Medicine and Health Sciences Commons^™

Possible Role Of Correlation Coefficients And Network Analysis Of Multiple Intracellular Proteins In Blood Cells Of Patients With Bipolar Disorder In Studying The Mechanism Of Lithium Responsiveness: A Proof-Concept Study, Keming Gao, Marzieh Ayati, Nicholas M. Kaye, Mehmet Koyutürk, Joseph R. Calabrese, Eric Christian, Hillard M. Lazarus, David Kaplan

Computer Science Faculty Publications and Presentations

Background: The mechanism of lithium treatment responsiveness in bipolar disorder (BD) remains unclear. The aim of this study was to explore the utility of correlation coefficients and protein-to-protein interaction (PPI) network analyses of intracellular proteins in monocytes and CD4+ lymphocytes of patients with BD in studying the potential mechanism of lithium treatment responsiveness. Methods: Patients with bipolar I or II disorder who were diagnosed with the MINI for DSM-5 and at any phase of the illness with at least mild symptom severity and received lithium (serum level ≥ 0.6 mEq/L) for 16 weeks were divided into two groups, responders (≥50% …

Modeling The Effect Of Observational Social Learning On Parental Decision-Making For Childhood Vaccination And Diseases Spread Over Household Networks, Tamer Oraby, Andras Balogh

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

In this paper, we introduce a novel model for parental decision-making about vaccinations against a childhood disease that spreads through a contact network. This model considers a bilayer network comprising two overlapping networks, which are either Erdős–Rényi (random) networks or Barabási–Albert networks. The model also employs a Bayesian aggregation rule for observational social learning on a social network. This new model encompasses other decision models, such as voting and DeGroot models, as special cases. Using our model, we demonstrate how certain levels of social learning about vaccination preferences can converge opinions, influencing vaccine uptake and ultimately disease spread. In addition, …

Using Dna Flow-Stretching Assay As A Tool To Validate The Tagging Of Dna-Binding Proteins For Single-Molecule Experiments, Miranda Molina, Lindsey E. Way, Zhongqing Ren, Qin Liao, Bianca Guerra, Brandon Shields, Xindan Wang, Hyeongjun Kim

Physics and Astronomy Faculty Publications and Presentations

Highlights

• KCK tag can alter protein properties both quantitatively and qualitatively

• Electrostatic interactions between the KCK tag and DNA contribute to the artifacts

• Adding a short peptide tag to ParB protein does not lead to its in vivo changes

• Single-molecule DNA flow-stretching assay can detect protein property changes

Motivation

Single-molecule fluorescence microscopy has been extensively used in modern biology to define the molecular action of proteins. Appending short peptide tags is a common strategy to enhance fluorescence labeling. Here, we evaluate the impact of a commonly used tag, the lysine-cysteine-lysine (KCK) tag, on protein behavior in single-molecule DNA flow-stretching assay, …

Explainable Machine Learning Reveals The Relationship Between Hearing Thresholds And Speech-In-Noise Recognition In Listeners With Normal Audiograms, Jithin Raj Balan, Hansapani Rodrigo, Udit Saxena, Srikanta K. Mishra

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Some individuals complain of listening-in-noise difficulty despite having a normal audiogram. In this study, machine learning is applied to examine the extent to which hearing thresholds can predict speech-in-noise recognition among normal-hearing individuals. The specific goals were to (1) compare the performance of one standard (GAM, generalized additive model) and four machine learning models (ANN, artificial neural network; DNN, deep neural network; RF, random forest; XGBoost; eXtreme gradient boosting), and (2) examine the relative contribution of individual audiometric frequencies and demographic variables in predicting speech-in-noise recognition. Archival data included thresholds (0.25–16 kHz) and speech recognition thresholds (SRTs) from listeners with …

Stability Analyses On The Effect Of Vaccination And Contact Tracing In Monkeypox Virus Transmission, Solomon Eshun, Richmond Essieku, James Ladzekpo

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Monkeypox is a significant health concern due to its potential for morbidity and occasional mortality. Vaccination and effective contact tracing play pivotal roles in controlling infectious diseases, including monkeypox. This study aims to contribute to our understanding of monkeypox dynamics by developing a comprehensive mathematical model that incorporates key factors such as vaccination, quarantining, and contact tracing. Through rigorous sensitivity analysis, we explore the impact of varying vaccination coverage and contact tracing on the disease’s dynamics. In particular, we investigate the dynamics of the disease in relation to variable vaccination coverage and contact tracing. Our findings highlight the critical role …

