Spatiotemporal impacts of human activities and socio-demographics during the COVID-19 outbreak in the US.

BACKGROUND: Understanding non-epidemiological factors is essential for the surveillance and prevention of infectious diseases, and the factors are likely to vary spatially and temporally as the disease progresses. However, the impacts of these influencing factors were primarily assumed to be stationary over time and space in the existing literature. The spatiotemporal impacts of mobility-related and social-demographic factors on disease dynamics remain to be explored. METHODS: Taking daily cases data during the coronavirus disease 2019 (COVID-19) outbreak in the US as a case study, we develop a mobility-augmented geographically and temporally weighted regression (M-GTWR) model to quantify the spatiotemporal impacts of social-demographic factors and human activities on the COVID-19 dynamics. Different from the base GTWR model, the proposed M-GTWR model incorporates a mobility-adjusted distance weight matrix where travel mobility is used in addition to the spatial adjacency to capture the correlations among local observations. RESULTS: The results reveal that the impacts of social-demographic and human activity variables present significant spatiotemporal heterogeneity. In particular, a 1% increase in population density may lead to 0.63% more daily cases, and a 1% increase in the mean commuting time may result in 0.22% increases in daily cases. Although increased human activities will, in general, intensify the disease outbreak, we report that the effects of grocery and pharmacy-related activities are insignificant in areas with high population density. And activities at the workplace and public transit are found to either increase or decrease the number of cases, depending on particular locations. CONCLUSIONS: Through a mobility-augmented spatiotemporal modeling approach, we could quantify the time and space varying impacts of non-epidemiological factors on COVID-19 cases. The results suggest that the effects of population density, socio-demographic attributes, and travel-related attributes will differ significantly depending on the time of the pandemic and the underlying location. Moreover, policy restrictions on human contact are not universally effective in preventing the spread of diseases.

Preparation and Photocatalytic Properties of a Bagasse Cellulose-Supported Nano-TiO2 Photocatalytic-Coupled Microbial Carrier.

Intimate coupling of photocatalysis and biodegradation (ICPB) has shown promise in removing unwanted organic compounds from water. In this study, bagasse cellulose titanium dioxide composite carrier (SBC-TiO2) was prepared by low-temperature foaming methods. The optimum preparation conditions, material characterization and photocatalytic performance of the composite carrier were then explored. By conducting a single factor test, we found that bagasse cellulose with a mass fraction of 4%, a polyvinyl alcohol solution (PVA) with a mass fraction of 5% and 20 g of a pore-forming agent were optimum conditions for the composite carrier. Under these conditions, good wet density, porosity, water absorption and retention could be realized. Scanning electron microscopy (SEM) results showed that the composite carrier exhibited good biologic adhesion. X-ray spectroscopy (EDS) results confirmed the successful incorporation of nano-TiO2 dioxide into the composite carrier. When the mass concentration of methylene blue (MB) was 10 mg L-1 at 200 mL, 2 g of the composite carrier was added and the initial pH value of the reaction was maintained at 6, the catalytic effect was best under these conditions and the degradation rate reached 78.91% after 6 h. The method of preparing the composite carrier can aid in the degradation of hard-to-degrade organic compounds via ICPB. These results provide a solid platform for technical research and development in the field of wastewater treatment.