This journal article describes the first climate-based model used to predict outbreaks of dengue fever. Researchers from the University of Miami and the University of Costa Rica used climate data and vegetation indices from Costa Rica to predict disease outbreaks with 83 per cent accuracy.

Globally, there are up to 100 million cases of dengue fever, and its more dangerous form, dengue haemorrhagic fever, every year. The spread of dengue fever is set to rise as the world's climate changes. The importance of this model is that it could be used as the basis for an early warning system to prevent the spread of the disease by warning populations that are at risk.

The indices used in the model include variables such as El Niño Southern Oscillations and sea surface temperature, which affect populations of the Aedes aegypti mosquito that spreads the infection.

A population's immunity to disease can greatly affect outbreaks of vector-borne disease, and isolating the influence of climate variability has proven difficult. This research study sets out to evaluate the effect of climate by accounting for population immunity.

The authors collated data on cholera cases from a predominant strain in the rural area of Matlab, Bangladesh, from 1966–2002. They used a model to incorporate immunity from previous infections and also potential cross-immunity from previous infections by other strains. They found that both forms of immunity were long-lasting — over 10 years in some cases. Yet the variation in transmission did not always match variations in immunity; at several points, it coincided with severe weather change such as monsoon rains or river overflow.

The authors suggest that forecasting disease will require considering climate variability alongside population susceptibility.

1990 saw the first major effort to estimate the main causes of illness and the biggest killer diseases in different countries. The data are important for public-health officials to allocate their resources wisely but also for feeding into estimates to plan for the future. Importantly, these need to be regularly updated to ensure that health programmes are still going in the right direction. This paper updates the 1990 study and offer predictions up to 2030.

The most forceful change in disease trends is in developing countries, with the proportion of people affected by non-communicable diseases set to increase. Proportionally, the number of people with infectious diseases is set to fall, though not when it comes to HIV/AIDS.

Because the authors also rely on predicting socio-economic development trends, they created best-case and worst-case scenarios for economic growth. In the pessimistic scenario, by 2030, the three leading causes of illness will be HIV/AIDS, depression, and ischaemic heart disease; in the optimistic scenario, road-traffic accidents will replace heart disease as the third leading cause.