Negative airflow isolation bed provides an option for NIV ventilation during COVID -19 pandemic
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PROVIDER: S-EPMC7368648 | biostudies-literature | 2020 Jul
REPOSITORIES: biostudies-literature
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| S-EPMC7282792 | biostudies-literature
Project description:As COVID-19 spreads across the United States, people experiencing homelessness (PEH) are among the most vulnerable to the virus. To mitigate transmission, municipal governments are procuring isolation facilities for PEH to utilize following possible exposure to the virus. Here we describe the framework for anticipating isolation bed demand in PEH communities that we developed to support public health planning in Austin, Texas during March 2020. Using a mathematical model of COVID-19 transmission, we projected that, under no social distancing orders, a maximum of 299 (95% Confidence Interval: 223, 321) PEH may require isolation rooms in the same week. Based on these analyses, Austin Public Health finalized a lease agreement for 205 isolation rooms on March 27th 2020. As of October 7th 2020, a maximum of 130 rooms have been used on a single day, and a total of 602 PEH have used the facility. As a general rule of thumb, we expect the peak proportion of the PEH population that will require isolation to be roughly triple the projected peak daily incidence in the city. This framework can guide the provisioning of COVID-19 isolation and post-acute care facilities for high risk communities throughout the United States.
| S-EPMC8115830 | biostudies-literature
Project description:BackgroundIn chronic obstructive pulmonary disease, the prognosis for patients who have survived an episode of acute hypercapnic respiratory failure due to an exacerbation is poor. Despite being shown to improve survival and quality-of-life in stable patients with chronic hypercapnic respiratory failure, long-term noninvasive ventilation is controversial in unstable patients with frequent exacerbations, complicated by acute hypercapnic respiratory failure. In an uncontrolled group of patients with previous episodes of acute hypercapnic respiratory failure, treated with noninvasive ventilation, we have been able to reduce mortality and the number of repeat respiratory failure and readmissions by continuing the acute noninvasive ventilatory therapy as a long-term therapy.MethodsMulti-center open label randomized controlled trial of 150 patients having survived an admission with noninvasive ventilatory treatment of acute hypercapnic respiratory failure due chronic obstructive pulmonary disease. The included patients are randomized to usual care or to continuing the acute noninvasive ventilation as a long-term therapy, both with a one-year follow-up period. The primary endpoint is time to death or repeat acute hypercapnic respiratory failure; secondary endpoints are one-year mortality, number of readmissions and repeat acute hypercapnic respiratory failure, exacerbations, dyspnea, quality of life, sleep quality, lung function, and arterial gases.DiscussionThough previous studies of long-term noninvasive ventilation have shown conflicting results, we believe the treatment can reduce mortality and readmissions when applied in patients with previous need of acute ventilatory support, regardless of persistent hypercapnia.Trial registrationclinicaltrials.org: NCT01513655 16-Jan-2012.
| S-EPMC4751632 | biostudies-literature
Project description:BackgroundPrediction of the necessary capacity of beds by ward type (e.g. ICU) is essential for planning purposes during epidemics, such as the COVID- 19 pandemic. The COVID- 19 taskforce within the Ghent University hospital made use of ten-day forecasts on the required number of beds for COVID- 19 patients across different wards.MethodsThe planning tool combined a Poisson model for the number of newly admitted patients on each day with a multistate model for the transitions of admitted patients to the different wards, discharge or death. These models were used to simulate the required capacity of beds by ward type over the next 10 days, along with worst-case and best-case bounds.ResultsOverall, the models resulted in good predictions of the required number of beds across different hospital wards. Short-term predictions were especially accurate as these are less sensitive to sudden changes in number of beds on a given ward (e.g. due to referrals). Code snippets and details on the set-up are provided to guide the reader to apply the planning tool on one's own hospital data.ConclusionsWe were able to achieve a fast setup of a planning tool useful within the COVID- 19 pandemic, with a fair prediction on the needed capacity by ward type. This methodology can also be applied for other epidemics.
