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Distribution and growth rate of COVID-19 outbreak in Tamil Nadu: A log-linear regression approach.
Bhaskar, Adhin; Ponnuraja, Chinnaiyan; Srinivasan, Ramalingam; Padmanaban, Srinivasan.
Afiliación
  • Bhaskar A; Scientist B, Department of Statistics, National Institute for Research in Tuberculosis, Chennai, Tamil Nadu, India.
  • Ponnuraja C; Scientist E, Department of Statistics, National Institute for Research in Tuberculosis, Chennai, Tamil Nadu, India.
  • Srinivasan R; Senior Technical Officer, Department of Statistics, National Institute for Research in Tuberculosis, Chennai, Tamil Nadu, India.
  • Padmanaban S; Scientist B, Department of Statistics, National Institute for Research in Tuberculosis, Chennai, Tamil Nadu, India.
Indian J Public Health ; 64(Supplement): S188-S191, 2020 Jun.
Article en En | MEDLINE | ID: mdl-32496253
BACKGROUND: Most of the countries are affected with the pandemic outbreak of the coronavirus infection. Understanding the severity and distribution in various regions will help in planning the controlling measures. OBJECTIVES: The objective was to assess the distribution and growth rate of COVID-19 infection in Tamil Nadu, India. METHODS: The data on the number of infections of COVID-19 have been obtained from the media reports released by the Government of Tamil Nadu. The data contain information on the incidence of the disease for the first 41 days of the outbreak started on March 7, 2020. Log-linear model has been used to estimate the progression of the COVID-19 infection in Tamil Nadu. Separate models were employed to model the growth rate and decay rate of the disease. Spatial Poisson regression was used to identify the high-risk areas in the state. RESULTS: : The models estimated the doubling time for the number of cases in growth phase as 3.96 (95% confidence interval [CI]: 2.70, 9.42) days and halving time in the decay phase as 12.08 (95% CI: 6.79, 54.78) days. The estimated median reproduction numbers were 1.88 (min = 1.09, max = 2.51) and 0.76 (min = 0.56, max = 0.99) in the growth and decay phases, respectively. The spatial Poisson regression identified 11 districts as high risk. CONCLUSION: The results indicate that the outbreak is showing decay in the number of infections of the disease which highlights the effectiveness of controlling measures.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neumonía Viral / Infecciones por Coronavirus Tipo de estudio: Incidence_studies / Prognostic_studies Límite: Humans País/Región como asunto: Asia Idioma: En Revista: Indian J Public Health Año: 2020 Tipo del documento: Article País de afiliación: India Pais de publicación: India
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neumonía Viral / Infecciones por Coronavirus Tipo de estudio: Incidence_studies / Prognostic_studies Límite: Humans País/Región como asunto: Asia Idioma: En Revista: Indian J Public Health Año: 2020 Tipo del documento: Article País de afiliación: India Pais de publicación: India