Mosquito Age Grading and Vector-Control Programmes

Advancing age grading techniques for Glossina morsitans morsitans, vectors of African trypanosomiasis, through mid-infrared spectroscopy and machine learning

Tsetse are the insects responsible for transmitting African trypanosomes, which cause sleeping sickness in humans and animal trypanosomiasis in wildlife and livestock. Knowing the age of these flies is important when assessing the effectiveness of vector control programs and modelling disease risk. Current methods to assess fly age are, however, labour-intensive, slow, and often inaccurate as skilled personnel are in short supply. Mid-infrared spectroscopy (MIRS), a fast and cost-effective tool to accurately estimate several biological traits of insects, offers a promising alternative. This is achieved by characterising the biochemical composition of the insect cuticle using infrared light coupled with machine-learning (ML) algorithms to estimate the traits of interest. We tested the performance of MIRS in estimating tsetse sex and age for the first-time using spectra obtained from their cuticle. We used 541 insectary-reared Glossina m. morsitans of two different age groups for males (5 and 7 weeks) and three age groups for females (3 days, 5 weeks, and 7 weeks). Spectra were collected from the head, thorax, and abdomen of each sample. ML models differentiated between male and female flies with a 96% accuracy and predicted the age group with 94% and 87% accuracy for males and females, respectively. The key infrared regions important for discriminating sex and age classification were characteristic of lipid and protein content. Our results support the use of MIRS as a rapid and accurate way to identify tsetse sex and age with minimal pre-processing. Further validation using wild-caught tsetse could pave the way for this technique to be implemented as a routine surveillance tool in vector control programmes.

Estimation of population age structure, daily survival rates, and potential to support dengue virus transmission for Florida Keys Aedes aegypti via transcriptional profiling

Aedes aegypti is an important vector of dengue virus and other arboviruses that affect human health. After being ingested in an infectious bloodmeal, but before being transmitted from mosquito to human, dengue virus must disseminate from the vector midgut into the hemocoel and then the salivary glands. This process, the extrinsic incubation period, typically takes 6-14 days. Since older mosquitoes are responsible for transmission, understanding the age structure of vector populations is important. Transcriptional profiling can facilitate predictions of the age structures of mosquito populations, critical for estimating their potential for pathogen transmission. In this study, we utilized a two-gene transcript model to assess the age structure and daily survival rates of three populations (Key West, Marathon, and Key Largo) of Ae. aegypti from the Florida Keys, United States, where repeated outbreaks of autochthonous dengue transmission have recently occurred. We found that Key Largo had the youngest Ae. aegypti population with the lowest daily survival rate, while Key West had the oldest population and highest survival rate. Across sites, 22.67% of Ae. aegypti females were likely old enough to transmit dengue virus (at least 15 days post emergence). Computed estimates of the daily survival rate (0.8364 using loglinear and 0.8660 using non-linear regression), indicate that dengue vectors in the region experienced relatively low daily mortality. Collectively, our data suggest that Ae. aegypti populations across the Florida Keys harbor large numbers of older individuals, which likely contributes to the high risk of dengue transmission in the area.

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.

An analytically tractable, age-structured model of the impact of vector control on mosquito-transmitted infections

Vector control is a vital tool utilised by malaria control and elimination programmes worldwide, and as such it is important that we can accurately quantify the expected public health impact of these methods. There are very few previous models that consider vector-control-induced changes in the age-structure of the vector population and the resulting impact on transmission. We analytically derive the steady-state solution of a novel age-structured deterministic compartmental model describing the mosquito feeding cycle, with mosquito age represented discretely by parity-the number of cycles (or successful bloodmeals) completed. Our key model output comprises an explicit, analytically tractable solution that can be used to directly quantify key transmission statistics, such as the effective reproductive ratio under control, Rc, and investigate the age-structured impact of vector control. Application of this model reinforces current knowledge that adult-acting interventions, such as indoor residual spraying of insecticides (IRS) or long-lasting insecticidal nets (LLINs), can be highly effective at reducing transmission, due to the dual effects of repelling and killing mosquitoes. We also demonstrate how larval measures can be implemented in addition to adult-acting measures to reduce Rc and mitigate the impact of waning insecticidal efficacy, as well as how mid-ranges of LLIN coverage are likely to experience the largest effect of reduced net integrity on transmission. We conclude that whilst well-maintained adult-acting vector control measures are substantially more effective than larval-based interventions, incorporating larval control in existing LLIN or IRS programmes could substantially reduce transmission and help mitigate any waning effects of adult-acting measures.

