Effects of infection fatality ratio and social contact matrices on vaccine prioritization strategies

Abstract

Effective strategies of vaccine prioritization are essential to mitigate the impacts of severe infectious diseases. We investigate the role of infection fatality ratio (IFR) and social contact matrices on vaccination prioritization using a compartmental epidemic model fueled by real-world data of different diseases (COVID-19 and influenza) and countries (Brazil, Germany, and Uganda). Our study confirms that massive and early vaccination is extremely effective to reduce the disease fatality if the contagion is mitigated, but the effectiveness is increasingly reduced as vaccination beginning delays in an uncontrolled epidemiological scenario. The optimal and least effective prioritization strategies depend non-linearly on epidemiological variables. Regions of the epidemiological parameter space, in which prioritizing the most vulnerable is more effective than the most contagious individuals, are substantially broader for COVID-19's IFR in comparison with influenza. Demographics and social contact matrices deform the phase diagrams but do not alter their qualitative shapes.