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1.
PLoS One ; 12(8): e0182720, 2017.
Article in English | MEDLINE | ID: mdl-28854244

ABSTRACT

Vaccines are arguably the most important means of pandemic influenza mitigation. However, as during the 2009 H1N1 pandemic, mass immunization with an effective vaccine may not begin until a pandemic is well underway. In the U.S., state-level public health agencies are responsible for quickly and fairly allocating vaccines as they become available to populations prioritized to receive vaccines. Allocation decisions can be ethically and logistically complex, given several vaccine types in limited and uncertain supply and given competing priority groups with distinct risk profiles and vaccine acceptabilities. We introduce a model for optimizing statewide allocation of multiple vaccine types to multiple priority groups, maximizing equal access. We assume a large fraction of available vaccines are distributed to healthcare providers based on their requests, and then optimize county-level allocation of the remaining doses to achieve equity. We have applied the model to the state of Texas, and incorporated it in a Web-based decision-support tool for the Texas Department of State Health Services (DSHS). Based on vaccine quantities delivered to registered healthcare providers in response to their requests during the 2009 H1N1 pandemic, we find that a relatively small cache of discretionary doses (DSHS reserved 6.8% in 2009) suffices to achieve equity across all counties in Texas.


Subject(s)
Influenza A Virus, H1N1 Subtype/isolation & purification , Influenza Vaccines/supply & distribution , Influenza, Human/prevention & control , Public Health/methods , Adolescent , Adult , Child , Child, Preschool , Female , Humans , Infant , Influenza Vaccines/therapeutic use , Influenza, Human/epidemiology , Male , Mass Vaccination , Middle Aged , Pregnancy , Texas/epidemiology , Vaccination , Young Adult
2.
Emerg Infect Dis ; 23(6): 914-921, 2017 06.
Article in English | MEDLINE | ID: mdl-28518041

ABSTRACT

In preparing for influenza pandemics, public health agencies stockpile critical medical resources. Determining appropriate quantities and locations for such resources can be challenging, given the considerable uncertainty in the timing and severity of future pandemics. We introduce a method for optimizing stockpiles of mechanical ventilators, which are critical for treating hospitalized influenza patients in respiratory failure. As a case study, we consider the US state of Texas during mild, moderate, and severe pandemics. Optimal allocations prioritize local over central storage, even though the latter can be deployed adaptively, on the basis of real-time needs. This prioritization stems from high geographic correlations and the slightly lower treatment success assumed for centrally stockpiled ventilators. We developed our model and analysis in collaboration with academic researchers and a state public health agency and incorporated it into a Web-based decision-support tool for pandemic preparedness and response.


Subject(s)
Influenza, Human/epidemiology , Models, Statistical , Pandemics , Respiratory Insufficiency/epidemiology , Ventilators, Mechanical/supply & distribution , Civil Defense/organization & administration , Humans , Influenza, Human/complications , Influenza, Human/physiopathology , Influenza, Human/therapy , Public Health/methods , Respiratory Insufficiency/etiology , Respiratory Insufficiency/physiopathology , Respiratory Insufficiency/therapy , Texas/epidemiology
3.
Emerg Infect Dis ; 21(2): 251-8, 2015 Feb.
Article in English | MEDLINE | ID: mdl-25625858

ABSTRACT

We provide a data-driven method for optimizing pharmacy-based distribution of antiviral drugs during an influenza pandemic in terms of overall access for a target population and apply it to the state of Texas, USA. We found that during the 2009 influenza pandemic, the Texas Department of State Health Services achieved an estimated statewide access of 88% (proportion of population willing to travel to the nearest dispensing point). However, access reached only 34.5% of US postal code (ZIP code) areas containing <1,000 underinsured persons. Optimized distribution networks increased expected access to 91% overall and 60% in hard-to-reach regions, and 2 or 3 major pharmacy chains achieved near maximal coverage in well-populated areas. Independent pharmacies were essential for reaching ZIP code areas containing <1,000 underinsured persons. This model was developed during a collaboration between academic researchers and public health officials and is available as a decision support tool for Texas Department of State Health Services at a Web-based interface.


Subject(s)
Antiviral Agents/supply & distribution , Influenza, Human/epidemiology , Algorithms , Decision Support Techniques , Geography , Humans , Influenza, Human/drug therapy , Influenza, Human/prevention & control , Models, Theoretical , Pharmacies , Texas
4.
Food Chem ; 128(2): 348-57, 2011 Sep 15.
Article in English | MEDLINE | ID: mdl-25212141

ABSTRACT

Phytochemical investigation of the ethanol extract from the fruits of Schisandra sphenanthera has resulted in isolation of seven new oxygenated lignans (1-7), in addition to 11 known compounds (8-18). Their structures were determined on the basis of 2D-NMR (COSY, HMQC, HMBC and NOESY) analyses. The isolated components were evaluated with a reporter gene assay that measures their anti-liver fibrosis activity. Compounds 1, 2, 4, 11, 13, 14 and 18 exhibited significant anti-inflammatory activity on HSC-T6 test.

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