1. bookVolume 31 (2022): Issue 1 (March 2022)
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2719-9509
First Published
01 Jan 1992
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4 times per year
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English
access type Open Access

Estimated Public Health Gains From German Smokers Switching to Reduced-Risk Alternatives: Results From Population Health Impact Modelling

Published Online: 05 May 2022
Volume & Issue: Volume 31 (2022) - Issue 1 (March 2022)
Page range: 35 - 51
Received: 27 May 2021
Accepted: 01 Mar 2022
Journal Details
License
Format
Journal
eISSN
2719-9509
First Published
01 Jan 1992
Publication timeframe
4 times per year
Languages
English
Summary Background

Smoking is associated with cancer and cardio-respiratory mortality. Reducing smoking prevalence will lead to fewer deaths and more life-years. Here, we estimate the impact of hypothetical introduction of reduced-risk products (heat-not-burn products and e-cigarettes) in Germany from 1995 to 2015 on mortality from lung cancer, chronic obstructive pulmonary disease, ischaemic heart disease, and stroke in men and women aged 30–79 years.

Methods

We used a previously described population health impact model, with individuals with a defined baseline cigarette smoking distribution followed under a “Null Scenario”, with reduced-risk products never introduced, and various “Alternative Scenarios” where they are. Transition probabilities allow product use to change annually, with the individual product histories allowing estimation of risks, relative to never users, which are then used to estimate reductions in deaths and life-years lost for each Alternative Scenario.

Results

In the Null Scenario, we estimated 852,000 deaths from cigarette smoking (42,600 per year), with 8.61 million life-years lost. Had everyone ceased smoking in 1995, and with no use of reduced-risk products, these numbers would reduce by 217,000 and 2.88 million. Compared to the Null Scenario, the estimated reductions would be 159,000 and 2.06 million with an immediate complete switch to heat-not-burn products and 179,000 and 2.34 million with 50% of smokers immediately switching to heat-not-burn products and 50% to e-cigarettes. In four Scenarios with a more gradual switch, the estimated decreases were 39,800–81,000 deaths and 0.50–1.05 million life-years, representing 17.5%–37.5% of the effect of immediate cessation in 1995. These estimates assume that switching to heat-not-burn products and e-cigarettes involves risk decreases of 80% and 95% of those from quitting, respectively. The reductions in mortality would be greater with more diseases and a wider age range considered or with a longer follow-up period, as the decreases increased markedly with time. Various limitations are discussed, none affecting the conclusion that introducing these new products into Germany in 1995 could have substantially reduced deaths and life-years lost.

Conclusions

Deaths from cigarette smoking could be substantially reduced not only by cessation but additionally by switching to reduced-risk products. Respective public health campaigns might increase such switching.

Keywords

INTRODUCTION

Smoking represents the greatest avoidable risk factor for health (1, 2). Nevertheless, the World Health Organization (WHO) estimates there will be 1.1 billion smokers globally in 2025 (3). In Germany, smoking prevalence is around 28%, with no change since 2016 (4), and numbers of quit attempts are currently decreasing (5). In 2013, an estimated 125,000 people died from smoking-related diseases in Germany (6).

Clearly, smokers would best quit all nicotine and tobacco use at once, but many do not. Recently, increasing numbers of public health experts institutions have embraced tobacco harm reduction as a complementary tool to existing control efforts (7,8,9,10,11,12). This is directed at adults who would otherwise continue to smoke conventional cigarettes (CCs), aiming to encourage them to switch to smoke-free alternatives such as snus, the e-cigarette (ECig), or the heat-not-burn product (HnB). The aerosols of ECigs and HnBs have been shown to contain toxicant levels lower by an average of > 90% compared with cigarette smoke (13,14,15).

The proof of principle for tobacco harm reduction comes from epidemiological findings spanning decades from Swedish smokers switching to snus, so that smoking rates and smoking-related mortality in Sweden are the lowest in Europe (16). The efficacy of ECigs in randomized controlled trials to support abandoning CCs (17), coupled with their high acceptance by smokers wishing to replace CCs, could explain the observation that ECigs have contributed to 50,000 to 70,000 additional smokers abandoning cigarettes in the UK per year (18). At the same time, youth initiation continues to be low in the UK and New Zealand (19, 20), and there seems to exist an inverse relationship between youth vaping and smoking (21), with common liabilities suggesting ECigs may have replaced CC smoking (22). In Japan, 20% of smokers have switched to HnBs, which plausibly contributes to the unprecedented drop in cigarette sales seen there (23). These facts suggest that both ECigs and HnBs could help to reduce smoking-attributed morbidity and mortality.

In Germany, ECigs have been available since 2007, current users now forming about 1–3% of the population aged 14 or over [(4), https://www.debra-study.info/], with a 30-day prevalence of 6.9% among young adults (24). HnB products only became available later, in 2016, with numbers of users estimated to have risen from about 36,000 in 2017 to 300,000 in 2019, then forming about 0.4% of the population aged 18 or over, according to Philip Morris market research, with others reporting 0.3% for overall current use (25) and 1.3% for 30-day prevalence among 18- to 25-year-old young adults (24), respectively. Both ECigs and HnBs are predominantly used by current or former smokers, and only by few never-smokers (4). Among 12- to 17-year-olds, use in the last 30 days, not necessarily a good marker for regular use, remains low at 4.1% for ECigs and 0.1% for HnBs (26).

Our main objective is to estimate the population health impact of introducing HnBs or ECigs into Germany during 1995–2015 under various assumptions about their rate of uptake. We compare our estimates to a set of extreme scenarios, including those derived assuming the whole population ceased smoking cigarettes immediately. The estimated effect sizes could inform cost-benefit assessments by German public health authorities and regulators on tools aimed at steering smokers away from cigarettes, preferably by cessation, but, for smokers continuing to smoke, also by switching to reduced risk products (RRPs). To avoid uncertainty about the future, including the effect on future mortality rates of factors such as medical progress and disease epidemics, we use a “hindcasting” approach, in which individuals start in 1995, with a nationally representative distribution of cigarette smoking, then being followed until 2015 under various assumptions. This approach has previously been used to assess the population health impact of introducing HnBs into the US (27, 28) and Japanese (29) markets. Here, we have considered both HnBs and ECigs. Both can be termed RRPs – products considered likely to present less risk of harm to cigarette smokers who switch to them.

The approach generates estimates of numbers of smoking-related deaths (SRD) and number of years of life lost (YLL) in scenarios where RRPs are or are not introduced, the difference between the two scenarios being termed the drop in deaths (DD) and number of years of life saved (YLS). These are calculated separately for the main diseases related to cigarette smoking, lung cancer (LC), chronic obstructive pulmonary disease (COPD), ischaemic heart disease (IHD), and stroke. While the term SRD normally refers to the additional deaths arising from cigarette smoking, here it is used to refer to the additional deaths arising from the use of cigarettes, HnBs, or ECigs.

MATERIALS AND METHODS
Outline of the approach used in population health impact modelling (PHIM)

The basic method used for estimating the impact of introducing an RRP into a country is as described earlier (30), and involves two components, the Prevalence (P-) component and the Epidemiologic (E-) component.

The P-component starts in a specified year with individuals of a given sex and age range with a defined cigarette smoking distribution. This group is then followed over discrete time intervals under a “Null Scenario” and various “Alternative Scenarios”, by using different sets of transition probabilities (TPs). In the Null Scenario, RRPs are never introduced, and each individual's cigarette smoking status (never, current, or former) is updated yearly. In each Alternative Scenario, RRPs are introduced during follow-up, and the TPs allow for switching between six groups (never user, current exclusive cigarette smoker, current exclusive HnB user, current exclusive ECig user, current multiple product user, and former product user). “Never users” have never used cigarettes or either of the two RRPs considered. “Current multiple product users” currently use two or three of the products considered, while “former product users” have previously used at least one product but currently do not use any. At the end of the P-component, each individual has a complete history of product use over the follow-up period under each scenario. The modelling ignores products other than cigarettes, ECigs, and HnBs.

The E-component then uses the product histories to estimate, for each individual, the relative risk (RR), compared to never users, of LC, COPD, IHD, and stroke for each follow-up year and scenario. The estimation involves an extension of the negative exponential model (NEM), allowing for multiple changes in use, fully described elsewhere (27). The NEM requires estimates of the RR for continued smoking for each of the four diseases, the quitting half-life (H) – i.e., the time from quitting when the excess relative risk (RR!1) declines to half of that for continuing smokers – and also estimates of the effective doses for current exclusive HnB use, exclusive ECig use, and multiple product use relative to that for current cigarette smoking (taken as one unit). The decline of the excess relative risk by time since quitting cigarette smoking is well described using a NEM for LC (31), COPD (32), IHD (33), and stroke (34).

The estimation of the RR for an individual does not specifically take into account the amount smoked, but the effective dose for multiple product users may be set to reflect a reduced cigarette consumption. A discussion of how the effective dose may be quantified for an RRP is given elsewhere (30).

For each scenario, the average RR for each disease for individuals of a given sex and age group is then calculated for each follow-up year, from which the proportions of SRD can be derived. These are then converted to numbers using national mortality estimates by sex, age group, and year. The differences in estimated numbers and proportions between the scenarios then quantify the effect of RRP introduction.

For a given scenario, YLL is estimated using the method of GARDNER and SANBORN (35). YLS is then calculated from the difference in YLL between the Alternative and Null Scenarios.

Each of the individuals in each scenario is followed up over the whole period considered, with no removals for death. While, the estimates of DD and YLS assume that the size of the populations of risk remains the same during follow-up, with no correction for differential survival, a correction can be made if required (30).

The methodology can also compare the Null Scenario with Alternative Scenarios where RRPs are not introduced but where different sets of TPs for cigarette smoking are used. The modelling starts with a population aged 10–79 years, individuals dropping out of the calculations as they reach 80 years of age. This is partly because cause of death certification is unreliable at an older age and partly as our estimates of population health impact also include YLS, which is unaffected by deaths above the age of 74 years.

Common features of each simulation

Each simulation involved follow-up of 100,000 individuals in 1-year intervals from 1995, with the product use status of each individual estimated at each year of follow-up until the year 2015 (or age 79, if that came earlier). For each situation described, separate simulations were conducted for each sex.

Population at baseline

As previously described (27), each individual in a simulation is allocated at the start of the P-component to a year of age, then to a cigarette smoking group (never, current, or former), and, then, for former smokers, to an age of quitting, based on random numbers and the relevant distributions for Germany.

The sex-specific age distributions used for Germany for 1995 are as published by the United Nations (36).

Sex- and age-specific distributions of current and former smoking prevalence for Germany for individual years from 1995 to 2015 were derived by combining data from three sources: International Smoking Statistics (37), which provides results by 5-year age groups from 1980–2015 for current smoking; a report by FOREY and LEE (2012) (38), which provides results by 15-year age groups from 1980–2005 for former smoking; and the German Socioeconomic Panel (39), which provides data for 2002 and 2012 for current and former smoking.

The sex- and age-specific distribution of time quit for former smokers used for the baseline population in 1995 was taken, in the absence of alternative data, from estimates for 2002 derived from the German Socioeconomic Panel (39). Because this source only provided data for age groups 20–24 and above, data for younger age groups were taken from US estimates for 2006 (27).

Additional File S1 gives further details on the derivation of the data on current and former smoking prevalence and time quit. It also includes tables summarizing the age-specific distribution of the population and the data on smoking habits used to assign the initial status of each member of the simulated population in 1995.

Estimation of histories of cigarette smoking for the Null Scenario

The sex- and age-specific TPs used in the P-component for developing the histories of cigarette smoking for the Null Scenario were derived as described in Additional File S2 and are shown in Table 1. To test the validity of the TPs, the prevalences predicted by using them were compared with the estimates for Germany derived for years up to 2015 as described in Additional File S1.

Yearly transition probabilities (per million) in the Null Scenario for Germany.

