Yellow fever: examining potential burden on vaccine strategy

In a recent study posted to the SSRN* preprint server, researchers presented a stochastic model of yellow fever transmission based on environmental covariates, which estimated the force of the infection using data on the spillover of the virus from non-human primate or sylvatic reservoirs and human-to-human transmission reproduction number.

Study: Assessing Yellow Fever Outbreak Potential and Implications for Vaccine Strategy. Image Credit: frank60/Shutterstock.com

*Important notice: Preprints with The Lancet / SSRN publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Background

Yellow fever is a viral disease that causes hemorrhagic fever and spreads through insect vectors. It has a high fatality rate for severe cases and is prevalent in the tropical regions of South America and Africa.

Moreover, since the virus persists among non-human primates, the complete eradication of the disease has been impossible, and vaccines remain the major form of disease control.

Recent years have seen an increase in the number of yellow fever outbreaks, and prevention of yellow fever outbreaks is essential, especially for regions with no previous history of yellow fever with populations that are immunologically naïve and unvaccinated.

Furthermore, the paucity of data on seroprevalence in populations that have experienced yellow fever outbreaks and infection rates necessitates using mathematical models to estimate the probability of yellow fever outbreaks and the health burden of these outbreaks.

Previous models have largely considered the overall longitudinal burden of yellow fever rather than the size and frequency of outbreaks. Accurate estimations of outbreak risk are essential for implementing vaccination and other public health policies against yellow fever.

About the study

In the present study, the researchers developed a novel stochastic transmission model that uses environmental covariates and estimates the risk of outbreaks using data on urban transmission between humans through mosquitoes that feed on humans and spillover from sylvatic reservoirs that involve mosquitoes that feed on non-human primates and humans.

Previous models considered the two transmission rates — non-human primate-to-human and human-to-human — separately.

The researchers used available case data and serological information. They applied the model to project how effective vaccine coverage targets would be in preventing outbreaks by decreasing the human-to-human transmission effective reproduction number.

The model was also used to evaluate the effectiveness of the World Health Organization’s (WHO) strategy to eliminate yellow fever outbreaks.

A wide range of parameters was incorporated into the model, including the basic and effective reproduction numbers, the number of severe cases, the fatality rates among severe cases, reporting rates for extreme cases and fatalities, vaccine efficacy, etc.

Annual case data and serological information were simulated for hypothetical regions to evaluate the model’s ability to infer epidemiological parameters using insufficient data.

Serological and reported annual case data were obtained from studies across South American and African countries between 1985 and 2015, and the United Nations World Population Prospects database was used to obtain population-wide data on mass vaccination campaigns and infant vaccination programs.

Various environmental covariates such as the occurrence of non-human primate species within a region, the presence-absence data for Aedes aegypti mosquitoes, the suitable temperature range for mosquitoes, and the proportion of land area in the region covered by grasslands were also used in the model.

Results

The results reported that based on the model estimates, the WHO’s Eliminate Yellow Fever Epidemics (EYE) strategy, which aims for 50%, 60%, and 80% coverage across individuals between the ages of one and 60 years, would be effective in reducing the effective annual reproduction in all regions of Africa to below one, which would prevent large outbreaks.

However, the EYE strategy would not be enough to lower the effective annual reproduction to below 0.5 in all the regions and, therefore, would be unable to prevent yellow fever outbreaks in regions with a high seasonal range.

Furthermore, extreme climatic events, climate change, flooding, substantial changes in land use, and seasonal variations could result in significant fluctuations in viral transmission rates across and between years.

Despite applying more stringent criteria, the probability of the WHO’s vaccination strategy lowering the effective annual reproduction to below 0.5 was found to be 5% in some regions of Africa. However, the probability of lowering the effective annual reproduction to below one in all regions of Africa was 100%.

These findings indicate that the vaccination targets need to be reviewed and improved, possibly by expanding the target age range. This might present a challenge in some regions of Africa.

Conclusions

To summarize, the new stochastic model presented in this study reported that the EYE strategy by the WHO aiming to increase the vaccination coverage against yellow fever among individuals between the ages of one and 60 years would be sufficient in limiting the number of large outbreaks in all regions of Africa but might not be sufficient in eliminating the occurrence of outbreaks.

Furthermore, climate change and extreme weather events might change annual transmission rates and increase the probability of outbreaks in certain high-burden regions.

*Important notice: Preprints with The Lancet / SSRN publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Written by

Dr. Chinta Sidharthan

Chinta Sidharthan is a writer based in Bangalore, India. Her academic background is in evolutionary biology and genetics, and she has extensive experience in scientific research, teaching, science writing, and herpetology. Chinta holds a Ph.D. in evolutionary biology from the Indian Institute of Science and is passionate about science education, writing, animals, wildlife, and conservation. For her doctoral research, she explored the origins and diversification of blindsnakes in India, as a part of which she did extensive fieldwork in the jungles of southern India. She has received the Canadian Governor General’s bronze medal and Bangalore University gold medal for academic excellence and published her research in high-impact journals.