Background: Dengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to climate change in Vietnam. Objective: This study aimed to develop an accurate DF prediction model in Vietnam using a wide range of meteorological factors as inputs to inform public health responses for outbreak prevention in the context of future climate change. Methods: Convolutional neural network (CNN), Transformer, long short-term memory (LSTM), and attention-enhanced LSTM (LSTM-ATT) models were compared with traditional machine learning models on weather-based DF forecasting. Models were developed using lagged DF incidence and meteorological variables (measures of temperature, humidity, rainfall, evaporation, and sunshine hours) as inputs for 20 provinces throughout Vietnam. Data from 1997–2013 were used to train models, which were then evaluated using data from 2014–2016 by Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Results and discussion: LSTM-ATT displayed the highest performance, scoring average places of 1.60 for RMSE-based ranking and 1.95 for MAE-based ranking. Notably, it was able to forecast DF incidence better than LSTM in 13 or 14 out of 20 provinces for MAE or RMSE, respectively. Moreover, LSTM-ATT was able to accurately predict DF incidence and outbreak months up to 3 months ahead, though performance dropped slightly compared to short-term forecasts. To the best of our knowledge, this is the first time deep learning methods have been employed for the prediction of both long- and short-term DF incidence and outbreaks in Vietnam using unique, rich meteorological features. Conclusion: This study demonstrates the usefulness of deep learning models for meteorological factor-based DF forecasting. LSTM-ATT should be further explored for mitigation strategies against DF and other climate-sensitive diseases in the coming years.

Food-borne diseases are attracting a lot of attention in Vietnam as a result of repeated episodes of adulterated and unsafe food. In this paper, we provide some perspectives on food safety in Vietnam from the point of view of an international research institution working on food safety with partners in the country. We argue that one of the key issues of food safety in Vietnam is that certain food value chain stakeholders lack ethics, which leads to the production and trading of unsafe foods in order to make profits irrespective of adverse health effects on consumers. In turn, the shortfall in ethical behaviours around food can be attributed to a lack of incentives or motivating factors. Although food safety causes panic in the population, it is unclear how much contaminated food contributes to the burden of food-borne diseases and food poisonings in Vietnam. However, globally, the biggest health problem associated with food are infections from consuming food contaminated with viruses, bacteria or parasites. A major food safety challenge is the inappropriate way of communicating food risks to the public. Another key constraint is the inherent difficulty in managing food in wet markets and from smallholder production. On the other hand, local foods, and local food production and processing are an important cultural asset as well as being essential to food safety, and these aspects can be put at risk if food safety concerns motivate consumers to purchase more imported foods. In this paper, we also discuss good experiences in food safety management from other countries and draw lessons learnt for Vietnam on how to better deal with the current food safety situation.

Background: The Global Climate Risk Index 2020 ranked Vietnam as the sixth country in the world most affected by climate variability and extreme weather events over the period 1999-2018. Sea level rise and extreme weather events are projected to be more severe in coming decades, which, without additional action, will increase the number of people at risk of climate-sensitive diseases, challenging the health system. This article summaries the results of a health vulnerability and adaptation (V&A) assessment conducted in Vietnam as evidences for development of the National Climate Change Health Adaptation Plan to 2030. Methods: The assessment followed the first 4 steps outlined in the World Health Organization’s Guidelines in conducting “Vulnerability and Adaptation Assessments.” A framework and list of indicators were developed for semi-quantitative assessment for the period 2013 to 2017. Three sets of indicators were selected to assess the level of (1) exposure to climate change and extreme weather events, (2) health sensitivity, and (3) adaptation capacity. The indicators were rated and analyzed using a scoring system from 1 to 5. Results: The results showed that climate-sensitive diseases were common, including dengue fever, diarrheal, influenza, etc, with large burdens of disease that are projected to increase. From 2013 to 2017, the level of “exposure” to climate change–related hazards of the health sector was “high” to “very high,” with an average score from 3.5 to 4.4 (out of 5.0). For “health sensitivity,” the scores decreased from 3.8 in 2013 to 3.5 in 2017, making the overall rating as “high.” For “adaptive capacity,” the scores were from 4.0 to 4.1, which meant adaptive capacity was “very low.” The overall V&A rating in 2013 was “very high risk” (score 4.1) and “high risk” with scores of 3.8 in 2014 and 3.7 in 2015 to 2017. Conclusions: Adaptation actions of the health sector are urgently needed to reduce the vulnerability to climate change in coming decades. Eight adaptation solutions, among recommendations of V&A assessment, were adopted in the National Health Climate Change Adaptation Plan.

Antibiotic residues in chicken meat samples is a serious public health concern due to their harmful effects on consumers’ health. We conducted this research in 2017 to determine antibiotic residues in chicken meat samples and to describe the knowledge, attitude, and practice (KAP) of farmers on the antibiotic uses in poultry farms at Tay Ninh province. Farmers who raised chickens at their farmhouses were surveyed using a KAP survey questionnaire, and 106 chicken meat samples were analyzed for 29 kinds of antibiotic residues. The results showed that 27.4% samples were positive with 11 kinds of 4 antibiotic groups: fluoroquinolones, sulfonamides, tetracycline, and macrolides. A total of 50.9% farmers needed to improve their knowledge on the appropriate use of antibiotics. Although 54.7% famers had positive attitude, just 17% had good practices. It was recommended that the levels of antibiotic residues in chickens should be communicated to food safety and veterinary authorities, chicken farmers, and the general public. Enhancing the training and coaching for each group of farmers to improve their knowledge and practices on the appropriate use of antibiotics in raising chickens is needed. Local government should enhance the level of control and punishment for drug sellers and end users regarding the use of banned antibiotics in chickens.