Neighbor danger: Yellow fever virus epizootics in urban and urban-rural transition areas of Minas Gerais state, during 2017-2018 yellow fever outbreaks in Brazil

Abstract

Background: From the end of 2016 until the beginning of 2019, Brazil faced a massive sylvatic yellow fever (YF) outbreak. The 2016-2019 YF epidemics affected densely populated areas, especially the Southeast region, causing thousands of deaths of humans and non-human primates (NHP).

Methodology/principal findings: We conducted a molecular investigation of yellow fever virus (YFV) RNA in 781 NHP carcasses collected in the urban, urban-rural interface, and rural areas of Minas Gerais state, from January 2017 to December 2018. Samples were analyzed according to the period of sampling, NHP genera, sampling areas, and sampling areas/NHP genera to compare the proportions of YFV-positive carcasses and the estimated YFV genomic loads. YFV infection was confirmed in 38.1% of NHP carcasses (including specimens of the genera Alouatta, Callicebus, Callithrix, and Sapajus), from the urban, urban-rural interface, and rural areas. YFV RNA detection was positively associated with epidemic periods (especially from December to March) and the rural environment. Higher median viral genomic loads (one million times) were estimated in carcasses collected in rural areas compared to urban ones.

Conclusions/significance: The results showed the wide occurrence of YF in Minas Gerais in epidemic and non-epidemic periods. According to the sylvatic pattern of YF, a gradient of viral dissemination from rural towards urban areas was observed. A high YF positivity was observed for NHP carcasses collected in urban areas with a widespread occurrence in 67 municipalities of Minas Gerais, including large urban centers. Although there was no documented case of urban/Aedes YFV transmission to humans in Brazil during the 2016-2019 outbreaks, YFV-infected NHP in urban areas with high infestation by Aedes aegypti poses risks for YFV urban/Aedes transmission and urbanization.

Fig 1. Yellow fever virus (YFV) investigation in non-human primate (NHP) carcasses, in Minas Gerais state, January 2017-December 2018.

(A) Geopolitical map of Brazil with biomes distribution. (B) Map of Minas Gerais state indicating municipalities from where NHP carcasses were collected and investigated for YFV RNA. Municipalities are colored as follows: in grey are 120 municipalities without detection of YFV in NHP (in this study); in light red are 110 municipalities with detection of YFV in NHP (this study and official bulletins); and in blue are 49 municipalities with detection of YFV in NHP (only in this study) where YFV circulation has not been described, during 2016–2018 outbreaks. Based on official bulletins, YFV was detected (humans or NHP) in another 31 municipalities of Minas Gerais by the State Surveillance Secretary during 2016–2018 outbreaks [13,21,22]. Abbreviations referring to Federal District and states as follows: AC: Acre; AL: Alagoas; AP: Amapá; AM: Amazonas; BA: Bahia; CE: Ceará; DF: Distrito Federal; ES: Espírito Santo; GO: Goiás; MA: Maranhão; MT: Mato Grosso; MS: Mato Grosso do Sul; MG: Minas Gerais; PA: Pará; PB: Paraíba; PR: Paraná; PE: Pernambuco; PI: Piauí; RR: Roraima; RO: Rondônia; RJ: Rio de Janeiro; RN: Rio Grande do Norte; RS: Rio Grande do Sul; SC: Santa Catarina; SP: São Paulo; SE: Sergipe; and TO: Tocantins. Numbers indicate the mesoregions of Minas Gerais as follows: 1. Triângulo Mineiro e Alto Paranaíba; 2. Northwest; 3. North; 4. Jequitinhonha; 5. Vale do Mucuri; 6. Vale do Rio Doce; 7. Zona da Mata; 8. South/Southwest; 9. West; 10. Central; 11. Metropolitan region; 12. Campo das Vertentes. Maps were created using the QGIS software version 3.8.2.

Fig 2. Association between detection of yellow fever virus (YFV) in the liver of non-human primate (NHP) carcasses with (a) NHP genera, (b) period of sampling (c) environment, and (d) environment plus NHP genera.

YFV ND: yellow fever virus RNA was not detected. YFV pos: yellow fever virus RNA was detected. Pearson residuals (standardized) were extracted from the chi-square function and plotted. In each cell, the size of the circle is proportional to the amount of cell contribution, and colors indicate positive residuals (blue) or negative residuals (red). The vertical bars indicate Pearson residuals values. Analyses were run in R software v.3.6.0.