Search

Aircraft cabins have high-performance ventilation systems, yet typically hold large numbers of people in close proximity for long periods. The current study estimated airborne virus exposure and infection reductions for vacant middle seats and masking in aircraft. Tracer particle data reported by U.S. Transportation Command (TRANSCOM) and CFD simulations reported by Boeing were used, along with NIOSH data, to build nonlinear regression models with particle exposure and distance from particle source as variables. These models that estimate exposure at given distances from the viral source were applied to evaluate exposure reductions when middle seats are vacant compared to full occupancy. Reductions averaged 54% for the seat row where an infectious passenger is located and 36% for a 24-row cabin containing one infectious passenger, with middle seats vacant. Analysis of the TRANSCOM data showed that universal masking (surgical masks) reduced exposures by 62% and showed masking and physical distancing provide further reductions when practiced together. For a notional scenario involving 10 infectious passengers, compared with no intervention, masking, distancing, and both would prevent 6.2, 3.8 and 7.6 secondary infections, respectively, using the Wells-Riley equation. These results suggest distancing and masking reduce SARS CoV-2 exposure risk when an infectious passenger is present.

Purpose Our aim was to assess the different voice prostheses (VPs) to identify the most efficient, safest, patient-tailored, longest lifetime, and inexpensive VPs and assess the different factors affecting their quality. Method In September 2017, 15 databases were searched to include all randomized controlled trials. A new search was done in May 2019 to include all other study design articles, which include all the new-era VPs subtypes. Network meta-analysis (NMA) was applied to all 27 outcomes, besides NMA overall and partial order setting was done by using Hasse scatter plots. p values were used in NMA, where the best VPs are approaching one and the least approaches zero. Meta-analysis was done for the rest of the outcomes. Results Two hundred one articles were eligible for inclusion in our study ( N = 11,918). Provox-2 was significantly the most efficient and safest device concerning the most patient preference (odds ratio [ OR ] = 33.88 [0.65, 1762.24]; p = .92), the least dislodgement (risk ratio [RR] = 0.27 [0.13, 0.57]; p = .79), the least airflow resistance (RR = 0.42 [0.08, 2.11]; p = .84), the least granulation formation (RR = 0.73 [0.02, 26.32]; p = .60), and the least VPs' inaccurate size (RR = 0.77 (0.23, 2.61); p = .66). Heat and moisture exchanger addition showed a significant increase in maximum phonation time and breathing experience, with p values (1 and .59), respectively. While heat and moisture exchanger addition showed a significant decline in stoma cleaning frequency, coughing frequency, forced expectoration, sputum production, sleeping problems, and loosening of adhesive, with p values (.99, .72, .69, .96, 1, and 0.96), respectively, Groningen low resistance and Nijdam were considered the worst devices with both overall mean p value of .44. Conclusions Provox-2 is considered the best choice as being the most preferable for patients, with the least airflow resistance, dislodgment, granulation formation, and prosthesis inaccurate size. Groningen low resistance and Nijdam were considered the worst devices according to our analysis. Supplemental Material https://doi.org/10.23641/asha.14802903