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.

Targeted indoor residual insecticide applications shift Aedes aegypti age structure and arbovirus transmission potential

While residual insecticide applications have the potential to decrease pathogen transmission by reducing the density of vectors and shifting the age structure of the adult mosquito population towards younger stages of development, this double entomological impact has not been documented for Aedes aegypti. Aedes collected from households enrolled in a cluster-randomized trial evaluating the epidemiological impact of targeted indoor residual spraying (TIRS) in Merida, Mexico, were dissected and their age structure characterized by the Polovodova combined with Christopher's ovariole growth methods. In total, 813 females were dissected to characterize age structure at 1, 3, 6, and 9 months post-TIRS. Significant differences in the proportion of nulliparous Ae. aegypti females between the treatment groups was found at one-month post-TIRS (control: 35% vs. intervention: 59%), three months (20% vs. 49%) but not at six or nine months post-TIRS. TIRS significantly shiftted Ae. aegypti age structure towards younger stages and led to a non-linear reduction in survivorship compared to the control arm. Reduced survivorship also reduced the number of arbovirus transmitting females (those who survived the extrinsic incubation period). Our findings provide strong evidence of the full entomological impact of TIRS, with important implications for quantifying the epidemiological impact of vector control methods.

Key considerations, target product profiles, and research gaps in the application of infrared spectroscopy and artificial intelligence for malaria surveillance and diagnosis

Studies on the applications of infrared (IR) spectroscopy and machine learning (ML) in public health have increased greatly in recent years. These technologies show enormous potential for measuring key parameters of malaria, a disease that still causes about 250 million cases and 620,000 deaths, annually. Multiple studies have demonstrated that the combination of IR spectroscopy and machine learning (ML) can yield accurate predictions of epidemiologically relevant parameters of malaria in both laboratory and field surveys. Proven applications now include determining the age, species, and blood-feeding histories of mosquito vectors as well as detecting malaria parasite infections in both humans and mosquitoes. As the World Health Organization encourages malaria-endemic countries to improve their surveillance-response strategies, it is crucial to consider whether IR and ML techniques are likely to meet the relevant feasibility and cost-effectiveness requirements-and how best they can be deployed. This paper reviews current applications of IR spectroscopy and ML approaches for investigating malaria indicators in both field surveys and laboratory settings, and identifies key research gaps relevant to these applications. Additionally, the article suggests initial target product profiles (TPPs) that should be considered when developing or testing these technologies for use in low-income settings.

Life expectancy of Anopheles funestus is double that of Anopheles arabiensis in southeast Tanzania based on mark-release-recapture method

Anopheles arabiensis and Anopheles funestus sensu stricto mosquitoes are major East African malaria vectors. Understanding their dispersal and population structure is critical for developing effective malaria control tools. Three mark-release-recapture (MRR) experiments were conducted for 51 nights to assess daily survival and flight range of An. arabiensis and An. funestus mosquitoes in south-eastern, Tanzania. Mosquitoes were marked with a fluorescent dye as they emerged from breeding sites via a self-marking device. Mosquitoes were collected indoors and outdoors using human landing catches (HLC) and Centers for Disease Control and Prevention light traps (CDC-LT). In total, 4210 An. arabiensis and An. funestus were collected with 316 (7.5%) marked and recaptured (MR). Daily mean MR was 6.8, standard deviation (SD ± 7.6) for An. arabiensis and 8.9 (SD ± 8.3) for An. funestus. Probability of daily survival was 0.76 for An. arabiensis and 0.86 for An. funestus translating into average life expectancy of 3.6 days for An. arabiensis and 6.5 days for An. funestus. Dispersal distance was 654 m for An. arabiensis and 510 m for An. funestus. An. funestus life expectancy was substantially longer than that of An. arabiensis. The MRR method described here could be routinely utilized when evaluating the impact of new vector control tools on mosquito survival.

Drivers of longevity of wild-caught Aedes albopictus populations

BACKGROUND

Age structure and longevity constitute fundamental determinants of mosquito populations' capacity to transmit pathogens. However, investigations on mosquito-borne diseases primarily focus on aspects such as abundance or dispersal rather than survival and demography. Here, we examine the post-capture longevity of wild-caught populations of the Asian tiger mosquito Aedes albopictus to investigate the influence of environmental factors and individual frailty on longevity.

