Staff Profile

@article{pmid38709852,

title = {Challenges of COVID-19 Case Forecasting in the US, 2020-2021},

author = {Velma K Lopez and Estee Y Cramer and Robert Pagano and John M Drake and Eamon B O'Dea and Madeline Adee and Turgay Ayer and Jagpreet Chhatwal and Ozden O Dalgic and Mary A Ladd and Benjamin P Linas and Peter P Mueller and Jade Xiao and Johannes Bracher and Alvaro J Castro Rivadeneira and Aaron Gerding and Tilmann Gneiting and Yuxin Huang and Dasuni Jayawardena and Abdul H Kanji and Khoa Le and Anja M\"{u}hlemann and Jarad Niemi and Evan L Ray and Ariane Stark and Yijin Wang and Nutcha Wattanachit and Martha W Zorn and Sen Pei and Jeffrey Shaman and Teresa K Yamana and Samuel R Tarasewicz and Daniel J Wilson and Sid Baccam and Heidi Gurung and Steve Stage and Brad Suchoski and Lei Gao and Zhiling Gu and Myungjin Kim and Xinyi Li and Guannan Wang and Lily Wang and Yueying Wang and Shan Yu and Lauren Gardner and Sonia Jindal and Maximilian Marshall and Kristen Nixon and Juan Dent and Alison L Hill and Joshua Kaminsky and Elizabeth C Lee and Joseph C Lemaitre and Justin Lessler and Claire P Smith and Shaun Truelove and Matt Kinsey and Luke C Mullany and Kaitlin Rainwater-Lovett and Lauren Shin and Katharine Tallaksen and Shelby Wilson and Dean Karlen and Lauren Castro and Geoffrey Fairchild and Isaac Michaud and Dave Osthus and Jiang Bian and Wei Cao and Zhifeng Gao and Juan Lavista Ferres and Chaozhuo Li and Tie-Yan Liu and Xing Xie and Shun Zhang and Shun Zheng and Matteo Chinazzi and Jessica T Davis and Kunpeng Mu and Ana Pastore Y Piontti and Alessandro Vespignani and Xinyue Xiong and Robert Walraven and Jinghui Chen and Quanquan Gu and Lingxiao Wang and Pan Xu and Weitong Zhang and Difan Zou and Graham Casey Gibson and Daniel Sheldon and Ajitesh Srivastava and Aniruddha Adiga and Benjamin Hurt and Gursharn Kaur and Bryan Lewis and Madhav Marathe and Akhil Sai Peddireddy and Przemyslaw Porebski and Srinivasan Venkatramanan and Lijing Wang and Pragati V Prasad and Jo W Walker and Alexander E Webber and Rachel B Slayton and Matthew Biggerstaff and Nicholas G Reich and Michael A Johansson},

doi = {10.1371/journal.pcbi.1011200},

issn = {1553-7358},

year  = {2024},

date = {2024-05-01},

journal = {PLoS Comput Biol},

volume = {20},

number = {5},

pages = {e1011200},

abstract = {During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a na\"{i}ve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37302445,

title = {Hepatocellular Carcinoma Incidence Threshold for Surveillance in Virologically Cured Hepatitis C Individuals},

author = {Jagpreet Chhatwal and Ali Hajjar and Peter P Mueller and Gizem Nemutlu and Neeti Kulkarni and Mary Linton B Peters and Fasiha Kanwal},

doi = {10.1016/j.cgh.2023.05.024},

issn = {1542-7714},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {Clin Gastroenterol Hepatol},