Purpose: Our aim was to assess the different voice prostheses (VPs) to identify the most efficient, safest, patient-tailored, longest lifetime, and inexpensive VPs and assess the different factors affecting their quality.Method: In September 2017, 15 databases were searched to include all randomized controlled trials. A new search was done in May 2019 to include all other study design articles, which include all the new-era VPs subtypes. Network meta-analysis (NMA) was applied to all 27 outcomes, besides NMA overall and partial order setting was done by using Hasse scatter plots. p values were used in NMA, where the best VPs are approaching one and the least approaches zero. Meta-analysis was done for the rest of the outcomes.Results: Two hundred one articles were eligible for inclusion in our study (N = 11,918). Provox-2 was significantly the most efficient and safest device concerning the most patient preference (odds ratio [OR] = 33.88 [0.65, 1762.24]; p = .92), the least dislodgement (risk ratio [RR] = 0.27 [0.13, 0.57]; p = .79), the least airflow resistance (RR = 0.42 [0.08, 2.11]; p = .84), the least granulation formation (RR = 0.73 [0.02, 26.32]; p = .60), and the least VPs’ inaccurate size (RR = 0.77 (0.23, 2.61); p = .66). Heat and moisture exchanger addition showed a significant increase in maximum phonation time and breathing experience, with p values (1 and .59), respectively. While heat and moisture exchanger addition showed a significant decline in stoma cleaning frequency, coughing frequency, forced expectoration, sputum production, sleeping problems, and loosening of adhesive, with p values (.99, .72, .69, .96, 1, and .96), respectively, Groningen low resistance and Nijdam were considered the worst devices with both overall mean p value of .44.Conclusions: Provox-2 is considered the best choice as being the most preferable for patients, with the least airflow resistance, dislodgment, granulation formation, and prosthesis inaccurate size. Groningen low resistance and Nijdam were considered the worst devices according to our analysis.Supplemental FiguresS1. Risk of bias assessment summary.S2. Risk of bias assessment graph of included randomized controlled trials.S3. Network meta-analysis for Replacements frequency of each device.S4. Network meta-analysis for Duration lifetime of each device.S5. Network meta-analysis for Air flow resistance of each device.S6. Network meta-analysis for Maximum phonation time of each device.S7. Network meta-analysis for Leakage rate of each device.S8. Network meta-analysis for Speech rate of each device. S9. Network meta-analysis for Patient device preference of each device. S10. Network meta-analysis for Stoma cleaning of each device. S11. Network meta-analysis for Breathing problems of each device. S12. Network meta-analysis for Coughing Frequency of each device. S13. Network meta-analysis for Forced expectorations of each device. S14. Network meta-analysis for Sputum production of each device. S15. Network meta-analysis for Sleeping problems of each device. S16. Network meta-analysis for Loosening of adhesive of each device. S17. Network meta-analysis for Increase phonatory effort of each device.S18. Network meta-analysis for Voice speech quality of each device. S19. Network meta-analysis for Fundamental Frequency of each device. S20. Network meta-analysis for Voice Loudness of each device.S21. Network meta-analysis for Speech Intelligibility of each device.S22. Network meta-analysis for Stoma stenosis of each device.S23. Network meta-analysis for Dislodgement of each device.S24. Network meta-analysis for Fistula problems of each device.S25. Network meta-analysis for Granulation of each device.S26. Network meta-analysis for Breathing Experience of each device.S27. Network meta-analysis for Prosthesis inaccurate size of each device.S28. Network meta-analysis for Prosthesis deterioration of each device.S29. Network meta-analysis for Follow-up survival rate of each device. S30A. Meta-analysis for Aspiration pneumonia rate of each device. S30B. Meta-analysis for Fungal colonization rate of each device. S31A. Meta-analysis for Experience with speaking rate of each device. S31B. Meta-analysis for Skin irritation rate of each device. Supplemental TablesS1. PRISMA 2009 Checklist.S2. Detailed search strategy for each database search.S3. Detailed definitions of each outcome in the study.S4. All equations used in data extraction.S5. Baseline characteristics of the patients in the included studies. Tawfik, G. M., Makram, O. M., Zayan, A. H., Ghozy, S., Eid, P. S., Mahmoud, M. H., Abdelaal, A., Abdelghany, S. M., Sayed, A. M., Sang, T. K., Kassem, M., Ho, Q. L. M., Eltanany, H. H., Ali, A. F., Sweiny, O. G., Elsherbiny, K. E., Shafik, A. G., Hirayama, K., & Huy, N. T. (2021). Voice rehabilitation by voice prostheses after total laryngectomy: A systematic review and network meta-analysis for 11,918 patients. Journal of Speech, Language, and Hearing Research. Advance online publication. https://doi.org/10.1044/2021_JSLHR-20-00597

