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Literature detail

Seasonality of agricultural exposure as an important predictor of seasonal yellow fever spillover in Brazil.

Arran Hamlet1,2 Daniel Garkauskas Ramos3 Katy A M Gaythorpe1,4 Alessandro Pecego Martins Romano3 Tini Garske1,4 Neil M Ferguson1,4
Affiliations 4 institutions
  1. MRC Centre for Global Infectious Disease Analysis
  2. and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London, London, UK. [email protected].
  3. Secretariat for Health Surveillance, Brazilian Ministry of Health, Brasilia, Brazil.
  4. and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London, London, UK.
PMID 34131128 2021 Nat Commun eng epublish
PubMed DOI Browse context

Article

Publication summary

Yellow fever virus (YFV) is a zoonotic arbovirus affecting both humans and non-human primates (NHP's) in Africa and South America. Previous descriptions of YF's seasonality have relied purely on climatic explanations, despite the high proportion of cases occurring in people involved in agriculture. We use a series of random forest classification models to predict the monthly occurrence of YF in humans and NHP's across Brazil, by fitting four classes of covariates related to the seasonality of climate and agriculture (planting and harvesting), crop output and host demography. We find that models captured seasonal YF reporting in humans and NHPs when they considered seasonality of agriculture rather than climate, particularly for monthly aggregated reports. These findings illustrate the seasonality of exposure, through agriculture, as a component of zoonotic spillover. Additionally, by highlighting crop types and anthropogenic seasonality, these results could directly identify areas at highest risk of zoonotic spillover.

Agriculture Disease Outbreaks Seasons Animals Brazil Climate Forests Humans Primates Yellow Fever Yellow fever virus Zoonoses

Structured evidence records

Evidence records

4 total
Reservoir Ecology 2 records
Reservoir Ecology Extraction confidence 0.95
Key finding

Seasonality of agricultural activity predicts monthly yellow fever virus occurrence in humans and non-human primates in Brazil, highlighting agricultural exposure as an ecological driver of spillover.

Virus
YFV
Location
Brazil Brazil
Supporting text

We use a series of random forest classification models to predict the monthly occurrence of YF in humans and NHP's across Brazil... We find that models captured seasonal YF reporting in humans and NHPs when they considered seasonality of agriculture rather than climate.

Method
random forest classification models
Geographic raw
Brazil
Country inferred
Brazil
Reservoir Ecology Extraction confidence 0.95
Key finding

Seasonality of agricultural activity predicts monthly yellow fever virus occurrence in non-human primates in Brazil, implicating agricultural exposure as a driver of viral maintenance at the human–wildlife interface.

Virus
YFV
Host
Primates
Location
Brazil Brazil
Supporting text

We use a series of random forest classification models to predict the monthly occurrence of YF in humans and NHP's across Brazil... We find that models captured seasonal YF reporting in humans and NHPs when they considered seasonality of agriculture rather than climate.

Method
random forest classification models
Geographic raw
Brazil
Country inferred
Brazil
Spillover Event 1 records
Spillover Event Extraction confidence 0.95
Key finding

Yellow fever virus spillover from non-human primates to humans in Brazil is seasonal and related to agricultural exposure.

Virus
YFV
Location
Brazil Brazil
Supporting text

Yellow fever virus (YFV) is a zoonotic arbovirus affecting both humans and non-human primates (NHP's) in Africa and South America. We use a series of random forest classification models to predict the monthly occurrence of YF in humans and NHP's across Brazil. These findings illustrate the seasonality of exposure, through agriculture, as a component of zoonotic spillover.

Method
random forest classification models
Study design
modeling study
Transmission direction
animal-to-human
Geographic raw
Brazil
Country inferred
Brazil
Zoonotic Surveillance 1 records
Zoonotic Surveillance Extraction confidence 0.80
Key finding

Yellow fever virus occurrence in humans and non-human primates was monitored across Brazil using predictive modeling based on agricultural seasonality, identifying patterns relevant to zoonotic spillover surveillance.

Virus
YFV
Host
Primates
Location
Brazil Brazil
Supporting text

We use a series of random forest classification models to predict the monthly occurrence of YF in humans and NHP's across Brazil, by fitting four classes of covariates related to the seasonality of climate and agriculture (planting and harvesting), crop output and host demography.

Method
modeling; random forest classification
Geographic raw
Brazil
Country inferred
Brazil