When a disease spreads through a population, it encounters certain individuals it cannot infect. If there are enough of these individuals, the epidemic stops. This phenomenon is known as ‘herd immunity’, and it occurs in many animals – for example, it plays an important role in human vaccination schemes. While bacteria can cause disease, they are themselves targeted by viruses called ‘phages’. Bacteria can overcome this threat, and they resist phage attacks in ways that are well understood at the molecular level. However, little is known about the impact of this resistance at the scale of the population. Can herd immunity occur in bacteria? If so, what factors influence the threshold at which it will occur? In other words, what affects the minimum percentage of immune bacteria needed to stop the spread of a phage infection? To answer these questions, Payne et al. used both experimental and mathematical methods. For the experiments, a phage and two strains of bacteria were used, one immune to the virus and one not. The two strains were combined to form several populations with different percentages of resistant bacteria, and the phage was added. How the virus could spread in these different populations was recorded. This confirmed that herd immunity does occur in bacteria and showed how the resistant bacteria influence the speed which an epidemic spreads in a population. Building on the experiments, Payne et al. then produced a mathematical model to explore how different factors affect herd immunity. For example, the model showed that the thresholds for herd immunity can be predicted from how quickly bacteria and phages replicate. The thresholds are lower when bacteria reproduce more quickly, but higher when it is the phages that multiply faster. The model also helps infer a formula that informs on how diseases spread in any species, such as humans. In particular, it becomes possible to predict herd immunity thresholds based on how quickly an epidemic spreads in a population where few people are vaccinated. Future research is needed to adapt the formula to the specific factors that shape disease outbreaks in humans. Ultimately, this could help policymakers design strategies to deal with infectious diseases, such as yearly outbreaks of the flu.
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