Malaria is a major health problem in many tropical and subtropical countries and in the south of Iran. In this study, due to the importance of the disease in Sistan and Baluchestan province, the influence of temperature, humidity, and rainfall on malaria has been evaluated in areas with a high incidence of malaria. Malaria incidence data were inquired from the Province Health Authority, and climatic variables were inquired from the Bureau of Meteorology from 2000 to 2012 and were analyzed on a monthly basis. Changes in incidence of malaria with climatic factors were analyzed by negative binomial regression by Stata 11, and the correlations were calculated with Minitab15 for determining the potential impact of meteorological variables with and without lags on malaria transmission. The incidence of malaria had a significant positive correlation with the average, minimum, and maximum monthly temperatures and a negative correlation with rainfall and low humidity (<60%). However, humidity >60% had a positive impact on incidence; as in the town of Chabahar after adjusting variables such as rainfall and temperature; every one percent increase in humidity caused a 4% increase in malaria incidence in the same month and a significant 6% increase in the next month. Temperature and humidity over 60% are effective climate parameters in the incidence of malaria. These factors should be considered in planning for controlling and preventing malaria.

Formation evaluation in thin bed lamination is challenging and classic petrophysical workflow would results in underestimation of true hydrocarbon pore thickness and consequently underestimation of hydrocarbon in place in oil and gas fields. Due to deficiency of conventional well logs to detect thin bed shale sand laminations, they appear as non- hydrocarbon bearing low resistivity interval on well logs. True log response cannot be recorded in thin bed shale sand lamination intervals since thickness of these layers is lower than logging tool resolution. Logging tools can only record the average log response of shale and sand together – rather than true response of sand - anywhere the thickness of each lamination falls below vertical resolution of logging tools. Forward modeling and inversion workflow was applied in a thinly laminated shaly sand reservoir to calculate true hydrocarbon pore thickness. The process of forward modeling and inversion was optimized by using Genetic Algorithm approach by developing a computer code. A new workflow for formation evaluation was proposed for formation evaluation in thin bed shale sand laminations and verified successfully. The result was fully integrated and verified with core, well log and production data. True hydrocarbon pore thickness was increased, and new perforation interval was suggested based on the findings.