My current research falls broadly within three primary categories: the influences of climate on health, precipitation and hydrologic variability and change, and societal impacts of climate change. These projects employ a wide variety of statistical methods and comparisons across a variety of weather and climate data, including station-based observations, gridded meteorological and hydrological products like reanalyses, and state-of-the-art climate model output. These weather and climate data sets are frequently combined with societal data like disease counts and country-wide crime data. Please read on for more details.
Linking Climate Variability and Vector-Borne Disease
Climate impacts vector-borne disease through a number of pathways. For instance, temperature and precipitation play critical roles in malaria prevalence by affecting the life cycle and behavior of its carrier, the Anopheles mosquito, as well as the malaria parasite itself. Currently, I am working to identify spatial and temporal patterns of West Nile virus in the United States to link West Nile virus outbreaks to predictable climate factors and subsequently increase the lead-time of early warning systems. In earlier work, I led an interdisciplinary team which compared weekly district-level malaria rates with observed sea surface temperatures and atmospheric reanalysis data to link two modes of interannual climate variability to precipitation and malaria rates in Mozambique.
Maximizing the Effective Use of Climate Data in Health Research
Research at the intersection of climate and health is a rapidly growing field. To build community capacity in this area and take advantage of my unique cross-affiliation between NOAA and the CDC, I explore the best sources of climate data for public health and epidemiology use cases. This includes 1) exploring the data needs of the health community, 2) identifying ideal data processing practices, and 3) comparing the influences of the different data sources and processing on disease modeling efforts.
Examining the Use of Environmental Data in West Nile Virus Modeling through Forecasting Challenges
Forecasting challenges are a valuable tool to analyze the abilities of state-of-the-science epidemiological models. Building off of earlier efforts, I manage the open 2023 CDC West Nile Virus Forecasting Project for the upcoming West Nile virus season in the United States. Models and their resultant forecasts can be submitted by academic and non-academic teams alike. These forecasts, along with the forecasts from the completed 2022 challenge, will be validated and compared against one another to examine the impacts of incorporating various types of environmental data into disease models, along with other factors. Similar efforts have been published for the 2020 edition of the challenge.
Characterizing Changes in Global Precipitation and Hydrologic Variability and Extremes
Anthropogenic climate change is driving widespread shifts in precipitation worldwide. While alterations in extreme precipitation drive enhanced dangers to human well-being and extensive hazards to infrastructure through flooding and drought, changes in precipitation variability are less studied but also impactful. For example, recent research found that precipitation variability is a constraint on pastoral vegetation and can drive adverse birth outcomes in Amazonia. Examining precipitation records from long-standing station data, we explore global trends in observed precipitation extremes, frequency, and variability. We also look to provide the hydrologic context beneath observed changes in extreme precipitation by examining changes in the soil moisture levels underlying the most intense events.
Patterns in Human Mobility Responses to Weather and Climate
Understanding how day-to-day human mobility is influenced by weather and climate has important applications for infectious disease modeling, transportation planning, and climate migration. We combine daily visit data for over one million points of interest around the United States with relevant meteorological variables from reanalyses to empirically determine how human mobility behavior responds to weather fluctuations. We also examine spatial heterogeneity across major metropolitan areas and their varying climates around the country.