%0 Journal Article %A Imai, Chisato %A Cheong, Hae-Kwan %A Kim, Ho %A Honda, Yasushi %A Eum, Jin-Hee %A Kim, Clara %A Kim, Jin %A Kim, Yoonhee %A Behera, Swadhin %A Hassan, Mohd %A Nealon, Joshua %A Chung, Hyenmi %A Hashizume, Masahiro %D 2016 %T Additional file 1: Table S1. of Associations between malaria and local and global climate variability in five regions in Papua New Guinea %U https://springernature.figshare.com/articles/journal_contribution/Additional_file_1_Table_S1_of_Associations_between_malaria_and_local_and_global_climate_variability_in_five_regions_in_Papua_New_Guinea/4431797 %R 10.6084/m9.figshare.c.3633629_D1.v1 %2 https://ndownloader.figshare.com/files/7158431 %K Malaria %K Weather %K Climate %K Papua New Guinea %K Climate change %X The periods of time for the respective local weather and global climate models for each study locations. Table S2: The crude Pearson’s correlations among malaria cases and local weather factors during the study period at each study location. Figure S1: Cross-correlations for malaria cases and local weather factors. Cross-correlations identify the lagged relationships. The correlograms shows the correlations between malaria cases at time t and local weather at lag time t + k (i.e., k is a lag). Figure S2: Cross-correlations for malaria cases and global climate factors. The associations between malaria cases at time t and global climate indices at time t + k (i.e., lag). Figure S3: Time series plots for malaria cases, precipitation, and minimum temperature in each region during the study period. Figure S4: Correlation, histogram, and plot matrix for EMII, NINO3.4 Anomaly, DMI and SAM during 1997 – 2008. (PDF 1057 kb) %I figshare