Effect Of Total Population, Population Density And Weighted Population Density On The Spread Of Covid-19 In Malaysia, Hui Shan Wong, Md Zobaer Hasan, Omar Sharif, Azizur Rahman

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Since November 2019, most countries across the globe have suffered from the disastrous consequences of the Covid-19 pandemic which redefined every aspect of human life. Given the inevitable spread and transmission of the virus, it is critical to acknowledge the factors that catalyse transmission of the disease. This research investigates the relation of the external demographic parameters such as total population, population density and weighted population density on the spread of Covid-19 in Malaysia. Pearson correlation and simple linear regression were utilized to identify the relation between the population-related variables and the spread of Covid-19 in Malaysia using data from …

Air Pollution In South Texas: A Short Communication Of Health Risks And Implications, Sai Deepak Pinakana, Esmeralda Mendez, Ismaila Ibrahim, Md. Salahuddin Majumder, Amit U. Raysoni

School of Earth, Environmental, and Marine Sciences Faculty Publications and Presentations

Air pollution is a major public health concern. The region of South Texas in the United States has experienced high levels of air pollution in recent years due to an increase in population, cross-border trade between the U.S.A. and Mexico, and high vehicular activity. This review assesses the relationships between human health and air pollution in South Texas. A thorough scientific search was performed using PubMed, Science Direct, and ProQuest, with most of the literature focusing on the source apportionment of particulate matter that is 2.5 microns or less in width (PM2.5), Carbon Dioxide (CO2), carbon monoxide (CO), Black Carbon …

Hearing Healthcare Professionals’ Views About Over-The-Counter (Otc) Hearing Aids: Analysis Of Retrospective Survey Data, Vinaya Manchaiah, Anu Sharma, Hansapani Rodrigo, Abram Bailey, Karina C. De Sousa, De Wet Swanepoel

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Over-the-counter hearing aids have been available to consumers in the US since 17 October 2022 following a ruling by the Food and Drug Administration. However, their reception by hearing healthcare professionals (HHP) has been mixed, and concerns have been expressed by many HHPs. The aim of this study was to examine the concerns that HHPs have towards over-the-counter (OTC) hearing aids. The study used a retrospective survey design. The survey data of HHPs (n = 730) was obtained from Hearing Tracker. A 22-item structured questionnaire was administered using a Question Scout platform. Descriptive analyses examined reported areas of concern and …

Divergent Directionality Of Immune Cell-Specific Protein Expression Between Bipolar Lithium Responders And Non-Responders Revealed By Enhanced Flow Cytometry, Keming Gao, Nicholas M. Kaye, Marzieh Ayati, Mehmet Koyuturk, Joseph R. Calabrese, Eric Christian, Hillard M. Lazarus, David Kaplan

Computer Science Faculty Publications and Presentations

Background and Objectives: There is no biomarker to predict lithium response. This study used CellPrint™ enhanced flow cytometry to study 28 proteins representing a spectrum of cellular pathways in monocytes and CD4+ lymphocytes before and after lithium treatment in patients with bipolar disorder (BD). Materials and Methods: Symptomatic patients with BD type I or II received lithium (serum level ≥ 0.6 mEq/L) for 16 weeks. Patients were assessed with standard rating scales and divided into two groups, responders (≥50% improvement from baseline) and non-responders. Twenty-eight intracellular proteins in CD4+ lymphocytes and monocytes were analyzed with CellPrint™, an enhanced flow …

Predicting The Outcomes Of Internet-Based Cognitive Behavioral Therapy For Tinnitus: Applications Of Artificial Neural Network And Support Vector Machine, Hansapani Rodrigo, Eldré W. Beukes, Gerhard Andersson, Vinaya Manchaiah

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Purpose:

Internet-based cognitive behavioral therapy (ICBT) has been found to be effective for tinnitus management, although there is limited understanding about who will benefit the most from ICBT. Traditional statistical models have largely failed to identify the nonlinear associations and hence find strong predictors of success with ICBT. This study aimed at examining the use of an artificial neural network (ANN) and support vector machine (SVM) to identify variables associated with treatment success in ICBT for tinnitus.