| S-EPMC8128685 | biostudies-literature
Project description:Background/methodsQualitative studies suggest that bed nets affect the thermal comfort of users. To understand and reduce this discomfort the effect of bed nets on temperature, humidity, and airflow was measured in rural homes in Asia and Africa, as well as in an experimental wind tunnel. Two investigators with architectural training selected 60 houses in The Gambia, Tanzania, Philippines, and Thailand. Data-loggers were used to measure indoor temperatures in hourly intervals over a 12 months period. In a subgroup of 20 houses airflow, temperature and humidity were measured at five-minute intervals for one night from 21.00 to 6.00 hrs inside and outside of bed nets using sensors and omni-directional thermo-anemometers. An investigator set up a bed net with a mesh size of 220 holes per inch 2 in each study household and slept under the bed net to simulate a realistic environment. The attenuation of airflow caused by bed nets of different mesh sizes was also measured in an experimental wind tunnel.ResultsThe highest indoor temperatures (49.0 C) were measured in The Gambia. During the hottest months of the year the mean temperature at night (9 pm) was between 33.1 C (The Gambia) and 26.2 C (Thailand). The bed net attenuated the airflow from a minimum of 27% (Philippines) to a maximum of 71% (The Gambia). Overall the bed nets reduced airflow compared to un-attenuated airflow from 9 to 4 cm sec-1 or 52% (p<0.001). In all sites, no statistically significant difference in temperature or humidity was detected between the inside and outside of the bed net. Wind tunnel experiments with 11 different mesh-sized bed nets showed an overall reduction in airflow of 64% (range 55 - 71%) compared to un-attenuated airflow. As expected, airflow decreased with increasing net mesh size. Nets with a mesh of 136 holes inch-2 reduced airflow by 55% (mean; range 51 - 73%). A denser net (200 holes inch-2) attenuated airflow by 59% (mean; range 56 - 74%).DiscussionDespite concerted efforts to increase the uptake of this intervention in many areas uptake remains poor. Bed nets reduce airflow, but have no influence on temperature and humidity. The discomfort associated with bed nets is likely to be most intolerable during the hottest and most humid period of the year, which frequently coincides with the peak of malaria vector densities and the force of pathogen transmission.ConclusionsThese observations suggest thermal discomfort is a factor limiting bed net use and open a range of architectural possibilities to overcome this limitation.
| S-EPMC3441282 | biostudies-literature
Project description:BackgroundThe outbreak of COVID-19 has been defined by the World Health Organization as a pandemic, and containment depends on traditional public health measures. However, the explosive growth of the number of infected cases in a short period of time has caused tremendous pressure on medical systems. Adequate isolation facilities are essential to control outbreaks, so this study aims to quickly estimate the demand and number of isolation beds.MethodsWe established a discrete simulation model for epidemiology. By adjusting or fitting necessary epidemic parameters, the effects of the following indicators on the development of the epidemic and the occupation of medical resources were explained: (1) incubation period, (2) response speed and detection capacity of the hospital, (3) disease healing time, and (4) population mobility. Finally, a method for predicting the number of isolation beds was summarized through multiple linear regression. This is a city level model that simulates the epidemic situation from the perspective of population mobility.ResultsThrough simulation, we show that the incubation period, response speed and detection capacity of the hospital, disease healing time, degree of population mobility, and infectivity of cured patients have different effects on the infectivity, scale, and duration of the epidemic. Among them, (1) incubation period, (2) response speed and detection capacity of the hospital, (3) disease healing time, and (4) population mobility have a significant impact on the demand and number of isolation beds (P <0.05), which agrees with the following regression equation: N = P × (-0.273 + 0.009I + 0.234M + 0.012T1 + 0.015T2) × (1 + V).
| S-EPMC8234972 | biostudies-literature
Project description: Not available
| S-BSST1076 | biostudies-other
Project description:COVID-19 pandemic sets the healthcare system to a shortage of ventilators. We aimed at assessing tidal volume (VT) delivery and air recirculation during expiration when one ventilator is divided into 2 test-lungs. The study was performed in a research laboratory in a medical ICU of a University hospital. An ICU (V500) and a lower-level ventilator (Elisée 350) were attached to two test-lungs (QuickLung) through a dedicated flow-splitter. A 50 mL/cmH2O Compliance (C) and 5 cmH2O/L/s Resistance (R) were set in both A and B test-lungs (A C50R5 / B C50R5, step1), A C50-R20 / B C20-R20 (step 2), A C20-R20 / B C10-R20 (step 3), and A C50-R20 / B C20-R5 (step 4). Each ventilator was set in volume and pressure control mode to deliver 800mL VT. We assessed VT from a pneumotachograph placed immediately before each lung, pendelluft air, and expiratory resistance (circuit and valve). Values are median (1st-3rd quartiles) and compared between ventilators by non-parametric tests. Between Elisée 350 and V500 in volume control VT in A/B test- lungs were 381/387 vs. 412/433 mL in step 1, 501/270 vs. 492/370 mL in step 2, 509/237 vs. 496/332 mL in step 3, and 496/281 vs. 480/329 mL in step 4. In pressure control the corresponding values were 373/336 vs. 430/414 mL, 416/185 vs. 322/234 mL, 193/108 vs. 176/ 92 mL and 422/201 vs. 481/329mL, respectively (P<0.001 between ventilators at each step for each volume). Pendelluft air volume ranged between 0.7 to 37.8 ml and negatively correlated with expiratory resistance in steps 2 and 3. The lower-level ventilator performed closely to the ICU ventilator. In the clinical setting, these findings suggest that, due to dependence of VT to C, pressure control should be preferred to maintain adequate VT at least in one patient when C and/or R changes abruptly and monitoring of VT should be done carefully. Increasing expiratory resistance should reduce pendelluft volume.
| S-EPMC7815120 | biostudies-literature
Project description: Not available
| S-EPMC7605199 | biostudies-literature
Project description: Not available
| S-EPMC8091344 | biostudies-literature