MATLAB code to simulate the effects of combination of control strategies on the transmission of diphtheria
Data files
Sep 19, 2023 version files 4.66 KB
Abstract
This research introduced an extensive mathematical model to capture the dynamics of diphtheria transmission. The study examined the interaction of five control measures viz: routine diphtheria vaccination, often administered with tetanus and pertussis vaccines; interventions for symptomatic to isolated treatment transitions; collaborative efforts addressing asymptomatic to home quarantine transitions; surveillance measures for home quarantine to isolated treatment transitions; and vigilance to detect cases in individuals exposed to symptomatic cases. We established the epidemiological viability of the model by proving, among others, its positivity, equilibrium under endemic conditions, equilibrium in the absence of disease, global and local stability and boundedness. Also the sensitivity analysis of the model highlighted the importance of the important variables in influencing disease occurrence and spread. In addition, the control measures significantly impact virus transmission dynamics, and results from simulations demonstrated that combination of these control strategies effectively flattened the curve of diphtheria transmission. These findings provided healthcare professionals and policymakers with valuable insights into crucial measures for eradicating diphtheria from the population.
README: MATLAB code to simulate the effects of the combination of control strategies on the transmission of Diphtheria
https://doi.org/10.5061/dryad.qrfj6q5ng
Description of the data
c=200; %c=beta -recruitment of individuals into the susceptible population
d=0.000097; %d=landa -transmission rate
e=0.7; %e=gamma -modification parameter for the transmission rate
f=0.002; %f=meu -natural mortality
a=0.55; %proportion of symptomatic individuals
g=0.95; %g=phi -The rate of exposed individuals to symptomatic
h=0.0054; %h=delta -diphtheria mortality rate
k1=0.9; %tau1 -routine vaccination
k2=0.9; %tau2 -effort of health facilities in the transition of symptomatic to isolated treatment
k3=0.9; %tau3 -effort of health facilities in the transition of asymptomatic to home quarantine
k4=0.9; %tau4 -effort of health facilities in the transition of home quarantine to isolated treatment
k5=0.99; %tau5 -effort of health facilities in the transition of exposed to symptomatic
i=2.1429; %i=sigma2 -rate of home-quarantine individuals to recovered class
b=0.55; %proportion of isolated individuals
j=2.1429; %j=sigma1-rate of home-quarantine individuals to recovered class
plotchoice=8; %change plot choice
Sharing/Access information
The codes were written by the authors to simulate the outcome of all parameters.
Code/Software
MATLAB code is run by MATLAB software.