Period (years) Initiation (PNC) Quitting (PCF) Re-initiation (PFC)




Age Men Women Men Women Men Women
1–5 10–14 50,351 40,762 28,960 17,309 13,903 8,308
15–19 67,051 77,814 46,165 82,605 22,164 39,653
20–24 8,903 35,760 16,045 58,582 7,701 28,119
25–29 6,699 8,653 24,172 37,175 11,602 17,840
30–34 2,637 4,288 30,186 30,128 14,495 14,459
35–39 0 0 26,610 9,641 12,765 4,634
40–44 0 0 23,808 18,902 11,424 3,080
45–49 0 0 27,218 19,232 9,796 1,559
50–54 0 0 36,677 25,626 5,291 1,032
55–59 0 0 40,739 33,146 2,912 684
60–64 0 0 40,265 40,970 1,427 420
65–69 0 0 55,101 26,610 960 264
70–74 0 0 90,546 223,260 684 192
75–79 0 0 90,546 223,260 684 192
6–10 10–14 42,977 35,249 24,477 26,200 11,756 12,575
15–19 63,577 60,793 57,559 83,602 27,628 40,127
20–24 6,174 23,515 11,626 60,079 5,578 28,832
25–29 14,672 11,436 38,461 51,426 18,454 24,676
30–34 3,953 5,649 35,122 29,264 16,860 14,045
35–39 0 0 22,246 10,770 10,675 5,172
40–44 0 0 20,917 25,907 9,558 3,104
45–49 0 0 27,066 27,745 7,200 1,667
50–54 0 0 43,070 31,795 5,172 960
55–59 0 0 48,060 32,086 2,888 684
60–64 0 0 46,430 39,282 2,529 420
65–69 0 0 67,962 47,417 1,858 252
70–74 0 0 55,785 177,670 1,367 180
75–79 0 0 55,785 177,670 1,367 180
11+ 10–14 34,053 24,583 21,858 42,274 10,497 20,281
15–19 64,469 54,133 72,396 106,963 34,750 51,335
20–24 3,869 9,165 6,914 53,403 3,319 25,626
25–29 22,974 13,772 57,718 70,086 27,698 33,646
30–34 5,948 6,783 42,366 24,888 20,328 11,946
35–39 0 0 17,321 11,079 8,308 5,315
40–44 0 0 18,489 36,711 7,152 4,407
45–49 0 0 30,676 35,749 4,574 2,792
50–54 0 0 49,103 35,458 3,678 2,170
55–59 0 0 54,714 28,960 2,050 1,655
60–64 0 0 51,438 32,040 1,954 876
65–69 0 0 87,902 27,523 1,631 492
70–74 0 0 18,737 63,915 432 372
75–79 0 0 18,737 63,915 684 192

The first period relates to 5 years starting from 1995, the second to 5 years starting from 2000, and the third to 10 years starting from 2005. The transition probabilities between the three states N (never), C (current), and F (former) are described by P followed by two subscripts, the first representing the state changed from and the second the state changed to.

Note that RRPs are not introduced in the Null Scenario.

Estimation of histories of product use for the Alternative Scenarios

Seven different Alternative Scenarios were tested and are summarized in Table 2; Scenarios 1 to 3 are termed “Extreme Scenarios” and Scenarios 4 to 7 “Pragmatic Scenarios”. Together with the Null Scenario, which reflects the actual observed smoking prevalence in Germany in 1995–2015, the Extreme Scenarios calculate theoretical maximum effects of immediate cessation or immediate switch to RRPs. The Pragmatic Scenarios were designed to reflect a range of more gradual potential uptake rates of HnBs and ECigs, loosely based on early market data for Germany and international RRP uptake dynamics by 2019, with Scenario 4 (the “Conservative Scenario”) being a more pessimistic one, Scenario 5 (the “Dynamic Scenario”) an intermediate one and Scenarios 6 (the “Conversion Scenario”) and 7 (the “Full Conversion Scenario”) more optimistic ones. Exclusive RRP users are defined as the estimated number of Legal Age (over 18 years old) users that used the RRP for 100% of their daily nicotine product consumption over the past 7 days.

The Alternative Scenarios.

Scenario Number Name Summary description and comments
Extreme Scenarios
1 Complete cessation In 1995, all current cigarette smokers immediately stop smoking. There is no further initiation or re-initiation of cigarettes, HnB, or ECig use.
2 Complete switch to RRPs (HnBs) In 1995, all current cigarette smokers immediately switch to HnBs. The subsequent initiation, re-initiation, and quitting rates are as in the Null Scenario, but only involve transfers in or out of HnBs.
3 Complete switch to RRPs (50% HnBs and 50% ECigs) In 1995, all current cigarette smokers immediately switch to either HnBs or ECigs with equal probability. The subsequent rates are as in the Null Scenario, but only involve transfers involving the new products.
Pragmatic Scenarios
HnB: The market share in 2005 is 9% of that in 1995 for cigarette smoking, with 67% exclusive users.ECig: The market share in 2005 is 27% of that in 1995 for cigarette smoking, with 40% exclusive users.The calculated target distributions for 2005 are:
Never Cig only HnB only ECig only Multiple use Former use
4 Conservative Scenario Men 35.46 24.22 2.28 4.09 7.25 26.70
Women 60.56 15.64 1.47 2.64 4.68 15.01
Note: Multiple (product) users currently use at least one of the three products, while former (product) users have used at least one of the products, but do not currently use an).
The sum of the TPs for initiation and the sum of the TPs for re-initiation are the same as that for the Null Scenario. Each quitting TP is as for the Null Scenario. The difference between the four Pragmatic Scenarios only relates to the rates of switching among the three products.
The market shares in 2005 increase to 15.5% for HnBs and 36.4% for ECigs. The proportions of exclusive users are as in the Conservative Scenario.The calculated target distributions for 2005 are:
Never Cig only HnB only ECig only Multiple use Former use
5 Dynamic Scenario Men 35.46 18.20 3.93 5.51 10.20 26.70
Women 60.56 11.75 2.54 3.56 6.59 15.01
The rates of switching from exclusive cigarette smoking are increased from those in the Conservative Scenario.
The same as the Dynamic Scenario, except that the proportions of exclusive users rise to 84% for both RRPs.The calculated target distributions for 2005 are:
6 Conversion Scenario Never Cig only HnB only ECig only Multiple use Former use
Men 35.46 18.20 4.93 11.57 3.14 26.70
Women 60.56 11.75 3.18 7.47 2.03 15.01
Relative to the Dynamic Scenario, all 12 possible rates of switching vary, except those of switching from exclusive use of one RRP to exclusive use of the other.
The same as the Dynamic Scenario, except that the proportions of exclusive users rise to 100% for both RRPs.The calculated target distributions for 2005 are:
7 Full Conversion Scenario Men 35.46 18.20 5.87 13.87 0.00 26.70
Women 60.56 11.75 3.79 8.89 0.00 15.01
The comment for the Conversion Scenario applies here as well.

Abbreviations used: Cig = cigarette; ECig = e-cigarette; HnB =heat-not-burn; TP = transition probability;

No RRP is introduced in Alternative Scenario 1. For the other six Alternative Scenarios, the effective doses are assumed to be 0.2 for exclusive HnB use and 0.05 for exclusive ECig use, in contrast to an effective dose of 1 for exclusive cigarette smoking. The value for HnBs was based on biomarkers and clinical findings (40), and for ECigs on a published expert opinion (41). For multiple product use, the effective dose is assumed to be the mean of the three effective doses (i.e., 0.42).

The TPs used in the P-component for developing usage histories in the Alternative Scenario are presented in Additional File S3. Note that, for each Alternative Scenario, the sum of the initiation TPs (for a given sex, age, and follow-up period) was constrained to equal the corresponding initiation TP for the Null Scenario. The same constraint was applied to the re-initiation TPs. Each cessation TP in the Alternative Scenario was also constrained to equal the cessation TP in the Null Scenario. These constraints were applied so that the various Alternative Scenarios considered only the effect of the RRPs introduced on the distribution of current effect sizes, without any effect on overall initiation, cessation, or re-initiation rates.

Estimating relative risks on the basis of product use histories

For each disease, the estimates of RR for continued cigarette smoking and of H were derived from published meta-analyses. The estimates and sources are given in Table 3. The sex- and age-specific data on national population size for Germany for 1995 to 2015 are as published by the United Nations Department of Economic and Social Affairs Population Division (36).

Assumed relative risk for continued smoking and quitting half-life by disease for Germany.

Age (years) LC COPD Stroke IHD
Relative risk Any 8.68 3.31
to 54 2.48 3.38
55–64 2.13 2.32
65–74 1.39 1.70
75–79 1.06 1.27
Half-life Any 13.32 4.78
to 49 6.98 1.47
50–59 10.39 5.22
60–69 10.60 7.48
70–79 12.99 13.77

See (27) for the sources of these estimates.

The data on numbers of deaths in Germany from LC, COPD, IHD, and stroke come from the WHO (42). The data on population size and numbers of deaths for Germany for 1995 to 2015 are presented in Additional File S4, which gives fuller details on sources and disease definitions.

The method of estimating the number of deaths and increase in death rates associated with tobacco is as described earlier (27). Unless indicated, results are presented without adjustment for changes in population size associated with each Alternative Scenario.

RESULTS
Comparing smoking prevalences simulated in the Null Scenario and those derived for Germany

Figure 1 compares never, current, and former smoking prevalence estimates for Germany by sex for years up to 2015 and for age groups 30–34, 50–54, and 70–74 years as simulated in the Null Scenario (broken lines) with those derived as described in the Methods section (solid lines). The fit is generally very good, though there is some tendency for the Null Scenario current smoking estimates to be lower than the derived estimates at age 70–74 years.

Figure 1

Comparison of Null Scenario and derived estimates of current smoker prevalence.

Predicted prevalence of tobacco product use for the Alternative Scenarios

Figure 2 presents the simulated estimates of product usage in the Conversion Scenario by sex, age (30–34, 50–54, and 70–74 years), and year (1995, 2000, 2005, 2010, and 2015). In 1995, the estimates for current, never and former product use are identical, as expected, to those for cigarette smoking in the Null Scenario shown in Fig 1. The proportions of never and former product users in Figure 1 and Figure 2 remain very similar over the whole time period. While in the Null Scenario, the current product users all smoke cigarettes, in the Conversion Scenario, they fall into four groups. Over the first 15 years, there is a large decline in exclusive cigarette smoking and a corresponding increase in the other three current product use categories. This pattern flattens out between 2010 and 2015, with some decline in some of the groups. Further details for the Conversion Scenario as well as other Pragmatic Scenarios are shown in Additional File S5.

Figure 2

Product usage in the Conversion Scenario. Abbreviations used: ECig = e-cigarettes; HnB = heat-not-burn;

Additional File S6 summarizes the current product use distributions in 2005 for all the scenarios. With regard to the distributions in 2005, after 10 years follow-up, there were, as expected, no current product users at all in Scenario 1, with all HnB users in Scenario 2 and half HnB and half ECig users in Scenario 3.

In the Pragmatic Scenarios, the proportions of exclusive cigarette smokers decrease and those of exclusive HnB and ECig users increase from Scenarios 4 to 7. Relative to Scenario 5, the proportions of multiple product users decline in Scenarios 6 and 7. In 2010 (and also at other time points) the overall prevalence of current product users is essentially the same in each of Scenarios 2 to 7. This represents a drop of about 25% in men and 12% in women relative to the proportions in 1995.

Smoking-related deaths and loss of life in the Null Scenario

As estimated by the E-component of PHIM, 852,000 deaths from LC, COPD, IHD, and stroke combined for both sexes, were attributed to cigarette smoking over the period of 20 years from 1995 to 2015, in the absence of any switching to HnBs or ECigs and with the patterns of prevalence of cigarette smoking as existing in Germany (our Null Scenario). 77.9% of these were in males, with the percentages by disease being 54.6% for LC, 26.4% for IHD, 13.4% for COPD and 5.7% for stroke.

In the Null Scenario, 8.61 million YLL were attributed to cigarette smoking. 76.2% of these were in males, with the percentages by disease being 51.6% for LC, 31.8% for IHD, 8.4% for COPD and 8.2% for stroke. The percentages by disease, compared to those given above for attributable deaths, reflect the higher proportion of deaths at younger ages for IHD and stroke than for LC and COPD.

Smoking-related deaths and loss of life in the Alternative Scenarios

We explored a wide range of scenarios assessing the possible effect of RRP introduction on the population health in Germany in 1995–2015.

Our Extreme Scenarios (1–3) estimated theoretical maximum effects. As expected, the greatest impact would have occurred had all cigarette smokers quit in 1995, with no further use of cigarettes, HnBs, or ECigs (Scenario 1), resulting in a DD of about 217,000 and 2.88 million YLS. This extreme scenario has been designed to demonstrate the maximum potential risk reduction for the German population, and it can be considered a point of reference for every other scenario investigated.

Substantial reductions would also have occurred had cigarette smoking in Germany been immediately replaced by either HnB use (Scenario 2; 159,000 DD and 2.06 million YLS) or equally by either HnB or ECig use (Scenario 3; 179,000 DD and 2.34 million YLS), with the greater numbers for Scenario 3 reflecting the assumed lower effective dose for ECigs (0.05) compared with HnBs (0.2). Four Pragmatic Scenarios revealed more plausible estimates by moving gradually a proportion of cigarette smokers to use HnBs and ECigs.

Table 4 presents the estimated DD values at age 30–79 years over the whole follow-up period for all seven scenarios. These are shown for each disease separately and combined. The results are expressed both as numbers and percentages of all SRD.

Drop in deaths in Germany over the whole follow-up period for the seven Alternative Scenarios.

