Optimizing influenza vaccine policies for controlling 2009-like pandemics and regular outbreaks

Chen, Sheng-I; Wu, Chia Yuan; Wu, Yu; Hsieh, Min Wei

doi:10.7717/peerj.6340

Cited by 5 publications

(4 citation statements)

References 27 publications

(26 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1A ; Table 1 ). This class of SEIR models has been used extensively to model influenza ( Andreasen & Frommelt, 2005 ; Coburn, Wagner & Blower, 2009 ; Modchang et al, 2012 ; Chen et al, 2019 ) and COVID-19 ( Wang et al, 2020 ; He, Peng & Sun, 2020 ), and we extended the SEIR framework in order to account for isolation policies ( Box 1 ).…”

Section: Methodsmentioning

confidence: 99%

Effectiveness of isolation policies in schools: evidence from a mathematical model of influenza and COVID-19

Burns

Gutfraind

2021

PeerJ

View full text Add to dashboard Cite

Background Non-pharmaceutical interventions such as social distancing, school closures and travel restrictions are often implemented to control outbreaks of infectious diseases. For influenza in schools, the Center of Disease Control (CDC) recommends that febrile students remain isolated at home until they have been fever-free for at least one day and a related policy is recommended for SARS-CoV-2 (COVID-19). Other authors proposed using a school week of four or fewer days of in-person instruction for all students to reduce transmission. However, there is limited evidence supporting the effectiveness of these interventions. Methods We introduced a mathematical model of school outbreaks that considers both intervention methods. Our model accounts for the school structure and schedule, as well as the time-progression of fever symptoms and viral shedding. The model was validated on outbreaks of seasonal and pandemic influenza and COVID-19 in schools. It was then used to estimate the outbreak curves and the proportion of the population infected (attack rate) under the proposed interventions. Results For influenza, the CDC-recommended one day of post-fever isolation can reduce the attack rate by a median (interquartile range) of 29 (13–59)%. With 2 days of post-fever isolation the attack rate could be reduced by 70 (55–85)%. Alternatively, shortening the school week to 4 and 3 days reduces the attack rate by 73 (64–88)% and 93 (91–97)%, respectively. For COVID-19, application of post-fever isolation policy was found to be less effective and reduced the attack rate by 10 (5–17)% for a 2-day isolation policy and by 14 (5–26)% for 14 days. A 4-day school week would reduce the median attack rate in a COVID-19 outbreak by 57 (52–64)%, while a 3-day school week would reduce it by 81 (79–83)%. In both infections, shortening the school week significantly reduced the duration of outbreaks. Conclusions Shortening the school week could be an important tool for controlling influenza and COVID-19 in schools and similar settings. Additionally, the CDC-recommended post-fever isolation policy for influenza could be enhanced by requiring two days of isolation instead of one.

show abstract

Section: Methodsmentioning

confidence: 99%

Effectiveness of isolation policies in schools: evidence from a mathematical model of influenza and COVID-19

Burns

Gutfraind

2021

PeerJ

View full text Add to dashboard Cite

show abstract

“…We use a deterministic compartmental dynamical model known as the Susceptible, Exposed, Infectious, Recovered (SEIR) model that tracks the number of individuals of various cohorts and immunological states for each day during an outbreak (Figure 1). This class of SEIR models has been used extensively to model influenza 14,20,33,34 and COVID-19 35,36 , and we extended the SEIR framework in order to account for isolation policies.…”

Section: Methodsmentioning

confidence: 99%

Effectiveness of Isolation Policies in Schools: Evidence from a Mathematical Model of Influenza and COVID-19

Burns

Gutfraind

2020

Preprint

View full text Add to dashboard Cite

Background: Controlling the transmission of respiratory infections such as influenza andCOVID-19 is a critical public health priority. Non-pharmaceutical intervention policies such as community quarantines, closures and travel bans are often implemented in emergencies but many of them are disruptive and difficult to maintain for extended periods of time. A promising alternative recommended by the CDC for influenza is requiring individuals showing fever symptoms to remain isolated at home until they are fever-free for at least one day, but there is limited evidence to support the effectiveness of such symptom-based isolation policies. Methods:Here we introduce a computational model of symptom-based isolation that accounts for the timing of symptoms, viral shedding and the population structure. It was validated on outbreaks of influenza in schools and modified to account for COVID-19. It was then used to estimate the outbreak curves and the attack rates (the proportion of the population infected) under one or more days of fever-based isolation.Results: Using the model we find evidence that symptom-based isolation policies could reduce the attack rates of both influenza and COVID-19 outbreaks, and flatten the outbreak curves.Specifically, we found that across a range of influenza scenarios, a CDC-recommended policy of one day isolation following fever can reduce the attack rate from 27% of the population to 12%, : medRxiv preprint implementing one day post-fever isolation would reduce the attack rate from 79% to 71%, and there is possible benefit from isolation for six days. In both influenza and COVID-19, the policies are predicted to reduce the peak number of infected but not shorten the outbreak duration.Conclusions : Symptom-based isolation could be an important tool to control influenza and COVID-19 outbreaks in schools, and potentially other settings. We recommend that schools implement a post-fever isolation policy of two days for influenza and six days for COVID-19.

show abstract

“…The next step is computing the covariance matrix. The covariance matrix is used to identify the correlation and dependencies among the features as shown in Equation (3).…”

Section: Covid-19mentioning

confidence: 99%

“…Although the number of infections continues to rise, the United States seems to have failed to take effective vaccine distribution and isolation measures [ 2 ]. According to [ 3 ] who investigated vaccine allocation, it is important for a region to prioritize who receives vaccines. According to [ 4 ], reasonable vaccine distribution protocols are needed in the case of regions with unstable resources.…”

Section: Introductionmentioning

confidence: 99%

Cluster Analysis of US COVID-19 Infected States for Vaccine Distribution

Shih

et al. 2022

Healthcare

View full text Add to dashboard Cite

Since December 2019, COVID-19 has been raging worldwide. To prevent the spread of COVID-19 infection, many countries have proposed epidemic prevention policies and quickly administered vaccines, However, under facing a shortage of vaccines, the United States did not put forward effective epidemic prevention policies in time to prevent the infection from expanding, resulting in the epidemic in the United States becoming more and more serious. Through “The COVID Tracking Project”, this study collects medical indicators for each state in the United States from 2020 to 2021, and through feature selection, each state is clustered according to the epidemic’s severity. Furthermore, through the confusion matrix of the classifier to verify the accuracy of the cluster analysis, the study results show that the Cascade K-means cluster analysis has the highest accuracy. This study also labeled the three clusters of the cluster analysis results as high, medium, and low infection levels. Policymakers could more objectively decide which states should prioritize vaccine allocation in a vaccine shortage to prevent the epidemic from continuing to expand. It is hoped that if there is a similar epidemic in the future, relevant policymakers can use the analysis procedure of this study to determine the allocation of relevant medical resources for epidemic prevention according to the severity of infection in each state to prevent the spread of infection.

show abstract

Optimizing influenza vaccine policies for controlling 2009-like pandemics and regular outbreaks

Cited by 5 publications

References 27 publications

Effectiveness of isolation policies in schools: evidence from a mathematical model of influenza and COVID-19

Effectiveness of isolation policies in schools: evidence from a mathematical model of influenza and COVID-19

Effectiveness of Isolation Policies in Schools: Evidence from a Mathematical Model of Influenza and COVID-19

Cluster Analysis of US COVID-19 Infected States for Vaccine Distribution

Contact Info

Product

Resources

About