To predict the incidence trends of hand, foot and mouth disease (HFMD) in Shenzhen city, Guangdong province based on the meteorological lag effect and the long short-term memory (LSTM) model, thereby providing methodological support for establishing a more scientific and accurate meteorological disease risk early warning system.

Data from 523 weeks (January 1, 2015 to December 31, 2024) of HFMD case reports in the China Disease Control and Prevention Information System were collected. A total of 353 046 HFMD cases in children aged ≤5 years were aggregated weekly. Meteorological parameters, including average weekly temperature (Temp), relative humidity (RH), temperature-humidity index (THI), apparent temperature (AT), and wind speed (WS), were integrated. Significant correlated variables were screened by Spearman rank correlation analysis to construct three types of LSTM models: a baseline model (case count only), single-factor models (case count + Temp/RH lagged 1–3 weeks), and composite models (case count + THI/AT lagged 1–3 weeks). Model performance was evaluated and compared via the root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R²).

Comparative analysis on the test set showed that all the models incorporating meteorological factors outperformed the baseline model (RMSE = 211.109, MAE = 117.654, R² = 0.942). Among the single-factor models, the model with Temp lagged by 2 weeks (Temp-lag2) performed best (RMSE = 179.915, MAE = 108.290, R² = 0.958), and the model with RH lagged by 2 weeks (RH-lag2) was optimal among all the models (RMSE = 177.457, MAE = 97.873, R² = 0.959). Among the composite models, the model with THI lagged by 2 weeks (THI-lag2) performed best (RMSE = 185.061, MAE = 103.817, R² = 0.956) but was slightly inferior to the RH-lag2 model. The RH-lag2 model predicted a bimodal pattern (peaks at weeks 10 and 15) for the HFMD incidence trends in the first 20 weeks of 2025, which closely matched the spring peak pattern of 2024 and showed a significant overall shift forward compared to the average peak period (weeks 9–35) from 2015 to 2024.

The LSTM model constructed based on RH lagged by 2 weeks effectively characterizes the promoting effects of a hot and humid environment on the survival and transmission of enteroviruses, significantly improving the prediction accuracy of HFMD incidence trends.

To analyze the effects of meteorological factors on the incidence of scarlet fever in Guangzhou from 2014 to 2022.

The epidemiological characteristics of scarlet fever in Guangzhou were described. The effects of meteorological factors on the risk of scarlet fever were evaluated via Spearman correlation analysis, distributed lag non-linear models, and bivariate response models.

The incidence of scarlet fever had correlations (P < 0.05) with mean temperature (rs = −0.255), wind speed (rs = −0.126), air pressure (rs = 0.116), and sunshine duration (rs = −0.177). Mean temperature exhibited risk effects at lower temperatures and protective effects at higher temperatures, with the relative risk (RR) peaking at 1.41 (95%CI: 1.09–1.83) when the temperature was 12 ℃. The relationships of wind speed and sunshine duration with incidence of scarlet fever followed a wave-like pattern, with the strongest risk effect observed at a wind speed of 4.3 m/s (RR = 5.67, 95%CI: 1.61–19.84). When sunshine duration exceeded 8 h/d, the risk effect increased markedly, albeit not statistically significant (95%CI: 0.97–4.95). Air pressure demonstrated protective effects at low levels and risk effects at high levels on the incidence of scarlet fever, with the RR peaking at 2.26 (95%CI: 1.70–3.02) when the air pressure was 1 016.5 hPa. The interactions of meteorological factors such as low temperature, high wind speed, long sunshine duration, and high air pressure further contributed to an increase in scarlet fever incidence in Guangzhou.

Mean temperature, wind speed, air pressure, and sunshine duration demonstrate non-linear relationships and lag effects with the incidence of scarlet fever, with interactions among each other. Therefore, adjusting these meterological factors can be taken as a focus of prevention and control efforts for scarlet fever.

To construct and validate a risk diagnostic model for diabetes in rural elderly individuals with both hypertension and dyslipidemia, thus providing a scientific basis for the prevention and control of the co-morbidity of hypertension, hyperglycemia, and dyslipidemia in rural elderly people in China.

With the data of 583 rural elderly individuals with hypertension and dyslipidemia from the 2015 China Health and Retirement Longitudinal Study (CHARLS) as the training set, a multivariate unconditional logistic regression model was adopted to analyze the influencing factors of diabetes in rural elderly individuals with hypertension and dyslipidemia and construct a risk diagnostic model. The goodness-of-fit of the model was tested via the Hosmer-Lemeshow method. The physical examination data of 1 185 elderly individuals who aged 65 and above and had both hypertension and dyslipidemia and complete outcome variables and key variables in Anfeng town, Dongtai city, Jiangsu province were used for external validation. Receiver operating characteristic (ROC) curves, calibration curves, and decision curves were established. The restricted cubic spline (RCS) model was employed to analyze the dose-response relationships of the Chinese visceral adiposity index (CVAI) and white blood cell count with the prevalence of diabetes in rural elderly individuals with both hypertension and dyslipidemia.

The results of the analysis on CHARLS data showed that CVAI, alcohol consumption status, and white blood cell count were the main factors influencing the prevalence of diabetes among rural elderly individuals with both hypertension and dyslipidemia (all P < 0.05). The results of the RCS model analysis showed that CVAI and white blood cell count were linearly positively correlated with the risk of diabetes (non-linear test P = 0.964 and 0.755), and the risk of diabetes increased linearly with the increase in CVAI and white blood cell count. The Hosmer-Lemeshow goodness-of-fit test (P = 0.739), the ROC curve of the external validation set [AUC (95%CI): 0.924 (0.910–0.939)], the calibration curve, and the decision curve all indicated that the risk diagnostic model constructed in this study for diabetes has good performance.

The risk diagnostic model for diabetes in rural elderly individuals with both hypertension and dyslipidemia, which is constructed in this study, has excellent performance and clinical benefits. In this population, drinkers as well as those with higher CVAI and white blood cell count should be regarded as the key groups for diabetes prevention.

To improve the normality, effectiveness, and rationality of China′s management system for products in contact with drinking water and proposed corresponding measures and suggestions.

The horizontal comparison analysis was conducted to compare the domestic and foreign management systems for products in contact with drinking water from two dimensions of management basis and management process. Then, according to the comparison results, SWOT analysis was performed to elucidate the strengths, weaknesses, opportunities, and threats in China′s management system.

The United States, the European Union, and Japan started early in the management of such products, and they mostly appointed the third-party testing organizations for product safety evaluation and certification and adopted the market for supervision after product marketing. Third-party certification organizations in these countries and regions are generally mature, have sound testing standards, and produce reliable test results. China started late in building the management system but developed rapidly in this field, establishing a management system within a short period of time. In China, the health administrative department is responsible for the management of products in contact with drinking water throughout the whole chain. Meanwhile, China actively introduces relevant regulations and standards to maximize the protection of people′s health.

The United States, the European Union, and Japan mainly rely on the market to manage products in contact with drinking water, with the government responsible for post-mortem supervision. China′s management system of products in contact with drinking water is characterized by government-guided standard formulation and implementation and emphasizes access mechanism but is weak in content updating. In the context of rapid development, new ideas should be incorporated into the management of products in contact with drinking water, thereby safeguarding the safety of drinking water.