Method:

The study involved a secondary analysis of data from 228 individuals who had completed ICBT in previous intervention studies. A 13-point reduction …

Comparative Analysis Of All-Terrain Vehicles, Motorcycle And Automobile-Related Trauma In A Rural Border Community Of The Usa, Haissam S. Elzaim, Kristina Vatcheva, Annelyn Torres-Reveron, Gregery Pequeno, Monica Michelle Betancourt-Garcia

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Introduction: There is widespread use of all-terrain vehicles (ATVs) in the USA for both work-related and recreational activities. In this study, we aimed to determine the difference in injury severity, Glasgow Coma scales and length of stay between ATV-related injuries and injuries sustained from motorcycles (MOTOs) and automobiles (AUTOs).

Methods: We retrospectively analysed ATV, MOTO and AUTO injuries from a Level 2 Trauma Center between 01 January 2015 and 31 August 2020. Proportional odds regression analyses, as well as multivariable regression models, were used to analyse the data.

Results: There were significantly more male and paediatric patients that suffered ATV-related …

Statistical Analysis Methods Applied To Early Outpatient Covid-19 Treatment Case Series Data, Eleftherios Gkioulekas, Peter A. Mccullough, Vladimir Zelenko

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

When confronted with a public health emergency, significant innovative treatment protocols can sometimes be discovered by medical doctors at the front lines based on repurposed medications. We propose a statistical framework for analyzing the case series of patients treated with such new protocols, that enables a comparison with our prior knowledge of expected outcomes, in the absence of treatment. The goal of the proposed methodology is not to provide a precise measurement of treatment efficacy, but to establish the existence of treatment efficacy, in order to facilitate the binary decision of whether the treatment protocol should be adopted on an …

A Comparison Of Statistical Methods For Modeling Count Data With An Application To Hospital Length Of Stay, Gustavo Fernandez, Kristina Vatcheva

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Background

Hospital length of stay (LOS) is a key indicator of hospital care management efficiency, cost of care, and hospital planning. Hospital LOS is often used as a measure of a post-medical procedure outcome, as a guide to the benefit of a treatment of interest, or as an important risk factor for adverse events. Therefore, understanding hospital LOS variability is always an important healthcare focus. Hospital LOS data can be treated as count data, with discrete and non-negative values, typically right skewed, and often exhibiting excessive zeros. In this study, we compared the performance of the Poisson, negative binomial (NB), …

Sar Study Of Niclosamide Derivatives In The Human Glioblastoma U-87 Mg Cells, Shizue Mito, Benxu Cheng, Benjamin A. Garcia, Daniela Gonzalez, Xin Yee Ooi, Tess C. Ruiz, Francisco Xavier Elisarraras, Andrew Tsin, Sue Anne Chew, Marco A. Arriaga

Chemistry Faculty Publications and Presentations

Glioblastoma is a lethal malignant brain tumor, and the development of efficient chemotherapeutic agents remains an urgent need. Niclosamide, an anthelmintic drug, which has been used to treat tapeworm infections more than 50 years, has recently attracted renewed attention due to its evident anticancer activities. It has been shown that niclosamide induces cytotoxicity in human glioblastoma U-87 MG cells corresponding with increased protein ubiquitination, ER stress, and autophagy. Furthermore, niclosamide showed down regulation of multiple pro-survival signaling pathways including Wnt/β-catenin, PI3K/AKT, MAPK/ERK, and STAT3, which further caused reduction of U87-MG cell viability. However, the molecular mechanisms of niclosimide and its …

Networks Of Necessity: Simulating Covid-19 Mitigation Strategies For Disabled People And Their Caregivers, Thomas E. Valles, Hannah Shoenhard, Joseph Zinski, Sarah Trick, Mason A. Porter, Michael R. Lindstrom

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Abstract

A major strategy to prevent the spread of COVID-19 is the limiting of in-person contacts. However, limiting contacts is impractical or impossible for the many disabled people who do not live in care facilities but still require caregivers to assist them with activities of daily living. We seek to determine which interventions can best prevent infections of disabled people and their caregivers. To accomplish this, we simulate COVID-19 transmission with a compartmental model that includes susceptible, exposed, asymptomatic, symptomatically ill, hospitalized, and removed/recovered individuals. The networks on which we simulate disease spread incorporate heterogeneity in the risk levels of …

