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      Predictors of COVID-19 epidemics in countries of the World Health Organization African Region

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          Abstract

          Countries of the World Health Organization (WHO) African Region have experienced a wide range of coronavirus disease 2019 (COVID-19) epidemics. This study aimed to identify predictors of the timing of the first COVID-19 case and the per capita mortality in WHO African Region countries during the first and second pandemic waves and to test for associations with the preparedness of health systems and government pandemic responses. Using a region-wide, country-based observational study, we found that the first case was detected earlier in countries with more urban populations, higher international connectivity and greater COVID-19 test capacity but later in island nations. Predictors of a high first wave per capita mortality rate included a more urban population, higher pre-pandemic international connectivity and a higher prevalence of HIV. Countries rated as better prepared and having more resilient health systems were worst affected by the disease, the imposition of restrictions or both, making any benefit of more stringent countermeasures difficult to detect. Predictors for the second wave were similar to the first. Second wave per capita mortality could be predicted from that of the first wave. The COVID-19 pandemic highlights unanticipated vulnerabilities to infectious disease in Africa that should be taken into account in future pandemic preparedness planning.

          Abstract

          A new study from the WHO African Region identifies features of countries that predict timing of the first case and the per capita mortality rate for the first and second waves of the COVID-19 epidemics.

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          Most cited references42

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          A Novel Coronavirus from Patients with Pneumonia in China, 2019

          Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)
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            The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak

            Motivated by the rapid spread of COVID-19 in Mainland China, we use a global metapopulation disease transmission model to project the impact of travel limitations on the national and international spread of the epidemic. The model is calibrated based on internationally reported cases, and shows that at the start of the travel ban from Wuhan on 23 January 2020, most Chinese cities had already received many infected travelers. The travel quarantine of Wuhan delayed the overall epidemic progression by only 3 to 5 days in Mainland China, but has a more marked effect at the international scale, where case importations were reduced by nearly 80% until mid February. Modeling results also indicate that sustained 90% travel restrictions to and from Mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.
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              Risk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysis

              Background An epidemic of Coronavirus Disease 2019 (COVID-19) began in December 2019 and triggered a Public Health Emergency of International Concern (PHEIC). We aimed to find risk factors for the progression of COVID-19 to help reducing the risk of critical illness and death for clinical help. Methods The data of COVID-19 patients until March 20, 2020 were retrieved from four databases. We statistically analyzed the risk factors of critical/mortal and non-critical COVID-19 patients with meta-analysis. Results Thirteen studies were included in Meta-analysis, including a total number of 3027 patients with SARS-CoV-2 infection. Male, older than 65, and smoking were risk factors for disease progression in patients with COVID-19 (male: OR = 1.76, 95% CI (1.41, 2.18), P 40U/L, creatinine(Cr) ≥ 133mol/L, hypersensitive cardiac troponin I(hs-cTnI) > 28pg/mL, procalcitonin(PCT) > 0.5ng/mL, lactatede hydrogenase(LDH) > 245U/L, and D-dimer > 0.5mg/L predicted the deterioration of disease while white blood cells(WBC) 40U/L:OR=4.00, 95% CI (2.46, 6.52), P 28 pg/mL: OR = 43.24, 95% CI (9.92, 188.49), P 0.5 ng/mL: OR = 43.24, 95% CI (9.92, 188.49), P 245U/L: OR = 43.24, 95% CI (9.92, 188.49), P 0.5mg/L: OR = 43.24, 95% CI (9.92, 188.49), P < 0.00001; WBC < 4 × 109/L: OR = 0.30, 95% CI (0.17, 0.51), P < 0.00001]. Conclusion Male, aged over 65, smoking patients might face a greater risk of developing into the critical or mortal condition and the comorbidities such as hypertension, diabetes, cardiovascular disease, and respiratory diseases could also greatly affect the prognosis of the COVID-19. Clinical manifestation such as fever, shortness of breath or dyspnea and laboratory examination such as WBC, AST, Cr, PCT, LDH, hs-cTnI and D-dimer could imply the progression of COVID-19.
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                Author and article information

                Contributors
                feifei.zhang@ed.ac.uk
                Journal
                Nat Med
                Nat Med
                Nature Medicine
                Nature Publishing Group US (New York )
                1078-8956
                1546-170X
                3 September 2021
                3 September 2021
                2021
                : 27
                : 11
                : 2041-2047
                Affiliations
                [1 ]GRID grid.4305.2, ISNI 0000 0004 1936 7988, Usher Institute, , University of Edinburgh, ; Edinburgh, United Kingdom
                [2 ]GRID grid.463718.f, ISNI 0000 0004 0639 2906, WHO Regional Office for Africa, ; Brazzaville, Republic of Congo
                [3 ]GRID grid.10604.33, ISNI 0000 0001 2019 0495, University of Nairobi Institute of Tropical and Infectious Diseases, ; Nairobi, Kenya
                [4 ]GRID grid.4305.2, ISNI 0000 0004 1936 7988, School of Biological Sciences, , University of Edinburgh, ; Edinburgh, United Kingdom
                [5 ]GRID grid.4305.2, ISNI 0000 0004 1936 7988, Roslin Institute and Royal (Dick) School of Veterinary Studies, , University of Edinburgh, ; Edinburgh, United Kingdom
                [6 ]GRID grid.194645.b, ISNI 0000000121742757, Department of Medicine, Li Ka Shing Faculty of Medicine, , University of Hong Kong, ; Hong Kong, China
                [7 ]GRID grid.8652.9, ISNI 0000 0004 1937 1485, West African Centre for Cell Biology of Infectious Pathogens, , University of Ghana, ; Accra, Ghana
                Author information
                http://orcid.org/0000-0002-3718-243X
                http://orcid.org/0000-0002-6277-2095
                http://orcid.org/0000-0003-1187-0362
                http://orcid.org/0000-0003-0474-9492
                http://orcid.org/0000-0001-8277-3178
                http://orcid.org/0000-0002-0980-2953
                http://orcid.org/0000-0003-3608-2880
                http://orcid.org/0000-0002-0657-473X
                http://orcid.org/0000-0003-3946-1130
                http://orcid.org/0000-0003-3765-8167
                Article
                1491
                10.1038/s41591-021-01491-7
                8604723
                34480125
                6c9e2678-264b-4874-9d46-5a3ad13b9859
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 7 May 2021
                : 5 August 2021
                Funding
                Funded by: Darwin Trust of Edinburgh
                Funded by: FundRef https://doi.org/10.13039/501100000272, DH | National Institute for Health Research (NIHR);
                Award ID: 16/136/33
                Award ID: 16/136/33
                Award ID: 16/136/33
                Award Recipient :
                Categories
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                © The Author(s), under exclusive licence to Springer Nature America, Inc. 2021

                Medicine
                risk factors,epidemiology,health policy
                Medicine
                risk factors, epidemiology, health policy

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