CoV-2 virus?

A

Network derived from high-resolution GPS data, from citizen science-generated social network:
Seen in BBC’s ‘Contagion! The BBC Four Pandemic’

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12
Q

What is an overview of BBC’s contagion?

A

Data collected in autumn 2017 - to simulate the spread of a highly infectious flu
Hannah Fry acted as ‘Patient Zero’ by walking the streets of Haslemere in Surrey to launch an outbreak

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13
Q

What is the context for BBC’s contagion?

A

In absence of vaccine
Isolation of symptomatic individuals & quarantining of their contacts
High reproduction number in early outbreak
High transmission from pre- and asymptomatic individuals
Similar to early Covid

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14
Q

How did BBC’s contagion measure spread of disease?

A

Used public dataset on human social interactions
Contact = dyads ≥ 1 daily 5 min at ≤ 4m
Tested effects of:
test, trace, isolation and quarantine
social distancing strategy
‘test and release’

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15
Q

What were the main conclusion of BBC’s contagion?

A

No control – 75% population infected within 70days
Isolation of infected individuals - 66%
Primary contact tracing (+ quarantine) – 48%*
Secondary contact tracing (+ quarantine) – 16%*
*results in large numbers of people in quarantine

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16
Q

What are the effects of social distancing measures?

A

High social distancing reduced overall cases by 28-61%
Led to lower proportion of quarantine

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17
Q

What are key factors for limiting spread?

A

Tracing and quarantining contacts of contacts (secondary)
Combining social distancing with contact tracing

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18
Q

What were the limitations for BBC’s contagion?

A

Data from single small town
Short period of time
Not everyone involved in the town (<13 years old excluded)
Pre-covid

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19
Q

What is an overview of transmissibility, prevalence and patterns of movement?

A

Central to:
Impact of pandemic
Design of effective control strategies

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20
Q

What is an overview of evolutionary trees for pandemics?

A

Key insights into spread of SARS-CoV-2
Investigation of individual outbreaks
Transmission chains in specific settings

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21
Q

What is the use of phylodynamics for pandemics?

A

Track virus genetic changes
Identify emerging variants
Inform public health strategy

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22
Q

What is an overview of multiple sequence allignment?

A

Alligne DNA sequences of different organisms and compared the differences to judge the base sequence and the evolutionary tree

23
Q

What is an overview of the information that goes into making models?

A

Location of case, important or local, nosocial/occupational infections, phenotypes and increased transmissibility, re-infections or chronic infections, phylogenies and epidemiology

24
Q

What information is used from models on infectious diseases?

A

Decisions on public health
Epidemiological parameters
Clinical parameters

25
Q

What are examples of R numbers model parameters of SARS-Cov-2?

A

Australia - 24/03/20 – 29/04/20 R = 1.08
Iceland - 18/03/20 – 29/04/20 R = 1.4
Taiwan - 27/03/20 – 29/04/20 R = 1.02

26
Q

What is an overview of the convergent evolution in Covid?

A

Convergent evolution of SARS-Cov-2 spike protein
Phylogenies of first year of the pandemic show the independant emergence of spike deltaH69/19 in genomes of B.1.1.7 and B.1.258 lineages

27
Q

What is an overview of cancer?

A

A disease involving unregulated cell growth
Cells divide and grow uncontrollably, forming malignant tumors
Invade nearby parts of the body
Cancer may also spread to more distant parts of the body Through the lymphatic system of bloodstream.

28
Q

What are hallmarks of cancer?

A

Tissue invasion and metastasis
Inflammatory microenvironment
Insensitivity of growth inhibitors
Self-sufficiency in growth signals
Limitless replicative potential
Sustained angiogenesis
Evasion of apoptosis

29
Q

What is the evolution of cancer?

A

Cancer has existed as long as animals. An Osteosarcoma has been identified in a 150 million year old dinosaur bone.
Cancer is found across many taxa

30
Q

What is the history of cancer discovery?

A

Cancer was described by Hippocrates (ca 460-ca 370 BC) calling them “carcinos” (crab)
The first cause of cancer identified by British surgeon Percivall Pott - in 1775
Cancer of the scrotum common in London chimney sweeps
Historical records of cancer incidence are unreliable – has cancer incidence increased over time?

31
Q

What modern life factors increase cancer risk?

