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Multi-level mathematical modeling of malaria: disease and epidemiology
Thesis (MSc)--Stellenbosch University, 2025.
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Stellenbosch : Stellenbosch University
2026
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| _version_ | 1867613949554327552 |
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| access_status_str | Open Access |
| author | Wilson, Julia Alice |
| author2 | Van Niekerk, D. D. |
| author_browse | Van Niekerk, D. D. Wilson, Julia Alice |
| author_facet | Van Niekerk, D. D. Wilson, Julia Alice |
| author_sort | Wilson, Julia Alice |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MSc)--Stellenbosch University, 2025. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/134874 |
| institution | Stellenbosch University (South Africa) |
| last_indexed | 2026-06-10T12:44:16.501Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/134874 Multi-level mathematical modeling of malaria: disease and epidemiology Wilson, Julia Alice Van Niekerk, D. D. Snoep, J. L. Stellenbosch University. Faculty of Science. Dept. of Biochemistry. Malaria -- Epidemiology Mosquitoes as carriers of disease Plasmodium -- Parasites Communicable diseases -- Transmission -- Africa Mathematical models Multilevel models (Statistics) -- Data processing World health Vector control -- Biological control -- Mathematical models UCTD Thesis (MSc)--Stellenbosch University, 2025. Wilson, J. A. 2025. Multi-Level Mathematical Modeling of Malaria: Disease and Epidemiology. Unpublished masters thesis. Stellenbosch: Stellenbosch University [online]. Available: https://scholar.sun.ac.za/items/8920be4b-ae34-41ab-82bd-66f9a3a70c80 ENGLISH ABSTRACT: Malaria, a mosquito-borne infectious disease caused by Plasmodium parasites, continues to cause a substantial global health burden. According to the WHO, approximately 263 million people were affected by malaria in 2023, representing an increase from 241 million cases in 2020. The highest impact of the disease is present in the WHO African Region, accounting for 94% of reported cases. Malaria-related deaths reached an estimated 597 000 in 2023, primarily affecting vulnerable populations, such as young children and pregnant women. Effective malaria control is a multifaceted challenge as it requires interventions that address both the infection within an individual and the transmission between host and vector. While mathematical models are powerful tools for understanding the disease, they often focus on a single biological level (e.g. epidemiology, within-host disease) and therefore do not capture the full dynamics of the disease. This thesis aims to identify potential intervention targets to reduce parasitemia within a host and prevalence at the population level, by performing sensitivity analyses on both single- and multi-level malaria models. Sensitivity analyses identified three population-level and three within-host processes as potential intervention targets. Population-level targets included mosquito mortality, mosquito-to-human transmission, and human recovery rates, while within-host targets comprised the merozoite infection rate and death rates of infected red blood cells and immune cells. These processes were subsequently targeted with intervention strategies using a variety of single- and multi-level models. While the single-level models displayed the effectiveness of each targeted intervention, the multi-level models supported their effectiveness and revealed further insights on interventions at different biological levels. Population-level interventions effectively reduced prevalence but had limited impact on disease severity, whereas enhancing immune cell longevity reduced both severity and transmission. Overall, these multi-level models provide a framework for future analyses of the effects of combined interventions on multiple biological levels in a multifaceted approach to combating malaria. AFRIKAANSE OPSOMMING: Malaria, ’n muskietgedraagde aansteeklike siekte wat deur Plasmodium-parasiete veroor-saak word, is steeds ’n aansienlike wereldwye gesondheidslas. Volgens die WGO is ongeveer 263 miljoen mense in 2023 deur malaria geraak, wat ’n toename van 241 mil-joen gevalle in 2020 verteenwoordig. Die grootste impak van die siekte is teenwoordig in die WGO se Afrika-streek, wat 94% van die aangemelde gevalle verteenwoordig. Malariaverwante sterftes in 2023 na raming 597 000 bereik, wat hoofsaaklik kwesbare bevolkings, soos jong kinders en swanger vroue, raak. Doeltreffende malariabeheer is ’n veelsydige uitdaging, aangesien dit intervensies vereis wat beide die infeksie binne ’n individu en die oordrag tussen gasheer en vektor aans-preek. Terwyl wiskundige modelle kragtige instrumente is om die siekte te verstaan, fokus hulle dikwels op ’n enkele biologiese vlak (bv. epidemiologie, siekte binne die gasheer) en vang dus nie die volle dinamika van die siekte vas nie. Hierdie tesis het ten doel om potensiële intervensieteikens te identifiseer om parasitemie binne ’n gasheer en prevalensie op populasievlak te verminder, deur sensitiwiteitsontledings op beide enkel- en multivlak-malariamodelle uit te voer. Sensitiwiteitsanalises het drie populasievlak- en drie binne gasheerprosesse as potensiele intervensieteikens geidentifiseer. Populasievlak-teikens het muskietsterftes, muskiet-na-mens-oordrag en menslike herstelkoerse ingesluit, terwyl binne-gasheer-teikens die merozoiet infeksiekoers en sterftesyfers van besmette rooibloedselle en immuunselle ingesluit het. Hierdie prosesse is vervolgens geteiken met intervensiestrategiee deur van ’n verskeidenheid enkel- en meervlakkige modelle gebruik te maak. Terwyl die enkelvlakmodelle die doeltreffendheid van elke geteikende intervensie getoon het, het die meervlakkige modelle hul doeltreffendheid ondersteun en verdere insigte oor in-tervensies op verskillende biologiese vlakke onthul. Populasievlak-intervensies het die voorkoms effektief verminder, maar het beperkte impak op die erns van die siekte gehad, terwyl die verbetering van die lewensduur van immuunsel beide die erns en oordrag verminder het. Oor die algemeen bied hierdie multivlakmodelle ’n raamwerk vir toekomstige ontledings van die effekte van gekombineerde intervensies op verskeiebiologiese vlakke in ’n veelsydige benadering tot die bestryding van malaria. Masters 2026-01-13T12:32:02Z 2026-01-13T12:32:02Z 2025-12 Thesis https://scholar.sun.ac.za/handle/10019.1/134874 Stellenbosch University xvi, 141 pages : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Malaria -- Epidemiology Mosquitoes as carriers of disease Plasmodium -- Parasites Communicable diseases -- Transmission -- Africa Mathematical models Multilevel models (Statistics) -- Data processing World health Vector control -- Biological control -- Mathematical models UCTD Wilson, Julia Alice Multi-level mathematical modeling of malaria: disease and epidemiology |
| title | Multi-level mathematical modeling of malaria: disease and epidemiology |
| title_full | Multi-level mathematical modeling of malaria: disease and epidemiology |
| title_fullStr | Multi-level mathematical modeling of malaria: disease and epidemiology |
| title_full_unstemmed | Multi-level mathematical modeling of malaria: disease and epidemiology |
| title_short | Multi-level mathematical modeling of malaria: disease and epidemiology |
| title_sort | multi level mathematical modeling of malaria disease and epidemiology |
| topic | Malaria -- Epidemiology Mosquitoes as carriers of disease Plasmodium -- Parasites Communicable diseases -- Transmission -- Africa Mathematical models Multilevel models (Statistics) -- Data processing World health Vector control -- Biological control -- Mathematical models UCTD |
| url | https://scholar.sun.ac.za/handle/10019.1/134874 |
| work_keys_str_mv | AT wilsonjuliaalice multilevelmathematicalmodelingofmalariadiseaseandepidemiology |