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Effectiveness of neuraminidase inhibitors for preventing staff absenteeism during pandemic influenza.

ABSTRACT: We used a deterministic SEIR (susceptible-exposed-infectious-removed) meta-population model, together with scenario, sensitivity, and simulation analyses, to determine stockpiling strategies for neuraminidase inhibitors that would minimize absenteeism among healthcare workers. A pandemic with a basic reproductive number (R0) of 2.5 resulted in peak absenteeism of 10%. Treatment decreased peak absenteeism to 8%, while 8 weeks' prophylaxis reduced it to 2%. For pandemics with higher R0, peak absenteeism exceeded 20% occasionally and 6 weeks' prophylaxis reduced peak absenteeism by 75%. Insufficient duration of prophylaxis increased peak absenteeism compared with treatment only. Earlier pandemic detection and initiation of prophylaxis may render shorter prophylaxis durations ineffective. Eight weeks' prophylaxis substantially reduced peak absenteeism under a broad range of assumptions for severe pandemics (peak absenteeism > 10%). Small investments in treatment and prophylaxis, if adequate and timely, can reduce absenteeism among essential staff.

SUBMITTER: Lee VJ

PROVIDER: S-EPMC2725890 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Neuraminidase inhibitors (NAIs) effectively treat influenza. The clinical effectiveness of four NAIs (oseltamivir, zanamivir, laninamivir, and peramivir) was evaluated against influenza A/H1N1pdm09, A/H3N2, and B viruses. Additionally, fever duration in patients infected with oseltamivir-resistant influenza A/H1N1pdm09 with the H275Y mutation was evaluated. METHODS:Patients aged <20 years who visited outpatient clinics in Japan with influenza-like illnesses were enrolled during 4 influenza seasons from 2012/2013 to 2015/2016. After obtaining informed consent, patients who tested positive for influenza with rapid tests received one of the four NAIs. Patients recorded their body temperature daily for 8 days from the first visit. The influenza strain was identified using real-time polymerase chain reaction. Univariate and multivariable analyses were used to evaluate factors influencing fever duration. In children aged ?5 years treated with oseltamivir, fever duration in oseltamivir-resistant A/H1N1pdm09-infected patients was compared to that in oseltamivir-sensitive A/H1N1pdm09-infected patients. RESULTS:Of the 1,368 patients analyzed, 297 (21.7%), 683 (49.9%), and 388 (28.4%) were infected with influenza A/H1N1pdm09, A/H3N2, and B, respectively. In multivariable analysis factors associated with significantly prolonged fever duration included: treatment with laninamivir (hazard ratio [HR]: 0.78, p = 0.006, compared to oseltamivir), influenza B (HR: 0.58, p<0.001, compared to influenza A/H1N1pdm09), and a higher body temperature at the clinic visit (HR: 0.87 per degree Celsius, p<0.001). Increasing age was associated with a significantly shorter duration of fever (HR: 1.31 for 6-9 years old, p<0.001; and HR: 1.65 for 10-19 years old, p<0.001, respectively, compared to 0-5 years old). Following treatment with oseltamivir, fever duration was significantly longer for oseltamivir-resistant A/H1N1pdm09-infected patients (n = 5) than for oseltamivir-sensitive A/H1N1pdm09 infected patients (n = 111) (mean, 89 versus 40 hours, p<0.001). CONCLUSIONS:Our results revealed characteristic information on the effectiveness of the four NAIs and also on oseltamivir-resistant viruses that may affect patients' clinical care.

Project description:The fight against the emergence of mutant influenza strains has led to the screening of an increasing number of compounds for inhibitory activity against influenza neuraminidase. This study explores the chemical space of neuraminidase inhibitors (NAIs), which provides an opportunity to obtain further molecular insights regarding the underlying basis of their bioactivity. In particular, a large set of 347 and 175 NAIs against influenza A and B, respectively, was compiled from the literature. Molecular and quantum chemical descriptors were obtained from low-energy conformational structures geometrically optimized at the PM6 level. The bioactivities of NAIs were classified as active or inactive according to their half maximum inhibitory concentration (IC50) value in which IC50 < 1µM and ≥ 10µM were defined as active and inactive compounds, respectively. Interpretable decision rules were derived from a quantitative structure-activity relationship (QSAR) model established using a set of substructure descriptors via decision tree analysis. Univariate analysis, feature importance analysis from decision tree modeling and molecular scaffold analysis were performed on both data sets for discriminating important structural features amongst active and inactive NAIs. Good predictive performance was achieved as deduced from accuracy and Matthews correlation coefficient values in excess of 81% and 0.58, respectively, for both influenza A and B NAIs. Furthermore, molecular docking was employed to investigate the binding modes and their moiety preferences of active NAIs against both influenza A and B neuraminidases. Moreover, novel NAIs with robust binding fitness towards influenza A and B neuraminidase were generated via combinatorial library enumeration and their binding fitness was on par or better than FDA-approved drugs. The results from this study are anticipated to be beneficial for guiding the rational drug design of novel NAIs for treating influenza infections.

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Effectiveness of neuraminidase inhibitors for preventing staff absenteeism during pandemic influenza.

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