The Experts below are selected from a list of 507 Experts worldwide ranked by ideXlab platform
Lauren Ancel Meyers - One of the best experts on this subject based on the ideXlab platform.
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correction optimizing tactics for use of the u s antiviral Strategic National Stockpile for pandemic influenza
PLOS ONE, 2011Co-Authors: Nedialko B Dimitrov, Sebastian Goll, Nathaniel Hupert, Babak Pourbohloul, Lauren Ancel MeyersAbstract:One of the author's funding sources was not acknowledged in the published manuscript. The authors wish to add the following funding information to the Funding section: "This work was supported by grants to LM from NIH Models of Infectious Disease Agent Study (MIDAS) (U01-GM087719-01), the James S. McDonnell Foundation, and NSF (DEB-0749097) and grants to BP from CIHR(PTL-97125 and PAP-93425) and the Michael Smith Foundation for Health Research."
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optimizing tactics for use of the u s antiviral Strategic National Stockpile for pandemic influenza
PLOS ONE, 2011Co-Authors: Nedialko B Dimitrov, Sebastian Goll, Nathaniel Hupert, Babak Pourbohloul, Lauren Ancel MeyersAbstract:In 2009, public health agencies across the globe worked to mitigate the impact of the swine-origin influenza A (pH1N1) virus. These efforts included intensified surveillance, social distancing, hygiene measures, and the targeted use of antiviral medications to prevent infection (prophylaxis). In addition, aggressive antiviral treatment was recommended for certain patient subgroups to reduce the severity and duration of symptoms. To assist States and other localities meet these needs, the U.S. Government distributed a quarter of the antiviral medications in the Strategic National Stockpile within weeks of the pandemic's start. However, there are no quantitative models guiding the geo-temporal distribution of the remainder of the Stockpile in relation to pandemic spread or severity. We present a tactical optimization model for distributing this Stockpile for treatment of infected cases during the early stages of a pandemic like 2009 pH1N1, prior to the wide availability of a strain-specific vaccine. Our optimization method efficiently searches large sets of intervention strategies applied to a stochastic network model of pandemic influenza transmission within and among U.S. cities. The resulting optimized strategies depend on the transmissability of the virus and postulated rates of antiviral uptake and wastage (through misallocation or loss). Our results suggest that an aggressive community-based antiviral treatment strategy involving early, widespread, pro-rata distribution of antivirals to States can contribute to slowing the transmission of mildly transmissible strains, like pH1N1. For more highly transmissible strains, outcomes of antiviral use are more heavily impacted by choice of distribution intervals, quantities per shipment, and timing of shipments in relation to pandemic spread. This study supports previous modeling results suggesting that appropriate antiviral treatment may be an effective mitigation strategy during the early stages of future influenza pandemics, increasing the need for systematic efforts to optimize distribution strategies and provide tactical guidance for public health policy-makers.
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Optimizing tactics for use of the U.S. Antiviral Strategic National Stockpile for Pandemic (H1N1) Influenza, 2009.
PLoS currents, 2009Co-Authors: Nedialko B Dimitrov, Sebastian Goll, Nathaniel Hupert, Babak Pourbohloul, Lauren Ancel MeyersAbstract:Public health agencies across the globe are working to mitigate the impact of the 2009 pandemic caused by swine-origin influenza A (H1N1) virus. Prior to the large-scale distribution of an effective vaccine, the primary modes of control have included careful surveillance, social distancing and hygiene measures, Strategic school closures, other community measures, and the prudent use of antiviral medications to prevent infection (prophylaxis) or reduce the severity and duration of symptoms (treatment). Here, we use mathematical models to determine the optimal geo-temporal tactics for distributing the U.S. Strategic National Stockpile of antivirals for treatment of infected cases during the early stages of a pandemic, prior to the wide availability of vaccines.We present a versatile optimization method for efficiently searching large sets of public health intervention strategies, and apply it to evaluating tactics for distributing antiviral medications from the U.S. Strategic National Stockpile (SNS). We implemented the algorithm on a network model of H1N1 transmission within and among U.S. cities to project the epidemiological impacts of antiviral Stockpile distribution schedules and priorities. The resulting optimized strategies critically depend on the rates of antiviral uptake and wastage (through misallocation or loss). And while a surprisingly simple pro rata distribution schedule is competitive with the optimized strategies across a wide range of uptake and wastage, other equally simple policies perform poorly.Even as vaccination campaigns get underway worldwide, antiviral medications continue to play a critical in reducing H1N1-associated morbidity and mortality. If efforts are made to increase the fraction of cases treated promptly with antivirals above current levels, our model suggests that optimal use of the antiviral component of the Strategic National Stockpile may appreciably slow the transmission of H1N1 during fall 2009, thereby improving the impact of targeted vaccination. A more aggressive optimized antiviral strategy of this type may prove critical to mitigating future flu pandemics, but may increase the risk of antiviral resistance.