Drop in deaths % Drop in deaths



Sex/Scenario LC IHD Stroke COPD All four diseases LC IHD Stroke COPD All four diseases
Men
1 Complete cessation 48,092 83,798 15,429 14,166 161,485 13.38 45.26 46.06 16.48 24.32
2 Complete switch to RRPs (HnBs) 34,148 61,591 11,783 10,820 118,342 9.50 33.27 35.17 12.59 17.82
3 Complete switch to RRPs (50% HnBs; 50% ECigs) 38,967 69,431 13,111 12,038 133,547 10.84 37.50 39.14 14.01 20.11
4 Conservative Scenario 8,316 16,144 3,286 2,969 30,714 2.31 8.72 9.81 3.46 4.63
5 Dynamic Scenario 13,437 25,533 5,136 4,680 48,785 3.74 13.79 15.33 5.44 7.35
6 Conversion Scenario 15,950 30,276 6,004 5,425 57,655 4.44 16.35 17.92 6.31 8.68
7 Full Conversion Scenario 17,210 32,734 6,431 5,777 62,153 4.79 17.68 19.20 6.72 9.36
Women
1 Complete cessation 23,231 18,101 7,345 6,487 55,165 22.01 45.20 50.02 23.22 29.31
2 Complete switch to RRPs (HnBs) 16,617 13,670 5,649 5,000 40,936 15.74 34.14 38.47 17.89 21.75
3 Complete switch to RRPs (50% HnBs; 50% ECigs) 18,882 15,245 6,261 5,534 45,923 17.89 38.07 42.64 19.81 24.40
4 Conservative Scenario 3,476 3,089 1,369 1,169 9,104 3.29 7.71 9.32 4.19 4.84
5 Dynamic Scenario 5,605 4,934 2,141 1,859 14,540 5.31 12.32 14.58 6.66 7.72
6 Conversion Scenario 7,014 6,035 2,616 2,277 17,942 6.64 15.07 17.81 8.15 9.53
7 Full Conversion Scenario 7,530 6,404 2,783 2,424 19,140 7.13 15.99 18.95 8.67 10.17

Abbreviations used: COPD = chronic obstructive pulmonary disease, ECig = e-cigarette, HnB = heat-not-burn, IHD = ischaemic heart disease, LC = lung cancer;

The DDs are lower in the Pragmatic Scenarios, because the transition from cigarettes to HnBs and ECigs is less rapid. As would be predicted from the patterns of uptake by scenario shown in Table 2, the greatest DDs are seen in the Full Conversion Scenario, where smokers switch gradually to the RRPs – they are about 40% of the DDs associated with Complete Cessation, where smokers quit smoking immediately in 1995.

The patterns of DDs for the individual diseases are similar to that for the four diseases combined. Among men, the largest absolute DDs are for IHD, with LC next, followed by stroke and COPD with lower and similar DDs. Among women, the DDs for LC are higher than those for IHD, reflecting the lower overall IHD rate among women. As a proportion of all SRDs, the DDs in both sexes are substantially higher for IHD and stroke than for LC and COPD, reflecting the shorter H values for IHD and stroke (i.e., the more rapid reduction in cardiovascular disease risk after smoking cessation or switching to RRPs).

The DDs in the Conversion Scenario are also shown by disease over the whole follow-up period in Figure 3.

Figure 3

DDs in the Conversion Scenario over the whole follow-up period. Abbreviations used: COPD = chronic obstructive pulmonary disease; IHD = ischaemic heart disease; LC = lung cancer;

As is shown for the Conversion Scenario (Figure 3), but as is also evident from Additional File S5 for the other scenarios, an increase in DDs is seen with time in both sexes. This is due partly to the time needed for take-up of HnBs and ECigs and partly to the time required for the resulting decline in risk. This trend suggests that the DDs would have been substantially greater had the follow-up period been extended.

Table 5 and Figure 4 summarize the results for the seven scenarios with regard to YLS by age 75 over the whole follow-up period. The relative values for the different scenarios are very similar to those for DD seen in Table 4. Indeed, on the basis of the results for the four diseases combined in Tables 4 and 5, the sex- and scenario-specific ratios of YLS to DD can be estimated to only vary between 12.5 and 13.4.

Years of life saved (thousands) by age 75 over the whole follow-up period in Germany.

Men Women



Scenario LC IHD Stroke COPD All four diseases LC IHD Stroke COPD All four diseases
1 Complete cessation 520 1,329 213 98 2,160 292 258 118 52 720
2 Complete switch to RRPs (HnBs) 357 943 160 74 1,534 203 189 89 40 521
3 Complete switch to RRPs (50% HnBs; 50% ECigs) 412 1,077 180 83 1,752 233 213 99 44 589
4 Conservative Scenario 83 241 43 20 387 42 43 21 10 116
5 Dynamic Scenario 134 379 68 31 612 67 68 33 15 183
6 Conversion Scenario 161 461 80 37 739 84 84 40 18 226
7 Full Conversion Scenario 176 506 86 39 807 90 89 43 19 241

Abbreviations used: COPD = chronic obstructive pulmonary disease; ECig = e-cigarette; HnB = heat-not-burn; IHD = ischaemic heart disease; LC = lung cancer; RRP = reduced risk product;

Figure 4

YLS by Scenario over the whole follow-up period.

See Table 2 for a description of the scenarios.

The analyses summarized above do not take into account the increase in population size associated with the reduced mortality in the Alternative Scenarios relative to that in the Null Scenario. As shown in the detailed results in Additional File S5, this had little effect on the estimated DD or YLS. For example, for the Conversion Scenario, where the overall unadjusted DDs were 57,655 (8.68% of all SRD) in men and 17,942 (9.53% of SRD) in women, the corresponding adjusted DDs were 57,026 (8.59%) and 17,892 (9.51%), respectively. Full results of the analyses are available in Additional File S5.

DISCUSSION

We estimated the possible population health effect of introducing HnBs or ECigs into Germany during 1995–2015 by exploring a wide range of scenarios with various assumptions about their rate of uptake. Clearly, quitting all tobacco use brings the greatest benefits to the health of a population as a whole and can result in 2.88 million YLS and 217,000 DD upon total elimination of smoking after 20 years. Substantial reductions would also occur if, instead of quitting, CC smoking were immediately replaced by either HnB use or equally by either HnB or ECig use and these scenarios produced drop in deaths that were 74% and 83% of that for total cessation, respectively. Although these are the extreme scenarios and very unlikely to become reality, the simulated results provide the estimates of the highest theoretical benefits.

More plausible are the estimates associated with our Pragmatic Scenarios in which a proportion of cigarette smokers move gradually to use HnBs and ECigs. These scenarios aim to reflect potential effect sizes under less or more favorable conditions for the uptake of RRPs in Germany, rather than reflecting actual or expected RRP uptake dynamics. They are used to estimate how the uptake of ECigs and HnBs by smokers could have affected DDs and YLS in Germany in 1995–2021. Scenarios 4 to 7 vary in the extents to which uptake of these RRPs occurs and to which RRP users fully convert to exclusive RRP use, rather than becoming multiple users of cigarettes and RRPs. However, each scenario shows a positive population health impact, with DD varying, between Scenarios 4 and 7, from 39,800 to 81,300 and YLS from 0.50 to 1.05 million. The different Pragmatic Scenarios would thus have achieved 18–38% for DD and 17–36% for YLS of the effect of immediate cessation (Scenario 1). These estimates could inform public health authorities’ cost-benefit assessments on programs aimed at reducing the rate of CC smoking.

The Pragmatic Scenarios could be considered optimistic as they postulate market shares of the CC market in 2005 after ten years of 9 to 15.5% for HnB and 27 to 36.4% for ECig. They could also be considered pessimistic when compared to population health impact models by other authors. For example, Levy et al. (43) assumed CC smoking in the US was largely replaced by ECig use within 10 years.

There are four reasons why our calculated estimates, based on the scenarios chosen, may be too low. The first is that we only considered deaths from the four main smoking-related diseases due to lack of reliable data on RR and H for each smoking-associated disease. As estimated elsewhere (30), our estimates of deaths saved would have to be multiplied by about 1.52 to yield an estimate for all smoking-related diseases.

Another reason is that we limited attention to deaths up to age 79, partly to avoid the uncertainty of cause of death certification at older ages. Had we not done so, our estimates of deaths saved would have been higher.

A third and very important reason is that we only considered a 20-year follow-up period, as we did not wish to project into the future, where disease rates might be affected by various exogenous factors. The results in Figure 3 show that the DD values increase rapidly over time, particularly from LC and COPD, where quitting takes a long time to reduce risk.

The final reason is that we did not account for the possibility that cigarette smokers who take up ECigs or HnBs might be more likely to quit cigarette smoking than those who continued to exclusively smoke cigarettes. Evidence from the US shows that use of ECigs is associated with increased cessation rates (44).

Our analyses are limited by various factors shown previously (27) to have only a modest effect on estimates of population health impact. These include failure to consider pipe and cigar smoking, use of smokeless tobacco or nicotine replacement therapy, ignoring exposure from environmental tobacco smoke, and not allowing TPs to vary by previous product use history. Though the NEM has been validated on the basis of extensive data on quitting as well as limited data on changes in the number of cigarettes smoked (45), the accuracy of its predictions on more complex changes in usage over time has not been formally tested.

Our results for the introduction of RRPs will be affected by the effective doses chosen. For ECigs, we used an estimate of 0.05 on the basis of expert opinion (41), although this was derived based on chemistry and short-term toxicological results. For HnBs, our estimate of 0.20 was based on biomarker and clinical data (40), with results for a number of endpoints suggesting a lower effective dose. Elsewhere (27), we have demonstrated that the estimated DD is linearly related to the assumed values of the effective dose used, with DD increasing as the effective dose decreases. While the estimated effective dose is an important factor when smokers switch to RRPs like ECigs and HnBs, other factors also play a role. These include changes in the frequency of use and the extent to which cigarettes are completely abandoned.

A possible limitation of our modelling is that we considered people who simultaneously used two or three out of cigarettes, ECigs, and HnBs as multiple-product users, with their effective dose taken as the mean of 1, 0.05, and 0.20. Those who are dual users of cigarettes with either ECigs or HnBs might have a higher effective dose than the mean, while those who are dual users of ECigs and HnBs might have a lower one. However, the proportion of multiple product users is quite low, particularly for the Conversion and Full Conversion Scenarios, so the overall effect of this limitation on the results seems likely to be modest.

The rate at which smokers switch to ECigs and HnBs is likely to depend on product risk perception, much evidence having already shown this to be the case for ECigs. For instance, accurately perceiving ECigs as less harmful than cigarettes predicted subsequent ECig use among British smokers (46) and continues to correlate with ECig use among UK smokers (47). German smokers were more likely to use ECigs for smoking cessation if they perceived them as less harmful than cigarettes (48). US adult dual users of ECigs and cigarettes who perceived ECigs as less harmful than cigarettes were more likely to switch to exclusive ECig use 1 year later (49). However, correct risk perceptions of ECigs remain low and are getting worse over time, both internationally (46, 47) and in Germany, where more than half of the population perceives ECigs (50, 51) as at least as harmful as cigarettes. Even among ever-users of HnBs in Germany, only just over half of them accurately perceived HnBs as less harmful than cigarettes (52). Public health experts in the UK, the US, and Germany are, therefore, calling for better access to fact-based information (9, 46, 53, 54). Educational campaigns via trusted public health institutions are likely the most effective tool (55). While such campaigns exist in the UK, they are virtually absent in Germany.

Intuitively, maximizing the beneficial population health impact of introducing ECigs and HnBs will require a combination of high uptake among smokers, with many ultimately becoming exclusive RRP users. Our modelling results support this notion, with the DD and YLS increasing between Scenarios 4 and 5, when uptake was increased, and between Scenarios 5 and 7, when exclusive product use was increased. As discussed above, RR perceptions for ECig/HnB vs. smoking are potential drivers for both product uptake and exclusive product use, with health policy actions like public education campaigns being a recommended tool. Other factors likely to have an impact include risk-proportionate regulation in general (56) – such as product health warnings (57) – and local smoking cessation guidelines and healthcare professional recommendations (58) as well as media headlines (59). Moreover, fiscal policies can have an impact on relative product use. Recent US retail panel data suggest that ECig taxation increased cigarette sales (60).

Many other publications have estimated the population health impact of introducing RRPs. These include estimates based on our methodology, but applied to the USA (27, 28) or Japan (29), as well as attempts using different methodology, supported by other tobacco companies (61,62,63,64,65,66,67) or by public funding (43, 68,69,70,71,72,73). Despite methodological differences, most modellers have assumed the risk from RRP use, relative to that from cigarette smoking, is low and have concluded as we have that introduction of RRPs is likely to have a beneficial impact. For example, Levy et al. (43) concluded that a strategy including replacing CC smoking by ECig use would yield substantial health gains, even under pessimistic assumptions regarding cessation, initiation and relative harm.

