Evaluation of Dacryodes edulis (Burseraceae) exudate as a binding agent in paracetamol matrix tablet formulation

The binding ability of the stem bark exudate of Dacryodes edulis (Buseraceae) in paracetamol matrix tablet formulation was compared with that of Eudragit L-100. Crude exudates were purified by differential precipitation with water in acetone and petroleum ether and air-dried. Varying concentrations (1-10 %w/v) of the purified exudate or Eudragit L-100 were dissolved in acetone and used to form paracetamol matrix granules while 15 % w/v maize starch was used to form conventional granules by wet granulation. Drug excipient compatibility was carried out and the granules compressed into tablets. Tablet properties were evaluated and the data analyzed statistically using the student t-test (p < 0.05). Results showed a 71 % yield of the purified exudate. The exudate functioned perfectly as binder in the formulation of tablets at concentrations > 2.5 %w/v and compared favourably with Eudragit L-100. Tablets formed did not disintegrate within 15 min except for those formed with maize starch mucilage. The dissolution data fitted into the Higuchi equation with r2-values ≥ 0.95. Dacroydes edulis exudate extended the release profile of paracetamol up to 70 % within 5 h.Keywords: Dacroydes edulis, exudate, binder, Eudragit L-100, tablet

A primer on using mathematics to understand COVID-19 dynamics : modeling, analysis and simulations

The novel coronavirus (COVID-19) pandemic that emerged from Wuhan city in December 2019 overwhelmed health systems and paralyzed economies around the world. It became the most important public health challenge facing mankind since the 1918 Spanish flu pandemic. Various theoretical and empirical approaches have been designed and used to gain insight into the transmission dynamics and control of the pandemic. This study presents a primer for formulating, analysing and simulating mathematical models for understanding the dynamics of COVID-19. Specifically, we introduce simple compartmental, Kermack-McKendrick-type epidemic models with homogeneously- and heterogeneously-mixed populations, an endemic model for assessing the potential population-level impact of a hypothetical COVID-19 vaccine. We illustrate how some basic non-pharmaceutical interventions against COVID-19 can be incorporated into the epidemic model. A brief overview of other kinds of models that have been used to study the dynamics of COVID-19, such as agent-based, network and statistical models, is also presented. Possible extensions of the basic model, as well as open challenges associated with the formulation and theoretical analysis of models for COVID-19 dynamics, are suggested.The Simons Foundation and the National Science Foundation.http://www.keaipublishing.com/idmam2022Mathematics and Applied Mathematic

A Comparative Study of Sentiment-Based Graphs of Text Summaries

Sentiment included in a sentence can indicate whether a sentence may have positive, negative or neutral polarity. Polarity of the sentences is deemed important in text summarization, especially when summarizing narrative texts. This paper proposes to discover the patterns and sentiment scores of the summaries generated by established summarization methods: Luhn, Latent Semantic Analysis (LSA) and LexRank. This is done by conducting a study and comparison on the generated sentiment-based graphs of the summaries. A comparative study is conducted on the sentiment-based graph of the generated summaries with two different sentiment lexicons, namely SentiWordNet and VADER. The analysis is conducted by comparing the patterns of the sentiment-based graph and their sentiment scores as well. In the experiments conducted, there is an obvious pattern for the two sentiment lexicons. This implies that sentiment-based graph’s pattern and score are helpful in generating a compact summary. The analysis will alleviate future research on sentiment-based summarization and motivates a new method which can be considered as a graph-based summarization to extract a summary based on its sentiment score

Mathematical modeling of the impact of periodic release of sterile male mosquitoes and seasonality on the population abundance of malaria mosquitoes

This study presents a new mathematical model for assessing the impact of sterile insect technology (SIT) and seasonal variation in local temperature on the population abundance of malaria mosquitoes in an endemic setting. Simulations of the model, using temperature data from Kipsamoite area of Kenya, show that a peak abundance of the mosquito population is attained in the Kipsamoite area when the mean monthly temperature reaches 30∘C. Furthermore, in the absence of seasonal variation in local temperature, our results show that releasing more sterile male mosquitoes (e.g., 100,000) over a one year period with relatively short duration between releases (e.g., weekly, bi-weekly or even monthly) is more effective than releasing smaller numbers of the sterile male mosquitoes (e.g., 10,000) over the same implementation period and frequency of release. It is also shown that density-dependent larval mortality plays an important role in determining the threshold number of sterile male mosquitoes that need to be released in order to achieve effective control (or elimination) of the mosquito population in the community. In particular, low(high) density-dependent mortality requires high(low) numbers of sterile male mosquitoes to be released to achieve such control. In the presence of seasonal variation in local temperature, effective control of the mosquito population using SIT is only feasible if a large number of the sterile male mosquitoes (e.g., 100,000) is periodically released within a very short time interval (at most weekly). In other words, seasonal variation in temperature necessitates more frequent releases (of a large number) of sterile male mosquitoes to ensure the effectiveness of the SIT intervention in curtailing the targeted mosquito population.The National Institute for Mathematical and Biological Synthesis (NIMBioS) for funding the Working Group on Climate Change and Vector-borne Diseases (VBDs). NIMBioS is an Institute sponsored by the National Science Foundation, the U.S. Department of Homeland Security, and the U.S. Department of Agriculture through NSF Award #EF-0832858, with additional support from The University of Tennessee, Knoxville. ABG also acknowledge the support, in part, of the Simons Foundation (Award #585022) and the National Science Foundation (Award #1917512).https://www.worldscientific.com/worldscinet/jbs2021-04-18hj2020Mathematics and Applied Mathematic

Will an imperfect vaccine curtail the COVID-19 pandemic in the U.S.?

