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David T. Levy, Ph.D. Lombardi Comprehensive Cancer Center
Computational Models
Simulation models/computational models are used in other fields, but are increasingly common in public health, especially in the fields of tobacco control and obesity
Models are especially useful where there are dynamic systems with many stages (e.g., policy -> environment -> behaviors -> health outcomes) and where the effects unfold over time.
Models attempt to make the connections between stages across stages and over time explicit, focusing on the movement of whole system rather than an isolated part
Characteristics of Modeling
Generally combine data and parameters from
different sources
Provides structure by developing a framework
and making assumptions explicit
Incorporates the effects that are difficult to
distinguish empirically in statistical studies
Non-linear relationships
Interdependencies
Dynamic processes
Feedback loops
Types of Model
Macro-simulations: groups of individuals (e.g., current, former and never smokers)
Uni-directional causality
Systems dynamic (feedback loops)
Micro-simulations: individuals in proportion
to their composition in the population
Monte-Carlo
Agent-based and network models; make
explicit assumptions about behaviors
Tobacco Control and Smoking
Tobacco control policies provide an
example of one the greatest public health
success stories – important to study what
type of policies work in tobacco control
and lessons for other public health risks
Smoking is a behavioral risk factor with
clearest link to cancer- can study the role
of dose, duration, and age; and the
interaction with other non-cancer chronic
diseases
What is SimSmoke? • SimSmoke simulates the dynamics of smoking rates
and smoking-attributed deaths in a State or Nation,
and the effects of policies on those outcomes.
• Compartmental (macro) model with smokers, ex-smokers and never smokers evolving through time by age and gender.
• Focus on tobacco control policies Effects vary by:
depending on the way the policy is implemented,
by age and gender
the length of time that the policy is in effect
Nonlinear and interactive effects of policies
SimSmoke: Basic Approach
Policy
Changes Taxes
Clean air laws
Media Camp.
Marketing
Bans
Warning labels
Cessation Tx
Youth Access
Cigarette
Use
Smoking-
Attributable
Deaths Total Mortality and
by type:
Lung cancer
Other cancers
Heart disease
Stroke
COPD
MCH Outcomes
Norms,
Attitudes,
Opportu-
nities
Former and
current
smokers,
relative risks
Relationship between policies and
smoking rates based on:
Evidence from tobacco and other risky behavior
literature,
Theories (Economics, Sociology, Psychology,
Epidemiology, etc), and
Advice by a multidisciplinary expert panel
Policies based on FCTC/MPOWER
Cigarette excise taxes: Through prices
Smoke-Free Air Laws: Worksites, restaurant and bars, other public places
Tobacco control/media campaigns
Marketing/Advertising Bans
Health Warnings
Cessation Treatment: Availability of
pharmacotherapy, cessation treatment (financial
access, quitlines and web-based treatment
Youth access (minimum purchase age): enforcement and vending and self-service bans
Past vs. Future
Tracking Period- starts from year where requisite
data available, e.g., 1993 for most US models, and
continues to the current recent year. The tracking
period is used to:
Calibrate the model- adjust the parameters
Validate the model- test how well it predicts
Examine the role of past policies
Future Projection- examine the effect of policies
from current year forward, e.g., the effect of a ciga-
rette tax increase or the ability to reach the Healthy
People 2020 smoking prevalence goal of 12%
Models built for:
32 Countries:
Albania*, Argentina*, Bangladesh, Brazil,* China,
Czech Republic,* Egypt, Finland,* France,*
Germany,* Great Britain,* India, Indonesia,
Ireland,* Italy,* Japan,* Korea*, Malaysia,
Mexico, Netherlands*, Pakistan, Poland,
Philippines, Taiwan*, Russia, Spain, Sweden,
Thailand,* Turkey, Ukraine, US,* Vietnam*
6 States: Arizona*, California*, Kentucky*,
Massachusetts, Minnesota,* NY
* Paper published
• ADVOCACY: Justification by forecasting future tobacco use and
health outcomes and showing the effect of past policies
• PLANNING:
• Estimate the likely impact of alternative interventions in
specific situations and on specific populations
• Assess and rank strategies for reaching goals prior to
commitment of resources
• Develop more systematic surveillance and evaluation
networks
• HEURISTIC: Understanding the complex network of policies
surrounding tobacco use and health outcomes at
research and policy-making levels.
