Dataset Information

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

ABSTRACT: Many (re)emerging infectious diseases in humans arise from pathogen spillover from wildlife or livestock, and accurately predicting pathogen spillover is an important public health goal. In the Americas, yellow fever in humans primarily occurs following spillover from non-human primates via mosquitoes. Predicting yellow fever spillover can improve public health responses through vector control and mass vaccination. Here, we develop and test a mechanistic model of pathogen spillover to predict human risk for yellow fever in Brazil. This environmental risk model, based on the ecology of mosquito vectors and non-human primate hosts, distinguished municipality-months with yellow fever spillover from 2001 to 2016 with high accuracy (AUC = 0.72). Incorporating hypothesized cyclical dynamics of infected primates improved accuracy (AUC = 0.79). Using boosted regression trees to identify gaps in the mechanistic model, we found that important predictors include current and one-month lagged environmental risk, vaccine coverage, population density, temperature and precipitation. More broadly, we show that for a widespread human viral pathogen, the ecological interactions between environment, vectors, reservoir hosts and humans can predict spillover with surprising accuracy, suggesting the potential to improve preventive action to reduce yellow fever spillover and avert onward epidemics in humans. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.

SUBMITTER: Childs ML

PROVIDER: S-EPMC6711306 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Childs Marissa L ML Nova Nicole N Colvin Justine J Mordecai Erin A EA

Philosophical transactions of the Royal Society of London. Series B, Biological sciences 20190812 1782

Many (re)emerging infectious diseases in humans arise from pathogen spillover from wildlife or livestock, and accurately predicting pathogen spillover is an important public health goal. In the Americas, yellow fever in humans primarily occurs following spillover from non-human primates via mosquitoes. Predicting yellow fever spillover can improve public health responses through vector control and mass vaccination. Here, we develop and test a mechanistic model of pathogen spillover to predict hu ...[more]

PMID: 31401964

Similar Datasets

Project description:BackgroundYellow fever virus is a mosquito-borne flavivirus that persists in an enzoonotic cycle in non-human primates (NHPs) in Brazil, causing disease in humans through spillover events. Yellow fever (YF) re-emerged in the early 2000s, spreading from the Amazon River basin towards the previously considered low-risk, southeastern region of the country. Previous methods mapping YF spillover risk do not incorporate the temporal dynamics and ecological context of the disease, and are therefore unable to predict seasonality in spatial risk across Brazil. We present the results of a bagged logistic regression predicting the propensity for YF spillover per municipality (administrative sub-district) in Brazil from environmental and demographic covariates aggregated by month. Ecological context was incorporated by creating National and Regional models of spillover dynamics, where the Regional model consisted of two separate models determined by the regions' NHP reservoir species richness (high vs low).ResultsOf the 5560 municipalities, 82 reported YF cases from 2001 to 2013. Model accuracy was high for the National and low reservoir richness (LRR) models (AUC = 0.80), while the high reservoir richness (HRR) model accuracy was lower (AUC = 0.63). The National model predicted consistently high spillover risk in the Amazon, while the Regional model predicted strong seasonality in spillover risk. Within the Regional model, seasonality of spillover risk in the HRR region was asynchronous to the LRR region. However, the observed seasonality of spillover risk in the LRR Regional model mirrored the national model predictions.ConclusionsThe predicted risk of YF spillover varies with space and time. Seasonal trends differ between regions indicating, at times, spillover risk can be higher in the urban coastal regions than the Amazon River basin which is counterintuitive based on current YF risk maps. Understanding the spatio-temporal patterns of YF spillover risk could better inform allocation of public health services.

Project description:The recent reemergence of yellow fever virus (YFV) in Brazil has raised serious concerns due to the rapid dissemination of the virus in the southeastern region. To better understand YFV genetic diversity and dynamics during the recent outbreak in southeastern Brazil, we generated 18 complete and nearly complete genomes from the peak of the epidemic curve from nonhuman primates (NHPs) and human infected cases across the Espírito Santo and Rio de Janeiro states. Genomic sequencing of 18 YFV genomes revealed the estimated timing, source, and likely routes of yellow fever virus transmission and dispersion during one of the largest outbreaks ever registered in Brazil. We showed that during the recent epidemic, YFV was reintroduced from Minas Gerais to the Espírito Santo and Rio de Janeiro states multiple times between 2016 and 2019. The analysis of data from portable sequencing could identify the corridor of spread of YFV. These findings reinforce the idea that continued genomic surveillance strategies can provide information on virus genetic diversity and transmission dynamics that might assist in understanding arbovirus epidemics.IMPORTANCE Arbovirus infections in Brazil, including yellow fever, dengue, zika, and chikungunya, result in considerable morbidity and mortality and are pressing public health concerns. However, our understanding of these outbreaks is hampered by the limited availability of genomic data. In this study, we investigated the genetic diversity and spatial distribution of YFV during the current outbreak by analyzing genomic data from areas in southeastern Brazil not covered by other previous studies. To gain insights into the routes of YFV introduction and dispersion, we tracked the virus by sequencing YFV genomes sampled from nonhuman primates and infected patients from the southeastern region. Our study provides an understanding of how YFV initiates transmission in new Brazilian regions and illustrates that genomics in the field can augment traditional approaches to infectious disease surveillance and control.

Project description:BACKGROUND: Aedes aegypti Linnaeus is a peridomestic mosquito that lays desiccation-resistant eggs in water-filled human-made containers. Previous investigations connected egg hatching with declining dissolved oxygen (DO) that is associated with bacterial growth. However, past studies failed to uncouple DO from other potential stimulatory factors and they contained little quantitative information about the microbial community; consequently, a direct role for bacteria or compounds associated with bacteria in stimulating egg hatching cannot be dismissed. METHODOLOGY/PRINCIPAL FINDINGS: Environmental factors stimulating hatch of Ae. aegypti eggs were investigated using non-sterile and sterile white oak leaf (WOL) infusions and a bacterial culture composed of a mix of 14 species originally isolated from bamboo leaf infusion. In WOL infusion with active microbes, 92.4% of eggs hatched in 2-h at an average DO concentration of 2.4 ppm. A 24-h old bacterial culture with a DO concentration of 0.73 ppm also stimulated 95.2% of eggs hatch within 1-h. In contrast, only 4.0% of eggs hatched in sterile infusion, whose DO averaged 7.4 ppm. Effects of bacteria were uncoupled from DO by exposing eggs to bacterial cells suspended in NaCl solution. Over a 4-h exposure period, 93.8% of eggs hatched while DO concentration changed minimally from 7.62 to 7.50 ppm. Removal of bacteria by ultra-filtration and cell-free filtrate resulted in only 52.0% of eggs hatching after 4-h at an average DO concentration of 5.5 ppm. CONCLUSIONS/SIGNIFICANCE: Collectively, the results provide compelling evidence that bacteria or water-soluble compounds secreted by bacteria, not just low DO concentration, stimulate hatching of Ae. aegypti eggs. However, the specific cues involved remain to be identified. These research findings contribute new insight into an important aspect of the oviposition biology of Ae. aegypti, a virus vector of global importance, providing the basis for a new paradigm of environmental factors involved in egg hatching.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets