Global stability and analysing the sensitivity of parameters of a multiple-susceptible population model of SARS-CoV-2 emphasising vaccination drive

China's policies: post-COVID-19 challenges for the older population

On 7 December 2022, the State Council of China released 'Measures to Further Optimize the Implementation of the Prevention and Control of the New Coronavirus Epidemic'. The previous three-year dynamic zero epidemic prevention policy was then replaced with a full liberalization policy. On 5 May 2023, the World Health Organization declared that COVID-19 no longer constituted a 'public health emergency of international concern.' However, given the ongoing prevalence of coronavirus, emerging mutations, and the liberalization of restrictions, there are increased risks of vulnerable people contracting new variants. Low vaccination coverage among older people with compromised immune systems, puts them at further risk. The policy shift will increase pressure on already stretched health infrastructure and medical resources. This short article adds to the current debate arguing that the Chinese government should take commensurate preventive measures, including strengthening medical facilities and equipment and targeting ongoing vaccination in older people.

Implementation of computationally efficient numerical approach to analyze a Covid-19 pandemic model

Corona virus disease (Covid-19) which has caused frustration in the human community remains the concern of the globe as every government struggles to defeat the pandemic. To deal with the situation, we have extensively studied a deadly Covid-19 model to provide a deep insight into the disease dynamics. A mathematical analysis of the model utilizing preventive measures is performed with the aim to reduce the disease burden. Some comprehensive mathematical techniques are employed to demonstrate several essential properties of solutions. To start with, we proved the existence and uniqueness of solutions. Equilibrium points are stated both in the absence and presence of the pandemic. Biologically important quantity known as threshold parameter is computed to handle the future disease dynamics and analyzed for its sensitivity. We proved the stability of the proposed model at equilibrium points by employing necessary conditions on threshold parameter. A reliable and competitive numerical analysis is conducted to observe the effectiveness of implemented strategies and to verify obtained analytical results. The most sensitive parameters are determined through sensitivity analysis. An important feature of this study is to employ Non-Standard Finite Difference (NSFD) numerical scheme to solve the system instead of other standard methods like Runge–Kutta method of order 4 (RK4). Finally, several numerical simulations are performed to validate our former theoretical analysis. Numerical results exhibiting dynamical behavior of Covid-19 system under the influence of involved parameters suggest that both the implemented strategies, especially quarantine of exposed individuals, are effective for the substantial reduction in the diseased population and to achieve the herd immunity.

Evaluating the impact of multiple factors on the control of COVID-19 epidemic: A modelling analysis using India as a case study

The currently ongoing COVID-19 outbreak remains a global health concern. Understanding the transmission modes of COVID-19 can help develop more effective prevention and control strategies. In this study, we devise a two-strain nonlinear dynamical model with the purpose to shed light on the effect of multiple factors on the outbreak of the epidemic. Our targeted model incorporates the simultaneous transmission of the mutant strain and wild strain, environmental transmission and the implementation of vaccination, in the context of shortage of essential medical resources. By using the nonlinear least-square method, the model is validated based on the daily case data of the second COVID-19 wave in India, which has triggered a heavy load of confirmed cases. We present the formula for the effective reproduction number and give an estimate of it over the time. By conducting Latin Hyperbolic Sampling (LHS), evaluating the partial rank correlation coefficients (PRCCs) and other sensitivity analysis, we have found that increasing the transmission probability in contact with the mutant strain, the proportion of infecteds with mutant strain, the ratio of probability of the vaccinated individuals being infected, or the indirect transmission rate, all could aggravate the outbreak by raising the total number of deaths. We also found that increasing the recovery rate of those infecteds with mutant strain while decreasing their disease-induced death rate, or raising the vaccination rate, both could alleviate the outbreak by reducing the deaths. Our results demonstrate that reducing the prevalence of the mutant strain, improving the clearance of the virus in the environment, and strengthening the ability to treat infected individuals are critical to mitigate and control the spread of COVID-19, especially in the resource-constrained regions.

Protection against SARS-CoV-2 BA.4 and BA.5 subvariants via vaccination and natural infection: A modeling study

With continuing emergence of new SARS-CoV-2 variants, understanding the proportion of the population protected against infection is crucial for public health risk assessment and decision-making and so that the general public can take preventive measures. We aimed to estimate the protection against symptomatic illness caused by SARS-CoV-2 Omicron variants BA.4 and BA.5 elicited by vaccination against and natural infection with other SARS-CoV-2 Omicron subvariants. We used a logistic model to define the protection rate against symptomatic infection caused by BA.1 and BA.2 as a function of neutralizing antibody titer values. Applying the quantified relationships to BA.4 and BA.5 using two different methods, the estimated protection rate against BA.4 and BA.5 was 11.3% (95% confidence interval [CI]: 0.01-25.4) (method 1) and 12.9% (95% CI: 8.8-18.0) (method 2) at 6 months after a second dose of BNT162b2 vaccine, 44.3% (95% CI: 20.0-59.3) (method 1) and 47.3% (95% CI: 34.1-60.6) (method 2) at 2 weeks after a third BNT162b2 dose, and 52.3% (95% CI: 25.1-69.2) (method 1) and 54.9% (95% CI: 37.6-71.4) (method 2) during the convalescent phase after infection with BA.1 and BA.2, respectively. Our study indicates that the protection rate against BA.4 and BA.5 are significantly lower compared with those against previous variants and may lead to substantial morbidity, and overall estimates were consistent with empirical reports. Our simple yet practical models enable prompt assessment of public health impacts posed by new SARS-CoV-2 variants using small sample-size neutralization titer data to support public health decisions in urgent situations.