Implications of temperature variation for malaria parasite development across Africa.

Temperature is an important determinant of malaria transmission. Recent work has shown that mosquito and parasite biology are influenced not only by average temperature, but also by the extent of the daily temperature variation. Here we examine how parasite development within the mosquito (Extrinsic Incubation Period) is expected to vary over time and space depending on the diurnal temperature range and baseline mean temperature in Kenya and across Africa. Our results show that under cool conditions, the typical approach of using mean monthly temperatures alone to characterize the transmission environment will underestimate parasite development. In contrast, under warmer conditions, the use of mean temperatures will overestimate development. Qualitatively similar patterns hold using both outdoor and indoor temperatures. These findings have important implications for defining malaria risk. Furthermore, understanding the influence of daily temperature dynamics could provide new insights into ectotherm ecology both now and in response to future climate change.

An investigation of relationships between climate and dengue using a water budgeting technique.

Climatic water budget indicators were used to assess intra- and interannual variations in dengue incidence for San Juan, Puerto Rico. Multivariate stochastic relationships between dengue and the water budget were developed to (1) determine and quantify the particular climatic measures and their associated lag periods related to dengue variations, and (2) assess their use for dengue prediction and initiation of emergency response procedures. Such a predictive model would be advantageous because it is based on reliable, easily obtained, and low-cost weather observations. Daily running averages of water budget variables over an 8-week period were related to daily running averages of unconfirmed dengue totals (1988-1993). Resultant models show that a variety of water budget and traditional climate measures over the full 8-week period are associated with dengue. The mean seasonal variation in dengue is highly related (R2=88.1%) to the mean seasonal climate variation, with those thermal and energy variables immediately preceding the dengue response showing the strongest relationships. However, moisture variables, predominantly in the form of surplus, are more influential many weeks in advance. For the interannual model (R2=44.1%), energy change, thermal change, and moisture variables are significant across the 8-week period, with moisture variables playing a stronger role than in the intraannual model. Standardisation substantially changes the importance and timing of the variables, and suggests that dengue during this period is more associated with the mean annual variation of climate than deviations from mean conditions. A dengue early-warning model (based on 5 weeks of climate data) was also developed to predict dengue incidence 3 weeks later. While this predictive model is not reliable as a sole predictor of dengue in San Juan, it may be useful as part of a multifaceted watch/warning system.