Vector biology and insect‑borne disease dynamics: A comprehensive review

Introduction

Vector-borne diseases arise when pathogens are transmitted between hosts by blood-feeding insects (vectors). In a typical biological transmission cycle, an infected human (or animal) carries a pathogen in the blood that is picked up by a feeding insect [47,7] . The pathogen then must survive and often replicate within the vector's body (over an "extrinsic incubation period") before the vector can transmit it to another host during a subsequent bite. This interaction involves three components: the pathogen, the vector (insect) and the vertebrate host, with environmental and social factors influencing each [65,48] . These diseases cause a large global burden of illness and death. For example, malaria alone causes hundreds of millions of cases annually, and dengue virus infects tens of millions [15] . Other important examples include Chagas disease, leishmaniasis, yellow fever and lymphatic filariasis. The distribution of these diseases is determined by the ecology of the vectors (which often thrive in tropical and subtropical climates) as well as by human factors such as urbanisation and travel [25,40] . Climate variables (temperature, rainfall) influence vector breeding and survival, which can expand or contract transmission seasons. Key epidemiological metrics in vector-borne disease include vector competence (the intrinsic ability of a given vector population to become infected by and transmit a pathogen) and vectorial capacity (a broader quantity that includes competence, vector density, biting rate and longevity). Together, these determine the basic reproduction number R₀ (the expected number of secondary cases from one primary case) [72,41] . For instance, the classic RossMacdonald model relates R₀ for malaria to parameters such as the mosquito biting rate, the probability of parasite transmission per bite, the mosquito mortality rate, and the duration of the mosquito's infectious period. In general, higher vector abundance, biting frequency, or survival increases R₀, as does shorter extrinsic incubation (allowing vectors to become infectious sooner) [102,39,16] . This review covers multiple aspects of insect-vector biology and disease dynamics. We begin with a historical overview of major discoveries and scientists in the field. We then survey major insect vectors and associated diseases (see Table 1) and discuss their lifecycles and control challenges. Next, we examine determinants of vector competence genetic, physiological and behavioural factors and how they are measured in the lab and field (Table 2). Following that, we compare surveillance and control tools/technologies ranging from traps and pesticides to genetic strategies (Table 3). We also discuss modelling approaches for disease transmission (compartmental, agent-based, statistical, etc.) and summarize their data needs, assumptions and typical outputs (Table 4). Throughout, we emphasize an analytical perspective, integrating foundational concepts with current advances.

History and Pioneers of Vector Biology

 The field of vector biology has a long and rich history. In 1877 Sir Patrick Manson demonstrated that filarial worms (Wuchereria spp.) could be transmitted by mosquitoes, establishing the concept of insects as carriers of human parasites [8,100] . In the 1880s and 1890s, Alphonse Laveran identified the malaria parasite in human blood, and researchers including Manson and Giovanni Grassi suspected that Anopheles mosquitoes played a role [49] . The definitive proof came in 1897 when Sir Ronald Ross dissected a mosquito (Anopheles) that had fed on a malaria patient and found the parasites in its gut. For this discovery of malaria transmission, Ross was later awarded the Nobel Prize [64,1] .  Similarly, in the 1880s Cuban physician Carlos J. Finlay proposed that Aedes aegypti mosquitoes transmitted yellow fever virus [27] . Although his work was not initially accepted, it was validated in 1900 by the US Yellow Fever Commission led by Walter Reed. Reed and his team confirmed that Aedes mosquitoes could carry and transmit yellow fever, cementing Finlay's hypothesis. These breakthroughs established the model of insect vector-borne cycles for human pathogens [37,99] .  In the first half of the 20th century, many other vectors were identified. Italian and British scientists showed that Triatoma bugs transmit Trypanosoma cruzi (Chagas disease) in the Americas, and that blackflies (Simulium) transmit Onchocerca volvulus (river blindness) in Africa. The discovery of DDT's insecticidal properties in 1939 (by Paul Müller) revolutionized control: by the 1950s WHO was launching a Global Malaria Eradication Program based on DDT spraying and bed nets. Although that campaign achieved local successes (in Europe, North America, and parts of Asia), it ultimately failed to eliminate malaria worldwide due to logistical, ecological and resistance issues [63, 50] .  Insecticide resistance became a major challenge by the 1970s. In response, new strategies emerged: biological larvicides (such as Bacillus thuringiensis israelensis in the 1980s) and integrated vector management approaches. From the late 20th century onward, genetic and microbial control gained interest [82] . The Sterile Insect Technique (SIT) was trialed for tsetse flies and mosquitoes. In the 21st century, releases of genetically engineered mosquitoes (e.g. carrying lethal genes or gene drives) and Wolbachia-infected mosquitoes have shown promise in reducing disease transmission. These modern efforts build on the century of discoveries that laid the foundations of vector biology [81,98] .