METHODS

We captured females of Ae. albopictus from June to November 2021 in a vegetated and an urban area by two methods of capture (BG traps and Human Landing catch). They were kept in semi-controlled conditions in the field, and survival was monitored daily across the 859 individuals captured. We studied the differences in longevity per capture method and location and the influence on longevity of seasonal, climatic and individual factors.

RESULTS

Photoperiod, GDD, minimum and maximum temperature and relative humidity showed an effect on the risk of death of females in the field. Females captured in urban area with Human Landing catch methods had greater longevity than females captured in non-urban areas with BG traps. Individual variance, reflecting individual frailties, had an important effect on the risk of death: the greater the frailty, the shorter the post-capture longevity. Overall, longevity is affected not only by climate and seasonal drivers like temperature and photoperiod but also by the individual frailty of mosquitoes.

CONCLUSION

This work unravels environmental drivers of key demographic parameters such as longevity, as modulated by individual frailty, in disease vectors with strong seasonal dynamics. Further demographic understanding of disease vectors in the wild is needed to adopt new surveillance and control strategies and improve our understanding of disease risk and spread.

Accurate age-grading of field-aged mosquitoes reared under ambient conditions using surface-enhanced Raman spectroscopy and artificial neural networks

Age-grading mosquitoes are significant because only older mosquitoes are competent to transmit pathogens to humans. However, we lack effective tools to do so, especially at the critical point where mosquitoes become a risk to humans. In this study, we demonstrated the capability of using surface-enhanced Raman spectroscopy and artificial neural networks to accurately age-grade field-aged low-generation (F2) female Aedes aegypti mosquitoes held under ambient conditions (error was 1.9 chronological days, in the range 0-22 days). When degree days were used for model calibration, the accuracy was further improved to 20.8 degree days (approximately equal to 1.4 chronological days), which indicates the impact of temperature fluctuation on prediction accuracy. This performance is a significant advancement over binary classification. The great accuracy of this method outperforms traditional age-grading methods and will facilitate effective epidemiological studies, risk assessment, vector intervention monitoring, and evaluation.

Effect of age on wingbeat frequency of Aedes aegypti and potential application for age estimation of mosquitoes

To combat mosquito-borne diseases, a variety of vector control tools have been implemented. Estimating age structure in populations of vector species is important for understanding transmission potential. Age-grading techniques have been used as critical methods for evaluating the efficacy of vector control tools. However, methods like mark-release-recapture and ovarian dissection are laborious and require a high level of training. For decades, scientists have discussed the wide array of acoustic signatures of different mosquito species. These distinguishable wingbeat signatures with spatiotemporal classification allow mosquitoes of the same species to locate one another for mating. In recent years, the use of sensitive acoustic devices like mobile phones have proved effective. Wingbeat signatures can be used to identify mosquito species without the challenge of intensive field collections and morphological and molecular identifications. In this study, laboratory Aedes aegypti (L.) female and male wingbeats were recorded using mobile phones to determine whether sex and age differences with chronological time, and across different physiological stages, can be detected. Our results indicate significantly different wingbeat signatures between male and female Ae. aegypti, and a change of wingbeat frequencies with age and reproduction stage in females.

Deep learning and wing interferential patterns identify Anopheles species and discriminate amongst Gambiae complex species

We present a new and innovative identification method based on deep learning of the wing interferential patterns carried by mosquitoes of the Anopheles genus to classify and assign 20 Anopheles species, including 13 malaria vectors. We provide additional evidence that this approach can identify Anopheles spp. with an accuracy of up to 100% for ten out of 20 species. Although, this accuracy was moderate (> 65%) or weak (50%) for three and seven species. The accuracy of the process to discriminate cryptic or sibling species is also assessed on three species belonging to the Gambiae complex. Strikingly, An. gambiae, An. arabiensis and An. coluzzii, morphologically indistinguishable species belonging to the Gambiae complex, were distinguished with 100%, 100%, and 88% accuracy respectively. Therefore, this tool would help entomological surveys of malaria vectors and vector control implementation. In the future, we anticipate our method can be applied to other arthropod vector-borne diseases.

