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Inter-provincial disparity of COVID-19 transmission and control in Nepal.
Pantha, Buddhi; Acharya, Subas; Joshi, Hem Raj; Vaidya, Naveen K.
  • Pantha B; Department of Science and Mathematics, Abraham Baldwin Agricultural College, Tifton, GA, 31793, USA.
  • Acharya S; Department of Mathematical Sciences, University of Texas at Dallas, Dallas, TX, USA.
  • Joshi HR; Department of Mathematics, Xavier University, Cincinnati, OH, USA.
  • Vaidya NK; Department of Mathematics and Statistics, San Diego State University, San Diego, CA, USA. nvaidya@sdsu.edu.
Sci Rep ; 11(1): 13363, 2021 06 25.
Article in English | MEDLINE | ID: covidwho-1281730
ABSTRACT
Despite the global efforts to mitigate the ongoing COVID-19 pandemic, the disease transmission and the effective controls still remain uncertain as the outcome of the epidemic varies from place to place. In this regard, the province-wise data from Nepal provides a unique opportunity to study the effective control strategies. This is because (a) some provinces of Nepal share an open-border with India, resulting in a significantly high inflow of COVID-19 cases from India; (b) despite the inflow of a considerable number of cases, the local spread was quite controlled until mid-June of 2020, presumably due to control policies implemented; and (c) the relaxation of policies caused a rapid surge of the COVID-19 cases, providing a multi-phasic trend of disease dynamics. In this study, we used this unique data set to explore the inter-provincial disparities of the important indicators, such as epidemic trend, epidemic growth rate, and reproduction numbers. Furthermore, we extended our analysis to identify prevention and control policies that are effective in altering these indicators. Our analysis identified a noticeable inter-province variation in the epidemic trend (3 per day to 104 per day linear increase during third surge period), the median daily growth rate (1 to 4% per day exponential growth), the basic reproduction number (0.71 to 1.21), and the effective reproduction number (maximum values ranging from 1.20 to 2.86). Importantly, results from our modeling show that the type and number of control strategies that are effective in altering the indicators vary among provinces, underscoring the need for province-focused strategies along with the national-level strategy in order to ensure the control of a local spread.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-92253-5

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-92253-5