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Woldegebriel Assefa Woldegerima Person1 #715767 Dr. Woldegerima, knows as "Assefa", is an Assistant Professor at the Department of Mathematics and Statistics at York University. | - Before his recruitment to York University, Assefa was a Postdoctoral Research Fellow at the Mathematical Models and Methods in Biosciences and Bioengineering Lab at the University of Pretoria, South Africa. He has obtained his Ph.D. from the University of Buea, Cameroon in a collaboration with Lehigh University in the USA in August 2018 on In-host Immunopathogenesis modelling”, and his Master’s degrees: one from the African Institute for Mathematical Sciences (AIMS) with a master thesis on “Existence and uniqueness of viscosity solutions for Hamilton-Jacobi PDEs and applications to optimal control theory”.
Research Interests - In-host modelling, infectious modelling, modelling the impact of climate change on infectious disease dynamics, applied differential equations, AI for pandemic prepardness, ODE Neural networks, data analysis in Python.
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+Citations (8) - CitationsAjouter une citationList by: CiterankMapLink[2] COVID-19 and Malaria Co-Infection: Do Stigmatization and Self-Medication Matter? A Mathematical Modelling Study for Nigeria
En citant: Wisdom Avusuglo, Qing Han, Woldegebriel Assefa Woldegerima, Nicola Luigi Bragazzi, Ali Ahmadi, Ali Asgary, Jianhong Wu, James Orbinski, Jude Dzevela Kong Publication date: 11 May 2022 Publication info: SSRN Cité par: David Price 5:56 PM 1 December 2023 GMT Citerank: (6) 679750Ali AsgaryAssociate Professor and Associate Director, Advanced Disaster, Emergency and Rapid Response Simulation (ADERSIM) in the School of Administrative Studies, and Adjunct Professor in the School of Information Technology, at York University.10019D3ABAB, 679812Jianhong WuProfessor Jianhong Wu is a University Distinguished Research Professor and Senior Canada Research Chair in industrial and applied mathematics at York University. He is also the NSERC Industrial Research Chair in vaccine mathematics, modelling, and manufacturing. 10019D3ABAB, 679815Jude KongDr. Jude Dzevela Kong is an Assistant Professor in the Department of Mathematics and Statistics at York University and the founding Director of the Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC). 10019D3ABAB, 701037MfPH – Publications144B5ACA0, 704042Malaria859FDEF6, 704045Covid-19859FDEF6 URL: DOI: http://dx.doi.org/10.2139/ssrn.4090040
| Extrait - [SSRN, 11 May 2022]
Self-medication and the use of complementary medicine are common among people in the Global South for social, economic, and psychological reasons. Governments in these countries are generally faced with several challenges, including limited resources and poor infrastructure, and patient health literacy. For COVID-19, this is fueled by the rapid spread of rumors in favour of these modalities on social media. Also common in the Global South is the stigmatization of people with COVID-19. Because of the stigma attached to having COVID-19, most COVID-19 patients prefer to test instead for malaria, since malaria (which is very common in the Global South) and COVID-19 share several symptoms leading to misdiagnosis. Thus, to efficiently predict the dynamics of COVID-19 in the Global South, the role of the self-medicated population, the dynamics of malaria, and the impact of stigmatization need to be taken into account. In this paper, we formulate and analyze a mathematical model for the co-dynamics of COVID-19 and malaria in Nigeria. The model is represented by a system of compartmental ODEs that take into account the self-medicated population and the impact of COVID-19 stigmatization. Our findings reveal that COVID-19 stigmatization and misdiagnosis contribute to self-medication, which, in turn, increases the prevalence of COVID-19. The basic and invasion reproduction numbers for these diseases and quantification of model parameters uncertainties and sensitivities are presented. |
Link[3] Knowing the unknown: The underestimation of monkeypox cases. Insights and implications from an integrative review of the literature
