Journal of Mosquito Research 2024, Vol.14, No.4, 215-225 http://emtoscipublisher.com/index.php/jmr 217 chikungunya and Zika viruses, for instance, have shown remarkable adaptability, with chikungunya causing millions of infections globally and Zika leading to significant public health concerns due to its association with congenital abnormalities. The identification of these pathogens involves understanding their viral biology, historical transmission routes, and the mechanisms that facilitate their rapid global invasion (Mordecai et al., 2019). 3.2 Epidemiological trends and threat assessment The epidemiological trends of mosquito-borne diseases indicate a rising incidence and geographic spread, driven by factors such as climate change, urbanization, and increased human mobility. For example, the resurgence of dengue in tropical and subtropical regions and the spread of West Nile virus and Japanese encephalitis to new habitats highlight the dynamic nature of these diseases. The threat assessment of these pathogens involves analyzing climatic and environmental variables, such as temperature and precipitation, which are key factors influencing the distribution and transmission of mosquito vectors (Figure 1) (Bartlow et al., 2019). Additionally, the socioeconomic changes and land-use patterns significantly contribute to the changing epidemiology of these diseases （Franklinos et al., 2019). Figure 1 Disease and climate systems for mosquito borne diseases (Adapted from Bartlow et al., 2019) Image caption: Each system must be coupled together with validation from ground truth real-time data. Data from Figure 1 feeds into each of these systems and data fusion issues are addressed throughout the process (Adapted from Bartlow et al., 2019) Bartlow et al. (2019) found that the integration of multiple models—climate, terrestrial, mosquito, and epidemiological—is crucial for accurately predicting the risks associated with mosquito-borne diseases. The climate model influences the mosquito habitat and population dynamics by simulating events such as inundation and vegetation changes. These environmental factors directly impact mosquito breeding sites and, subsequently, the spread of diseases. Additionally, the terrestrial model contributes by modeling vegetation and its effects on mosquito habitats, while the mosquito model focuses on population dynamics. The epidemiological model further incorporates the movement of animal and human populations, which are essential for understanding disease transmission patterns. The interaction and data flow between these models, validated by real-time ground truth data, ensure that the risk predictions are robust and actionable. The holistic approach enables better preparedness and response strategies for managing the public health impacts of mosquito-borne diseases.
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