Policymakers have used models for:
Counterfactuals: Brazil
Past Policies 1989-2010 To consider the effect of all policies implemented since 1989,
we first set policies through 2010 to their 1989 levels to obtain
the counterfactual smoking rates in the absence of post-1989
policies.
The difference between the smoking prevalence with polices
at 1989 levels and the smoking rate with actual policies
implemented yields the net effect of policies implemented
since 1989.
For the role of single policies, we compared the scenario with
only that policy implemented to the counterfactual policy
scenario.
The impact of policies on deaths was estimated by subtracting
the number of SADs with policies implemented from their
number with policies kept at 1989 levels.
Brazil Counterfactuals:
Smoking prevalence 1989-2010
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
45.0%
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Status quo Counterfactual price only
Percent of the Reduction in 2010 Smoking Prevalence*
Due to Individual Policies Implemented Since 1989
48.4%
13.6%
6.3%
13.7%
7.8%
9.8% 0.3%
Price only Smoke-Free Air only Media onlyAdvertising only Health warnings only Cessation tx onlyYouth Access only
Effect of Policies Implemented:
1989-2010 Policy Implementation Year
1989 2000 2010 2010 Lower
Bounda
2010 Upper
Bounda
2050
SMOKING PREVALENCE
Counterfactual: all policies
at 1989 level 35.4% 32.6% 31.0% 24.9%
All policies implemented 35.4% 23.7% 16.8% 22.2% 10.5% 10.3%
Percent reduction in smoking prevalence from policy changea
All policies −27.4% −45.9% −27.8% −66.4% −59.1%
SMOKING ATTRIBUTABLE DEATHS
1989 2010 Cumulative 2010 2010 Lower
Bounda
2010 Upper
Bounda
Cumulative 2050
Counterfactual: all policies at
1989 level
181,957 283,048 4,998,024 20,401,516
All policies implemented
181,957 225,048 4,578,810 4,739,196 4,282,963 13,471,388
Deaths averted from policy change
All policies — 58,000 419,214 258,828 715,061 6,930,128
Low birth weight babies avoided from policy changes 1989-2010
With ;policies implemented 14,827 704,976
Advocacy: Other successes due to tobacco
policies
Percent reduction in smoking prevalence (18 and above):
> 30% reduction
Brazil (almost 50% reduction due to policies)
California
At least 25% Reduction
United Kingdom
Minnesota
Thailand
20% Reduction
Arizona
Korea
Ireland
NYS
Netherlands
Advocacy: There may be limits to current policies:
We may need more than traditional policies to
reduce smoking by more than 50%
Those with the weakest current policies (e.g., Russia
and China) show the potential for largest reductions
in smoking prevalence, with forecasts of about a 50%
reduction in smoking prevalence in going from very
limited policies to fully FCTC-consistent policies
How can we surpass a 50% reduction?