En citant: Nicola Luigi Bragazzi, Woldegebriel Assefa Woldegerima, Sarafa Adewale Iyaniwura, Qing Han, Xiaoying Wang, Aminath Shausan, Kingsley Badu, Patrick Okwen, Cheryl Prescod, Michelle Westin, Andrew Omame, Manlio Converti, Bruce Mellado, Jianhong Wu, Jude Dzevela Kong Publication date: 23 September 2022 Publication info: Frontiers in Microbiology, 23 September 2022 Cité par: David Price 5:57 PM 1 December 2023 GMT Citerank: (4) 679812Jianhong WuProfessor Jianhong Wu is a University Distinguished Research Professor and Senior Canada Research Chair in industrial and applied mathematics at York University. He is also the NSERC Industrial Research Chair in vaccine mathematics, modelling, and manufacturing. 10019D3ABAB, 679815Jude KongDr. Jude Dzevela Kong is an Assistant Professor in the Department of Mathematics and Statistics at York University and the founding Director of the Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC). 10019D3ABAB, 701037MfPH – Publications144B5ACA0, 715667mpox859FDEF6 URL: DOI: https://doi.org/10.3389/fmicb.2022.1011049
| Extrait - [Frontiers in Microbiology, 23 September 2022]
Monkeypox is an emerging zoonotic disease caused by the monkeypox virus, which is an infectious agent belonging to the genus Orthopoxvirus. Currently, commencing from the end of April 2022, an outbreak of monkeypox is ongoing, with more than 43,000 cases reported as of 23 August 2022, involving 99 countries and territories across all the six World Health Organization (WHO) regions. On 23 July 2022, the Director-General of the WHO declared monkeypox a global public health emergency of international concern (PHEIC), since the outbreak represents an extraordinary, unusual, and unexpected event that poses a significant risk for international spread, requiring an immediate, coordinated international response. However, the real magnitude of the burden of disease could be masked by failures in ascertainment and under-detection. As such, underestimation affects the efficiency and reliability of surveillance and notification systems and compromises the possibility of making informed and evidence-based policy decisions in terms of the adoption and implementation of ad hoc adequate preventive measures. In this review, synthesizing 53 papers, we summarize the determinants of the underestimation of sexually transmitted diseases, in general, and, in particular, monkeypox, in terms of all their various components and dimensions (under-ascertainment, underreporting, under-detection, under-diagnosis, misdiagnosis/misclassification, and under-notification). |
Link[4] Assessing the epidemiological and economic impact of alternative vaccination strategies: a modeling study
En citant: S. Kim, S. Athar, Y. LI, S. Koumarianos, T. Cheng, L. Amiri, W. Avusuglo, W.A. Woldegerima, A.A. Fall, A. John-Baptiste, A. Diener, J. Wu Publication date: 28 February 2022 Publication info: International Journal of Infectious Diseases, 116, S60–S60, March 2022. Cité par: David Price 5:58 PM 1 December 2023 GMT Citerank: (6) 679812Jianhong WuProfessor Jianhong Wu is a University Distinguished Research Professor and Senior Canada Research Chair in industrial and applied mathematics at York University. He is also the NSERC Industrial Research Chair in vaccine mathematics, modelling, and manufacturing. 10019D3ABAB, 686719Alan DienerDr. Diener is the Assistant Director of the Policy Research, Economics and Analytics unit, in the Strategic Policy Branch at Health Canada. Alan received his PhD in economics from McMaster University and he has previously held positions at the University of Nebraska Medical Center, the Public Health Agency of Canada, and the Organisation for Economic Cooperation and Development (OECD) where he was a consultant in the Health Division from 2011 to 2013.10019D3ABAB, 701037MfPH – Publications144B5ACA0, 703957Economics859FDEF6, 704041Vaccination859FDEF6, 704045Covid-19859FDEF6 URL: DOI: https://doi.org/10.1016/j.ijid.2021.12.142
| Extrait - [International Journal of Infectious Diseases, 28 February 2022]
Purpose: Given limited supplies of vaccines, having information on the costs, and associated health and economic impacts, is important for the development of optimal vaccination strategies. This study explores the epidemiological and economic impact, in terms of the value of lost production, of four vaccination strategies – fixed-dose interval (M1), prioritization of the first dose (M2), screen and forego vaccine for those with COVID-19 infection history (M3), and prioritization of the first dose along with screen and forego vaccine for those with COVID-19 infection history(M4), under constraints limiting the daily vaccine supply.