volume = {22},

issue = {1},

pages = {91-101},

abstract = {BACKGROUND \& AIMS: Guidelines recommend biannual surveillance for hepatocellular carcinoma (HCC) in hepatitis C individuals with cirrhosis if the HCC incidence rate is above 1.5 per 100 person-years (PY). However, the incidence threshold for surveillance in individuals who achieve a virologic cure is unknown. We estimated the HCC incidence rate above which routine HCC surveillance is cost-effective in this growing population of virologically cured hepatitis C individuals with cirrhosis or advanced fibrosis.nnMETHODS: We developed a Markov-based microsimulation model of the natural history of HCC in individuals with hepatitis C who achieved virologic cure with oral direct-acting antivirals. We used published data on the natural history of hepatitis C, competing risk post virologic cure, HCC tumor progression, real-world HCC surveillance adherence, contemporary HCC treatment options and associated costs, and utilities of different health states. We estimated the HCC incidence above which biannual HCC surveillance using ultrasound and alpha-fetoprotein would be cost-effective.nnRESULTS: In virologically cured hepatitis C individuals with cirrhosis or advanced fibrosis, HCC surveillance is cost-effective if HCC incidence exceeds 0.7 per 100 PY using $100,000 per quality-adjusted life year willingness-to-pay. At this HCC incidence, routine HCC surveillance would result in 2650 and 5700 additional life years per 100,000 cirrhosis and advanced fibrosis persons, respectively, compared with no surveillance. At $150,000 willingness-to-pay, surveillance is cost-effective if HCC incidence exceeds 0.4 per 100 PY. Sensitivity analysis showed that the threshold mostly remained below 1.5 per 100 PY.nnCONCLUSIONS: The contemporary HCC incidence threshold is much lower than the previous 1.5% incidence value used to guide HCC surveillance decisions. Updating clinical guidelines could improve the early diagnosis of HCC.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37461007,

title = {A multimorbidity model for estimating health outcomes from the syndemic of injection drug use and associated infections in the United States},

author = {John J Chiosi and Peter P Mueller and Jagpreet Chhatwal and Andrea L Ciaranello},

doi = {10.1186/s12913-023-09773-1},

issn = {1472-6963},

year  = {2023},

date = {2023-07-17},

urldate = {2023-07-01},

journal = {BMC Health Serv Res},

volume = {23},

number = {1},

pages = {760},

abstract = {BACKGROUND: Fatal drug overdoses and serious injection-related infections are rising in the US. Multiple concurrent infections in people who inject drugs (PWID) exacerbate poor health outcomes, but little is known about how the synergy among infections compounds clinical outcomes and costs. Injection drug use (IDU) converges multiple epidemics into a syndemic in the US, including opioid use and HIV. Estimated rates of new injection-related infections in the US are limited due to widely varying estimates of the number of PWID in the US, and in the absence of clinical trials and nationally representative longitudinal observational studies of PWID, simulation models provide important insights to policymakers for informed decisions.nnMETHODS: We developed and validated a MultimorbiditY model to Reduce Infections Associated with Drug use (MYRIAD). This microsimulation model of drug use and associated infections (HIV, hepatitis C virus [HCV], and severe bacterial infections) uses inputs derived from published data to estimate national level trends in the US. We used Latin hypercube sampling to calibrate model output against published data from 2015 to 2019 for fatal opioid overdose rates. We internally validated the model for HIV and HCV incidence and bacterial infection hospitalization rates among PWID. We identified best fitting parameter sets that met pre-established goodness-of-fit targets using the Pearson's chi-square test. We externally validated the model by comparing model output to published fatal opioid overdose rates from 2020.nnRESULTS: Out of 100 sample parameter sets for opioid use, the model produced 3 sets with well-fitting results to key calibration targets for fatal opioid overdose rates with Pearson's chi-square test ranging from 1.56E-5 to 2.65E-5, and 2 sets that met validation targets. The model produced well-fitting results within validation targets for HIV and HCV incidence and serious bacterial infection hospitalization rates. From 2015 to 2019, the model estimated 120,000 injection-related overdose deaths, 17,000 new HIV infections, and 144,000 new HCV infections among PWID.nnCONCLUSIONS: This multimorbidity microsimulation model, populated with data from national surveillance data and published literature, accurately replicated fatal opioid overdose, incidence of HIV and HCV, and serious bacterial infections hospitalization rates. The MYRIAD model of IDU could be an important tool to assess clinical and economic outcomes related to IDU behavior and infections with serious morbidity and mortality for PWID.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37294571,