Validation of a method for the dry preservation and rehydration of Anopheles gambiae sensu lato for parity analysis to assess the impact of vector control measures in the field

BACKGROUND

As the control of malaria remains heavily dependent on vector management interventions, it is important to understand the impact of these on mosquito populations. Age-grading is a valuable tool for this; however, logistical challenges in remote, resource-poor areas make current methodologies difficult to incorporate into clinical trials and routine surveillance. Our aim was to validate a methodology that could be easily implemented in such settings. Using dried mosquito specimens instead of freshly killed ones, we validated the commonly used ovarian tracheation technique for assessing population age structure.

METHODS

Laboratory-reared Anopheles coluzzii mosquitoes with known parity status were dry preserved in silica gel for up to 12 weeks and rehydrated prior to parity assessment. The results were compared to parity results for freshly killed mosquitoes from the same colony. Preserved, field-caught Anopheles gambiae sensu lato (s.l.) from Guinea-Bissau were assessed by three different assessors blinded to each other's scores. An overall index of agreement was calculated using inter-rater reliability of all assessor pairings. The impact of preservation time was investigated using a one-way ANOVA to look for differences in assessor agreement over three time periods.

RESULTS

The parity status was correctly identified for 90% of dry preserved and rehydrated insectary-reared An. coluzzii and for 98% of freshly killed insectary-reared An. coluzzii. The inter-rater reliability was highest (0.94) for freshly killed An. coluzzii. The results for all time points showed excellent strength of agreement between assessors. For field-caught An. gambiae s.l., the overall index of agreement between all three assessors was 0.86 (95% confidence interval 0.78-0.93), indicating almost perfect agreement. There was no significant difference between assessor agreement between time frames.

CONCLUSIONS

Dry preserving and rehydrating Anopheles mosquitoes provides an alternative to using freshly killed mosquitoes to assess the efficacy of a control intervention in remote settings where it is logistically difficult to dissect fresh specimens. This method also provides the flexibility required for parity assessment to be done on larger scales over bigger areas.

The buzz in the field: the interaction between viruses, mosquitoes, and metabolism

Among many medically important pathogens, arboviruses like dengue, Zika and chikungunya cause severe health and economic burdens especially in developing countries. These viruses are primarily vectored by mosquitoes. Having surmounted geographical barriers and threat of control strategies, these vectors continue to conquer many areas of the globe exposing more than half of the world's population to these viruses. Unfortunately, no medical interventions have been capable so far to produce successful vaccines or antivirals against many of these viruses. Thus, vector control remains the fundamental strategy to prevent disease transmission. The long-established understanding regarding the replication of these viruses is that they reshape both human and mosquito host cellular membranes upon infection for their replicative benefit. This leads to or is a result of significant alterations in lipid metabolism. Metabolism involves complex chemical reactions in the body that are essential for general physiological functions and survival of an organism. Finely tuned metabolic homeostases are maintained in healthy organisms. However, a simple stimulus like a viral infection can alter this homeostatic landscape driving considerable phenotypic change. Better comprehension of these mechanisms can serve as innovative control strategies against these vectors and viruses. Here, we review the metabolic basis of fundamental mosquito biology and virus-vector interactions. The cited work provides compelling evidence that targeting metabolism can be a paradigm shift and provide potent tools for vector control as well as tools to answer many unresolved questions and gaps in the field of arbovirology.

In Vitro and In Vivo Coinfection and Superinfection Dynamics of Mayaro and Zika Viruses in Mosquito and Vertebrate Backgrounds

