Min KD, et al. J Korean Med Sci. 2020 Aug;35(35):e321. https://doi.org/10.3346/jkms.2020.35.e321

Background: Scrub typhus is an important public health issue in Korea. Risk factors for scrub typhus include both individual-level factors and environmental drivers, and some are related to the increased density of vector mites and rodents, the natural hosts of the mites. In this regard, deforestation is a potential risk factor, because the deforestation-induced secondary growth of scrub vegetation may increase the densities of mites and rodents. To examine this hypothesis, this study investigated the association between scrub typhus and deforestation. Methods: We acquired district-level data for 2006–2017, including the number of cases of scrub typhus reported annually, deforestation level, and other covariates. Deforestation was assessed using preprocessed remote-sensing satellite data. Bayesian regression models, including Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial models, were examined, and spatial autocorrelation was considered in hierarchical models. A sensitivity analysis was conducted using different accumulation periods for the deforestation level to examine the robustness of the association. Results: The final models showed a significant association between deforestation and the incidence of scrub typhus (relative risk = 1.20, 95% credible interval = 1.15–1.24). The sensitivity analysis gave consistent results, and a potential long-term effect of deforestation for up to 5 years was shown. Conclusion: The results support the potential public health benefits of forest conservation by suppressing the risk of scrub typhus, implying the need for strong engagement of public health sectors in conservation issues from a One Health perspective.

Analysis of occupational injuries is essential for developing preventive strategies. However, few studies have evaluated severe occupational injuries in migrant workers from the perspective of gender. Therefore, using a new analytical method, this study was performed to identify gender-specific characteristics associated with fatal occupational injuries among migrant workers; the interactions between these factors, were also analyzed. In addition, we compared the utility of explainable artificial intelligence (XAI) using SHapley Additive exPlanations (SHAP) with logistic regression (LR) and discuss caveats regarding its use. We analyzed national statistics for occupational injuries among migrant workers (n = 67,576) in South Korea between January 1, 2007, and September 30, 2018. We applied an extreme gradient boosting model and developed SHAP and LR models for comparison. We found clear gender differences in fatal occupational injuries among migrant workers, with males in the same occupation having a higher risk of death than females. These gender differences suggest the need for gender-specific occupational injury prevention interventions for migrant workers to reduce the mortality rate. Occupation was a significant predictor of death among female migrant workers only, with care jobs having the highest fatality risk. The occupational fatality risk of female workers would not have been identified without the performance of detailed job-specific analyses stratified by gender. The major advantages of SHAP identified in the present study were the automatic identification and analysis of interactions, ability to determine the relative contributions of each feature, and high overall performance. The major caveat when using SHAP is that causality cannot be established. Detailed job-specific analyses stratified by gender, and interventions considering the gender of migrant workers, are necessary to reduce occupational fatality rates. The XAI approach should be considered as a complementary analytical method for epidemiological studies, as it overcomes the limitations of traditional statistical analyses.

We assessed the risk of fatal occupational injuries among migrant workers with two different types of employment permits in South Korea. This observational study used national data from January 2007 to September 2018 and analyzed 42,089 cases of occupationally injured migrant workers of Chinese nationality. Fatality rates were analyzed according to year, sex, age, occupation, industry, and type of employment permit. Chinese workers were permitted to work for one employer and prohibited from changing employers, whereas Korean-Chinese workers were permitted to change their employer. The adjusted fatality rate of occupational injuries of Chinese migrant workers was significantly higher (1.80-fold, 95% confidence interval 1.31–2.46) than that of Korean-Chinese migrant workers. The prohibition on changing workplaces; male sex; age ≥ 45 years; machine operator; construction industry; and agriculture, livestock, and fisheries industry were risk factors for fatal occupational injuries. The results imply a need for revision of the migrant-worker employment permit systems and implementation of occupational safety and health policies for all workers to promote health equity.

Background: Lassa fever (LF) is one of the most devastating rodent-borne diseases in West Africa, causing thousands of deaths annually. The geographical expansion of LF is also a concern; cases were recently identified in Ghana and Benin. Previous ecological studies have suggested that high natural-host biodiversity reduces the likelihood of spillover transmission of rodent-borne diseases, by suppressing the activities of reservoir species. However, the association of biodiversity with the geographical expansion of LF has not been the subject of epidemiological studies.Methodology/Principal findings: We conducted a spatial analysis based on sociodemographic, geographical, and ecological data, and found that higher rodent species richness was significantly associated with a lower risk of LF emergence in West Africa from 2008 to 2017 (Odds Ratio = 0.852, 95% Credible Interval = 0.745–0.971).Conclusions/Significance: The results reinforce the importance of the ‘One Health’ approach by demonstrating that a high level of biodiversity could benefit human health.