Major Insect Vectors and Diseases 1. A variety of insect taxa serve as vectors for human disease. Table 1 compares the major vector groups and the pathogens they transmit, along with their global distribution, salient life-cycle features, and control challenges. Notably, mosquitoes of several genera (Anopheles, Aedes, Culex, Mansonia) are responsible for most human parasitic and viral diseases (malaria, dengue, Zika, filariasis, etc.) [38] . Other insect vectors include tsetse flies (Glossina spp.) for African trypanosomiasis, sandflies (Phlebotomus and Lutzomyia) for leishmaniasis, triatomine bugs (Triatoma spp.) for Chagas disease, blackflies (Simulium) for onchocerciasis, rat fleas (Xenopsylla) for plague and typhus, human fleas (Pulex) for typhus, and body lice (Pediculus humanus) for epidemic typhus and relapsing fever. Biting midges (Culicoides) are vectors of animal viruses like bluetongue (and occasionally Oropouche virus in humans), while horse-flies and deer-flies (Tabanidae) mechanically transmit parasitic worms like Loa loa [73,18] . 2. These vectors occupy diverse habitats. Mosquitoes typically have aquatic larvae (fresh or polluted water), sandflies breed in soil, and tsetse flies produce larvae that pupate on the ground. Many vector species have close associations with human habitats (e.g. Aedes aegypti in urban containers) or with animal hosts (e.g. Culex birds-mammal cycle for West Nile virus) [51,88] . Control is correspondingly diverse: for example, removing breeding sites and bed net use can greatly reduce malaria, but Aedes control often requires eliminating small water containers and indoor spraying. Insecticide resistance, adaptive behaviours (like biting times and places), and animal reservoir hosts often complicate control efforts [101,26] .

Table 1:

The table highlights common features across vectors. For example, mosquito vectors all breed in standing water (with some species tolerating pollution or attaching to plants), and adult female mosquitoes transmit disease [89,74,28,9,17,52,66,83] .

Vector Pathogen(s) / Disease(s) Distribution

Determinants of Vector Competence

Vector competence is the intrinsic ability of an insect population to acquire, support development of, and transmit a pathogen [35] .

After taking an infectious blood meal, a pathogen must infect the midgut of the insect, escape into the body cavity (hemocoel), and finally invade the salivary glands to be transmitted to a new host [62,2] . Each of these steps can be hindered by vector barriers (e.g. midgut infection barrier, salivary gland barrier). The overall competence is quantified by lab metrics such as the infection rate (fraction of exposed vectors that become infected), dissemination rate (fraction whose infection spreads beyond the gut) and transmission rate (fraction with virus in saliva) [54] . It is also influenced by the extrinsic incubation period (EIP): vectors must survive long enough for the pathogen to incubate [42,10] . Many intrinsic and extrinsic factors influence competence. Genetic factors include the vector species or strain and specific genes that affect susceptibility (e.g. receptors or immune pathways). For instance, different Aedes aegypti strains can vary markedly in their ability to transmit dengue virus. Mutations or variations in innate immunity genes (RNA interference, Toll, JAK-STAT pathways) also change viral susceptibility [3,67] .

Physiological factors include the insect's age (older mosquitoes have had more time to complete EIP), nutritional status, presence of endosymbionts, and microbiome composition. For example, mosquitoes infected with Wolbachia bacteria often show reduced dengue virus levels, drastically lowering transmission. Similarly, gut bacteria may inhibit or enhance a virus [20,76] . Environmental factors like temperature are especially important: higher ambient temperatures usually speed up viral replication, shortening the EIP and raising transmission potential [42,96] . Behavioural factors such as host preference (feeding on humans vs. animals), biting frequency (gonotrophic cycle length) and timing of activity affect how often vectors encounter susceptible hosts. For example, highly anthropophilic vectors like Aedes aegypti tend to sustain human epidemics, while zoophilic species do not [55,30,75] .

The following table (Table 2) lists representative determinants of competence, categorised by type, with examples and methods used to assess them. For each determinant, we note its impact on transmission potential [90,19,29,36,56,68,84,97,103] .