Globalization and climate change have contributed to the simultaneous increase and spread of arboviral diseases. Cocirculation of several arboviruses in the same geographic region provides an impetus to study the impacts of multiple concurrent infections within an individual vector mosquito. Here, we describe coinfection and superinfection with the Mayaro virus (Togaviridae, Alphavirus) and Zika virus (Flaviviridae, Flavivirus) in vertebrate and mosquito cells, as well as Aedes aegypti adult mosquitoes, to understand the interaction dynamics of these pathogens and effects on viral infection, dissemination, and transmission. Aedes aegypti mosquitoes were able to be infected with and transmit both pathogens simultaneously. However, whereas Mayaro virus was largely unaffected by coinfection, it had a negative impact on infection and dissemination rates for Zika virus compared to single infection scenarios. Superinfection of Mayaro virus atop a previous Zika virus infection resulted in increased Mayaro virus infection rates. At the cellular level, we found that mosquito and vertebrate cells were also capable of being simultaneously infected with both pathogens. Similar to our findings in vivo, Mayaro virus negatively affected Zika virus replication in vertebrate cells, displaying complete blocking under certain conditions. Viral interference did not occur in mosquito cells. IMPORTANCE Epidemiological and clinical studies indicate that multiple arboviruses are cocirculating in human populations, leading to some individuals carrying more than one arbovirus at the same time. In turn, mosquitoes can become infected with multiple pathogens simultaneously (coinfection) or sequentially (superinfection). Coinfection and superinfection can have synergistic, neutral, or antagonistic effects on viral infection dynamics and ultimately have impacts on human health. Here we investigate the interaction between Zika virus and Mayaro virus, two emerging mosquito-borne pathogens currently circulating together in Latin America and the Caribbean. We find a major mosquito vector of these viruses-Aedes aegypti-can carry and transmit both arboviruses at the same time. Our findings emphasize the importance of considering co- and superinfection dynamics during vector-pathogen interaction studies, surveillance programs, and risk assessment efforts in epidemic areas.

Rapid identification of mosquito species and age by mass spectrometric analysis

BACKGROUND

A rapid, accurate method to identify and to age-grade mosquito populations would be a major advance in predicting the risk of pathogen transmission and evaluating the public health impact of vector control interventions. Whilst other spectrometric or transcriptomic methods show promise, current approaches rely on challenging morphological techniques or simple binary classifications that cannot identify the subset of the population old enough to be infectious. In this study, the ability of rapid evaporative ionisation mass spectrometry (REIMS) to identify the species and age of mosquitoes reared in the laboratory and derived from the wild was investigated.

RESULTS

The accuracy of REIMS in identifying morphologically identical species of the Anopheles gambiae complex exceeded 97% using principal component/linear discriminant analysis (PC-LDA) and 84% based on random forest analysis. Age separation into 3 different age categories (1 day, 5-6 days, 14-15 days) was achieved with 99% (PC-LDA) and 91% (random forest) accuracy. When tested on wild mosquitoes from the UK, REIMS data could determine the species and age of the specimens with accuracies of 91 and 90% respectively.

CONCLUSIONS

The accuracy of REIMS to resolve the species and age of Anopheles mosquitoes is comparable to that achieved by infrared spectroscopy approaches. The processing time and ease of use represent significant advantages over current, dissection-based methods. Importantly, the accuracy was maintained when using wild mosquitoes reared under differing environmental conditions, and when mosquitoes were stored frozen or desiccated. This high throughput approach thus has potential to conduct rapid, real-time monitoring of vector populations, providing entomological evidence of the impact of alternative interventions.

Close-kin mark-recapture methods to estimate demographic parameters of mosquitoes

Close-kin mark-recapture (CKMR) methods have recently been used to infer demographic parameters such as census population size and survival for fish of interest to fisheries and conservation. These methods have advantages over traditional mark-recapture methods as the mark is genetic, removing the need for physical marking and recapturing that may interfere with parameter estimation. For mosquitoes, the spatial distribution of close-kin pairs has been used to estimate mean dispersal distance, of relevance to vector-borne disease transmission and novel biocontrol strategies. Here, we extend CKMR methods to the life history of mosquitoes and comparable insects. We derive kinship probabilities for mother-offspring, father-offspring, full-sibling and half-sibling pairs, where an individual in each pair may be a larva, pupa or adult. A pseudo-likelihood approach is used to combine the marginal probabilities of all kinship pairs. To test the effectiveness of this approach at estimating mosquito demographic parameters, we develop an individual-based model of mosquito life history incorporating egg, larva, pupa and adult life stages. The simulation labels each individual with a unique identification number, enabling close-kin relationships to be inferred for sampled individuals. Using the dengue vector Aedes aegypti as a case study, we find the CKMR approach provides unbiased estimates of adult census population size, adult and larval mortality rates, and larval life stage duration for logistically feasible sampling schemes. Considering a simulated population of 3,000 adult mosquitoes, estimation of adult parameters is accurate when ca. 40 adult females are sampled biweekly over a three month period. Estimation of larval parameters is accurate when adult sampling is supplemented with ca. 120 larvae sampled biweekly over the same period. The methods are also effective at detecting intervention-induced increases in adult mortality and decreases in population size. As the cost of genome sequencing declines, CKMR holds great promise for characterizing the demography of mosquitoes and comparable insects of epidemiological and agricultural significance.

