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COVID-19 model for strategic lockdown policy

CO19 Outbreak lockdowns mapIn 1957, M.S. Bartlett, FRS, introduced the concept of critical community size (CCS) below which an infectious disease does not persist in a closed population. With a subaward from a NIH Fogarty grant (PI: D. Burke, Co-PI: C. Bunker, S. Pyne) for training disease modelers in India, Prof. Indranil Mukhopadhyay and Sarmistha Das of Indian Statistical Institute, and their collaborators, used CCS to develop a model of strategic and focused lockdown policy for COVID-19 in a given population. Saumyadipta Pyne is a co-author of the study, which was published in 'Statistics and Applications' in June 2020. Image courtesy: Wikipedia.

Probabilistic Event Detection using Data Fusion

PA Radon EPADr. Saumyadipta Pyne and collaborators (Prof. Benjamin Kedem and Xuze Zhang, University of Maryland) have developed a new statistical framework for real and synthetic data fusion to estimate exceedance probabilities in an observed stream of events with only a few observations. Starting with a baseline distribution,​ this method can model a dynamic distortion of that original template, and thus, be used for modeling environmental exposures. The study was published in 'Applied Stochastic Models in Business and Industry' in June 2020. Image courtesy: US EPA.

A Computational Model to Identify Rare Events in Big Data

i1Whether it is a forgotten shelf of classics in a large library, or a tiny collection of cells with special properties in our immune system, the presence of rare events in a large sample is often very hard to detect without precise guidance. The problem gets computationally even harder if the search space has many dimensions. Dr. Saumyadipta Pyne of PHDL led an inter-disciplinary team of researchers from Europe, Asia and the United States to develop an efficient solution using a Bayesian hierarchical model and powerful parallel inference.

PHDL Scientific Director Gives Prof. C.R. Rao Centenary Lecture

Rao and PyneDr. Saumyadipta Pyne, Scientific Director of PHDL and faculty member of Biostatistics, delivered the Prof. C.R. Rao Birth Centenary Lecture on January 2, 2020, at the Department of Statistics, University of Pune (formally, Savitribai Phule Pune University). Born in 1920, C.R. Rao, F.R.S., is known for his pioneering work that laid the foundations of many branches of statistics. It includes the topic of the lecture, "On weighted distributions and applications", featuring Pyne's recent work on environmental data fusion. Weighted distributions allow inference when it is difficult to observe random samples from a population under study. Rao was University Professor at the University of Pittsburgh in the 1980s when he established a unique Center for Multivariate Analysis at Pitt.

New PHDL members with geoinformatics background

Pedram Gharani and Raanan GurewitschDr. Pedram Gharani completed his PhD in Information Science at University of Pittsburgh in July 2019. His dissertation focused on sensor fusion for indoor positioning and obstacle detection. He joined as a postdoctoral associate at PHDL where he is working with Dr. S. Pyne on data fusion and population synthesis for public health.

Raanan Gurewitsch graduated with BPhil in Information Science at University of Pittsburgh in April 2019. His thesis involved geospatial data analysis to predict lead plumbing in Pittsburgh's water systems. Following a Civic Digital data science fellowship with the US Census Bureau, he joined PHDL to work with Dr. S. Pyne on mortality and environmental data analytics.

Lower Vaccination Rates Make Texas Cities Susceptible to Measles Outbreaks

Austin MeaslesA University of Pittsburgh Graduate School of Public Health study found that large and small cities in Texas are becoming increasingly vulnerable to measles outbreaks due to more parents exempting their children from required vaccinations. Texas is the largest state by population that allows parents to opt their children out of vaccinations for nonmedical reasons making it an interesting place to study measles outbreaks. If the vaccination rate among students in Texas continues to decrease in schools with undervaccinated populations, the potential number of cases associated with measles outbreaks is estimated to increase exponentially. The 2018 vaccination rates in multiple metropolitan areas may permit large measles outbreaks, which could infect not only vaccine refusers but also other members of the population. These findings, published in JAMA Open Network on August 21, 2019, indicate that an additional 5% decrease in vaccination rates, which have been on a downward trend since 2003, would increase the size of a potential measles outbreak by up to 4,000% in some communities.

The Texas Pediatric Society asked the University of Pittsburgh Graduate School of Public Health to model Texas using FRED (Framework for Reconstructing Epidemiological Dynamics), a software platform developed at the Pitt Graduate School of Public Health as a tool for creating simulation models of dynamic processes in human social systems. FRED allows researchers to see how measles could spread from person to person. According to lead author, David Sinclair, "If policy stays as it is and there is no change in the public's perspective of vaccinations and the importance of vaccinating their children, then the potential measles outbreaks will only get worse". When there is "geographic clustering" of unvaccinated people, potential outbreaks get worse.

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