Introduction: Certain behavioral practices, such as wearing masks, practicing social distancing, and accepting vaccines, play a crucial role in impeding the spread of COVID-19 and reducing the severity of symptoms. Opinions regarding whether to observe such behavioral practices evolve over time through interactions via networks that overlap with but are not identical to the physical interaction networks over which the disease progresses. This necessitates the joint study of the dynamics of COVID-19 and opinion evolution.
Methods: We develop a mathematical model that can be easily adapted to a wide range of behavioral practices and captures in a computationally tractable manner the joint evolution of the disease and relevant opinions in populations of large sizes. Populations of large sizes are typically heterogeneous in that they comprise individuals of different age groups, genders, races, and underlying health conditions. Such groups have different propensities to imbibe severe forms of the disease, different physical contact, and social interaction patterns and rates. These lead to different disease and opinion dynamics in them. Our model is designed to effectively capture such diversities.
Results: Computations using our model reveal that opinion dynamics have a strong impact on fatality and hospitalization counts and the number of man-days lost due to symptoms both in the regular form of the disease and the extended forms, more commonly known as long COVID. We show that opinion dynamics in certain groups have a disproportionate impact on the overall public health attributes because they have high physical interaction rates, even when they have the lowest propensity to imbibe severe forms of the disease. This identifies a social vulnerability that malactors can utilize to inflict heavy public health damages through opinion campaigns targeting specific segments. Once such vulnerabilities are identified, which we accomplish, adequate precautions may be designed to enhance resilience to such targeted attacks and better protect public health.
Discussion: By recognizing and understanding the vulnerabilities, appropriate precautions can be developed to enhance resilience against targeted attacks and safeguard public health. Our study underscores the importance of considering opinion evolution alongside disease dynamics, providing insights into the interplay between behavioral practices, opinions, and disease outcomes. We believe that our model is a valuable tool for understanding the joint dynamics of COVID-19 and opinions. We hope that our findings will help to inform public health policy and facilitate evidence-based decision-making for public health interventions.
Keywords: COVID-19; COVID-19 dynamics; behavioral practice; cooperativity; disease and opinion dynamics; long Covid; opinion dynamics; opinion spread rate.
© 2023 Ali and Sarkar.