Relative roles of weather variables and change in human population in malaria: comparison over different states of India.

BACKGROUND: Pro-active and effective control as well as quantitative assessment of impact of climate change on malaria requires identification of the major drivers of the epidemic. Malaria depends on vector abundance which, in turn, depends on a combination of weather variables. However, there remain several gaps in our understanding and assessment of malaria in a changing climate. Most of the studies have considered weekly or even monthly mean values of weather variables, while the malaria vector is sensitive to daily variations. Secondly, rarely all the relevant meteorological variables have been considered together. An important question is the relative roles of weather variables (vector abundance) and change in host (human) population, in the change in disease load. METHOD: We consider the 28 states of India, characterized by diverse climatic zones and changing population as well as complex variability in malaria, as a natural test bed. An annual vector load for each of the 28 states is defined based on the number of vector genesis days computed using daily values of temperature, rainfall and humidity from NCEP daily Reanalysis; a prediction of potential malaria load is defined by taking into consideration changes in the human population and compared with the reported number of malaria cases. RESULTS: For most states, the number of malaria cases is very well correlated with the vector load calculated with the combined conditions of daily values of temperature, rainfall and humidity; no single weather variable has any significant association with the observed disease prevalence. CONCLUSION: The association between vector-load and daily values of weather variables is robust and holds for different climatic regions (states of India). Thus use of all the three weather variables provides a reliable means of pro-active and efficient vector sanitation and control as well as assessment of impact of climate change on malaria.

A model of malaria epidemiology involving weather, exposure and transmission applied to north East India.

BACKGROUND: Quantitative relations between weather variables and malaria vector can enable pro-active control through meteorological monitoring. Such relations are also critical for reliable projections in a changing climate, especially since the vector abundance depends on a combination of weather variables, each in a given range. Further, such models need to be region-specific as vector population and exposure depend on regional characteristics. METHODS: We consider days of genesis based on daily temperature, rainfall and humidity in given ranges. We define a single model parameter based on estimates of exposure and transmission to calibrate the model; the model is applied to 12 districts of Arunachal Pradesh, a region endemic to malaria. The epidemiological data is taken as blood samples that test positive. The meteorological data is adopted from NCEP daily Reanalysis on a global grid; population data is used to estimate exposure and transmission coefficients. RESULTS: The observed annual cycles (2006-2010) and the interannual variability (2002-2010) of epidemiology are well simulated for each of the 12 districts by the model. While no single weather variable like temperature can reproduce the observed epidemiology, a combination of temperature, rainfall and humidity provides an accurate description of the annual cycle as well as the inter annual variability over all the 12 districts. CONCLUSION: Inclusion of the three meteorological variables, along with the expressions for exposure and transmission, can quite accurately represent observed epidemiology over multiple locations and different years. The model is potentially useful for outbreak forecasts at short time scales through high resolution weather monitoring; however, validation with longer and independent epidemiological data is required for more robust estimation of realizable skill. While the model has been examined over a specific region, the basic algorithm is easily applicable to other regions; the model can account for shifting vulnerability due to regional climate change.

New clerodane diterpenoids from the aerial parts of Pulicaria wightiana.

Two new ent-clerodane-type diterpenoids, compounds 1 and 2, were isolated from the aerial parts of Pulicaria wightiana, together with three known constituents. Their structures were established based on spectroscopic data, and their antibacterial activities were evaluated (Table 2).

An efficient synthesis of 2-benzoxepines from Morita-Baylis-Hillman adducts using heterogeneous recyclable catalysts.

2-Benzoxepines have efficiently been synthesized from Morita-Baylis-Hillman adducts, alkyl 3-aryl-3-hydroxy-2-methylenepropanoates by treatment with HCHO catalyzed by silica supported perchloric acid (HClO4.SiO2) or Amberlyst-15 in CH2Cl2 under reflux for a short period of time (1.5-2.5 h). The catalyst can be recovered and recycled. The antibacterial properties of the new 2-benzoxepines were studied but no activity was found.