Mathematical modeling of postcoinfection with influenza A virus and Streptococcus pneumoniae, with implications for pneumonia and COPD-risk assessment

Abstract

Background

The interaction between influenza and pneumococcus is important for understanding how coinfection may exacerbate pneumonia. Secondary pneumococcal pneumonia associated with influenza infection is more likely to increase respiratory morbidity and mortality. This study aimed to assess exacerbated inflammatory effects posed by secondary pneumococcal pneumonia, given prior influenza infection.

Materials and methods

A well-derived mathematical within-host dynamic model of coinfection with influenza A virus and Streptococcus pneumoniae (SP) integrated with dose–response relationships composed of previously published mouse experimental data and clinical studies was implemented to study potentially exacerbated inflammatory responses in pneumonia based on a probabilistic approach.

Results

We found that TNFα is likely to be the most sensitive biomarker reflecting inflammatory response during coinfection among three explored cytokines. We showed that the worst inflammatory effects would occur at day 7 SP coinfection, with risk probability of 50% (likely) to develop severe inflammatory responses. Our model also showed that the day of secondary SP infection had much more impact on the severity of inflammatory responses in pneumonia compared to the effects caused by initial virus titers and bacteria loads.

Conclusion

People and health care workers should be wary of secondary SP infection on day 7 post-influenza infection for prompt and proper control-measure implementation. Our quantitative risk-assessment framework can provide new insights into improvements in respiratory health especially, predominantly due to chronic obstructive pulmonary disease (COPD).

Keywords:

• chronic obstructive pulmonary disease
• pneumonia
• influenza
• coinfection
• modeling
• risk assessment

Supplementary materials

Figure S1 Relationships between bacterial loads and different cytokine levels.

Note: Linear regression analysis for various inflammatory cytokines (A) IL6, (B) IL10, (C) KC, (D) TNFα, and (E) IFNγ.

Table S1 Summary of extracted data for mice coinfected with IAV and SP from previously published studies

Table S2 Inflammatory cytokines in IAV-associated pneumonia patients

Table S3 IAV and SP coinfection-associated inflammatory effect (fold) varied with cytokines, day of introducing SP post-IAV infection, and exceedance risks at 0.8, 0.5, and 0.2

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Acknowledgments

The authors acknowledge the financial support of the Ministry of Science and Technology, Republic of China, under grant MOST 104-2221-E-002-030-MY3.

Author contributions

All authors contributed toward data analysis, drafting and critically revising the paper, and agreed to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.