Back to the Future: Quantifying Wing Wear as a Method to Measure Mosquito Age

Vector biologists have long sought the ability to accurately quantify the age of wild mosquito populations, a metric used to measure vector control efficiency. This has proven difficult due to the difficulties of working in the field and the biological complexities of wild mosquitoes. Ideal age grading techniques must overcome both challenges while also providing epidemiologically relevant age measurements. Given these requirements, the Detinova parity technique, which estimates age from the mosquito ovary and tracheole skein morphology, has been most often used for mosquito age grading despite significant limitations, including being based solely on the physiology of ovarian development. Here, we have developed a modernized version of the original mosquito aging method that evaluated wing wear, expanding it to estimate mosquito chronological age from wing scale loss. We conducted laboratory experiments using adult Anopheles gambiae held in insectary cages or mesocosms, the latter of which also featured ivermectin bloodmeal treatments to change the population age structure. Mosquitoes were age graded by parity assessments and both human- and computational-based wing evaluations. Although the Detinova technique was not able to detect differences in age population structure between treated and control mesocosms, significant differences were apparent using the wing scale technique. Analysis of wing images using averaged left- and right-wing pixel intensity scores predicted mosquito age at high accuracy (overall test accuracy: 83.4%, average training accuracy: 89.7%). This suggests that this technique could be an accurate and practical tool for mosquito age grading though further evaluation in wild mosquito populations is required.

Rapid age-grading and species identification of natural mosquitoes for malaria surveillance

The malaria parasite, which is transmitted by several Anopheles mosquito species, requires more time to reach its human-transmissible stage than the average lifespan of mosquito vectors. Monitoring the species-specific age structure of mosquito populations is critical to evaluating the impact of vector control interventions on malaria risk. We present a rapid, cost-effective surveillance method based on deep learning of mid-infrared spectra of mosquito cuticle that simultaneously identifies the species and age class of three main malaria vectors in natural populations. Using spectra from over 40, 000 ecologically and genetically diverse An. gambiae, An. arabiensis, and An. coluzzii females, we develop a deep transfer learning model that learns and predicts the age of new wild populations in Tanzania and Burkina Faso with minimal sampling effort. Additionally, the model is able to detect the impact of simulated control interventions on mosquito populations, measured as a shift in their age structures. In the future, we anticipate our method can be applied to other arthropod vector-borne diseases.

Knowing the age of malaria-transmitting mosquitoes is important to understand transmission risk as only old mosquitoes can transmit the disease. Here, the authors develop a method based on mid-infrared spectra of mosquito cuticle that can rapidly identify the species and age class of main malaria vectors.

Use of transcriptional age grading technique to determine the chronological age of Sri Lankan Aedes aegypti and Aedes albopictus females

BACKGROUND

Aedes aegypti and Ae. albopictus are important vectors of human diseases such as dengue, chikungunya, and zika. In Sri Lanka, they have been responsible for transmitting dengue virus. One of the most important parameters influencing the likelihood of arbovirus transmission is the age structure of the mosquito population. However, mosquito age is difficult to measure with accuracy. This study aims to construct multivariate calibration models using the transcriptional abundance of three age-responsive genes: Ae15848 (calcium-binding protein), Ae8505 (structural component of cuticle), and Ae4274 (fizzy cell cycle/cell division cycle 20).

METHODS

The transcriptional age-grading technique was applied to determine the chronological age of Ae. aegypti and Ae. albopictus female mosquito populations from Sri Lanka using the age-responsive genes Ae15848, Ae8505, and Ae4274. Furthermore, Ae. aegypti samples obtained from colonies reared at two temperatures (23 and 27 °C) were used to investigate the influence of temperature on this age-grading technique. Expression levels of these three genes were quantified using reverse transcription qualitative PCR (qRT-PCR), and results were normalized against the housekeeping gene ribosomal gene S17 (RpS17).

RESULTS

The expression of Ae15848 and Ae8505 decreased with the age of mosquitoes and showed the most significant and consistent change while expression of Ae4274 increased with age. The multivariate calibration models showed > 80% correlation between expression of these age-responsive genes and the age of female mosquitoes at both temperatures. At 27 °C the accuracy of age predictions using the models was 2.19 (± 1.66) days and 2.58 (± 2.06) days for Ae. aegypti and Ae. albopictus females, respectively. The accuracy of the model for Ae. aegypti at 23 °C was 3.42 (± 2.74) days.

