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Climate change and sugarcane expansion increase Hantavirus infection risk
Hantavirus Cardiopulmonary Syndrome (HCPS) is a disease caused by Hantavirus, which is highly virulent for humans. High temperatures and conversion of native vegetation to agriculture, particularly sugarcane cultivation can alter abundance of rodent generalist species that serve as the principal reservoir host for HCPS, but our understanding of the compound effects of land use and climate on HCPS incidence remains limited, particularly in tropical regions. Here we rely on a Bayesian model to fill this research gap and to predict the effects of sugarcane expansion and expected changes in temperature on Hantavirus infection risk in the state of São Paulo, Brazil. The sugarcane expansion scenario was based on historical data between 2000 and 2010 combined with an agro-environment zoning guideline for the sugar and ethanol industry. Future evolution of temperature anomalies was derived using 32 general circulation models from scenarios RCP4.5 and RCP8.5 (Representative greenhouse gases Concentration Pathways adopted by IPCC). Currently, the state of São Paulo has an average Hantavirus risk of 1.3%, with 6% of the 645 municipalities of the state being classified as high risk (HCPS risk ≥ 5%). Our results indicate that sugarcane expansion alone will increase average HCPS risk to 1.5%, placing 20% more people at HCPS risk. Temperature anomalies alone increase HCPS risk even more (1.6% for RCP4.5 and 1.7%, for RCP8.5), and place 31% and 34% more people at risk. Combined sugarcane and temperature increases led to the same predictions as scenarios that only included temperature. Our results demonstrate that climate change effects are likely to be more severe than those from sugarcane expansion. Forecasting disease is critical for the timely and efficient planning of operational control programs that can address the expected effects of sugarcane expansion and climate change on HCPS infection risk. The predicted spatial location of HCPS infection risks obtained here can be used to prioritize management actions and develop educational campaigns
NOTES ON AN ARTIFICIAL ROOST OF Myotis albescens (CHIROPTERA, VESPERTILIONIDAE) IN SOUTHEASTERN BRAZIL
Myotis albescens has a wide distribution, occurring from southern Mexico to central Argentina and Uruguay, where it is usually caught near streams or flooded areas. M. albescens roosts during the day in cavities such as hollow logs, rock cavities, and buildings. Here, we describe a group of M. albescens roosting in a highway underpass in an Atlantic Forest area in Rancharia, southeastern Brazil. The group was found inside a culvert with a shallow stream passing through it. The animals left the roost and were mist-netted in the first hours of the night. The M. albescens group was composed of 18 individuals, eleven males and seven females. In October, all males had descended testes and two females were pregnant, as confirmed by abdominal palpation. Morphological characters of the specimens fell in the known variation for the species. Our data show that highway underpasses can be important day roosts for bats, especially if riparian areas are preserve
Use of a portable thermograph as a potential tool to identify nocturnal airport bird risks / Uso de um termógrafo portátil como uma ferramenta potencial para identificar riscos noturnos de aves em aeroportos
Worldwide, wildlife-aircraft collisions constitute a major human health and safety concern. About 98% of wildlife-aircraft strikes involve bird species (i.e., bird strikes) resulting in an annual loss of 20.000,00 costs
SING DIFFERENT PROXIES TO PREDICT HANTAVIRUS DISEASE RISK IN SÃO PAULO STATE, BRAZIL
Recent studies predict disease risk using different proxies, such as pathogen prevalence in hosts, abundance of the main hosts, and the number of reported disease cases. These proxies are used to build risk maps that can aid the prevention of new disease outbreaks. To date, these proxies have not been widely tested for differences in their predictions and effectiveness, which could have serious implications for disease control measures. In this study, we compared two different proxies inferring hantavirus disease risk in the state of São Paulo. We compared risk level distribution to the accuracy of risk maps using (a) Rodent Reservoir Abundance data (RRA) sampled in 2002--2008 and (b) Hantavirus Pulmonary Syndrome cases reported (RC) in 1993--2012. RRA data were collected within forest fragments and in the matrix of six landscapes, and were extrapolated for São Paulo State through regression models using the amount of forest cover and the collection context as predictors. Using Bayesian models, we created a HPS risk map using annual HPS incidence, climate, landscape structure metrics and social factors. We validated RRA and RC risk maps with actual reported HPS cases (2013--2015). These data were categorized according to risk levels and compared using histograms and correlations. The two risk maps (RRA and RC) had a low Pearson correlation (0,038) and a low covariance (0,016), indicating high uncertainty in the predictions between these two proxies. The RRA map predicted that 68% of the municipalities in the state are in the medium to high risk categories, while the RC map predicted only 6%. This indicates that the RRA risk map might be overestimating high risk areas. The RRA map also had a higher sensitivity than the RC map to newly reported cases, correctly identifying 82% of the cases in medium to high risk areas. On the other hand, the RC map had a higher specificity (91%), leading to better prediction of the low risk areas (31% for RRA map). Our results draw attention to the fact that different proxies can give different results and predict different risk levels and should be used carefully in disease studies.Recent studies predict disease risk using different proxies, such as pathogen prevalence in hosts, abundance of the main hosts, and the number of reported disease cases. These proxies are used to build risk maps that can aid