Introduction: Malaria is an endemic disease especially in tropical areas transmitted by Anopheles species through their bites. Therefore, bed nets are considered one of the best methods for protection against their bites. However, many regions have limited access to bed nets and limited knowledge about their importance. Objectives: The objectives were to estimate rate of bed net possession and usage during a period of 10 years. The secondary objectives aimed to calculate prevalence of specific types of bed nets. Methods: We performed electronic search on 12 databases, and 106 studies was included obeying the criteria. Results: The studies eligible for our meta-analysis were 106. Most of the study participants were from Africa while the rest were from Asia and a few from southern America. The overall ownership rate of bed net households among countries was (72.1%, 95% CI: 62.9-79.7). An overall ownership rate in all countries of (event rate=52.5%, 95% CI: 37-67.4). The overall usage rate of bed net households among countries was (event rate=41.2%, 95% CI: 25.1-59.3) while bed net usage for individuals was (event rate= 41.2%, 95% CI: 25.1-59.3). Conclusion: This study suggests that the bed net ownership and usage rate among different countries are less satisfactory, hence not maximizing the potential benefit of the bed net. There is a crucial need to increase the awareness towards the bed net usage across the endemic areas and implement programs for free distribution of bed nets. Funding Statement: None. Declaration of Interests: None of the authors has any conflicts of interest to declare.

The dispersion characteristics of airborne pathogens were investigated in a Boeing 767 mockup cabin containing 11 rows with 7 seats per row, using two tracer gas source methods: continuous injection at low velocity and a coughing manikin. Both the injection source and the coughing manikin were located on the same seat in the sixth row. The injection source utilized CO2 gas at an injection rate of 5.0 liters per minute mixed with helium at a rate of 3.07 liters per minute to neutralize buoyancy. The manikin coughed approximately once every 75 seconds, with a volume of 4.2 liters of CO2 per cough. To ensure sufficient data were collected at each sampling location, each coughing manikin test was run for 6 coughs and each injection source test for 30 minutes of continuous injection. In both test methods, the tracer gas concentration was measured using CO2 gas analyzers at seated passenger breathing height of 1.2 m and radially up to 3.35 m away from the gas injection location, representing approximately four rows of a standard B767 aircraft. The collected data obtained from each tracer method was then normalized to provide a suitable comparison basis that is independent of tracer gas introduction flowrate. The results showed that both tracer source methods gave similar dispersion trends in diagonal and lateral directions away from the injection location. However, the tracer gas concentration was higher along the longitudinal direction in the coughing manikin tests due to the cough momentum. The results of this work will help researchers analyze different experimental and numerical approaches used to determine contaminant dispersion in various environments and will provide a better understanding of the associated transport phenomena.

With more than two billion passengers annually, in-flight transmission of infectious diseases is a major global health concern. It is widely believed that principal transmission risk associated with air travel for most respiratory infectious diseases is limited to within two rows of an infectious passenger. However, several passengers became infected despite sitting several rows away from the contagious passenger. This work thoroughly investigated the potential for disease spread inside airplane cabins using tracer gas to quantify airborne dispersion. Measurements were conducted in a full-scale, 11-row mock-up of a wide-body aircraft cabin. Heated mannequins to simulate passengers’ thermal load were placed on the cabin seats. Tracer gas was injected at the breathing level at four different hypothetical contagious passenger locations. The tracer gas concentration was measured radially up to 3.35 m away from the injection location representing four rows of a standard aircraft. A four-port sampling tree was used to collect samples at the breathing level at four different radial locations simultaneously. Each port was sampled for 30 minutes. A total of 42 tests were conducted in matching pairs to alleviate potential statistical or measurements bias. The results showed that the airflow pattern inside the mock-up airplane cabin plays a major role in determining tracer gas concentration meaning that the concentration at the same radial distance in different directions are not necessarily the same. Also, due to the air distribution pattern and cabin walls, concentrations at some seats may be higher than the source seat.

e18031Background: Prognosis of total laryngectomy following laryngeal tumors mostly SCC, reaches a five-year survival rate of 65-75%, making it treatment of choice. Total laryngectomy is accompanie...