CONCLUSIONS

An adult rearing temperature difference of 4 °C (23-27 °C) did not significantly affect the age predictions. The calibration models created during this study could be successfully used to estimate the age of wild Ae. aegypti and Ae. albopictus mosquitoes from Sri Lanka.

Time Flies-Age Grading of Adult Flies for the Estimation of the Post-Mortem Interval

The estimation of the minimum time since death is one of the main applications of forensic entomology. This can be done by calculating the age of the immature stage of necrophagous flies developing on the corpse, which is confined to approximately 2–4 weeks, depending on temperature and species of the first colonizing wave of flies. Adding the age of the adult flies developed on the dead body could extend this time frame up to several weeks when the body is in a building or closed premise. However, the techniques for accurately estimating the age of adult flies are still in their beginning stages or not sufficiently validated. Here we review the current state of the art of analysing the aging of flies by evaluating the ovarian development, the amount of pteridine in the eyes, the degree of wing damage, the modification of their cuticular hydrocarbon patterns, and the increasing number of growth layers in the cuticula. New approaches, including the use of age specific molecular profiles based on the levels of gene and protein expression and the application of near infrared spectroscopy, are introduced, and the forensic relevance of these methods is discussed.

Prediction of malaria transmission drivers in Anopheles mosquitoes using artificial intelligence coupled to MALDI-TOF mass spectrometry

Vector control programmes are a strategic priority in the fight against malaria. However, vector control interventions require rigorous monitoring. Entomological tools for characterizing malaria transmission drivers are limited and are difficult to establish in the field. To predict Anopheles drivers of malaria transmission, such as mosquito age, blood feeding and Plasmodium infection, we evaluated artificial neural networks (ANNs) coupled to matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry (MS) and analysed the impact on the proteome of laboratory-reared Anopheles stephensi mosquitoes. ANNs were sensitive to Anopheles proteome changes and specifically recognized spectral patterns associated with mosquito age (0–10 days, 11–20 days and 21–28 days), blood feeding and P. berghei infection, with best prediction accuracies of 73%, 89% and 78%, respectively. This study illustrates that MALDI-TOF MS coupled to ANNs can be used to predict entomological drivers of malaria transmission, providing potential new tools for vector control. Future studies must assess the field validity of this new approach in wild-caught adult Anopheles. A similar approach could be envisaged for the identification of blood meal source and the detection of insecticide resistance in Anopheles and to other arthropods and pathogens.

Age-structured vectorial capacity reveals timing, not magnitude of within-mosquito dynamics is critical for arbovirus fitness assessment

Background

Transmission dynamics of arboviruses like Zika virus are often evaluated by vector competence (the proportion of infectious vectors given exposure) and the extrinsic incubation period (EIP, the time it takes for a vector to become infectious), but vector age is another critical driver of transmission dynamics. Vectorial capacity (VC) is a measure of transmission potential of a vector-pathogen system, but how these three components, EIP, vector competence and vector age, affect VC in concert still needs study.

Methods

The interaction of vector competence, EIP, and mosquito age at the time of infection acquisition (Age_acquisition) was experimentally measured in an Aedes aegypti-ZIKV model system, as well as the age-dependence of probability of survival and the willingness to bite. An age-structured vectorial capacity framework (VC_age) was then developed using both EIP_Min and EIP_Max, defined as the time to first observed minimum proportion of transmitting mosquitoes and the time to observed maximum proportion of transmitting mosquitoes.

Results

The within-mosquito dynamics of vector competence/EIP were not significant among treatments where mosquitoes were exposed at different ages. However, VC_age revealed: (i) age-dependence in vector-virus interactions is important for transmission success; (ii) lower vector competence but at shorter EIPs was sufficient for transmission perpetuation; and (iii) R₀ may be overestimated by using non-age-structured VC.

Conclusions

The results indicate that ultimately the temporal component of the virus-vector dynamics is most critical, especially when exposure occurred at advanced mosquito age. While our study is limited to a single virus-vector system, and a multitude of other factors affect both vector competence and mosquito mortality, our methods can be extrapolated to these other scenarios. Results indicate that how ‘highly’ or ‘negligibly’ competent vectors are categorized may need adjustment.