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Quantitative source apportionment and health risk assessment for polycyclic aromatic hydrocarbon and their derivatives in indoor dust from housing and public buildings of a mega-city in China.
J Hazard Mater
December 2024
School of Environment, Nanjing Normal University, Jiangsu Province Engineering Research Center of Environmental Risk Prevention and Emergency Response Technology, Nanjing 210023, China. Electronic address:
Indoor dust can adsorb various pollutants and long-term deposition can significantly impact air quality and human health. This study investigated the occurrence, source apportionment, and health risks associated with polycyclic aromatic hydrocarbons (PAHs) and their derivatives (d-PAHs) in indoor dust, by focusing on residential and public buildings in Nanjing, China. The concentration of 16 PAHs and 27 d-PAHs ranged from 511 to 5472 ng/g and from 422 to 2904 ng/g, with the most abundant compounds being fluoranthene and 1,2-benz[a]anthraquinone, respectively.
View Article and Find Full Text PDFA Theoretical Analysis of Mass Testing Strategies to Control Epidemics.
Bull Math Biol
January 2025
Department of Mathematics, University of Trento, Via Sommarive 14, Povo, 38123, Trento, Italy.
One of the strategies used in some countries to contain the COVID-19 epidemic has been the test-and-isolate policy, generally coupled with contact tracing. Such strategies have been examined in several simulation models, but a theoretical analysis of their effectiveness in simple epidemic model is, to our knowledge, missing. In this paper, we present four epidemic models of either SIR or SEIR type, in which it is assumed that at fixed times the whole population (or a part of the population) is tested and, if positive, isolated.
View Article and Find Full Text PDFEpidemiological and Clinical Characteristics of Mpox in Jakarta, Indonesia During October 2023 to February 2024.
Disaster Med Public Health Prep
January 2025
Faculty of Public Health, Universitas Islam Negeri Sumatera Utara, Medan, Indonesia.
Objective: Mpox, a zoonotic disease, has emerged as a significant international public health concern due to an increase in the number of cases diagnosed in non-endemic countries. To support public health response efforts to interrupt Mpox transmission in the community, this study aims to identify epidemiological and clinical aspects of Mpox in Jakarta, Indonesia.
Methods: The study collected Mpox data from the Provincial Health Department in Jakarta, Indonesia, from October 2023 to February 2024.
Extending and Testing Protection Motivation Theory in the Context of COVID-19 Contact-Tracing Technology: A Comparison of South Korea and the United States.
Health Commun
January 2025
Department of Communications and New Media, National University of Singapore.
This study applies protection motivation theory (PMT) to the COVID-19 contact-tracing context by including privacy concerns, collective efficacy, and a mediator (fear of COVID-19) and tests it in the US and South Korea. The study uses a structural equation modeling (SEM) approach and a sample of 418 Americans and 444 South Koreans. According to the results, fear was positively associated with adoption intentions in the US sample but not in the Korean sample.
View Article and Find Full Text PDFThe role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development.
Mol Biomed
January 2025
Department of Artificial Intelligence and Machine Learning, Faculty of Engineering and Technology, Datta Meghe Institute of Higher Education and Research (Deemed to Be University), Wardha, Maharashtra, 442001, India.
Integrating Artificial Intelligence (AI) across numerous disciplines has transformed the worldwide landscape of pandemic response. This review investigates the multidimensional role of AI in the pandemic, which arises as a global health crisis, and its role in preparedness and responses, ranging from enhanced epidemiological modelling to the acceleration of vaccine development. The confluence of AI technologies has guided us in a new era of data-driven decision-making, revolutionizing our ability to anticipate, mitigate, and treat infectious illnesses.
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