Mosquito and primate ecology predict human risk of yellow fever virus spillover in Brazil

Childs, Marissa L.; Nova, Nicole; Colvin, Justine; Mordecai, Erin A.

doi:10.1098/rstb.2018.0335

Cited by 49 publications

(49 citation statements)

References 112 publications

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“…Analyzing dynamical models in a comparative way (for instance, looking at the dynamics generated across multiple NHPs and vectors) may reveal parameters that are particularly influential for YFV transmission dynamics and species that are particularly important for spillover transmission. In addition to organismal factors, machine learning of environmental factors describing YFV spillover [58], in combination with transmission models of YFV transmission [59] can help distinguish the relative importance of multiple interacting factors contributing to the risk of spillover transmission.…”

Section: Predictive Modeling For Yfv Ecologymentioning

confidence: 99%

Re-emergence of yellow fever in the neotropics — quo vadis?

Sacchetto

Drumond

Han

et al. 2020

Emerging Topics in Life Sciences

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Yellow fever virus (YFV) is the etiological agent of yellow fever (YF), an acute hemorrhagic vector-borne disease with a significant impact on public health, is endemic across tropical regions in Africa and South America. The virus is maintained in two ecologically and evolutionary distinct transmission cycles: an enzootic, sylvatic cycle, where the virus circulates between arboreal Aedes species mosquitoes and non-human primates, and a human or urban cycle, between humans and anthropophilic Aedes aegypti mosquitoes. While the urban transmission cycle has been eradicated by a highly efficacious licensed vaccine, the enzootic transmission cycle is not amenable to control interventions, leading to recurrent epizootics and spillover outbreaks into human populations. The nature of YF transmission dynamics is multifactorial and encompasses a complex system of biotic, abiotic, and anthropogenic factors rendering predictions of emergence highly speculative. The recent outbreaks in Africa and Brazil clearly remind us of the significant impact YF emergence events pose on human and animal health. The magnitude of the Brazilian outbreak and spillover in densely populated areas outside the recommended vaccination coverage areas raised the specter of human — to — human transmission and re-establishment of enzootic cycles outside the Amazon basin. Herein, we review the factors that influence the re-emergence potential of YFV in the neotropics and offer insights for a constellation of coordinated approaches to better predict and control future YF emergence events.

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Section: Predictive Modeling For Yfv Ecologymentioning

confidence: 99%

Re-emergence of yellow fever in the neotropics — quo vadis?

Sacchetto

Drumond

Han

et al. 2020

Emerging Topics in Life Sciences

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“…Climatic variables such as temperature and rainfall have been shown to be significantly correlated with the global distribution of YFV [ 51 , 54 ], and previous studies have highlighted the role of seasonality in climatic factors in driving outbreaks [ 55 ]. Specifically, the interaction between temperature suitability and rainfall has been shown to account for much of the variability of YFV transmission across Africa [ 51 ].…”

Section: Vector-borne Diseasesmentioning

confidence: 99%

“…The existence of a sylvatic cycle for YFV complicates the picture as climate change is likely to alter the interactions of mosquito species with non-human primates, and could lead to the evolution of new serotypes thereby compromising vaccination programs [ 56 ]. The risk of yellow fever spillover from non-human primates has been shown to be associated with rainfall-driven seasonality in the vector populations and temperature-driven seasonality in vector survival and infectiousness [ 55 ]. The complex interactions between global changes such as climate change, demographic change, and land-use change are likely to have an impact on YFV evolution and the burden of yellow fever globally.…”

Section: Vector-borne Diseasesmentioning

confidence: 99%

The Impact of Climate Change on Vaccine-Preventable Diseases: Insights From Current Research and New Directions