Methods & Materials: Using mathematical and statistical modelling, we quantified the number quarantined, hospitalization days, vaccine doses saved, and deaths averted, and production losses, for each strategy, in comparison to M1. The model parameters and initial conditions were based on Canadian data, and the simulation ran over 365 days starting from June 1, 2021. Sensitivity analyses explored how each strategy changes with different conditions of daily vaccine supply, the initial proportion recovered from COVID19 infection, and initial coverage of the first dose.
Results: Strategy M2 results in a reduction of 67,130,775 doses of vaccine administered, 20 lives saved, and a reduction of $3.8 billion of lost production in comparison to M1. M3 does not save any vaccine dose administered, but results in 5 lives saved, and a reduction of $575,149 in lost production in comparison to strategy M1. Due to the large proportion of the Canadian population who have already received a first vaccine dose, no screening actually occurs under scenario M3 and the daily vaccine supply was used entirely to provide second doses. While M2 is the dominant strategy under the current Canadian setting, sensitivity analyses revealed that M3 dominates when the vaccine supply increased or when the initial recovered proportion from COVID-19 was large enough.
Conclusion: The findings quantify the potential benefits of alternative vaccination strategies that can save lives and costs. Our study findings can help policymakers identify the optimal COVID19 vaccination strategy and our study framework can be adapted to other settings. |
Link[5] Mitigating co-circulation of seasonal influenza and COVID-19 pandemic in the presence of vaccination: A mathematical modeling approach
En citant: Bushra Majeed, Jummy Funke David, Nicola Luigi Bragazzi, Zack McCarthy, Martin David Grunnill, Jane Heffernan, Jianhong Wu, Woldegebriel Assefa Woldegerima Publication date: 4 January 2023 Publication info: Frontiers in Public Health, 4 January 2023 Cité par: David Price 5:58 PM 1 December 2023 GMT Citerank: (6) 679806Jane HeffernanJane Heffernan is a professor of infectious disease modelling in the Mathematics & Statistics Department at York University. She is a co-director of the Canadian Centre for Disease Modelling, and she leads national and international networks in mathematical immunology and the modelling of waning and boosting immunity.10019D3ABAB, 679812Jianhong WuProfessor Jianhong Wu is a University Distinguished Research Professor and Senior Canada Research Chair in industrial and applied mathematics at York University. He is also the NSERC Industrial Research Chair in vaccine mathematics, modelling, and manufacturing. 10019D3ABAB, 701037MfPH – Publications144B5ACA0, 703974Influenza859FDEF6, 704041Vaccination859FDEF6, 704045Covid-19859FDEF6 URL: DOI: https://doi.org/10.3389/fpubh.2022.1086849
| Extrait - [Frontiers in Public Health, 4 January 2023]
The co-circulation of two respiratory infections with similar symptoms in a population can significantly overburden a healthcare system by slowing the testing and treatment. The persistent emergence of contagious variants of SARS-CoV-2, along with imperfect vaccines and their waning protections, have increased the likelihood of new COVID-19 outbreaks taking place during a typical flu season. Here, we developed a mathematical model for the co-circulation dynamics of COVID-19 and influenza, under different scenarios of influenza vaccine coverage, COVID-19 vaccine booster coverage and efficacy, and testing capacity. We investigated the required minimal and optimal coverage of COVID-19 booster (third) and fourth doses, in conjunction with the influenza vaccine, to avoid the coincidence of infection peaks for both diseases in a single season. We show that the testing delay brought on by the high number of influenza cases impacts the dynamics of influenza and COVID-19 transmission. The earlier the peak of the flu season and the greater the number of infections with flu-like symptoms, the greater the risk of flu transmission, which slows down COVID-19 testing, resulting in the delay of complete isolation of patients with COVID-19 who have not been isolated before the clinical presentation of symptoms and have been continuing their normal daily activities. Furthermore, our simulations stress the importance of vaccine uptake for preventing infection, severe illness, and hospitalization at the individual level and for disease outbreak control at the population level to avoid putting strain on already weak and overwhelmed healthcare systems. As such, ensuring optimal vaccine coverage for COVID-19 and influenza to reduce the burden of these infections is paramount. We showed that by keeping the influenza vaccine coverage about 35% and increasing the coverage of booster or fourth dose of COVID-19 not only reduces the infections with COVID-19 but also can delay its peak time. If the influenza vaccine coverage is increased to 55%, unexpectedly, it increases the peak size of influenza infections slightly, while it reduces the peak size of COVID-19 as well as significantly delays the peaks of both of these diseases. Mask-wearing coupled with a moderate increase in the vaccine uptake may mitigate COVID-19 and prevent an influenza outbreak. |