As noted in the introduction, the number of smoking-attributable deaths estimated by Mons and Brenner to have occurred in Germany in 2013 is 125,000 (6). In the Null Scenario, in 2013, the number of SRD was estimated to be 39,600. There are three main reasons for this discrepancy. First, we only considered four diseases, which form only about 67.5% of the total number of smoking-related diseases (2). Second, we only considered the deaths of people aged 30–79 years, whereas the published estimate was related to age 35 years or above. Third, the disease-specific RRs used by Mons (2) were derived from specific US studies, whereas ours were derived from detailed meta-analyses (see Table 5). While the RRs from the two studies were quite similar for both IHD and stroke, those for LC (23.26 for men and 12.69 for women vs. 11.68 for both sexes) and COPD (10.58 for men and 13.08 for women vs. 4.56 for both sexes) were markedly higher in the previous study. Had we considered more diseases, a wider age range, or higher RRs, the estimated DD and YLS would, of course, have increased.

Overall, our results provide insight into how much the introduction of the two RRPs considered might affect the distribution of usage in Germany and the mortality related to cigarette smoking. Policies and regulation can accelerate switching to these RRPs, including calling for a more risk-proportionate approach and for the best available information on RRPs to be available to adult smokers. This will help increase the perception of the harm-reduction capabilities of RRPs and encourage switching, make alternatives to cigarettes more attractive for smokers, and help maintain product standards for building consumer trust in RRPs. Rather than any single measure, an integrated tobacco control strategy is likely to be more successful in encouraging smokers to switch to RRPs and thus result in an overall public health gain.

CONCLUSIONS

Based on estimates of the rate of uptake of two RRPs (HnBs and ECigs) in Germany and their effective dose compared with cigarettes, it is estimated that there would have been a drop in SRDs from LC, COPD, IHD, and stroke of approximately 40,000 to 81,000, with 0.50 to 1.05 million life years saved, corresponding to 17–38% of the effect of immediate cessation (Scenario 1). While cessation is the best option for smokers, we estimate that introducing RRPs and encouraging smokers who would otherwise continue to smoke cigarettes to switch to them will result in a substantial population health benefit in Germany, even under what may be considered more pessimistic assumptions about their relative harm and rate of uptake. These estimated effect sizes could help inform German public health authorities’ cost-benefit assessments on programs aimed at reducing the rate of CC smoking.

Figure 1

Comparison of Null Scenario and derived estimates of current smoker prevalence.
Comparison of Null Scenario and derived estimates of current smoker prevalence.

Figure 2

Product usage in the Conversion Scenario. Abbreviations used: ECig = e-cigarettes; HnB = heat-not-burn;
Product usage in the Conversion Scenario. Abbreviations used: ECig = e-cigarettes; HnB = heat-not-burn;

Figure 3

DDs in the Conversion Scenario over the whole follow-up period. Abbreviations used: COPD = chronic obstructive pulmonary disease; IHD = ischaemic heart disease; LC = lung cancer;
DDs in the Conversion Scenario over the whole follow-up period. Abbreviations used: COPD = chronic obstructive pulmonary disease; IHD = ischaemic heart disease; LC = lung cancer;

Figure 4

YLS by Scenario over the whole follow-up period.See Table 2 for a description of the scenarios.
YLS by Scenario over the whole follow-up period.See Table 2 for a description of the scenarios.

Assumed relative risk for continued smoking and quitting half-life by disease for Germany.

Age (years) LC COPD Stroke IHD
Relative risk Any 8.68 3.31
to 54 2.48 3.38
55–64 2.13 2.32
65–74 1.39 1.70
75–79 1.06 1.27
Half-life Any 13.32 4.78
to 49 6.98 1.47
50–59 10.39 5.22
60–69 10.60 7.48
70–79 12.99 13.77

Years of life saved (thousands) by age 75 over the whole follow-up period in Germany.

Men Women



Scenario LC IHD Stroke COPD All four diseases LC IHD Stroke COPD All four diseases
1 Complete cessation 520 1,329 213 98 2,160 292 258 118 52 720
2 Complete switch to RRPs (HnBs) 357 943 160 74 1,534 203 189 89 40 521
3 Complete switch to RRPs (50% HnBs; 50% ECigs) 412 1,077 180 83 1,752 233 213 99 44 589
4 Conservative Scenario 83 241 43 20 387 42 43 21 10 116
5 Dynamic Scenario 134 379 68 31 612 67 68 33 15 183
6 Conversion Scenario 161 461 80 37 739 84 84 40 18 226
7 Full Conversion Scenario 176 506 86 39 807 90 89 43 19 241

Drop in deaths in Germany over the whole follow-up period for the seven Alternative Scenarios.

Drop in deaths % Drop in deaths



Sex/Scenario LC IHD Stroke COPD All four diseases LC IHD Stroke COPD All four diseases
Men
1 Complete cessation 48,092 83,798 15,429 14,166 161,485 13.38 45.26 46.06 16.48 24.32
2 Complete switch to RRPs (HnBs) 34,148 61,591 11,783 10,820 118,342 9.50 33.27 35.17 12.59 17.82
3 Complete switch to RRPs (50% HnBs; 50% ECigs) 38,967 69,431 13,111 12,038 133,547 10.84 37.50 39.14 14.01 20.11
4 Conservative Scenario 8,316 16,144 3,286 2,969 30,714 2.31 8.72 9.81 3.46 4.63
5 Dynamic Scenario 13,437 25,533 5,136 4,680 48,785 3.74 13.79 15.33 5.44 7.35
6 Conversion Scenario 15,950 30,276 6,004 5,425 57,655 4.44 16.35 17.92 6.31 8.68
7 Full Conversion Scenario 17,210 32,734 6,431 5,777 62,153 4.79 17.68 19.20 6.72 9.36
Women
1 Complete cessation 23,231 18,101 7,345 6,487 55,165 22.01 45.20 50.02 23.22 29.31
2 Complete switch to RRPs (HnBs) 16,617 13,670 5,649 5,000 40,936 15.74 34.14 38.47 17.89 21.75
3 Complete switch to RRPs (50% HnBs; 50% ECigs) 18,882 15,245 6,261 5,534 45,923 17.89 38.07 42.64 19.81 24.40
4 Conservative Scenario 3,476 3,089 1,369 1,169 9,104 3.29 7.71 9.32 4.19 4.84
5 Dynamic Scenario 5,605 4,934 2,141 1,859 14,540 5.31 12.32 14.58 6.66 7.72
6 Conversion Scenario 7,014 6,035 2,616 2,277 17,942 6.64 15.07 17.81 8.15 9.53
7 Full Conversion Scenario 7,530 6,404 2,783 2,424 19,140 7.13 15.99 18.95 8.67 10.17

Yearly transition probabilities (per million) in the Null Scenario for Germany.

Period (years) Initiation (PNC) Quitting (PCF) Re-initiation (PFC)




Age Men Women Men Women Men Women
1–5 10–14 50,351 40,762 28,960 17,309 13,903 8,308
15–19 67,051 77,814 46,165 82,605 22,164 39,653
20–24 8,903 35,760 16,045 58,582 7,701 28,119
25–29 6,699 8,653 24,172 37,175 11,602 17,840
30–34 2,637 4,288 30,186 30,128 14,495 14,459
35–39 0 0 26,610 9,641 12,765 4,634
40–44 0 0 23,808 18,902 11,424 3,080
45–49 0 0 27,218 19,232 9,796 1,559
50–54 0 0 36,677 25,626 5,291 1,032
55–59 0 0 40,739 33,146 2,912 684
60–64 0 0 40,265 40,970 1,427 420
65–69 0 0 55,101 26,610 960 264
70–74 0 0 90,546 223,260 684 192
75–79 0 0 90,546 223,260 684 192
6–10 10–14 42,977 35,249 24,477 26,200 11,756 12,575
15–19 63,577 60,793 57,559 83,602 27,628 40,127
20–24 6,174 23,515 11,626 60,079 5,578 28,832
25–29 14,672 11,436 38,461 51,426 18,454 24,676
30–34 3,953 5,649 35,122 29,264 16,860 14,045
35–39 0 0 22,246 10,770 10,675 5,172
40–44 0 0 20,917 25,907 9,558 3,104
45–49 0 0 27,066 27,745 7,200 1,667
50–54 0 0 43,070 31,795 5,172 960
55–59 0 0 48,060 32,086 2,888 684
60–64 0 0 46,430 39,282 2,529 420
65–69 0 0 67,962 47,417 1,858 252
70–74 0 0 55,785 177,670 1,367 180
75–79 0 0 55,785 177,670 1,367 180
11+ 10–14 34,053 24,583 21,858 42,274 10,497 20,281
15–19 64,469 54,133 72,396 106,963 34,750 51,335
20–24 3,869 9,165 6,914 53,403 3,319 25,626
25–29 22,974 13,772 57,718 70,086 27,698 33,646
30–34 5,948 6,783 42,366 24,888 20,328 11,946
35–39 0 0 17,321 11,079 8,308 5,315
40–44 0 0 18,489 36,711 7,152 4,407
45–49 0 0 30,676 35,749 4,574 2,792
50–54 0 0 49,103 35,458 3,678 2,170
55–59 0 0 54,714 28,960 2,050 1,655
60–64 0 0 51,438 32,040 1,954 876
65–69 0 0 87,902 27,523 1,631 492
70–74 0 0 18,737 63,915 432 372
75–79 0 0 18,737 63,915 684 192

The Alternative Scenarios.

Scenario Number Name Summary description and comments
Extreme Scenarios
1 Complete cessation In 1995, all current cigarette smokers immediately stop smoking. There is no further initiation or re-initiation of cigarettes, HnB, or ECig use.
2 Complete switch to RRPs (HnBs) In 1995, all current cigarette smokers immediately switch to HnBs. The subsequent initiation, re-initiation, and quitting rates are as in the Null Scenario, but only involve transfers in or out of HnBs.
3 Complete switch to RRPs (50% HnBs and 50% ECigs) In 1995, all current cigarette smokers immediately switch to either HnBs or ECigs with equal probability. The subsequent rates are as in the Null Scenario, but only involve transfers involving the new products.
Pragmatic Scenarios
HnB: The market share in 2005 is 9% of that in 1995 for cigarette smoking, with 67% exclusive users.ECig: The market share in 2005 is 27% of that in 1995 for cigarette smoking, with 40% exclusive users.The calculated target distributions for 2005 are:
Never Cig only HnB only ECig only Multiple use Former use
4 Conservative Scenario Men 35.46 24.22 2.28 4.09 7.25 26.70
Women 60.56 15.64 1.47 2.64 4.68 15.01
Note: Multiple (product) users currently use at least one of the three products, while former (product) users have used at least one of the products, but do not currently use an).
The sum of the TPs for initiation and the sum of the TPs for re-initiation are the same as that for the Null Scenario. Each quitting TP is as for the Null Scenario. The difference between the four Pragmatic Scenarios only relates to the rates of switching among the three products.
The market shares in 2005 increase to 15.5% for HnBs and 36.4% for ECigs. The proportions of exclusive users are as in the Conservative Scenario.The calculated target distributions for 2005 are:
Never Cig only HnB only ECig only Multiple use Former use
5 Dynamic Scenario Men 35.46 18.20 3.93 5.51 10.20 26.70
Women 60.56 11.75 2.54 3.56 6.59 15.01
The rates of switching from exclusive cigarette smoking are increased from those in the Conservative Scenario.
The same as the Dynamic Scenario, except that the proportions of exclusive users rise to 84% for both RRPs.The calculated target distributions for 2005 are:
6 Conversion Scenario Never Cig only HnB only ECig only Multiple use Former use
Men 35.46 18.20 4.93 11.57 3.14 26.70
Women 60.56 11.75 3.18 7.47 2.03 15.01
Relative to the Dynamic Scenario, all 12 possible rates of switching vary, except those of switching from exclusive use of one RRP to exclusive use of the other.
The same as the Dynamic Scenario, except that the proportions of exclusive users rise to 100% for both RRPs.The calculated target distributions for 2005 are:
7 Full Conversion Scenario Men 35.46 18.20 5.87 13.87 0.00 26.70
Women 60.56 11.75 3.79 8.89 0.00 15.01
The comment for the Conversion Scenario applies here as well.

