RESUMEN
Leptospirosis, the infectious disease caused by a spirochete bacteria, is a major public health problem worldwide. In Argentina, some regions have climatic and geographical characteristics that favor the habitat of bacteria of the Leptospira genus, whose survival strongly depends on climatic factors, enhanced by climate change, which increase the problems associated with people's health. In order to have a method to predict leptospirosis cases, in this paper, five time series forecasting methods are compared: two parametric (autoregressive integrated moving average and an alternative one that allows covariates, ARIMA and ARIMAX, respectively), two nonparametric (Nadaraya-Watson Kernel estimator, one and two kernels versions, NW-1 K and NW-2 K), and one semiparametric (semi-functional partial linear regression, SFPLR) method. For this, the number of cases of leptospirosis registered from 2009 to 2020 in three important cities of northeastern Argentina is used, as well as hydroclimatic covariates related to the presence of cases. According to the obtained results, there is no method that improves considerably the rest and can be recommended as a unique tool for leptospirosis prediction. However, in general, the NW-2 K method gets a better performance. This work, in addition to using a long-term high-quality time series, enriches the area of applications of statistical models to epidemiological leptospirosis data by the incorporation of hydroclimatic variables, and it is recommended directing further efforts in this line of research, under the context of current climate change.
Asunto(s)
Leptospirosis , Humanos , Incidencia , Estaciones del Año , Leptospirosis/epidemiología , Leptospirosis/microbiología , Modelos Estadísticos , Brotes de EnfermedadesRESUMEN
We synthesized NaOH-activated hydrochars via hydrothermal carbonization (HTC) of Brazilian pine fruit shells at HTC residence times of 24, 48, and 72 h. The hydrochars were used as adsorbents to remove bisphenol A (BPA) from aqueous solutions. The surface area of the samples can reach up to 2220 m2 g-1, and the maximum adsorption of BPA onto the surfaces was achieved at a pH of 7.0 (708 mg g-1). Adsorption occurred mainly via monolayer formation with a low retention time of the adsorbate (τ) on the surfaces, indicating that the BPA molecules reached the already occupied active sites and returned after undergoing heat exchange (τ > 0). Adsorption is an endothermic spontaneous process that results in a balance between entropic and enthalpic contributions. In such a reaction, ΔG°< 0, even with ΔH°> 0, the process occurs with an important increase in the entropy. The desorption was more efficient with ethanol and methanol than with HCl, NaOH, and NaCl owing to the dipole-dipole forces between the adsorbate and the alcohols. Additionally, the low desorption efficiency using acid, base, and salts can be attributed to competitive effects between the desorption agents and the active sites of the adsorbents.