In silico characterization of missense mutations in infectious diseases: case studies of tuberculosis and COVID-19
- Authors: Barozi, Victor
- Date: 2023-10-13
- Subjects: Microbial mutation , COVID-19 (Disease) , Drug resistance in microorganisms , Antitubercular agents , Tuberculosis , Molecular dynamics , Single nucleotide polymorphisms
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/431626 , vital:72791 , DOI 10.21504/10962/431626
- Description: One of the greatest challenges facing modern medicine and the global public health today is antimicrobial drug resistance (AMR). This “silent pandemic,” as coined by the world health organization (WHO), is steadily increasing with an estimated 4.95 million mortalities attributed to AMR in 2019, 1.27 million of which were directly linked to AMR. Some of the contributors to AMR include self-prescription, drug overuse, sub-optimal drug prescriptions by health workers, and inaccessibility to drugs, especially in remote areas, which leads to poor adherence. The situation is aggravated by the upsurge of new zoonotic infections like the coronavirus disease 2019, which present unique challenges and take the bulk of resources hence stunting the fight against AMR. Quite alarming still is our current antimicrobial arsenal, which hasn’t had any novel antimicrobial drug discovery/addition, of a new class, since the 1980s. This puts a burden on the existing broad-spectrum antimicrobial drugs which are already struggling against multi-drug resistant strains like multi-drug resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB). Besides the search for new antimicrobial agents, the other avenue for addressing AMR is studying drug resistance mechanisms, especially single nucleotide polymorphisms (SNPs), that change drug target characteristics. With the advancement of computational power and data storage resources, computational approaches can be applied in mutational studies to provide insight into the drug resistance mechanisms with an aim to inform future drug design and development. Therefore, in the first part of this thesis, we employ integrative in silico approaches, including 3D structure modeling, molecular dynamic (MD) simulations, comparative essential dynamics (ED), and protein network analysis approaches i.e., dynamic residue network (DRN) analysis to decipher drug resistance mechanisms in tuberculosis (TB). This involved an investigation of the drug resistance mutations in the catalase-peroxidase (KatG) and pyrazinamidase (MtPncA) enzymes which are responsible for activation of TB first-line drugs; Isoniazid (INH) and Pyrazinamide (PZA), respectively. In the case of KatG, eleven high confidence (HC) KatG mutations associated with a high prevalence of phenotypic INH resistance were identified and their 3D structures modeled before subjecting them to MD simulations. Global analysis showed an unstable KatG structure and active site environment in the mutants compared to the wildtype. Active site dynamics in the mutants compromised cofactor (heme) interactions resulting in less bonds/interactions compared to the wildtype. Given the importance of the heme, reduced interactions affect enzyme function. Trajectory analysis also showed asymmetric protomer behavior both in the wildtype and mutant systems. DRN analysis identified the KatG dimerization domain and C-terminal domain as functionally important and influential in the enzyme function as per betweenness centrality and eigenvector centrality distribution. In the case of the MtPncA enzyme, our main focus was on understanding the MtPncA binding ability of Nicotinamide (an analogue of PZA) in comparison to PZA, especially in the presence of 82 resistance conferring MtPncA mutations. Like in KatG, the mutant structures were modeled and subjected to MD simulations and analysis. Interestingly, more MtPncA mutants favored NAM interactions compared to PZA i.e., 34 MtPncA mutants steadily coordinated NAM compared to 21 in the case of PZA. Trajectory and ligand interaction analysis showed how increased active site lid loop dynamics affect the NAM binding, especially in the systems with the active site mutations i.e., H51Y, W68R, C72R, L82R, K96N, L159N, and L159R. This led to fewer protein-ligand interactions and eventually ligand ejection. Network analysis further identified the protein core, metal binding site (MBS), and substrate binding site as the most important regions of the enzyme. Furthermore, the degree of centrality analysis showed how specific MtPncA mutations i.e., C14H, F17D, and T412P, interrupt intra-protein communication from the MtPncA core to the MBS, affecting enzyme activity. The analysis of KatG and MtPncA enzyme mutations not only identified the effects of mutations on enzyme behaviour and communication, but also established a framework of computational approaches that can be used for mutational studies in any protein. Besides AMR, the continued encroachment of wildlife habitats due to population growth has exposed humans to wildlife pathogens leading to zoonotic diseases, a recent example being coronavirus disease 2019 (COVID-19). In the second part of the thesis, the established computational approaches in Part 1, were employed to investigate the changes in inter-protein interactions and communication patterns between the severe acute respiratory coronavirus 2 (SARS-CoV-2) with the human