title = {Estimated Reductions in Opioid Overdose Deaths With Sustainment of Public Health Interventions in 4 US States},

author = {Jagpreet Chhatwal and Peter P Mueller and Qiushi Chen and Neeti Kulkarni and Madeline Adee and Gary Zarkin and Marc R LaRochelle and Amy B Knudsen and Carolina Barbosa},

doi = {10.1001/jamanetworkopen.2023.14925},

issn = {2574-3805},

year  = {2023},

date = {2023-06-01},

journal = {JAMA Netw Open},

volume = {6},

number = {6},

pages = {e2314925},

abstract = {IMPORTANCE: In 2021, more than 80 000 US residents died from an opioid overdose. Public health intervention initiatives, such as the Helping to End Addiction Long-term (HEALing) Communities Study (HCS), are being launched with the goal of reducing opioid-related overdose deaths (OODs).nnOBJECTIVE: To estimate the change in the projected number of OODs under different scenarios of the duration of sustainment of interventions, compared with the status quo.nnDESIGN, SETTING, AND PARTICIPANTS: This decision analytical model simulated the opioid epidemic in the 4 states participating in the HCS (ie, Kentucky, Massachusetts, New York, and Ohio) from 2020 to 2026. Participants were a simulated population transitioning from opioid misuse to opioid use disorder (OUD), overdose, treatment, and relapse. The model was calibrated using 2015 to 2020 data from the National Survey on Drug Use and Health, the US Centers for Disease Control and Prevention, and other sources for each state. The model accounts for reduced initiation of medications for OUD (MOUDs) and increased OODs during the COVID-19 pandemic.nnEXPOSURE: Increasing MOUD initiation by 2- or 5-fold, improving MOUD retention to the rates achieved in clinical trial settings, increasing naloxone distribution efforts, and furthering safe opioid prescribing. An initial 2-year duration of interventions was simulated, with potential sustainment for up to 3 additional years.nnMAIN OUTCOMES AND MEASURES: Projected reduction in number of OODs under different combinations and durations of sustainment of interventions.nnRESULTS: Compared with the status quo, the estimated annual reduction in OODs at the end of the second year of interventions was 13% to 17% in Kentucky, 17% to 27% in Massachusetts, 15% to 22% in New York, and 15% to 22% in Ohio. Sustaining all interventions for an additional 3 years was estimated to reduce the annual number of OODs at the end of the fifth year by 18% to 27% in Kentucky, 28% to 46% in Massachusetts, 22% to 34% in New York, and 25% to 41% in Ohio. The longer the interventions were sustained, the better the outcomes; however, these positive gains would be washed out if interventions were not sustained.nnCONCLUSIONS AND RELEVANCE: In this decision analytical model study of the opioid epidemic in 4 US states, sustained implementation of interventions, including increased delivery of MOUDs and naloxone supply, was found to be needed to reduce OODs and prevent deaths from increasing again.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Mueller2022,

title = {Duration and cost-effectiveness of hepatocellular carcinoma surveillance in hepatitis C patients after viral eradication.},

author = {Peter P. Mueller and Qiushi Chen and Turgay Ayer and Gizem Nemutlu and Ali Hajjar and Emily D. Bethea and Mary Linton B. Peters and Brian P. Lee and Naveed Z. Janjua and Fasiha Kanwal and Jagpreet Chhatwal},

