Citation: Oying Doso, Sarsing Gao. An overview of small hydro power development in India[J]. AIMS Energy, 2020, 8(5): 896-917. doi: 10.3934/energy.2020.5.896
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The smoking behaviors have been considered as a critical problem on both health and social aspects for a long time. It is well-known that smoking can increase the risks of having serious diseases such as cancer and cardiovascular disease. WHO has estimated that tobacco use (smoking and smokeless) is currently responsible for the death of about six million people across the world each year with many of these deaths occurring prematurely. Although often associated with ill-health, disability and death from noncommunicable chronic diseases, tobacco smoking is also associated with an increased risk of death from communicable diseases [1].
To reduce such serious effect, many nations and global health organizations had applied control policies. According to WHO Comprehensive Information Systems, During the most recent decade, the prevalence of tobacco smoking in men fell in 125 (72%) countries, and in women fell in 155 (87%) countries. If these trends continue, only 37 (21%) countries are on track to achieve their targets for men and 88 (49%) are on track for women, and there would be an estimated 1.1 billion current tobacco smokers (95% credible interval 700 million to 1.6 billion) in 2025 [2]. Among many control policies, health education campaigns played an important role. Ian Bier
Above evidences motivated us to construct a mathematical model to mimic the smoking dynamics with health educational campaigns involved. We think it can be a helpful tool to analyze smoking behaviors and their control.
Back to 90's, smoking dynamics were only been studied by using basic SIR model. In a recent decade, several more sophisticated models about smoking dynamics have been studied. In 2008, Sharomo and Gumel [6] introduced new classes
Above works guide us to derive a smoking model along with health educational campaigns involved. The paper is organized as follows. In Section 2, we present the model with health education effect, and prove the model is well posed. Section 3 focuses on the existence of smoking-free equilibrium and smoking-present equilibrium. Derivations for the reproduction number and both local and global stability properties for equilibria are also included in this section. In Section 4, we provide some numerical simulation results to support our analytic results. Section 5 includes discussions of the results.
In this section we describe our smoking model with health educational campaigns involved. We first divide the whole population into 6 groups:
PN(t): Normal susceptible population, who do not smoke or smoke occasionally and do not get health education, may become smokers in future.PE(t): Educated susceptible population, who get health education and do not smoke or smoke occasionally, have lower chance to develop smoking behaviors.S(t): Smoking populationQt(t): Temporary quitters, who are currently abstaining smoking, but may not succeed.Qp(t): Permanent quitters, who permanently quit smoking, never smoke again.Z(t): Smokers with associated diseases, yield extra death rate. |
The total number of population at time t is given by
N(t)=PN(t)+PE(t)+S(t)+Qt(t)+Qp(t)+Z(t) |
The following system of ODEs forms our model (Figure 1):
˙PN=qμ−μPN−βPNS˙PE=(1−q)μ−μPE−βδPES˙S=−(μ+γ+λ)S+βS(PN+δPE)+αQt˙Qt=−μQt−αQt−ηQt+γS˙Qp=−μQp+ηQt˙Z=λS−(μ+ν)Z |
First of all, every group share same death rate
Boundedness is one of important properties of a system, and we shall provide it for our system by following lemma.
Lemma 2.1. If
Proof. Suppose above lemma does not hold, then at least one of
1. There exists a first time
2. There exists a first time
3. There exists a first time
4. There exists a first time
5. There exists a first time
6. There exists a first time
That shows the contradiction, therefore the lemma has to be true.
