Analysing the impact of migration on HIV/AIDS cases using epidemiological modelling to guide policy makers

In this paper,we present the impact of migration on the spread of HIV and AIDS cases.A simple model for HIV and AIDS that incorporates migration and addresses its contributions to the spread of HIV and AIDS cases was constructed.The model was calibrated to HIV and AIDS incidence data from Malaysia.We explore the use of Markov chain Monte Carlo(MCMC)simulation method to estimate uncertainty in all the unknown parameters incorporated in our proposed model.Among the migrant population,1.5572e-01 were susceptible to HIV transmission,which constituted 67,801 migrants.A proportion of migrants,6.3773e-04,were estimated to be HIV infected,constituting 278 migrants.There were 72(per 10,000)migrants estimated to have had AIDS,representing a proportion of 1.6611e-08.The result suggests that the disease-free steady state was unstable since the estimated basic reproduction number R0 was 2.0906 and 2.3322 for the models without and with migration,respectively.This is not a good indicator from the public health point of view,as the aim is to stabilize the epidemic at the disease-free equilibrium.The advantage of introduction of migration to the simple model validated the true R0 and the transmission rate b associated with HIV and AIDS epidemic disease in Malaysia.It also indicates an approximately 12 percentage points increase in the rate of HIV infection with migration.

A COVID-19 mathematical model of at-risk populations with non-pharmaceutical preventive measures:The case of Brazil and South Africa

This work examines a mathematical model of COVID-19 among two subgroups:low-risk and high-risk populations with two preventive measures;non-pharmaceutical interventions including wearing masks,maintaining social distance,and washing hands regularly by the low-risk group.In addition to the interventions mentioned above,highrisk individuals must take extra precaution measures,including telework,avoiding social gathering or public places,etc.to reduce the transmission.Those with underlying chronic diseases and the elderly(ages 60 and above)were classified as high-risk individuals and the rest as low-risk individuals.The parameter values used in this study were estimated using the available data from the Johns Hopkins University on COVID-19 for Brazil and South Africa.We evaluated the effective reproduction number for the two countries and observed how the various parameters affected the effective reproduction number.We also performed numerical simulations and analysis of the model.Susceptible and infectious populations for both low-risk and high-risk individuals were studied in detail.Results were displayed in both graphical and table forms to show the dynamics of each country being studied.We observed that non-pharmaceutical interventions by highrisk individuals significantly reduce infections among only high-risk individuals.In contrast,non-pharmaceutical interventions by low-risk individuals have a significant reduction in infections in both subgroups.Therefore,low-risk individuals’preventive actions have a considerable effect on reducing infections,even among high-risk individuals.

A compartmental model to investigate the dynamics of the COVID-19 pandemic:A case study in five countries

Coronavirus Disease 2019(COVID-19),caused by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infections,was declared a pandemic by the WHO on March 12,2020.By April 10,2020,it has spread to almost 215 UN Territories,affected more than 1,600,000 people,and become fatal to more than 100,000 people.We propose a compartmental model to investigate the dynamics of the COVID-19 pandemic and analyze the effects of governments and health officials’intervention strategies,using data in the USA,Italy,Spain,Germany,and France.These are the countries with the most confirmed cases of the COVID-19 as of April 11,2020.We perform parameter estimations,sensitivity,and predictive analysis and compare the COVID-19 trend in these understudy countries.Based on the model,we compute the basic reproduction number of the pandemic in these countries.The results indicate that the most sensitive parameters are the contact rate and degree of intervention;these parameters have high value in containing the pandemic.The basic reproduction number in each of the countries under study is more than unity.Based on our findings,the COVID-19 pandemic will continue to spread;but higher compliance with the intervention strategies will help minimize the disease’s spread.

The impact of implementing HIV prevention policies therapy and control strategy among HIV and AIDS incidence cases in Malaysia

Malaysia is faced with a high HIV/AIDS burden that poses a public health threat.We constructed and applied a compartmental model to understand the spread and control of HIV/AIDS in Malaysia.A simple model for HIV and AIDS disease that incorporates condom and uncontaminated needle-syringes interventions and addresses the relative impact of given treatment therapy for infected HIV newborns on reducing HIV and AIDS incidence is presented.We demonstrated how treatment therapy for new-born babies and the use of condoms or uncontaminated needle-syringes impact the dynamics of HIV in Malaysia.The model was calibrated to HIV and AIDS incidence data from Malaysia from 1986 to 2011.The epidemiological parameters are estimated using Bayesian inference via Markov chain Monte Carlo simulation method.The reproduction number optimal for control of the HIV/AIDS disease obtained suggests that the disease-free equilibrium was unstable during the 25 years.However,the results indicated that the use of condoms and uncontaminated needle-syringes are pivotal intervention control strategies;a comprehensive adoption of the intervention may help stop the spread of HIV disease.Treatment therapy for newborn babies is also of high value;it reduces the epidemic peak.The combined effect of condom use or uncontaminated needle-syringe is more pronounced in controlling the spread of HIV/AIDS.