Spatiotemporal trends and meteorological influence on hand, foot, and mouth disease in Ho Chi Minh City: insights from 2015–2022 using machine learning and trend analysis

This work used seven meteorological indicators to investigate their effects on hand, foot, and mouth disease (HFMD) in Ho Chi Minh City (HCMC) and the spatiotemporal pattern trends of HFMD from 2015 to 2022 by integrating multiple approaches, including Innovative Polygon Trend Analysis (IPTA), Inverse Distance Weight (IDW), Sobol’s method, and long short-term memory (LSTM). The consistent results detected that maximum temperature and relative humidity significantly contributed to the tendency of HFMD for both Sobol and LSTM methods. HFMD performed a downward trend from November to July, while an upward trend appeared in April, May, and June. Two highlight transitions were observed from April to May and November to December, with the amount of 88.58 and 1828.27 cases/month for HFMD, respectively. There was a geographical heterogeneity related to the cases that occurred, more HFMD cases were occupied in Cu Chi and Hoc Mon districts than in other areas in HCMC. Generally, this study revealed the impact of meteorological factors on HFMD and the trends potentially varying based on geographic regions and the time of year. These findings will be expected to provide preliminary knowledge for the early warning and preventive strategies against HFMD.