Comparative modelling of the destruction of a soft armour barrier using two- and threedimensional textile materials based on orthogonal fabrics

The article suggests an approach to virtual testing of textile materials for high-speed penetration. The comparison of two materials developed using different technologies – 3D orthogonal fabric and a package of plain weave fabric is carried out. For this purpose, such parameters of fabrics are selected so that the surface density is identical, the number of layers is the same, the linear density of the threads would be the same. The material of the threads is aramid fibre. In general, according to the assessment along the warp and weft, the lesion area for 3D orthogonal tissue is higher by up to 30 %. At the same time, 31.7 % more kinetic energy of the bullet was extinguished.

Prioritisation of colonoscopy services in colorectal cancer screening programmes to minimise impact of COVID-19 pandemic on predicted cancer burden: A comparative modelling study

Objectives Colorectal cancer (CRC) screening with a faecal immunochemical test (FIT) has been disrupted in many countries during the COVID-19 pandemic. Performing catch-up of missed screens while maintaining regular screening services requires additional colonoscopy capacity that may not be available. This study aimed to compare strategies that clear the screening backlog using limited colonoscopy resources. Methods A range of strategies were simulated using four country-specific CRC natural-history models: Adenoma and Serrated pathway to Colorectal CAncer (ASCCA) and MIcrosimulation SCreening ANalysis for CRC (MISCAN-Colon) (both in the Netherlands), Policy1-Bowel (Australia) and OncoSim (Canada). Strategies assumed a 3-month screening disruption with varying recovery period lengths (6, 12, and 24 months) and varying FIT thresholds for diagnostic colonoscopy. Increasing the FIT threshold reduces the number of referrals to diagnostic colonoscopy. Outcomes for each strategy were colonoscopy demand and excess CRC-related deaths due to the disruption. Results Performing catch-up using the regular FIT threshold in 6, 12 and 24 months could prevent most excess CRC-related deaths, but required 50%, 25% and 12.5% additional colonoscopy demand, respectively. Without exceeding usual colonoscopy demand, up to 60% of excess CRC-related deaths can be prevented by increasing the FIT threshold for 12 or 24 months. Large increases in FIT threshold could lead to additional deaths rather than preventing them. Conclusions Clearing the screening backlog in 24 months could avert most excess CRC-related deaths due to a 3-month disruption but would require a small increase in colonoscopy demand. Increasing the FIT threshold slightly over 24 months could ease the pressure on colonoscopy resources.

Projections of human papillomavirus (HPV) vaccination impact in Ethiopia, India, Nigeria and Pakistan: a comparative modelling study

IntroductionCervical cancer is the second most common cancer among women in Ethiopia, India, Nigeria and Pakistan. Our study objective was to assess similarities and differences in vaccine-impact projections through comparative modelling analysis by independently estimating the potential health impact of human papillomavirus (HPV) vaccination.MethodsUsing two widely published models (Harvard and Papillomavirus Rapid Interface for Modelling and Economics (PRIME)) to estimate HPV vaccination impact, we simulated a vaccination scenario of 90% annual coverage among 10 cohorts of 9-year-old girls from 2021 to 2030 in Ethiopia, India, Nigeria and Pakistan. We estimated potential health impact in terms of cervical cancer cases, deaths and disability-adjusted life years averted among vaccinated cohorts from the time of vaccination until 2100. We harmonised the two models by standardising input data to comparatively estimate HPV vaccination impact.ResultsPrior to harmonising model assumptions, the range between PRIME and Harvard models for number of cervical cancer cases averted by HPV vaccination was: 262 000 to 2 70 000 in Ethiopia; 1 640 000 to 1 970 000 in India; 330 000 to 3 36 000 in Nigeria and 111 000 to 1 33 000 in Pakistan. When harmonising model assumptions, alignment on HPV type distribution significantly narrowed differences in vaccine-impact estimates.ConclusionDespite model differences, the Harvard and PRIME models yielded similar vaccine-impact estimates. The main differences in estimates are due to variation in interpretation around data on cervical cancer attribution to HPV-16/18. As countries make progress towards WHO targets for cervical cancer elimination, continued explorations of underlying differences in model inputs, assumptions and results when examining cervical cancer prevention policy will be critical.

Projections of human papillomavirus (HPV) vaccination impact in Ethiopia, India, Nigeria, and Pakistan: a comparative modelling study

Background: Cervical cancer is the second most common cancer among women in Ethiopia, India, Nigeria, and Pakistan. However, of these four countries, only Ethiopia has introduced human papillomavirus (HPV) vaccination at the national level in 2018 and India in a few states in 2016. Our study objective was to estimate the potential health impact of HPV vaccination among ten cohorts of 9-year-old girls from 2021-2030 in Ethiopia, India, Nigeria, and Pakistan using two independent mathematical models, and assess similarities and differences in vaccine impact projections through comparative modelling analysis. Methods: Using two widely published models (Harvard and PRIME) to estimate HPV vaccination impact, we simulated a vaccination scenario of 90% annual coverage among 9-year-old girls from 2021-2030 in Ethiopia, India, Nigeria, and Pakistan. We estimated the potential health impact in terms of cervical cancer cases, deaths, and disability-adjusted life years (DALYs) averted among vaccinated cohorts from the time of vaccination until 2100. We also conducted a comparative modelling analysis to understand the differences in vaccine impact estimates generated by the two models. Results: Prior to harmonising model assumptions, the range between the PRIME model and the Harvard model for the potential health impact of HPV vaccination in terms of the number of cervical cancer cases averted among girls vaccinated 2021-2030 between the year of vaccination and 2100 was: 262,000 to 270,000 in Ethiopia; 1,640,000 to 1,970,000 in India; 330,000 to 336,000 in Nigeria; and 111,000 to 133,000 in Pakistan. When harmonising model assumptions, alignment on HPV type distribution significantly narrowed the differences in vaccine impact estimates. Conclusions: The main difference in estimates for cases, deaths, and DALYs averted by vaccination between the models are due to variation in interpretation around data on cervical cancer attribution to HPV-16/18; differences in estimates for DALYs averted are additionally due to differences in age-specific remaining life expectancy over time between the two models. As countries make progress towards the World Health Organization targets for cervical cancer elimination, continued explorations of underlying differences in model inputs, assumptions, and results when examining cervical cancer prevention policy will be critical.