host receptor protein (ACE2: angiotensin-converting enzyme 2) consequent to mutations in the SARS-CoV-2 receptor binding domain (RBD). Here, the focus was on RBD mutations of the Omicron sub-lineages. We identified four Omicron-sub lineages with RBD mutations i.e., BA.1, BA.2, BA.3 and BA.4. Each sub-lineage mutations were modeled into RBD structure in complex with the hACE2. MD analysis of the RBD-hACE2 complex highlighted how the RBD mutations change the conformational flexibility of both the RBD and hACE2 compared to the wildtype (WT). Furthermore, DRN analysis identified novel allosteric paths composed of residues with high betweenness and eigenvector centralities linking the RBD to the hACE2 in both the wildtype and mutant systems. Interestingly, these paths were modified with the progression of Omicron sub-lineages, highlighting how the virus evolution affects protein interaction. Lastly, the effect of mutations on S RBD and hACE2 interaction was investigated from the hACE2 perspective by focusing on mutations in the hACE2 protein. Here, naturally occurring hACE2 polymorphisms in African populations i.e., S19P, K26R, M82I, K341R, N546D, and D597Q, were identified and their effects on RBD-hACE2 interactions investigated in presence of the Omicron BA.4/5 RBD mutations. The hACE2 polymorphisms subtly affected the complex dynamics; however, RBD-hACE2 interaction analysis showed that hACE2 mutations effect the complex formation and interaction. Here, the K26R mutation favored RBD-hACE2 interactions, whereas S19P resulted in fewer inter-protein interactions than the reference system. The M82I mutation resulted in a higher RBD-hACE2 binding energy compared to the wildtype meaning that the mutation might not favor RBD binding to the hACE2. On the other hand, K341R had the most RBD-hACE2 interactions suggesting that it probably favors RBD binding to the hACE2. N546D and D597Q had diminutive differences to the reference system. Interestingly, the network of high betweenness centrality residues linking the two proteins, as seen in the previous paragraph, were maintained/modified in presence of hACE2 mutations. HACE2 mutations also changed the enzyme network patterns resulting in a concentration of high eigenvector centrality residues around the zinc-binding and active site region, ultimately influencing the enzyme functionality. Altogether, the thesis highlights fundamental structural and network changes consequent to mutations both in TB and COVID-19 proteins of interest using in silico approaches. These approaches not only provide a new context on impact of mutations in TB and COVID target proteins, but also presents a framework that be implemented in other protein mutation studies. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2023
- Full Text:
- Date Issued: 2023-10-13
- Authors: Barozi, Victor
- Date: 2023-10-13
- Subjects: Microbial mutation , COVID-19 (Disease) , Drug resistance in microorganisms , Antitubercular agents , Tuberculosis , Molecular dynamics , Single nucleotide polymorphisms
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/431626 , vital:72791 , DOI 10.21504/10962/431626
- Description: One of the greatest challenges facing modern medicine and the global public health today is antimicrobial drug resistance (AMR). This “silent pandemic,” as coined by the world health organization (WHO), is steadily increasing with an estimated 4.95 million mortalities attributed to AMR in 2019, 1.27 million of which were directly linked to AMR. Some of the contributors to AMR include self-prescription, drug overuse, sub-optimal drug prescriptions by health workers, and inaccessibility to drugs, especially in remote areas, which leads to poor adherence. The situation is aggravated by the upsurge of new zoonotic infections like the coronavirus disease 2019, which present unique challenges and take the bulk of resources hence stunting the fight against AMR. Quite alarming still is our current antimicrobial arsenal, which hasn’t had any novel antimicrobial drug discovery/addition, of a new class, since the 1980s. This puts a burden on the existing broad-spectrum antimicrobial drugs which are already struggling against multi-drug resistant strains like multi-drug resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB). Besides the search for new antimicrobial agents, the other avenue for addressing AMR is studying drug resistance mechanisms, especially single nucleotide polymorphisms (SNPs), that change drug target characteristics. With the advancement of computational power and data storage resources, computational approaches can be applied in mutational studies to provide insight into the drug resistance mechanisms with an aim to inform future drug design and development. Therefore, in the first part of this thesis, we employ integrative in silico approaches, including 3D structure modeling, molecular dynamic (MD) simulations, comparative essential dynamics (ED), and protein network analysis approaches i.e., dynamic residue network (DRN) analysis to decipher drug resistance mechanisms in tuberculosis (TB). This involved an investigation of the drug resistance mutations in the catalase-peroxidase (KatG) and pyrazinamidase (MtPncA) enzymes which are responsible for activation of TB first-line drugs; Isoniazid (INH) and Pyrazinamide (PZA), respectively. In the case of KatG, eleven high confidence (HC) KatG mutations associated with a high prevalence of phenotypic INH resistance were identified and their 3D structures modeled before subjecting them to MD simulations. Global analysis showed an unstable KatG structure and active site environment in the mutants compared to the wildtype. Active site dynamics in the mutants compromised cofactor (heme) interactions resulting in less bonds/interactions compared to the wildtype. Given the importance of the heme, reduced interactions affect enzyme function. Trajectory analysis also showed asymmetric protomer behavior both in the wildtype and mutant systems. DRN analysis identified the KatG dimerization domain and C-terminal domain as functionally important and influential in the enzyme function as per betweenness centrality and eigenvector centrality distribution. In the case of the MtPncA enzyme, our main focus was on understanding the MtPncA binding ability of Nicotinamide (an analogue of PZA) in comparison to PZA, especially in the presence of 82 resistance conferring MtPncA mutations. Like in KatG, the mutant structures were modeled and subjected to MD simulations and analysis. Interestingly, more MtPncA mutants favored NAM interactions compared to PZA i.e., 34 MtPncA mutants steadily coordinated NAM compared to 21 in the case of PZA. Trajectory and ligand interaction analysis showed how increased active site lid loop dynamics affect the NAM binding, especially in the systems with the active site mutations i.e., H51Y, W68R, C72R, L82R, K96N, L159N, and L159R. This led to fewer protein-ligand interactions and eventually ligand ejection. Network analysis further identified the protein core, metal binding site (MBS), and substrate binding site as the most important regions of the enzyme. Furthermore, the degree of centrality analysis showed how specific MtPncA mutations i.e., C14H, F17D, and T412P, interrupt intra-protein communication from the MtPncA core to the MBS, affecting enzyme activity. The analysis of KatG and MtPncA enzyme mutations not only identified the effects of mutations on enzyme behaviour and communication, but also established a framework of computational approaches that can be used for mutational studies in any protein. Besides AMR, the continued encroachment of wildlife habitats due to population growth has exposed humans to wildlife pathogens leading to zoonotic diseases, a recent example being coronavirus disease 2019 (COVID-19). In the second part of the thesis, the established computational approaches in Part 1, were employed to investigate the changes in inter-protein interactions and communication patterns between the severe acute respiratory coronavirus 2 (SARS-CoV-2) with the human host receptor protein (ACE2: angiotensin-converting enzyme 2) consequent to mutations in the SARS-CoV-2 receptor binding domain (RBD). Here, the focus was on RBD mutations of the Omicron sub-lineages. We identified four Omicron-sub lineages with RBD mutations i.e., BA.1, BA.2, BA.3 and BA.4. Each sub-lineage mutations were modeled into RBD structure in complex with the hACE2. MD analysis of the RBD-hACE2 complex highlighted how the RBD mutations change the conformational flexibility of both the RBD and hACE2 compared to the wildtype (WT). Furthermore, DRN analysis identified novel allosteric paths composed of residues with high betweenness and eigenvector centralities linking the RBD to the hACE2 in both the wildtype and mutant systems. Interestingly, these paths were modified with the progression of Omicron sub-lineages, highlighting how the virus evolution affects protein interaction. Lastly, the effect of mutations on S RBD and hACE2 interaction was investigated from the hACE2 perspective by focusing on mutations in the hACE2 protein. Here, naturally occurring hACE2 polymorphisms in African populations i.e., S19P, K26R, M82I, K341R, N546D, and D597Q, were identified and their effects on RBD-hACE2 interactions investigated in presence of the Omicron BA.4/5 RBD mutations. The hACE2 polymorphisms subtly affected the complex dynamics; however, RBD-hACE2 interaction analysis showed that hACE2 mutations effect the complex formation and interaction. Here, the K26R mutation favored RBD-hACE2 interactions, whereas S19P resulted in fewer inter-protein interactions than the reference system. The M82I mutation resulted in a higher RBD-hACE2 binding energy compared to the wildtype meaning that the mutation might not favor RBD binding to the hACE2. On the other hand, K341R had the most RBD-hACE2 interactions suggesting that it probably favors RBD binding to the hACE2. N546D and D597Q had diminutive differences to the reference system. Interestingly, the network of high betweenness centrality residues linking the two proteins, as seen in the previous paragraph, were maintained/modified in presence of hACE2 mutations. HACE2 mutations also changed the enzyme network patterns resulting in a concentration of high eigenvector centrality residues around the zinc-binding and active site region, ultimately influencing the enzyme functionality. Altogether, the thesis highlights fundamental structural and network changes consequent to mutations both in TB and COVID-19 proteins of interest using in silico approaches. These approaches not only provide a new context on impact of mutations in TB and COVID target proteins, but also presents a framework that be implemented in other protein mutation studies. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2023