Link[6] A cross-country analysis of macroeconomic responses to COVID-19 pandemic using Twitter sentiments
En citant: Zahra Movahedi Nia, Ali Ahmadi, Nicola L. Bragazzi, Woldegebriel Assefa Woldegerima, Bruce Mellado, Jianhong Wu, James Orbinski, Ali Asgary, Jude Dzevela Kong Publication date: 24 August 2022 Publication info: PLOS ONE, 17(8), e0272208 Cité par: David Price 5:59 PM 1 December 2023 GMT
Citerank: (7) 679750Ali AsgaryAssociate Professor and Associate Director, Advanced Disaster, Emergency and Rapid Response Simulation (ADERSIM) in the School of Administrative Studies, and Adjunct Professor in the School of Information Technology, at York University.10019D3ABAB, 679812Jianhong WuProfessor Jianhong Wu is a University Distinguished Research Professor and Senior Canada Research Chair in industrial and applied mathematics at York University. He is also the NSERC Industrial Research Chair in vaccine mathematics, modelling, and manufacturing. 10019D3ABAB, 679815Jude KongDr. Jude Dzevela Kong is an Assistant Professor in the Department of Mathematics and Statistics at York University and the founding Director of the Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC). 10019D3ABAB, 701037MfPH – Publications144B5ACA0, 703957Economics859FDEF6, 704045Covid-19859FDEF6, 715666Social networks859FDEF6 URL: DOI: https://doi.org/10.1371/journal.pone.0272208
| Extrait - [PLOS ONE, 24 August 2022]
The COVID-19 pandemic has had a devastating impact on the global economy. In this paper, we use the Phillips curve to compare and analyze the macroeconomics of three different countries with distinct income levels, namely, lower-middle (Nigeria), upper-middle (South Africa), and high (Canada) income. We aim to (1) find macroeconomic changes in the three countries during the pandemic compared to pre-pandemic time, (2) compare the countries in terms of response to the COVID-19 economic crisis, and (3) compare their expected economic reaction to the COVID-19 pandemic in the near future. An advantage to our work is that we analyze macroeconomics on a monthly basis to capture the shocks and rapid changes caused by on and off rounds of lockdowns. We use the volume and social sentiments of the Twitter data to approximate the macroeconomic statistics. We apply four different machine learning algorithms to estimate the unemployment rate of South Africa and Nigeria on monthly basis. The results show that at the beginning of the pandemic the unemployment rate increased for all the three countries. However, Canada was able to control and reduce the unemployment rate during the COVID-19 pandemic. Nonetheless, in line with the Phillips curve short-run, the inflation rate of Canada increased to a level that has never occurred in more than fifteen years. Nigeria and South Africa have not been able to control the unemployment rate and did not return to the pre-COVID-19 level. Yet, the inflation rate has increased in both countries. The inflation rate is still comparable to the pre-COVID-19 level in South Africa, but based on the Phillips curve short-run, it will increase further, if the unemployment rate decreases. Unfortunately, Nigeria is experiencing a horrible stagflation and a wild increase in both unemployment and inflation rates. This shows how vulnerable lower-middle-income countries could be to lockdowns and economic restrictions. In the near future, the main concern for all the countries is the high inflation rate. This work can potentially lead to more targeted and publicly acceptable policies based on social media content. |
Link[7] Adaptive changes in sexual behavior in the high-risk population in response to human monkeypox transmission in Canada can help control the outbreak: Insights from a two-group, two-route epidemic model
