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Dengue Immunity May Protect Against Zika

mosquitoAn international team of scientists led by the University of Pittsburgh Graduate School of Public Health, Yale School of Public Health, and the University of Florida reported in the February issue of Science that the higher a person's immunity to dengue virus, the lower their risk of Zika infection. The study, which followed nearly 1,500 people living in a poor neighborhood at the heart of the 2015 Zika outbreak in Brazil, also provides evidence that Brazil's Zika epidemic has largely petered out because enough people acquired immunity to reduce the efficiency of transmission. "Take that with a grain of salt, though. Our study was in a very small urban area, and it is likely that in other parts of Brazil, even different neighborhoods within the same city, people are still susceptible to Zika infection," said co-senior author Ernesto T.A. Marques, M.D., Ph.D., associate professor in Pitt Public Health's Department of Infectious Diseases and Microbiology and public health researcher at Fundação Oswaldo Cruz in Brazil.

Paradoxically, computational models by co-senior author Derek A.T. Cummings, PhD, professor of biology at the University of Florida, showed that participants who had a very recent dengue infection were actually more susceptible to Zika. Possible explanations include protective antibodies have not developed yet or there is something about the immune systems of these people that increases their risk of contracting Zika; or the mosquitoes that transmit dengue also transmit Zika, so a recent dengue infection could mean they are in a place where Zika transmission is active as well. Additional study is needed to determine how these findings could prove useful to clinicians.

PHDL Participates in Disease Modelling Meeting in India

DMPH Discussion Meeting Group Photo
DMPH Workshop Group Photo

Dr. Saumyadipta Pyne, Scientific Director of the Public Health Dynamics Lab (PHDL) at Pitt Public Health, was a co-organizer of a week long discussion meeting and workshop on Mathematical and Statistical Explorations in Disease Modelling and Public Health held in July in Bangalore, India. The aims of this meeting included: 1) exploring different mathematical, statistical and computational approaches to integrate experimental and clinical data, and; 2) discussion on how mathematical modeling can help to interpret and integrate experimental data, frame and test hypotheses, and suggest novel experiments allowing for more conclusive and quantitative interpretations of biological, immunological and disease-related processes.

Dr. David Sinclair, PHDL Post-doctoral Researcher, highlighted the PHDL's agent-based modeling system FRED (A Framework for Reconstructing Epidemiological Dynamics), in his July 1st presentation on "Forecasted size of measles outbreaks associated with vaccination exemptions for school children". Though measles was eliminated from the US in 2000, over the last decade outbreaks continue to occur due to international travel and exemptions from mandatory Measles immunization for all school children based on personal and or religious reasons. Dr. Sinclair discussed the efforts to estimate potential outbreak sizes using an agent-based model, populated with synthetic representation of the US state of Texas.

Dr. Saumyadipta Pyne delivered a virtual presentation on July 4th on "Hierarchical modeling of high-dimensional human immuno-phenotypic diversity". Dr. Pyne described the computational frameworks developed with a focus on fast and automatic modeling and identification of different cell populations, their hierarchical structures and inter-relationships under different biological conditions.

 

PHDL Scientific Director Inaugural Lecturer

Dr. Saumyadipta Pyne, Scientific Director of Public Health Dynamics Lab and faculty member of Biostatistics, University of Pittsburgh Graduate School of Public Health, will be delivering the first Dr. Dipankar Chakraborti Memorial Lecture on 'Geostatistical Prediction Models in Public Health' at Jadavpur University, India, on March 15, 2019. Dr. Pyne was recently appointed an Honorary Adviser to India's National Institute of Medical Statistics in New Delhi.

who Picture1(Picture courtesy of World Health Organization)

In the ongoing fight against what is regarded as "the largest mass poisoning of a population in history because groundwater used for drinking has been contaminated with naturally occurring inorganic arsenic" in parts of South Asia, Dr. Dipankar Chakraborti (1943-2018) was among the foremost global leaders. Dr. Chakraborti (popularly known as Dip), a dedicated field researcher and environmental chemist, was also committed to welfare of the victims of this geogenic environmental exposure.

In the late 1980s, Dr. Chakraborti left his academic position in the U.S. to return to India to direct the School of Environmental Studies at Jadavpur University. His extensive research highlighted the severity of groundwater arsenic contamination in the Ganga River Basin (GRB), which encompasses significant geographic portions of India, Bangladesh, Nepal, and Tibet. His team studied several populations for dermal, neurological, reproductive, cognitive, and cancerous effects of arsenicosis.