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Supplemental Analysis for Optimizing Tactics for use of the U.S. Antiviral Strategic National Stockpile for Pandemic (H1N1) Influenza, 2009
2009Co-Authors: Nedialko B Dimitrov, Sebastian Goll, Nathaniel Hupert, Babak Pourbohloul, Lauren Ancel MeyersAbstract:We simulate the spread of disease within and between the 100 largest metropolitan areas in theUnited States. Disease is transmitted within cities according to a deterministic compartmentalSEIRmodel (city model). Disease moves stochastically between cities via infected travelers (networkmodel). In each simulation run we alternately simulate a week (i.e., 7 days) of disease transmissionwithin each city using the city model and then simulate between-city transmission using the networkmodel, as described below. This process is repeated for 53 weeks or until the disease dies out,whichever occurs first.
Nathaniel Hupert - One of the best experts on this subject based on the ideXlab platform.
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correction optimizing tactics for use of the u s antiviral Strategic National Stockpile for pandemic influenza
PLOS ONE, 2011Co-Authors: Nedialko B Dimitrov, Sebastian Goll, Nathaniel Hupert, Babak Pourbohloul, Lauren Ancel MeyersAbstract:One of the author's funding sources was not acknowledged in the published manuscript. The authors wish to add the following funding information to the Funding section: "This work was supported by grants to LM from NIH Models of Infectious Disease Agent Study (MIDAS) (U01-GM087719-01), the James S. McDonnell Foundation, and NSF (DEB-0749097) and grants to BP from CIHR(PTL-97125 and PAP-93425) and the Michael Smith Foundation for Health Research."
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optimizing tactics for use of the u s antiviral Strategic National Stockpile for pandemic influenza
PLOS ONE, 2011Co-Authors: Nedialko B Dimitrov, Sebastian Goll, Nathaniel Hupert, Babak Pourbohloul, Lauren Ancel MeyersAbstract:In 2009, public health agencies across the globe worked to mitigate the impact of the swine-origin influenza A (pH1N1) virus. These efforts included intensified surveillance, social distancing, hygiene measures, and the targeted use of antiviral medications to prevent infection (prophylaxis). In addition, aggressive antiviral treatment was recommended for certain patient subgroups to reduce the severity and duration of symptoms. To assist States and other localities meet these needs, the U.S. Government distributed a quarter of the antiviral medications in the Strategic National Stockpile within weeks of the pandemic's start. However, there are no quantitative models guiding the geo-temporal distribution of the remainder of the Stockpile in relation to pandemic spread or severity. We present a tactical optimization model for distributing this Stockpile for treatment of infected cases during the early stages of a pandemic like 2009 pH1N1, prior to the wide availability of a strain-specific vaccine. Our optimization method efficiently searches large sets of intervention strategies applied to a stochastic network model of pandemic influenza transmission within and among U.S. cities. The resulting optimized strategies depend on the transmissability of the virus and postulated rates of antiviral uptake and wastage (through misallocation or loss). Our results suggest that an aggressive community-based antiviral treatment strategy involving early, widespread, pro-rata distribution of antivirals to States can contribute to slowing the transmission of mildly transmissible strains, like pH1N1. For more highly transmissible strains, outcomes of antiviral use are more heavily impacted by choice of distribution intervals, quantities per shipment, and timing of shipments in relation to pandemic spread. This study supports previous modeling results suggesting that appropriate antiviral treatment may be an effective mitigation strategy during the early stages of future influenza pandemics, increasing the need for systematic efforts to optimize distribution strategies and provide tactical guidance for public health policy-makers.