By summing the equations of our system, we find that
P′N+P′E+S′+Q′t+Q′p+Z′=μ[1−(PN+PE+S+Qt+Qp+Z)]−νZ≤μ[1−(PN+PE+S+Qt+Qp+Z)] |
It follows that
Ω={(PN,PE,S,Qt,Qp,Z)∈R6+:PN+PE+S+Qt+Qp+Z≤1} |
is positively invariant for our system. Hence, the global stability of the system will be only considered within set
By setting the right-hand side of the model to 0, we get following equations:
PN=qμμ+βSPE=(1−q)μμ+βδSS=αQt(μ+γ+η)−β(PN+δPE)Qt=γSμ+η+αQp=ημQtZ=λSμ+ν |
We see that the model has a smoking-free equilibrium
PN0=q PE0=1−q |
The smoking infected compartments are
dXdt=F(X)−V(X) |
where
F(X)=(βPNS+βδPES00000) V(X)=((μ+γ+λ)S−αQt(α+μ+η)Qt−γS(μ+ν)Z−λSμPN+βPNS−qμμPE+βδPES−(1−q)μμQp−ηQt) |
By computing the Jacobian matrices at
DF(E0)=(F3×3000) DV(E0)=(V3×30J1J2) |
where
F=(βPN0+βδPE000000000) V=(μ+γ+λ−α0−γα+μ+η0−λ0μ+ν) |
J1=(βPN000βγPE0000−η0) J2=(μ000μ000μ) |
Further,
R0=ρ(FV−1)=β(PN0+δPE0)(μ+η+α)(μ+γ+λ)(μ+η+α)−αγ |
By Theorem 2 from van den Driessche and Watmough [16], the local stability of smoking-free equilibrium
Theorem 3.1. The smoking-free equilibrium
Now we look at smoking-present equilibrium
PN=qμμ+βSPE=(1−q)μμ+βδSQt=γSμ+η+αS[β(PN+δPE)−(μ+γ+λ)]+αQt=0 |
By substituting
S[β(PN+δPE)−(μ+γ+λ)]+γSμ+η+α=0⇒ S(β(PN+δPE)−(μ+γ+λ)+γμ+η+α)=0 |
Since
β(PN+δPE)−(μ+γ+λ)+γμ+η+α=0⇒ PN+δPE=1β((μ+γ+λ)−γμ+η+α) |
By substituting
Y(S):=q(μ+βδS)+(1−q)δ(μ+βS)(μ+βS)(μ+βδS)−(μ+γ+λ)(μ+η+α)−αγμβ(μ+η+α)=0 |
By taking the derivative of
Y′(S)=−β{β2δ2S2+μS[2βδ2(1−q)+2βδq]+μ2[δ2(1−q)+q]}(μ+βS)2(μ+βδS)2<0 |
Hence, the function
Y(S)<1βS−(μ+γ+λ)(μ+η+α)−αγμβ(μ+η+α) |
Thus,
Y(0)=(μ+γ+λ)(μ+η+α)−αγμβ(μ+η+α)(R0−1)Y(1)<1β−(μ+γ+λ)(μ+η+α)−αγμβ(μ+η+α)=−λ(μ+η+α)+γ(μ+η)μβ(μ+η+α)<0 |
If
Theorem 3.2. The system always has the smoking-free equilibrium
P∗N=qμμ+βS∗P∗E=(1−q)μμ+βδS∗Q∗t=γS∗μ+η+αQ∗p=ημQ∗tZ∗=λS∗μ+ν |
and
Theorem 3.3. The smoking-present equilibrium
Proof. Since variables
˙PN=qμ−μPN−βPNS˙PE=(1−q)μ−μPE−βδPES˙S=−(μ+γ+λ)S+βS(PN+δPE)+αQt˙Qt=−μQt−αQt−ηQt+γS |
Consider the previous four equations in the original system, we get its Jacobian matrix at the smoking-present equilibrium
J(E∗)=[−βS−μ0−βPN00−μδS−μ−βδPE0βSβδSβ(δPE+PN)−μ−γ−λα00γ−μ−α−η]. |
β(δPE+PN)−μ−γ−λ=−αγα+η+μ. |
Hence, we have
J(E∗)=[−βS−μ0−βPN00−μδS−μ−βδPE0βSβδS−αγα+η+μα00γ−μ−α−η]. |
Our aim is to prove
a11=βS+μ, a13=βPN, a22=μδS+μ, a23=βδPE, a31=Sβ, a32=Sδβ, a44=μ+α+η. |
Even the new variables are not independent, we would like to investigate them in a broader ranges.
