Control measure implications of COVID-19 infection in healthcare facilities reconsidered from human physiological and engineering aspects

The Wells-Riley model invokes human physiological and engineering parameters to successfully treat airborne transmission of infectious diseases. Applications of this model would have high potentiality on evaluating policy actions and interventions intended to improve public safety efforts on preventing the spread of COVID-19 in an enclosed space. Here, we constructed the interaction relationships among basic reproduction number (R₀) − exposure time − indoor population number by using the Wells-Riley model to provide a robust means to assist in planning containment efforts. We quantified SARS-CoV-2 changes in a case study of two Wuhan (Fangcang and Renmin) hospitals. We conducted similar approach to develop control measures in various hospital functional units by taking all accountable factors. We showed that inhalation rates of individuals proved crucial for influencing the transmissibility of SARS-CoV-2, followed by air supply rate and exposure time. We suggest a minimum air change per hour (ACH) of 7 h⁻¹ would be at least appropriate with current room volume requirements in healthcare buildings when indoor population number is < 10 and exposure time is < 1 h with one infector and low activity levels being considered. However, higher ACH (> 16 h⁻¹) with optimal arranged-exposure time/people and high-efficiency air filters would be suggested if more infectors or higher activity levels are presented. Our models lay out a practical metric for evaluating the efficacy of control measures on COVID-19 infection in built environments. Our case studies further indicate that the Wells-Riley model provides a predictive and mechanistic basis for empirical COVID-19 impact reduction planning and gives a framework to treat highly transmissible but mechanically heterogeneous airborne SARS-CoV-2.

     

Mixture risk assessment due to ingestion of arsenic,copper, and zinc from milkfish farmed in contaminated coastal areas

Human health risks associated with the consumption of metal-contaminated fish over extended periods have become a concern particularly in Taiwan, where fish is consumed on a large scale. This study applied the interaction-based hazard index (HI) to assess the mixture health risks for fishers and non-fishers who consume the arsenic (As), copper (Cu), and zinc (Zn) contaminated milkfish from As-contaminated coastal areas in Taiwan, taking into account joint toxic actions and potential toxic interactions. We showed that the interactions of As–Zn and Cu–Zn were antagonistic, whereas As–Cu interaction was additive. We found that HI estimates without interactions considered were 1.3–1.6 times higher than interactive HIs. Probability distributions of HI estimates for non-fishers were less than 1, whereas all 97.5%-tile HI estimates for fishers were >1. Analytical results revealed that the level of inorganic As in milkfish was the main contributor to HIs, indicating a health risk posed to consumers of fish farmed in As-contaminated areas. However, we found that Zn supplementation could significantly decrease As-induced risk of hematological effect by activating a Zn-dependent enzyme. In order to improve the accuracy of health risk due to exposure to multiple metals, further toxicological data, regular environmental monitoring, dietary survey, and refinement approaches for interactive risk assessment are warranted.