Unexpected Infection Spikes in a Model of Respiratory Syncytial Virus Vaccination

Use of mathematical modelling to assess respiratory syncytial virus epidemiology and interventions: a literature review

Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory tract infection worldwide, resulting in approximately sixty thousand annual hospitalizations of< 5-year-olds in the United States alone and three million annual hospitalizations globally. The development of over 40 vaccines and immunoprophylactic interventions targeting RSV has the potential to significantly reduce the disease burden from RSV infection in the near future. In the context of RSV, a highly contagious pathogen, dynamic transmission models (DTMs) are valuable tools in the evaluation and comparison of the effectiveness of different interventions. This review, the first of its kind for RSV DTMs, provides a valuable foundation for future modelling efforts and highlights important gaps in our understanding of RSV epidemics. Specifically, we have searched the literature using Web of Science, Scopus, Embase, and PubMed to identify all published manuscripts reporting the development of DTMs focused on the population transmission of RSV. We reviewed the resulting studies and summarized the structure, parameterization, and results of the models developed therein. We anticipate that future RSV DTMs, combined with cost-effectiveness evaluations, will play a significant role in shaping decision making in the development and implementation of intervention programs.

Mathematical modelling of respiratory syncytial virus (RSV) in low- and middle-income countries: A systematic review

Background:

Due to high burden of respiratory syncytial virus (RSV) in low- and middle-income countries (LMIC), international funding organizations have prioritized the development of RSV vaccines. Mathematical models of RSV will play an important role in assessing the relative value of these interventions. Our objectives were to provide an overview of the existing RSV modelling literature in LMIC and summarize available results on population-level effectiveness and cost-effectiveness.

Methods:

We searched MEDLINE from 2000 to 2020 for English language publications that employed a mathematical model of RSV calibrated to LMIC. Qualitative data were extracted on study and model characteristics. Quantitative data were collected on key model input assumptions and base case effectiveness and cost-effectiveness estimates for various immunization strategies.

Findings:

Of the 283 articles reviewed, 15 met inclusion criteria. Ten studies used modelling techniques to explore RSV transmission and/or natural history, while eight studies evaluated RSV vaccines and/or monoclonal antibodies, three of which included cost-effectiveness analyses. Six studies employed deterministic compartmental models, five studies employed individual transmission models, and four studies used different types of cohort models. Nearly every model was calibrated to at least one middle-income country, while four were calibrated to low-income countries.

Interpretation:

The mathematical modelling literature in LMIC has demonstrated the potential effectiveness of RSV vaccines and monoclonal antibodies. This review has demonstrated the importance of accounting for seasonality, social contact rates, immunity from prior infection and maternal antibody transfer. Future models should consider incorporating individual-level risk factors, subtype-specific effects, long-term sequelae of RSV infections, and out-of-hospital mortality.