Then, we have
J(E∗)=[−a110−a1300−a22−a230a31a32−αγa44α00γ−a44]. |
Ep(x)=a44x4+(a442+(a11+a22)a44+αγ)x3+((a11+a22)a442+(a11a22+a13a31+a23a32)a44+γα(a11+a22))x2+((a11a22+a13a31+a23a32)a442+(a11a23a32+a13a22a31)a44+γa11a22α)x+a442(a11a23a32+a13a22a31). |
All coefficients of
Theorem 3.4. If
Proof. Since variables
˙PN=qμ−μPN−βPNS˙PE=(1−q)μ−μPE−βδPES˙S=−(μ+γ+λ)S+βS(PN+δPE)+αQt˙Qt=−μQt−αQt−ηQt+γS |
By proving the global stability of smoking-free equilibrium
For the smoking-free equilibrium
qμ−μPN=0(1−q)μ−μPE=0 |
Hence, we can rewrite above system as
˙PN=PN[qμ(1PN−1PN0)−βS]˙PE=PE[(1−q)μ(1PE−1PE0)−βδS]˙S=βS[(PN0+δPE0)+(PN−PN0)+δ(PE−PE0)]+αQt−(μ+γ+λ)S˙Qt=γS−(μ+η+α)Qt |
Define the Lyapunov function:
V1=(PN−PN0−PN0lnPNPN0)+(PE−PE0−PE0lnPEPE0)+S+αμ+η+αQt |
By taking the derivative, we have
V′1=(PN−PN0)P′NPN+(PE−PE0)P′EPE+S′+αμ+η+αQ′t=(PN−PN0)[qμ(1PN−1PN0)−βS]+(PE−PE0)[(1−q)μ(1PE−1PE0)−βδS]+βS[(PN0+δPE0)+(PN−PN0)+δ(PE−PE0)]+αQt−(μ+γ+λ)S+αμ+η+α[γS−(μ+η+α)Qt]=(μ+γ+λ)(μ+η+α)−αγμ+η+α(R0−1)S+F(PN,PE) |
, where
F(PN,PE)=qμ(PN−PN0)(1PN−1PN0)+(1−q)μ(PE−PE0)(1PE−1PE0)=qμ(2−PNPN0−PN0PN)+(1−q)μ(2−PEPE0−PE0PE) |
Let
F(PN,PE)=qμ(2−x−1x)+(1−q)μ(2−y−1y)=qμ((−1)(x−1)2x)+(1−q)μ((−1)(y−1)2y) |
It is obvious that
Theorem 3.5. If
Proof. Similarly, we prove the stability of original smoking-present equilibrium
For
qμ−μPN−βPNS=0(1−q)μ−μPE−βδPES=0−(μ+γ+λ)S+βS(PN+δPE)+αQt=0γS−Qt(μ+η+α)=0 |
Let
a′=a[qμP∗N(1a−1)−βS∗(c−1)]b′=b[(1−q)μP∗E(1b−1)−βδS∗(c−1)]c′=c[βP∗N(a−1)+βδP∗E(b−1)+αQ∗tS∗(dc−1)]d′=d[γS∗Q∗t(cd−1)] |
Define the Lyapunov function:
V2=P∗N(a−1−lna)+P∗E(b−1−lnb)+S∗(c−1−lnc)+αμ+η+αQ∗t(d−1−lnd) |
By taking the derivative, we have
V′2=P∗N(a−1a)a′+P∗E(b−1b)b′+S∗(c−1c)c′+αμ+η+αQ∗t(d−1d)d′=(a−1)[qμ(1a−1)−βP∗NS∗(c−1)]+(b−1)[(1−q)μ(1b−1)−βδP∗ES∗(c−1)]+(c−1)[βP∗NS∗(a−1)+βδP∗ES∗(b−1)+αQ∗t(dc−1)]+αγS∗μ+η+α(d−1)(cd−1)=qμ(a−1)(1a−1)−βP∗NS∗(a−1)(c−1)+(1−q)μ(b−1)(1b−1)−βδP∗ES∗(b−1)(c−1)+βP∗NS∗(c−1)(a−1)+βδP∗ES∗(c−1)(b−1)+αQ∗t(c−1)(dc−1)+αγS∗μ+η+α(d−1)(cd−1)=qμ(−(a−1)2a)+(1−q)μ(−(b−1)2b)+αQ∗t(d−c−dc+1)αγS∗μ+η+α(c−d−cd+1)=F(a,b)+G(c,d) |
where
F(a,b)=qμ(−(a−1)2a)+(1−q)μ(−(b−1)2b)G(c,d)=αγS∗μ+η+α(2−cd−dc)=αγS∗μ+η+α(−(c−d)2cd) |
It is easy to see that
In this section, we provide some numerical results to support our analytic results from above. For the choices of parameters, some are chosen from medical researches, and others are estimated. The values for normal mortality
Parameter | Meaning | Value | Source |
q | non-educated portion of new recruitment rate | 0.7 | Estimated for test case |
| natural death rate and new recruitment rate | 0.017 | McEvoy, John W., et al. "Mortality rates in smokers and nonsmokers in the presence or absence of coronary artery calcification." JACC: Cardiovascular Imaging 5.10 (2012): 1037-1045. |
| transmission coefficient for potential smokers (both non-educated and educated) transfer to smokers (S) | 0.2/0.7 | Estimated for test cases |
| immuity coefficient for educated population ( | 0.25 | Smoking & Tobacco Use.17 Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 3 Feb. 2017 |
| transmission coefficient for smokers (S) transfer to temporary quitters ( | 0.554 | Morbidity and Mortality Weekly Report (MMWR).17 Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 14 Aug. 2017 |
| transmission coefficient for temporary quitters ( | 0.48 | Morbidity and Mortality Weekly Report (MMWR).17 Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 14 Aug. 2017 |
| transmission coefficient for temporary quitters ( | 0.074 | Morbidity and Mortality Weekly Report (MMWR).17 Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 14 Aug. 2017 |
| transmission coefficient for smokers (S) transfer to smokers with diseases (Z) | 0.4233 | Smoking & Tobacco Use.17 Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 3 Feb. 2017 |
| extra death rate for smokers with diseases (Z) | 0.043 | McEvoy, John W., et al. "Mortality rates in smokers and nonsmokers in the presence or absence of coronary artery calcification." JACC: Cardiovascular Imaging 5.10 (2012): 1037-1045. |
The model is simulated for following different initial values such that
1.