- Full Text:
- Date Issued: 2023-10-13
Identification of selective novel hits against Mycobacterium tuberculosis KasA potential allosteric sites using bioinformatics approaches
- Authors: Hare, Fadzayi Faith
- Date: 2022-10-14
- Subjects: Tuberculosis , Docking , Molecules Models , Virtual screening , Multidrug-resistant tuberculosis , Fatty acids Synthesis , Drugs Design
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/362842 , vital:65367
- Description: Tuberculosis (TB) is a global health threat that has led to approximately 1.5 million deaths annually. According to the World Health Organization (WHO), TB is among the top ten deadly diseases and is the leading cause of death due to a single infectious agent. The main challenge in the effective treatment and control of TB is the ongoing emergence of resistant strains of Mycobacterium tuberculosis (Mtb) which lead to multi-drug resistant (MDR) and extensive-drug resistant (XDR) TB. Hence, the identification and characterization of novel drug targets and drugs that modulate the activity of the pathogen are an urgent priority. The current situation even necessitates the reengineering or repurposing of drugs in order to achieve effective control. The β-ketoacyl-acyl carrier protein synthase I (KasA) of Mycobacterium tuberculosis is an essential enzyme in the mycobacterial fatty acid synthesis (FAS-II) pathway and is believed to be a promising target for drug discovery in TB. It is one of the five main proteins of the FAS-II pathway and catalyzes a key condensation reaction in the synthesis of meromycolate chains, the precursors of mycolic acids involved in cell wall formation. Although this protein has been extensively studied, little research has been devoted to the allosteric inhibition of potential drug compounds. The main aim of this research was to identify the allosteric sites on the protein that could be involved in the inhibition of substrate binding activities and novel drug compounds that bind to these sites by use of in-silico approaches. The bioinformatics approaches used in this study were divided into four main objectives namely identification of KasA homolog sequences, sequence analysis and protein characterization, allosteric site search and lastly virtual screening of DrugBank compounds via molecular docking. Fifteen homolog sequences were identified from the BLASTP analysis and were derived from bacteria, fungi and mammals. In order to discover important residues and regions within the KasA proteins, sequence alignment, motif analysis and phylogenetic studies were performed using Mtb KasA as a reference. Sequence alignment revealed conserved residues in all KasA proteins that have functional importance such as the catalytic triad residues (Cys171, His311 and His345). Motif analysis identified 18 highly conserved motifs within the KasA proteins with structural and functional roles. In addition, motifs unique to the Mtb KasA protein were also identified and explored for inhibitor drug design purposes. Phylogenetic analysis of the homolog sequences showed a distinct clustering of prokaryotes and eukaryotes. A distinctive clustering was also observed for species belonging to the same genus. Since the mechanism of action of most drugs involves the active site, allosteric site search was conducted on Mtb KasA and the human homolog protein using a combination of pocket detection algorithms with the aim of identifying sites that could be utilized in allosteric modulator drug discovery. This was followed by the virtual screening of 2089 FDA approved DrugBank compounds against the entire protein surfaces of Mtb KasA and Hsmt KasA, performed via molecular docking using AutoDock Vina. Screening of the compounds was based on the binding energies, with more focus on identifying ligands that bound exclusively to the acyl-binding tunnel of Mtb KasA. This reduced the data set to 27 promising drug compounds with a relatively high binding affinity for Mtb KasA, however, further experiments need to be performed to validate this result. Among these compounds were DB08889, DB06755, DB09270, DB11226, DB00392, DB12278, DB08936, DB00781, DB13720 and DB00392, which displayed relatively low binding energies for Mtb KasA when compared to the human homolog protein. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
- Date Issued: 2022-10-14
- Authors: Hare, Fadzayi Faith
- Date: 2022-10-14
- Subjects: Tuberculosis , Docking , Molecules Models , Virtual screening , Multidrug-resistant tuberculosis , Fatty acids Synthesis , Drugs Design
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/362842 , vital:65367
