Optimizing Distribution of Pandemic Influenza Antiviral Drugs

Singh, Bhanwar; Huang, Hsin Chan; Morton, David P.; Johnson, Gregory P.; Gutfraind, Alexander; Galvani, Alison P.; Clements, Bruce W.; Meyers, Lauren Ancel

doi:10.3201/eid2102.141024

Cited by 16 publications

(21 citation statements)

References 14 publications

(12 reference statements)

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“…Computational and data availability considerations therefore limit a detailed representation of the system. We adopt a model by Singh et al [ 28 ], which optimizes pharmacy-based distribution of antiviral drugs for Texas for the 2009 H1N1 pandemic. The model is relatively simple to solve and intuitive, and is available as a Web-based decision support tool for the Texas Department of State Health Services [ 29 ].…”

Section: Methodsmentioning

confidence: 99%

Selecting pharmacies for COVID-19 testing to ensure access

Risanger

Singh

Morton

et al. 2021

Health Care Manag Sci

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Section: Methodsmentioning

confidence: 99%

Selecting pharmacies for COVID-19 testing to ensure access

Risanger

Singh

Morton

et al. 2021

Health Care Manag Sci

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Section: Methodsmentioning

confidence: 99%

“…The model require the willingness to travel of the population as input. We use the data-driven willingness-to-travel function from [20], which is estimated using National Household Travel Survey data [28] for privately operated vehicles. Equation 2shows the fraction of the population, ρ, willing to travel distance d. The willingness-to-travel function is an exponentially decaying fraction of the population, where the population has different travel behavior for distances below and above a five-mile threshold.…”

Section: Introductionmentioning

confidence: 99%

“…We calculate travel distance d ij as the distance between two ZCTA centroid coordinates, as calculated by the Haversine formula. As in Singh et al [20], we assume that the full population in a ZCTA is willing to travel to a pharmacy in their own ZCTA. The travel distance to pharmacies within a ZCTA is approximated as the square root of land area of the ZCTA divided by two for the full population.…”

Section: Introductionmentioning

confidence: 99%

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Selecting pharmacies for COVID-19 testing to ensure access

Risanger

Singh

Morton

et al. 2020

Preprint

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Rapid diagnostic testing for COVID-19 is key to guiding social distancing orders and containing emerging disease clusters by contact tracing and isolation. However, communities throughout the US do not yet have adequate access to tests. Pharmacies are already engaged in testing, but there is capacity to greatly increase coverage. Using a facility location optimization model and willingness-to-travel estimates from US National Household Travel Survey data, we find that if COVID-19 testing became available in all US pharmacies, an estimated 94% of the US population would be willing to travel to obtain a test, if warranted. Whereas the largest chain provides high coverage in densely populated states, like Massachusetts, Rhode Island, New Jersey, and Connecticut, independent pharmacies would be required for sufficient coverage in Montana, South Dakota, and Wyoming. If only 1,000 pharmacies in the US are selected to provide testing, judicious selection, using our optimization model, provides estimated access to 29 million more people than selecting pharmacies simply based on population density. COVID-19 testing through pharmacies can improve access across the US. Even if only few pharmacies offer testing, judicious selection of specific sites can simplify logistics and improve access.

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“…Previous researchers 12 – 17 have considered many related aspects of this problem. For example, Althouse et al .…”

Section: Related Workmentioning

confidence: 99%

Feedback Between Behavioral Adaptations and Disease Dynamics

Chen

Marathe

2018

Sci Rep

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We study the feedback processes between individual behavior, disease prevalence, interventions and social networks during an influenza pandemic when a limited stockpile of antivirals is shared between the private and the public sectors. An economic model that uses prevalence-elastic demand for interventions is combined with a detailed social network and a disease propagation model to understand the feedback mechanism between epidemic dynamics, market behavior, individual perceptions, and the social network. An urban and a rural region are simulated to assess the robustness of results. Results show that an optimal split between the private and public sectors can be reached to contain the disease but the accessibility of antivirals from the private sector is skewed towards the richest income quartile. Also, larger allocations to the private sector result in wastage where individuals who do not need it are able to purchase it but who need it cannot afford it. Disease prevalence increases with household size and total contact time but not by degree in the social network, whereas wastage of antivirals decreases with degree and contact time. The best utilization of drugs is achieved when individuals with high contact time use them, who tend to be the school-aged children of large families.

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Optimizing Distribution of Pandemic Influenza Antiviral Drugs

Abstract: Effective distribution of these drugs will reduce illness and death in underinsured populations.

Cited by 16 publications

References 14 publications

Selecting pharmacies for COVID-19 testing to ensure access

Selecting pharmacies for COVID-19 testing to ensure access

Selecting pharmacies for COVID-19 testing to ensure access

Feedback Between Behavioral Adaptations and Disease Dynamics

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