Publications by authors named "Tanvi Ingle"
Bacteriophage ϕX174 has been widely used as a model organism to study fundamental processes in molecular biology. However, several aspects of ϕX174 gene regulation are not fully resolved. Here we construct a computational model for ϕX174 and use the model to study gene regulation during the phage infection cycle.
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- The rise of antimicrobial resistant (AMR) infections poses a significant global health danger, influenced by complex factors, including socioeconomic conditions.
- A study in the Dallas-Fort Worth area analyzed patient data from 2015 to 2020, linking bacterial culture results to socioeconomic indices to understand AMR patterns.
- Findings indicated that regions with high deprivation levels had higher AMR rates, suggesting that improving socioeconomic factors could help reduce AMR spread.
Unlabelled: In mid-2020, there was significant concern that the overlapping 2020-2021 influenza season and COVID-19 pandemic would overwhelm already stressed health care systems in the Northern Hemisphere, particularly if influenza immunization rates were low. Using a mathematical susceptible-exposed-infected-recovered (SEIR) compartmental model incorporating the age-specific viral transmission rates and disease severity of Austin, Texas, a large metropolitan region, we projected the incidence and health care burden for both COVID-19 and influenza across observed levels of SARS-CoV-2 transmission and influenza immunization rates for the 2020-2021 season. We then retrospectively compared scenario projections made in August 2020 with observed trends through June 2021.
View Article and Find Full Text PDFReal-time pandemic surveillance using hospital admissions and mobility data.
Proc Natl Acad Sci U S A
February 2022
Article Synopsis
- The forecasting of COVID-19's impact has faced challenges due to biased case reporting and delays in death counts, making accurate predictions difficult.
- A new model that combines hospital admissions with mobility data has proven effective in predicting transmission rates and healthcare demand for COVID-19, guiding policies in Austin, TX.
- The model showed a high initial reproduction rate of COVID-19, a notable improvement in case detection by January 2021, and a significant decrease in transmission due to increased public safety measures, demonstrating its reliability in predicting future healthcare needs.
As COVID-19 spreads across the United States, people experiencing homelessness (PEH) are among the most vulnerable to the virus. To mitigate transmission, municipal governments are procuring isolation facilities for PEH to utilize following possible exposure to the virus. Here we describe the framework for anticipating isolation bed demand in PEH communities that we developed to support public health planning in Austin, Texas during March 2020.
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