scholarly journals Impact of COVID-19 epidemic curtailment strategies in selected Indian states: an analysis by reproduction number and doubling time with incidence modelling

Author(s):  
Arun Mitra ◽  
Abhijit P Pakhare ◽  
Adrija Roy ◽  
Ankur Joshi

The Government of India in networks with its state government has implemented the epidemic curtailment strategies inclusive of case-isolation, quarantine and lockdown in response to ongoing novel coronavirus (COVID-19) outbreak . In this manuscript we attempt to estimate the effect of these steps across ten Indian states using crowd-sourced data. The chosen transmission parameters are -reproduction number (R0), doubling time and growth rate during the early epidemic phase (15 days into lockdown) and 30 days into lockdown (23rd April 2020) through maximum likelihood approach. The overall analysis shows the decreasing trends in reproductive numbers and growth rate (with few exceptions) and incremental doubling time. The curtailment strategies employed by the Indian government seemed to be effective in reducing the transmission parameters of the COVID-19 epidemic. The effective reproductive numbers are still higher above the threshold of 1 and the resultant absolute numbers tend to be exponentiating fundamentally. The curtailment strategy thus may take into account these findings while formulating further course of actions.

2020 ◽  
Author(s):  
Rabinder Kumar Prasad ◽  
Rosy Sarmah ◽  
Subrata Chakraborty

Abstract The novel Coronavirus (COVID-19) incidence in India is currently experiencing exponential rise with apparent spatial variation in growth rate and doubling time. We classify the states into five clusters with low to high-risk category and identify how the different states moved from one cluster to the other since the onset of the first case on $30^{th}$ January 2020 till the end of $15^{th}$ September 2020. We cluster the Indian states into $5$ groups using incrementalKMN clustering \cite{b1}. We observed and comment on the changing scenario of the formation of the clusters starting from before lockdown, through lockdown and the various unlock phases.


Author(s):  
Oyelola A. Adegboye ◽  
Adeshina I. Adekunle ◽  
Ezra Gayawan

On 31 December 2019, the World Health Organization (WHO) was notified of a novel coronavirus disease in China that was later named COVID-19. On 11 March 2020, the outbreak of COVID-19 was declared a pandemic. The first instance of the virus in Nigeria was documented on 27 February 2020. This study provides a preliminary epidemiological analysis of the first 45 days of COVID-19 outbreak in Nigeria. We estimated the early transmissibility via time-varying reproduction number based on the Bayesian method that incorporates uncertainty in the distribution of serial interval (time interval between symptoms onset in an infected individual and the infector), and adjusted for disease importation. By 11 April 2020, 318 confirmed cases and 10 deaths from COVID-19 have occurred in Nigeria. At day 45, the exponential growth rate was 0.07 (95% confidence interval (CI): 0.05–0.10) with a doubling time of 9.84 days (95% CI: 7.28–15.18). Separately for imported cases (travel-related) and local cases, the doubling time was 12.88 days and 2.86 days, respectively. Furthermore, we estimated the reproduction number for each day of the outbreak using a three-weekly window while adjusting for imported cases. The estimated reproduction number was 4.98 (95% CrI: 2.65–8.41) at day 22 (19 March 2020), peaking at 5.61 (95% credible interval (CrI): 3.83–7.88) at day 25 (22 March 2020). The median reproduction number over the study period was 2.71 and the latest value on 11 April 2020, was 1.42 (95% CrI: 1.26–1.58). These 45-day estimates suggested that cases of COVID-19 in Nigeria have been remarkably lower than expected and the preparedness to detect needs to be shifted to stop local transmission.


2017 ◽  
Vol 5 (7) ◽  
pp. 140-150
Author(s):  
Sayyid Abdulla Shakir

Kerala, southern fringe of India has different story of development from the rest of Indian states. The implementation of different policies by the government has been resulted in the betterment of different marginalized communities, especially in the case of women empowerment. For women empowerment, state government has initiated may programs with the support of other local bodies including government and non-government organizations like Kudumbashree program, Gender park etc. It has created many opportunities for women to come forward to main stream of the society and engaging in many public activities. This paper is an attempt to look at state sponsored program for fisher women empowerment called ‘Society for Assistance to Fisherwomen’ (SAF), for uplift of fisherwomen, with the support of both secondary material and ground reality. This paper also discusses about development model of Kerala with special focus on women empowerment.


BMJ Open ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. e056636
Author(s):  
Thomas Ward ◽  
Alex Glaser ◽  
Alexander Johnsen ◽  
Feng Xu ◽  
Ian Hall ◽  
...  