A Socio-Ecological Model To Assess Tuberculosis In Migrant Farmworkers In The Us-Mexico Border Region, Amit U. Raysoni

School of Earth, Environmental, and Marine Sciences Faculty Publications and Presentations

The migrant and seasonal farmworker toiling in the fields and orchards of the United States of America surmounts innumerable problems daily. Some of these problems pertain to the overall health of the farmworker in addition to the various occupational hazards that he or she faces. This research paper focuses on Tuberculosis infection—both latent and active—in the migrant farmworkers in the United States with a special focus on the US-Mexico border. Using the Socio-Ecological Model as a theoretical framework, the TB health issues faced by this group are studied. The various determinants of health at every level of the Socio-Ecological Model …

Using A Stochastic Continuous-Time Markov Chain Model To Examine Alternative Timing And Duration Of The Covid-19 Lockdown In Kuwait: What Can Be Done Now?, Mustafa Al-Zoughool, Tamer Oraby, Harri Vainio, Janvier Gasana, Joseph C. Longenecker, Walid Al Ali, Mohammad Alseaidan, Susie Elsaadany, Michael G. Tyshenko

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Background

Kuwait had its first COVID-19 in late February, and until October 6, 2020 it recorded 108,268 cases and 632 deaths. Despite implementing one of the strictest control measures-including a three-week complete lockdown, there was no sign of a declining epidemic curve. The objective of the current analyses is to determine, hypothetically, the optimal timing and duration of a full lockdown in Kuwait that would result in controlling new infections and lead to a substantial reduction in case hospitalizations.

Methods

The analysis was conducted using a stochastic Continuous-Time Markov Chain (CTMC), eight state model that depicts the disease transmission and …

Studying Spread Patterns Of Covid-19 Based On Spatiotemporal Data, Beiyu Lin, Xiaowei Jia, Zhiqian Chen

Computer Science Faculty Publications and Presentations

The current COVID-19 epidemic have transformed every aspect of our lives, especially our behavior and routines. These changes have been drastically impacting the economy in each region, such as local restaurants and transportation systems. With massive amounts of ambient data being collected everywhere, we now can develop innovative algorithms to have a much greater understanding of epidemic spread patterns of COVID-19 based on spatiotemporal data. The findings will open up the possibility to design adaptive planning or scheduling systems that will help preventing the spread of COVID-19 and other infectious diseases.

In this tutorial, we will review the trending state-of-theart …

Combined Amplification And Sound Therapy For Individuals With Tinnitus And Coexisting Hearing Loss: A Retrospective Cohort Study, Purushothaman Ganesan, Hansapani Rodrigo, Jason Schmiedge, Rob Reiter, Simham Swapna, Vinaya Manchaiah

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

BACKGROUND: The heterogeneity of tinnitus perception and its impact necessitates a tailor-made management approach in everyone. The current study examined the effects of residual inhibition in combined amplification and sound therapy in individuals with tinnitus and coexisting hearing loss.

METHODS: A retrospective analysis was performed on patients with tinnitus and coexisting hearing loss between 2016 and 2019. A total of 72 patients provided with combined amplification and sound therapy were divided into 3 groups based on residual inhibition: (i) complete residual inhibition, (ii) partial residual inhibition, and (iii) negative residual inhibition. Tinnitus severity was measured using the Tinnitus …

Identification And Characterization Of Bisbenzimide Compounds That Inhibit Human Cytomegalovirus Replication, Nicole Falci Finardi, Hyeongjun Kim, Lee Z. Hernandez, Matthew R. G. Russell, Catherine M-K Ho, Vattipally B. Sreenu, Hannah A. Wenham, Andy Merritt, Blair L. Strang

Physics and Astronomy Faculty Publications and Presentations

The shortcomings of current anti-human cytomegalovirus (HCMV) drugs has stimulated a search for anti-HCMV compounds with novel targets. We screened collections of bioactive compounds and identified a range of compounds with the potential to inhibit HCMV replication. Of these compounds, we selected bisbenzimide compound RO-90-7501 for further study. We generated analogues of RO-90-7501 and found that one compound, MRT00210423, had increased anti-HCMV activity compared to RO-90-7501. Using a combination of compound analogues, microscopy and biochemical assays we found RO-90-7501 and MRT00210423 interacted with DNA. In single molecule microscopy experiments we found RO-90-7501, but not MRT00210423, was able to compact DNA, …

