In 2022, the US Centers for Disease Control and Prevention commissioned the National Academies of Sciences, Engineering, and Medicine to assess the role of community-level wastewater-based epidemiology (WBE) beyond COVID-19. WBE is recognized as a promising mechanism for promptly identifying infectious diseases, including COVID-19 and other novel pathogens. An important conclusion from this initiative is the critical importance of maintaining equity and expanding access to fully realize the benefits of wastewater surveillance for marginalized communities. To address this need, we propose an optimization framework that strategically allocates wastewater monitoring resources at the wastewater treatment plant (WWTP) level, ensuring more effective and equitable distribution of surveillance efforts to serve underserved populations. The purpose of the framework is to obtain a balanced spatial distribution, inclusive population coverage, and efficient representation of disadvantaged groups in the allocation of resources for WBE. Furthermore, the framework concentrates on areas with high population density and gives priority to vulnerable regions, as well as identifying signals that display significant variations from other monitored sources. The optimization objective is to maximize a weighted combination of these critical factors. This problem is formulated as an integer optimization problem and solved using simulated annealing. We evaluate various scenarios, considering different weighting factors, to optimize the allocation of WWTPs with monitoring systems. This optimization framework provides an opportunity to enhance WBE by providing customized monitoring strategies created to address specific priorities and situations, thus enhancing the decision-making processes in public health responses.
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http://dx.doi.org/10.1016/j.epidem.2024.100804 | DOI Listing |
Nano Converg
January 2025
Bendable Electronics and Sustainable Technologies (BEST) Group, Electrical and Computer Engineering Department, Northeastern University, Boston, MA, 02115, USA.
The intriguing way the receptors in biological skin encode the tactile data has inspired the development of electronic skins (e-skin) with brain-inspired or neuromorphic computing. Starting with local (near sensor) data processing, there is an inherent mechanism in play that helps to scale down the data. This is particularly attractive when one considers the huge data produced by large number of sensors expected in a large area e-skin such as the whole-body skin of a robot.
View Article and Find Full Text PDFAnal Chem
January 2025
State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan 430074, PR China.
The elemental imaging of laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) provides spatial information on elements and therefore can further investigate the growth or evolution processes of an analyte. However, the accurate determination of spatial information is limited by the decoupling between the elemental distribution and mass spectrometry signals. This phenomenon, which is more distinct when high-diffusion ablation cells are used, arises from the overlap of ablation and the transport dispersion of aerosols.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy.
Aromia bungii is an invasive Cerambycidae of major concern at the global scale because of the damage caused to Rosaceae. Given the major phytosanitary relevance of A. bungii, predicting its spread in invaded areas and identifying possible new suitable regions worldwide remains a key action to develop appropriate management practices and optimise monitoring and early detection campaigns.
View Article and Find Full Text PDFCommun Biol
January 2025
Instituto de Fisiología, Facultad de Ciencias, Universidad de Valparaíso, Valparaíso, Chile.
During spatial learning, subjects progressively adjust their navigation strategies as they acquire experience. The medial prefrontal cortex (mPFC) supports this operation, for which it may integrate information from distributed networks, such as the hippocampus (HPC) and the posterior parietal cortex (PPC). However, the mechanism underlying the prefrontal coordination with HPC and PPC during spatial learning is poorly understood.
View Article and Find Full Text PDFSci Rep
January 2025
International Livestock Research Institute (ILRI), Human and Animal Health, Berlin, Germany.
Crimean Congo hemorrhagic fever (CCHF) is a re-emerging tick-borne zoonosis that is caused by CCHF virus (CCHFV). The geographical distribution of the disease and factors that influence its occurrence are poorly known. We analysed historical records on its outbreaks in various countries across the sub-Saharan Africa (SSA) to identify hotspots and determine socioecological and demographicfactors associated with these outbreaks.
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