The novel coronavirus (COVID-19) that emerged from Wuhan city of China in late December 2019 continue to pose devastating public health and economic challenges across the world. Although the community-wide implementation of basic non-pharmaceutical intervention measures, such as social distancing, quarantine of suspected COVID-19 cases, isolation of confirmed cases, use of face masks in public, contact tracing and testing, have been quite effective in curtailing and mitigating the burden of the pandemic, it is universally believed that the use of a vaccine may be necessary to effectively curtail and eliminating COVID-19 in human populations. This study is based on the use of a mathematical model for assessing the impact of a hypothetical imperfect anti-COVID-19 vaccine on the control of COVID-19 in the United States. An analytical expression for the minimum percentage of unvaccinated susceptible individuals needed to be vaccinated in order to achieve vaccine-induced community herd immunity is derived. The epidemiological consequence of the herd immunity threshold is that the disease can be effectively controlled or eliminated if the minimum herd immunity threshold is achieved in the community. Simulations of the model, using baseline parameter values obtained from fitting the model with COVID-19 mortality data for the U.S., show that, for an anti-COVID- 19 vaccine with an assumed protective efficacy of 80%, at least 82% of the susceptible US population need to be vaccinated to achieve the herd immunity threshold. The prospect of COVID-19 elimination in the US, using the hypothetical vaccine, is greatly enhanced if the vaccination program is combined with other interventions, such as face mask usage and/or social distancing. Such combination of strategies significantly reduces the level of the vaccine-induced herd immunity threshold needed to eliminate the pandemic in the US. For instance, the herd immunity threshold decreases to 72% if half of the US population regularly wears face masks in public (the threshold decreases to 46% if everyone wears a face mask).The Simons Foundation and the National Science Foundation.http://www.keaipublishing.com/idmam2020Mathematics and Applied Mathematic

Toward achieving a vaccine-derived herd immunity threshold for COVID-19 in the U.S.

A novel coronavirus emerged in December of 2019 (COVID-19), causing a pandemic that inflicted unprecedented public health and economic burden in all nooks and corners of the world. Although the control of COVID-19 largely focused on the use of basic public health measures (primarily based on using non-pharmaceutical interventions, such as quarantine, isolation, social-distancing, face mask usage, and community lockdowns) initially, three safe and highly-effective vaccines (by AstraZeneca Inc., Moderna Inc., and Pfizer Inc.), were approved for use in humans in December 2020. We present a new mathematical model for assessing the population-level impact of these vaccines on curtailing the burden of COVID-19. The model stratifies the total population into two subgroups, based on whether or not they habitually wear face mask in public. The resulting multigroup model, which takes the form of a deterministic system of nonlinear differential equations, is fitted and parameterized using COVID-19 cumulative mortality data for the third wave of the COVID-19 pandemic in the United States. Conditions for the asymptotic stability of the associated disease-free equilibrium, as well as an expression for the vaccine-derived herd immunity threshold, are rigorously derived. Numerical simulations of the model show that the size of the initial proportion of individuals in the mask-wearing group, together with positive change in behavior from the non-mask wearing group (as well as those in the mask-wearing group, who do not abandon their mask-wearing habit) play a crucial role in effectively curtailing the COVID-19 pandemic in the United States. This study further shows that the prospect of achieving vaccine-derived herd immunity (required for COVID-19 elimination) in the U.S., using the Pfizer or Moderna vaccine, is quite promising. In particular, our study shows that herd immunity can be achieved in the U.S. if at least 60% of the population are fully vaccinated. Furthermore, the prospect of eliminating the pandemic in the U.S. in the year 2021 is significantly enhanced if the vaccination program is complemented with non-pharmaceutical interventions at moderate increased levels of compliance (in relation to their baseline compliance). The study further suggests that, while the waning of natural and vaccine-derived immunity against COVID-19 induces only a marginal increase in the burden and projected time-to-elimination of the pandemic, adding the impacts of therapeutic benefits of the vaccines into the model resulted in a dramatic reduction in the burden and time-to-elimination of the pandemic.The Simons Foundation, the Cameroon Ministry of Higher Education and the National Science Foundation.https://www.frontiersin.org/journals/public-health#am2022Mathematics and Applied Mathematic

Mathematical modeling and analysis of COVID-19 pandemic in Nigeria

A mathematical model is designed and used to study the transmission dynamics and control of COVID-19 in Nigeria. The model, which was rigorously analysed and parametrized using COVID-19 data published by the Nigeria Centre for Disease Control (NCDC), was used to assess the community-wide impact of various control and mitigation strategies in some jurisdictions within Nigeria (notably the states of Kano and Lagos, and the Federal Capital Territory, Abuja). Numerical simulations of the model showed that COVID-19 can be effectively controlled in Nigeria using moderate levels of social-distancing strategy in the jurisdictions and in the entire nation. Although the use of face masks in public can significantly reduce COVID-19 in Nigeria, its use, as a sole intervention strategy, may fail to lead to a substantial reduction in disease burden. Such substantial reduction is feasible in the jurisdictions (and the entire Nigerian nation) if the public face mask use strategy is complemented with a social-distancing strategy. The community lockdown measures implemented in Nigeria on March 30, 2020 need to be maintained for at least three to four months to lead to the effective containment of COVID-19 outbreaks in the country. Relaxing, or fully lifting, the lockdown measures sooner, in an e ort to re-open the economy or the country, may trigger a deadly second wave of the pandemic.The Simons Foundation and the National Science Foundation.http://www.aimspress.com/journal/MBEam2021Mathematics and Applied Mathematic

Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel Coronavirus

Please read abstract in the article.The Simons Foundation and the National Science Foundation.http://www.elsevier.com/locate/mbshj2021Mathematics and Applied Mathematic