Role of delay differential equations in modelling low level HIV viral load

Over the past 30 years, HIV has infected over 60 million people, with almost half succumbing to AIDS-related illnesses.While antiretroviral therapy, used to significantly reduce within-host HIV replication, was available within 10 years of the discovery of HIV/AIDS, it is only within the last 10 years that it has become truly effective and universally accessible. However, there are problems with this therapy, not least that it must be administered indefinitely , but is expensive and highly toxic. Furthermore, as therapy reaches more resource-limited regions, continual access can not be guaranteed, resulting in therapy interruptions. This, coupled with a significant cost reduction by systematically interrupting therapy, means a set of models which can account for both treatment events need to be developed, as numerous models exist for therapy introduction, but those for therapy removal are limited. Thus a set of delay differential models are designed, which account for previously overlooked important features of intracellular delay and HIV latency. Incorporation of these features requires additional model components, leading to a rapid increase in complexity. To combat this complexity issue, dimensional analysis is introduced, as a novel method of identifying key components to model function, thus allowing significant reduction in parameter space. Based on these developed models, a number of existing and potential treatment interruption regimes are investigated, with a best practice regime suggested

Modelling the South African tuberculosis epidemic: the effect of HIV, sex differences, and the impact of interventions

The South African tuberculosis (TB) epidemic is driven mainly by HIV, and the TB disease burden is greater in males than females. Additional factors that drive the epidemic include undiagnosed and untreated TB, contributing to transmission; and highly prevalent TB risk factors such as alcohol misuse, smoking, diabetes, and undernutrition, which increase the risk of progression to TB disease. These factors are distributed differently by sex and likely explain the observed sex disparities in TB. The South African TB control programme has implemented multiple interventions, including directly observed therapy strategy (DOTS), antiretroviral therapy (ART), intensified screening activities, the provision of isoniazid preventative therapy (IPT) and the implementation of Xpert MTB/RIF as a first-line diagnostic tool. However, few analyses have quantified the historical impact of HIV and the combined impact of TB interventions on the South African TB epidemic at a national level. In addition, factors that influence sex disparities in the South African TB burden have not been explored thoroughly. Also, it remains uncertain whether, with existing interventions, it would be feasible for South Africa to meet the End TB targets to reduce TB incidence and mortality by 80% and 90% respectively (relative to 2015 levels) by 2030. This thesis aims to address the abovementioned gaps in knowledge and provide insights into understanding the population-level TB dynamics, using a mathematical model. The first objective is to quantify TB incidence and mortality due to HIV and assess the impact of interventions mentioned above on TB incidence and mortality between 1990 and 2019. The second objective is to explore the extent to which the following factors contribute to sex differences in TB: HIV, ART uptake, smoking, alcohol abuse, undernutrition, diabetes, health-seeking patterns, social contact rates and TB treatment discontinuation. The third objective is to project the future impact of increasing screening, improving linkage to TB care and retention, increasing preventative therapy, and reducing ART interruptions. An age- and sex-stratified dynamic tuberculosis transmission model for South Africa was developed. To dynamically model the effect of HIV and ART on TB incidence and mortality, the TB model was integrated into the Thembisa model, a previously developed HIV and demographic model. In addition, age- and sex-specific relative risks were applied to rates of progression to TB disease to capture age and sex differences in tuberculosis incidence. The model also included a diagnostic pathway representing health-seeking patterns and the sensitivity and specificity of the diagnostic algorithm. A Bayesian approach was used to calibrate the model to the numbers of people starting treatment from the electronic tuberculosis register, deaths from the vital register, microbiological tests, and the national tuberculosis prevalence survey. The model estimated rapid increases in TB incidence and mortality in the mid-to-late 1990s, influenced by HIV. Between 1990 and 2019, approximately eight million people developed tuberculosis, and two million died from TB; HIV accounted for at least half and two-thirds of the TB incidence and mortality, respectively. The TB epidemic peaked in the mid-to-late 2000s, followed by declines until 2019. The ART program and TB screening efforts, which were expanded in the mid-2000s, contributed the most to reductions in TB incidence and mortality, while other interventions had minor impacts. Due to the heavier HIV burden in women than men, women experienced greater HIV-associated TB incidence and mortality than men. However, because of the higher ART uptake among women than men, women experienced greater relative reductions in TB incidence and mortality over the period 2005– 2019. Consequently, the higher TB burden among men has been sustained; the estimated male-to-female ratios of TB incidence and mortality in 2019 were 1.7 and 1.65, respectively. Additional factors explaining the excess TB in men are smoking, alcohol abuse and delays in health-seeking patterns. Sex differences in undernutrition, social contact patterns, and treatment discontinuation had minimal effect on TB sex disparities. Projections of the model to 2030, considering the effects of COVID-19-related disruptions to TB care, suggest that increasing TB screening would be the most impactful among all interventions explored. However, the model also suggests that the 2030 End TB milestone is unlikely to be met by scaling up existing interventions. Other interventions that need to be explored include targeted universal TB testing and other diagnostic tests such as digital chest x-rays, urine Lipoarabinomannan, and biomarkers to identify individuals at risk of TB disease. Accelerating progress toward TB incidence and mortality reductions will require developing affordable and efficient rapid diagnostic tools to identify potential and active TB cases. Research and innovation efforts towards finding a vaccine effective in preventing TB disease are also critical. In addition, it is essential to improve the uptake of TB preventative therapy in HIV-positive individuals and perhaps further expand provision to other TB risk group

