Dr. Michael Johansson presented during two sessions at the AMCA 91st Annual Meeting.
Tuesday, March 4th 2025
During the session "Environmental drivers of West Nile virus Symposium" he gave the talk "Forecasting West Nile virus incidence with environmental drivers".
West Nile virus (WNV) is a zoonotic virus and thus intrinsically linked to the environmental conditions that support the vector mosquitoes and birds necessary for its propagation. Population dynamics of the vectors and hosts and the seasonality of WNV disease in humans underscore the link between transmission biology and human epidemiology. However, the role of environment in determining substantial year-to-year variability in yearly WNV incidence is unclear. In 2020 and 2022, the Centers for Disease Control and Prevention coordinated WNV Forecasting Challenges to assess the ability of models to forecast county-level incidence across the United States. The majority of submitted forecasts integrated climate data with some also using data on land use, mosquitoes, birds. Despite including these relevant factors in carefully built models, a simple model based only on historical human WNV data that used no year-specific information performed as well as the best submitted forecast in 2020 and was second only to the ensemble in 2022. Moreover, amongst submitted forecasts we found mixed evidence about the value of environmental data. Evaluation of additional forecast models using standard time series and machine learning methods with environmental covariates similarly indicated limited forecasting skill, even when models were fitted within climate regions. Together, these results indicate that despite clear biological links to the environment, environmental data were not sufficient to improve yearly forecasts across the US with the models assessed here. These findings also highlight potential avenues to improve forecasts, such as using different approaches for high incidence versus low incidence locations and tailoring models more specifically to local dynamics where the combinations of avian and mosquito species and their environmental determinants may be highly varied.
Wednesday, March 5th 2025
During the session "11 Annual AMCA Arthropod Vector Highlights Symposium" presented the "Advances and challenges in vector-borne forecasting and modeling".
Vector-borne diseases present unique challenges due to the complex interactions of pathogens, multiple vectors and hosts, and the environment. We never have all the information on these components in real-time and face challenging decisions with limited resources and diverse mitigation options. In the last decade, infectious disease modeling and forecasting has gone from research aims to real-time public health tools that can help fill in these gaps. Ensemble forecasts have proven effective for short-term situational awareness and collaborative modeling of future scenarios has provided invaluable insight for longer term planning. Nonetheless many challenges remain for vector-borne diseases. Despite integrating information about vector biology and the environment, most forecasts for vector-borne diseases offer little improvement over baseline models informed only by historical disease data. Models have also been used extensively to assess interventions such as the potential impacts of vector control, Wolbachia, and vaccines on dengue. However, validation of these scenario-based models is even more difficult, making it hard to assess their reliability and integrate them into routine use. One key challenge is the limited availability of real-time case data and data on vectors and other hosts. Moreover, while models can represent complex transmission ecology that are critical to the spatiotemporal dynamics of vector-borne diseases, the interactions between varied environments, vectors, and hosts are difficult to measure and easy to overestimate. Improving real-time data availability and assessing the value of detailed vector and non-human host population data could drive advances in model reliability and utility. Models will be most useful if they are validated, generalizable, accessible, scalable, and directly integrated into vector control and public health practice. They will be critical for difficult and important challenges such as optimizing the spatiotemporal application of vector control, assessing the relative effectiveness of intervention strategies, and preparing for an uncertain future.