the prevention of new disease outbreaks. To date, these proxies have not been widely tested for differences in their predictions and effectiveness, which could have serious implications for disease control measures. In this study, we compared two different proxies inferring hantavirus disease risk in the state of São Paulo. We compared risk level distribution to the accuracy of risk maps using (a) Rodent Reservoir Abundance data (RRA) sampled in 2002--2008 and (b) Hantavirus Pulmonary Syndrome cases reported (RC) in 1993--2012. RRA data were collected within forest fragments and in the matrix of six landscapes, and were extrapolated for São Paulo State through regression models using the amount of forest cover and the collection context as predictors. Using Bayesian models, we created a HPS risk map using annual HPS incidence, climate, landscape structure metrics and social factors. We validated RRA and RC risk maps with actual reported HPS cases (2013--2015). These data were categorized according to risk levels and compared using histograms and correlations. The two risk maps (RRA and RC) had a low Pearson correlation (0,038) and a low covariance (0,016), indicating high uncertainty in the predictions between these two proxies. The RRA map predicted that 68% of the municipalities in the state are in the medium to high risk categories, while the RC map predicted only 6%. This indicates that the RRA risk map might be overestimating high risk areas. The RRA map also had a higher sensitivity than the RC map to newly reported cases, correctly identifying 82% of the cases in medium to high risk areas. On the other hand, the RC map had a higher specificity (91%), leading to better prediction of the low risk areas (31% for RRA map). Our results draw attention to the fact that different proxies can give different results and predict different risk levels and should be used carefully in disease studies
Novos registros do lagarto-listrado Kentropyx paulensis para São Paulo, Brasil
The endemic Cerrado teiid lizard Kentropyx paulensis is classified in the “Endangered” and “Vulnerable” categories by the lists of the states of São Paulo and Minas Gerais, respectively, and is therefore considered threatened. Thus, this work aimed to compile records of K. paulensis obtained in several works carried out in the Planalto Ocidental Paulista, which occupies almost half of the total area of the State of São Paulo, Southeastern Brazil. Records were produced in seven municipalities (Anhembi, Assis, Castilho, Jaú, Piracicaba, Quatá and Santa Bárbara d'Oeste) in the hot and rainy season (December to March) in vegetation types ranging from natural environments such as Cerradão and Semideciduous Seasonal Forest to anthropized environments as reforestation and pastures of Urochloa sp. The intense process of changing the landscape that the Planalto Ocidental Paulista went through in the last century, because of the economic model that the state adopted, may have collaborated to reduce the viable areas for the maintenance of these populations. These new records indicate that the occurrence of the species may be broader, as a result of adaptations to recent conversion of cover natural that occurred in the State of São Paulo.O lagarto teídeo endêmico do Cerrado Kentropyx paulensis está classificado nas categorias “Em Perigo” e “Vulnerável” pelas listas do estado de São Paulo e Minas Gerais, respectivamente, sendo, portanto, considerado ameaçado. Com isso, esse trabalho objetivou compilar registros de K. paulensis obtidos em diversos trabalhos realizados no Planalto Ocidental Paulista, que ocupa praticamente metade da área total do Estado de São Paulo, sudeste do Brasil. Foram registradas ocorrências em sete municípios (Anhembi, Assis, Castilho, Jaú, Piracicaba, Quatá e Santa Bárbara d’Oeste) no período quente e chuvoso (dezembro a março) em fitofisionomias que vão desde ambientes naturais como Cerradão e Floresta Estacional Semidecidual até ambientes antropizados como reflorestamentos e pastagens de Urochloa sp. O intenso processo de alteração da paisagem que o Planalto Ocidental Paulista passou no século passado, fruto do modelo econômico que o estado adotou, pode ter colaborado para a diminuição de áreas viáveis para a manutenção dessas populações. Estes novos registros indicam que a ocorrência da espécie pode ser mais ampla, fruto de adaptações às recentes conversões de solo e ambientes naturais ocorridos no Estado de São Paulo. 
Spatiotemporal Dynamics of Hantavirus Cardiopulmonary Syndrome Transmission Risk in Brazil
Background: Hantavirus disease in humans is rare but frequently lethal in the Neotropics. Several abundant and widely distributed Sigmodontinae rodents are the primary hosts of Orthohantavirus and, in combination with other factors, these rodents can shape hantavirus disease. Here, we assessed the influence of host diversity, climate, social vulnerability and land use change on the risk of hantavirus disease in Brazil over 24 years. Methods: Landscape variables (native forest, forestry, sugarcane, maize and pasture), climate (temperature and precipitation), and host biodiversity (derived through niche models) were used in spatiotemporal models, using the 5570 Brazilian municipalities as units of analysis. Results: Amounts of native forest and sugarcane, combined with temperature, were the most important factors influencing the increase of disease risk. Population at risk (rural workers) and rodent host diversity also had a positive effect on disease risk. Conclusions: Land use change—especially the conversion of native areas to sugarcane fields—can have a significant impact on hantavirus disease risk, likely by promoting the interaction between the people and the infected rodents. Our results demonstrate the importance of understanding the interactions between landscape change, rodent diversity, and hantavirus disease incidence, and suggest that land use policy should consider disease risk. Meanwhile, our risk map can be used to help allocate preventive measures to avoid disease.publishedVersio
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