- Description: Tuberculosis (TB) is a global health threat that has led to approximately 1.5 million deaths annually. According to the World Health Organization (WHO), TB is among the top ten deadly diseases and is the leading cause of death due to a single infectious agent. The main challenge in the effective treatment and control of TB is the ongoing emergence of resistant strains of Mycobacterium tuberculosis (Mtb) which lead to multi-drug resistant (MDR) and extensive-drug resistant (XDR) TB. Hence, the identification and characterization of novel drug targets and drugs that modulate the activity of the pathogen are an urgent priority. The current situation even necessitates the reengineering or repurposing of drugs in order to achieve effective control. The β-ketoacyl-acyl carrier protein synthase I (KasA) of Mycobacterium tuberculosis is an essential enzyme in the mycobacterial fatty acid synthesis (FAS-II) pathway and is believed to be a promising target for drug discovery in TB. It is one of the five main proteins of the FAS-II pathway and catalyzes a key condensation reaction in the synthesis of meromycolate chains, the precursors of mycolic acids involved in cell wall formation. Although this protein has been extensively studied, little research has been devoted to the allosteric inhibition of potential drug compounds. The main aim of this research was to identify the allosteric sites on the protein that could be involved in the inhibition of substrate binding activities and novel drug compounds that bind to these sites by use of in-silico approaches. The bioinformatics approaches used in this study were divided into four main objectives namely identification of KasA homolog sequences, sequence analysis and protein characterization, allosteric site search and lastly virtual screening of DrugBank compounds via molecular docking. Fifteen homolog sequences were identified from the BLASTP analysis and were derived from bacteria, fungi and mammals. In order to discover important residues and regions within the KasA proteins, sequence alignment, motif analysis and phylogenetic studies were performed using Mtb KasA as a reference. Sequence alignment revealed conserved residues in all KasA proteins that have functional importance such as the catalytic triad residues (Cys171, His311 and His345). Motif analysis identified 18 highly conserved motifs within the KasA proteins with structural and functional roles. In addition, motifs unique to the Mtb KasA protein were also identified and explored for inhibitor drug design purposes. Phylogenetic analysis of the homolog sequences showed a distinct clustering of prokaryotes and eukaryotes. A distinctive clustering was also observed for species belonging to the same genus. Since the mechanism of action of most drugs involves the active site, allosteric site search was conducted on Mtb KasA and the human homolog protein using a combination of pocket detection algorithms with the aim of identifying sites that could be utilized in allosteric modulator drug discovery. This was followed by the virtual screening of 2089 FDA approved DrugBank compounds against the entire protein surfaces of Mtb KasA and Hsmt KasA, performed via molecular docking using AutoDock Vina. Screening of the compounds was based on the binding energies, with more focus on identifying ligands that bound exclusively to the acyl-binding tunnel of Mtb KasA. This reduced the data set to 27 promising drug compounds with a relatively high binding affinity for Mtb KasA, however, further experiments need to be performed to validate this result. Among these compounds were DB08889, DB06755, DB09270, DB11226, DB00392, DB12278, DB08936, DB00781, DB13720 and DB00392, which displayed relatively low binding energies for Mtb KasA when compared to the human homolog protein. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2022
- Full Text:
- Date Issued: 2022-10-14
Exploring socio-economic factors influencing incidences and outcome of multidrug resistance tuberculosis among patients and facility staffs in Makana Sub-District, Eastern Cape
- Cannon, Lesley-Ann https://orcid.org/0000-0002-7635-277X
- Authors: Cannon, Lesley-Ann https://orcid.org/0000-0002-7635-277X
- Date: 2022-02
- Subjects: Multidrug resistance , Tuberculosis
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/26706 , vital:65958
- Description: Background Drug-resistant Tuberculosis (DR-TB) is one of the main causes of global public health crisis, due to the morbidity and mortality rates associated with the disease. This DR TB is a complex illness having direct and indirect impact on finances, social functioning, and quality of life of infected individuals. Major research advances have been made in the diagnosis and treatment of DR-TB. However, minimal information exists on the socio-economic factors influencing the incidence and outcomes. This study aims to fill the gap by exploring the socio-economic factors from both the health care professional and patient perspective in particular settings to gain insights into developing context-specific strategies against the burden of DR-TB. Methodology The study applied a qualitative method to explore the socio-economic factors influencing MDR-TB through key-in-depth interviews (KIIs) and focus group discussions (FGDs). The study enrolled a total of thirty-two (32) consenting participants. The KIIs was conducted for ten (10) healthcare workers and nine (9) MDR-TB patients. Two focus group discussions were done involving seven (7) MDR TB patients and six (6) MDR-TB patients, respectively. The study targeted healthcare workers working in the MDR-TB field and TB patients with the following: GeneXpert Rifampicin resistance and patient confirmed as MDR TB. Eligible participants were selected using a purposive sampling technique from the hospitals` routine data electronic records (EDR-WEB database) and hardcopy registers (drug-resistant TB register) on MDR-TB patients enrolled in care at the study site. Informed consent was obtained from all study participants after thoroughly explaining the purpose. No personal information of participants was used. All responses from respondents were coded during analysis for autonomy and the respondents were not identifiable in any published or unpublished work following this research. The interviews were transcribed, some translated into English, where necessary, and analysed until saturation was reached. Data was coded and analysed using both thematic and content analysis technique. Results There were 3 main themes identified in the study: social factors, economic factors, and other contributing factors. 