Fig 1.
Circulation of yellow fever virus in Minas Gerais, 2016 to 2021.
A: Map of Minas Gerais showing the location of Curvelo, where yellow fever virus was detected in a Callithrix sp specimen, in 2020 (purple), municipalities that had cases of yellow fever affecting human and or non-human primate, 2016–2018 (green), and municipalities that had yellow fever epizootics confirmed from Jul 2020 to Jun 2022 (grey). The inset map displays the location of Minas Gerais in Southern Brazil. B: Phylogenetic tree reconstructed with using partial envelope sequence of yellow fever virus (1000nt). The sequence of yellow fever virus detected in a Callithrix sp specimen (NHP1041), in 2020, from Curvelo is shown in purple. Some branches were collapsed for clarity. The phylogenetic tree was reconstructed using the maximum likelihood method, nucleotide substitution model TN93 +I, with 1000 bootstrap replicates, using PhyML. The final tree was edited and visualized using iTOL. The map was generated using shapefiles “MG_Municipios_2020.shp” and “BR_UF_2020.shp” (https://www.ibge.gov.br/geociencias/organizacao-do-territorio/malhas-territoriais/15774-malhas.html?=&t=acesso-ao-produto) and QGIS, a free open source (GNU General Public License) system developed by Open Source Geospatial Foundation (https://www.qgis.org/pt_BR/site/forusers/download.html).
Table 1.
Non-human primate carcasses collected from 2019 to 2021 in Minas Gerais and screened for yellow fever virus.
Table 2.
Effect estimates and P values for each of the terms in our generalized additive mixed models.
Table 3.
R values (correlations between predicted and observed values as a proportion of the model’s overall fit) for each of the fitted terms in our GAMMs.
Fig 2.
The temporal progression of (from top to bottom): (A) total epizootic cases, taken from the Brazilian Ministry of Health’s official yellow fever surveillance program; (B) predicted YFV infection in sampled primates (points indicating positive and negative samples); (C) intensity of YFV in infected primate samples and labeled in Panel B; and (D) total of human cases taken from Brazilian Ministry of Health’s official yellow fever surveillance program. Date is presented in “days after the start of 2017,” with the start of each year signposted by grey dotted lines. The fitted line is the mean fit taken from our GAMMs, using an adaptive smooth; the shaded area represents the 95% confidence intervals. YFV intensity was scaled to have a mean of 0 and a standard deviation of 1. Note: the upturn to the right of the intensity curve (Panel C) is likely an artifact of the single high-intensity point that was the final collected sample, and should be disregarded.
Fig 3.
The geographic distribution of non-human primate carcasses.
(A); predicted YFV infection (B); and predicted mean YFV intensity (C). Panels B and C were taken from our GAMMs; darker colors represent greater predicted infection and intensity. The dark black line represents the coastline of Brazil. In panels B and C peripheral areas with very low or very high predicted intensity have been removed for plotting clarity (dark grey areas), due to a tendency for extreme estimates when extrapolating outside the limits of the data. Maps were created in R using the package rnaturalearth (https://www.rdocumentation.org/packages/rnaturalearth/versions/0.3.2), and the open source/public domain Natural Earth (https://www.naturalearthdata.com/).
Fig 4.
Fixed effect estimates taken from our GAMMs, for YFV infection (red) and intensity (blue), accounting for the nonlinear spatiotemporal variation seen in Figs 2 and 3.
Dots represent the mean estimated effects; error bars are the 95% credibility intervals. Significant effects (p<0.05) are marked with an asterisk (*). “Rural”, “Carcass: Bad”, and “Taxon: Alouatta” were all the base levels for their factor; we display them as zero to allow comparison between these factor levels and the other factor levels in the effect.