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Heat Waves and Infectious Diseases
A newly refined model shows how climate change can affect outbreaks
Many factors affect outbreaks of diseases, but weather is one that is often overlooked, or regarded as too difficult to model and predict. In the case of some intestinal diseases, it turns out there is a correlation between heat waves and the rate of infection, and now researchers are refining models that account for both factors and that could help public health officials plan better for future outbreaks.
Researchers Elena Naumova, an associate professor in the department of public health and family medicine at the Tufts School of Medicine, and Ian MacNeill, professor emeritus at the University of Western Ontario, found that the risk of weather-sensitive diseases may increase with climate variability or even gradual climate change, and that it is important to consider lags in the time it takes for diseases to develop and spread.
Naumova and MacNeill used cryptosporidiosis, an intestinal disease that causes upset stomach and diarrhea, in their model, and considered various factors: outdoor temperature, base level of a disease in a community before an outbreak, the number of people infected throughout the course of the outbreak, and the incubation time for a given disease.
"It is this last factor that affects what we call the lag time," says Naumova. "Infected individuals go on to infect others, and current models may be underestimating the number of cases in an outbreak by failing to account for lag time."
Naumova and MacNeill analyzed the association between high temperature and the daily incidence of cryptosporidiosis in Massachusetts from 1996 to 2001 to test their model.
"To consider such time-distributed lags is a challenging task, given that the length of a latent period varies from hours to months and depends on the type of pathogen, individual susceptibility to the pathogen, dose of exposure, route of transmission and many other factors," they wrote in the journal Environmetrics.
"Using data from the Massachusetts Department of Public Health, we demonstrated that the number of cases of cryptosporidiosis increased and can be sustained over the 21 days following a temperature spike exceeding 90 degrees Fahrenheit," says Naumova. "This model is able to provide an accurate estimate of cases of cryptosporidiosis that can be attributed to both lag time and the weather."
Their goal is to tailor the model for specific climate regions, infections and at-risk subpopulations, and look for patterns between outbreaks. "Continually refining our models will enable us to assess the effects of climate change on human health and make better projections about future infectious disease outbreaks," says Naumova.
Naumova's research focuses on developing mathematical models to more accurately predict the timing, severity and impact of diseases. A biostatistician, she is the director of the Tufts Initiative for the Forecasting and Modeling of Infectious Diseases, which seeks to improve biomedical research by developing innovative computational tools to assist life science researchers, public health professionals and policymakers.