Evaluation Of The United States Covid-19 Vaccine Allocation Strategy, Md Rafiul Islam, Tamer Oraby, Audrey Mccombs, Mohammad Mihrab Chowdhury, Mohammad Al-Mamun, Michael G. Tyshenko, Claus Kadelkai

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Background: Anticipating an initial shortage of vaccines for COVID-19, the Centers for Disease Control (CDC) in the United States developed priority vaccine allocations for specific demographic groups in the population. This study evaluates the performance of the CDC vaccine allocation strategy with respect to multiple potentially competing vaccination goals (minimizing mortality, cases, infections, and years of life lost (YLL)), under the same framework as the CDC allocation: four priority vaccination groups and population demographics stratified by age, comorbidities, occupation and living condition (congested or non-congested).

Methods and findings: We developed a compartmental disease model that incorporates key elements of the …

Exploratory Data Mining Techniques (Decision Tree Models) For Examining The Impact Of Internet-Based Cognitive Behavioral Therapy For Tinnitus: Machine Learning Approach, Hansapani Rodrigo, Eldré W. Beukes, Gerhard Andersson, Vinaya Manchaiah

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Background: There is huge variability in the way that individuals with tinnitus respond to interventions. These experiential variations, together with a range of associated etiologies, contribute to tinnitus being a highly heterogeneous condition. Despite this heterogeneity, a “one size fits all” approach is taken when making management recommendations. Although there are various management approaches, not all are equally effective. Psychological approaches such as cognitive behavioral therapy have the most evidence base. Managing tinnitus is challenging due to the significant variations in tinnitus experiences and treatment successes. Tailored interventions based on individual tinnitus profiles may improve outcomes. Predictive models of treatment …

Mitigating The Externality Of Diseases Of Poverty Through Health Aid, Kamal Jnawali, Michael G. Tyshenko, Tamer Oraby

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Externality exists in healthcare when an individual benefits from others being healthy as it reduces the probability of getting sick from illness. Healthy workers are considered to be the more productive labourers leading to a country’s positive economic growth over time. Several research studies have modelled disease transmission and its economic impact on a single country in isolation. We developed a two-country diseaseeconomy model that explores disease transmission and crossborder infection of disease for its impacts. The model includes aspects of a worsening and rapid transmission of disease juxtaposed by positive impacts to the economy from tourism. We found that …

From Reaction Kinetics To Dementia: A Simple Dimer Model Of Alzheimer’S Disease Etiology, Michael R. Lindstrom, Manuel B. Chavez, Elijah A. Gross-Sable, Eric Y. Hayden, David B. Teplow

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Oligomers of the amyloid β-protein (Aβ) have been implicated in the pathogenesis of Alzheimer’s disease (AD) through their toxicity towards neurons. Understanding the process of oligomerization may contribute to the development of therapeutic agents, but this has been difficult due to the complexity of oligomerization and the metastability of the oligomers thus formed. To understand the kinetics of oligomer formation, and how that relates to the progression of AD, we developed models of the oligomerization process. Here, we use experimental data from cell viability assays and proxies for rate constants involved in monomerdimer-trimer kinetics to develop a simple mathematical model …

Social Distancing And Testing As Optimal Strategies Against The Spread Of Covid-19 In The Rio Grande Valley Of Texas, Kristina P. Vatcheva, Josef A. Sifuentes, Tamer Oraby, Jose Campo Maldonado, Timothy Huber, Cristina Villalobos

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

At the beginning of August 2020, the Rio Grande Valley (RGV) of Texas experienced a rapid increase of coronavirus disease 2019 (abbreviated as COVID-19) cases and deaths. This study aims to determine the optimal levels of effective social distancing and testing to slow the virus spread at the outset of the pandemic. We use an age-stratified eight compartment epidemiological model to depict COVID-19 transmission in the community and within households. With a simulated 120-day outbreak period data we obtain a post 180-days period optimal control strategy solution. Our results show that easing social distancing between adults by the end of …