7 sub- themes were recorded under social factors and 2 subthemes under economic factors. Two independent factors that were also considered to impact MDR-TB were the attitude of healthcare workers, as well as the current COVID-19 pandemic. Conclusion MDR-TB is a major public health concern in the Makana Sub-district of the Eastern Cape. The findings of this study highlight the impact of socio- economic factors on the incidence, spread, defaulter rate and outcomes of MDR-TB. The social areas highlighted by the study participants as affecting the incidence and outcomes of MDR TB were housing and relocation, decreased immunity, stigma, patients’ attitude and lack of support, alcohol and other substance usage and prison/ incarceration. The economic factors identified by the participants were unemployment and job loss and health related expenses. Other factors are those factors contributing to the increased incidence and possible poor outcomes of MDR TB. Healthcare workers impact and attitude and the effects of the covid-19 pandemic were highlighted as additional factors influencing the incidence and outcomes of MDR TB. The management of MDR-TB requires rigorous efforts that should be directed at addressing the socio-economic factors. Therefore, future quantitative studies and important programmatic strategies should be considered to tackle the socio-economic challenges that contribute to the burden of MDR-TB infection in the Makana community. , Thesis (MPA) -- Faculty of Health Sciences, 2022
- Full Text:
- Date Issued: 2022-02
- Authors: Cannon, Lesley-Ann https://orcid.org/0000-0002-7635-277X
- Date: 2022-02
- Subjects: Multidrug resistance , Tuberculosis
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/26706 , vital:65958
- Description: Background Drug-resistant Tuberculosis (DR-TB) is one of the main causes of global public health crisis, due to the morbidity and mortality rates associated with the disease. This DR TB is a complex illness having direct and indirect impact on finances, social functioning, and quality of life of infected individuals. Major research advances have been made in the diagnosis and treatment of DR-TB. However, minimal information exists on the socio-economic factors influencing the incidence and outcomes. This study aims to fill the gap by exploring the socio-economic factors from both the health care professional and patient perspective in particular settings to gain insights into developing context-specific strategies against the burden of DR-TB. Methodology The study applied a qualitative method to explore the socio-economic factors influencing MDR-TB through key-in-depth interviews (KIIs) and focus group discussions (FGDs). The study enrolled a total of thirty-two (32) consenting participants. The KIIs was conducted for ten (10) healthcare workers and nine (9) MDR-TB patients. Two focus group discussions were done involving seven (7) MDR TB patients and six (6) MDR-TB patients, respectively. The study targeted healthcare workers working in the MDR-TB field and TB patients with the following: GeneXpert Rifampicin resistance and patient confirmed as MDR TB. Eligible participants were selected using a purposive sampling technique from the hospitals` routine data electronic records (EDR-WEB database) and hardcopy registers (drug-resistant TB register) on MDR-TB patients enrolled in care at the study site. Informed consent was obtained from all study participants after thoroughly explaining the purpose. No personal information of participants was used. All responses from respondents were coded during analysis for autonomy and the respondents were not identifiable in any published or unpublished work following this research. The interviews were transcribed, some translated into English, where necessary, and analysed until saturation was reached. Data was coded and analysed using both thematic and content analysis technique. Results There were 3 main themes identified in the study: social factors, economic factors, and other contributing factors. 7 sub- themes were recorded under social factors and 2 subthemes under economic factors. Two independent factors that were also considered to impact MDR-TB were the attitude of healthcare workers, as well as the current COVID-19 pandemic. Conclusion MDR-TB is a major public health concern in the Makana Sub-district of the Eastern Cape. The findings of this study highlight the impact of socio- economic factors on the incidence, spread, defaulter rate and outcomes of MDR-TB. The social areas highlighted by the study participants as affecting the incidence and outcomes of MDR TB were housing and relocation, decreased immunity, stigma, patients’ attitude and lack of support, alcohol and other substance usage and prison/ incarceration. The economic factors identified by the participants were unemployment and job loss and health related expenses. Other factors are those factors contributing to the increased incidence and possible poor outcomes of MDR TB. Healthcare workers impact and attitude and the effects of the covid-19 pandemic were highlighted as additional factors influencing the incidence and outcomes of MDR TB. The management of MDR-TB requires rigorous efforts that should be directed at addressing the socio-economic factors. Therefore, future quantitative studies and important programmatic strategies should be considered to tackle the socio-economic challenges that contribute to the burden of MDR-TB infection in the Makana community. , Thesis (MPA) -- Faculty of Health Sciences, 2022