Improved cessation treatments, e.g. better and more tailored
interventions with follow-up and integrated services
May need to alter the tobacco products available, e.g., reduce
nicotine and other addictive constituents or disallow current
cigarettes in favor of safer forms of tobacco
Planning: Male Smoking Prevalence: SimSmoke Predictions vs. Surveys, Minnesota
10.0%
12.0%
14.0%
16.0%
18.0%
20.0%
22.0%
24.0%
26.0%
28.0%
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
SimSmoke CPS-TUS MATS
Ireland Male Smoking Prevalence,1998-2010
data, data, data
Mexico: Many surveys
ENA, ENAULT, GATS
Ask different questions, may have
important implications for some day
smokers vs every day smokers
Planning: Ranking the effect of future policies
Brazil SimSmoke smoking prevalence
Policies/Year
2010
2015
2050
Lower
Bound
Upper
Bound
Cumu-
lative
2011–
2050
Lower
Bound
2011–
2050
Upper
Bound
2011–
2050
Smoking Prevalence
Smoking Attributable
Deaths
Status quo 16.8% 15.5% 10.3%
All FCTC policies implemented 16.8% 11.9% 6.3% 7.3% 4.7%
8,892,578 9,513,874 8,749,842
Reduction in Smoking
Prevalence 7,563,664 8,657,395 6,783,055
Independent policy effects
Tax at 75% of retail price −10.2% −16.7% −13.0% −21.5%
469,463 365,730 565,492
Well-enforced smoke-free air
laws
−4.5% −6.4% −3.1% −9.5%
268,042 135,972 396,336
Well-enforced marketing ban −3.0% −4.8% −2.4% −7.2%
171,180 86,231 254,867
High-intensity media campaign −4.8% −7.4% −3.6% −10.9%
305,436 157,126 459,018
Cessation treatment programs −2.3% −4.6% −6.9% −9.3%
198,382 100,530 489,257
Well-enforced youth access restrictions −0.8% −5.1% 0.0% −10.1% 28,491 0 42,734
With all policies implemented −23.5% −38.5% −29.0% −54.0% 1,328,914 856,474 1,966,787
Planning: Health Effects Delayed
SimSmoke Projections Smoking-Attributable Deaths Status Quo vs. All FCTC Policies for Finland
More immediate impact on
heart disease and maternal
and child health
Planning: There may be limits to current policies:
We may need more than traditional policies to
reduce smoking by more than 50%
Those with the weakest current policies (e.g., Russia
and China) show the potential for largest reductions
in smoking prevalence, with forecasts of about a 50%
reduction in smoking prevalence in going from very
limited policies to fully FCTC-consistent policies
How can we surpass a 50% reduction?
Improved cessation treatments, e.g. better and more tailored
interventions with follow-up and integrated services
May need to alter the tobacco products available, e.g., reduce
nicotine and other addictive constituents or disallow current
cigarettes in favor of safer forms of tobacco
25
FDA Public health standard
“Public health standard” calls for the review of the scientific evidence
regarding
1. Risks and benefits of the tobacco product standard to the population
as a whole, including both users and non-users of tobacco products;
2. Whether there is an increased or decreased likelihood that existing
users of tobacco products will stop using such products; and
3. Whether there is an increased or decreased likelihood that those who
do not currently use tobacco products, most notably youth, will start
to use tobacco products
Example: Mandatory “product standards” that would limit the allowable levels of
ingredients in tobacco products (menthol, nicotine, etc)
Planning: Modeling the effects of a ban on menthol cigarettes
Possible effects of a ban:
Menthol smokers switch to non-menthol brand.
Menthol smokers quit at differential rate than if non-menthol smoker.
Some individuals who would have initiated smoking with menthol cigarettes never start.
Scenarios investigated:
1. 10% of the former menthol smokers quit and 10% of those who would have initiated as menthol smokers never smoke;
2. 20% quit and 20% do not initiate, and;
3. 30% quit and 30% do not initiate
27
Pl a n n i n g M o d e l i n g a M e n t h o l B a n U s i n g S i m Sm o k e
Past literature suggests youth access policies
lead to increased retail compliance.
Effects on actual smoking rates are unclear. Two
potential reasons
Role of non-retail sources of cigarettes (parents older
friends theft)
Level and extent of policies
Heuristic: Youth Access Policy
Heuristic: Policy Components Affecting
Enforcement Compliance
Checks Per
Year
Penalties Publicity/
Education
Compliance
Multiplicative relationship
S-shaped curve, subject to
substitution into other sources
Reduced Smoking
Originally applied to youth access, but applies to marketing restrictions and smoke-free air laws
Anti-tobacco
Norms
Current
Smoker
Attempts
to Quit
No quit
attempt
Continues
Smoking
Self Quit
Rx Pharm.
