When a mean can be meaningless: evaluating mosquito infections with Plasmodium parasites
Abstract Several malaria control measures aim to reduce infection levels in mosquitoes, and evaluation of these measures usually relies on experimental infections of mosquitoes or evaluation in field populations. Both require robust statistical tools to account for multiple variables and non-normal...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
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| Series: | Parasitology |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S0031182025100541/type/journal_article |
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| Summary: | Abstract
Several malaria control measures aim to reduce infection levels in mosquitoes, and evaluation of these measures usually relies on experimental infections of mosquitoes or evaluation in field populations. Both require robust statistical tools to account for multiple variables and non-normal distributions of parasites in the vector host. We argue that a well-chosen generalized linear or mixed model is the most appropriate statistical tool for analysing and interpreting these biological data. We suggest specific methods to overcome datasets where some groups have zero/close to zero prevalence, or many zero counts of parasite numbers (as would be seen with an effective transmission blocking intervention). These methods are more broadly applicable across many parasitic infections with similar patterns of parasite numbers across hosts.
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| ISSN: | 0031-1820 1469-8161 |