url = {https://pubmed.ncbi.nlm.nih.gov/35157959/},

doi = {10.1016/j.jhep.2022.01.027},

issn = {1600-0641},

year  = {2022},

date = {2022-07-01},

urldate = {2022-02-01},

journal = {Journal of hepatology},

volume = {77},

issue = {1},

pages = {55-62},

abstract = {Successful treatment of chronic hepatitis C with oral direct-acting antiviral (DAA) leads to virological cure, however, the subsequent risk of hepatocellular carcinoma (HCC) persists. Our objective was to evaluate the cost-effectiveness of biannual surveillance for HCC in patients cured of hepatitis C and the optimal age to stop surveillance. We developed a microsimulation model of the natural history of HCC in hepatitis C individuals with advanced fibrosis or cirrhosis who achieved virological cure with oral DAAs. We used published data on HCC incidence, tumor progression, real-world HCC surveillance adherence, and costs and utilities of different health states. We compared biannual HCC surveillance using ultrasound and alpha-fetoprotein for varying durations of surveillance (from 5 years to lifetime) versus no surveillance. In virologically-cured patients with cirrhosis, the ICER of biannual surveillance remained below $150,000 per additional quality-adjusted life year (QALY) (range: $79,500-$94,800) when surveillance was stopped at age 70, irrespective of the start age (40-65). Compared with no surveillance, surveillance per 1000 cirrhosis patients detected 130 additional HCCs in 'very early'/early stage and yielded 51 additional QALYs. In virologically-cured patients with advanced fibrosis, the ICER of biannual surveillance remained below $150,000/QALY (range: $124,600-$129,800) when surveillance was stopped at age 60, irrespective of the start age (40-50). Compared with no surveillance, surveillance per 1000 advanced fibrosis patients detected 24 additional HCCs in 'very early'/early stage and yielded 12 additional QALYs. Biannual surveillance for HCC in virologically-cured hepatitis C patients is cost-effective until the age of 70 for cirrhosis patients, and until the age of 60 for patients with stable advanced fibrosis. Individuals who are cured of hepatitis C using oral antiviral drugs remain at risk of developing liver cancer. The value of lifelong screening for liver cancer in these individuals is not known. By simulating the life course of hepatitis C cured individuals, we found that ultrasound-based bi-annual screening for liver cancer is cost-effective up to age 70 in those having cirrhosis and up to age 60 in those having stable advanced fibrosis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35783994,

title = {What is the prevalence of and trend in opioid use disorder in the United States from 2010 to 2019? Using multiplier approaches to estimate prevalence for an unknown population size},

author = {Katherine M Keyes and Caroline Rutherford and Ava Hamilton and Joshua A Barocas and Kitty H Gelberg and Peter P Mueller and Daniel J Feaster and Nabila El-Bassel and Magdalena Cerd\'{a}},

doi = {10.1016/j.dadr.2022.100052},

issn = {2772-7246},

year  = {2022},

date = {2022-06-01},

journal = {Drug Alcohol Depend Rep},

volume = {3},

abstract = {Opioid-related overdose deaths have increased since 2010 in the U.S., but information on trends in opioid use disorder (OUD) prevalence is limited due to unreliable data. Multiplier methods are a classical epidemiological technique to estimate prevalence when direct estimation is infeasible or unreliable. We used two different multiplier approaches to estimate OUD prevalence from 2010 to 2019. First, we estimated OUD in National Survey on Drug Use and Health (NSDUH), and based on existing capture-recapture studies, multiplied prevalence by 4.5x. Second, we estimated the probability of drug poisoning death among people with OUD (Meta-analysis indicates 0.52/100,000), and divided the number of drug poisoning deaths in the US by this probability. Estimates were weighted to account for increase in drug-related mortality in recent years due to fentanyl. Estimated OUD prevalence was lowest when estimated in NSDUH with no multiplier, and highest when estimated from vital statistics data without adjustment. Consistent findings emerged with two methods: NSDUH data with multiplier correction, and vital statistics data with multiplier and adjustment. From these two methods, OUD prevalence increased from 2010 to 2014; then stabilized and slightly declined annually (survey data with multiplier, highest prevalence of 4.0% in 2015; death data with a multiplier and correction, highest prevalence of 2.35% in 2016). The number of US adolescent and adult individuals with OUD in 2019 was estimated between 6.7-7.6 million. When multipliers and corrections are used, OUD may have stabilized or slightly declined after 2015. Nevertheless, it remains highly prevalent, affecting 6-7 million US adolescents and adults.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35977324,