In his last paper, Dr. Chakraborti noted, "This alarming situation resembles a ticking time bomb. We feel that after 29 years of arsenic research in the GRB, we have seen the tip of the iceberg with respect to the actual magnitude of the catastrophe."

Drug Overdose Deaths Rising Exponentially

overdose mortality rate graphicIn the September 20 issue of Science, PDHL researchers revealed a paradox in drug overdose deaths that challenges the prevailing perception of the epidemic. They revealed that the overall death rates from drug overdoses in the U.S. have been on an exponential growth curve for nearly 40 years despite all the rises and falls of deaths due to individual drugs. This trajectory began at least 15 years before the mid-1990s surge in opioid prescribing, suggesting that overdose death rates may continue along this same historical growth trajectory for years to come. When use of one drug has declined, another has moved in to fill the void. "This smooth, exponential growth pattern caught us by surprise," Donald Burke, dean of the University of Pittsburgh Graduate School of Public Health, and the study's senior author, said in an interview with ABC news. After analyzing data from nearly 600,000 deaths attributed to drug overdose from the National Vital Statistics System, the researchers saw that the overdoses followed an almost perfectly exponential trajectory over the 38-year period from when the reporting first began in 1979 to 2016. The death rate due to overdoses doubled approximately every 9 years – by 2016 it was up to one death every 8 minutes.

The complexity behind the trend means that slowing or stopping the curve will require deeper changes than just cracking down on one substance or another, the authors said. "The dynamic is very complicated," stated Hawre Jalal, assistant professor of health policy and management, and lead author of the analysis, in an interview with the Wall Street Journal. "It's unlikely it will respond to a specific drug or age category. It will need a much, much more comprehensive intervention."

Modeling Conference art

Fall 2018 Modeling Behavior Conference and Workshop

A Modeling Social Dynamics and Health Behavior Conference will be sponsored by The Center for Social Dynamics & Community Health, the Public Health Dynamics Laboratory (PHDL) and the Clinical and Translational Science Institute (CTSI) at the University of Pittsburgh on Friday, October 26, 2018. This conference will bring together national leaders from across the country to discuss the integration of modeling approaches into the field of behavior and community health sciences. Through panel discussions and breakout sessions, attendees will learn about existing research, discuss associated challenges and opportunities, and chart a path forward for this emerging field. Keynote speaker will be Thomas W. Valente, PhD, Professor of Preventive Medicine, Institute for Prevention Research, Keck School of Medicine, University of Southern California.

A half-day Pre-Conference Behavior Modeling Workshop will be hosted at the University of Pittsburgh Graduate School of Public Health on Thursday, October 25, 2018. The workshop will highlight modeling using the Framework for Reconstructing Epidemiological Dynamics (FRED), an agent-based modeling and simulation platform.

There no is cost and registration is required for both events. Learn more, and register by October 12, 2018 at www.ctsi.pitt.edu/modeling. Click here to read the announcement.

Project Tycho Version 2.0

Project Tycho 2.0 has become a repository for global health data in a standardized format that is more compliant with FAIR (Findable, Accessible, Interoperable, and Reusable) guidelines. The Project Tycho team continues to conduct research in the areas of infectious disease epidemiology and global health informatics, but also provides services to help health agencies and researchers to improve access and use of global health data.

In 2013, the first version of Project Tycho was released containing weekly case counts for 50 notifiable conditions reported by health agencies in the United States for 50 states and 1284 cities between 1888 and 2014. Over the past four years, over 3,000 users have registered to use Project Tycho data for a total of 40 creative works, including peer-reviewed research papers, visualizations, online applications, and newspaper articles.

The second version of Project Tycho has expanded its scope to a global level. The database now includes more data and is more extensively standardized. Project Tycho 2.0 includes case counts for 28 additional notifiable conditions for the US and includes data for dengue-related conditions for 100 countries between 1955 and 2010, obtained from the World Health Organization and national health agencies. Project Tycho 2.0 datasets are represented in a standard format registered with FAIRsharing (bsg-s000718) and includes standard codes to help integrate Project Tycho datasets with other datasets.

In addition to the data, the Project Tycho website (https://www.tycho.pitt.edu/) has been updated. More features will be added in the near future for an optimal user experience.

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