Background To anticipate the impact of new pneumococcal vaccines and guide future updates, accurate forecasts of changes in non-vaccine serotypes (NVTs) are needed. We developed and evaluated three models that incorporated different assumptions about the way in which NVTs will increase and generated ensemble predictions for the frequency of NVTs in different post-pneumococcal conjugate vaccines (PCV) periods.

Methods We analyzed age- and serotype-specific invasive pneumococcal disease (IPD) cases from the United States CDC’s Active Bacterial Core surveillance during the pre-PCV (1998-1999), early post-PCV7 (2000-2004), late post-PCV7/pre-PCV13 (2005-2009), early post-PCV13 (2010-2014), and late post-PCV13 (2015-2019) periods. These data were augmented with IPD cases from several countries and combined with serotype-specific invasiveness to infer serotype-specific carriage prevalence. Three models (“Ranking”, “Proportionate”, “NFDS-lite”) generated independent predictions of post-PCV IPD frequencies, which were integrated using an accuracy-weighted ensemble. Model performance was evaluated using the normalized root mean square error (NRMSE).

Results A total of 23,959 non-PCV7 and 15,580 non-PCV13 cases were analyzed. NVT cases increased from the pre-PCV7 to the late post-PCV7 and post-PCV13 periods. The accuracy of predictions across age groups and models was consistent and high during the post-PCV13 periods but varied during the post-PCV7 periods. The Proportionate model (NRMSE=0.70-3.95) outperformed the NFDS-lite (NRMSE=0.93-8.91) and Ranking (NRMSE=1.51-5.37) models during the early-post-PCV7 period, whereas the NFDS-lite model (NRMSE=1.55-9.82) was superior to the Proportionate (NRMSE=1.45-10.22) and Ranking (NRMSE=1.86-11.35) models during the late post-PCV7 period. The Ensemble model improved on these individual models.

Conclusions The Ensemble model offers a tool for forecasting serotype patterns to inform pneumococcal vaccines impact and future pneumococcal vaccine formulation.

DT has received consulting fees from Vaxcyte for work unrelated to this manuscript. DMW has been principal investigator on grants from Pfizer and Merck to Yale University for work unrelated to this manuscript and has received consulting and/or speaking fees from Pfizer, Merck, Vaxcyte, and GSK/Affinivax.

Research reported in this manuscript was fully funded by GSK under award GR128426.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Centers for Disease Control and Prevention Active Bacterial Core surveillance project - Bact Facts Interactive Data Dashboard. In: Active Bacterial Core surveillance (ABCs): https://www.cdc.gov/abcs/bact-facts/data-dashboard.html

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes