RESUMO
During the last quarter of 2019, the beaches, mangroves, and estuaries of Northeast Brazil received an unprecedented volume of crude oil from the sea, which became the worst environmental disaster ever to reach the Brazilian coast. The oil, having reached the shores completely unnoticed, left both society and government agents completely clueless on (i) where the oil was coming from; (ii) how much oil was still in the ocean to reach the shorelines; and (iii) which beaches were going to be affected next! By exploring remote sensing data and ocean numerical modeling, along with oil dispersion chemistry on sea water, this study investigates the possible origin and path of the spill and whether it could have been detected from space. The oil dispersion modeling simulations performed for this investigation revealed a possible region and timing of the oil spill, also indicating the likelihood of it being advected toward the shoreline under the ocean surface.
Assuntos
Poluição por Petróleo , Petróleo , Poluentes Químicos da Água , Brasil , Monitoramento Ambiental , Poluentes Químicos da Água/análiseRESUMO
Hepatitis-A virus is a worldwide healthcare problem, mainly affecting countries with poor sanitary and socioeconomic conditions. This communication evaluates the spatiotemporal variability of the disease's socioepidemiological profile in one of the endemic Brazilian regions (Pará State) prior to (2008-2013) and after (2014-2017) the launch of the national public vaccination programme. Hepatitis-A epidemiological reports concerning Pará State - Brazil - were used for this study including municipalitylevel data of the disease's reported positive notification cases (PNCs). The analyses involved socioepidemiological profiling and space-time scan statistics. A total of 5500 PNCs were reported in the study period. On average, PNCs decreased over time throughout the state, with strongest drops after 2015. The PNCs were specific for gender, race/ethnic origin and age group. The predominant gender and race/ethnic groups was male and brown, respectively. While children were the most susceptible age group prior to 2015, there was a shift towards older ages (young and adults) in later years. Those found to be the most affected by the disease, as shown by space-time scan statistics, were people in densely populated municipalities with unsatisfactory sanitary conditions and also less well covered by the public vaccination programme. Despite drops in the number of hepatitis-A PNCs, thanks to the national vaccination programme, the disease still persists in Pará State and elsewhere in Brazil. The present study reinforces the need of continuous prevention and control strategies for effective control and erradication of hepatitis-A.
Assuntos
Instalações de Saúde , Hepatite , Adulto , Idoso , Brasil/epidemiologia , Criança , Suscetibilidade a Doenças , Humanos , Masculino , Pessoa de Meia-IdadeRESUMO
Hepatitis-A is a waterborne infectious disease transmitted by the eponymous hepatitis-A virus (HAV). Due to the disease's sociodemographic and environmental characteristics, this study applied public census and remote sensing data to assess risk factors for hepatitis-A transmission. Municipality-level data were obtained for the state of Pará, Brazil. Generalized linear and nonlinear models were evaluated as alternative predictors for hepatitis-A transmission in Pará. The Histogram Gradient Boost (HGB) regression model was deemed the best choice ( R M S E = 2.36, and higher R 2 = 0.95) among the tested models. Partial dependence analysis and permutation feature importance analysis were used to investigate the partial dependence and the relative importance values of the independent variables in the disease transmission prediction model. Results indicated a complex relationship between the disease transmission and the sociodemographic and environmental characteristics of the study area. Population size, lack of sanitation, urban clustering, year of notification, insufficient public vaccination programs, household proximity to open-air dumpsites and storm-drains, and lack of access to healthcare facilities and hospitals were sociodemographic parameters related to HAV transmission. Turbidity and precipitation were the environmental parameters closest related to disease transmission. Based on HGB model, a hepatitis-A risk map was built for Pará state. The obtained risk map can be thought of as an auxiliary tool for public health strategies. This study reinforces the need to incorporate remote sensing data in epidemiological modelling and surveillance plans for the development of early prevention strategies for hepatitis-A.
RESUMO
Human activity and natural climate trends constitute a major threat to coral reefs worldwide. Models predict a significant reduction in reef spatial extension together with a decline in biodiversity in the relatively near future. In this context, monitoring programs to detect changes in reef ecosystems are essential. In recent years, coral reef mapping using remote sensing data has benefited from instruments with better resolution and computational advances in storage and processing capabilities. However, the water column represents an additional complexity when extracting information from submerged substrates by remote sensing that demands a correction of its effect. In this article, the basic concepts of bottom substrate remote sensing and water column interference are presented. A compendium of methodologies developed to reduce water column effects in coral ecosystems studied by remote sensing that include their salient features, advantages and drawbacks is provided. Finally, algorithms to retrieve the bottom reflectance are applied to simulated data and actual remote sensing imagery and their performance is compared. The available methods are not able to completely eliminate the water column effect, but they can minimize its influence. Choosing the best method depends on the marine environment, available input data and desired outcome or scientific application.