A

Less sunlight exposure
More migration
Children are protected from infection
Longer life
More carcinogen exposure
Change in diet

32
Q

What is an overview of the research into cancer incidence by Armitage and Doll?

A

Age-incidence curves of most common epithelial cancers show rapidly increasing rates after the 4th–5th decades of life

33
Q

What is the overvire of Leslie Foulds and neoplastic development?

A

Foulds traces the rudimentary beginnings of the tumor progression concept
Followed thoughts first expressed by Haaland in 1911, Rous and Beard (1935) and H. S. N. Greene(1940).
But Foulds first thought out and clearly expressed the principles of tumor progression

33
Q

What was Armitage and Doll number of events for tumour development?

A

Classic mathematical models of tumour development developed by Armitage and Doll (1954) suggested that 5–8 rate-limiting events required to generate these patterns

34
Q

What are the stages of human colorectal cancer development?

A

Normal epithelium –> Hyperproliferative epithelium –> Small adenoma –> Large ademoma –> Colon carcinoma

35
Q

What are examples of mutations in human colorectal cancer that lead to next stage?

A

Normal epithelium –> Hyperproliferative epithelium –> APC mutation
Small adenoma –> Large adenoma –> K-ras mutation

36
Q

What is an overview of cancer cell initial development?

A

10^13 cells in the human body.
One cell can become a cancer and kill the patient.
Cancer clone evolution occurs within a tissue ecosystem that is set up to avoid cancer development

37
Q

What is the balance of regular cells for becoming cancer cells?

A

Many normal process have properties similar to those of cancer:
Self renewal
Angiogenesis
Cell migration
Invasion

38
Q

What are contraints to cancer growth?

A

Immune system; cell mortality; resource limitations; oxygen supply; compartmentalisation

39
Q

What is the difference between cancer and tumour doubling times?

A

Doubling time of cancer cells (1-2 days) is orders of magnitude less than the doubling time of a tumour (60-200 days); implying that most cancer cells die

40
Q

What factors promote cancer development?

A

Carcinogen exposure; genetics; absence of diet/exercise; infection; hormonal levels; radiation exposure; chemotherapy

41
Q

What is the process of cancer evolution?

A

A process of clonal evolution eg mutates for survival then proliferate then small population evovle chemotherapy
eg Treatments can prune off non-drug resistant cancers leaving only drug resistant strains

42
Q

What happens in the evolution of cancer?

A

Bottlenecks/selective pressure
Progentitor cell –> some become cancerous –> treatments further bottleneck population

43
Q

What does evolution of cancer mean for issues for treatment?

A

Influence of ecosystem
Need for ‘Darwinian bypass’, e.g. target normal cells supporting the cancer

44
Q

What is an overview of the clonal evolution of cancer with topographical seperation?

A

Foetal B lineage –> Intraplacental vascular anastomoses –> Monozygotic twins with concordant leukaemia
Embryonic germ cell progenitor –> Urogenital ridge migration/testis morphogenesis –> Bilateral testicular cancer

45
Q

What are used to sequence cancer?

A

Genome sequencing –> decreased hugely allowing for genome sequencing on a large scale

46
Q

How has DNA sequencing allowed for greater understanding of breast cancer?

A

Differences in mutations occurance
TP53 example of commonaly mutated
STK11 rarely mutated

47
Q

What can be the difference between cancer within a person?

A

Analysis of 100 single cells from a polygenomic breast tumour
Shows a great genetic diveristy of genotype
In example - 3 major subtumours within the cancer

48
Q

What is an example of transmissible cancer?

A

Devil facial tumour disease

49
Q

What is an overview of Devil facial tumour disease?

A

Spreads through devils fighting
Slowly spread across Tasmania first indentified in 1996
Caused population decline by 80%

50
Q

What was the response to the spread of Devil facial tumour disease?

A

Mitochondrial variants in cancer shows 21 different subtypes
Strong selective pressure on Devil’s showed that they have evolved resistance and to reproduce earlier, noticed in 2005
Selective pressure on cancer to become less severe noticed in 2015

51
Q

How have tasmanian devils become resistant to DFTD?

A

Rapid evolutionary response to DFTD. Identifed two genomic regions containing genes (related to immune function / cancer risk in humans) that exhibit concordant signatures of selection across three populations

52
Q
A