- Full Text:
- Date Issued: 2022-02
Tuberculosis knowledge, attitudes and health-seeking behaviour among tuberculosis patients in Nelson Mandela Bay Municipality, sub district C, South Africa
- Authors: Onyango, Peggy
- Date: 2019
- Subjects: Tuberculosis
- Language: English
- Type: Thesis , Masters , MPH
- Identifier: http://hdl.handle.net/10353/16780 , vital:40773
- Description: The aim of this study was to examine the knowledge and attitude of Tuberculosis (TB) patients regarding TB disease, causes, treatment adherence and health seeking behaviour in Nelson Mandela Bay, sub district C, South Africa. A cross-sectional study was done in three community health centres in Nelson Mandela Bay Municipality sub district C, South Africa. It involved 327 respondents aged eighteen years and above who were on TB treatment for more than one month who were conveniently selected from the three clinics. 54.1% of the patients were males and 45.9% of the patients were females. A structured questionnaire was used to collect data. Frequency counts and percentages were used to analyse the data. Multivariate logistic regression analysis was used to examine the influence of demographic variables on the knowledge, attitude and health seeking behaviour towards TB. None of the demographic variables was statistically significant to determine the TB patients’ knowledge and attitude of TB disease, causes, treatment and adherence. Only housing was statistically significant (p<0.05) as a variable determining the knowledge of TB causes, treatment and adherence. Compared with the reference group (informal housing scheme), the knowledge of TB patients with formal housing scheme were 0.556 (95% CI: 0.316-0.977) higher to determine the correct knowledge. Spearman correlation was used to determine the statistical significance between knowledge-attitude (K-A), Knowledge-Health seeking behaviour (K-HSB) and attitude-health seeking behaviour (A-HSB). There was statistical significance association among the variables. Results show that TB knowledge was generally good amongst the TB clients. However, there was misconception that TB is caused by cold air, dust and that TB disease can change into HIV. More than half of the respondents felt that TB treatment is difficult, takes a long time, unpleasant and interferes with work /marriage. Health seeking behaviour was fair amongst the participants.
- Full Text:
- Date Issued: 2019
- Authors: Onyango, Peggy
- Date: 2019
- Subjects: Tuberculosis
- Language: English
- Type: Thesis , Masters , MPH
- Identifier: http://hdl.handle.net/10353/16780 , vital:40773
- Description: The aim of this study was to examine the knowledge and attitude of Tuberculosis (TB) patients regarding TB disease, causes, treatment adherence and health seeking behaviour in Nelson Mandela Bay, sub district C, South Africa. A cross-sectional study was done in three community health centres in Nelson Mandela Bay Municipality sub district C, South Africa. It involved 327 respondents aged eighteen years and above who were on TB treatment for more than one month who were conveniently selected from the three clinics. 54.1% of the patients were males and 45.9% of the patients were females. A structured questionnaire was used to collect data. Frequency counts and percentages were used to analyse the data. Multivariate logistic regression analysis was used to examine the influence of demographic variables on the knowledge, attitude and health seeking behaviour towards TB. None of the demographic variables was statistically significant to determine the TB patients’ knowledge and attitude of TB disease, causes, treatment and adherence. Only housing was statistically significant (p<0.05) as a variable determining the knowledge of TB causes, treatment and adherence. Compared with the reference group (informal housing scheme), the knowledge of TB patients with formal housing scheme were 0.556 (95% CI: 0.316-0.977) higher to determine the correct knowledge. Spearman correlation was used to determine the statistical significance between knowledge-attitude (K-A), Knowledge-Health seeking behaviour (K-HSB) and attitude-health seeking behaviour (A-HSB). There was statistical significance association among the variables. Results show that TB knowledge was generally good amongst the TB clients. However, there was misconception that TB is caused by cold air, dust and that TB disease can change into HIV. More than half of the respondents felt that TB treatment is difficult, takes a long time, unpleasant and interferes with work /marriage. Health seeking behaviour was fair amongst the participants.
