Omitting age-dependent mosquito mortality in malaria models underestimates the effectiveness of insecticide-treated nets

On the necessity of accounting for age structure in human malaria transmission modeling

Malaria is one of the most common mosquito-borne diseases widespread in tropical and subtropical regions, causing thousands of deaths every year in the world. In a previous paper, we formulated an age-structured model containing three structural variables: (i) the chronological age of human and mosquito populations, (ii) the time since they are infected, and (iii) humans waning immunity (i.e. the progressive loss of protective antibodies after recovery). In the present paper, we expand the analysis of this age-structured model and focus on the derivation of entomological and epidemiological results commonly used in the literature, following the works of Smith and McKenzie. We generalize their results to the age-structured case. In order to quantify the impact of neglecting structuring variables such as chronological age, we assigned values from the literature to our model parameters. While some parameters values are readily accessible from the literature, at least those about the human population, the parameters concerning mosquitoes are less commonly documented and the values of a number of them (e.g. mosquito survival in the presence or in absence of infection) can be discussed extensively. Our analysis, informed by parameter values from the literature, demonstrates that overlooking those structural variables of human and mosquito populations may result in inaccurate epidemiological predictions and suboptimal control strategies. We highlight the epidemiological implications of these findings and emphasize the necessity of considering age structure in future malaria control programs.

Predicting the age of field Anopheles mosquitoes using mass spectrometry and deep learning

Mosquito-borne diseases like malaria are rising globally, and improved mosquito vector surveillance is needed. Survival of Anopheles mosquitoes is key for epidemiological monitoring of malaria transmission and evaluation of vector control strategies targeting mosquito longevity, as the risk of pathogen transmission increases with mosquito age. However, the available tools to estimate field mosquito age are often approximate and time-consuming. Here, we show a rapid method that combines matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry with deep learning for mosquito age prediction. Using 2763 mass spectra from the head, legs, and thorax of 251 field-collected Anopheles arabiensis mosquitoes, we developed deep learning models that achieved a best mean absolute error of 1.74 days. We also demonstrate consistent performance at two ecological sites in Senegal, supported by age-related protein changes. Our approach is promising for malaria control and the field of vector biology, benefiting other disease vectors like Aedes mosquitoes.

Estimating the effects of temperature on transmission of the human malaria parasite, Plasmodium falciparum

Despite concern that climate change could increase the human risk to malaria in certain areas, the temperature dependency of malaria transmission is poorly characterized. Here, we use a mechanistic model fitted to experimental data to describe how Plasmodium falciparum infection of the African malaria vector, Anopheles gambiae, is modulated by temperature, including its influences on parasite establishment, conversion efficiency through parasite developmental stages, parasite development rate, and overall vector competence. We use these data, together with estimates of the survival of infected blood-fed mosquitoes, to explore the theoretical influence of temperature on transmission in four locations in Kenya, considering recent conditions and future climate change. Results provide insights into factors limiting transmission in cooler environments and indicate that increases in malaria transmission due to climate warming in areas like the Kenyan Highlands, might be less than previously predicted.

Mosquito ageing modulates the development, virulence and transmission potential of pathogens

Host age variation is a striking source of heterogeneity that can shape the evolution and transmission dynamic of pathogens. Compared with vertebrate systems, our understanding of the impact of host age on invertebrate-pathogen interactions remains limited. We examined the influence of mosquito age on key life-history traits driving human malaria transmission. Females of Anopheles coluzzii, a major malaria vector, belonging to three age classes (4-, 8- and 12-day-old), were experimentally infected with Plasmodium falciparum field isolates. Our findings revealed reduced competence in 12-day-old mosquitoes, characterized by lower oocyst/sporozoite rates and intensities compared with younger mosquitoes. Despite shorter median longevities in older age classes, infected 12-day-old mosquitoes exhibited improved survival, suggesting that the infection might act as a fountain of youth for older mosquitoes specifically. The timing of sporozoite appearance in the salivary glands remained consistent across mosquito age classes, with an extrinsic incubation period of approximately 13 days. Integrating these results into an epidemiological model revealed a lower vectorial capacity for older mosquitoes compared with younger ones, albeit still substantial owing to extended longevity in the presence of infection. Considering age heterogeneity provides valuable insights for ecological and epidemiological studies, informing targeted control strategies to mitigate pathogen transmission.

Video augmentation of the WHO cone assay to quantify mosquito behavioural responses to insecticide-treated nets

BACKGROUND

Insecticide-treated nets (ITNs) using pyrethroids have been the main vector control tools deployed in malaria endemic countries and are responsible for the dramatic reduction in African malaria cases in the early 2000s. The World Health Organization (WHO) cone test was designed to assess the rapid toxicity effects of pyrethroid exposure on mosquito vectors but has yielded no insights beyond 60-min knockdown and 24-h mortality. As dual-active-ingredient (AI) ITNs become more widespread, bioassays that can provide realistic assessment of single- and dual-treated ITNs (i.e. nets with more than one active ingredient) are urgently needed.

METHODS

We present an augmentation of the cone test that enables accurate quantification of vector behavioural responses (specifically movement, spatial and temporal occupancy) to ITNs using video recording and bespoke software that uses background segmentation methods to detect spatial changes in the movement of mosquitoes within the cone. Four strains of Anopheles gambiae sensu lato (s.l.) were exposed to four ITNs (PermaNet 2.0, PermaNet 3.0, Olyset Net, Interceptor G2) and untreated nets in these modified cone tests. Life history data (post-exposure blood-feeding, blood meal weight, longevity) for individual mosquitoes were recorded.

RESULTS

All mosquitoes responded to the presence of ITNs, spending from 1.48 to 3.67 times more time in the upper region of the cone, depending on the ITN type. Of all ITNs, PermaNet 2.0 provoked the smallest change in behavioural response. Activity in the cone influenced observed post-exposure longevity, and in resistant strains exposed to Interceptor G2, the higher the activity, the greater the risk of dying, as long as the proportion of activity at the net surface was less than 50%. All ITNs inhibited blood-feeding, and smaller blood meals were taken when mosquitoes fed.

CONCLUSIONS

The additional mosquito behaviour data obtained by using this modification to the WHO cone test provides unique insight into the innate responses of different mosquito strains on untreated nets and the entomological mode of action of ITNs, important evidence when evaluating ITN characteristics.