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Optimizing tactics for use of the U.S. Antiviral Strategic National Stockpile for Pandemic (H1N1) Influenza, 2009.
PLoS currents, 2009Co-Authors: Nedialko B Dimitrov, Sebastian Goll, Nathaniel Hupert, Babak Pourbohloul, Lauren Ancel MeyersAbstract:Public health agencies across the globe are working to mitigate the impact of the 2009 pandemic caused by swine-origin influenza A (H1N1) virus. Prior to the large-scale distribution of an effective vaccine, the primary modes of control have included careful surveillance, social distancing and hygiene measures, Strategic school closures, other community measures, and the prudent use of antiviral medications to prevent infection (prophylaxis) or reduce the severity and duration of symptoms (treatment). Here, we use mathematical models to determine the optimal geo-temporal tactics for distributing the U.S. Strategic National Stockpile of antivirals for treatment of infected cases during the early stages of a pandemic, prior to the wide availability of vaccines.We present a versatile optimization method for efficiently searching large sets of public health intervention strategies, and apply it to evaluating tactics for distributing antiviral medications from the U.S. Strategic National Stockpile (SNS). We implemented the algorithm on a network model of H1N1 transmission within and among U.S. cities to project the epidemiological impacts of antiviral Stockpile distribution schedules and priorities. The resulting optimized strategies critically depend on the rates of antiviral uptake and wastage (through misallocation or loss). And while a surprisingly simple pro rata distribution schedule is competitive with the optimized strategies across a wide range of uptake and wastage, other equally simple policies perform poorly.Even as vaccination campaigns get underway worldwide, antiviral medications continue to play a critical in reducing H1N1-associated morbidity and mortality. If efforts are made to increase the fraction of cases treated promptly with antivirals above current levels, our model suggests that optimal use of the antiviral component of the Strategic National Stockpile may appreciably slow the transmission of H1N1 during fall 2009, thereby improving the impact of targeted vaccination. A more aggressive optimized antiviral strategy of this type may prove critical to mitigating future flu pandemics, but may increase the risk of antiviral resistance.
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Supplemental Analysis for Optimizing Tactics for use of the U.S. Antiviral Strategic National Stockpile for Pandemic (H1N1) Influenza, 2009
2009Co-Authors: Nedialko B Dimitrov, Sebastian Goll, Nathaniel Hupert, Babak Pourbohloul, Lauren Ancel MeyersAbstract:We simulate the spread of disease within and between the 100 largest metropolitan areas in theUnited States. Disease is transmitted within cities according to a deterministic compartmentalSEIRmodel (city model). Disease moves stochastically between cities via infected travelers (networkmodel). In each simulation run we alternately simulate a week (i.e., 7 days) of disease transmissionwithin each city using the city model and then simulate between-city transmission using the networkmodel, as described below. This process is repeated for 53 weeks or until the disease dies out,whichever occurs first.
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Mass medication modeling in response to public health emergencies: outcomes of a drive-thru exercise.
Journal of public health management and practice : JPHMP, 2007Co-Authors: Tyler Zerwekh, Nathaniel Hupert, Jason Mcknight, Daniel Wattson, Lisa Hendrickson, David LaneAbstract:This article presents the outcomes of a full-scale training exercise utilizing a drive-thru clinic model for dispensing of Strategic National Stockpile medication. The Hawaii Department of Health developed a clinic design for vehicles based on previous exercises and research on sample throughput rates. The streamlined model selected includes a triage area near the entrance and consecutive stations for the public to register, have an evaluation for drug contradictions, and receive the medication. During the 2-hour exercise held in April 2005, a total of 622 patients were processed in their vehicles for an overall rate of 5.2 persons per minute. Although patient services were reduced in comparison to current walk-in clinic models, the public was able to receive prophylactic medication in a timely manner with a high rate of accuracy and minimal human-to-human contact. These results demonstrate that local health departments, particularly in rural areas, can provide essential medications, vaccinations, or rations through a drive-thru clinic, thus limiting morbidity and mortality during a public health emergency.
