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Modelling the large-scale yellow fever outbreak in Luanda, Angola, and the impact of vaccination.

ABSTRACT: Yellow fever (YF), transmitted via bites of infected mosquitoes, is a life-threatening viral disease endemic to tropical and subtropical regions of Africa and South America. YF has largely been controlled by widespread national vaccination campaigns. Nevertheless, between December 2015 and August 2016, YF resurged in Angola, quickly spread and became the largest YF outbreak for the last 30 years. Recently, YF resurged again in Brazil (December 2016). Thus, there is an urgent need to gain better understanding of the transmission pattern of YF.The present study provides a refined mathematical model, combined with modern likelihood-based statistical inference techniques, to assess and reconstruct important epidemiological processes underlying Angola's YF outbreak. This includes the outbreak's attack rate, the reproduction number ([Formula: see text]), the role of the mosquito vector, the influence of climatic factors, and the unusual but noticeable appearance of two-waves in the YF outbreak. The model explores actual and hypothetical vaccination strategies, and the impacts of possible human reactive behaviors (e.g., response to media precautions).While there were 73 deaths reported over the study period, the model indicates that the vaccination campaign saved 5.1-fold more people from death and saved from illness 5.6-fold of the observed 941 cases. Delaying the availability of the vaccines further would have greatly worsened the epidemic in terms of increased cases and deaths. The analysis estimated a mean [Formula: see text] and an attack rate of 0.09-0.15% (proportion of population infected) over the whole period from December 2015 to August 2016. Our estimated lower and upper bounds of [Formula: see text] are in line with previous studies. Unusually, [Formula: see text] oscillated in a manner that was "delayed" with the reported deaths. High recent number of deaths were associated (followed) with periods of relatively low disease transmission and low [Formula: see text], and vice-versa. The time-series of Luanda's YF cases suggest the outbreak occurred in two waves, a feature that would have become far more prominent had there been no mass vaccination. The waves could possibly be due to protective reactive behavioral changes of the population affecting the mosquito population. The second wave could well be an outcome of the March-April rainfall patterns in the 2016 El Niño year by creating ideal conditions for the breeding of the mosquito vectors. The modelling framework is a powerful tool for studying future YF epidemic outbreaks, and provides a basis for future vaccination campaign evaluations.

SUBMITTER: Zhao S

PROVIDER: S-EPMC5798855 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Modelling the large-scale yellow fever outbreak in Luanda, Angola, and the impact of vaccination.

Zhao Shi S Stone Lewi L Gao Daozhou D He Daihai D

PLoS neglected tropical diseases 20180116 1

<h4>Background</h4>Yellow fever (YF), transmitted via bites of infected mosquitoes, is a life-threatening viral disease endemic to tropical and subtropical regions of Africa and South America. YF has largely been controlled by widespread national vaccination campaigns. Nevertheless, between December 2015 and August 2016, YF resurged in Angola, quickly spread and became the largest YF outbreak for the last 30 years. Recently, YF resurged again in Brazil (December 2016). Thus, there is an urgent n ...[more]

PMID: 29338001

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Project description:BackgroundSince 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.

Project description:In March 2005, the Centers for Disease Control and Prevention (CDC) investigated a large hemorrhagic fever (HF) outbreak in Uige Province in northern Angola, West Africa. In total, 15 initial specimens were sent to CDC, Atlanta, Ga., for testing for viruses associated with viral HFs known to be present in West Africa, including ebolavirus. Marburgvirus was also included despite the fact that the origins of all earlier outbreaks were linked directly to East Africa. Surprisingly, marburgvirus was confirmed (12 of 15 specimens) as the cause of the outbreak. The outbreak likely began in October 2004 and ended in July 2005, and it included 252 cases and 227 (90%) fatalities (report from the Ministry of Health, Republic of Angola, 2005), making it the largest Marburg HF outbreak on record. A real-time quantitative reverse transcription-PCR assay utilized and adapted during the outbreak proved to be highly sensitive and sufficiently robust for field use. Partial marburgvirus RNA sequence analysis revealed up to 21% nucleotide divergence among the previously characterized East African strains, with the most distinct being Ravn from Kenya (1987). The Angolan strain was less different ( approximately 7%) from the main group of East African marburgviruses than one might expect given the large geographic separation. To more precisely analyze the virus genetic differences between outbreaks and among viruses within the Angola outbreak itself, a total of 16 complete virus genomes were determined, including those of the virus isolates Ravn (Kenya, 1987) and 05DRC, 07DRC, and 09DRC (Democratic Republic of Congo, 1998) and the reference Angolan virus isolate (Ang1379v). In addition, complete genome sequences were obtained from RNAs extracted from 10 clinical specimens reflecting various stages of the disease and locations within the Angolan outbreak. While the marburgviruses exhibit high overall genetic diversity (up to 22%), only 6.8% nucleotide difference was found between the West African Angolan viruses and the majority of East African viruses, suggesting that the virus reservoir species in these regions are not substantially distinct. Remarkably few nucleotide differences were found among the Angolan clinical specimens (0 to 0.07%), consistent with an outbreak scenario in which a single (or rare) introduction of virus from the reservoir species into the human population was followed by person-to-person transmission with little accumulation of mutations. This is in contrast to the 1998 to 2000 marburgvirus outbreak, where evidence of several virus genetic lineages (with up to 21% divergence) and multiple virus introductions into the human population was found.

Project description:BackgroundYellow 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 findingsGeneralised 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.ConclusionsWith 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.

Project description:BackgroundTo 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 findingsWe 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.ConclusionsBy estimating YF burden and vaccine impact over a range of spatial and temporal scales, while accounting for the specificity of urban transmission, our model can be used to inform the current EYE strategy.

Dataset Information

Modelling the large-scale yellow fever outbreak in Luanda, Angola, and the impact of vaccination.

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Modelling the large-scale yellow fever outbreak in Luanda, Angola, and the impact of vaccination.

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