Estimated number of N95 respirators needed for healthcare workers in acute-care hospitals during the coronavirus disease 2019 (COVID-19) pandemic

Abstract

Objective: Due to shortages of N95 respirators during the COVID-19 pandemic, it is necessary to estimate the number of N95s required for healthcare workers (HCW) to inform manufacturing targets and resource allocation. Methods: We developed a model to determine the number of N95 respirators needed for HCWs both in a single acute care hospital and the United States. Results: For an acute care hospital with 400 all-cause monthly admissions, the number of N95 respirators needed to manage COVID-19 patients admitted during a month ranges from 113 (95% IPR: 50-229) if 0.5% of admissions are COVID-19 patients to 22,101 (95% IPR: 5,904-25,881) if 100% of admissions are COVID-19 patients (assuming single use per respirator, and 10 encounters between HCWs and each COVID-19 patient per day). The number of N95s needed decreases (22 [95% IPR: 10-43]-4,445 [95% IPR: 1,975-8,684]) if each N95 is used for five patient encounters. Varying monthly all-cause admissions to 2,000 requires 6,645-13,404 respirators with a 60% COVID-19 admission prevalence, 10 HCW-patient encounters, and reusing N95s 5-10 times. Nationally, the number of N95 respirators needed over the course of the pandemic ranges from 86 million (95% IPR: 37.1-200.6 million) to 1.6 billion (95% IPR: 0.7-3.6 billion) as 5-90% of the population is exposed (single-use), and 17.4 million (95% IPR: 7.3-41 million) to 312.3 million (95% IPR: 131.5-737.3 million) using each respirator for five encounters. Conclusions: Our study quantifies the number of N95 respirators needed for a given acute care hospital and nationally during the COVID-19 pandemic under varying conditions.

Maintaining face mask use before and after achieving different COVID-19 vaccination coverage levels: a modelling study

“…Each person who is symptomatic in turn travels through a probability tree of different possible sequential age-specific COVID-19 clinical outcomes ( appendix p 1 ). 12 , 13 , 14 , 15 , 16 , 17 The probabilities along with their distributions for each of the branches in the tree are provided here ( appendix pp 4–6 ). Although the initial model structure attempted to account for the less heterogenous mixing that has been occurring during the pandemic because of COVID-19 precautions, additional iterations of the model explored the effects of further stratifying the population by age (an example of a model stratified by children and adults is shown on appendix p 2 ) and giving different age groups different mixing patterns with each other following previous studies.…”

The potential epidemiologic, clinical, and economic value of a universal coronavirus vaccine: a modelling study

“…We represent a pan-coronavirus vaccine that is already stockpiled and available at the beginning of the epidemic and provides partial protection against the circulating coronaviruses. As previously described, 12 , 13 , 14 , 15 , 16 , 17 , 18 receiving a vaccine decreases the risk of an individual getting infected by 1 minus the pan-coronavirus vaccine efficacy to prevent infection. Once infected, a vaccinated individual has a lower probability of developing severe outcomes (1-vaccine efficacy to prevent severe disease).…”

“…We adapted our previously described SARS-CoV-2 computational model 12 , 13 , 14 , 15 , 16 , 17 , 18 (developed in Microsoft Excel with the Crystal Ball add-in) to represent the spread of a new virus strain from the SARBECO (SARS beta coronavirus) family in the U.S. The population is divided into three age groups: children (≤17 years old), adults (18–64 years old), and older adults (≥65 years old), following the 2021 U.S. Census.…”

“…1 B) that has been described in previous publications. 12 , 13 , 14 , 15 , 16 , 17 , 18 As each individual develops different clinical manifestations of the infection, this individual accrues the corresponding health effects, productivity losses, and direct medical costs. These then contributed to the calculation of cost-benefit and cost-effectiveness of pan-coronavirus vaccination from different perspectives such as that of the third-party payer (direct medical costs such as vaccination and hospitalisation) and societal (direct medical costs plus productivity losses) perspectives.…”

Cost-effectiveness of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) testing and isolation strategies in nursing homes

“…We developed an ABM in Python software representing a typical nursing home with 100 residents, its staff, their interactions with each other, SARS-CoV-2 spread, potential health and economic outcomes, [9][10][11][12][13][14][15] and testing. The nursing home model consists of 50 occupied double rooms, each in a housing pod, representing a physical location of 10 rooms.…”