Mahmud

Martinez

et al. 2020

Curr Envir Health Rpt

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Purpose of Review Vaccine-preventable diseases remain a major public health concern globally. Climate is a key driver of the dynamics of many infectious diseases, including those that are vaccine preventable. Understanding the impact of climate change on vaccine-preventable diseases is, thus, an important public health research priority. Here, we summarize the recent literature and highlight promising directions for future research. Recent Findings Vaccine-preventable enteric diseases, such as cholera, exhibit sensitivity to precipitation and flooding events. The predicted increase in extreme weather events as a result of climate change could exacerbate outbreaks of these pathogens. For airborne pathogens, temperature and specific humidity have been shown to be the most important environmental drivers, although the impact of climate change on disease burden and dynamics remains unclear. Finally, the transmission dynamics of vector-borne diseases are dependent on both temperature and precipitation, and climate change is expected to alter the burden and geographic range of these diseases. However, understanding the interacting effects of multiple factors, including socioeconomic and ecological factors, on the vector-borne disease ecosystem will be a crucial step towards forecasting disease burden under climate change. Summary Recent work has demonstrated associations between climate and transmission of vaccine-preventable diseases. Translating these findings into forecasts under various climate change scenarios will require mechanistic frameworks that account for both intrinsic and extrinsic drivers of transmission, and the non-linear effects on disease burden. Future research should also pay greater attention to uncertainty in both the climate modeling processes as well as disease outcomes in the context of vaccine-preventable diseases.

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“…Models that integrate such drivers can be highly predictive of spillover. For example, an ecologically driven model of yellow fever virus spillover that integrated various spatio-temporal data streams had the strongest predictive accuracy (AUC ¼ 0.79) when considering cyclical infection dynamics in wild primate reservoir hosts; critically, models considering the ecology of mosquito vectors and wild primate reservoirs were more predictive than those that also included human population size and immunity [34].…”

Section: Spatio-temporal Scales Of Spillover Predictionmentioning

confidence: 99%

The problem of scale in the prediction and management of pathogen spillover

Becker

Washburne

Faust

et al. 2019

Phil. Trans. R. Soc. B

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Disease emergence events, epidemics and pandemics all underscore the need to predict zoonotic pathogen spillover. Because cross-species transmission is inherently hierarchical, involving processes that occur at varying levels of biological organization, such predictive efforts can be complicated by the many scales and vastness of data potentially required for forecasting. A wide range of approaches are currently used to forecast spillover risk (e.g. macroecology, pathogen discovery, surveillance of human populations, among others), each of which is bound within particular phylogenetic, spatial and temporal scales of prediction. Here, we contextualize these diverse approaches within their forecasting goals and resulting scales of prediction to illustrate critical areas of conceptual and pragmatic overlap. Specifically, we focus on an ecological perspective to envision a research pipeline that connects these different scales of data and predictions from the aims of discovery to intervention. Pathogen discovery and predictions focused at the phylogenetic scale can first provide coarse and pattern-based guidance for which reservoirs, vectors and pathogens are likely to be involved in spillover, thereby narrowing surveillance targets and where such efforts should be conducted. Next, these predictions can be followed with ecologically driven spatio-temporal studies of reservoirs and vectors to quantify spatio-temporal fluctuations in infection and to mechanistically understand how pathogens circulate and are transmitted to humans. This approach can also help identify general regions and periods for which spillover is most likely. We illustrate this point by highlighting several case studies where long-term, ecologically focused studies (e.g. Lyme disease in the northeast USA, Hendra virus in eastern Australia, Plasmodium knowlesi in Southeast Asia) have facilitated predicting spillover in space and time and facilitated the design of possible intervention strategies. Such studies can in turn help narrow human surveillance efforts and help refine and improve future large-scale, phylogenetic predictions. We conclude by discussing how greater integration and exchange between data and predictions generated across these varying scales could ultimately help generate more actionable forecasts and interventions. This article is part of the theme issue ‘Dynamic and integrative approaches to understanding pathogen spillover’.

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Mosquito and primate ecology predict human risk of yellow fever virus spillover in Brazil

Cited by 49 publications

References 112 publications

Re-emergence of yellow fever in the neotropics — quo vadis?

Re-emergence of yellow fever in the neotropics — quo vadis?

The Impact of Climate Change on Vaccine-Preventable Diseases: Insights From Current Research and New Directions

The problem of scale in the prediction and management of pathogen spillover

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