Determinant (example)

Surveillance and Control Tools

Effective management of vector-borne diseases depends on both surveillance of vectors/pathogens and control of vector populations. Table 3 compares key tools and technologies. Classical chemical methods include insecticide-treated nets (ITNs/LLINs) and indoor residual spraying (IRS), which are highly effective against indoor-feeding mosquitoes and have dramatically reduced malaria in many regions [44] . Larval control (by source reduction, chemical larvicides or biological agents like Bacillus thuringiensis israelensis (Bti)) targets mosquitoes at the immature stage. Personal protection (repellents, protective clothing) protects individuals. Vaccination (where available, e.g. yellow fever) prevents disease independent of the vector [69,4] . More recent innovations include biocontrol approaches: for example, releasing sterile male mosquitoes (SIT), Wolbachiainfected mosquitoes, or genetically modified mosquitoes (Oxitec's Aedes) to suppress or modify wild populations. These methods can be species-specific and sustainable but face cost, regulatory and public acceptance hurdles [56] . Surveillance tools range from mosquito traps (light traps, BG-sentinel, gravid traps) to ovitraps for container-breeders, which help estimate vector abundance or detect presence of pathogens [21,31] . Geographic Information Systems (GIS) and remote sensing (satellite data) are used to predict habitat suitability and risk areas [43,77,91] . Molecular diagnostics (PCR, ELISA on collected insects) allow early detection of pathogen circulation in vectors. Each tool has trade-offs. Table 3 summarises their scale (local/community vs regional/global), strengths, limitations and cost/feasibility [57] . For example, ITNs are low-cost and community-wide but only protect against night-biting vectors. Larvicides and environmental management are effective but labor-intensive. Genetic strategies promise large impacts but currently have very high research costs and strict regulatory controls. Community engagement and education, while hard to quantify, are critical enablers of all other interventions [11,95] .

Table 3: summarises their scale (local/community vs regional/global), strengths, limitations and cost/feasibility [12,22,34,33,58,60,78,85,92,104] .

Modelling Disease Transmission Dynamics

Mathematical and computational models are essential for understanding and predicting vector-borne disease spread and control. Classic deterministic compartmental models (such as RossMacdonald or SEIR/SEI) divide the host and vector populations into compartments (Susceptible, Exposed, Infectious, etc.) and use differential equations to simulate transmission over time [79] . These models yield quantities like the basic reproduction number R₀, threshold criteria for control, and projected epidemic curves [5,93] . More complex approaches include stochastic simulations, which capture random events and chance fade-out, and agent-based models where individual humans and vectors interact in space and time. Network models focus on specific contact patterns (for example, travel or social networks) [13,70] . Climate-driven models incorporate weather inputs to forecast seasonal risk. Statistical time-series models (ARIMA, machine learning) use past incidence data (with or without climate covariates) to predict short-term trends. Each modelling approach has specific data requirements, core assumptions and typical outputs. In contrast, an agent-based model requires detailed demographic and movement data, assumes explicit individual behaviour, and outputs spatial case maps [23] . Bayesian and data-assimilation models combine multiple data sources and update forecasts with real-time data. Phylogenetic (phylodynamic) models use pathogen genomic data and assume a molecular clock to reconstruct transmission history (outputting estimates of R or origin of an outbreak) [86,45] . Ecological niche models use occurrence data and environmental layers to predict where vectors might exist, assuming species-environment equilibrium. In practice, models are chosen based on the questions and data available (e.g. predicting next month's dengue cases in a city vs. evaluating long-term elimination strategies for malaria) [32,59] .

Table 4: provides an overview. For example, a simple RossMacdonald model requires parameters like mosquito biting rate, human infectious period and vector lifespan, it assumes homogeneous mixing and constant parameters, and outputs an R₀ estimate [24,6,14,46,71,80,87,94,105] Modelling This review has taken a broad, global perspective (not focusing on a single country) and has centered on insect vectors of human diseases. Accordingly, we have implicitly assumed that key principles apply across regions (for example, the ecology of Aedes aegypti in Asia is analogous to that in the Americas). We have not covered non-insect vectors (ticks, mites, etc.) or plant/animal diseases, which are important fields in their own right. Our synthesis is based on the current scientific literature and fundamental concepts rather than new empirical data. Future challenges include managing insecticide resistance, adapting to changing vector ranges under climate warming, and understanding emerging vectors (such as Aedes albopictus establishing in temperate zones). Important research frontiers are developing reliable gene-drive systems for vector control, harnessing symbionts or microbiomes, and integrating human behavioral data (e.g. travel patterns) into transmission models. A One-Health approach recognizing the links between human health, animal reservoirs and the environment will be essential for controlling diseases like zoonotic flaviviruses or filarial worms. Finally, sustained community engagement and investment in surveillance infrastructure are critical, since the most effective control relies on local participation and real-time data. In sum, vector biology remains a dynamic field requiring continuous innovation to keep pace with evolving public health threats.

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