- Full Text:
- Date Issued: 2019
Investigation of the comparative cost-effectiveness of different strategies for the management of multidrug-resistant tuberculosis
- Authors: Rockcliffe, Nicole
- Date: 2003
- Subjects: Tuberculosis , Multidrug resistance , Tuberculosis -- Treatment
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:3788 , http://hdl.handle.net/10962/d1003266 , Tuberculosis , Multidrug resistance , Tuberculosis -- Treatment
- Description: The tuberculosis epidemic is escalating in South Africa as well as globally. This escalation is exacerbated by the increasing prevalence of multidrug-resistant tuberculosis (MDRTB), which is defined by the World Health Organisation (WHO) as resistance of Mycobacteria to at least isoniazid and rifampicin. Multi-drug resistant tuberculosis is estimated to occur in 1-2% of newly diagnosed tuberculosis (TB) patients and in 4-8% of previously treated patients. MDRTB is both difficult and expensive to treat, costing up to 126 times that of drug-sensitive TB. Resource constrained countries such as South Africa often lack both the money and the infrastructure to treat this disease. The aim of this project was to determine whether the performance of a systematic review with subsequent economic modelling could influence the decision making process for policy makers. Data was gathered and an economic evaluation of MDRTB treatment was performed from the perspective of the South African Department of Health. Three treatment alternatives were identified: a protocol regimen of second line anti-tuberculosis agents, as recommended in the South African guidelines for MDRTB, an appropriate regimen designed for each patient according to the results of culture and drug susceptibility tests, and non-drug management. A decision-analysis model using DATA 3.0 by Treeage® was developed to estimate the costs of each alternative. Outcomes were measured in terms of cost alone as well as the ‘number of cases cured’ and the number of ‘years of life saved’ for patients dying, being cured or failing treatment. Drug, hospital and laboratory costs incurred using each alternative were included in the analysis. A sensitivity analysis was performed on all variables in order to identify threshold values that would change the outcome of the evaluation. Results of the decision analysis indicate that the individualised regimen was both the cheaper and more cost-effective regimen of the two active treatment options, and was estimated to cost R50 661 per case cured and R2 070 per year of life saved. The protocol regimen was estimated to cost R73 609 per case cured and R2 741 per year of life saved. The outcome of the decision analysis was sensitive to changes in some of the variables used to model the disease, particularly the daily cost of drugs, the length of time spent in hospital and the length of treatment received by those patients dying or failing treatment. This modelling exercise highlighted significant deficiencies in the quality of evidence on MDRTB management available to policy makers. Pragmatic choices based on operational and other logistic concerns may need to be reviewed when further information becomes available. A case can be made for the establishment of a national database of costing and efficacy information to guide future policy revisions of the South African MDRTB treatment programme, which is resource intensive and of only moderate efficacy. However, due to the widely disparate range of studies on which this evaluation was based, the outcome of the study may not be credible. In this case, the use of a systematic review with subsequent economic modelling could not validly influence policy-makers to change the decision that they made on the basis of drug availability.
- Full Text:
- Date Issued: 2003
- Authors: Rockcliffe, Nicole
- Date: 2003
- Subjects: Tuberculosis , Multidrug resistance , Tuberculosis -- Treatment
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:3788 , http://hdl.handle.net/10962/d1003266 , Tuberculosis , Multidrug resistance , Tuberculosis -- Treatment
- Description: The tuberculosis epidemic is escalating in South Africa as well as globally. This escalation is exacerbated by the increasing prevalence of multidrug-resistant tuberculosis (MDRTB), which is defined by the World Health Organisation (WHO) as resistance of Mycobacteria to at least isoniazid and rifampicin. Multi-drug resistant tuberculosis is estimated to occur in 1-2% of newly diagnosed tuberculosis (TB) patients and in 4-8% of previously treated patients. MDRTB is both difficult and expensive to treat, costing up to 126 times that of drug-sensitive TB. Resource constrained countries such as South Africa often lack both the money and the infrastructure to treat this disease. The aim of this project was to determine whether the performance of a systematic review with subsequent economic modelling could influence the decision making process for policy makers. Data was gathered and an economic evaluation of MDRTB treatment was performed from the perspective of the South African Department of Health. Three treatment alternatives were identified: a protocol regimen of second line anti-tuberculosis agents, as recommended in the South African guidelines for MDRTB, an appropriate regimen designed for each patient according to the results of culture and drug susceptibility tests, and non-drug management. A decision-analysis model using DATA 3.0 by Treeage® was developed to estimate the costs of each alternative. Outcomes were measured in terms of cost alone as well as the ‘number of cases cured’ and the number of ‘years of life saved’ for patients dying, being cured or failing treatment. Drug, hospital and laboratory costs incurred using each alternative were included in the analysis. A sensitivity analysis was performed on all variables in order to identify threshold values that would change the outcome of the evaluation. Results of the decision analysis indicate that the individualised regimen was both the cheaper and more cost-effective regimen of the two active treatment options, and was estimated to cost R50 661 per case cured and R2 070 per year of life saved. The protocol regimen was estimated to cost R73 609 per case cured and R2 741 per year of life saved. The outcome of the decision analysis was sensitive to changes in some of the variables used to model the disease, particularly the daily cost of drugs, the length of time spent in hospital and the length of treatment received by those patients dying or failing treatment. This modelling exercise highlighted significant deficiencies in the quality of evidence on MDRTB management available to policy makers. Pragmatic choices based on operational and other logistic concerns may need to be reviewed when further information becomes available. A case can be made for the establishment of a national database of costing and efficacy information to guide future policy revisions of the South African MDRTB treatment programme, which is resource intensive and of only moderate efficacy. However, due to the widely disparate range of studies on which this evaluation was based, the outcome of the study may not be credible. In this case, the use of a systematic review with subsequent economic modelling could not validly influence policy-makers to change the decision that they made on the basis of drug availability.
- Full Text:
- Date Issued: 2003
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