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Article ; Online: COVID-19 epidemic in Libya.

Bredan, Amin / Bakoush, Omran

2021 Volume 16, Issue 1, Page(s) 1871798

Abstract: ... of the epidemic in Libya. Here, we estimated the number of Libyans exposed to COVID-19 by using a COVID-19 ... The first case of COVID-19 was identified in Libya on 24/3/2020, and about 2 months later ... the number of reported COVID-19 cases started to increase notably. The outbreak was first prominent ...

Abstract	The first case of COVID-19 was identified in Libya on 24/3/2020, and about 2 months later, the number of reported COVID-19 cases started to increase notably. The outbreak was first prominent in the southern region (Sabha) and then spread to the western and eastern parts of Libya. By 24/12/2020, the reported total number of deaths from COVID-19 reached 1415. There seems to be no published data on the size of the epidemic in Libya. Here, we estimated the number of Libyans exposed to COVID-19 by using a COVID-19 mortality adjusted mathematical model for the spread of infectious diseases. We estimated that 14-20% of the Libyan population have been exposed to the COVID-19 pandemic. Thus, the risk of spread of COVID-19 infections during the coming months is high, and a considerable number of Libyans, particularly the elderly and people with chronic diseases, should be protected against COVID-19 infection. This is particularly urgent in the light of unofficial reports that the relevant healthcare facilities are under extreme stress.
MeSH term(s)	COVID-19/epidemiology ; Humans ; Libya/epidemiology ; Pandemics ; Risk Factors ; SARS-CoV-2
Language	English
Publishing date	2021-01-06
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	2273005-9
ISSN	1819-6357 ; 1993-2820
ISSN (online)	1819-6357
ISSN	1993-2820
DOI	10.1080/19932820.2021.1871798
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: COVID-19 epidemic in Libya

Amin Bredan / Omran Bakoush

Libyan Journal of Medicine, Vol 16, Iss

2021 Volume 1

Abstract	The first case of COVID-19 was identified in Libya on 24/3/2020, and about 2 months later, the number of reported COVID-19 cases started to increase notably. The outbreak was first prominent in the southern region (Sabha) and then spread to the western and eastern parts of Libya. By 24/12/2020, the reported total number of deaths from COVID-19 reached 1415. There seems to be no published data on the size of the epidemic in Libya. Here, we estimated the number of Libyans exposed to COVID-19 by using a COVID-19 mortality adjusted mathematical model for the spread of infectious diseases. We estimated that 14–20% of the Libyan population have been exposed to the COVID-19 pandemic. Thus, the risk of spread of COVID-19 infections during the coming months is high, and a considerable number of Libyans, particularly the elderly and people with chronic diseases, should be protected against COVID-19 infection. This is particularly urgent in the light of unofficial reports that the relevant healthcare facilities are under extreme stress.
Keywords	covid-19 ; libya ; modeling ; epidemic spread ; Medicine ; R
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Taylor & Francis Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: A Preliminary Study on the Frequency of Influenza Infections during the Early 2022 Amid COVID-19 Epidemic in Libya

Alhudiri, Inas M. / Saad, Saad R. / Abusrewil, Zakarya / Amer, Asel O. / El Meshri, Salah Edin / Bin Abdallah, Mohamed Nasir / Elghazal, Mohamed M. / Said, Mohamed H. / Ebrahim, Fawzi O. / Abusanina, Mohamed S. / Ben Elfghi, Mohammed / Abdusalam, Mohamed M. / Elzagheid, Adam

Ibnosina Journal of Medicine and Biomedical Sciences

2022 Volume 14, Issue 04, Page(s) 130–134

Abstract: ... individuals to influenza infections in a time when coronavirus disease 2019 (COVID-19) was also highly ... with COVID-19, influenza infections were also rising. As the COVID-19 pandemic continues, the most ... at our laboratories at Libyan Biotechnology Research Center, Tripoli, Libya, between December 1, 2021, and January 31 ...

