Studies in disease dynamics [HBNI Th-244]
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TextLanguage: English Publication details: Chennai The Institute of Mathematical Sciences 2023Description: ix, 139pSubject(s): Computational Biology | Computational BiologyOnline resources: Click here to access online Dissertation note: Ph.D HBNI 2023 Summary: Infectious disease are transmitted by pathogens such as bacteria, viruses and parasites. This thesis describes modeling work on two different diseases: COVID-19 and Malaria. The first wave of
COVID-19 reached India at the end of January 2020, with the peak in the number of cases occurring in September of that year. The first wave of COVID-19 in India was modelled using a detailed
compartmental model for this disease, called INDSCI-SIM. We estimated the undercounting of deaths in the state of Karnataka. For Karnataka as a state and its districts, our estimate for this
undercounting range from 2 to 5 across the district. We estimated an undercounting factor of about 2.2 as a whole for the state of Karnataka. We went on to estimate the fraction of those infected by
the end of the pandemic, finding that this varied in the range 20% to 70% across Karnataka’s districts.
THESIS & DISSERTATION
| Current library | Home library | Collection | Call number | Materials specified | URL | Status | Date due | Barcode |
|---|---|---|---|---|---|---|---|---|
| IMSc Library | IMSc Library | IMSc Thesis | HBNI Th244 (Browse shelf (Opens below)) | Link to resource | Available | 78043 |
Ph.D HBNI 2023
Infectious disease are transmitted by pathogens such as bacteria, viruses and parasites. This thesis describes modeling work on two different diseases: COVID-19 and Malaria. The first wave of
COVID-19 reached India at the end of January 2020, with the peak in the number of cases occurring in September of that year. The first wave of COVID-19 in India was modelled using a detailed
compartmental model for this disease, called INDSCI-SIM. We estimated the undercounting of deaths in the state of Karnataka. For Karnataka as a state and its districts, our estimate for this
undercounting range from 2 to 5 across the district. We estimated an undercounting factor of about 2.2 as a whole for the state of Karnataka. We went on to estimate the fraction of those infected by
the end of the pandemic, finding that this varied in the range 20% to 70% across Karnataka’s districts.
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