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Transmission Dynamics and Short-Term Forecasts of COVID-19: Nepal 2020/2021

Nepal was hard hit by a second wave of COVID-19 from April–May 2021. We investigated the transmission dynamics of COVID-19 at the national and provincial levels by using data on laboratory-confirmed RT-PCR positive cases from the official national situation reports. We performed 8 week-to-week seque...

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Autores principales: Dahal, Sushma, Luo, Ruiyan, Subedi, Raj Kumar, Dhimal, Meghnath, Chowell, Gerardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9620946/
https://www.ncbi.nlm.nih.gov/pubmed/36417221
http://dx.doi.org/10.3390/epidemiologia2040043
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author Dahal, Sushma
Luo, Ruiyan
Subedi, Raj Kumar
Dhimal, Meghnath
Chowell, Gerardo
author_facet Dahal, Sushma
Luo, Ruiyan
Subedi, Raj Kumar
Dhimal, Meghnath
Chowell, Gerardo
author_sort Dahal, Sushma
collection PubMed
description Nepal was hard hit by a second wave of COVID-19 from April–May 2021. We investigated the transmission dynamics of COVID-19 at the national and provincial levels by using data on laboratory-confirmed RT-PCR positive cases from the official national situation reports. We performed 8 week-to-week sequential forecasts of 10-days and 20-days at national level using three dynamic phenomenological growth models from 5 March 2021–22 May 2021. We also estimated effective and instantaneous reproduction numbers at national and provincial levels using established methods and evaluated the mobility trends using Google’s mobility data. Our forecast estimates indicated a declining trend of COVID-19 cases in Nepal as of June 2021. Sub-epidemic and Richards models provided reasonable short-term projections of COVID-19 cases based on standard performance metrics. There was a linear pattern in the trajectory of COVID-19 incidence during the first wave (deceleration of growth parameter (p) = 0.41–0.43, reproduction number ([Formula: see text]) at 1.1 (95% CI: 1.1, 1.2)), and a sub-exponential growth pattern in the second wave (p = 0.61 (95% CI: 0.58, 0.64)) and [Formula: see text] at 1.3 (95% CI: 1.3, 1.3)). Across provinces, [Formula: see text] ranged from 1.2 to 1.5 during the early growth phase of the second wave. The instantaneous [Formula: see text] fluctuated around 1.0 since January 2021 indicating well sustained transmission. The peak in mobility across different areas coincided with an increasing incidence trend of COVID-19. In conclusion, we found that the sub-epidemic and Richards models yielded reasonable short-terms projections of the COVID-19 trajectory in Nepal, which are useful for healthcare utilization planning.
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spelling pubmed-96209462022-11-18 Transmission Dynamics and Short-Term Forecasts of COVID-19: Nepal 2020/2021 Dahal, Sushma Luo, Ruiyan Subedi, Raj Kumar Dhimal, Meghnath Chowell, Gerardo Epidemiologia (Basel) Article Nepal was hard hit by a second wave of COVID-19 from April–May 2021. We investigated the transmission dynamics of COVID-19 at the national and provincial levels by using data on laboratory-confirmed RT-PCR positive cases from the official national situation reports. We performed 8 week-to-week sequential forecasts of 10-days and 20-days at national level using three dynamic phenomenological growth models from 5 March 2021–22 May 2021. We also estimated effective and instantaneous reproduction numbers at national and provincial levels using established methods and evaluated the mobility trends using Google’s mobility data. Our forecast estimates indicated a declining trend of COVID-19 cases in Nepal as of June 2021. Sub-epidemic and Richards models provided reasonable short-term projections of COVID-19 cases based on standard performance metrics. There was a linear pattern in the trajectory of COVID-19 incidence during the first wave (deceleration of growth parameter (p) = 0.41–0.43, reproduction number ([Formula: see text]) at 1.1 (95% CI: 1.1, 1.2)), and a sub-exponential growth pattern in the second wave (p = 0.61 (95% CI: 0.58, 0.64)) and [Formula: see text] at 1.3 (95% CI: 1.3, 1.3)). Across provinces, [Formula: see text] ranged from 1.2 to 1.5 during the early growth phase of the second wave. The instantaneous [Formula: see text] fluctuated around 1.0 since January 2021 indicating well sustained transmission. The peak in mobility across different areas coincided with an increasing incidence trend of COVID-19. In conclusion, we found that the sub-epidemic and Richards models yielded reasonable short-terms projections of the COVID-19 trajectory in Nepal, which are useful for healthcare utilization planning. MDPI 2021-12-16 /pmc/articles/PMC9620946/ /pubmed/36417221 http://dx.doi.org/10.3390/epidemiologia2040043 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Dahal, Sushma
Luo, Ruiyan
Subedi, Raj Kumar
Dhimal, Meghnath
Chowell, Gerardo
Transmission Dynamics and Short-Term Forecasts of COVID-19: Nepal 2020/2021
title Transmission Dynamics and Short-Term Forecasts of COVID-19: Nepal 2020/2021
title_full Transmission Dynamics and Short-Term Forecasts of COVID-19: Nepal 2020/2021
title_fullStr Transmission Dynamics and Short-Term Forecasts of COVID-19: Nepal 2020/2021
title_full_unstemmed Transmission Dynamics and Short-Term Forecasts of COVID-19: Nepal 2020/2021
title_short Transmission Dynamics and Short-Term Forecasts of COVID-19: Nepal 2020/2021
title_sort transmission dynamics and short-term forecasts of covid-19: nepal 2020/2021
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9620946/
https://www.ncbi.nlm.nih.gov/pubmed/36417221
http://dx.doi.org/10.3390/epidemiologia2040043
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