Abstract	Background: At the time of conducting this study, we were at the peak of the influenza season, and influenza vaccinations were not readily accessible throughout the country. Thus, predisposing many high-risk individuals to influenza infections in a time when coronavirus disease 2019 (COVID-19) was also highly circulating, and the emerging Omicron variant of concern was peaking in many countries worldwide. Materials and Methods: We conducted a brief survey to prospectively estimate the frequency of influenza A and B and severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) in samples received at our laboratories at Libyan Biotechnology Research Center, Tripoli, Libya, between December 1, 2021, and January 31, 2022, for patients complaining of respiratory symptoms using a multiplex reverse transcription-polymerase chain reaction test for SARS-COV-2, influenza A and B, and RSV. Results: We analyzed nasopharyngeal swabs in viral transport media from 2,186 samples. About 27% (589/2186) of study patients tested positive for SARS-COV-2, 2.8% (61/2186) were positive for influenza A virus, 0.18% (4/2186) for influenza B virus, and 1.4% (31/2186) tested positive for RSV. Conclusions: These results revealed that along with COVID-19, influenza infections were also rising. As the COVID-19 pandemic continues, the most significant concern is the development of an influenza outbreak in the upcoming months. Therefore, continuing annual influenza vaccination is critical to increasing population immunity. National influenza surveillance and testing should also be conducted. Furthermore, sequencing and antigenic characterization should be performed regularly. There is a need for continuous monitoring in national laboratories to detect any zoonotic cases and substantial viral evolution.
Keywords	influenza vaccination ; COVID-19 ; surveillance ; influenza activity ; Libya
Language	English
Publishing date	2022-12-01
Publisher	Thieme Medical and Scientific Publishers Pvt. Ltd.
Publishing place	Stuttgart ; New York
Document type	Article
ZDB-ID	2585341-7
ISSN	1947-489X ; 1947-489X
ISSN (online)	1947-489X
ISSN	1947-489X
DOI	10.1055/s-0042-1760225
Database	Thieme publisher's database

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Article ; Online: Analysis of geo-temporal evolution and modeling of the COVID-19 epidemic in Libya

Bredan, Amin / Benamer, Hani / Bakoush, Omran

medRxiv

Abstract: ... and other protective measures in that region. The epidemic in Libya was modeled using the classical ... prepared to meet the challenges of the COVId-19 pandemic. Nevertheless, restriction of travel and ... Having been experiencing years of political fragmentation and military conflict, Libya was poorly ...

Abstract	Having been experiencing years of political fragmentation and military conflict, Libya was poorly prepared to meet the challenges of the COVId-19 pandemic. Nevertheless, restriction of travel and social distancing rules were put in place days before the first case was detected. During the next two months, the number of cases grew gradually to 77 cases, followed by a rapid spread that has produced 3691 confirmed cases and 80 deaths by the end of July 2020. The turning point on 26 May 2020 was preceded three weeks earlier by the arrival of the first of a series of flights repatriating Libyans who became stranded abroad when air travel was suspended. In the first weeks of the surge, the number of cases was particularly high in the less densely populated southern region, raising questions about the implementation of social distancing and other protective measures in that region. The epidemic in Libya was modeled using the classical Susceptible-Exposed-Infected-Recovered (SEIR) mathematical model of infectious disease epidemics. Three scenarios were developed based on three estimates of the fraction of the population exposed to the disease (1.5, 2.5 and 3.5%). The modeling portrays the peak of the epidemic around early August and estimates that the number of deaths will flatten out around early November at between 250 and 600, depending on the parameter employed. More deaths than those estimated implies that is more widespread than assumed. Greater promotion of awareness and understanding of social distancing practices and their value is needed, particularly in the south, and better protection of the elderly should decrease mortality.
Keywords	covid19
Language	English
Publishing date	2020-09-22
Publisher	Cold Spring Harbor Laboratory Press
Document type	Article ; Online
DOI	10.1101/2020.09.19.20197822
Database	COVID19

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Article ; Online: Analysis of geo-temporal evolution and modeling of the COVID-19 epidemic in Libya

Bredan, A. / Benamer, H. / Bakoush, O.

Abstract	Having been experiencing years of political fragmentation and military conflict, Libya was poorly prepared to meet the challenges of the COVId-19 pandemic. Nevertheless, restriction of travel and social distancing rules were put in place days before the first case was detected. During the next two months, the number of cases grew gradually to 77 cases, followed by a rapid spread that has produced 3691 confirmed cases and 80 deaths by the end of July 2020. The turning point on 26 May 2020 was preceded three weeks earlier by the arrival of the first of a series of flights repatriating Libyans who became stranded abroad when air travel was suspended. In the first weeks of the surge, the number of cases was particularly high in the less densely populated southern region, raising questions about the implementation of social distancing and other protective measures in that region. The epidemic in Libya was modeled using the classical Susceptible-Exposed-Infected-Recovered (SEIR) mathematical model of infectious disease epidemics. Three scenarios were developed based on three estimates of the fraction of the population exposed to the disease (1.5, 2.5 and 3.5%). The modeling portrays the peak of the epidemic around early August and estimates that the number of deaths will flatten out around early November at between 250 and 600, depending on the parameter employed. More deaths than those estimated implies that is more widespread than assumed. Greater promotion of awareness and understanding of social distancing practices and their value is needed, particularly in the south, and better protection of the elderly should decrease mortality.
Keywords	covid19
Publisher	MedRxiv; WHO
Document type	Article ; Online
DOI	10.1101/2020.09.19.20197822
Database	COVID19

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Article ; Online: Low SARS-CoV-2 Antibodies in Blood Donors After the First 6 Months of COVID-19 Epidemic in the Tobruk Region, Eastern Libya.

