Impact of Land-use Change on Dengue and Malaria in Northern Thailand

Land-use change, a major constituent of global environmental change, potentially has significant consequences for human health in relation to mosquito-borne diseases. Land-use change can influence mosquito habitat, and therefore the distribution and abundance of vectors, and land use mediates human–mosquito interactions, including biting rate. Based on a conceptual model linking the landscape, people, and mosquitoes, this interdisciplinary study focused on the impacts of changes in land use on dengue and malaria vectors and dengue transmission in northern Thailand. Extensive data on mosquito presence and abundance, land-use change, and infection risk determinants were collected over 3 years. The results of the different components of the study were then integrated through a set of equations linking land use to disease via mosquito abundance. The impacts of a number of plausible scenarios for future land-use changes in the region, and of concomitant behavioral change were assessed. Results indicated that land-use changes have a detectable impact on mosquito populations and on infection. This impact varies according to the local environment but can be counteracted by adoption of preventive measures.     

Nkx6.1 and nkx6.2 regulate α- and β-cell formation in zebrafish by acting on pancreatic endocrine progenitor cells

In mice, the Nkx6 genes are crucial to α- and β-cell differentiation, but the molecular mechanisms by which they regulate pancreatic subtype specification remain elusive. Here it is shown that in zebrafish, nkx6.1 and nkx6.2 are co-expressed at early stages in the first pancreatic endocrine progenitors, but that their expression domains gradually segregate into different layers, nkx6.1 being expressed ventrally with respect to the forming islet while nkx6.2 is expressed mainly in β-cells. Knockdown of nkx6.2 or nkx6.1 expression leads to nearly complete loss of α-cells but has no effect on β-, δ-, or ε-cells. In contrast, nkx6.1/nkx6.2 double knockdown leads additionally to a drastic reduction of β-cells. Synergy between the effects of nkx6.1 and nkx6.2 knockdown on both β- and α-cell differentiation suggests that nkx6.1 and nkx6.2 have the same biological activity, the required total nkx6 threshold being higher for α-cell than for β-cell differentiation. Finally, we demonstrate that the nkx6 act on the establishment of the pancreatic endocrine progenitor pool whose size is correlated with the total nkx6 expression level. On the basis of our data, we propose a model in which nkx6.1 and nkx6.2, by allowing the establishment of the endocrine progenitor pool, control α- and β-cell differentiation.     

Impact of short-term rainfall fluctuation on interannual land cover change in sub-Saharan Africa

Aim Interannual land cover change plays a significant role in food security, ecosystem processes, and regional and global climate modelling. Measuring the magnitude and location and understanding the driving factors of interannual land cover change are therefore of utmost importance to improve our understanding and prediction of these impacts and to better differentiate between natural and human causes of land cover change. Despite advances in quantifying the magnitude of land cover change, the interpretation of the observed land cover change in terms of climatic, ecological and anthropogenic processes still remains a complex issue. In this paper, we map land cover change across sub‐Saharan Africa and examine the influences of rainfall fluctuations on interannual change. Location The analysis was applied to sub‐Saharan Africa. Methods Ten‐day rainfall estimates (RFE) obtained from National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Center (CPC) were used to extract information on inter and intra‐annual rainfall fluctuations. The magnitude of land cover change was quantified based on the multitemporal change vector method measuring year‐to‐year differences in bidirectional reflectance distribution function (BRDF) corrected 16‐day enhanced vegetation index (EVI) data from the Moderate Resolution Imaging Spectro‐radiometer (MODIS). Statistical models were used to estimate the relationship between short‐term rainfall variability and the magnitude of land cover change. The analysis was stratified first by physiognomic vegetation type and second by chorological data on species distribution to gain insights into spatial variations in response to short‐term rainfall fluctuations. Results The magnitude of land cover change was significantly related to rainfall variability at the 5% level. Stratification considerably strengthened the relationship between the magnitude of change and rainfall variability. Explanatory power of the models ranged from R² = 0.22 for the unstratified model to 0.40–0.96 for the individual models stratified by patterns of species distribution. The total variability explained by the combined models including the influence of rainfall and differences in vegetation response ranged from 22% for the model not stratified by vegetation to 76% when stratified by chorological data. Main conclusions Using this methodology, we were able to measure the contribution of natural variation in precipitation to land cover change. Several ecosystems across sub‐Saharan Africa are highly sensitive to short‐term rainfall variability.     

Mapping malaria risk in Africa: What can satellite data contribute?

Recent developments in the access of remotely sensed vegetation and weather data, and their analysis along with other data sources within a geographical information system (GIS), have opened up new possibilities for African health services and research institutes in malaria stratification, monitoring and early warning. Madeleine Thomson, Stephen Connor, Paul Milligan and Stephane Flasse review the current situation and outline the way ahead.