The epidemiological characteristics of COVID-19 in Libya during the ongoing-armed conflict
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Abstract
Introductio n
COVID-19 can have even more dire consequences in countries with ongoing armed conflict. Libya, the second largest African country, has been involved in a major conflict since 2011. This study analyzed the epidemiological situation of the COVID-19 pandemic in Libya, examined the impact of the armed conflict in Libya on the spread of the pandemic, and proposes strategies for dealing with the pandemic during this conflict.
Methods
We collected the available information on all COVID-19 cases in the different regions of Libya, covering the period from March 25 to May 25, 2020. The cumulative number of cases and the daily new cases are presented in a way to illustrate the patterns and trends of COVID-19 and the effect of the ongoing armed conflict was assessed regionally.
Results
A total of 698 cases of COVID-19 were reported in Libya during a period of three months. The number of cases varied from one region to another and was affected by the fighting. The largest number of cases was reported in the southern part of the country, which has been severely affected by the conflict in comparison to the eastern and western parts of the country.
Conclusion
This study describes the epidemiological pattern of COVID-19 in Libya and how it has been affected by the ongoing armed conflict. This conflict seems to have hindered access to populations and thereby masked the true dimensions of the pandemic. Hence, efforts should be combined to combat these consequences.
Article activity feed
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SciScore for 10.1101/2020.09.17.20196352: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources Microsoft Excel and SPSS version 12.0 were used for data entry and analysis. Microsoft Excelsuggested: (Microsoft Excel, RRID:SCR_016137)SPSSsuggested: (SPSS, RRID:SCR_002865)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Despite the valuable epidemiological …
SciScore for 10.1101/2020.09.17.20196352: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources Microsoft Excel and SPSS version 12.0 were used for data entry and analysis. Microsoft Excelsuggested: (Microsoft Excel, RRID:SCR_016137)SPSSsuggested: (SPSS, RRID:SCR_002865)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Despite the valuable epidemiological information that this study presents, it has several limitations and uncertainties, particularly as it was carried out in a conflict-ridden country where security is lacking and collecting accurate information is difficult. First, the number of reported cases is affected by uncertainties due to problems in accuracy in the daily reports of new notifications, particularly from the regions affected by ongoing armed conflict. Furthermore, it refers only to cases confirmed by molecular analysis, which is not feasible in all suspected situations. Daw[25] and Chen et al advocated that patients are the key cause of COVID-19 infection[32]. Accordingly, patients with mild or less severe symptoms should be taken into account as they may lead to an increase in infectivity and fatality. Second, the study did not analyze the medical care resources and healthcare capacities (number of hospital beds and physicians) used to combat the pandemic, especially that the patients are scattered over a very large area. The resources are most likely inadequate for a large influx of patients.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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SciScore for 10.1101/2020.09.17.20196352: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable The average age was 43 years and mainly males were affected, with a male-to-female ratio of 4.4:1.0. Table 2: Resources
Software and Algorithms Sentences Resources Microsoft Excel and SPSS version 12.0 were used for data entry and analysis. Microsoft Excelsuggested: (Microsoft Excel, RRID:SCR_016137)…SPSSsuggested: (SPSS, RRID:SCR_002865)SciScore for 10.1101/2020.09.17.20196352: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable The average age was 43 years and mainly males were affected, with a male-to-female ratio of 4.4:1.0. Table 2: Resources
Software and Algorithms Sentences Resources Microsoft Excel and SPSS version 12.0 were used for data entry and analysis. Microsoft Excelsuggested: (Microsoft Excel, RRID:SCR_016137)SPSSsuggested: (SPSS, RRID:SCR_002865)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
Despite the valuable epidemiological information that this study presents, it has several limitations and uncertainties, particularly as it was carried out in a conflict-ridden country where security is lacking and collecting accurate information is difficult. First, the number of reported cases is affected by uncertainties due to problems in accuracy in the daily reports of new notifications, particularly from the regions affected by ongoing armed conflict. Furthermore, it refers only to cases confirmed by molecular analysis, which is not feasible in all suspected situations. Daw[25] and Chen et al advocated that patients are the key cause of COVID-19 infection[32]. Accordingly, patients with mild or less severe symptoms should be taken into account as they may lead to an increase in infectivity and fatality. Second, the study did not analyze the medical care resources and healthcare capacities (number of hospital beds and physicians) used to combat the pandemic, especially that the patients are scattered over a very large area. The resources are most likely inadequate for a large influx of patients.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
About SciScore
SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.
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