Comparison of Private vs. Public Interventions for Controlling Influenza Epidemics Joint work with...

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Comparison of Private vs. Public Interventions for Controlling Influenza Epidemics Joint work with Chris Barrett, Jiangzhuo Chen, Stephen Eubank, Bryan Lewis, Yifei Ma and Madhav Marathe Achla Marathe Virginia Bioinformatics Institute and Dept. of Agricultural and Applied Economics

Transcript of Comparison of Private vs. Public Interventions for Controlling Influenza Epidemics Joint work with...

Comparison of Private vs. Public Interventions for Controlling Influenza Epidemics

Joint work with Chris Barrett, Jiangzhuo Chen, Stephen Eubank, Bryan Lewis, Yifei Ma and Madhav Marathe

Achla MaratheVirginia Bioinformatics Institute and

Dept. of Agricultural and Applied Economics

This work has been funded in part by the following grants: NIH-MIDAS, NIH-R01, DoD CNIMS, NSF-ICES and NSF-NetSe.

Acknowledgment

• Goal: – Design effective intervention strategies to

control the spread of Influenza.• Challenges:– Lack of compliance for public health directives.– Lack of accurate knowledge about the global

prevalence and the severity of the disease.

Introduction

• This research considers two sets of interventions strategies, private and public.

• Evaluates the performance of each intervention strategy under a variety of scenarios through agent based simulations.

• Uses a synthetic social network of a large urban city as the area of study.

• Offers guidance to public health policy makers.

Introduction

Standard Evaluation Measures

• Effectiveness of intervention:– Reduce attack rate/peak– Delay outbreak/peak

• Cost– Number of antivirals or vaccines consumed. These are often

available in limited supply– Other costs: e.g. administration of a mass vaccination campaign

(not considered here)

• Individuals observe the health state of distance-1 (or immediate) contacts in the social network.

• After a threshold number of contacts become sick, individual intervenes with an antiviral or a vaccine.

Private Strategy

A A

Distance 1 neighbors of A Infected neighbors of A

Public Strategy

• Block intervention: take action on all people residing in a census block group if an outbreak is observed in the block group

• School intervention: take action on all students in a school if an outbreak is observed in the school

Private• Individuals observe the

health state of local contacts.• High accuracy on prevalence• Self motivated to intervene

when encounter sickness.• Compliance is high• No delay

Private vs. Public Intervention Strategies

Public• Public health officials use

global incidence data• Low accuracy on prevalence• Interventions are imposed

top-down on individuals.• Compliance is low• Delay in implementation

Experimental Settings

• Disease propagation through social contact network on a synthetic population– Miami network: 2 million people, 100 million people-people

contacts

• Assume unlimited supply of antiviral and vaccine– One course of antiviral is effective immediately for 10 days:

reduce incoming transmissibility by 80% and outgoing by 87%– Vaccine is effective after 2 weeks but remains effective for the

season. Vaccine efficacy is 100%.

• Simulation tool used: Indemics • Indemics is an interactive epidemic simulation and

modeling environment that was developed in our group.

Within Host Disease Model

Individuals move through disease states

• Incubation period: mean 1.9 days• Infectious period: mean 4.1 days• Symptomatic rate: 0.67• Asymptomatic are 50% less likely

to transmit the disease.

Experiment: A Factorial Design

• 3 different intervention strategies: D1, Block, School• 2 flu models: 20% (moderate) and 40% (catastrophic) attack

rate• Diagnosis rate: 2 values 1 and 0.3• 2 threshold values for taking actions: .01 and .05

– Fraction of direct contacts found to be sick: D1 intervention– Fraction of block group (school) subpopulation found to be sick: block

(school) intervention

• 2 compliance rates: 1 and 0.5.• 2 pharmaceutical actions: Antiviral and Vaccination (VAX)• Delay in implementing interventions: 2 values for Block and

School, 1 day and 5 days; no delay for D1• 2 x 2 x 2 x 2 x 2 x ( 2 + 2 + 1) = 160 cells• 25 replicates per cell (4000 simulation runs!)

Experimental Results

Attack Rate: Moderate Flu with Various Interventions

Intervention Coverage: Moderate Flu with Various Interventions

Attack Rate: Catastrophic Flu with Various Interventions

Intervention Coverage: Catastrophic Flu with Various Interventions

Experiment Results: Effectiveness of Actions

• Antiviral is very effective under D1; almost no effect under two public strategies

• No efficacy delay; protect people from sick contacts immediately• Efficacy expires after 10 days; hard to avoid transmissions from

farther-away nodes in the neighborhood• If only antiviral is available, should motivate people to take

antiviral by themselves• Vaccine performs best under Block, worst under School

• Two weeks efficacy delay; sick contacts become less relevant• Form larger “ring” around “hot-spots”• Large consumption under Block; little consumed under school

(school students <25% of whole population)• If sufficient vaccines are available, should apply Block

intervention strategy

Experiment Results

• Compliance: limited impact on attack rate; almost linearly determine drug consumption– Higher compliance more consumption– Double consumption ! twice reduction in attack rate

• Implementation delay: little difference between 1 day or 5 days

• Nothing is useful under low diagnosis + high threshold– Campaign to raise concern on epidemic and early action– Increase diagnosis accuracy and enhance public health surveillance

Antiviral or Vaccine

• D1 intervention is effective with antiviral; Block intervention is effective with vaccine

• School intervention consumes little: may be most cost-effective when drugs are available in limited quantity

Closer look at an interesting setting…

(catastrophic flu, high diagnosis rate, low threshold, only vaccines available)

Comparative Performance under Vaccination

Summary

• An interesting comparison study– Individual behavioral vs. public health level interventions– Use simulations to guide policy

• Unique capability to run such complex, realistic studies– No other tool can apply interventions based on social network

based relationships because it requires• Detailed social network• Network relationship based dynamic intervention capability• An efficient simulation environment

Summary

• Vaccine intervention: Block strategy performs better than D1. Given the 2 week delay in vaccine efficacy, block strategy is able to form a larger ring around hot-spots. The immediate contacts become less relevant. However a lot more vaccines are needed.

• If the transmissibility is high and vaccines are available in abundant supply, the Block strategy is likely to be the best choice.

• Antiviral Intervention: If antivirals are available in limited supply, it may be best to distribute them to people over the counter to make them easily accessible.

Thanks!

Indemics: Interactive Simulation

• Indemics: Interactive Epidemic Simulation and Modeling Environment• Data Models:

– Relational Data about individuals (P)– Social Contact Network (N)– Transmission Network/Dendrogram (D)

• Queries on a single data type– (P) Find all school-ages in area <x>– (N) Find all neighbors of person <a>– (D) Find all infected persons at day <t>

• Queries across multiple data types– Count number of infected persons in zip code 24060 (Blacksburg, VA)– Find all infectious students on day 20 in Blacksburg high school and their

family members

Dynamic Queries and Interventions

• Users interact with the system using well-defined languages– Indemics commands: count infected persons : group = seniors,

infected day = between 20 and 22– SQL statements: select * from social_network SN and infections INF

where SN.pid_a = INF.transmitee_pid and time = 20 (find all neighbors of all infections at day 20)

– Libraries of queries can be pre-defined by expert users

• Indemics Interventions– apply interventions: type = antiviral, duration = 10, group = school

age, infected_day = between 24 and 30– apply interventions: type=work closure, duration = 5, group =

adults, infected day = between 20 and 21; type = school closure, duration = 5, group = school age