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McDermott, Daniel (2023) Addressing sources of variation in entomological endpoints in the field evaluation of malaria vector control tools., Thesis (Doctoral), Liverpool School of Tropical Medicine.
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D McDermott thesis LSTM -.pdf - Accepted Version Download (6MB) | Preview |
Abstract
Vector control has been a cornerstone in the global effort to combat malaria transmission for several decades. Its notable successes, particularly since the early 2000s following the widespread distribution of insecticide-treated nets, have substantially reduced mortality and the disease burden in sub-Saharan Africa. However, recent years have witnessed a plateau in progress due to emerging challenges, prominently insecticide resistance in its various forms, which has constrained the effectiveness of existing tools in the pursuit of malaria eradication. Consequently, there has been a resurgence of interest in developing novel intervention products capable of overcoming these challenges.
The introduction of these innovative interventions necessitates rigorous yet cost effective evaluations across various eco epidemiological settings to establish evidence-based efficacy. A significant hurdle in assessing intervention efficacy and effectiveness lies in the limitations of commonly used entomological metrics and their tenuous connection to epidemiological endpoints of malaria transmission. These limitations impede the ability of entomological surveys to provide robust evidence for post-deployment evaluation of interventions in a non-invasive and cost-effective manner.
This thesis addresses concerns about entomological endpoints and vector control efficacy trials. Three key outcomes emerge:
Firstly, spatial considerations assume paramount importance in understanding vector dynamics and guiding control strategies. The examination of a spatial sampling framework's implementation in coastal Kenya highlights the influence of environmental variables, such as wetlands and proximity to rivers, on mosquito abundance. It underscores the importance of adopting a robust spatial sampling approach to pinpoint regions with heightened vector abundance, offering invaluable insights for both targeted control strategies and trial design.
Secondly, this thesis delves into the role of spatial autocorrelation within cluster randomized trials, employing the LLINEUP trial in Uganda as a case study. This exploration underscores the pivotal role played by baseline data and spatial random effects in enhancing model precision and narrowing confidence intervals around intervention effect estimates. This finding assumes particular significance in the context of emerging vector control tools, underscoring the necessity for resilient trial designs.
Finally, the research delves into the utility of mosquito parity data as an entomological endpoint, shedding light on issues related to missing data and seasonal fluctuations. These challenges cast doubt on parity's reliability as an endpoint in trials assessing intervention impact, while also proposing potential avenues for improving the utility of this metric in the future.
In summary, this study offers insights into vector control complexities in mosquito borne diseases. It underscores spatial considerations, baseline data, and endpoint selection's significance in shaping effective intervention evaluations. These findings are crucial for future strategies and research efforts aiming to address data quality concerns in entomological evaluation of vector control efficacy across diverse settings.
| Item Type: | Thesis (Doctoral) | ||||||||||||||||
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| Subjects: | QX Parasitology > QX 20 Research (General) QX Parasitology > Insects. Other Parasites > QX 650 Insect vectors WC Communicable Diseases > Tropical and Parasitic Diseases > WC 750 Malaria WC Communicable Diseases > Tropical and Parasitic Diseases > WC 765 Prevention and control |
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| Faculty: Department: | Biological Sciences > Vector Biology Department | ||||||||||||||||
| Depositing User: | Lynn Roberts-Maloney | ||||||||||||||||
| Date Deposited: | 18 Sep 2024 11:19 | ||||||||||||||||
| Last Modified: | 18 Dec 2024 04:13 | ||||||||||||||||
| URI: | https://archive.lstmed.ac.uk/id/eprint/25367 |
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