Ismail, Faisal / Farag, Atiya / Haq, Soghra / Kamal, Mohammad Amjad

Disaster medicine and public health preparedness

2022 , Page(s) 1–2

Language	English
Publishing date	2022-07-27
Publishing country	United States
Document type	Journal Article
ZDB-ID	2375268-3
ISSN	1938-744X ; 1935-7893
ISSN (online)	1938-744X
ISSN	1935-7893
DOI	10.1017/dmp.2022.180
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Article ; Online: A New Mathematical Approach for the Estimation of epidemic Model Parameters with Demonstration on COVID-19 Pandemic in Libya

Saleh, M. E. / Saleh, Z. E.

Abstract: ... epidemic model is used to model the COVID-19 pandemic in Libya. Two sets of data are needed to evaluate ... This new technique will be demonstrated on the spread of COVID-19 in Libya. Methods: A five compartmental ... to determine most of the model parameters. Results: Libya epidemic start-date was estimated as t_o=-18.5 days ...

Abstract	Background: The SEIR model or a variation of it is commonly used to study epidemic spread and make predictions on how it evolves. It is used to guide officials in their response to an epidemic. This research demonstrates an effective and simple approach that estimates the parameters of any variations of the SEIR model. This new technique will be demonstrated on the spread of COVID-19 in Libya. Methods: A five compartmental epidemic model is used to model the COVID-19 pandemic in Libya. Two sets of data are needed to evaluate the model parameters, the cumulative number of symptomatic cases and the total number of active cases. This data along with the assumption that the cumulative number of symptomatic cases grows exponentially, to determine most of the model parameters. Results: Libya epidemic start-date was estimated as t_o=-18.5 days, corresponding to May 5th. We mathematically demonstrated that the number of active cases follows two competing exponential distributions: a positive exponential function, measuring how many new cases are added, and a negative exponential function, measuring how many cases recovered. From this distribution we showed that the average recovery time is 48 days, and the incubation period is 15.2 days. Finally, the productive number was estimated as R0 = 7.6. Conclusions: With only the cumulative number of cases and the total number of active cases of COVID19, several important SEIR model parameters can be measured effectively. This approach can be applied for any infectious disease epidemic anywhere in the world.
Keywords	covid19
Publisher	MedRxiv; WHO
Document type	Article ; Online
DOI	10.1101/2020.07.19.20157115
Database	COVID19

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Article ; Online: A New Mathematical Approach for the Estimation of epidemic Model Parameters with Demonstration on COVID-19 Pandemic in Libya

Saleh, Mohamed E / Saleh, Zeinab Elmehdi

medRxiv

Abstract	Background: The SEIR model or a variation of it is commonly used to study epidemic spread and make predictions on how it evolves. It is used to guide officials in their response to an epidemic. This research demonstrates an effective and simple approach that estimates the parameters of any variations of the SEIR model. This new technique will be demonstrated on the spread of COVID-19 in Libya. Methods: A five compartmental epidemic model is used to model the COVID-19 pandemic in Libya. Two sets of data are needed to evaluate the model parameters, the cumulative number of symptomatic cases and the total number of active cases. This data along with the assumption that the cumulative number of symptomatic cases grows exponentially, to determine most of the model parameters. Results: Libya epidemic start-date was estimated as t_o=-18.5 days, corresponding to May 5th. We mathematically demonstrated that the number of active cases follows two competing exponential distributions: a positive exponential function, measuring how many new cases are added, and a negative exponential function, measuring how many cases recovered. From this distribution we showed that the average recovery time is 48 days, and the incubation period is 15.2 days. Finally, the productive number was estimated as R0 = 7.6. Conclusions: With only the cumulative number of cases and the total number of active cases of COVID19, several important SEIR model parameters can be measured effectively. This approach can be applied for any infectious disease epidemic anywhere in the world.
Keywords	covid19
Language	English
Publishing date	2020-07-21
Publisher	Cold Spring Harbor Laboratory Press
Document type	Article ; Online
DOI	10.1101/2020.07.19.20157115
Database	COVID19

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Article ; Online: Evaluation of health system resilience in 60 countries based on their responses to COVID-19.