ObjectivesImportations of novel variants of concern (VOC), particularly B.1.617.2, have become the impetus behind recent outbreaks of SARS-CoV-2. Concerns around the impact on vaccine effectiveness, transmissibility and severity are now driving the public health response to these variants. This paper analyses the patterns of growth in hospitalisations and confirmed cases for novel VOCs by age groups, geography and ethnicity in the context of changing behaviour, non-pharmaceutical interventions (NPIs) and the UK vaccination programme. We seek to highlight where strategies have been effective and periods that have facilitated the establishment of new variants.DesignWe have algorithmically linked the most complete testing and hospitalisation data in England to create a data set of confirmed infections and hospitalisations by SARS-CoV-2 genomic variant. We have used these linked data sets to analyse temporal, geographic and demographic distinctions.Setting and participantsThe setting is England from October 2020 to July 2021. Participants included all COVID-19 tests that included RT-PCR CT gene target data or underwent sequencing and hospitalisations that could be linked to these tests.MethodsTo calculate the instantaneous growth rate for VOCs we have developed a generalised additive model fit to multiple splines and varying day of the week effects. We have further modelled the instantaneous reproduction number Rt for the B.1.1.7 and B.1.617.2 variants and included a doubly interval censored model to temporally adjust the confirmed variant cases.ResultsWe observed a clear replacement of the predominant B.1.1.7 by the B.1.617.2 variant without observing sustained exponential growth in other novel variants. Modelled exponential growth of RT PCR gene target triple-positive cases was initially detected in the youngest age groups, although we now observe across all ages a very small doubling time of 10.7 (95% CI 9.1 to 13.2) days and 8 (95% CI 6.9 to 9.1) days for cases and hospitalisations, respectively. We observe that growth in RT PCR gene target triple-positive cases was first detected in the Indian ethnicity group in late February, with a peak of 0.06 (95% CI 0.07 to 0.05) in the instantaneous growth rate, but is now maintained by the white ethnicity groups, observing a doubling time of 6.8 (95% CI 4.9 to 11) days. Rt analysis indicates a reproduction number advantage of 0.45 for B.1.617.2 relative to B.1.1.7, with the Rt value peaking at 1.85 for B.1.617.2.ConclusionsOur results illustrate a clear transmission advantage for the B.1.617.2 variant and the growth in hospitalisations illustrates that this variant is able to maintain exponential growth within age groups that are largely doubly vaccinated. There are concerning signs of intermittent growth in the B.1.351 variant, reaching a 28-day doubling time peak in March 2021, although this variant is presently not showing any evidence of a transmission advantage over B.1.617.2. Step 1b of the UK national lockdown easing was sufficient to precipitate exponential growth in B.1.617.2 cases for most regions and younger adult age groups. The final stages of NPI easing appeared to have a negligible impact on the growth of B.1.617.2 with every region experiencing sustained exponential growth from step 2. Nonetheless, early targeted local NPIs appeared to markedly reduced growth of B.1.617.2. Later localised interventions, at a time of higher prevalence and greater geographic dispersion of this variant, appeared to have a negligible impact on growth.


2019 ◽  
Vol 8 (1) ◽  
pp. 35-40
Author(s):  
L. F. Sunitha

Kerala, southern fringe of India has different story of development from the rest of Indian states. The implementation of different policies by the government has been resulted in the betterment of different marginalized communities, especially in the case of women empowerment. For women empowerment, state government has initiated many programs with the support of other local bodies including government and non-government organizations like Kudumbashree program, Gender park etc. It has created many opportunities for women to come forward to mainstream of the society and engaging in many public activities. This paper is an attempt to look at state sponsored program for fisher women empowerment called ‘Society for Assistance to Fisherwomen’ (SAF), for uplift of fisherwomen, with the support of both secondary material and ground reality. This paper also discusses about the need for an alternative model for the development of the marginalized fisher households sector.


Author(s):  
Alessia Lai ◽  
Annalisa Bergna ◽  
Carla Acciarri ◽  
Massimo Galli ◽  
Gianguglielmo Zehender

ABSTRACTTo reconstruct the evolutionary dynamics of the 2019 novel coronavirus, 52 2019-nCOV genomes available on 04 February 2020 at GISAID were analysed.The two models used to estimate the reproduction number (coalescent-based exponential growth and a birth-death skyline method) indicated an estimated mean evolutionary rate of 7.8 × 10−4 subs/site/year (range 1.1×10−4–15×10−4).The estimated R value was 2.6 (range 2.1-5.1), and increased from 0.8 to 2.4 in December 2019. The estimated mean doubling time of the epidemic was between 3.6 and 4.1 days.This study proves the usefulness of phylogeny in supporting the surveillance of emerging new infections even as the epidemic is growing.


