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Coming Soon: New Release of FRED

New Release!A new version of FRED (A Framework for Reconstructing Epidemiological Dynamics) will soon be ready for release. FRED is a tool for building epidemiological agent-based (individual-based) models and is designed to study how patterns of health conditions in defined populations vary over time. The new FRED will make population modeling easier. It is a unique tool for social science modeling and no computer programming is needed. A systems thinking approach is required to identify conditions of interest, their states, and the rules for changing states. FRED will simplify the workflow environment and manage the data produced by the simulation. To read more about the new FRED platform, click here.

 

 

The Classics

nature coverIn June 2017, Google Scholar released a collection of highly-cited papers in their area of research that have stood the test of time. These Classic Papers were published in 2006 and the list includes the ten most-cited articles, proving that though research is often about the latest findings, some have an impact long after their publication.

We are proud to report that in the field of epidemiology, the Classic Papers list includes a 2006 publication co-authored by Dean Donald Burke, who was at Johns Hopkins University at the time, and others from Johns Hopkins, Imperial College London, and RTI. Not only was the Nature paper "Strategies for mitigating an influenza pandemic" included on the list, it had 1500 citations and was the #1 most cited article in the field of epidemiology!

Congratulations to Dean Burke and his co-authors!

 

Computer model increases effectiveness of Republic of Benin vaccination program

"A team of researchers recently used modeling software to aid West Africa's Republic of Benin in determining how to bring more lifesaving vaccines to its children.

The HERMES Logistics Modeling Team, made up of researchers from the Pittsburgh Supercomputing Center, the University of Pittsburgh School of Engineering and the Johns Hopkins Bloomberg School of Public Health, reported its findings this month in the journal Vaccine.

The HERMES model’s results have aided the Republic of Benin in enacting initial changes to its vaccines delivery system, which could lead to additional changes nationwide."

Read the full article at Vaccine News Daily

Project Tycho™ study estimates that 100 million cases of contagious diseases have been prevented by vaccination programs in the United States since 1924

Project Tycho™In a paper published November 28, 2013, in the New England Journal of Medicine entitled "Contagious diseases in the United States from 1888 to the Present", Project Tycho™ authors describe how U.S. disease surveillance data have been used to estimate that over 100 million cases have been prevented by vaccination programs against polio, measles, mumps, rubella, hepatitis A, diphtheria, and pertussis (whooping cough). Vaccination programs against these diseases have been in place for over decades but epidemics continue to occur. Despite the availability of a pertussis vaccine since the 1920s, the largest pertussis epidemic in the U.S. since 1959 occurred last year. This study was funded by the Bill & Melinda Gates Foundation and the National Institutes of Health and all data used for this study have been released through the online Project Tycho™ data system (www.tycho.pitt.edu). "Historical records are a precious yet undervalued resource. As Danish philosopher Soren Kierkegaard said, we live forward but understand backward," explained Dr. Donald Burke, senior author on the paper. "By 'rescuing' these historical disease data and combining them into a single, open-access, computable system, we can now better understand the devastating impact of epidemic diseases, and the remarkable value of vaccines in preventing illness and death."

 

Lack of Reliable Transportation Undermines Delivery of Lifesaving Vaccines

"Transportation of vaccines is a critical component for improving vaccination rates in low-income countries and warrants more attention, according to a computer simulation by the HERMES Logistics Modeling Team at the University of Pittsburgh and Pittsburgh Supercomputing Center (PSC). The team recently reported their findings in the PLOS ONE online journal (http://dx.plos.org/10.1371/journal.pone.0064303)."

Read the full article at the Pittsburgh Supercomputing Center website

UMass Amherst, International Research Team Improve Immunization Strategies for Dengue Fever in Thailand

Reich, NickAMHERST, Mass. – Using a unique data set spanning 40 years of dengue fever incidence in Thailand, an international team led by biostatistician Nicholas Reich at the University of Massachusetts Amherst has for the first time estimated from data that after an initial dengue infection, a person is protected from infection with other strains for between one and three years.
 
Their results have implications for designing more effective vaccine studies, say Reich and colleagues at the Johns Hopkins Bloomberg School of Public Health, the University of Michigan and the Armed Forces Research Institute of Medical Sciences (AFRIMS) in Bangkok. Findings appear in the current issue of the Journal of the Royal Society Interface.
 
Dengue fever is a mosquito-transmitted viral infection that sickens 5 percent of the world’s population each year and recently has begun to emerge in parts of the southeast United States. Building on a long-standing collaboration with Thai health officials and AFRIMS, Reich and his co-authors used the Bangkok dataset to characterize this important clinical and epidemiological feature, cross-protection. It means one’s immune response to infection with one dengue strain offers some protection against future infection with others.
 
They report the first explicit quantitative evidence that short-term cross-protection exists since human experimental infection studies performed in the 1940s and 1950s by Albert Sabin. By extending existing methods for analyzing infectious disease time-series data, they have created and applied a new framework for estimating the duration and strength of cross-protection between multiple strains of an infectious disease, Reich points out.
 
“This dataset from Bangkok is unique,” he says. “We don’t know of any other data like this in the world. AFRIMS has been collecting this data, with strain-specific information on individual cases of dengue, for over 40 years. It provided us with a unique opportunity to analyze long-term disease patterns in ways that we are not able to do with datasets of shorter duration.”
 