Jha, P., C. Ramasundarahettige, V. Landsman, B. Rostron, M. Thun, R.N. Anderson, T. McAfee, and R. Peto: 21st-Century Hazards of Smoking and Benefits of Cessation in the United States; N. Engl. J. Med. 368 (2013) 341–350. DOI: 10.1056/NEJMsa1211128 JhaP. RamasundarahettigeC. LandsmanV. RostronB. ThunM. AndersonR.N. McAfeeT. PetoR. 21st-Century Hazards of Smoking and Benefits of Cessation in the United States N. Engl. J. Med. 368 2013 341 350 10.1056/NEJMsa1211128 23343063 Open DOISearch in Google Scholar

Mons, U.: Tabakattributable Mortalität in Deutschland und in den Deutschen Bundesländern – Berechnungen mit Daten des Mikrozensus und der Todesursachenstatistik [Tobacco-Attributable Mortality in Germany and in the German Federal States - Calculations With Data From a Microcensus and Mortality Statistics]; Gesundheitswesen 73 (2011) 238–246. DOI: 10.1055/s-0030-1252039 MonsU. Tabakattributable Mortalität in Deutschland und in den Deutschen Bundesländern – Berechnungen mit Daten des Mikrozensus und der Todesursachenstatistik [Tobacco-Attributable Mortality in Germany and in the German Federal States - Calculations With Data From a Microcensus and Mortality Statistics] Gesundheitswesen 73 2011 238 246 10.1055/s-0030-1252039 20549599 Open DOISearch in Google Scholar

World Health Organization (WHO): WHO Global Report on Trends in Prevalence of Tobacco Smoking 2015; World Health Organization, Geneva, 2015. Available from: https://www.who.int/tobacco/publications/surveillance/reportontrendstobaccosmoking/en/index4.html (accessed March 2022) World Health Organization (WHO) WHO Global Report on Trends in Prevalence of Tobacco Smoking 2015 World Health Organization Geneva 2015 Available from: https://www.who.int/tobacco/publications/surveillance/reportontrendstobaccosmoking/en/index4.html (accessed March 2022) Search in Google Scholar

Kotz, D., M. Bockmann, and S. Kastaun: The Use of Tobacco, E-Cigarettes, and Methods to Quit Smoking in Germany: A Representative Study Using 6 Waves of Data Over 12 Months (the DEBRA Study); Dtsch. Arztebl. Int. 115 (2018) 235–242. DOI: 10.3238/arztebl.2018.0235 KotzD. BockmannM. KastaunS. The Use of Tobacco, E-Cigarettes, and Methods to Quit Smoking in Germany: A Representative Study Using 6 Waves of Data Over 12 Months (the DEBRA Study) Dtsch. Arztebl. Int. 115 2018 235 242 10.3238/arztebl.2018.0235 593854529716687 Open DOISearch in Google Scholar

Kotz, D., A. Batra, and S. Kastaun: Smoking Cessation Attempts and Common Strategies Employed: A Germany-Wide Representation Survey Conducted in 19 Waves From 2016 to 2019 (the DEBRA Study) and Analyzed by Socioeconomic Status; Dtsch. Ärztebl. Int. 117 (2020) 7–13. DOI: 10.3238/ärztebl.2020.0007 KotzD. BatraA. KastaunS. Smoking Cessation Attempts and Common Strategies Employed: A Germany-Wide Representation Survey Conducted in 19 Waves From 2016 to 2019 (the DEBRA Study) and Analyzed by Socioeconomic Status Dtsch. Ärztebl. Int. 117 2020 7 13 10.3238/ärztebl.2020.0007 Open DOISearch in Google Scholar

Mons, U. and H. Brenner: Demographic Ageing and the Evolution of Smoking-Attributable Mortality: The Example of Germany; Tob. Control 26 (2017) 455–457. DOI: 10.1136/tobaccocontrol-2016-053008 MonsU. BrennerH. Demographic Ageing and the Evolution of Smoking-Attributable Mortality: The Example of Germany Tob. Control 26 2017 455 457 10.1136/tobaccocontrol-2016-053008 27377343 Open DOISearch in Google Scholar

Chaloupka, F.J., D. Sweanor, and K.E. Warner: Differential Taxes for Differential Risks – Toward Reduced Harm From Nicotine-Yielding Products; N. Engl. J. Med. 373 (2015) 594–597. DOI: 10.1056/NEJMp1505710 ChaloupkaF.J. SweanorD. WarnerK.E. Differential Taxes for Differential Risks – Toward Reduced Harm From Nicotine-Yielding Products N. Engl. J. Med. 373 2015 594 597 10.1056/NEJMp1505710 26267620 Open DOISearch in Google Scholar

Royal College of Physicians (RCP): Nicotine Without Smoke: Tobacco Harm Reduction; RCP, London, UK, 2016. Available from: www.rcplondon.ac.uk/projects/outputs/nicotine-without-smoke-tobacco-harm-reduction (accessed March 2022) Royal College of Physicians (RCP) Nicotine Without Smoke: Tobacco Harm Reduction RCP London, UK 2016 Available from: www.rcplondon.ac.uk/projects/outputs/nicotine-without-smoke-tobacco-harm-reduction (accessed March 2022) Search in Google Scholar

Kozlowski, L.T. and D.B. Abrams: Obsolete Tobacco Control Themes can be Hazardous to Public Health: The Need for Updating Views on Absolute Product Risks and Harm Reduction; BMC Public Health 16 (2016) 432. DOI: 10.1186/s12889-016-3079-9 KozlowskiL.T. AbramsD.B. Obsolete Tobacco Control Themes can be Hazardous to Public Health: The Need for Updating Views on Absolute Product Risks and Harm Reduction BMC Public Health 16 2016 432 10.1186/s12889-016-3079-9 487803827221096 Open DOISearch in Google Scholar

Abrams, D.B., A.M. Glasser, A.C. Villanti, J.L. Pearson, S. Rose, and R.S. Niaura: Managing Nicotine Without Smoke to Save Lives Now: Evidence for Harm Minimization; Prev. Med. 117 (2018) 88–97. DOI: 10.1016/j.ypmed.2018.06.010 AbramsD.B. GlasserA.M. VillantiA.C. PearsonJ.L. RoseS. NiauraR.S. Managing Nicotine Without Smoke to Save Lives Now: Evidence for Harm Minimization Prev. Med. 117 2018 88 97 10.1016/j.ypmed.2018.06.010 693425329944902 Open DOISearch in Google Scholar

Abrams, D.B., A.M. Glasser, J.L. Pearson, A.C. Villanti, L.K. Collins, and R.S. Niaura: Harm Minimization and Tobacco Control: Reframing Societal Views of Nicotine Use to Rapidly Save Lives; Annu. Rev. Public Health 39 (2018) 193–213. DOI: 10.1146/annurev-publhealth-040617-013849 AbramsD.B. GlasserA.M. PearsonJ.L. VillantiA.C. CollinsL.K. NiauraR.S. Harm Minimization and Tobacco Control: Reframing Societal Views of Nicotine Use to Rapidly Save Lives Annu. Rev. Public Health 39 2018 193 213 10.1146/annurev-publhealth-040617-013849 694299729323611 Open DOISearch in Google Scholar

Fairchild, A., C. Healton, J. Curran, D. Abrams, and R. Bayer: Evidence, Alarm, and the Debate Over E-Cigarettes; Science 366 (2019) 1318–1320. DOI: 10.1126/science.aba0032 FairchildA. HealtonC. CurranJ. AbramsD. BayerR. Evidence, Alarm, and the Debate Over E-Cigarettes Science 366 2019 1318 1320 10.1126/science.aba0032 31831661 Open DOISearch in Google Scholar

McNeill, A., L.S. Brose, R. Calder, L. Bauld, and D. Robson: Evidence Review of E-Cigarettes and Heated Tobacco Products. A Report Commissioned by Public Health England; Public Health England, London, UK, 2018. Available at: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/684963/Evidence_review_of_e-cigarettes_and_heated_tobacco_products_2018.pdf (accessed March 2022) McNeillA. BroseL.S. CalderR. BauldL. RobsonD. Evidence Review of E-Cigarettes and Heated Tobacco Products. A Report Commissioned by Public Health England Public Health England London, UK 2018 Available at: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/684963/Evidence_review_of_e-cigarettes_and_heated_tobacco_products_2018.pdf (accessed March 2022) Search in Google Scholar

Schaller, J.P., D. Keller, L. Poget, P. Pratte, E. Kaelin, D. McHugh, G. Cudazzo, D. Smart, A.R. Tricker, L. Gautier, M. Yerly, R. Reis Pires, S. Le Bouhellec, D. Ghosh, I. Hofer, E. Garcia, P. Vanscheeuwijck, and S. Maeder: Evaluation of the Tobacco Heating System 2.2. Part 2: Chemical Composition, Genotoxicity, Cytotoxicity, and Physical Properties of the Aerosol; Regul. Toxicol. Pharmacol. 81 (2016) S27–S47. DOI: 10.1016/j.yrtph.2016.10.001 SchallerJ.P. KellerD. PogetL. PratteP. KaelinE. McHughD. CudazzoG. SmartD. TrickerA.R. GautierL. YerlyM. Reis PiresR. Le BouhellecS. GhoshD. HoferI. GarciaE. VanscheeuwijckP. MaederS. Evaluation of the Tobacco Heating System 2. Part 2: Chemical Composition, Genotoxicity, Cytotoxicity, and Physical Properties of the Aerosol Regul. Toxicol. Pharmacol. 81 2016 S27 S47 10.1016/j.yrtph.2016.10.001 Open DOISearch in Google Scholar

Mallock, N., L. Böss, R. Burk, M. Danziger, T. Welsch, H. Hahn, H.L. Trieu, J. Hahn, E. Pieper, F. Henkler-Stephani, C. Hutzler, and A. Luch: Levels of Selected Analytes in the Emissions of “Heat not Burn” Tobacco Products That are Relevant to Assess Human Health Risks; Arch. Toxicol. 92 (2018) 2145–2149. DOI: 10.1007/s00204-018-2215-y MallockN. BössL. BurkR. DanzigerM. WelschT. HahnH. TrieuH.L. HahnJ. PieperE. Henkler-StephaniF. HutzlerC. LuchA. Levels of Selected Analytes in the Emissions of “Heat not Burn” Tobacco Products That are Relevant to Assess Human Health Risks Arch. Toxicol. 92 2018 2145 2149 10.1007/s00204-018-2215-y Open DOISearch in Google Scholar

Ramström, L. and T. Wikmans: Mortality Attributable to Tobacco Among Men in Sweden and Other European Countries: An Analysis of Data in a WHO Report; Tob. Induc. Dis. 12 (2014) 14. DOI: 10.1186/1617-9625-12-14 RamströmL. WikmansT. Mortality Attributable to Tobacco Among Men in Sweden and Other European Countries: An Analysis of Data in a WHO Report Tob. Induc. Dis. 12 2014 14 10.1186/1617-9625-12-14 Open DOISearch in Google Scholar

Hajek, P., A. Phillips-Waller, D. Przulj, F. Pesola, K. Myers Smith, N. Bisal, J. Li, S. Parrott, P. Sasieni, L. Dawkins, L. Ross, M. Goniewicz, Q. Wu, and H.J. McRobbie: A Randomized Trial of E-Cigarettes Versus Nicotine-Replacement Therapy; N. Engl. J. Med. 380 (2019) 629–637. DOI: 10.1056/NEJMoa1808779 HajekP. Phillips-WallerA. PrzuljD. PesolaF. Myers SmithK. BisalN. LiJ. ParrottS. SasieniP. DawkinsL. RossL. GoniewiczM. WuQ. McRobbieH.J. A Randomized Trial of E-Cigarettes Versus Nicotine-Replacement Therapy N. Engl. J. Med. 380 2019 629 637 10.1056/NEJMoa1808779 Open DOISearch in Google Scholar

Beard, E., R. West, S. Michie, and J. Brown: Association of Prevalence of Electronic Cigarette Use With Smoking Cessation and Cigarette Consumption in England: A Time-Series Analysis Between 2006 and 2017; Addiction 115 (2019) 961–974. DOI: 10.1111/add.14851 BeardE. WestR. MichieS. BrownJ. Association of Prevalence of Electronic Cigarette Use With Smoking Cessation and Cigarette Consumption in England: A Time-Series Analysis Between 2006 and 2017 Addiction 115 2019 961 974 10.1111/add.14851 Open DOISearch in Google Scholar

Bauld, L., A.M. MacKintosh, B. Eastwood, A. Ford, G. Moore, M. Dockrell, D. Arnott, H. Cheeseman, and A. McNeill: Young People's Use of E-Cigarettes Across the United Kingdom: Findings From Five Surveys 2015–2017; Int. J. Environ. Res. Public Health 14 (2017). DOI: 10.3390/ijerph14090973 BauldL. MacKintoshA.M. EastwoodB. FordA. MooreG. DockrellM. ArnottD. CheesemanH. McNeillA. Young People's Use of E-Cigarettes Across the United Kingdom: Findings From Five Surveys 2015–2017 Int. J. Environ. Res. Public Health 14 2017 10.3390/ijerph14090973 Open DOISearch in Google Scholar