NRT OTC
Behavioral
Treatment
Behavioral
& Rx
Pharm
Behavioral
& NRT OTC
Success
Fail
Success
Fail
Success
Fail
Success
Fail
Success
Fail
Success
Fail
Heuristic: The Decision to Quit
Framework used to show effects for specific policies
Heuristic: Cessation Treatment Policies
AVAILABILITY: Ability to obtain NRT, Buproprion and Varenecline by Rx or over-the counter
FINANCIAL ACCESS: payment or mandatory coverage for cessation treatments Prescription or OTC pharmacotherapies alone
Behavioral treatment alone
Pharmacotherapies and behavioral
QUITLINES: delivered by government and coordinated through health care system
BRIEF INTERVENTIONS: delivered by health care providers
Web-based treatment: supervised and used by health care agencies of provider
Follow-up of Care: health care providers, quitlines, web
Each of the above affects quit attempts and treatment use with potential interactions (synergies among policies)
Harm reduction: As a substitute for cigarettes (provides the nicotine fix), it has been suggested that use of at least some smokeless can reduce overall harm, because of lower health risk, similar to methadone for heroine addicts.
Smokeless risks less than cigarettes (which are not inhaled into lung), but depends on contents, also no second hand smoke.
Potentially harm increasing, if:
If smokeless leads to increased youth initiation and acts as a gateway to cigarettes
Encourages dual use with cigarettes instead of cessation from cigarettes
Heuristic: Smokeless as Harm Reduction
Heuristic: Health effects and polytobacco use: simple example with only cigarettes and smokeless
Sole
cigarette
use
(habit)
Sole
smokeless
us
(habit)
Initiation
cigarette
use
Initiation
smokeless
use
Dual
cigarette &
smokeless
habit
Cigarette
only
attributable
death
Dual use
attributable
death
Smokeless
only
attributable
death
Need to know relative risks for those who continue to use and for former users
34
Tobacco Use in Sweden, Males, 2004 -2020
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
16.0%
18.0%
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Male Cigarette Use (alone) Male Snus Use (alone) Male Combined Snus and Cigarette Use
Declines in cigarette use
accompanied by constant rates of
sole and dual use of snus,
suggesting that users are shifting
from single to dual use
35
New Tobacco Products
Will be important to consider whether
smokers become new users or dual users
Whether youth use these products instead
of cigarettes and whether they eventually
use cigarettes
Whether former smokers use these
products and then become smokers
Heuristic: Tobacco control is complex:
Modeling provides a framework
Industry behavior Tobacco, retail
Tobacco Control Policy Taxes, laws, regulations
Environment Attitudes, norms,
opportunities (economic,
other)
Physiology Genetics, diet, other
Risky behaviors: Using
cigarettes, cigars, and
smokeless and other
non-combustibles
Health Outcomes Death, disease, dollars
Limited evidence for many of these linkages,
models provide guidance on areas for future research
Heuristic: Future challenges for Sim-
Smoke and tobacco control modeling
Better understanding of the initiation and cessation process
Constantly changing market with new products and dual
uses for cigarettes, smokeless, cigars, and pipes; transitions
in the use of the different products is unlikely to be stable
Difficult to anticipate industry reactions to policies both in
consumer markets and in the political arena
Need to consider the heterogeneity of nations and
individuals; tobacco users are increasingly low SES in MICs
and general population in LMICs with economic growth
Collaborative Modeling
Since different models will highlight different aspects of
the problem, information from the different models
will need to be combined in a systematic manner
An example is NCI’s CISNET program:
The models consider common research questions using a natural
history of disease framework
The models use a common data sources to help identify reasons for
any differences results
The results are compared to provide a reasonable range of
outcomes for decision-makers
Models are well documented using publicly available model profiler
Georgetown University is home for smoking/lung group Levy
and coordinating center for the breast cancer group
Para la elaboración de constancias,
favor de enviar lista de
participantes presenciales con:
Profra. Berta Luz Téllez
Videos y presentaciones anteriores en:
http://www.inspvirtual.mx
-Videoconferencias
https://www.facebook.com/videoconferenciasinsp