The influence of immune individuals in disease spread evaluated by cellular automaton and genetic algorithm.

BACKGROUND AND OBJECTIVE: One of the main goals of epidemiological studies is to build models capable of forecasting the prevalence of a contagious disease, in order to propose public health policies for combating its propagation. Here, the aim is to evaluate the influence of immune individuals in the processes of contagion and recovery from varicella. This influence is usually neglected. METHODS: An epidemic model based on probabilistic cellular automaton is introduced. By using a genetic algorithm, the values of three parameters of this model are determined from data of prevalence of varicella in Belgium and Italy, in a pre-vaccination period. RESULTS: This methodology can predict the varicella prevalence (with average relative error of 2%-4%) in these two European countries. Belgium data can be explained by ignoring the role of immune individuals in the infection propagation; however, Italy data can be explained by considering contagion exclusively mediated by immune individuals. CONCLUSIONS: The role of immune individuals should be accurately delineated in investigations on the dynamics of disease propagation. In addition, the proposed methodology can be adapted for evaluating, for instance, the role of asymptomatic carriers in the novel coronavirus spread.

Infection as a Stroke Risk Factor and Determinant of Outcome After Stroke.

Understanding the relationship between infection and stroke has taken on new urgency in the era of the coronavirus disease 2019 (COVID-19) pandemic. This association is not a new concept, as several infections have long been recognized to contribute to stroke risk. The association of infection and stroke is also bidirectional. Although infection can lead to stroke, stroke also induces immune suppression which increases risk of infection. Apart from their short-term effects, emerging evidence suggests that poststroke immune changes may also adversely affect long-term cognitive outcomes in patients with stroke, increasing the risk of poststroke neurodegeneration and dementia. Infections at the time of stroke may also increase immune dysregulation after the stroke, further exacerbating the risk of cognitive decline. This review will cover the role of acute infections, including respiratory infections such as COVID-19, as a trigger for stroke; the role of infectious burden, or the cumulative number of infections throughout life, as a contributor to long-term risk of atherosclerotic disease and stroke; immune dysregulation after stroke and its effect on the risk of stroke-associated infection; and the impact of infection at the time of a stroke on the immune reaction to brain injury and subsequent long-term cognitive and functional outcomes. Finally, we will present a model to conceptualize the many relationships among chronic and acute infections and their short- and long-term neurological consequences. This model will suggest several directions for future research.