Modeling The Effect Of Lockdown Timing As A Covid‑19 Control Measure In Countries With Differing Social Contacts, Tamer Oraby, Michael G. Tyshenko, Jose Campo Maldonado, Kristina Vatcheva, Susie Elsaadany, Walid Q. Alali, Joseph C. Longenecker, Mustafa Al‑Zoughool

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

The application, timing, and duration of lockdown strategies during a pandemic remain poorly quantified with regards to expected public health outcomes. Previous projection models have reached conflicting conclusions about the effect of complete lockdowns on COVID-19 outcomes. We developed a stochastic continuous-time Markov chain (CTMC) model with eight states including the environment (SEAMHQRD-V), and derived a formula for the basic reproduction number, R0, for that model. Applying the R 0 formula as a function in previously-published social contact matrices from 152 countries, we produced the distribution and four categories of possible R 0 for the 152 countries and chose one …

Heterocycles In The Treatment Of Neglected Tropical Diseases, Kush K. Maheshwari, Debasish Bandyopadhyay

Chemistry Faculty Publications and Presentations

Background: Neglected Tropical Diseases (NTDs) affect a huge population of the world and the majority of the victims belong to the poor community of the developing countries. Until now, the World Health Organization (WHO) has identified 20 tropical diseases as NTDs that must be addressed with high priority. However, many heterocyclic scaffolds have demonstrated potent therapeutic activity against several NTDs.

Objective: There are three major objectives: (1) To discuss the causes, symptoms, and current status of all the 20 NTDs; (2) To explore the available heterocyclic drugs, as well as their mechanisms of action (if known), that are being used …

Co-Phosphorylation Networks Reveal Subtype-Specific Signaling Modules In Breast Cancer, Marzieh Ayati, Mark R. Chance, Mehmet Koyuturk

Computer Science Faculty Publications and Presentations

Motivation Protein phosphorylation is a ubiquitous mechanism of post-ranslational modification that plays a central role in cellular signaling. Phosphorylation is particularly important in the context of cancer, as down-regulation of tumor suppressors and up-regulation of oncogenes by the dysregulation of associated kinase and phosphatase networks are shown to have key roles in tumor growth and progression. Despite recent advances that enable large-scale monitoring of protein phosphorylation, these data are not fully incorporated into such computational tasks as phenotyping and subtyping of cancers.

Results We develop a network-based algorithm, CoPPNet, to enable unsupervised subtyping of cancers using phosphorylation data. For this …

Estimation Of The Healthcare Waste Generation During Covid-19 Pandemic In Bangladesh, Tamal Chowdhury, Hemal Chowdhury, Md Salman Rahman, Nazia Hossain, Ashfaq Ahmed, Sadiq M. Sait

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

COVID-19 pandemic-borne wastes imposed a severe threat to human lives as well as the total environment. Improper handling of these wastes increases the possibility of future transmission. Therefore, immediate actions are required from both local and international authorities to mitigate the amount of waste generation and ensure proper disposal of these wastes, especially for low-income and developing countries where solid waste management is challenging. In this study, an attempt is made to estimate healthcare waste generated during the COVID-19 pandemic in Bangladesh. This study includes infected, ICU, deceased, isolated and quarantined patients as the primary sources of medical waste. Results …

Grappling With Covid-19 By Imposing And Lifting Nonpharmaceutical Interventions In Sri Lanka: A Modeling Perspective, Mahesh Jayaweera, Chamath Dannongoda, Dilum Dilshan, Janith Dissanayake, Hasini Perera, Jagath Manatunge, Buddhika Gunawardana

Physics and Astronomy Faculty Publications and Presentations

The imposition and lifting of non-pharmaceutical interventions (NPIs) to avert the COVID19 pandemic have gained popularity worldwide and will continue to be enforced until herd immunity is achieved. We developed a linear regression model to ascertain the nexus between the time-varying reproduction number averaged over a time window of six days (Rts) and seven NPIs: contact tracing, quarantine efforts, social distancing and health checks, hand hygiene, wearing of facemasks, lockdown and isolation, and health-related supports. Our analysis suggests that the second wave that emerged in Sri Lanka in early October 2020 continued despite numerous NPIs. The model indicates that the …