Assessing yellow fever outbreak potential and implications for vaccine strategy

PLOS Glob Public Health. 2024 Nov 13;4(11):e0003781. doi: 10.1371/journal.pgph.0003781. eCollection 2024.

Abstract

Yellow fever (YF), a vector-borne viral hemorrhagic fever, is endemic in tropical regions of Africa and South America, with large vaccination programmes being used for control. However, significant outbreaks have occurred in recent years. Data on infection rates and seroprevalence is often sparse, requiring robust mathematical models to estimate the burden of yellow fever. In particular, modelling is required to estimate the risk of outbreaks and inform policy decisions regarding the targeting of vaccination. We present a dynamic, stochastic model of YF transmission which uses environmental covariates to estimate the force of infection due to spillover from the sylvatic (non-human primate) reservoir and the basic reproduction number for human-to-human transmission. We examine the potential for targets identified by the World Health Organization EYE Strategy (50%, 60% or 80% vaccination coverage in 1-60 year olds) to achieve different threshold values for the effective reproduction number. Threshold values are chosen to reflect the potential for seasonal and/or climatic variation in YF transmission even in a scenario where vaccination lowers the median reproduction number below 1. Based on parameter estimates derived from epidemiological data, it is found that the 2022 EYE Strategy target coverage is sufficient to reduce the static averaged annual effective reproduction number R below 1 across most or all regions in Africa depending on the effectiveness of reported vaccinations, but insufficient to reduce it below 0.5 and thereby eliminate outbreaks in areas with high seasonal range. Coverage levels aligned with the 2026 targets are found to significantly decrease the proportion of regions where R is greater than 0.5.

Grants and funding

This work was conducted as part of the Vaccine Impact Modelling Consortium (www.vaccineimpact.org). The views expressed are those of the authors and do not necessarily reflect those of the Consortium or its funders. The funders were provided the opportunity to review the manuscript prior to publication, but the final decision on the content rests with the authors. This study was supported, in whole or in part, by the Bill & Melinda Gates Foundation through the Vaccine Impact Modelling Consortium [Grant Number INV-034281], previously (OPP1157270 / INV-009125), Gavi, the Vaccine Alliance, and the Wellcome Trust [Grant Number 226727_Z_22_Z]. In accordance with the grant conditions of the Foundation, a Creative Commons Attribution 4.0 Generic License has already been assigned to the Author Accepted Manuscript version that may arise from this submission. KF, NMF, and KAMG received funding from Gavi, the Bill & Melinda Gates Foundation, and/or the Wellcome Trust through VIMC during the course of this study. Additionally, KF, AH, NMF, and KAMG acknowledge funding from the MRC Centre for Global Infectious Disease Analysis (reference MR/X020258/1), supported by the UK Medical Research Council (MRC). This UK-funded award is part of the Global Health EDCTP3 Joint Undertaking.