Nedialko B Dimitrov - One of the best experts on this subject based on the ideXlab platform.
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correction optimizing tactics for use of the u s antiviral Strategic National Stockpile for pandemic influenza
PLOS ONE, 2011Co-Authors: Nedialko B Dimitrov, Sebastian Goll, Nathaniel Hupert, Babak Pourbohloul, Lauren Ancel MeyersAbstract:One of the author's funding sources was not acknowledged in the published manuscript. The authors wish to add the following funding information to the Funding section: "This work was supported by grants to LM from NIH Models of Infectious Disease Agent Study (MIDAS) (U01-GM087719-01), the James S. McDonnell Foundation, and NSF (DEB-0749097) and grants to BP from CIHR(PTL-97125 and PAP-93425) and the Michael Smith Foundation for Health Research."
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optimizing tactics for use of the u s antiviral Strategic National Stockpile for pandemic influenza
PLOS ONE, 2011Co-Authors: Nedialko B Dimitrov, Sebastian Goll, Nathaniel Hupert, Babak Pourbohloul, Lauren Ancel MeyersAbstract:In 2009, public health agencies across the globe worked to mitigate the impact of the swine-origin influenza A (pH1N1) virus. These efforts included intensified surveillance, social distancing, hygiene measures, and the targeted use of antiviral medications to prevent infection (prophylaxis). In addition, aggressive antiviral treatment was recommended for certain patient subgroups to reduce the severity and duration of symptoms. To assist States and other localities meet these needs, the U.S. Government distributed a quarter of the antiviral medications in the Strategic National Stockpile within weeks of the pandemic's start. However, there are no quantitative models guiding the geo-temporal distribution of the remainder of the Stockpile in relation to pandemic spread or severity. We present a tactical optimization model for distributing this Stockpile for treatment of infected cases during the early stages of a pandemic like 2009 pH1N1, prior to the wide availability of a strain-specific vaccine. Our optimization method efficiently searches large sets of intervention strategies applied to a stochastic network model of pandemic influenza transmission within and among U.S. cities. The resulting optimized strategies depend on the transmissability of the virus and postulated rates of antiviral uptake and wastage (through misallocation or loss). Our results suggest that an aggressive community-based antiviral treatment strategy involving early, widespread, pro-rata distribution of antivirals to States can contribute to slowing the transmission of mildly transmissible strains, like pH1N1. For more highly transmissible strains, outcomes of antiviral use are more heavily impacted by choice of distribution intervals, quantities per shipment, and timing of shipments in relation to pandemic spread. This study supports previous modeling results suggesting that appropriate antiviral treatment may be an effective mitigation strategy during the early stages of future influenza pandemics, increasing the need for systematic efforts to optimize distribution strategies and provide tactical guidance for public health policy-makers.
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Optimizing tactics for use of the U.S. Antiviral Strategic National Stockpile for Pandemic (H1N1) Influenza, 2009.
