A five-compartment model of age-specific transmissibility of SARS-CoV-2.

BACKGROUND: The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, also called 2019-nCoV) causes different morbidity risks to individuals in different age groups. This study attempts to quantify the age-specific transmissibility using a mathematical model. METHODS: An epidemiological model with five compartments (susceptible-exposed-symptomatic-asymptomatic-recovered/removed [SEIAR]) was developed based on observed transmission features. Coronavirus disease 2019 (COVID-19) cases were divided into four age groups: group 1, those ≤ 14 years old; group 2, those 15 to 44 years old; group 3, those 45 to 64 years old; and group 4, those ≥ 65 years old. The model was initially based on cases (including imported cases and secondary cases) collected in Hunan Province from January 5 to February 19, 2020. Another dataset, from Jilin Province, was used to test the model. RESULTS: The age-specific SEIAR model fitted the data well in each age group (P < 0.001). In Hunan Province, the highest transmissibility was from age group 4 to 3 (median: ß43 = 7.71 × 10- 9; SAR43 = 3.86 × 10- 8), followed by group 3 to 4 (median: ß34 = 3.07 × 10- 9; SAR34 = 1.53 × 10- 8), group 2 to 2 (median: ß22 = 1.24 × 10- 9; SAR22 = 6.21 × 10- 9), and group 3 to 1 (median: ß31 = 4.10 × 10- 10; SAR31 = 2.08 × 10- 9). The lowest transmissibility was from age group 3 to 3 (median: ß33 = 1.64 × 10- 19; SAR33 = 8.19 × 10- 19), followed by group 4 to 4 (median: ß44 = 3.66 × 10- 17; SAR44 = 1.83 × 10- 16), group 3 to 2 (median: ß32 = 1.21 × 10- 16; SAR32 = 6.06 × 10- 16), and group 1 to 4 (median: ß14 = 7.20 × 10- 14; SAR14 = 3.60 × 10- 13). In Jilin Province, the highest transmissibility occurred from age group 4 to 4 (median: ß43 = 4.27 × 10- 8; SAR43 = 2.13 × 10- 7), followed by group 3 to 4 (median: ß34 = 1.81 × 10- 8; SAR34 = 9.03 × 10- 8). CONCLUSIONS: SARS-CoV-2 exhibits high transmissibility between middle-aged (45 to 64 years old) and elderly (≥ 65 years old) people. Children (≤ 14 years old) have very low susceptibility to COVID-19. This study will improve our understanding of the transmission feature of SARS-CoV-2 in different age groups and suggest the most prevention measures should be applied to middle-aged and elderly people.

Effects of Carbon Source on TiC Particles' Distribution, Tensile, and Abrasive Wear Properties of In Situ TiC/Al-Cu Nanocomposites Prepared in the Al-Ti-C System.

The in situ TiC/Al-Cu nanocomposites were fabricated in the Al-Ti-C reaction systems with various carbon sources by the combined method of combustion synthesis, hot pressing, and hot extrusion. The carbon sources used in this paper were the pure C black, hybrid carbon source (50 wt.% C black + 50 wt.% CNTs) and pure CNTs. The average sizes of nano-TiC particles range from 67 nm to 239 nm. The TiC/Al-Cu nanocomposites fabricated by the hybrid carbon source showed more homogenously distributed nano-TiC particles, higher tensile strength and hardness, and better abrasive wear resistance than those of the nanocomposites fabricated by pure C black and pure CNTs. As the nano-TiC particles content increased, the tensile strength, hardness, and the abrasive wear resistance of the nanocomposites increased. The 30 vol.% TiC/Al-Cu nanocomposite fabricated by the hybrid carbon source showed the highest yield strength (531 MPa), tensile strength (656 MPa), hardness (331.2 HV), and the best abrasive wear resistance.

The Dry Sliding Wear Properties of Nano-Sized TiCp/Al-Cu Composites at Elevated Temperatures.

Nano-sized ceramic particle reinforced aluminum composites exhibit excellent room-temperature mechanical properties. However, there is limited research on the dry sliding wear behavior of those composites at elevated temperatures, which should be one of the major concerns on elevated temperature applications. Here the Al-Cu composites reinforced with nano-sized TiCp were fabricated. The dry sliding wear behaviors of the nano-sized TiCp/Al-Cu composites at various temperatures (140-220 °C) and loads (10-40 N) with different TiCp contents were studied, and the results showed that the nanocomposites exhibited superior wear resistance. For instance, the relative wear resistance of the 0.5 wt.% nano-sized TiCp/Al-Cu composite was 83.5% higher than that of the Al-Cu matrix alloy at 180 °C under 20 N, and was also 16.5% higher than that of the 5 wt.% micro-sized TiCp/Al-Cu composite, attributed to the pronounced Orowan strengthening effect of nanoparticles. The wear rates of the nanocomposites were always lower than those of the Al-Cu matrix alloy under the same test condition, which increased with the increase in temperature and load and with the decrease in TiCp content.

[Epidemiological characteristics on the clustering nature of pandemic (H1N1) 2009 in China].

OBJECTIVE: To study the epidemiological characteristics on the clustering nature of pandemic (H1N1) 2009 in China. METHODS: Time and place distribution of pandemic (H1N1) 2009 on the nature of clustering through data from Public Health Emergency Management Information System were described. RESULTS: As of August 10, 2010, 2773 pandemic (H1N1) 2009 clusters, a total of 77 363 cases (including 20 deaths) were reported in the mainland of China. The most reported number of clusters was from schools and kindergartens with the total number of 2498 (accounted for 90.08% of the total number). Middle schools appeared the have the most clusters (1223, accounting for 48.96%). The number of clusters reported in the southern provinces (cities) accounted for 77.03% of the total, and was more than that in the northern provinces (cities). Two reported peaks in the southern provinces (cities) were in June and November, 2009, respectively. There was only one reported peak in the northern provinces in September, 2009. CONCLUSION: Time and place distribution characteristics on the clusters of pandemic (H1N1) 2009 were similar to the seasonal influenza, but the beginning of winter peak was much earlier and intensity of reporting was much higher on the clusters of pandemic (H1N1) 2009 than that of seasonal influenza.