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Introduction: Traditional methods for determining radiation dose in nuclear medicine include the Monte Carlo method, the discrete ordinate method, and the point kernel integration method. This study presents a new mathematical model for predicting the radiation dose rate in the vicinity of nuclear medicine patients. Methods: A new algorithm was created by combining the physical model of "cylinder superposition" of the human body with integral analysis to assess the radiation dose rate in the vicinity of nuclear medicine patients. Results: The model accurately predicted radiation dose rates within distances of 0.1-3.0 m, with a deviation of less than 11% compared to observed rates. The model demonstrated greater accuracy at shorter distances from the radiation source, with a deviation of only 1.55% from observed values at 0.1 m. Discussion: The model proposed in this study effectively represents the spatial and temporal distribution of the radiation field around nuclear medicine patients and demonstrates good agreement with actual measurements. This model has the potential to serve as a radiation dose rate alert system in hospital environments.
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What is already known about this topic?: The impact of air temperature on varicella has been studied, but there is limited research exploring its effect on varicella by gender and age group. What is added by this report?: We conducted a time series analysis to examine the differential effects of air temperature on varicella infection across different demographic groups. Our findings indicate that lower temperatures have a more pronounced influence on varicella incidence among males and children compared to females and adults. What are the implications for public health practice?: These findings can assist in identifying populations that are vulnerable to temperature-related varicella and in guiding the implementation of effective measures for varicella control.
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Introduction: Varicella, a prevalent respiratory infection among children, has become an escalating public health issue in China. The potential to considerably mitigate and control these outbreaks lies in surveillance-based early warning systems. This research employed an autoregressive integrated moving average (ARIMA) model with the objective of predicting future varicella outbreaks in the country. Methods: An ARIMA model was developed and fine-tuned using historical data on the monthly instances of varicella outbreaks reported in China from 2005 to 2018. To determine statistically significant models, parameter and Ljung-Box tests were employed. The coefficients of determination (R2) and the normalized Bayesian Information Criterion (BIC) were compared to selecting an optimal model. This chosen model was subsequently utilized to forecast varicella outbreak cases for the year 2019. Results: Four models passed parameter (all P<0.05) and Ljung-Box tests (all P>0.05). ARIMA (1, 1, 1)×(0, 1, 1)12 was determined to be the optimal model based on its coefficient of determination R2 (0.271) and standardized BIC (14.970). Fitted values made by the ARIMA (1, 1, 1)×(0, 1, 1)12 model closely followed the values observed in 2019, the average relative error between the actual value and the predicted value is 15.2%. Conclusion: The ARIMA model can be employed to predict impending trends in varicella outbreaks. This serves to offer a scientific benchmark for strategies concerning varicella prevention and control.
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Introduction: Varicella outbreaks significantly disrupt schools and other child-centered institutions. This study aimed to identify patterns and epidemiological features of varicella outbreaks in China from 2006 to 2022. Methods: Data were extracted from outbreak reports submitted to the Public Health Emergency Reporting Management Information System within the specified timeframe. Analytical methods included Spearman correlation tests and the Mann-Kendall trend tests, conducted using R software to analyze and summarize reported data. Additionally, statistical analyses of trends and epidemiological characteristics were performed using SPSS software. Results: Between 2006 and 2022, a total of 11,990 varicella outbreaks were reported in China, resulting in 354,082 cases. The attack rates showed a decreasing trend over the years (Z=-4.49, P<0.05). These outbreaks occurred in two peaks annually. The eastern region accounted for the highest number of outbreaks (31.53%), followed by the southwestern (24.22%) and southern (17.93%) regions. Varicella outbreaks were most common in elementary schools. Most of the outbreaks (60.43%) were classified as Grade IV (general) severity, with 86.41% of the outbreaks having 10-49 cases. The median and inter-quartile ranges (IQR) of the duration of outbreaks, response time, and case counts were 21 (10, 39) days, 4 (0, 12) days, and 23 (16, 35) cases, respectively. These variables showed a positive correlation (P<0.001). Conclusions: Varicella outbreaks exhibited fluctuating trends, initially decreasing until 2012, followed by an increase, reaching the highest peak in 2018-2019. Continual monitoring of varicella epidemiology is necessary to assess the burden of the disease and formulate evidence-based strategies and policies for its prevention and control.
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What is already known about this topic?: Herpes zoster (shingles) is a common skin condition in older adults, which usually presents as a painful rash with blisters. Vaccination is the most effective method to prevent shingles. However, there is not sufficient population-based epidemiological data in China to optimize the timing of zoster vaccination. What is added by this report?: Clustering analyses of population-wide epidemiological data from the Healthcare Big Data Platform in Yichang, China showed that the average annual zoster incidence is the highest among people 55 years or older, at 10 cases per thousand persons per year, making this age group the optimal target population for vaccination. Incidence was lower but increased with age among younger adults, 28-54 years old. What are the implications for public health practice?: With limited vaccination resources, zoster vaccinations should be targeted at adults 55 years or older who are at the greatest risk for shingles. Research should be conducted to understand the risk of shingles among young and middle-aged adults and identify triggers of shingles: potentially leading to preventive measures.