PLoS currents, 2009Co-Authors: Nedialko B Dimitrov, Sebastian Goll, Nathaniel Hupert, Babak Pourbohloul, Lauren Ancel MeyersAbstract:Public health agencies across the globe are working to mitigate the impact of the 2009 pandemic caused by swine-origin influenza A (H1N1) virus. Prior to the large-scale distribution of an effective vaccine, the primary modes of control have included careful surveillance, social distancing and hygiene measures, Strategic school closures, other community measures, and the prudent use of antiviral medications to prevent infection (prophylaxis) or reduce the severity and duration of symptoms (treatment). Here, we use mathematical models to determine the optimal geo-temporal tactics for distributing the U.S. Strategic National Stockpile of antivirals for treatment of infected cases during the early stages of a pandemic, prior to the wide availability of vaccines.We present a versatile optimization method for efficiently searching large sets of public health intervention strategies, and apply it to evaluating tactics for distributing antiviral medications from the U.S. Strategic National Stockpile (SNS). We implemented the algorithm on a network model of H1N1 transmission within and among U.S. cities to project the epidemiological impacts of antiviral Stockpile distribution schedules and priorities. The resulting optimized strategies critically depend on the rates of antiviral uptake and wastage (through misallocation or loss). And while a surprisingly simple pro rata distribution schedule is competitive with the optimized strategies across a wide range of uptake and wastage, other equally simple policies perform poorly.Even as vaccination campaigns get underway worldwide, antiviral medications continue to play a critical in reducing H1N1-associated morbidity and mortality. If efforts are made to increase the fraction of cases treated promptly with antivirals above current levels, our model suggests that optimal use of the antiviral component of the Strategic National Stockpile may appreciably slow the transmission of H1N1 during fall 2009, thereby improving the impact of targeted vaccination. A more aggressive optimized antiviral strategy of this type may prove critical to mitigating future flu pandemics, but may increase the risk of antiviral resistance.
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Supplemental Analysis for Optimizing Tactics for use of the U.S. Antiviral Strategic National Stockpile for Pandemic (H1N1) Influenza, 2009
2009Co-Authors: Nedialko B Dimitrov, Sebastian Goll, Nathaniel Hupert, Babak Pourbohloul, Lauren Ancel MeyersAbstract:We simulate the spread of disease within and between the 100 largest metropolitan areas in theUnited States. Disease is transmitted within cities according to a deterministic compartmentalSEIRmodel (city model). Disease moves stochastically between cities via infected travelers (networkmodel). In each simulation run we alternately simulate a week (i.e., 7 days) of disease transmissionwithin each city using the city model and then simulate between-city transmission using the networkmodel, as described below. This process is repeated for 53 weeks or until the disease dies out,whichever occurs first.
Susan E Gorman - One of the best experts on this subject based on the ideXlab platform.
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planning considerations for state local tribal and territorial partners to receive medical countermeasures from cdc s Strategic National Stockpile during a public health emergency
American Journal of Public Health, 2018Co-Authors: Tina R Bhavsar, Deborah L Esbitt, Susan E GormanAbstract:The Centers for Disease Control and Prevention’s Strategic National Stockpile is a National repository of potentially life-saving medical countermeasures including pharmaceuticals and medical suppl...
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Planning Considerations for State, Local, Tribal, and Territorial Partners to Receive Medical Countermeasures From CDC’s Strategic National Stockpile During a Public Health Emergency
American Journal of Public Health, 2018Co-Authors: Tina R Bhavsar, Deborah L Esbitt, Susan E GormanAbstract:The Centers for Disease Control and Prevention’s Strategic National Stockpile is a National repository of potentially life-saving medical countermeasures including pharmaceuticals and medical suppl...
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Experimental studies on performance of ventilators stored in the Strategic National Stockpile.
Journal of emergency management (Weston Mass.), 2018Co-Authors: Ali Mehrabi, Eileen Malatino, Susan E Gorman, Patricia Dillon, Kyle Kelly, Kristina Hitchins, Madhusoodana Nambiar, Hilda F ScharenAbstract:Background: The Center for Devices and Radiological Health, Food and Drug Administration (FDA) launched a collaborative initiative with Centers for Disease Control and Prevention (CDC) to gain a better understanding of ventilators that are used during National emergencies. This initiative was intended to test reliability of ventilator devices stored long term in the CDC Strategic National Stockpile (SNS) and also used by the Department of Defense. These ventilators are intended to be used by trained operators to provide ventilatory support to adult and pediatric populations under diverse environmental conditions. The authors evaluated device performance and possible effects of long-term storage. Methods: Three SNS ventilator models: Impact Uni-Vent 754 Eagle™, Covidien (Puritan Bennett) LP10, and CareFusion LTV 1200 were used in this study. A total of 36 ventilators, 12 per model, were evaluated for performance in simulated adult populations using a test lung. The parameters evaluated included battery charge status and capability, battery longevity, positive end expiratory pressure consistency, device performance on AC and DC (battery) power, and device durability testing. Results: The out-of-the-box run time was equal to or higher than the manufacturer’s specifications for fully charged batteries for all ventilators except 58 percent of the Impact 754 ventilators. No significant ventilator performance issues were observed in terms of tidal volume consistency, proximal pressure, oxygen consumption, and a 2000-hour run test in LP10 models. Conclusions: These findings provide information about the long-term storage of ventilators that have regular maintenance, and their ability to perform reliably during a public health emergency.