Epidemiologists know that many multi-strain diseases confer at least partial short-term cross-protection to people who come down with one. But cross-protection introduces “significant challenges” to researchers trying to create an accurate model of disease transmission or to evaluate vaccine effectiveness. Knowing how long cross-protection may last can help in planning well-controlled vaccine studies.
 
“Dengue is a unique and convenient disease for studying these dynamics of cross-protection,” says Reich. “Many diseases either evolve too rapidly, like influenza, or have too many circulating subtypes, like malaria, for us to gain good traction on studying cross-protection. But dengue is sort of a ‘goldilocks’ virus in this way. It has four circulating strains, which means that it’s in sort of a genetic diversity ‘sweet spot.’ There are not too many strains and not too few, which provides us with fertile ground for such study.”
 
Reich and colleagues’ database consists of monthly, lab-confirmed dengue fever case counts for each strain for 38 years, from 1973 to 2010, at Queen Sirikit National Institute of Child Health (NICH) in Bangkok. Analyzing a total of 12,197 infections, they developed a new type of statistical model to help them weigh the evidence for and against the existence of cross-protection.
 
“We made head-to-head comparisons of models that included cross-protection and those that did not,” Reich explains. “We essentially let different models compete with each other to explain the data best. And each model makes different hypotheses about how dengue works once it infects you. Consistently, when we look at models that are saying ‘cross-protection exists,’ they fit the data better than models that are saying ‘cross-protection does not exist.’ Also, these models are able to explain more of the variability that we see in the irregular size of annual epidemics in Thailand.”
 
The team’s statistical model tested a wide range of possible durations of cross-protection, using a statistical technique called maximum likelihood to find the single duration and the range of durations that best explain the patterns observed in the data.
 
Other members of the research team are Sourya Shrestha, Aaron King and Pejman Rohani of the University of Michigan, Justin Lessler and Derek Cummings of Johns Hopkins, Siripen Kalayanarooj of Queen Sirikit NICH, In-Kyu Yoon and Robert Gibbons of AFRIMS and Donald Burke of the University of Pittsburgh.
 
The work was funded by the National Institute of General Medical Sciences at the National Institutes of Health and the Bill and Melinda Gates Foundation Vaccine Modeling Initiative.
 
Contact: Janet Lathrop
Contact Phone: 413/545-0444

Vaccine Work Continues at Pitt Public Health

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Peter Salk (standing, at left) recently welcomed Dean Donald Burke and Director of Development Kristen de Paor to visit the historic archives and warehoused materials of his father, world-famous public health pioneer Jonas Salk.

As Pitt Public Health looks forward to the centennial of Jonas Salk’s birth in 2014, the school continues its tradition of world-class contributions to research in disease prevention. Pitt Public Health is home to the Public Health Dynamics Laboratory. Led by Director John Grefenstette and Dean Donald Burke, the effort builds life-like computer simulations of the transmission of communicable infectious diseases, such as influenza, tuberculosis, and dengue.

The Public Health Dynamics Laboratory has joined the fight for the global eradication of polio. “Polio transmission rates have been greatly reduced to only a few hundred cases per year worldwide,” explains Willem van Panhuis, assistant professor of epidemiology. “Computational modeling is increasingly necessary to support decision making on polio eradication strategies.” A research group including van Panhuis, Burke, and Grefenstette is working with the Bill and Melinda Gates Foundation and the U.S. Centers for Disease Control and Prevention to obtain new sources of data and to use computational modeling to evaluate potential eradication strategies before they are used in real-world settings.

READ MORE...

Public Health Data Rescue in the Mekong

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The Vaccine Modeling Initiative (VMI) has developed collaborations with countries in the Southeast Asia Mekong region including Thailand, Laos, Cambodia and Vietnam. Through a partnership with Institut of Research for Development (IRD) in France, a dengue surveillance data digitization field project has been started in Laos. Disaggregated dengue surveillance data will be digitized from district and provincial health departments in Laos. Students from the Institut for Tropical Medicine (ITM) in Laos are visiting Provincial and District Health Departments and health clinics to scan and digitize (rescue) dengue surveillance data in two pilot provinces.

On May 23, Dr. Wilbert van Panhuis, a VMI investigator, and Dr. Marc Choisy from IRD, visited the Vientiane Capital Health Office to start planning dengue surveillance data collection and digitization. The Vientiane Capital Region includes nine district health centers and six central hospitals that serve a total population of about 800,000 people. This region reports the most dengue cases annually and is of great importance to this project. Institut Francophone pour la Medicine Tropicale (IFMT) students will arrive in June to start data collection.

A team from the University of Pittsburgh, IRD and IFMT and the National Center for Laboratory and Epidemiology in Laos , recently visited Savannakhet province to assess progress on dengue surveillance data collection. During this two day visit, the provincial health department, the provincial malaria station and provincial hospital were visited to review dengue surveillance documentation. In addition, two districts and two health centers were visited.

A Laos field blog (https://www.vaccinemodeling.org/index.php/laos-field-blog) has been started to follow this digitization project that is being conducted by students in collaboration with the Laos Ministry of Health.

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