Walker, N., V. Parag, S.F. Wong, B. Youdan, B. Broughton, C. Bullen, and R. Beaglehole: Use of E-Cigarettes and Smoked Tobacco in Youth Aged 14–15 Years in New Zealand: Findings From Repeated Cross-Sectional Studies (2014–19); Lancet Public Health 5 (2020) e204–e212. DOI: 10.1016/s2468-2667(19)30241-5 WalkerN. ParagV. WongS.F. YoudanB. BroughtonB. BullenC. BeagleholeR. Use of E-Cigarettes and Smoked Tobacco in Youth Aged 14–15 Years in New Zealand: Findings From Repeated Cross-Sectional Studies (2014–19) Lancet Public Health 5 2020 e204 e212 10.1016/s2468-2667(19)30241-5 Open DOISearch in Google Scholar

Levy, D.T., K.E. Warner, K.M. Cummings, D. Hammond, C. Kuo, G.T. Fong, J.F. Thrasher, M.L. Goniewicz, and R. Borland: Examining the Relationship of Vaping to Smoking Initiation Among US Youth and Young Adults: A Reality Check; Tob. Control 28 (2019) 629–635. DOI: 10.1136/tobaccocontrol-2018-054446 LevyD.T. WarnerK.E. CummingsK.M. HammondD. KuoC. FongG.T. ThrasherJ.F. GoniewiczM.L. BorlandR. Examining the Relationship of Vaping to Smoking Initiation Among US Youth and Young Adults: A Reality Check Tob. Control 28 2019 629 635 10.1136/tobaccocontrol-2018-054446 686040930459182 Open DOISearch in Google Scholar

Sokol, N.A. and J.M. Feldman: High School Seniors who Used E-Cigarettes may Have Otherwise Been Cigarette Smokers: Evidence From Monitoring the Future (United States, 2009–2018); Nicotine Tob. Res. 23 (2021) 1958–1961. DOI: 10.1093/ntr/ntab102 SokolN.A. FeldmanJ.M. High School Seniors who Used E-Cigarettes may Have Otherwise Been Cigarette Smokers: Evidence From Monitoring the Future (United States, 2009–2018) Nicotine Tob. Res. 23 2021 1958 1961 10.1093/ntr/ntab102 849646733991190 Open DOISearch in Google Scholar

Stoklosa, M., Z. Cahn, A. Liber, N. Nargis, and J. Drope: Effect of IQOS Introduction on Cigarette Sales: Evidence of Decline and Replacement; Tob. Control 29 (2019) 381–387. DOI: 10.1136/tobaccocontrol-2019-054998 StoklosaM. CahnZ. LiberA. NargisN. DropeJ. Effect of IQOS Introduction on Cigarette Sales: Evidence of Decline and Replacement Tob. Control 29 2019 381 387 10.1136/tobaccocontrol-2019-054998 31209129 Open DOISearch in Google Scholar

Orth, B. and C. Merkel: Die Drogenaffinität Jugendlicher in der Bundesrepublik Deutschland 2019. Rauchen, Alkoholkonsum und Konsum illegaler Drogen: Aktuelle Verbreitung und Trends; Bundeszentrale für gesundheitliche Aufklärung (BZGA), Cologne, Germany 2020. DOI: 10.17623/BZGA:225-DAS19-DE-1.0 OrthB. MerkelC. Die Drogenaffinität Jugendlicher in der Bundesrepublik Deutschland 2019. Rauchen, Alkoholkonsum und Konsum illegaler Drogen: Aktuelle Verbreitung und Trends Bundeszentrale für gesundheitliche Aufklärung (BZGA) Cologne, Germany 2020 10.17623/BZGA:225-DAS19-DE-1.0 Open DOISearch in Google Scholar

Kotz, D. and S. Kastaun: Invited Lecture: Consumption of Cigarettes, Waterpipe, E-Cigarettes and Heated Tobacco Products in Germany: Current Data From the DEBRA Study; Deutsche Befragung zum Rauchverhalten (DEBRA), 18th German Tobacco Control Conference, Heidelberg, Online, 02 December 2020. Available from: https://www.debra-study.info/forschung (accessed March 2022) KotzD. KastaunS. Invited Lecture: Consumption of Cigarettes, Waterpipe, E-Cigarettes and Heated Tobacco Products in Germany: Current Data From the DEBRA Study Deutsche Befragung zum Rauchverhalten (DEBRA) 18th German Tobacco Control Conference Heidelberg Online, 02 December 2020 Available from: https://www.debra-study.info/forschung (accessed March 2022) Search in Google Scholar

Orth, B. and C. Merkel: Rauchen bei Jugendlichen und jungen Erwachsenen in Deutschland 2018: Ergebnisse des Alkoholsurveys 2018 und Trends; Bundeszentrale für gesundheitliche Aufklärung (BZGA), Cologne, Germany, 2019. DOI: 10.17623/BZGA:225-ALKSY18-RAU-DE-1.0 OrthB. MerkelC. Rauchen bei Jugendlichen und jungen Erwachsenen in Deutschland 2018: Ergebnisse des Alkoholsurveys 2018 und Trends Bundeszentrale für gesundheitliche Aufklärung (BZGA) Cologne, Germany 2019 10.17623/BZGA:225-ALKSY18-RAU-DE-1.0 Open DOISearch in Google Scholar

Lee, P.N., J.S. Fry, J.F. Hamling, Z. Sponsiello-Wang, G. Baker, and R. Weitkunat: Estimating the Effect of Differing Assumptions on the Population Health Impact of Introducing a Reduced Risk Tobacco Product in the USA; Regul. Toxicol. Pharmacol. 88 (2017) 192–213. DOI: 10.1016/j.yrtph.2017.06.009 LeeP.N. FryJ.S. HamlingJ.F. Sponsiello-WangZ. BakerG. WeitkunatR. Estimating the Effect of Differing Assumptions on the Population Health Impact of Introducing a Reduced Risk Tobacco Product in the USA Regul. Toxicol. Pharmacol. 88 2017 192 213 10.1016/j.yrtph.2017.06.009 28651854 Open DOISearch in Google Scholar

Djurdjevic, S., P.N. Lee, R. Weitkunat, Z. Sponsiello-Wang, F. Lüdicke, and G. Baker: Modeling the Population Health Impact of Introducing a Modified Risk Tobacco Product Into the U.S. Market; Healthcare (Basel) 6 (2018) 47. DOI: 10.3390/healthcare6020047 DjurdjevicS. LeeP.N. WeitkunatR. Sponsiello-WangZ. LüdickeF. BakerG. Modeling the Population Health Impact of Introducing a Modified Risk Tobacco Product Into the U.S. Market Healthcare (Basel) 6 2018 47 10.3390/healthcare6020047 602331029772688 Open DOISearch in Google Scholar

Lee, P.N., S. Djurdjevic, R. Weitkunat, and G. Baker: Estimating the Population Health Impact of Introducing a Reduced-Risk Tobacco Product Into Japan. The Effect of Differing Assumptions, and Some Comparisons With the U.S.; Regul. Toxicol. Pharmacol. 100 (2018) 92–104. DOI: 10.1016/j.yrtph.2018.10.010 LeeP.N. DjurdjevicS. WeitkunatR. BakerG. Estimating the Population Health Impact of Introducing a Reduced-Risk Tobacco Product Into Japan. The Effect of Differing Assumptions, and Some Comparisons With the U.S. Regul. Toxicol. Pharmacol. 100 2018 92 104 10.1016/j.yrtph.2018.10.010 30367904 Open DOISearch in Google Scholar

Weitkunat, R., P.N. Lee, G. Baker, Z. Sponsiello-Wang, A.M. González-Zuloeta Ladd, and F. Lüdicke: A Novel Approach to Assess the Population Health Impact of Introducing a Modified Risk Tobacco Product; Regul. Toxicol. Pharmacol. 72 (2015) 87–93. DOI: 10.1016/j.yrtph.2015.03.011 WeitkunatR. LeeP.N. BakerG. Sponsiello-WangZ. González-Zuloeta LaddA.M. LüdickeF. A Novel Approach to Assess the Population Health Impact of Introducing a Modified Risk Tobacco Product Regul. Toxicol. Pharmacol. 72 2015 87 93 10.1016/j.yrtph.2015.03.011 25819932 Open DOISearch in Google Scholar

Fry, J.S., P.N. Lee, B.A. Forey, and K.J. Coombs: How Rapidly Does the Excess Risk of Lung Cancer Decline Following Quitting Smoking? A Quantitative Review Using the Negative Exponential Model; Regul. Toxicol. Pharmacol. 67 (2013) 13–26. DOI: 10.1016/j.yrtph.2013.06.001 FryJ.S. LeeP.N. ForeyB.A. CoombsK.J. How Rapidly Does the Excess Risk of Lung Cancer Decline Following Quitting Smoking? A Quantitative Review Using the Negative Exponential Model Regul. Toxicol. Pharmacol. 67 2013 13 26 10.1016/j.yrtph.2013.06.001 23764305 Open DOISearch in Google Scholar

Lee, P.N., J.S. Fry, and B.A. Forey: Estimating the Decline in Excess Risk of Chronic Obstructive Pulmonary Disease Following Quitting Smoking – A Systematic Review Based on the Negative Exponential Model; Regul. Toxicol. Pharmacol. 68 (2014) 231–239. DOI: 10.1016/j.yrtph.2013.12.006 LeeP.N. FryJ.S. ForeyB.A. Estimating the Decline in Excess Risk of Chronic Obstructive Pulmonary Disease Following Quitting Smoking – A Systematic Review Based on the Negative Exponential Model Regul. Toxicol. Pharmacol. 68 2014 231 239 10.1016/j.yrtph.2013.12.006 24361344 Open DOISearch in Google Scholar

Lee, P.N., J.S. Fry, and J.S. Hamling: Using the Negative Exponential Distribution to Quantitatively Review the Evidence on how Rapidly the Excess Risk of Ischaemic Heart Disease Declines Following Quitting Smoking; Regul. Toxicol. Pharmacol. 64 (2012) 51–67. DOI: 10.1016/j.yrtph.2012.06.009 LeeP.N. FryJ.S. HamlingJ.S. Using the Negative Exponential Distribution to Quantitatively Review the Evidence on how Rapidly the Excess Risk of Ischaemic Heart Disease Declines Following Quitting Smoking Regul. Toxicol. Pharmacol. 64 2012 51 67 10.1016/j.yrtph.2012.06.009 22728684 Open DOISearch in Google Scholar

Lee, P.N., J.S. Fry, and A. Thornton: Estimating the Decline in Excess Risk of Cerebrovascular Disease Following Quitting Smoking - A Systematic Review Based on the Negative Exponential Model; Regul. Toxicol. Pharmacol. 68 (2014) 85–95. DOI: 10.1016/j.yrtph.2013.11.013 LeeP.N. FryJ.S. ThorntonA. Estimating the Decline in Excess Risk of Cerebrovascular Disease Following Quitting Smoking - A Systematic Review Based on the Negative Exponential Model Regul. Toxicol. Pharmacol. 68 2014 85 95 10.1016/j.yrtph.2013.11.013 24291341 Open DOISearch in Google Scholar

Gardner, J.W. and J.S. Sanborn: Years of Potential Life Lost (YPLL) – What Does it Measure?; Epidemiology 1 (1990) 322–329. DOI: 10.1097/00001648-199007000-00012 GardnerJ.W. SanbornJ.S. Years of Potential Life Lost (YPLL) – What Does it Measure? Epidemiology 1 1990 322 329 10.1097/00001648-199007000-00012 2083312 Open DOISearch in Google Scholar

United Nations Department of Economic and Social Affairs Population Division: World Population Prospects: The 2015 Revision; United Nations, New York, NY, USA. Available at: http://esa.un.org/unpd/wpp/Download/Standard/Population/ United Nations Department of Economic and Social Affairs Population Division World Population Prospects: The 2015 Revision United Nations New York, NY, USA Available at: http://esa.un.org/unpd/wpp/Download/Standard/Population/ Search in Google Scholar

Forey, B., J. Hamling, J. Hamling, A. Thornton and P. Lee: International Smoking Statistics. A Collection of Worldwide Historical Data (2006–2016); Available at: www.pnlee.co.uk/iss.htm (accessed March 2022) ForeyB. HamlingJ. HamlingJ. ThorntonA. LeeP. International Smoking Statistics. A Collection of Worldwide Historical Data (2006–2016) Available at: www.pnlee.co.uk/iss.htm (accessed March 2022) Search in Google Scholar

Forey, B.A. and P.N. Lee: A Comparison of Smoking Prevalence and Quitting Between Countries Which use Either Virginia or Blended Tobacco Cigarettes; PN Lee Statistics and Computing Ltd, Sutton, Surrey, UK, 2012. Available from: www.pnlee.co.uk/Reports.htm [Download FOREY2012] ForeyB.A. LeeP.N. A Comparison of Smoking Prevalence and Quitting Between Countries Which use Either Virginia or Blended Tobacco Cigarettes PN Lee Statistics and Computing Ltd Sutton, Surrey, UK 2012 Available from: www.pnlee.co.uk/Reports.htm [Download FOREY2012] Search in Google Scholar

