We predicted that people with compassionate goals to support others and not harm them practiced more COVID-19 health behaviors during the SARS-CoV-2 pandemic to protect both themselves and others from infection. Three studies (N = 1,143 American adults) supported these predictions and ruled out several alternative explanations. Compassionate goals unrelated to the health context predicted COVID-19 health behaviors better than the general motivation to be healthy (Studies 2 and 3). In contrast, general health motivation predicted general health behaviors better than did compassionate goals. Compassionate goals and political ideology each explained unique variance in COVID-19 health behaviors (Studies 1–3). Compassionate goals predict unique variance in COVID-19 health behaviors beyond empathic concern, communal orientation, and relational self-construal (Study 3), supporting the unique contribution of compassionate goals to understanding health behaviors. Our results suggest that ecosystem motivation is an important predictor of health behaviors, particularly in the context of a highly contagious disease.
A cylindrical device was analyzed using a Laplace transform-based method. The two-dimensional model represented a pharmaceutical agent uniformly distributed in a polymeric matrix surrounded by an impermeable layer. Molecules could be transferred only through a small hole centered at the top surface of the cylinder. A closed-form solution was obtained to help study the effects of design parameters and geometries on the cumulative amount of drug released. The latter variable increased with the mass transfer and diffusion coefficients and decreased with any increment in the device's length. The delivery rate was described by an effective time constant calculated from Laplace transforms. Reducing the orifice diameter or fabricating a longer system would delay transport of the medication. Simplified expressions for the release profile and the time constant were derived for special design cases.
An analytical expression for the optimal control of an Ebola problem is obtained. The analytical solution is found as a first-order approximation to the Pontryagin Maximum Principle via the Euler-Lagrange equation. An implementation of the method is given using the computer algebra system Maple. Our analytical solutions confirm the results recently reported in the literature using numerical methods.The text is organized as follows. In Section 2 the optimal control problem is formulated. Our method is explained in Section 3 and illustrated with an example. Then, in Section 4, we apply it to the Ebola optimal control problem. We end with Section 5 of conclusions, while Appendix A provides the developed Maple code.
Leishmaniasis is a neglected tropical disease caused by the Leishmania parasite and transmitted by the Phlebotominae subfamily of sandflies, which infects humans and other mammals. Clinical manifestations of the disease include cutaneous leishmaniasis (CL), mucocutaneous leishmaniasis (MCL) and visceral leishmaniasis (VL) with a majority (more than three-quarters) of worldwide cases being CL. There are a number of risk factors for CL, such as the presence of multiple reservoirs, the movement of individuals, inequality, and social determinants of health. However, studies related to the role of these factors in the dynamics of CL have been limited. In this work, we (i) develop and analyze a vector-borne epidemic model to study the dynamics of CL in two ecologically distinct CL-affected regions—Madrid, Spain and Tolima, Colombia; (ii) derived three different methods for the estimation of model parameters by reducing the dimension of the systems; (iii) estimated reproduction numbers for the 2010 outbreak in Madrid and the 2016 outbreak in Tolima; and (iv) compared the transmission potential of the two economically-different regions and provided different epidemiological metrics that can be derived (and used for evaluating an outbreak), once R0 is known and additional data are available. On average, Spain has reported only a few hundred CL cases annually, but in the course of the outbreak during 2009–2012, a much higher number of cases than expected were reported and that too in the single city of Madrid. Cases in humans were accompanied by sharp increase in infections among domestic dogs, the natural reservoir of CL. On the other hand, CL has reemerged in Colombia primarily during the last decade, because of the frequent movement of military personnel to domestic regions from forested areas, where they have increased exposure to vectors. In 2016, Tolima saw an unexpectedly high number of cases leading to two successive outbreaks. On comparing, we estimated reproduction number of the Madrid outbreak to be 3.1 (with range of 2.8–3.9), which was much higher than reproduction number estimates of the Tolima first outbreak 1.2 (with range of 1.1–1.3), and the estimate for the second outbreak in Tolima of 1.019 (with range of 1.018–1.021). This suggests that the epidemic outbreak in Madrid was much more severe than the Tolima outbreak, even though Madrid was economically better-off compared to Tolima. It indicates a potential relationship between urban development and increasing health disparities.
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