Using visible light to activate antiviral and antimicrobial properties of TiO2 nanoparticles in paints and coatings: focus on new developments for frequent-touch surfaces in hospitals.

The COVID-19 pandemic refocused scientists the world over to produce technologies that will be able to prevent the spread of such diseases in the future. One area that deservedly receives much attention is the disinfection of health facilities like hospitals, public areas like bathrooms and train stations, and cleaning areas in the food industry. Microorganisms and viruses can attach to and survive on surfaces for a long time in most cases, increasing the risk for infection. One of the most attractive disinfection methods is paints and coatings containing nanoparticles that act as photocatalysts. Of these, titanium dioxide is appealing due to its low cost and photoreactivity. However, on its own, it can only be activated under high-energy UV light due to the high band gap and fast recombination of photogenerated species. The ideal material or coating should be activated under artificial light conditions to impact indoor areas, especially considering wall paints or frequent-touch areas like door handles and elevator buttons. By introducing dopants to TiO2 NPs, the bandgap can be lowered to a state of visible-light photocatalysis occurring. Naturally, many researchers are exploring this property now. This review article highlights the most recent advancements and research on visible-light activation of TiO2-doped NPs in coatings and paints. The progress in fighting air pollution and personal protective equipment is also briefly discussed. Graphical Abstract: Indoor visible-light photocatalytic activation of reactive oxygen species (ROS) over TiO2 nanoparticles in paint to kill bacteria and coat frequently touched surfaces in the medical and food industries.

Using visible light to activate antiviral and antimicrobial properties of TiO2 nanoparticles in paints and coatings: focus on new developments for frequent-touch surfaces in hospitals

The COVID-19 pandemic refocused scientists the world over to produce technologies that will be able to prevent the spread of such diseases in the future. One area that deservedly receives much attention is the disinfection of health facilities like hospitals, public areas like bathrooms and train stations, and cleaning areas in the food industry. Microorganisms and viruses can attach to and survive on surfaces for a long time in most cases, increasing the risk for infection. One of the most attractive disinfection methods is paints and coatings containing nanoparticles that act as photocatalysts. Of these, titanium dioxide is appealing due to its low cost and photoreactivity. However, on its own, it can only be activated under high-energy UV light due to the high band gap and fast recombination of photogenerated species. The ideal material or coating should be activated under artificial light conditions to impact indoor areas, especially considering wall paints or frequent-touch areas like door handles and elevator buttons. By introducing dopants to TiO2 NPs, the bandgap can be lowered to a state of visible-light photocatalysis occurring. Naturally, many researchers are exploring this property now. This review article highlights the most recent advancements and research on visible-light activation of TiO2-doped NPs in coatings and paints. The progress in fighting air pollution and personal protective equipment is also briefly discussed. Graphical Indoor visible-light photocatalytic activation of reactive oxygen species (ROS) over TiO2 nanoparticles in paint to kill bacteria and coat frequently touched surfaces in the medical and food industries.

Short- to medium-run forecasting of mobility with dynamic linear models

BACKGROUND Long-term projections of mobility are key inputs to sub-national population projections. These long-term projections are based on extrapolations of long-term trends. In cases of strong, potentially temporal, fluctuations it is informative to analyse the short-to medium -term dynamics of mobility, using data of monthly frequency. OBJECTIVE We develop two univariate models to forecast short-to medium-term mobility in the Netherlands. We apply a recent turning point in the time series of mobility to demonstrate how short-to medium-term forecasts can provide early warning signals about possible changes in the annual trend. METHODS The models we apply are Dynamic Linear Models (DLMs) which belong to the state space family of models. The two models developed in the paper incorporate trend, sea-sonal and autoregressive components but differ in the representation of the long-term trend. Posterior sampling allows for calculation of consistent prediction intervals for both monthly and annual data. CONCLUSION Forecast accuracy is evaluated using time series cross-validation. Point forecast errors and calibration of prediction intervals are compared to those of several other popular univariate forecasting models. One of our DLM models is more accurate than the models included as comparison. CONTRIBUTION The paper shows how short-to medium-term forecasts of mobility can be used to inform long-term projections based on annual data. This will be a challenging task for statistical offices generating post-COVID-19 demographic projections.

Early hydroxychloroquine but not chloroquine use reduces ICU admission in COVID-19 patients.

BACKGROUND: The global push for the use of hydroxychloroquine (HCQ) and chloroquine (CQ) against COVID-19 has resulted in an ongoing discussion about the effectivity and toxicity of these drugs. Recent studies report no effect of (H)CQ on 28-day mortality. We investigated the effect of HCQ and CQ in hospitalized patients on the non-ICU COVID-ward. METHODS: A nationwide, observational cohort study was performed in The Netherlands. Hospitals were given the opportunity to decide independently on the use of three different COVID-19 treatment strategies: HCQ, CQ, or no treatment. We compared the outcomes between these groups. The primary outcomes were 1) death on the COVID-19 ward, and 2) transfer to the intensive care unit (ICU). RESULTS: The analysis included 1064 patients from 14 hospitals: 566 patients received treatment with either HCQ (n = 189) or CQ (n = 377), and 498 patients received no treatment. In a multivariate propensity-matched weighted competing regression analysis, there was no significant effect of (H)CQ on mortality on the COVID ward. However, HCQ was associated with a significantly decreased risk of transfer to the ICU (hazard ratio (HR) = 0.47, 95% CI = 0.27-0.82, p = 0.008) when compared with controls. This effect was not found in the CQ group (HR = 0.80, 95% CI = 0.55-1.15, p = 0.207), and remained significant after competing risk analysis. CONCLUSION: The results of this observational study demonstrate a lack of effect of (H)CQ on non-ICU mortality. However, we show that the use of HCQ - but not CQ - is associated with a 53% reduction in risk of transfer of COVID-19 patients from the regular ward to the ICU. Recent prospective studies have reported on 28-day, all-cause mortality only; therefore, additional prospective data on the early effects of HCQ in preventing transfer to the ICU are still needed.