Bennewitz, E. and A. Kaul: Quitting Smoking in Germany: Evidence From the SOEP; Saarland University, Saarbrücken, Germany, 2020. Available at: https://www.uni-saarland.de/fileadmin/user_upload/Professoren/fr12_ProfKaul/Research/2020_01_29_Quitting_Smoking.pdf (accessed March 2022) BennewitzE. KaulA. Quitting Smoking in Germany: Evidence From the SOEP Saarland University Saarbrücken, Germany 2020 Available at: https://www.uni-saarland.de/fileadmin/user_upload/Professoren/fr12_ProfKaul/Research/2020_01_29_Quitting_Smoking.pdf (accessed March 2022) Search in Google Scholar

Martin, F., G. Vuillaume, G. Baker, Z. Sponsiello-Wang, P.F. Ricci, F. Lüdicke, and R. Weitkunat: Quantifying the Risk-Reduction Potential of New Modified Risk Tobacco Products; Regul. Toxicol. Pharmacol. 92 (2018) 358–369. DOI: 10.1016/j.yrtph.2017.12.011 MartinF. VuillaumeG. BakerG. Sponsiello-WangZ. RicciP.F. LüdickeF. WeitkunatR. Quantifying the Risk-Reduction Potential of New Modified Risk Tobacco Products Regul. Toxicol. Pharmacol. 92 2018 358 369 10.1016/j.yrtph.2017.12.011 29258927 Open DOISearch in Google Scholar

Nutt, D.J., L.D. Phillips, D. Balfour, H.V. Curran, M. Dockrell, J. Foulds, K. Fagerstrom, K. Letlape, A. Milton, R. Polosa, J. Ramsey, and D. Sweanor: Estimating the Harms of Nicotine-Containing Products Using the MCDA Approach; Eur. Addict. Res. 20 (2014) 218–225. DOI: 10.1159/000360220 NuttD.J. PhillipsL.D. BalfourD. CurranH.V. DockrellM. FouldsJ. FagerstromK. LetlapeK. MiltonA. PolosaR. RamseyJ. SweanorD. Estimating the Harms of Nicotine-Containing Products Using the MCDA Approach Eur. Addict. Res. 20 2014 218 225 10.1159/000360220 24714502 Open DOISearch in Google Scholar

World Health Organization (WHO): WHO Mortality Database; available at: http://www.who.int/healthinfo/mortality_data/en/ (accessed March 2022) World Health Organization (WHO) WHO Mortality Database available at: http://www.who.int/healthinfo/mortality_data/en/ (accessed March 2022) Search in Google Scholar

Levy, D.T., R. Borland, E.N. Lindblom, M.L. Goniewicz, R. Meza, T.R. Holford, Z. Yuan, Y. Luo, R.J. O’Connor, R. Niaura, and D.B. Abrams: Potential Deaths Averted in USA by Replacing Cigarettes With E-Cigarettes; Tob. Control 27 (2018) 18–25. DOI: 10.1136/tobaccocontrol-2017-053759 LevyD.T. BorlandR. LindblomE.N. GoniewiczM.L. MezaR. HolfordT.R. YuanZ. LuoY. O’ConnorR.J. NiauraR. AbramsD.B. Potential Deaths Averted in USA by Replacing Cigarettes With E-Cigarettes Tob. Control 27 2018 18 25 10.1136/tobaccocontrol-2017-053759 580165328970328 Open DOISearch in Google Scholar

Zhu, S.H., Y.L. Zhuang, S. Wong, S.E. Cummins, and G.J. Tedeschi: E-Cigarette use and Associated Changes in Population Smoking Cessation: Evidence From US Current Population Surveys; BMJ 358 (2017) j3262. DOI: 10.1136/bmj.j3262 ZhuS.H. ZhuangY.L. WongS. CumminsS.E. TedeschiG.J. E-Cigarette use and Associated Changes in Population Smoking Cessation: Evidence From US Current Population Surveys BMJ 358 2017 j3262 10.1136/bmj.j3262 552604628747333 Open DOISearch in Google Scholar

Lee, P.N., J. Hamling, J. Fry, and B. Forey: Using the Negative Exponential Model to Describe Changes in Risk of Smoking-Related Diseases Following Changes in Exposure to Tobacco; Advances in Epidemiology, Article ID 487876 (2015) 13 pages. DOI: 10.1155/2015/487876 LeeP.N. HamlingJ. FryJ. ForeyB. Using the Negative Exponential Model to Describe Changes in Risk of Smoking-Related Diseases Following Changes in Exposure to Tobacco Advances in Epidemiology Article ID 487876 2015 13 pages. 10.1155/2015/487876 Open DOISearch in Google Scholar

Brose, L.S., J. Brown, S.C. Hitchman, and A. McNeill: Perceived Relative Harm of Electronic Cigarettes Over Time and Impact on Subsequent Use. A Survey With 1-Year and 2-Year Follow-Ups; Drug Alcohol Depend. 157 (2015) 106–111. DOI: 10.1016/j.drugalcdep.2015.10.014 BroseL.S. BrownJ. HitchmanS.C. McNeillA. Perceived Relative Harm of Electronic Cigarettes Over Time and Impact on Subsequent Use. A Survey With 1-Year and 2-Year Follow-Ups Drug Alcohol Depend. 157 2015 106 111 10.1016/j.drugalcdep.2015.10.014 468604526507173 Open DOISearch in Google Scholar

Action on Smoking and Health (ASH): Use of E-Cigarettes (Vapes) Among Adults in Great Britain, 2021; ASH, London, UK, 2021. Available at: https://ash.org.uk/wp-content/uploads/2021/06/Use-of-e-cigarettes-vapes-among-adults-in-Great-Britain-2021.pdf (accessed April 2022) Action on Smoking and Health (ASH) Use of E-Cigarettes (Vapes) Among Adults in Great Britain, 2021 ASH London, UK 2021 Available at: https://ash.org.uk/wp-content/uploads/2021/06/Use-of-e-cigarettes-vapes-among-adults-in-Great-Britain-2021.pdf (accessed April 2022) Search in Google Scholar

Atzendorf, J., A.B. Aschenbrenner, E. Gomes de Matos, L. Kraus, C. Kröger, S. Delle, and D. Piontek: E-Zigaretten: Einschätzung von Gesundheitsgefahren und Nutzung zur Tabakentwöhnung (E-Cigarettes: Perceived Harmfulness and Use for Smoking Cessation); Bundesgesundheitsbl. 61 (2018) 1415–1421. DOI: 10.1007/s00103-018-2822-z AtzendorfJ. AschenbrennerA.B. Gomes de MatosE. KrausL. KrögerC. DelleS. PiontekD. E-Zigaretten: Einschätzung von Gesundheitsgefahren und Nutzung zur Tabakentwöhnung (E-Cigarettes: Perceived Harmfulness and Use for Smoking Cessation) Bundesgesundheitsbl. 61 2018 1415 1421 10.1007/s00103-018-2822-z 30284625 Open DOISearch in Google Scholar

Persoskie, A., E.K. O’Brien, and K. Poonai: Perceived Relative Harm of Using E-Cigarettes Predicts Future Product Switching Among US Adult Cigarette and E-Cigarette Dual Users; Addiction 114 (2019) 2197–2205. DOI: 10.1111/add.14730 PersoskieA. O’BrienE.K. PoonaiK. Perceived Relative Harm of Using E-Cigarettes Predicts Future Product Switching Among US Adult Cigarette and E-Cigarette Dual Users Addiction 114 2019 2197 2205 10.1111/add.14730 31278802 Open DOISearch in Google Scholar

Eichler, M., M. Blettner, and S. Singer: The Use of E-Cigarettes - A Population-Based Cross-Sectional Survey of 4002 Individuals in 2016; Dtsch. Ärztebl. Int. 113 (2016) 847–854. DOI: 10.3238/arztebl.2016.0847 EichlerM. BlettnerM. SingerS. The Use of E-Cigarettes - A Population-Based Cross-Sectional Survey of 4002 Individuals in 2016 Dtsch. Ärztebl. Int. 113 2016 847 854 10.3238/arztebl.2016.0847 527358728098063 Open DOISearch in Google Scholar

Verband des eZigarettenhandels (VdeH): E-Zigaretten - die unterschätzte Chance. Was die Deutschen über E-Zigaretten wissen - und was nicht. Ergebnisse der repräsentativen Forsa-Befragung; VdeH, Berlin, Germany, November 2019. Available at: https://vd-eh.de/wp-content/uploads/2019/11/vdeh-forsa-2019.pdf (accessed March 2022) Verband des eZigarettenhandels (VdeH) E-Zigaretten - die unterschätzte Chance. Was die Deutschen über E-Zigaretten wissen - und was nicht. Ergebnisse der repräsentativen Forsa-Befragung VdeH Berlin, Germany November 2019 Available at: https://vd-eh.de/wp-content/uploads/2019/11/vdeh-forsa-2019.pdf (accessed March 2022) Search in Google Scholar

Kotz, D. and S. Kastaun: E-Zigaretten und Tabakerhitzer: repräsentative Daten zu Konsumverhalten und assoziierten Faktoren in der deutschen Bevölkerung (die DEBRA-Studie) (E-Cigarettes and Heat-Not-Burn Products: Representative Data on Consumer Behaviour and Associated Factors in the German Population (The DEBRA Study)); Bundesgesundheitsbl. 61 (2018) 1407–1414. DOI: 10.1007/s00103-018-2827-7 KotzD. KastaunS. E-Zigaretten und Tabakerhitzer: repräsentative Daten zu Konsumverhalten und assoziierten Faktoren in der deutschen Bevölkerung (die DEBRA-Studie) (E-Cigarettes and Heat-Not-Burn Products: Representative Data on Consumer Behaviour and Associated Factors in the German Population (The DEBRA Study)) Bundesgesundheitsbl. 61 2018 1407 1414 10.1007/s00103-018-2827-7 30284626 Open DOISearch in Google Scholar

Kozlowski, L.T. and D. Sweanor: Withholding Differential Risk Information on Legal Consumer Nicotine/Tobacco Products: The Public Health Ethics of Health Information Quarantines; Int. J. Drug Policy 32 (2016) 17–23. DOI: 10.1016/j.drugpo.2016.03.014 KozlowskiL.T. SweanorD. Withholding Differential Risk Information on Legal Consumer Nicotine/Tobacco Products: The Public Health Ethics of Health Information Quarantines Int. J. Drug Policy 32 2016 17 23 10.1016/j.drugpo.2016.03.014 27209528 Open DOISearch in Google Scholar

Science Media Center Germany (SMC): Press Briefing: Wie sollen E-Zigaretten künftig reguliert werden?; SMC gGmbH, Heidelberg, Germany, 21 January 2020; Available at: https://www.sciencemediacenter.de/alle-angebote/press-briefing/details/news/wie-sollen-e-zigaretten-kuenftig-reguliert-werden/ (accessed March 2022) Science Media Center Germany (SMC) Press Briefing: Wie sollen E-Zigaretten künftig reguliert werden? SMC gGmbH Heidelberg, Germany 21 January 2020 Available at: https://www.sciencemediacenter.de/alle-angebote/press-briefing/details/news/wie-sollen-e-zigaretten-kuenftig-reguliert-werden/ (accessed March 2022) Search in Google Scholar

Weaver, S.R., A. Jazwa, L. Popova, P. Slovic, R.B. Rothenberg, and M.P. Eriksen: Worldviews and Trust of Sources for Health Information on Electronic Nicotine Delivery Systems: Effects on Risk Perceptions and Use; SSM Popul. Health 3 (2017) 787–794. DOI: 10.1016/j.ssmph.2017.09.003 WeaverS.R. JazwaA. PopovaL. SlovicP. RothenbergR.B. EriksenM.P. Worldviews and Trust of Sources for Health Information on Electronic Nicotine Delivery Systems: Effects on Risk Perceptions and Use SSM Popul. Health 3 2017 787 794 10.1016/j.ssmph.2017.09.003 576909529349263 Open DOISearch in Google Scholar

Levy, D.T., G.T. Fong, K.M. Cummings, R. Borland, D.B. Abrams, A.C. Villanti, and R. Niaura: The Need for a Comprehensive Framework; Addiction 112 (2017) 22–24. DOI: 10.1111/add.13600 LevyD.T. FongG.T. CummingsK.M. BorlandR. AbramsD.B. VillantiA.C. NiauraR. The Need for a Comprehensive Framework Addiction 112 2017 22 24 10.1111/add.13600 539638727936507 Open DOISearch in Google Scholar

