A modelling approach to characterise the interaction between behavioral response and epidemics: A study based on COVID-19

During epidemic outbreaks, human behavior is highly influential on the disease transmission and hence affects the course, duration and outcome of the epidemics. In order to examine the feedback effect between the dynamics of the behavioral response and disease outbreak, a simple SIR-β type model is established by introducing the independent variable β of effective contact rate, characterizing how human behavior interacts with disease transmission dynamics and allowing for the feedback changing over time along the progress of epidemic and population's perception of risk. By a particle swarm optimization algorithm in the solution procedures and time series of COVID-19 data with different shapes of infection peaks, we show that the proposed model, together with such behavioral change mechanism, is capable of capturing the trend of the selected data and can give rise to oscillatory prevalence of different magnitude over time, revealing how different levels of behavioral response affect the waves of infection as well as the evolution of the disease.

Modelling human response to information in voluntary vaccination behaviour using epidemic data

Here, we considered Holling functional responses, a core concept in population dynamics, and discussed their potential interpretation in the context of social epidemiology. Then, we assessed which Holling functional response best represents the vaccination behaviour of individuals when such a behaviour is influenced by information and rumours about the disease. In particular, we used the Holling functionals to represent the information-dependent vaccination rate in a socio-epidemiological model for meningococcal meningitis. As a field case test, we estimated the information-related parameters by using official data from a meningitis outbreak in Nigeria and numerically assessed the impact of the functionals on the solutions of the model. We observed significant inaccuracies on parameter estimates when either Holling type Ⅰ or Holling type Ⅲ functional were used. On the contrary, when the Holling type Ⅱ functional was employed, epidemiological data were well reproduced, and reasonable values of the information parameters were obtained. Given the socio-epidemiological interpretation of the Holling type Ⅱ functional, this means that the rate at which susceptible individuals come into contact with information may be assumed to be constant and that the time needed to handle the available information cannot be neglected.

Evaluating vaccination timing, hesitancy and effectiveness to prevent future outbreaks: insights from COVID-19 modelling and transmission dynamics

The COVID-19 vaccine has been available in India since January 2021, although many individuals have refused to take the vaccine for various reasons. Vaccination plays a crucial role in disease control by preventing a substantial number of cases and associated disabilities. However, vaccine hesitancy poses a barrier that hinders these efforts. Our article presents a novel approach by proposing a mathematical model for COVID-19 that incorporates vaccine hesitancy, vaccine efficacy and behaviour compensation post-vaccination. The model is calibrated with COVID-19 incidence data for India from 13 February 2021 to 12 January 2022, using the Markov chain Monte Carlo method. The analysis examines the effects of hesitancy and social interventions through a series of practical simulations. The simulation results show that while COVID-19-infected individuals may have natural immunity, vaccination post-recovery is crucial to reduce cases by up to 64.1%. Social interventions, such as face masks and distancing, remain essential to prevent a rise in cases and ensure effective disease control. The model demonstrates that vaccination, combined with continued social interventions, is crucial for effectively reducing COVID-19 cases and preventing future outbreaks. Addressing vaccine hesitancy and maintaining preventive measures are key to successfully controlling the pandemic.

Lunar New Year and Eid al Fitr: the circle of COVID-19

Lunar New Year and Eid al-Fitr are national holidays, and mass movement of people is seen. Lunar New Year 2020 potentiated the spread of coronavirus disease 2019 (COVID-19), while Eid al-Fitr 2022 was a test for federal management of COVID-19 and the success of the Indonesian vaccination campaign. Analysis of new confirmed cases, hospitalizations and the number of elective surgery cancellations due to positive polymerase chain reaction screening in the pre-operative period provides a snapshot of herd immunity.