![Interconnecting Global Threats: Climate Change, Biodiversity Loss, and Infectious Diseases](http://daphnia.ecology.uga.edu/drakelab/wp-content/uploads/2024/04/planetary_health_slider4-470x140.png)
Climate change, biodiversity loss, and the spread of infectious diseases are three major challenges for planetary health. We know from major reports such as the…
![Impacts of climate change on mosquito-borne diseases](http://daphnia.ecology.uga.edu/drakelab/wp-content/uploads/2024/03/Dahlin_pub_image-470x140.jpg)
As the planet warms, the behavior and distribution of mosquitoes is expected to change. But it’s not just about the mosquitoes; it’s also about the…
![A data-driven semi-parametric model of SARS-CoV-2 transmission in the United States](http://daphnia.ecology.uga.edu/drakelab/wp-content/uploads/2024/02/pompv1_wordpress-1-470x140.jpg)
As infectious disease modelers, one of the greatest challenges we face is in accurately reflecting the complexities of transmission, particularly human behavior. Important factors we…
![Disasters collide at the intersection of extreme weather and infectious diseases](http://daphnia.ecology.uga.edu/drakelab/wp-content/uploads/2023/10/disasters-web-01-470x140.png)
Natural disasters like hurricanes, droughts, and floods are becoming increasingly frequent and severe as a result of global climate change and human activities. Perhaps more…
![Anticipating epidemic transitions in metapopulations with multivariate spectral similarity](http://daphnia.ecology.uga.edu/drakelab/wp-content/uploads/2023/10/ghadami-wp-slide-470x140.jpg)
The control and prediction of emerging pathogens are major challenges for the health and safety of the public, as they are among the most unpredictable…
![OutbreakTrees: an Open-access database of infectious disease transmission trees](http://daphnia.ecology.uga.edu/drakelab/wp-content/uploads/2021/01/outbreaktrees-slider-470x140.jpg)
Transmission trees describe who infected whom during outbreaks of infectious diseases (see example tree below). These data are routinely collected through resource intensive methods including…
![Transient indicators of tipping points in infectious diseases](http://daphnia.ecology.uga.edu/drakelab/wp-content/uploads/2020/09/vaccine_sm-470x140.jpg)
A variety of generic indicators have been proposed to identify gradual changes in a population that can be used to anticipate the onset or conclusion…
![Diarrheal disease in rural Madagascar](http://daphnia.ecology.uga.edu/drakelab/wp-content/uploads/2020/05/Pivot-Photo-768x513-470x140.png)
Socio-demographic, and not environmental, risk factors explain fine-scale spatial patterns of diarrheal disease in Ifanadiana, rural Madagascar Diarrheal disease (DD) is responsible for over 700,000…
![Environmental Predictors of Schistosomiasis Persistent Hotspots following Mass Treatment with Praziquantel](http://daphnia.ecology.uga.edu/drakelab/wp-content/uploads/2020/01/Schistosomiasis2933-750x380-1-470x140.png)
Schistosomiasis is a parasitic disease that impairs the physical and cognitive development of more than 200 million individuals globally, as a result of physiological disruptions…
![Disentangling reporting and disease transmission](http://daphnia.ecology.uga.edu/drakelab/wp-content/uploads/2020/01/disentangle-reporting-feature-02-470x140.png)
Second order statistics such as variance and autocorrelation can in principle provide early warning of disease (re-)emergence. Such statistics can detect the approach to an…