title = {Projecting COVID-19 Mortality as States Relax Nonpharmacologic Interventions},

author = {Benjamin P Linas and Jade Xiao and Ozden O Dalgic and Peter P Mueller and Madeline Adee and Alec Aaron and Turgay Ayer and Jagpreet Chhatwal},

doi = {10.1001/jamahealthforum.2022.0760},

issn = {2689-0186},

year  = {2022},

date = {2022-04-01},

journal = {JAMA Health Forum},

volume = {3},

number = {4},

pages = {e220760},

abstract = {Importance: A key question for policy makers and the public is what to expect from the COVID-19 pandemic going forward as states lift nonpharmacologic interventions (NPIs), such as indoor mask mandates, to prevent COVID-19 transmission.



Objective: To project COVID-19 deaths between March 1, 2022, and December 31, 2022, in each of the 50 US states, District of Columbia, and Puerto Rico assuming different dates of lifting of mask mandates and NPIs.



Design Setting and Participants: This simulation modeling study used the COVID-19 Policy Simulator compartmental model to project COVID-19 deaths from March 1, 2022, to December 31, 2022, using simulated populations in the 50 US states, District of Columbia, and Puerto Rico. Projected current epidemiologic trends for each state until December 31, 2022, assuming the current pace of vaccination is maintained into the future and modeling different dates of lifting NPIs.



Exposures: Date of lifting statewide NPI mandates as March 1, April 1, May 1, June 1, or July 1, 2022.



Main Outcomes and Measures: Projected COVID-19 incident deaths from March to December 2022.



Results: With the high transmissibility of current circulating SARS-CoV-2 variants, the simulated lifting of NPIs in March 2022 was associated with resurgences of COVID-19 deaths in nearly every state. In comparison, delaying by even 1 month to lift NPIs in April 2022 was estimated to mitigate the amplitude of the surge. For most states, however, no amount of delay was estimated to be sufficient to prevent a surge in deaths completely. The primary factor associated with recurrent epidemics in the simulation was the assumed high effective reproduction number of unmitigated viral transmission. With a lower level of transmissibility similar to those of the ancestral strains, the model estimated that most states could remove NPIs in March 2022 and likely not see recurrent surges.



Conclusions and Relevance: This simulation study estimated that the SARS-CoV-2 virus would likely continue to take a major toll in the US, even as cases continued to decrease. Because of the high transmissibility of the recent Delta and Omicron variants, premature lifting of NPIs could pose a substantial threat of rebounding surges in morbidity and mortality. At the same time, continued delay in lifting NPIs may not prevent future surges.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Linas2021,

title = {A clash of epidemics: Impact of the COVID-19 pandemic response on opioid overdose.},

author = {Benjamin P Linas and Alexandra Savinkina and Carolina Barbosa and Peter P. Mueller and Magdalena Cerd\'{a} and Katherine Keyes and Jagpreet Chhatwal},

url = {https://pubmed.ncbi.nlm.nih.gov/33298298/},

doi = {10.1016/j.jsat.2020.108158},

issn = {1873-6483},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Journal of substance abuse treatment},

