Interactions between chronic diseases: asymmetric outcomes of co-infection at individual and population scales

TL;DR

This study combines empirical data and modeling to explore how co-infection with two bacterial pathogens affects individual health and population dynamics, revealing asymmetric impacts where one pathogen facilitates infection at the individual level but suppresses the other at the population level.

Contribution

The paper introduces a novel model linking individual-level effects of co-infection to population-level patterns, supported by four-year cohort data from African buffalo.

Findings

BTB increases the risk of brucellosis at the individual level.

Both infections reduce host survival but do not affect fecundity.

Brucellosis presence decreases BTB prevalence and reproduction at the population level.

Abstract

Co-infecting parasites and pathogens remain a leading challenge for global public health due to their consequences for individual-level infection risk and disease progression. However, a clear understanding of the population-level consequences of co-infection is lacking. Here, we constructed a model that includes three individual-level effects of co-infection: mortality, fecundity, and transmission. We used the model to investigate how these individual-level consequences of co-infection scale up to produce population-level infection patterns. To parameterize this model, we conducted a four-year cohort study in African buffalo to estimate the individual-level effects of co-infection with two bacterial pathogens, bovine tuberculosis (BTB) and brucellosis, across a range of demographic and environmental contexts. At the individual-level, our empirical results identified BTB as a risk factor for acquiring brucellosis, but we found no association between brucellosis and the risk of acquiring BTB. Both infections were associated with reductions in survival and neither infection was associated with reductions in fecundity. Results of the model reproduce co-infection patterns in the data and predict opposite impacts of co-infection at individual and population scales: whereas BTB facilitated brucellosis infection at the individual-level, our model predicts the presence of brucellosis to have a strong negative impact on BTB at the population-level. In modeled populations where brucellosis is present, the endemic prevalence and basic reproduction number (Ro) of BTB were lower than in populations without brucellosis. Therefore, these results provide a data-driven example of competition between co-infecting pathogens that occurs when one pathogen facilitates secondary infections at the individual level.