Eliminating yellow fever epidemics in Africa: Vaccine demand forecast and impact modelling

Abstract

Background To counter the increasing global risk of Yellow fever (YF), the World Health Organisation initiated the Eliminate Yellow fever Epidemics (EYE) strategy. Estimating YF burden, as well as vaccine impact, while accounting for the features of urban YF transmission such as indirect benefits of vaccination, is key to informing this strategy. Methods and findings We developed two model variants to estimate YF burden in sub-Saharan Africa, assuming all infections stem from either the sylvatic or the urban cycle of the disease. Both relied on an ecological niche model fitted to the local presence of any YF reported event in 34 African countries. We calibrated under-reporting using independent estimates of transmission intensity provided by 12 serological surveys performed in 11 countries. We calculated local numbers of YF infections, deaths and disability-adjusted life years (DALYs) lost based on estimated transmission intensity while accounting for time-varying vaccination coverage. We estimated vaccine demand and impact of future preventive mass vaccination campaigns (PMVCs) according to various vaccination scenarios. Vaccination activities conducted in Africa between 2005 and 2017 were estimated to prevent from 3.3 (95% CI 1.2-7.7) to 6.1 (95% CI 2.4-13.2) millions of deaths over the lifetime of vaccinees, representing extreme scenarios of none or maximal herd effects, respectively. By prioritizing provinces based on the risk of urban YF transmission in future PMVCs, an average of 37.7 million annual doses for PMVCs over eight years would avert an estimated 9,900,000 (95% CI 7,000,000-13,400,000) infections and 480,000 (180,000-1,140,000) deaths over the lifetime of vaccinees, corresponding to 1.7 (0.7-4.1) deaths averted per 1,000 vaccine doses.

The global burden of yellow fever

“…We estimate our models from two main sources of data that we have updated where possible. The occurrence data was expanded to account for additional years and locations from Garske et al, 2014 ; Gaythorpe et al, 2019 ; Jean et al, 2020 ; Hamlet et al, 2019 . Yet there are assumptions and uncertainty that are inherent in this data.…”

“…A database of yellow fever occurrence was collated. This was compiled in two parts: occurrence in Africa was compiled originally in Garske et al and has been subsequently maintained and updated ( Garske et al, 2014 ; Gaythorpe et al, 2019 ; Jean et al, 2020 ). Occurrence of yellow fever in South America was collated by Hamlet et al, 2019 .…”

Assessing the impact of preventive mass vaccination campaigns on yellow fever outbreaks in Africa: A population-level self-controlled case series study

“…This study relied on datasets that were previously collected and regularly updated for a broader project aiming at estimating the burden of yellow fever and the impact of vaccine activities [ 4 , 6 ]. The analytic plan was defined before the start of the analysis.…”

“…Previous attempts have been made to estimate the impact of vaccination activities, including PMVCs [ 4 – 6 ]. These attempts mostly relied on mathematical models to estimate PMVC impact in terms of deaths or cases prevented over the long term.…”

Assessing the impact of preventive mass vaccination campaigns on yellow fever outbreaks in Africa : a population-level self-controlled case-series study

“…Previous attempts were made in order to estimate the impact of vaccination activities, including PMVCs [4–6]. These attempts mostly relied on mathematical models to estimate PMVCs impact in terms of deaths or cases prevented on the long term.…”