Literature DB >> 34012040

COVID-19 non-pharmaceutical intervention portfolio effectiveness and risk communication predominance.

Louis Yat Hin Chan1,2,3, Baoyin Yuan4,5, Matteo Convertino6,7.   

Abstract

Non-pharmaceutical interventions (NPIs) including resource allocation, risk communication, social distancing and travel restriction, are mainstream actions to control the spreading of Coronavirus disease 2019 (COVID-19) worldwide. Different countries implemented their own combinations of NPIs to prevent local epidemics and healthcare system overloaded. Portfolios, as temporal sets of NPIs have various systemic impacts on preventing cases in populations. Here, we developed a probabilistic modeling framework to evaluate the effectiveness of NPI portfolios at the macroscale. We employed a deconvolution method to back-calculate incidence of infections and estimate the effective reproduction number by using the package EpiEstim. We then evaluated the effectiveness of NPIs using ratios of the reproduction numbers and considered them individually and as a portfolio systemically. Based on estimates from Japan, we estimated time delays of symptomatic-to-confirmation and infection-to-confirmation as 7.4 and 11.4 days, respectively. These were used to correct surveillance data of other countries. Considering 50 countries, risk communication and returning to normal life were the most and least effective yielding the aggregated effectiveness of 0.11 and - 0.05 that correspond to a 22.4% and 12.2% reduction and increase in case growth. The latter is quantified by the change in reproduction number before and after intervention implementation. Countries with the optimal NPI portfolio are along an empirical Pareto frontier where mean and variance of effectiveness are maximized and minimized independently of incidence levels. Results indicate that implemented interventions, regardless of NPI portfolios, had distinct incidence reductions and a clear timing effect on infection dynamics measured by sequences of reproduction numbers. Overall, the successful suppression of the epidemic cannot work without the non-linear effect of NPI portfolios whose effectiveness optimality may relate to country-specific socio-environmental factors.

Entities:  

Year:  2021        PMID: 34012040     DOI: 10.1038/s41598-021-88309-1

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  11 in total

1.  Learning about COVID-19: sources of information, public trust, and contact tracing during the pandemic.

Authors:  Philip S Amara; Jodyn E Platt; Minakshi Raj; Paige Nong
Journal:  BMC Public Health       Date:  2022-07-15       Impact factor: 4.135

2.  How national leaders keep 'us' safe: A longitudinal, four-nation study exploring the role of identity leadership as a predictor of adherence to COVID-19 non-pharmaceutical interventions.

Authors:  Svenja B Frenzel; S Alexander Haslam; Nina M Junker; Aidos Bolatov; Valerie A Erkens; Jan A Häusser; Ronit Kark; Ines Meyer; Andreas Mojzisch; Lucas Monzani; Stephen D Reicher; Adil Samekin; Sebastian C Schuh; Niklas K Steffens; Liliya Sultanova; Dina Van Dijk; Llewellyn E van Zyl; Rolf van Dick
Journal:  BMJ Open       Date:  2022-05-10       Impact factor: 3.006

3.  Combining Direct PCR Technology and Capillary Electrophoresis for an Easy-to-Operate and Highly Sensitive Infectious Disease Detection System for Shrimp.

Authors:  Hung-Yun Lin; Shao-Chieh Yen; Shou-Kuan Tsai; Fan Shen; John Han-You Lin; Han-Jia Lin
Journal:  Life (Basel)       Date:  2022-02-13

4.  Impact of implementation timing on the effectiveness of stay-at-home requirement under the COVID-19 pandemic: Lessons from the Italian Case.

Authors:  Stefano Mingolla; Zhongming Lu
Journal:  Health Policy       Date:  2022-04-04       Impact factor: 3.255

5.  In.To. COVID-19 socio-epidemiological co-causality.

Authors:  Elroy Galbraith; Jie Li; Victor J Del Rio-Vilas; Matteo Convertino
Journal:  Sci Rep       Date:  2022-04-06       Impact factor: 4.379

6.  Differential COVID-19 Symptoms Given Pandemic Locations, Time, and Comorbidities During the Early Pandemic.

Authors:  Yang Wang; Fengwei Zhang; J Brian Byrd; Hong Yu; Xianwei Ye; Yongqun He
Journal:  Front Med (Lausanne)       Date:  2022-01-28

7.  Can naive Bayes classifier predict infection in a close contact of COVID-19? A comparative test for predictability of the predictive model and healthcare workers in Japan.

Authors:  Hideo Yoshikawa
Journal:  J Infect Chemother       Date:  2022-02-24       Impact factor: 2.065

8.  An assessment of transmission dynamics via time-varying reproduction number of the second wave of the COVID-19 epidemic in Fiji.

Authors:  Rajnesh Lal; Weidong Huang; Zhenquan Li; Swastika Prasad
Journal:  R Soc Open Sci       Date:  2022-08-31       Impact factor: 3.653

9.  Assessing Public Health and Social Measures Against COVID-19 in Japan From March to June 2021.

Authors:  Katsuma Hayashi; Taishi Kayano; Asami Anzai; Marie Fujimoto; Natalie Linton; Misaki Sasanami; Ayako Suzuki; Tetsuro Kobayashi; Kanako Otani; Masato Yamauchi; Motoi Suzuki; Hiroshi Nishiura
Journal:  Front Med (Lausanne)       Date:  2022-07-12

10.  Factors affecting adherence to non-pharmaceutical interventions for COVID-19 infections in the first year of the pandemic in the UK.

Authors:  Xuejie Ding; David M Brazel; Melinda C Mills
Journal:  BMJ Open       Date:  2021-10-25       Impact factor: 3.006

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