2020 ◽  
Vol 10 (4) ◽  
pp. 325-326
Author(s):  
Khalid Aziz ◽  
Muhammad Usman ◽  
Muhammad Fahim

Somewhere in the beginning of March 2020, State Government suddenly announced the closure of all educational institutions as a preventive measure to restrict the spread of novel coronavirus. It has been over five months since the government has completely shut down the educational institutions


Author(s):  
Sung-mok Jung ◽  
Andrei R. Akhmetzhanov ◽  
Katsuma Hayashi ◽  
Natalie M. Linton ◽  
Yichi Yang ◽  
...  

AbstractThe exported cases of 2019 novel coronavirus (COVID-19) infection that were confirmed outside of China provide an opportunity to estimate the cumulative incidence and confirmed case fatality risk (cCFR) in mainland China. Knowledge of the cCFR is critical to characterize the severity and understand the pandemic potential of COVID-19 in the early stage of the epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction number—the average number of secondary cases generated by a single primary case in a naïve population. We modeled epidemic growth either from a single index case with illness onset on 8 December, 2019 (Scenario 1), or using the growth rate fitted along with the other parameters (Scenario 2) based on data from 20 exported cases reported by 24 January, 2020. The cumulative incidence in China by 24 January was estimated at 6924 cases (95% CI: 4885, 9211) and 19,289 cases (95% CI: 10,901, 30,158), respectively. The latest estimated values of the cCFR were 5.3% (95% CI: 3.5%, 7.5%) for Scenario 1 and 8.4% (95% CI: 5.3%, 12.3%) for Scenario 2. The basic reproduction number was estimated to be 2.1 (95% CI: 2.0, 2.2) and 3.2 (95% CI: 2.7, 3.7) for Scenarios 1 and 2, respectively. Based on these results, we argued that the current COVID-19 epidemic has a substantial potential for causing a pandemic. The proposed approach provides insights in early risk assessment using publicly available data.


Author(s):  
Alok Tiwari

ABSTRACTCOVID 19 entered during the last week of April 2020 in India has caused 3,546 deaths with 1,13,321 number of reported cases. Indian government has taken many proactive steps, including strict lockdown of the entire nation for more than 50 days, identification of hotspots, app-based tracking of citizens to track infected. This paper investigated the evolution of COVID 19 in five states of India (Maharashtra, UP, Gujrat, Tamil Nadu, and Delhi) from 1st April 2020 to 20th May 2020. Variation of doubling rate and reproduction number (from SIQR) with time is used to analyse the performance of the majorly affected Indian states. It has been determined that Uttar Pradesh is one of the best performers among five states with the doubling rate crossing 18 days as of 20th May. Tamil Nadu has witnessed the second wave of infections during the second week of May. Maharashtra is continuously improving at a steady rate with its doubling rate reaching to 12.67 days. Also these two states are performing below the national average in terms of infection doubling rate. Gujrat and Delhi have reported the doubling rate of 16.42 days and 15.49 days respectively. Comparison of these states has also been performed based on time-dependent reproduction number. Recovery rate of India has reached to 40 % as the day paper is written.


Author(s):  
Oyelola A. Adegboye ◽  
Adeshina I. Adekunle ◽  
Ezra Gayawan

AbstractBackgroundOn December 31, 2019, the World Health Organization (WHO) was notified of a novel coronavirus in China that was later named COVID-19. On March 11, 2020, the outbreak of COVID-19 was declared a pandemic. The first instance of the virus in Nigeria was documented on February 27, 2020.MethodsThis study provides a preliminary epidemiological analysis of the first 45 days of COVID-19 outbreak in Nigeria quantifying. We estimated the early transmissibility via time-varying reproduction number based on Bayesian method that incorporates uncertainty in the distribution of serial interval (time interval between symptoms onset in an infected individual and the infector) and adjusted for disease importation.FindingsBy April 11, 2020, 318 confirmed cases and 10 deaths from COVID-19 have occurred in Nigeria. At day 45, the exponential growth rate was 0.07 (95% Confidence Interval (CI): 0.05 – 0.10) with doubling time of 9.84 days (95% CI: 7.28 – 15.18). Separately for travel related and local cases the doubling time was 12.88 days and 2.86 days, respectively. Furthermore, we estimated the reproduction number for each day of the outbreak using three-weekly window while adjusting for travel related cases. The estimated reproduction number was 4.98 (95% CrI: 2.65 – 8.41) at day 22 (March 19, 2020), peaking at 5.61 (95% CrI: 3.83 –7.88) at day 25 (March 22, 2020). The median reproduction number over the study period was 2.71 and the latest value at April 11, 2020 was 1.42 (95% CI: 1.26 – 1.58).InterpretationThese 45-day estimates suggested that cases of COVID-19 in Nigeria have been remarkably lower than expected and the preparedness to detect needs to be shifted to stop local transmission.FundingNone


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