Research & Highlights

The collaborative study led by Dr. Alexander Kirpich and implemented by Aleksandr Shishkin (Ph.D. Public Health - Epidemiology, Spring 2025) in collaboration with Dr. Pavel Skums, Dr. Gerardo Chowell, Dr. Alexander Perez Tchernov, and other researchers tackles a major challenge in public health forecasting, which is the delay in traditional surveillance reporting. The researchers present an approach that leverages Google Trends search query data to improve both the speed and accuracy of predictions for the spread and impact of COVID-19. By analyzing search terms related to disease incidence and mortality, the team identified and ranked keywords according to their predictive value. These keywords were then incorporated into forecasting models such as ARIMA, Prophet, and XGBoost to generate near-term predictions of reported cases and deaths. Incorporating the most predictive search terms significantly increased forecast accuracy, with improvements ranging from 50 to 90 percent across different models.

A collaborative study led by Dr. Alexander Kirpich, Dr. Pavel Skums, and Dr. Alexander Perez Tchernov introduced and applied a clustering-based methodology to examine how COVID-19 patterns across 42 European countries relate to public health, mobility, and sociodemographic factors. The analysis compared hierarchical clustering trees built from six key variables, revealing distinct relationships among incidence, mortality, vaccination, genetic diversity, and population characteristics. The study highlights the usefulness of cluster analysis for understanding epidemiological patterns in a comparative, cross-country context. The findings were presented at the ITSE 2025 Conference in Gran Canaria, Spain, and published in Royal Society Open Science in September 2025.

Alexander Kirpich Ph.D. successfully attended Epidemics 9: International Conference on Infectious Disease Dynamics in Bologna, Italy, from 28 November to 1 December 2023. Two poster talks were successfully presented, and one received the 2nd Prize Poster Award, which includes a publication fee waiver for one publication in the Epidemics Journal.

Alexander Kirpich Ph.D. delivered an online talk at the School of Public Health at Georgia State University titled "Biostatistics and Infectious Disease Modeling in Public Health." The talk explained the use of biostatistics in infectious disease modeling and introduced two projects with direct applications of biostatistics to infectious diseases data.

Alexander Kirpich Ph.D. is delighted to announce the official launch of his personal website. Alexander extends his sincere gratitude to Aliaksandr Zenin and TexasDigitalConsulting.com for their exceptional efforts in designing and launching the website during the spring and summer of 2023. The website serves as an ideal platform for Alexander Kirpich Ph.D. to present and summarize their research findings in a structured and captivating manner.

Dr. Alexander Kirpich, together with Dr. Michael H. Norris, Dr. Thomas A. Weppelman, Dr. Michael von Fricken, and Dr. Kirpich's students, conducted a study that aimed to investigate the seasonal relationships between meteorological factors, water quality, and sporadic cases of Legionnaires' disease in Washington, DC. Recognizing the challenges associated with studying large geographic areas due to the sporadic nature of the cases and data aggregation complexities, the researchers opted to focus on the discrete municipality of Washington, DC for a retrospective ecological study spanning from 2001 to 2019.

Recently, Aleksandr Shishkin, a Ph.D. student, successfully published a manuscript under the direct supervision of Dr. Alexander Kirpich. The manuscript focuses on excess mortality in Ukraine during the COVID-19 pandemic. This publication marks Aleksandr's debut as a lead author, and it presents a comprehensive analysis of all-cause and cause-specific mortality in Ukraine throughout 2020 and 2021.