TY - JOUR
T1 - Method for the Analysis of Health Personnel Availability in a Pandemic Crisis Scenario through Monte Carlo Simulation
AU - Pando-Ezcurra, Tamara
AU - Auccahuasi, Wilver
AU - Saenz Arenas, Esther Rosa
AU - Rosario Pacahuala, Emilio Augusto
AU - González Ponce de León, Erica Rojana
AU - Olaya Cotera, Sandro
AU - Flores Castañeda, Rosalynn Ornella
AU - Herrera, Lucas
N1 - Publisher Copyright:
© 2022 by the authors.
PY - 2022/8
Y1 - 2022/8
N2 - During pandemic times, difficulties and problems related to the health sector are evident as the number of patients coming to health centers is higher compared to normal situations. This increase in the number of patients is typical of the pandemic, due to the high level of contagion in the population. Health personnel have a higher risk of infection, due to their sharing the work of caring for positive patients, so the infection rate is much higher. Hence, it remains necessary to understand the behavior of infection of health personnel, in order to be prepared to deal with the care of patients. Accordingly, in this research, we present a method to estimate different scenarios of infection and assess the probability of occurrence, so we can estimate the infection rate of health personnel. We present a simulation of 21 possible scenarios with 100 workers and a minimum of 80% needed to guarantee patient care. The results show that it is more likely that a 50% contagion scenario will occur, with an acceptable probability of 20%.
AB - During pandemic times, difficulties and problems related to the health sector are evident as the number of patients coming to health centers is higher compared to normal situations. This increase in the number of patients is typical of the pandemic, due to the high level of contagion in the population. Health personnel have a higher risk of infection, due to their sharing the work of caring for positive patients, so the infection rate is much higher. Hence, it remains necessary to understand the behavior of infection of health personnel, in order to be prepared to deal with the care of patients. Accordingly, in this research, we present a method to estimate different scenarios of infection and assess the probability of occurrence, so we can estimate the infection rate of health personnel. We present a simulation of 21 possible scenarios with 100 workers and a minimum of 80% needed to guarantee patient care. The results show that it is more likely that a 50% contagion scenario will occur, with an acceptable probability of 20%.
KW - inputs
KW - model
KW - probability
KW - risk
KW - simulation
UR - http://www.scopus.com/inward/record.url?scp=85136581743&partnerID=8YFLogxK
U2 - 10.3390/app12168299
DO - 10.3390/app12168299
M3 - Artículo
AN - SCOPUS:85136581743
SN - 2076-3417
VL - 12
JO - Applied Sciences (Switzerland)
JF - Applied Sciences (Switzerland)
IS - 16
M1 - 8299
ER -