Abstract
SummaryBackgroundSince late 2015, an epidemic of yellow fever has caused more than 7334 suspected cases in Angola and the Democratic Republic of the Congo, including 393 deaths. We sought to understand the spatial spread of this outbreak to optimise the use of the limited available vaccine stock.MethodsWe jointly analysed datasets describing the epidemic of yellow fever, vector suitability, human demography, and mobility in central Africa to understand and predict the spread of yellow fever virus. We used a standard logistic model to infer the district-specific yellow fever virus infection risk during the course of the epidemic in the region.FindingsThe early spread of yellow fever virus was characterised by fast exponential growth (doubling time of 5–7 days) and fast spatial expansion (49 districts reported cases after only 3 months) from Luanda, the capital of Angola. Early invasion was positively correlated with high population density (Pearson's r 0·52, 95% CI 0·34–0·66). The further away locations were from Luanda, the later the date of invasion (Pearson's r 0·60, 95% CI 0·52–0·66). In a Cox model, we noted that districts with higher population densities also had higher risks of sustained transmission (the hazard ratio for cases ceasing was 0·74, 95% CI 0·13–0·92 per log-unit increase in the population size of a district). A model that captured human mobility and vector suitability successfully discriminated districts with high risk of invasion from others with a lower risk (area under the curve 0·94, 95% CI 0·92–0·97). If at the start of the epidemic, sufficient vaccines had been available to target 50 out of 313 districts in the area, our model would have correctly identified 27 (84%) of the 32 districts that were eventually affected.InterpretationOur findings show the contributions of ecological and demographic factors to the ongoing spread of the yellow fever outbreak and provide estimates of the areas that could be prioritised for vaccination, although other constraints such as vaccine supply and delivery need to be accounted for before such insights can be translated into policy.FundingWellcome Trust.
Highlights
Yellow fever virus is a mosquito-borne flavivirus that causes infections in human beings, with symptoms ranging from mild non-specific illness to severe disease with jaundice, haemorrhage, and death.[1]
Interpretation Our findings show the contributions of ecological and demographic factors to the ongoing spread of the yellow fever outbreak and provide estimates of the areas that could be prioritised for vaccination, other constraints such as vaccine supply and delivery need to be accounted for before such insights can be translated into policy
Under the assumptions that reporting remained stable during this period and that the generation time had a mean of 15 days (SD 6; appendix), we estimated that the reproduction number of yellow fever virus was 4·8
Summary
Yellow fever virus is a mosquito-borne flavivirus that causes infections in human beings, with symptoms ranging from mild non-specific illness to severe disease with jaundice, haemorrhage, and death.[1] A single-dose vaccine has existed since the 1940s and has helped to control and reduce yellow fever virus transmission substantially.[2,3,4] Complete eradication is, prevented by the sylvatic cycle of the virus within which non-human primates act as primary hosts and Aedes aegypti mosquitoes are responsible for occasional transmission to people.[5,6]. From Dec 5, 2015, to November, 2016, a large yellow fever outbreak has affected Angola and the Democratic Republic of the Congo (DR Congo), with 7334 suspected cases, of which 962 have been confirmed, and 393 deaths reported to WHO as of Oct 28, 2016.7 Responses to such outbreaks rely mainly on reactive vaccination campaigns and pose various strategic and logistical challenges. In the context of finite resources, decisions about which geographic areas should be targeted first need to be informed by a detailed understanding of the determinants of the spatial spread of yellow fever virus and by predictions of where yellow fever virus is most likely to spread to in the future
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