bioRxiv Science⌕ Search

bioRxiv · 10.1101/2022.05.30.494059

A Meta-analysis of Longevity Estimates of Mosquito Vectors of Disease

Abstract

Mosquitoes are responsible for more human deaths than any other animal, yet we still know relatively little about their ecology. Mosquito lifespan is a key determinant of the force of transmission for the diseases they vector, but the field experiments and dissection methods used to determine this quantity produce estimates with high uncertainty. In this paper, we use Bayesian hierarchical models to analyse a previously published database of 232 mark-release-recapture (MRR) experiments and two databases of different types of mosquito dissection experiments. One, compiled by us, consisted of 131 detailed estimates of the number of egg-laying (gonotrophic) cycles, the other, a recently published dataset of 1490 studies of parity (whether a mosquito has laid eggs or not) in anopheline malaria vectors. We analysed all studies with the same methodology and used Bayesian hierarchical statistics to obtain estimate at the species and genus level. For the major African malaria vector Anopheles gambiae s.l., we estimate lifespans ranging from 4.4 days (from MRR analysis) to 10.3 days (from parity analysis). For the predominantly East-African vector An. funestus s.l., our lifespan estimates range from 4.2 days (MRR) to 7.1 days (dichotomous parity analysis). We estimate lifespans ranging from 4.7 days (physiological age analysis) to 6.2 days (MRR) for Aedes aegypti, and a lifespan of 11.6 days for Ae. Albopictus (only present in MRR data) - the predominant vectors of key arboviruses. Additionally, we estimate that female mosquitoes outlive males by 1.2 days on average (mean estimate; 25%-75% CI: 0.3-1.6 days). By fitting a range of survival models to the data, we found relatively little evidence for senescence in the field. Our analyses, supplemented by power analyses, indicate the considerable uncertainty that remains about mosquito lifespan in the wild. We conclude further progress will require larger and longer experiments or the development of novel new methodologies. Author summaryMosquitoes transmit some of the most important diseases afflicting humans, with malaria alone killing between 390,000 and 460,000 people in 2019, chiefly children in low-income countries. The force of transmission of these diseases depends critically on the duration of mosquito lifespans, and some of the most successful disease control interventions, including insecticide-treated bednets, work because they reduce mosquito longevity. In this study, we conduct meta-analyses of two important classes of field experiments used to estimate wild mosquito lifespan: mark-release-recapture studies, where mosquitoes are marked with dye then released with the number of marked mosquitoes caught monitored over time; and experiments involving dissection of wild-caught females, whose reproductive anatomy is used as a biological clock to determine physiological age. In all analyses, we estimate that most mosquito species live less than 10 days on average, which suggests that relatively few mosquitoes live sufficiently long to transmit disease. The estimates obtained across the two field experiment types were largely discordant and indicated conflicting sources of heterogeneity in lifespan, likely due to the weak power of small-scale experiments. Finally, by fitting a range of survival models to the data, we conclude that, for most species, mosquitoes do not experience strong age-related increases in mortality. We critique the quality of the existing evidence base about mosquito lifespans in the field and suggest how it may be improved. Author contributionsBL, AN and HCJG designed this study. BL was responsible for data curation, developing the statistical methodology and conducting the investigation. All authors were involved in drafting the original manuscript and revising it.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Lambert, B., North, A., Godfray, C.. 2022-05-31. A Meta-analysis of Longevity Estimates of Mosquito Vectors of Disease. https://doi.org/10.1101/2022.05.30.494059

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Beyond Single-Metric Assessments: Uncovering Masked Butterfly Declines via Multi-Scalar Analysis in Central Alberta