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Planning Considerations for State, Local, Tribal, and Territorial Partners to Receive Medical Countermeasures From CDC's Strategic National Stockpile During a Public Health Emergency.
American journal of public health, 2018Co-Authors: Tina R Bhavsar, Deborah L Esbitt, Susan E GormanAbstract:The Centers for Disease Control and Prevention's Strategic National Stockpile is a National repository of potentially life-saving medical countermeasures including pharmaceuticals and medical supplies for use in a public health emergency severe enough to cause local, regional, and state supplies to run out. Several planning considerations can assist state, local, tribal, and territorial jurisdictions in preparing to receive, distribute, dispense, and administer medical countermeasures from the Strategic National Stockpile. These considerations include, but are not limited to, issues surrounding regulatory requirements, controlled substances, cold chain management, and ancillary supply needs. Multiple aspects to consider for each of these functions are discussed here to assist partners in their planning efforts.
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Koenig and Schultz's Disaster Medicine: Comprehensive Principles and Practices: Mass Dispensing of Antibiotics and Vaccines
Koenig and Schultz's Disaster Medicine, 1Co-Authors: Susan E Gorman, Nicki PesikAbstract:The development of mass dispensing clinics and mass vaccination clinics should be incorporated into community disaster plans. Federal assistance in the event of a large-scale public health emergency requiring mass antibiotic prophylaxis or vaccination includes obtaining necessary medications from several sources. In the United States, the Strategic National Stockpile (SNS) is a federally managed supply of antibiotics, vaccines, antitoxins, antivirals, medical supplies, and equipment that is available to affected areas once local, state, or regional supplies are depleted or systems are overwhelmed. Points of dispensing (PODs) operation are the mechanisms available for dispensing medication or administering vaccines to large population after a catastrophic event. Medication-related adverse events may be seen in varying numbers in a mass dispensing or mass vaccination campaign. Each POD location should have the appropriate equipment such as forklifts or pallet jacks to move deliveries as well as sufficient equipment to provide cold chain storage as needed.
Sebastian Goll - One of the best experts on this subject based on the ideXlab platform.
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correction optimizing tactics for use of the u s antiviral Strategic National Stockpile for pandemic influenza
PLOS ONE, 2011Co-Authors: Nedialko B Dimitrov, Sebastian Goll, Nathaniel Hupert, Babak Pourbohloul, Lauren Ancel MeyersAbstract:One of the author's funding sources was not acknowledged in the published manuscript. The authors wish to add the following funding information to the Funding section: "This work was supported by grants to LM from NIH Models of Infectious Disease Agent Study (MIDAS) (U01-GM087719-01), the James S. McDonnell Foundation, and NSF (DEB-0749097) and grants to BP from CIHR(PTL-97125 and PAP-93425) and the Michael Smith Foundation for Health Research."