Analyzing policymaking for tuberculosis control in Nigeria

Today, tuberculosis (TB) is still one of the major threats to humankind, being the first cause of death by an infectious disease worldwide. TB is a communicable chronic disease that every year affects 10 million people and kills almost 2 million people in the world. The main key factors fueling the disease are the progressive urbanization of the population and poverty-related socioeconomic factors.Moreover, the lack of effective tools for TB diagnosis, prevention, and treatment has decisively contributed to the lack of an effectivemodel to predict TB spread. In Nigeria, the rapid urbanization along with unprecedented population growth is causing TB to be endemic.This paper proposes a mathematical model to evaluate TB burden in Nigeria by using data obtained from the local TB control program in the community. This research aims to point out effective strategies that could be used to effectively reduce TB burden and death due to TB in this country at different levels.The study shows that efforts should be oriented to more active case finding rather than increasing the treatment effectiveness only. It also reveals that the persistence of the disease is related to a large number of latently infected individuals and quantifies the lives that could be saved by increasing the notification rate using active case finding strategy.We conclude that undiagnosis is the bottleneck that needs to be overcome in addition to the incorporation, improvement, and/or strengthening of treatmentmanagement and other essential TB control measures in Nigeria.Peer ReviewedPostprint (published version

A mathematical model of the transmission dynamics of tuberculosis with exogenous reinfection in the infection-free state

In the present work, a perturbation of the model presented by Feng, Castillo-Chávez and Capurro (2000) will be carried out, where the dynamics of tuberculosis transmission will be described, where recovery from the disease will be incorporated. The model will include four epidemiological populations: Susceptible (S), Exposed (E), Infected (I) and Infected with treatment (T). This will allow to know how the interaction that exists with the infected can cause the permanence of the individuals with the disease. For which, its qualitative behavior will be analyzed as its evolution in time of the epidemiological populations for the model by the ordinary differential equations (ODE) and its perturbation to the dalay differential equations (DDE). In this way, it will allow us to know how the parameters influence the spread of the disease at the point free of infection and with a computational extension to evaluate an endemic situation.Campus Lima Nort

Early experiences with Isoniazid Preventive Therapy roll-out in an ART programme : a pharmacist's perspective.

Masters Degree. University of KwaZulu-Natal, Durban.Tuberculosis (TB) remains the leading cause of mortality amongst people infected with Human Immunodeficiency Virus (HIV). Additionally, TB recurrence after successful treatment completion occurs more frequently amongst HIV positive people. Isoniazid provided as part of isoniazid preventive therapy (IPT) has been the gold standard of TB preventive therapy provision for the last few decades. IPT has been recommended by the World Health Organisation (WHO) and implemented by national health programmes in countries across the world. Despite global efforts and campaigns to promote IPT, uptake still remains a challenge and, progress in the operational scale- up of IPT is slow. Both international and in-country guidelines have advanced to recommending the use of IPT in HIV infected patients who have previously been treated for TB because these patients remain at risk for recurrent TB especially in TB endemic settings. However, there still remains a paucity in data on the successful programmatic use of IPT secondary to previous cured TB among HIV infected patients and is the focus of the current analysis from a pharmacists’ perspective. Methods: A retrospective secondary analysis was conducted from October 2009 to October 2013, amongst HIV infected patients, previously treated for TB, accessing HIV care at the urban CAPRISA clinical research clinic in Durban, South Africa. The aim of the study was to evaluate the implementation of Isoniazid Preventive Therapy (IPT) within the parent study titled “TB recurrence upon treatment with HAART” (TRuTH). Data was collected on IPT uptake, course completion, drug toxicity, treatment interruption, and the occurrence of incident TB either during treatment or post IPT completion. The multidisciplinary team approach in providing IPT to at risk HIV infected patients, including the specific role of the pharmacist, was also assessed. Results: There were 402 patients enrolled in the parent study. Of these 344 (85.6%) were eligible to receive IPT and of whom 212 (61.6%) initiated IPT. Among those that commenced IPT, 184 (86.8%) completed the six-month course, 24 (11.3%) permanently discontinued IPT and of these, 3.8% discontinued due to side effects. More women (n=130; 61.3%) were initiated on IPT (p=0.001) than men. Overall median adherence to IPT was 97.6% (IQR: 94.2 - 99.4). There were 22 cases of incident TB in this cohort: 13 occurred prior to IPT and nine after IPT (incidence rate ratio 0.67; 95% CI 0.29- 1.58; p=0.362). CONCLUSIONS: Overall, we demonstrated a successful IPT roll-out in a high TB endemic setting with good uptake of IPT, minimal course interruptions or side effects reported. IPT is a safe and tolerable TB prevention intervention within ART programmes and importantly amongst patients on ART with previous TB treatment experience. The pharmacist played an important role in continuum of care in IPT provision within an ART programme. This role included ensuring stable supply chain management, supporting clinic staff in monitoring safe IPT use and provided data on IPT course completion rate

