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Review 2: "Yellow Fever in Ghana: Predicting Emergence and Ecology from Historical Outbreaks"

While acknowledging the strengths of the studies, reviewers also offer constructive criticism regarding methodological clarity, data interpretation, and the need for updated references. 

Published onMar 08, 2024
Review 2: "Yellow Fever in Ghana: Predicting Emergence and Ecology from Historical Outbreaks"
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key-enterThis Pub is a Review of
Yellow fever in Ghana: Predicting emergence and ecology from historical outbreaks
Yellow fever in Ghana: Predicting emergence and ecology from historical outbreaks

Abstract Understanding the epidemiology and ecology of yellow fever in endemic regions is critical for preventing future outbreaks. Ghana is a high-risk country for yellow fever. In this study we estimate the epidemiology, ecological cycles, and areas at risk for yellow fever in Ghana based on historical outbreaks. We identify 2371 cases and 887 deaths (case fatality rate 37.4%) from yellow fever reported in Ghana from 1910 to 2022. Since implementation of routine childhood vaccination in 1992, the estimated mean annual number of cases decreased by 81% and the geographic distribution of yellow fever cases also changed. While there have been multiple large historical outbreaks of yellow fever in Ghana from the urban cycle, recent outbreaks have originated among unvaccinated nomadic groups in rural areas with the sylvatic/savanna cycles. Using machine learning and an ecological niche modeling framework, we predict areas in Ghana that are similar to where prior yellow fever outbreaks have originated based on temperature, precipitation, landcover, elevation, and human population density. We find differences in predictions depending on the ecological cycles of outbreaks. Ultimately, these findings and methods could be used to inform further subnational risk assessments for yellow fever in Ghana and other high-risk countries.Author Summary Yellow fever is a viral hemorrhagic fever transmitted by mosquitoes in Africa and South America through different ecological transmission cycles. While West Africa has had the most cases of yellow fever, less is known about the epidemiology and ecology of yellow fever among countries in this region. Ghana has had multiple yellow fever outbreaks, including a recent outbreak in 2021-2022. In this study we estimate cases and deaths due to yellow fever in Ghana, compare the ecological cycles of outbreaks, and predict future areas at risk based on prior yellow fever cases and environmental conditions. We find that the populations at risk for yellow fever in Ghana have changed over the past century and that different ecological factors influence the risk of future emergence. Understanding these changes and the nuances of yellow fever epidemiology and ecology within countries will be important for future outbreak preparedness.

RR:C19 Evidence Scale rating by reviewer:

  • Strong. The main study claims are very well-justified by the data and analytic methods used. There is little room for doubt that the study produced has very similar results and conclusions as compared with the hypothetical ideal study. The study’s main claims should be considered conclusive and actionable without reservation.


Review: The main claim of "Yellow fever in Ghana: Predicting emergence and ecology from historical outbreaks" by Seth D. Judson and colleagues is that by analyzing historical outbreaks of yellow fever in Ghana, it is possible to predict future emergence and understand the ecological factors contributing to its spread. This study on the epidemiology and ecology of yellow fever in Ghana stands out as a pivotal contribution to our understanding of infectious diseases in Africa, addressing a critical gap in the availability of detailed information on endemic pathogens. The authors' exhaustive collection and analysis of data from 1910 to 2022, revealing 2371 cases and 887 fatalities, offer invaluable insights into the historical and ongoing impact of yellow fever. Their pioneering application of machine learning and ecological niche modeling introduces a groundbreaking approach to predicting potential outbreak areas, considering various environmental and human factors. The nuanced differentiation between past urban outbreaks and recent ones among unvaccinated, nomadic populations in rural areas underlines the adaptability and complexity of yellow fever transmission. This insight is particularly valuable for tailoring public health measures to the evolving nature of the disease's spread. The study's methodology, blending historical data analysis with advanced predictive modeling, provides a robust framework that can significantly inform and enhance public health strategies not only in Ghana but also in other regions facing similar challenges.By emphasizing the reduction in yellow fever cases following the implementation of routine childhood vaccinations and identifying shifts in the geographic distribution of cases, the research highlights the effectiveness of ongoing public health interventions and the importance of continued vigilance in disease surveillance and vaccination efforts.

The most important takeaway for the lay public, policymakers, and media from this preprint is the significance of using historical data on yellow fever outbreaks in Ghana to forecast future occurrences and identify ecological drivers. This knowledge is crucial for improving public health strategies, informing policy decisions, and raising awareness about yellow fever prevention and control measures to mitigate the impact of future outbreaks.

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