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This study aimed to describe the characteristics of COVID-19 cases and close contacts during the first wave of COVID-19 in Malaysia (23 January 2020 to 26 February 2020), and to analyse the reasons why the outbreak did not continue to spread and lessons that can be learnt from this experience. Characteristics of the cases and close contacts, spatial spread, epidemiological link, and timeline of the cases were examined. An extended SEIR model was developed using several parameters such as the average number of contacts per day per case, the proportion of close contact traced per day and the mean daily rate at which infectious cases are isolated to determine the basic reproduction number (R) and trajectory of cases. During the first wave, a total of 22 cases with 368 close contacts were traced, identified, tested, quarantine and isolated. Due to the effective and robust outbreak control measures put in place such as early case detection, active screening, extensive contact tracing, testing and prompt isolation/quarantine, the outbreak was successfully contained and controlled. The SEIR model estimated the R at 0.9 which further supports the decreasing disease dynamics and early termination of the outbreak. As a result, there was a 11-day gap (free of cases) between the first and second wave which indicates that the first wave was not linked to the second wave.
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http://dx.doi.org/10.3390/ijerph19073828 | DOI Listing |
Sci Adv
September 2025
School of Biomedical Engineering, ShanghaiTech University, Shanghai, China.
Developing intelligent robots with integrated sensing capabilities is critical for advanced manufacturing, medical robots, and embodied intelligence. Existing robotic sensing technologies are limited to recording of acceleration, driving torque, pressure feedback, and so on. Expanding and integrating with the multimodal sensors to mimic and even surpass the human feeling is substantially underdeveloped.
View Article and Find Full Text PDFJ Gerontol B Psychol Sci Soc Sci
September 2025
Department of Sociology and Center for Innovation in Social Science, Boston University, Boston, Massachusetts, United States.
Objectives: This study explores the dyadic relationship between cognitive function and friendship characteristics among older married couples framed within the "linked lives" dimension of the life course perspective. The study also explores whether the dyadic consequences of cognitive function for friendship networks vary by gender.
Methods: The study uses the data from the 2014/2016 Health and Retirement Study (N = 2,944 dyads).
Cureus
August 2025
Department of Cardiology, Pulmonology, Hypertension, and Nephrology, Ehime University Graduate School of Medicine, Toon, JPN.
Objectives In Japan, clinical diagnosis based solely on symptoms, without the use of test kits, has been adopted to enable the rapid identification of individuals infected with coronavirus disease 2019 (COVID-19). A history of close contact with COVID-19 patients is a prerequisite for such symptom-based diagnosis. However, the current diagnostic criteria lack objectivity.
View Article and Find Full Text PDFBMC Health Serv Res
September 2025
African Population and Health Research Center (APHRC), APHRC Campus, 2nd Floor, Manga Close off Kirawa Road, P.O. Box 10787-00100, Nairobi, Kenya.
Background: Maternal healthcare (MHC) in Cameroon reflects the persistent challenges in Sub-Saharan Africa, where high maternal mortality continues despite improved service utilization, stressing inequitable effective coverage (EC). This study applied EC cascade analysis-including service contact, continuity, and input-adjusted coverage-to quantify geographic and socioeconomic disparities, informing equity-focused strategies to dismantle structural barriers in the MHC continuum.
Methods: We combined population and health facility data (2018 Cameroon Demographic and Health Survey and 2015 Emergency Obstetric and Neonatal Care Assessment) to estimate the input-adjusted coverage of antenatal care (ANC) and intra-and postpartum care (IPC).
Prog Mol Biol Transl Sci
September 2025
Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego, La Jolla, CA, United States. Electronic address:
Nano-electronics based neural implants represent a rapidly advancing interdisciplinary domain at the intersection of bioelectronics, nanotechnology, and neuro-engineering. These implantable systems are engineered to restore, modulate, or augment neural functions by establishing high-fidelity, long-term interfaces with neural tissues. The design of such implants necessitates careful consideration of both materials and structural configurations to ensure biocompatibility, mechanical compliance, electrical functionality, and chronic stability.
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