Yellow Fever in Africa: estimating the burden of disease and impact of mass vaccination from outbreak and serological data

Abstract

Background: Yellow fever is a vector-borne disease affecting humans and non-human primates in tropical areas of Africa and South America. While eradication is not feasible due to the wildlife reservoir, large scale vaccination activities in Africa during the 1940s to 1960s reduced yellow fever incidence for several decades. However, after a period of low vaccination coverage, yellow fever has resurged in the continent. Since 2006 there has been substantial funding for large preventive mass vaccination campaigns in the most affected countries in Africa to curb the rising burden of disease and control future outbreaks. Contemporary estimates of the yellow fever disease burden are lacking, and the present study aimed to update the previous estimates on the basis of more recent yellow fever occurrence data and improved estimation methods.

Methods and findings: Generalised linear regression models were fitted to a dataset of the locations of yellow fever outbreaks within the last 25 years to estimate the probability of outbreak reports across the endemic zone. Environmental variables and indicators for the surveillance quality in the affected countries were used as covariates. By comparing probabilities of outbreak reports estimated in the regression with the force of infection estimated for a limited set of locations for which serological surveys were available, the detection probability per case and the force of infection were estimated across the endemic zone. The yellow fever burden in Africa was estimated for the year 2013 as 130,000 (95% CI 51,000-380,000) cases with fever and jaundice or haemorrhage including 78,000 (95% CI 19,000-180,000) deaths, taking into account the current level of vaccination coverage. The impact of the recent mass vaccination campaigns was assessed by evaluating the difference between the estimates obtained for the current vaccination coverage and for a hypothetical scenario excluding these vaccination campaigns. Vaccination campaigns were estimated to have reduced the number of cases and deaths by 27% (95% CI 22%-31%) across the region, achieving up to an 82% reduction in countries targeted by these campaigns. A limitation of our study is the high level of uncertainty in our estimates arising from the sparseness of data available from both surveillance and serological surveys.

Conclusions: With the estimation method presented here, spatial estimates of transmission intensity can be combined with vaccination coverage levels to evaluate the impact of past or proposed vaccination campaigns, thereby helping to allocate resources efficiently for yellow fever control. This method has been used by the Global Alliance for Vaccines and Immunization (GAVI Alliance) to estimate the potential impact of future vaccination campaigns.

Figure 1. Geographical distribution of yellow fever occurrence and transmission.

(A) Presence/absence of yellow fever over a 25-year period, by province. White, absence; red, presence of yellow fever reports. (B) Model predictions giving the estimated probability of at least one yellow fever report. (C) Estimates of the annual force of infection at the province level in the 32 countries considered endemic for yellow fever. (D) Estimates of the country-specific detection probability per infection. Countries not considered endemic for yellow fever are shown in navy (A, B, and D) or white (C).

Figure 2. Goodness of fit measures.

(A) BIC and (B) AUC values for the 15 models investigated with MCMC, with a prior standard deviation on the country factors of 2. Circles show posterior means, lines the 95% posterior range.

Figure 3. Impact of preventive mass vaccination campaigns between 2006 and 2012 on the estimated number of deaths due to yellow fever in 2013 by country.

Red bars show the number of deaths estimated assuming implementation of no mass vaccination campaigns between 2006 and 2012, orange bars show the number of deaths estimated for the actual vaccination. Lines show the 95% credibility intervals of the estimated number of deaths. Countries are ordered west to east.

Figure 4. Deaths over time under various vaccination coverage scenarios for Ghana (top: A–C) and Liberia (bottom: D–F).

Thick lines show the point estimate, hashed areas the 95% credibility intervals. Baseline scenario (black) in (A–F) includes past mass vaccination and infant immunization, plus continuing infant immunization at 2011 coverage levels. Alternative scenario (red): (A and D): as baseline, but excluding the mass vaccination campaigns; (B and E): as baseline, but assuming no infant immunization at any time; (C and F): as baseline, but including mass vaccination campaigns targeting children under 5 every 5 years at a coverage of 90% instead of future infant immunization.

Figure 5. Percentage of the all-cause mortality attributable to yellow fever by country.

Grey bars indicate the point estimates, black lines the range spanned by the 95% CIs of the burden estimates. Countries are ordered west to east.