1. This study analyzed 21 years (2000-2025) of butterfly count data from Central Alberta, integrated with intensive 5-year (2021-2025) high-resolution intra-seasonal sampling. 2. Long-term macro-scale analysis revealed a significant decline in Shannon Diversity, a change that remained obscured when relying solely on traditional metrics of species richness and evenness. 3. This diversity decline was primarily driven by the severe, long-term collapse of the native Common Ringlet (Coenonympha tullia). 4. Four other dominant species--Cabbage White (Pieris rapae), Clouded Sulphur (Colias eriphyle), European Skipper (Thymelicus lineola), and Common Wood Nymph (Cercyonis pegala)--maintained long-term population stability, though their abundances were significantly constrained by extreme winter minimum temperatures and rapid spring warming. 5. High-resolution intra-seasonal analysis (2021-2025) demonstrated that community indices and species-specific abundances were strongly limited by daily weather, particularly wind velocity and temperature. 6. These findings illustrate that while traditional metrics like richness and evenness are fundamental to community ecology, they provide incomplete insights when applied in isolation; they are most effective when utilized as part of a complementary, multi-scalar framework. 7. This study highlights the necessity of coupling multi-decadal historical datasets with high-frequency, fine-scale sampling to accurately identify the mechanisms of community turnover that simpler metrics may overlook. 8. The results underscore the critical importance of standardized citizen science monitoring in quantifying environmental impacts and establishing conservation priorities for terrestrial insect groups.

ecology↗

From concentration to export: resource contrasts and bee traits shape pollinator spillover to crops

Floral plantings can either concentrate bees or export them to adjacent crops, yet the ecological conditions influencing these outcomes remain unclear. Here, we develop a mathematical model as proof of concept for our previous integrative hypothesis: concentrator and exporter outcomes can arise as alternative, context-dependent outcomes of the same underlying resource-selection process. Using bees as a model and focusing specifically on spillover from floral plantings to crops, we identified resource-specific thresholds separating concentration- and export-favoring conditions. Our model translates differences in relative patch attractiveness into context-dependent concentration and export outcomes and generates resource-specific, testable predictions about the conditions favoring pollinator movement into crops. In our simulations, the concentrator-exporter transition occurred at a lower flowering-intensity contrast than at pollen or nectar contrasts, which suggests that flowering intensity may provide an initial cue for bee movement, whereas nectar and pollen rewards refine or sustain bee responses once crops are perceived as attractive. Spillover thresholds differed among resource contrasts, whereas response steepness varied across bee-trait and community scenarios. Under the model's trait-sensitivity formulation, predicted spillover probability responded more strongly to flowering contrast for specialists than for generalists; colony size amplified this response, whereas bee richness dampened it. Together, these patterns show how flowering and resource contrasts interact with bee traits and community context to shape predicted spillover. Our results confirm that the concentrator and exporter hypotheses can be understood as context-dependent outcomes of the same ecological process rather than as mutually exclusive alternatives. Experimental tests of the predicted thresholds conducted in the field could reveal when and where floral plantings are most likely to promote bee spillover to crops, potentially supporting crop pollination.

ecology↗

A Computational Re-evaluation of Spatial Trials for Zoonotic Tuberculosis Control: Model Misspecification, Diagnostic Miss-classification, and the Illusion of Wildlife Culling Efficacy

1. Wildlife reservoir management frequently relies on the Randomised Badger Culling Trial's (RBCT) trade-off hypothesis, which posits that reductions in cattle herd infections are offset by a perturbation effect driven by disrupted host dispersal. This paper evaluates the computational and epidemiological robustness of this historical trial, which serves as the foundational empirical experiment guiding zoonotic tuberculosis (Mycobacterium bovis) control policies. 2. Using generalized linear mixed models with a generalized Poisson error distribution to explicitly address historical data overdispersion, this study contrasts traditional parametric inference against exact cluster-constrained permutation tests across distinct operational definitions of disease incidence. 3. Non-parametric diagnostics reveal that previously reported treatment and perturbation effects render as statistical artifacts under exact non-parametric permutation. Inside culling zones, parametric significance fails to withstand exact permutation verification due to extreme data leverage in localized cluster blocks. 4. Crucially, when diagnostic misclassification biases are eliminated by analysing total reactor datasets, all apparent culling effects disappear, and information criteria overwhelmingly favour nested null architectures. Unconfirmed reactors likely represent true biological infections missed by low-sensitivity post-mortem macro-necropsy, proving that host removal tracks observation noise rather than genuine zoonotic transmission pathways. 5. Finally, empirical scaling conducted in this study identifies a novel mathematical saturation effect, demonstrating that this sub-linear scaling is an operational artifact of unmodelled herd-level disease recurrence over time. 6. Policy implications. Because current zoonotic tuberculosis intervention frameworks are built upon a structurally misspecified statistical model, they have driven large-scale veterinary policies resulting in substantial, unevidenced ecological and economic interventions while failing to provide genuine public health, animal health, or disease control benefits.

ecology↗