Kimber, C., D. Frings, S. Cox, I.P. Albery, and L. Dawkins: Communicating the Relative Health Risks of E-Cigarettes: An Online Experimental Study Exploring the Effects of a Comparative Health Message Versus the EU Nicotine Addiction Warnings on Smokers’ and Non-Smokers’ Risk Perceptions and Behavioural Intentions; Addict. Behav. 101 (2020) 106177. DOI: 10.1016/j.addbeh.2019.106177 KimberC. FringsD. CoxS. AlberyI.P. DawkinsL. Communicating the Relative Health Risks of E-Cigarettes: An Online Experimental Study Exploring the Effects of a Comparative Health Message Versus the EU Nicotine Addiction Warnings on Smokers’ and Non-Smokers’ Risk Perceptions and Behavioural Intentions Addict. Behav. 101 2020 106177. 10.1016/j.addbeh.2019.106177 689125731753541 Open DOISearch in Google Scholar

Hummel, K., G.E. Nagelhout, G.T. Fong, C.I. Vardavas, S. Papadakis, A. Herbeć, U. Mons, B. van den Putte, R. Borland, E. Fernández, H. de Vries, A. McNeill, S. Gravely, K. Przewoźniak, P. Kovacs, A.C. Trofor, and M.C. Willemsen: Quitting Activity and use of Cessation Assistance Reported by Smokers in Eight European Countries: Findings From the EUREST-PLUS ITC Europe Surveys; Tob. Induc. Dis. 16 (2018). DOI: 10.18332/tid/98912 HummelK. NagelhoutG.E. FongG.T. VardavasC.I. PapadakisS. HerbećA. MonsU. van den PutteB. BorlandR. FernándezE. de VriesH. McNeillA. GravelyS. PrzewoźniakK. KovacsP. TroforA.C. WillemsenM.C. Quitting Activity and use of Cessation Assistance Reported by Smokers in Eight European Countries: Findings From the EUREST-PLUS ITC Europe Surveys Tob. Induc. Dis. 16 2018 10.18332/tid/98912 665955631363422 Open DOISearch in Google Scholar

Reimer, J., S. Kuhn, and K. Lehmann: Konsumgewohnheiten und Motive von E-Zigaretten-Konsumenten in Deutschland - Eine Querschnittsanalyse; Zentrum für Interdisziplinäre Suchtforschung der Universität Hamburg (ZIS), Hamburg, Germany, 2016. Available at: https://www.bundesgesundheitsministerium.de/fileadmin/Dateien/5_Publikationen/Drogen_und_Sucht/Berichte/161005_Anlage_5-Abschlussbericht_ZIS.pdf (accessed March 2022) ReimerJ. KuhnS. LehmannK. Konsumgewohnheiten und Motive von E-Zigaretten-Konsumenten in Deutschland - Eine Querschnittsanalyse Zentrum für Interdisziplinäre Suchtforschung der Universität Hamburg (ZIS) Hamburg, Germany 2016 Available at: https://www.bundesgesundheitsministerium.de/fileadmin/Dateien/5_Publikationen/Drogen_und_Sucht/Berichte/161005_Anlage_5-Abschlussbericht_ZIS.pdf (accessed March 2022) Search in Google Scholar

Cotti, C.D., C.J. Courtemanche, J.C. Maclean, E.T. Nesson, M.F. Pesko, and N. Tefft: The Effects of E-Cigarette Taxes on E-Cigarette Prices and Tobacco Product Sales: Evidence From Retail Panel Data; National Bureau of Economic Research (NBER), Working Paper 26724, Cambridge, MA, USA, 2020. Available at: https://www.nber.org/papers/w26724.pdf (accessed March 2022) CottiC.D. CourtemancheC.J. MacleanJ.C. NessonE.T. PeskoM.F. TefftN. The Effects of E-Cigarette Taxes on E-Cigarette Prices and Tobacco Product Sales: Evidence From Retail Panel Data National Bureau of Economic Research (NBER) Working Paper 26724, Cambridge, MA, USA 2020 Available at: https://www.nber.org/papers/w26724.pdf (accessed March 2022) 10.3386/w26724 Search in Google Scholar

Bachand, A.M. and S.I. Sulsky: A Dynamic Population Model for Estimating All-Cause Mortality due to Lifetime Exposure History; Regul. Toxicol. Pharmacol. 67 (2013) 246–251. DOI: 10.1016/j.yrtph.2013.08.003 BachandA.M. SulskyS.I. A Dynamic Population Model for Estimating All-Cause Mortality due to Lifetime Exposure History Regul. Toxicol. Pharmacol. 67 2013 246 251 10.1016/j.yrtph.2013.08.003 23933005 Open DOISearch in Google Scholar

Bachand, A.M., S.I. Sulsky, and G.M. Curtin: Assessing the Likelihood and Magnitude of a Population Health Benefit Following the Market Introduction of a Modified-Risk Tobacco Product: Enhancements to the Dynamic Population Modeler, DPM(+1); Risk Anal. 38 (2018) 151–162. DOI: 10.1111/risa.12819 BachandA.M. SulskyS.I. CurtinG.M. Assessing the Likelihood and Magnitude of a Population Health Benefit Following the Market Introduction of a Modified-Risk Tobacco Product: Enhancements to the Dynamic Population Modeler, DPM(+1) Risk Anal. 38 2018 151 162 10.1111/risa.12819 28437870 Open DOISearch in Google Scholar

Black, R., J. Murillo, and Y. Pithawalla (Editors): Population Modeling. A Practical Approach to Evaluate the Net Benefit of a new Tobacco Product; Proceedings of Tobacco Computational Modeling Meeting, NYU College of Global Public Health, July 23–24, 2018. BlackR. MurilloJ. PithawallaY. (Editors) Population Modeling. A Practical Approach to Evaluate the Net Benefit of a new Tobacco Product Proceedings of Tobacco Computational Modeling Meeting, NYU College of Global Public Health July 23–24, 2018 Search in Google Scholar

Camacho, O.M., A. Hill, S. Fiebelkorn, A. Williams, and J.J. Murphy: Investigating the Health Effects of 3 Coexisting Tobacco and Nicotine Products Using System Dynamics Population Modeling: An Italian Population Case Study; medRxiv Preprint: Apr 19, 2021. DOI: 10.1101/2021.04.12.21255338 Available at: https://www.medrxiv.org/content/10.1101/2021.04.12.21255338v1.full.pdf (accessed March 2022) CamachoO.M. HillA. FiebelkornS. WilliamsA. MurphyJ.J. Investigating the Health Effects of 3 Coexisting Tobacco and Nicotine Products Using System Dynamics Population Modeling: An Italian Population Case Study medRxiv Preprint: Apr 19 2021 10.1101/2021.04.12.21255338 Available at: https://www.medrxiv.org/content/10.1101/2021.04.12.21255338v1.full.pdf (accessed March 2022) Open DOISearch in Google Scholar

Hill, A. and O.M. Camacho: A System Dynamics Modelling Approach to Assess the Impact of Launching a New Nicotine Product on Population Health Outcomes; Regul. Toxicol. Pharmacol. 86 (2017) 265–278. DOI: 10.1016/j.yrtph.2017.03.012 HillA. CamachoO.M. A System Dynamics Modelling Approach to Assess the Impact of Launching a New Nicotine Product on Population Health Outcomes Regul. Toxicol. Pharmacol. 86 2017 265 278 10.1016/j.yrtph.2017.03.012 28342844 Open DOISearch in Google Scholar

Muhammad-Kah, R.S., Y.B. Pithawalla, E.L. Boone, L. Wei, M.A. Jones, R.A. Black, T.M. Bryan, and M.A. Sarkar: A Computational Model for Assessing the Population Health Impact of Introducing a Modified Risk Claim on an Existing Smokeless Tobacco Product; Int. J. Environ. Res. Public Health 16 (2019) 1264. DOI: 10.3390/ijerph16071264 Muhammad-KahR.S. PithawallaY.B. BooneE.L. WeiL. JonesM.A. BlackR.A. BryanT.M. SarkarM.A. A Computational Model for Assessing the Population Health Impact of Introducing a Modified Risk Claim on an Existing Smokeless Tobacco Product Int. J. Environ. Res. Public Health 16 2019 1264 10.3390/ijerph16071264 647938930970571 Open DOISearch in Google Scholar

Poland, B. and F. Teischinger: Population Modeling of Modified Risk Tobacco Products Accounting for Smoking Reduction and Gradual Transitions of Relative Risk; Nicotine Tob. Res. 19 (2017) 1277–1283. DOI: 10.1093/ntr/ntx070 PolandB. TeischingerF. Population Modeling of Modified Risk Tobacco Products Accounting for Smoking Reduction and Gradual Transitions of Relative Risk Nicotine Tob. Res. 19 2017 1277 1283 10.1093/ntr/ntx070 28371856 Open DOISearch in Google Scholar

Apelberg, B.J., S.P. Feirman, E. Salazar, C.G. Corey, B.K. Ambrose, A. Paredes, E. Richman, S.J. Verzi, E.D. Vugrin, N.S. Brodsky, and B.L. Rostron: Potential Public Health Effects of Reducing Nicotine Levels in Cigarettes in the United States; N. Engl. J. Med. 378 (2018) 1725–1733. DOI: 10.1056/NEJMsr1714617 ApelbergB.J. FeirmanS.P. SalazarE. CoreyC.G. AmbroseB.K. ParedesA. RichmanE. VerziS.J. VugrinE.D. BrodskyN.S. RostronB.L. Potential Public Health Effects of Reducing Nicotine Levels in Cigarettes in the United States N. Engl. J. Med. 378 2018 1725 1733 10.1056/NEJMsr1714617 29543114 Open DOISearch in Google Scholar

Kalkhoran, S. and S.A. Glantz: Modeling the Health Effects of Expanding E-Cigarette Sales in the United States and United Kingdom: A Monte Carlo Analysis; JAMA Intern. Med. 175 (2015) 1671–1680. DOI: 10.1001/jamainternmed.2015.4209 KalkhoranS. GlantzS.A. Modeling the Health Effects of Expanding E-Cigarette Sales in the United States and United Kingdom: A Monte Carlo Analysis JAMA Intern. Med. 175 2015 1671 1680 10.1001/jamainternmed.2015.4209 459419626322924 Open DOISearch in Google Scholar

Levy, D.T., R. Borland, A.C. Villanti, R. Niaura, Z. Yuan, Y. Zhang, R. Meza, T.R. Holford, G.T. Fong, K.M. Cummings, and D.B. Abrams: The Application of a Decision-Theoretic Model to Estimate the Public Health Impact of Vaporized Nicotine Product Initiation in the United States; Nicotine Tob. Res. 19 (2017) 149–159. DOI: 10.1093/ntr/ntw158 LevyD.T. BorlandR. VillantiA.C. NiauraR. YuanZ. ZhangY. MezaR. HolfordT.R. FongG.T. CummingsK.M. AbramsD.B. The Application of a Decision-Theoretic Model to Estimate the Public Health Impact of Vaporized Nicotine Product Initiation in the United States Nicotine Tob. Res. 19 2017 149 159 10.1093/ntr/ntw158 523436527613952 Open DOISearch in Google Scholar

Soneji, S.S., H.Y. Sung, B.A. Primack, J.P. Pierce, and J.D. Sargent: Quantifying Population-Level Health Benefits and Harms of E-Cigarette use in the United States; PLoS One 13 (2018) e0193328. DOI: 10.1371/journal.pone.0193328 SonejiS.S. SungH.Y. PrimackB.A. PierceJ.P. SargentJ.D. Quantifying Population-Level Health Benefits and Harms of E-Cigarette use in the United States PLoS One 13 2018 e0193328 10.1371/journal.pone.0193328 585155829538396 Open DOISearch in Google Scholar

Vugrin, E.D., B.L. Rostron, S.J. Verzi, N.S. Brodsky, T.J. Brown, C.J. Choiniere, B.N. Coleman, A. Paredes, and B.J. Apelberg: Modeling the Potential Effects of new Tobacco Products and Policies: A Dynamic Population Model for Multiple Product Use and Harm; PLoS One 10 (2015) e0121008. DOI: 10.1371/journal.pone.0121008 VugrinE.D. RostronB.L. VerziS.J. BrodskyN.S. BrownT.J. ChoiniereC.J. ColemanB.N. ParedesA. ApelbergB.J. Modeling the Potential Effects of new Tobacco Products and Policies: A Dynamic Population Model for Multiple Product Use and Harm PLoS One 10 2015 e0121008 10.1371/journal.pone.0121008 437680625815840 Open DOISearch in Google Scholar

Warner, K.E. and D. Mendez: E-Cigarettes: Comparing the Possible Risks of Increasing Smoking Initiation With the Potential Benefits of Increasing Smoking Cessation; Nicotine Tob. Res. 21 (2019) 41–47. DOI: 10.1093/ntr/nty062 WarnerK.E. MendezD. E-Cigarettes: Comparing the Possible Risks of Increasing Smoking Initiation With the Potential Benefits of Increasing Smoking Cessation Nicotine Tob. Res. 21 2019 41 47 10.1093/ntr/nty062 29617887 Open DOISearch in Google Scholar

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