2.
3.
4.
For
In this paper, we consider the health education effect on the smoking dynamic model. We have derived the reproduction number (
It will be very interesting to consider the time delay in this model, and it will be more realistic and give us more insights into the smoking dynamics, but some complex dynamic behaviors may occur([15,17]).
The authors would like to thank the generous support from the mathematics department at University of Evansville.
Authors declare no conflicts of interest in this paper.
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Parameter | Meaning | Value | Source |
q | non-educated portion of new recruitment rate | 0.7 | Estimated for test case |
| natural death rate and new recruitment rate | 0.017 | McEvoy, John W., et al. "Mortality rates in smokers and nonsmokers in the presence or absence of coronary artery calcification." JACC: Cardiovascular Imaging 5.10 (2012): 1037-1045. |
| transmission coefficient for potential smokers (both non-educated and educated) transfer to smokers (S) | 0.2/0.7 | Estimated for test cases |
| immuity coefficient for educated population ( | 0.25 | Smoking & Tobacco Use.17 Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 3 Feb. 2017 |
| transmission coefficient for smokers (S) transfer to temporary quitters ( | 0.554 | Morbidity and Mortality Weekly Report (MMWR).17 Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 14 Aug. 2017 |
| transmission coefficient for temporary quitters ( | 0.48 | Morbidity and Mortality Weekly Report (MMWR).17 Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 14 Aug. 2017 |
| transmission coefficient for temporary quitters ( | 0.074 | Morbidity and Mortality Weekly Report (MMWR).17 Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 14 Aug. 2017 |
| transmission coefficient for smokers (S) transfer to smokers with diseases (Z) | 0.4233 | Smoking & Tobacco Use.17 Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 3 Feb. 2017 |
| extra death rate for smokers with diseases (Z) | 0.043 | McEvoy, John W., et al. "Mortality rates in smokers and nonsmokers in the presence or absence of coronary artery calcification." JACC: Cardiovascular Imaging 5.10 (2012): 1037-1045. |
Parameter | Meaning | Value | Source |
q | non-educated portion of new recruitment rate | 0.7 | Estimated for test case |
| natural death rate and new recruitment rate | 0.017 | McEvoy, John W., et al. "Mortality rates in smokers and nonsmokers in the presence or absence of coronary artery calcification." JACC: Cardiovascular Imaging 5.10 (2012): 1037-1045. |
| transmission coefficient for potential smokers (both non-educated and educated) transfer to smokers (S) | 0.2/0.7 | Estimated for test cases |
| immuity coefficient for educated population ( | 0.25 | Smoking & Tobacco Use.17 Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 3 Feb. 2017 |
| transmission coefficient for smokers (S) transfer to temporary quitters ( | 0.554 | Morbidity and Mortality Weekly Report (MMWR).17 Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 14 Aug. 2017 |
| transmission coefficient for temporary quitters ( | 0.48 | Morbidity and Mortality Weekly Report (MMWR).17 Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 14 Aug. 2017 |
| transmission coefficient for temporary quitters ( | 0.074 | Morbidity and Mortality Weekly Report (MMWR).17 Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 14 Aug. 2017 |
| transmission coefficient for smokers (S) transfer to smokers with diseases (Z) | 0.4233 | Smoking & Tobacco Use.17 Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 3 Feb. 2017 |
| extra death rate for smokers with diseases (Z) | 0.043 | McEvoy, John W., et al. "Mortality rates in smokers and nonsmokers in the presence or absence of coronary artery calcification." JACC: Cardiovascular Imaging 5.10 (2012): 1037-1045. |