Predicting climate impacts on health at sub-seasonal to seasonal timescales.

24 Oct 2018
Tompkins AM, Lowe R, Nissan H, Martiny N, Roucou P, Thomson MC, Nakazawa T,

Variations in climate can have wide-ranging impacts on human health. These include direct impacts, involving immediate danger to human life resulting from weather extremes such as high winds, floods, storm surges, and weather-related accidents. Indirect impacts in- clude nutritional deficiencies due to crop failures resulting from climate-induced pest out- breaks or drought in regions relying on rain-fed agriculture (World Health Organization, 2012). A wide range of diseases are also affected by climate due to the sensitivity of disease pathogens, vectors, or hosts to variations in climate. Health impacts may be derived as a result of variations in rainfall, temperature, and hu- midity (and related factors) over multiple timescales, from weather variations (days to weeks) through seasonal variability (weeks to months) to decadal variability and climate change (years to centuries). Here, the focus is on the prediction of weather and its impacts over sub-seasonal to seasonal (S2S) time frames of weeks to approximately 2 months. This time- scale is situated between short-term weather forecasts, which predict the evolution from accurate atmospheric initial conditions, and seasonal climate forecasts (SCFs). At each predic- tion timescale, modes of atmospheric and oceanic variability can provide predictability, such as the El NiƱo-Southern Oscillation (ENSO) at a seasonal timescale or the Madden-Julian Oscillation at sub-seasonal scales. In this chapter, we explore the potential value of S2S forecasting for health decision makers and seek to identify opportunities for adding value to current uses of weather and SCFs in the development of health early warning systems (HEWSs). Operational requirements for effec- tive S2S-based forecasts for health are introduced using four case studies contributed by the coauthors, where prior work has shown the potential for weather and SCFs to inform decision making. Our discussion compares the results of heat stress early warning with that of infec- tious diseases, including viral (dengue) and parasitic (malaria) vector-borne diseases, as well as an airborne bacterial infection (meningococcal meningitis). Despite the early stage of applying S2S predictions to support public health decision making, we believe that valuable lessons can be learned and applied to a wide range of climate-sensitive diseases. While variations in climate affect health in both developed and developing countries, developing countries are more vulnerable. These countries lack protection against exposure to extreme temperatures in the home and workplace, and vector-borne disease outbreaks are more prevalent. Therefore, the case studies presented here predominantly focus on the developing regions of the globe.