Dengue fever is a serious and growing public health problem in Latin America and elsewhere, intensified by climate change and human mobility. This paper reviews the approaches to the epidemiological prediction of dengue fever using the One Health perspective, including an analysis of how Machine Learning techniques have been applied to it and focuses on the risk factors for dengue in Latin America to put the broader environmental considerations into a detailed understanding of the small-scale processes as they affect disease incidence. Determining that many factors can act as predictors for dengue outbreaks, a large-scale comparison of different predictors over larger geographic areas than those currently studied is lacking to determine which predictors are the most effective. In addition, it provides insight into techniques of Machine Learning used for future predictive models, as well as general workflow for Machine Learning projects of dengue fever.

Malaria remains a major health problem in many parts of the world, including Sub-Saharan Africa. Insecticide-treated nets, in combination with other control measures, have been effective in reducing malaria incidence over the past two decades. Nevertheless, there are concerns about improper handling and misuse of nets, producing possible health effects from intoxication and collateral environmental damage. The latter is caused, for instance, from artisanal fishing. We formulate a model of impulsive differential equations to describe the interplay between malaria dynamics, human intoxication, and ecosystem damage; affected by human awareness to these risks and levels of net usage. Our results show that an increase in mosquito net coverage reduces malaria prevalence and increases human intoxications. In addition, a high net coverage significantly reduces the risk perception to disease, naturally increases the awareness for intoxications from net handling, and scarcely increases the risk perception to collateral damage from net fishing. According to our model, campaigns aiming at reducing disease prevalence or intoxications are much more successful than those creating awareness to ecosystem damage. Furthermore, we can observe from our results that introducing closed fishing periods reduces environmental damage more significantly than strategies directed towards increasing the risk perception for net fishing.

Introduction Migration figures place Chile as one of the South American countries with the highest rate of migrants. The present study estimated the relationship between sociodemographic characteristics, quality of life, and psychosocial occupational risks in migrant workers from the Maule region.Methods Cross-sectional study with migrant workers between 18 and 60 years of age residing in the Maule region (n = 145). The applied questionnaires were: a psychosocial risk questionnaire, a health and quality of life questionnaire, and a sociodemographic questionnaire. A bivariate statistical analysis was performed using nonparametric Mann-Whitney U tests, Kruskal Wallis, Spearman correlation, and multiple linear regression models.Results In Chile, 21% of the migrants maintained the same work activity as in their country of origin. Although the quality of life in physical and mental health is adequate, 52% have low psychological demands at work, 48.9% have low levels of active work and development skills, 57.7% have a high -risk level of compensation and self-esteem, and 65.5% have a high -risk level of double presence at work. Migrants with a higher quality of life in the physical health dimension have a lower risk of maintaining a balance between effort and reward; they worked 44 hours a week and did not work directly at Maule. Migrants with a higher quality of life in the mental health dimension have a lower risk of emotional demands, perceive greater social support in the company, and are less concerned about domestic chores.Conclusions Migrants with lower quality of life in the physical health dimension presented less compensation at work and recognition, came to work directly in the region, and had jobs with fewer contract hours. Workers with lower quality of life in their mental health exhibited a greater risk of psychological demands at work and perceived low social support in the company; they were concerned about having to respond to domestic and salaried work.

Concerning health, experience indicates that in all human groups a percentage of individuals behave conscientiously when facing contagious diseases. This aware group responds with activities to prevent disease transmission and to minimize risk. In contrast, other individuals tend to behave with less engagement except in catastrophic cases. Assuming the theoretical and methodological framework provided by mathematical epidemiology, and based on a Susceptible – Infectious - Recovered (SIR) model, we evaluated the factors of size and intensity of the behaviours in the aware group to determine the basic reproduction number. This number is the reduction in the number of secondary cases that would be produced by a first infectious individual. Additionally, we calculated the total and individual prevented prevalence for each aware individual for different parametric scenarios. Lastly, we suggest that distance and interpersonal contact should be included as factors associated to the potential of transmission.

Yellow fever remains a major public health threat in endemic and re-emerging regions of Africa and South America, with recent outbreaks highlighting persistent gaps in prevention and surveillance. Pregnant women represent a particularly vulnerable population, yet the epidemiology, clinical impact, and preventive strategies for yellow fever in pregnancy are insufficiently characterized. Physiological and immunological changes during gestation may influence host responses to infection; however, current evidence does not demonstrate increased susceptibility to or severity of yellow fever during pregnancy. Adverse materno-fetal outcomes, including miscarriage, stillbirth, preterm birth, and, in rare cases, perinatal transmission, have been reported but remain poorly characterized. Diagnostic challenges, overlapping clinical presentations with other arboviral and hepatic diseases, and limited access to specialized care further complicate clinical management in many endemic settings. This perspective provides a comprehensive overview of yellow fever in pregnancy during the 2024–2026 outbreak in the Americas, including a risk-stratification framework for prevention. We summarize current evidence on epidemiology, pathophysiology, diagnosis, and supportive care, and examine prevention strategies with particular emphasis on vaccination. Accumulated observational evidence and substantial real-world experience have not demonstrated an increased risk of serious adverse events and generally support the effectiveness of yellow fever vaccination during pregnancy when administered with appropriate clinical judgment. In high-risk settings, the benefits of maternal immunization clearly outweigh theoretical concerns, supporting a flexible, risk-based approach, despite relatively limited evidence. We also discuss national and international policies, post-pregnancy booster recommendations, and the importance of integrating vaccination assessment into antenatal care. Finally, we highlight critical knowledge gaps and research priorities, including the need for prospective registries and strengthened pharmacovigilance. Coordinated clinical and public health strategies are essential to protect maternal and neonatal health and to reduce the burden of yellow fever in endemic and re-emerging settings.