volume = {120},

pages = {108158},

abstract = {Coronavirus disease 2019 (COVID-19) will have a lasting impact on public health. In addition to the direct effects of COVID-19 infection, physical distancing and quarantine interventions have indirect effects on health. While necessary, physical distancing interventions to control the spread of COVID-19 could have multiple impacts on people living with opioid use disorder, including impacts on mental health that lead to greater substance use, the availability of drug supply, the ways that people use drugs, treatment-seeking behaviors, and retention in care. The degree to which COVID-19 will impact the opioid epidemic and through which of the possible mechanisms that we discuss is important to monitor. We employed simulation modeling to demonstrate the potential impact of physical distancing on overdose mortality.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1001/jamanetworkopen.2018.7621,

title = {Prevention of Prescription Opioid Misuse and Projected Overdose Deaths in the United States},

author = {Qiushi Chen and Marc R. Larochelle and Davis Weaver and Anna Lietz and Peter P. Mueller and Sarah Fletcher Mercaldo and Sarah E. Wakeman and Kenneth A. Freedberg and Tiana Raphel and Amy Knudsen and Pari Pandharipande and Jagpreet Chhatwal},

url = {https://dx.doi.org/10.1001/jamanetworkopen.2018.7621},

doi = {10.1001/jamanetworkopen.2018.7621},

issn = {2574-3805},

year  = {2019},

date = {2019-02-01},

journal = {JAMA Network Open},

volume = {2},

number = {2},

pages = {e187621-e187621},

abstract = {Deaths due to opioid overdose have tripled in the last decade. Efforts to curb this trend have focused on restricting the prescription opioid supply; however, the near-term effects of such efforts are unknown.To project effects of interventions to lower prescription opioid misuse on opioid overdose deaths from 2016 to 2025.This system dynamics (mathematical) model of the US opioid epidemic projected outcomes of simulated individuals who engage in nonmedical prescription or illicit opioid use from 2016 to 2025. The analysis was performed in 2018 by retrospectively calibrating the model from 2002 to 2015 data from the National Survey on Drug Use and Health and the Centers for Disease Control and Prevention.Comparison of interventions that would lower the incidence of prescription opioid misuse from 2016 to 2025 based on historical trends (a 7.5% reduction per year) and 50% faster than historical trends (an 11.3% reduction per year), vs a circumstance in which the incidence of misuse remained constant after 2015.Opioid overdose deaths from prescription and illicit opioids from 2016 to 2025 under each intervention.Under the status quo, the annual number of opioid overdose deaths is projected to increase from 33 100 in 2015 to 81 700 (95% uncertainty interval [UI], 63 600-101 700) in 2025 (a 147% increase from 2015). From 2016 to 2025, 700 400 (95% UI, 590 200-817 100) individuals in the United States are projected to die from opioid overdose, with 80% of the deaths attributable to illicit opioids. The number of individuals using illicit opioids is projected to increase by 61%\textemdashfrom 0.93 million (95% UI, 0.83-1.03 million) in 2015 to 1.50 million (95% UI, 0.98-2.22 million) by 2025. Across all interventions tested, further lowering the incidence of prescription opioid misuse from 2015 levels is projected to decrease overdose deaths by only 3.0% to 5.3%.This study’s findings suggest that interventions targeting prescription opioid misuse such as prescription monitoring programs may have a modest effect, at best, on the number of opioid overdose deaths in the near future. Additional policy interventions are urgently needed to change the course of the epidemic.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{CHHATWAL2018819,

title = {Hep C Calculator: an online tool for cost-effectiveness analysis of DAAs},

author = {Jagpreet Chhatwal and Qiushi Chen and Emily Bethea and Mary Ann Ladd and Peter P. Mueller and Yvan Hutin and Rakesh Aggarwal},

url = {http://www.sciencedirect.com/science/article/pii/S2468125318302814},

doi = {https://doi.org/10.1016/S2468-1253(18)30281-4},

issn = {2468-1253},

year  = {2018},

date = {2018-12-01},

urldate = {2018-12-01},

journal = {The Lancet Gastroenterology \& Hepatology},

volume = {3},

number = {12},

pages = {819},

keywords = {},

pubstate = {published},

tppubtype = {article}

}