En citant: Nicola Luigi Bragazzi, Qing Han, Sarafa Adewale Iyaniwura, Andrew Omame, Aminath Shausan, Xiaoying Wang, Woldegebriel Assefa Woldegerima, Jianhong Wu, Jude Dzevela Kong Publication date: 11 February 2023 Publication info: Journal of Medical Virology, Volume 95, Issue 4 e28575 Cité par: David Price 6:00 PM 1 December 2023 GMT Citerank: (4) 679812Jianhong WuProfessor Jianhong Wu is a University Distinguished Research Professor and Senior Canada Research Chair in industrial and applied mathematics at York University. He is also the NSERC Industrial Research Chair in vaccine mathematics, modelling, and manufacturing. 10019D3ABAB, 679815Jude KongDr. Jude Dzevela Kong is an Assistant Professor in the Department of Mathematics and Statistics at York University and the founding Director of the Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC). 10019D3ABAB, 701037MfPH – Publications144B5ACA0, 715667mpox859FDEF6 URL: DOI: https://doi.org/10.1002/jmv.28575
| Extrait - [Journal of Medical Virology, 11 February 2023]
Monkeypox, a zoonotic disease, is emerging as a potential sexually transmitted infection/disease, with underlying transmission mechanisms still unclear. We devised a risk-structured, compartmental model, incorporating sexual behavior dynamics. We compared different strategies targeting the high-risk population: a scenario of control policies geared toward the use of condoms and/or sexual abstinence (robust control strategy) with risk compensation behavior change, and a scenario of control strategies with behavior change in response to the doubling rate (adaptive control strategy). Monkeypox's basic reproduction number is 1.464, 0.0066, and 1.461 in the high-risk, low-risk, and total populations, respectively, with the high-risk group being the major driver of monkeypox spread. Policies imposing condom use or sexual abstinence need to achieve a 35% minimum compliance rate to stop further transmission, while a combination of both can curb the spread with 10% compliance to abstinence and 25% to condom use. With risk compensation, the only option is to impose sexual abstinence by at least 35%. Adaptive control is more effective than robust control where the daily sexual contact number is reduced proportionally and remains constant thereafter, shortening the time to epidemic peak, lowering its size, facilitating disease attenuation, and playing a key role in controlling the current outbreak. |
Link[8] Seminar 16: Quantifying the basic reproduction number and the under-estimated fraction of mpox cases around the world at the onset of the outbreak
En citant: Woldegebriel Assefa Woldegerima Publication date: 18 January 2024 Publication info: OMNI-REUNIS Super-Spreader Seminar Series Cité par: David Price 5:34 PM 2 February 2024 GMT Citerank: (1) 717279240118 Quantifying the basic reproduction number of mpox casesSeminar 16: Quantifying the basic reproduction number and the under-estimated fraction of mpox cases around the world at the onset of the outbreak: a mathematical modelling and machine learning-based study. Speaker: Dr. Woldegebriel Assefa Woldegerima, 18 January 2024.63E883B6 URL:
| Extrait - Abstract: The current global outbreak of mpox, which started in April 2022 has different epidemiological and clinical features compared to previous mpox outbreaks. Sexual contact has been hypothesized as the major transmission route for the disease in this outbreak, with the community of men having sex with men (MSM) disproportionately and dramatically affected. To better understand the transmission dynamics of the disease, it is essential to understand its dynamics during the early stages of the outbreak. In this article, we estimate the basic reproduction number and the ascertainment fraction of the reported cases of mpox around the world. We divide the population of each country into two groups (high- risk and low-risk groups) and consider two routes of transmission: sexual and non- sexual. Our estimate of the basic reproduction number of mpox in the considered countries ranges between 1.37 (Canada) and 3.68 (Germany). Furthermore, our estimates of the ascertainment fraction for the reported cases of mpox show a large variation in the under-reporting of cases in the high-risk population around the world with ascertainment fractions between 0.25 and 0.93, and a more consistent ascertainment fraction for the low-risk population, which ranges from 0.65 to 0.85. The ratio between the total estimated and observed cases yielded the highest values for Colombia (3.60), followed by Chile (2.57) and Mexico (2.16), whilst the lowest value was obtained for Canada (1.08). Its median value was 1.8. Our estimates can help public health decision- and policymakers better understand the mpox outbreak, in terms of how many underestimated cases can occur in several countries, and how the epidemic can spread differently. |
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