Zhao, Laijun / Jin, Yajun / Zhou, Lixin / Yang, Pingle / Qian, Ying / Huang, Xiaoyan / Min, Mengmeng

Frontiers in public health

2023 Volume 10, Page(s) 1081068

Abstract: Introduction: In 2020, the COVID-19 epidemic swept the world, and many national health systems ... for national health systems based on their responses to COVID-19 using four resilience dimensions: government ... Government governance and prevention of COVID-19 will greatly affect a country's success in fighting future ...

Abstract	Introduction: In 2020, the COVID-19 epidemic swept the world, and many national health systems faced serious challenges. To improve future public health responses, it's necessary to evaluate the performance of each country's health system. Methods: We developed a resilience evaluation system for national health systems based on their responses to COVID-19 using four resilience dimensions: government governance and prevention, health financing, health service provision, and health workers. We determined the weight of each index by combining the three-scale and entropy-weight methods. Then, based on data from 2020, we used the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to rank the health system resilience of 60 countries, and then used hierarchical clustering to classify countries into groups based on their resilience level. Finally, we analyzed the causes of differences among countries in their resilience based on the four resilience dimensions. Results: Switzerland, Japan, Germany, Australia, South Korea, Canada, New Zealand, Finland, the United States, and the United Kingdom had the highest health system resilience in 2020. Eritrea, Nigeria, Libya, Tanzania, Burundi, Mozambique, Republic of the Niger, Benin, Côte d'Ivoire, and Guinea had the lowest resilience. Discussion: Government governance and prevention of COVID-19 will greatly affect a country's success in fighting future epidemics, which will depend on a government's emergency preparedness, stringency (a measure of the number and rigor of the measures taken), and testing capability. Given the lack of vaccines or specific drug treatments during the early stages of the 2020 epidemic, social distancing and wearing masks were the main defenses against COVID-19. Cuts in health financing had direct and difficult to reverse effects on health systems. In terms of health service provision, the number of hospitals and intensive care unit beds played a key role in COVID-19 clinical care. Resilient health systems were able to cope more effectively with the impact of COVID-19, provide stronger protection for citizens, and mitigate the impacts of COVID-19. Our evaluation based on data from 60 countries around the world showed that increasing health system resilience will improve responses to future public health emergencies.
MeSH term(s)	Humans ; United States ; COVID-19/epidemiology ; COVID-19/prevention & control ; SARS-CoV-2 ; Epidemics ; Public Health ; Government
Language	English
Publishing date	2023-01-09
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2711781-9
ISSN	2296-2565 ; 2296-2565
ISSN (online)	2296-2565
ISSN	2296-2565
DOI	10.3389/fpubh.2022.1081068
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Article ; Online: The Heterogeneous Severity of COVID-19 in African Countries: A Modeling Approach.

Musa, Salihu Sabiu / Wang, Xueying / Zhao, Shi / Li, Shudong / Hussaini, Nafiu / Wang, Weiming / He, Daihai

Bulletin of mathematical biology

2022 Volume 84, Issue 3, Page(s) 32

Abstract: ... infection attack rate. We develop a simple epidemic model and fitted it to reported COVID-19 deaths in 12 ... The COVID-19 pandemic has had a considerable impact on global health and economics. The impact ... COVID-19 deaths to estimate the time-varying basic reproductive number ([Formula: see text]) and ...

Abstract	The COVID-19 pandemic has had a considerable impact on global health and economics. The impact in African countries has not been investigated thoroughly via fitting epidemic models to the reported COVID-19 deaths. We downloaded the data for the 12 most-affected countries with the highest cumulative COVID-19 deaths to estimate the time-varying basic reproductive number ([Formula: see text]) and infection attack rate. We develop a simple epidemic model and fitted it to reported COVID-19 deaths in 12 African countries using iterated filtering and allowing a flexible transmission rate. We observe high heterogeneity in the case-fatality rate across the countries, which may be due to different reporting or testing efforts. South Africa, Tunisia, and Libya were most affected, exhibiting a relatively higher [Formula: see text] and infection attack rate. Thus, to effectively control the spread of COVID-19 epidemics in Africa, there is a need to consider other mitigation strategies (such as improvements in socioeconomic well-being, healthcare systems, the water supply, and awareness campaigns).
MeSH term(s)	COVID-19 ; Humans ; Mathematical Concepts ; Models, Biological ; Pandemics ; SARS-CoV-2 ; South Africa
Language	English
Publishing date	2022-01-24
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	184905-0
ISSN	1522-9602 ; 0007-4985 ; 0092-8240
ISSN (online)	1522-9602
ISSN	0007-4985 ; 0092-8240
DOI	10.1007/s11538-022-00992-x
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