All Stories

  1. Knowledge and beliefs about climate change and emerging infectious diseases in bangladesh: implications for one health approach
  2. Unraveling global malaria incidence and mortality using machine learning and artificial intelligence–driven spatial analysis
  3. Dengue Early Warning System and Outbreak Prediction Tool in Bangladesh Using Interpretable Tree‐Based Machine Learning Model
  4. Utilizing artificial intelligence to predict and analyze socioeconomic, environmental, and healthcare factors driving tuberculosis globally
  5. Impact of Climate Change on Emerging Infectious Diseases and Human Physical and Mental Health in Bangladesh
  6. Machine learning and spatio-temporal analysis of meteorological factors on waterborne diseases in Bangladesh
  7. Spatio‐temporal pattern and associate meteorological factors of airborne diseases in Bangladesh using geospatial mapping and spatial regression model
  8. Predicting anxiety, depression, and insomnia among Bangladeshi university students using tree‐based machine learning models
  9. Uptake of COVID-19 vaccine among high-risk urban populations in Southern Thailand using the COM-B model
  10. A quantile regression approach to identify risk factors for high blood glucose levels among Bangladeshi individuals
  11. A Machine Learning Web App to Predict Diabetic Blood Glucose Based on a Basic Noninvasive Health Checkup, Sociodemographic Characteristics, and Dietary Information: Case Study
  12. A Machine Learning Web App to Predict Diabetic Blood Glucose Based on a Basic Noninvasive Health Checkup, Sociodemographic Characteristics, and Dietary Information: Case Study (Preprint)
  13. Risk factors of caesarean deliveries in urban–rural areas of Bangladesh
  14. The experiences of district public health officers during the COVID-19 crisis and its management in the upper southern region of Thailand: A mixed methods approach
  15. Understanding dengue solution and larval indices surveillance system among village health volunteers in high- and low-risk dengue villages in southern Thailand
  16. Epidemiological profile of dengue in Champasak and Savannakhet provinces, Lao People’s Democratic Republic, 2003–2020
  17. A data-driven eXtreme gradient boosting machine learning model to predict COVID-19 transmission with meteorological drivers
  18. Role of artificial intelligence-internet of things (AI-IoT) based emerging technologies in the public health response to infectious diseases in Bangladesh
  19. Accuracy comparison of ARIMA and XGBoost forecasting models in predicting the incidence of COVID-19 in Bangladesh
  20. Mapping the spatial distribution of the dengue vector Aedes aegypti and predicting its abundance in northeastern Thailand using machine-learning approach
  21. Development and Comparison of Dengue Vulnerability Indices Using GIS-Based Multi-Criteria Decision Analysis in Lao PDR and Thailand
  22. Analyzing Predictors of Control Measures and Psychosocial Problems Associated with COVID-19 Pandemic: Evidence from Eight Countries
  23. Ecological, Social, and Other Environmental Determinants of Dengue Vector Abundance in Urban and Rural Areas of Northeastern Thailand
  24. Correction: Doum, D., et al. Dengue Seroprevalence and Seroconversion in Urban and Rural Populations in Northeastern Thailand and Southern Laos. Int. J. Environ. Res. Public Health 2020, 17, 9134
  25. Knowledge, attitudes, and practices on climate change and dengue in Lao People's Democratic Republic and Thailand
  26. COVID-19 Epidemic in Bangladesh among Rural and Urban Residents: An Online Cross-Sectional Survey of Knowledge, Attitudes, and Practices
  27. Dengue Seroprevalence and Seroconversion in Urban and Rural Populations in Northeastern Thailand and Southern Laos
  28. Climate change and dengue fever knowledge, attitudes and practices in Bangladesh: a social media–based cross-sectional survey
  29. Defending against the Novel Coronavirus (COVID-19) outbreak: How can the Internet of Things (IoT) help to save the world?
  30. Survival probabilities of stomach and colon cancer patients in Bangladesh
  31. The SARS, MERS and novel coronavirus (COVID-19) epidemics, the newest and biggest global health threats: what lessons have we learned?
  32. Forecasting the BDT/USD Exchange Rate: An Accuracy Comparison of Artificial Neural Network Models and Different Time Series Models
  33. Weak Form, Run test, Autocorrelation test, Variance Ratio Test, CSE.