Background Analysis of spatiotemporal dynamics of malaria data of health care systems along with climatic variables and assessment of the intervention tools provides important insights into the changing malaria situation, which might guide adjustments of malaria program activities and priorities of malaria research topics. The objectives of this study were to compare trends of malaria, to ana-lyze spatiotemporal dynamics of malaria in the Gilgel Gibe Hydroelectric dam (GGHD) site, to examine the role of climatic variables on malaria, to determine possession and utilization of long lasting insecticidal nets (LLINs/ITNs), and to evaluate the prevalence of malaria around GGHD and a control site. Materials and methods Records of malaria cases over eight years period in health facilities of the two sites were re-viewed along climatic variables. Malaria episode and meteorological data were registered on excel spreadsheet separately. Summary of the data were exported to SPSS version 20 for Win-dows and linked together using unique identifiers. Prevalence of malaria was analyzed and de-scribed by person, place and time using line graphs. Spearman correlation coefficient was ana-lyzed to explore the correlation between climatic variables and malaria episodes. Malaria epi-sodes of the two sites was compared using odds ratios. Spatial analysis was carried out by linking malaria episodes data of GGHD site with the Gilgel Gibe Health and Demographic System (GGHD-HDSS) data that have been geo-referenced. Pois-son regression model was applied to estimate odds ratios of the malaria episodes among buffer zones and altitude ranges of the site using the STATA statistical software version 12. A household survey was conducted during peak malaria transmission season to assess possession and utiliza-tion of LLINS by households. Similarly, blood survey was conducted during the same season us-ing rapid diagnostic test (RDT). Both data of the household and blood surveys were entered into EpiData entry II database and exported to SPSS version 20 for Windows for analysis. Binary and multinomial logistic regressions were employed to identify predictors of LLIN ownership and uti-lization. xiv Results Two-third of the 163,918 registered malaria episodes were slide/RDT confirmed cases. Plasmo-dium falciparum (P. falciparum) and Plasmodium vivax (P. vivax) accounted for 54.6% (60.4% in GGHD site and 52.3% in control site) and 41.6% (33.6 in GGHD site and 44.7% in control site), the rest (3.8%) was mixed species infections. P. falciparum and P. vivax were twice and nearly trice times more likely to occur in the control site compared to GGHD site. Several peaks of ma-laria transmission seasons were noted in the control site whereas only two small one main trans-mission peaks were observed in the GGHD. The probabilities of infections by both P. falciparum and P. vivax were high in the control site than in the GGHD site in all age categories. Children from 10 to 14 years were the most affected followed by children below the age of 10 years. In the GGHD site, 45.0% of the P. falciparum episodes were registered within one-kilometer ra-dius of the Dam. Yet, as distance increases from the GGHD, the odds of P. falciparum occur-rence increases significantly up to five kms, when adjusted for population density. Positive and significant correlation between P. falciparum occurrence and altitude was also noted. Again; as the distances from the GGHD increases, the occurrence of P. vivax increases. On the other hand, increasing altitude was negatively and significantly associated with the occurrence of P. vivax malaria. At the GGHD site, moderate correlations were seen at months 2 and 3 lags with both rainfall and relative humidity. There were only weak positive correlations at month 4 for rainfall and months 2 through 4 for relative humidity at the control site. The overall coverage of LLINS was 56.6% ( in GGHD site and control site). Higher number of HHs from GGHD site reported to have at least one LLINS (OR = 2.2 & P < 0.001) whereas high-er number of HHs from control site reported to have two or more LLINS (OR = 2.1 & P < 0.001). Factors that independently affect the possession and utilization of LLINS were found to be age of HH heads, HH RWI, accessibility to all weather roads, proximity to health facilities. From the total 2269-screened individuals, only 17 were tested positive for malaria. Since all the cases were from District based site, the prevalence in the site was 1.4% whereas it was zero in the site where the Community-based IRS was applied. xv Conclusions Malaria prevalence was higher in the control than the GGHD site. The present finding did not show evidence of excess malaria burden in the GGHD over the study period. Yet, the fact that the trend of malaria prevalence in GGHD exhibited increasing slope, the identification of malaria cases near GGHD and significantly high prevalence of P. falciparum near the GGHD imply the possible role of the dam in maintaining malaria hot spot. Weak/absence of linear correlation be-tween malaria episodes and climatic variables does not prove absence of the association between malaria and climate variables. The blood survey positivity rate was very low suggesting the need for additional study before concluding whether the community based model of IRS works effec-tively to control malaria. In GGHD site, irrespective of the low prevalence noticed, the transmis-sion of malaria might have been maintained associated with the Dam. Recommendations  Regarding the increment of P. falciparum with altitude and that of P. vivax with distance from reservoir of dams, further exploration is needed.  There is a need to consider additional factors such as normalized difference vegetation index and the physico-chemical nature of the breeding sites of mosquitoes.  Attention needs to be given to the poor, distant and inaccessible households in the efforts of malaria intervention programmes. Well-tailored information, education and communi-cation (IEC) is needed to address the problem of non-users of LLINs.  Applicability of the community-based model of IRS need to be further explored in different localities to fully replace the district based model of IRS in the future.  Patient records at health facilities should include family identity (ID) so that spatial anal-ysis of diseases can be carried out by linking cases history to the family. Key words: Climatic variables, Ethiopia, Gilgel Gibe, hydroelectric dam, malaria trend, spatiotemporal dynamics, bed nets