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      Assessing the dynamic impacts of non-pharmaceutical and pharmaceutical intervention measures on the containment results against COVID-19 in Ethiopia

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          Abstract

          The rapid spread of COVID-19 in Ethiopia was attributed to joint effects of multiple factors such as low adherence to face mask-wearing, failure to comply with social distancing measures, many people attending religious worship activities and holiday events, extensive protests, country election rallies during the pandemic, and the war between the federal government and Tigray Region. This study built a system dynamics model to capture COVID-19 characteristics, major social events, stringencies of containment measures, and vaccination dynamics. This system dynamics model served as a framework for understanding the issues and gaps in the containment measures against COVID-19 in the past period (16 scenarios) and the spread dynamics of the infectious disease over the next year under a combination of different interventions (264 scenarios). In the counterfactual analysis, we found that keeping high mask-wearing adherence since the outbreak of COVID-19 in Ethiopia could have significantly reduced the infection under the condition of low vaccination level or unavailability of the vaccine supply. Reducing or canceling major social events could achieve a better outcome than imposing constraints on people’s routine life activities. The trend analysis found that increasing mask-wearing adherence and enforcing more stringent social distancing were two major measures that can significantly reduce possible infections. Higher mask-wearing adherence had more significant impacts than enforcing social distancing measures in our settings. As the vaccination rate increases, reduced efficacy could cause more infections than shortened immunological periods. Offsetting effects of multiple interventions (strengthening one or more interventions while loosening others) could be applied when the levels or stringencies of one or more interventions need to be adjusted for catering to particular needs (e.g., less stringent social distancing measures to reboot the economy or cushion insufficient resources in some areas).

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          Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia

          Abstract Background The initial cases of novel coronavirus (2019-nCoV)–infected pneumonia (NCIP) occurred in Wuhan, Hubei Province, China, in December 2019 and January 2020. We analyzed data on the first 425 confirmed cases in Wuhan to determine the epidemiologic characteristics of NCIP. Methods We collected information on demographic characteristics, exposure history, and illness timelines of laboratory-confirmed cases of NCIP that had been reported by January 22, 2020. We described characteristics of the cases and estimated the key epidemiologic time-delay distributions. In the early period of exponential growth, we estimated the epidemic doubling time and the basic reproductive number. Results Among the first 425 patients with confirmed NCIP, the median age was 59 years and 56% were male. The majority of cases (55%) with onset before January 1, 2020, were linked to the Huanan Seafood Wholesale Market, as compared with 8.6% of the subsequent cases. The mean incubation period was 5.2 days (95% confidence interval [CI], 4.1 to 7.0), with the 95th percentile of the distribution at 12.5 days. In its early stages, the epidemic doubled in size every 7.4 days. With a mean serial interval of 7.5 days (95% CI, 5.3 to 19), the basic reproductive number was estimated to be 2.2 (95% CI, 1.4 to 3.9). Conclusions On the basis of this information, there is evidence that human-to-human transmission has occurred among close contacts since the middle of December 2019. Considerable efforts to reduce transmission will be required to control outbreaks if similar dynamics apply elsewhere. Measures to prevent or reduce transmission should be implemented in populations at risk. (Funded by the Ministry of Science and Technology of China and others.)
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            Neutralizing antibody levels are highly predictive of immune protection from symptomatic SARS-CoV-2 infection

            Predictive models of immune protection from COVID-19 are urgently needed to identify correlates of protection to assist in the future deployment of vaccines. To address this, we analyzed the relationship between in vitro neutralization levels and the observed protection from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using data from seven current vaccines and from convalescent cohorts. We estimated the neutralization level for 50% protection against detectable SARS-CoV-2 infection to be 20.2% of the mean convalescent level (95% confidence interval (CI) = 14.4-28.4%). The estimated neutralization level required for 50% protection from severe infection was significantly lower (3% of the mean convalescent level; 95% CI = 0.7-13%, P = 0.0004). Modeling of the decay of the neutralization titer over the first 250 d after immunization predicts that a significant loss in protection from SARS-CoV-2 infection will occur, although protection from severe disease should be largely retained. Neutralization titers against some SARS-CoV-2 variants of concern are reduced compared with the vaccine strain, and our model predicts the relationship between neutralization and efficacy against viral variants. Here, we show that neutralization level is highly predictive of immune protection, and provide an evidence-based model of SARS-CoV-2 immune protection that will assist in developing vaccine strategies to control the future trajectory of the pandemic.
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              Fair Allocation of Scarce Medical Resources in the Time of Covid-19

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                Author and article information

                Contributors
                Role: Data curationRole: ValidationRole: Writing – original draft
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: Resources
                Role: Data curationRole: Formal analysis
                Role: ConceptualizationRole: Formal analysisRole: Methodology
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Validation
                Role: ConceptualizationRole: InvestigationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                26 July 2022
                2022
                26 July 2022
                : 17
                : 7
                : e0271231
                Affiliations
                [1 ] Research Institute of Economics and Management, Southwestern University of Finance and Economics, Chengdu, China
                [2 ] Institute of Advanced Studies in Humanities and Social Sciences, Beijing Normal University at Zhuhai, Zhuhai, China
                [3 ] Personal Finance Department, HQ of China Construction Bank, Beijing, China
                [4 ] College of Business and Economics, University of Gondar, Gondar, Ethiopia
                [5 ] Business School, University of Shanghai for Science & Technology, Shanghai, China
                [6 ] Department of Public Health, College of Medicine & Health Science, University of Gondar, Gondar, Ethiopia
                [7 ] School of Resources and Environmental Science, Wuhan University, Wuhan, China
                [8 ] International Institute of Spatial Lifecourse Epidemiology (ISLE), Wuhan, China
                Federal University of São João del-Rei: Universidade Federal de Sao Joao del-Rei, BRAZIL
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-4463-9431
                https://orcid.org/0000-0002-1995-9153
                Article
                PONE-D-22-02713
                10.1371/journal.pone.0271231
                9321453
                35881650
                aaf05647-8881-420a-9462-ad059600bc74
                © 2022 Zhu et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 27 January 2022
                : 24 June 2022
                Page count
                Figures: 24, Tables: 2, Pages: 26
                Funding
                Funded by: Ministry of Education in China Project of Humanities and Social Sciences
                Award ID: 21YJAZH053
                Award Recipient :
                The study was supported by the MOE (Ministry of Education in China) Project of Humanities and Social Sciences (21YJAZH053). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Infectious Disease Control
                Vaccines
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Viral Diseases
                Covid 19
                Biology and Life Sciences
                Immunology
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                Preventive Medicine
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                Epidemiology
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                COVID-19

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