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optimizing tactics for use of the u s antiviral Strategic National Stockpile for pandemic influenza
PLOS ONE, 2011Co-Authors: Nedialko B Dimitrov, Sebastian Goll, Nathaniel Hupert, Babak Pourbohloul, Lauren Ancel MeyersAbstract:In 2009, public health agencies across the globe worked to mitigate the impact of the swine-origin influenza A (pH1N1) virus. These efforts included intensified surveillance, social distancing, hygiene measures, and the targeted use of antiviral medications to prevent infection (prophylaxis). In addition, aggressive antiviral treatment was recommended for certain patient subgroups to reduce the severity and duration of symptoms. To assist States and other localities meet these needs, the U.S. Government distributed a quarter of the antiviral medications in the Strategic National Stockpile within weeks of the pandemic's start. However, there are no quantitative models guiding the geo-temporal distribution of the remainder of the Stockpile in relation to pandemic spread or severity. We present a tactical optimization model for distributing this Stockpile for treatment of infected cases during the early stages of a pandemic like 2009 pH1N1, prior to the wide availability of a strain-specific vaccine. Our optimization method efficiently searches large sets of intervention strategies applied to a stochastic network model of pandemic influenza transmission within and among U.S. cities. The resulting optimized strategies depend on the transmissability of the virus and postulated rates of antiviral uptake and wastage (through misallocation or loss). Our results suggest that an aggressive community-based antiviral treatment strategy involving early, widespread, pro-rata distribution of antivirals to States can contribute to slowing the transmission of mildly transmissible strains, like pH1N1. For more highly transmissible strains, outcomes of antiviral use are more heavily impacted by choice of distribution intervals, quantities per shipment, and timing of shipments in relation to pandemic spread. This study supports previous modeling results suggesting that appropriate antiviral treatment may be an effective mitigation strategy during the early stages of future influenza pandemics, increasing the need for systematic efforts to optimize distribution strategies and provide tactical guidance for public health policy-makers.
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Optimizing tactics for use of the U.S. Antiviral Strategic National Stockpile for Pandemic (H1N1) Influenza, 2009.
PLoS currents, 2009Co-Authors: Nedialko B Dimitrov, Sebastian Goll, Nathaniel Hupert, Babak Pourbohloul, Lauren Ancel MeyersAbstract:Public health agencies across the globe are working to mitigate the impact of the 2009 pandemic caused by swine-origin influenza A (H1N1) virus. Prior to the large-scale distribution of an effective vaccine, the primary modes of control have included careful surveillance, social distancing and hygiene measures, Strategic school closures, other community measures, and the prudent use of antiviral medications to prevent infection (prophylaxis) or reduce the severity and duration of symptoms (treatment). Here, we use mathematical models to determine the optimal geo-temporal tactics for distributing the U.S. Strategic National Stockpile of antivirals for treatment of infected cases during the early stages of a pandemic, prior to the wide availability of vaccines.We present a versatile optimization method for efficiently searching large sets of public health intervention strategies, and apply it to evaluating tactics for distributing antiviral medications from the U.S. Strategic National Stockpile (SNS). We implemented the algorithm on a network model of H1N1 transmission within and among U.S. cities to project the epidemiological impacts of antiviral Stockpile distribution schedules and priorities. The resulting optimized strategies critically depend on the rates of antiviral uptake and wastage (through misallocation or loss). And while a surprisingly simple pro rata distribution schedule is competitive with the optimized strategies across a wide range of uptake and wastage, other equally simple policies perform poorly.Even as vaccination campaigns get underway worldwide, antiviral medications continue to play a critical in reducing H1N1-associated morbidity and mortality. If efforts are made to increase the fraction of cases treated promptly with antivirals above current levels, our model suggests that optimal use of the antiviral component of the Strategic National Stockpile may appreciably slow the transmission of H1N1 during fall 2009, thereby improving the impact of targeted vaccination. A more aggressive optimized antiviral strategy of this type may prove critical to mitigating future flu pandemics, but may increase the risk of antiviral resistance.
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Supplemental Analysis for Optimizing Tactics for use of the U.S. Antiviral Strategic National Stockpile for Pandemic (H1N1) Influenza, 2009
2009Co-Authors: Nedialko B Dimitrov, Sebastian Goll, Nathaniel Hupert, Babak Pourbohloul, Lauren Ancel MeyersAbstract:We simulate the spread of disease within and between the 100 largest metropolitan areas in theUnited States. Disease is transmitted within cities according to a deterministic compartmentalSEIRmodel (city model). Disease moves stochastically between cities via infected travelers (networkmodel). In each simulation run we alternately simulate a week (i.e., 7 days) of disease transmissionwithin each city using the city model and then simulate between-city transmission using the networkmodel, as described below. This process is repeated for 53 weeks or until the disease dies out,whichever occurs first.