The challenges and opportunities in tuberculosis control, from Texas to Afghanistan

Tuberculosis is one of the most ancient human pathogens. Very early in the history of humans, tuberculosis spread throughout the world and currently infects one third of the world’s population1. Tuberculosis, both as a pathogen and a disease state, is fascinating in its own right. Considering the global public health significance of tuberculosis, which infects one third of the world’s population and kills over 1.5 million people per year, tuberculosis remains a threat and demands further research. For these reasons, my undergraduate research has largely centered on tuberculosis. Chapter 1 gives a broad overview of tuberculosis, applicable but not specific to my research. Each subsequent chapter focuses on a research project, with relevant additional background on tuberculosis. Chapter 2 is based on an internship at the Texas Department of State Health Services analyzing reasons for delayed completion of tuberculosis therapy for patients whose therapy initiated in Texas in 2006. Chapter 3 examines the potential for molecular methods of tuberculosis in low-resource setting, building off of my experience using mutations in the rpoB gene as a surrogate marker of rifampin resistance in Afghanistan. Chapter 4 briefly expands upon further work done in the lab of Dr. Andrew Ellington at the University of Texas at Austin under the supervision of Xi Chen, developing non-enzymatic methods of nucleic acid detection to indicate the presence of tuberculosis and other pathogens.Biological Sciences, School o

Standing genetic variation and the evolution of drug resistance in HIV

Drug resistance remains a major problem for the treatment of HIV. Resistance can occur due to mutations that were present before treatment starts or due to mutations that occur during treatment. The relative importance of these two sources is unknown. We study three different situations in which HIV drug resistance may evolve: starting triple-drug therapy, treatment with a single dose of nevirapine and interruption of treatment. For each of these three cases good data are available from literature, which allows us to estimate the probability that resistance evolves from standing genetic variation. Depending on the treatment we find probabilities of the evolution of drug resistance due to standing genetic variation between 0 and 39%. For patients who start triple-drug combination therapy, we find that drug resistance evolves from standing genetic variation in approximately 6% of the patients. We use a population-dynamic and population-genetic model to understand the observations and to estimate important evolutionary parameters. We find that both, the effective population size of the virus before treatment, and the fitness of the resistant mutant during treatment, are key-parameters that determine the probability that resistance evolves from standing genetic variation. Importantly, clinical data indicate that both of these parameters can be manipulated by the kind of treatment that is used.Comment: 33 pages 6 figure

Progression from latent infection to active disease in dynamic tuberculosis transmission models: a systematic review of the validity of modelling assumptions

Mathematical modelling is commonly used to evaluate infectious disease control policy and is influential in shaping policy and budgets. Mathematical models necessarily make assumptions about disease natural history and, if these assumptions are not valid, the results of these studies can be biased. We did a systematic review of published tuberculosis transmission models to assess the validity of assumptions about progression to active disease after initial infection (PROSPERO ID CRD42016030009). We searched PubMed, Web of Science, Embase, Biosis, and Cochrane Library, and included studies from the earliest available date (Jan 1, 1962) to Aug 31, 2017. We identified 312 studies that met inclusion criteria. Predicted tuberculosis incidence varied widely across studies for each risk factor investigated. For population groups with no individual risk factors, annual incidence varied by several orders of magnitude, and 20-year cumulative incidence ranged from close to 0% to 100%. A substantial proportion of modelled results were inconsistent with empirical evidence: for 10-year cumulative incidence, 40% of modelled results were more than double or less than half the empirical estimates. These results demonstrate substantial disagreement between modelling studies on a central feature of tuberculosis natural history. Greater attention to reproducing known features of epidemiology would strengthen future tuberculosis modelling studies, and readers of modelling studies are recommended to assess how well those studies demonstrate their validity

Political, Economic, and Health Determinants of Tuberculosis Incidence

The epidemiologic transition has shifted major causes of mortality from infectious disease to chronic disease; however, infectious diseases are again re-emerging as a major global concern (Diamond, 1997; Karlen, 1995; McNeil, 1976). This research aimed to identify potential areas of infectious disease influence that are not health-related in order to help governments and policymakers establish new policies, correct current policies, or further address these issues in order to effectively prevent and combat infectious disease. This study employed a retrospective, cross-sectional, non-experimental design via structural equation modeling (SEM) and examined tuberculosis incidence rates at the country-level. Secondary data from open-source, international databases like World Bank\u27s World Development Indicators, World Governance Indicators, and World Health Organization for the year 2014 was utilized. Results revealed that the latent constructs of political stability, health system indicators, and detection policies directly affected tuberculosis incidence rates; they also exhibited an indirect effect due to covariation. Economic stability did not direct affect tuberculosis incidence, but it indirectly influenced incidence through the covariation of political stability, health system indicators, and detection policies. As a country\u27s political stability increased, tuberculosis incidence decreased. As positive health system indicators increased, tuberculosis incidence decreased. Countries with more Xpert detection policies in place experienced an apparent increase in tuberculosis incidence