In addition, the RAMSE valuess did not show a specific behaviour but only spatially correlation coefficient changes led to a stronger decrease of RAMSE values than the SAR model when our new structure was applied. The new approach presented here is more flexible than the SAR process without severe increasing RAMSE values.Malaria is a leading cause of mortality and morbidity globally. Land Use and Land Cover (LULC) change have been found to affect the transmission of malaria in other regions, but no study has examined such relationships in Nepal. Therefore, this study has three aims first, to analyze the spatial and temporal trend of Malaria Incidence Rate (MIR) between 1999 and 2015, second to assess LULC change between 2000 and 2010, and finally to understand the relationship between LULC and malaria in Nepal. The land cover types examined are forest, water bodies, agriculture, grassland, shrubland, barren areas, built-up areas, and rice paddies. The temporal trend of MIR and the relationship between MIR and LULC were evaluated using Poisson and negative binomial regression. Forest, water bodies, and built-up area increased in Nepal by 0.8%, 8.2%, and 28.4% respectively, while other LULC variables decreased between 2000 and 2010. MIR decreased significantly in 21 districts; however, four districts, namely Pyuthan, Kaski, Rupandehi, and Siraha, had a significantly increasing MIR trend between 1999 and 2015. MIR was positively related to water bodies and rice paddies during 2001, 2002, and 2003 but negatively related to grassland during 2010. However, there was no relationship between LULC and MIR during 2000, 2011, 2012 and 2013. This information will be helpful for public health officials to increase control efforts in those districts and in areas near water bodies and rice paddies to aid in their effort to eliminate malaria from Nepal.The rising burden of non-communicable diseases is taxing health systems globally. Using data science and information systems is necessary to support public health practices. Geographic Information Systems (GIS) are key to inform and help guide public health policies related to place (i.e. location or where one lives) and how it affects health. Despite the increasing use of GIS for public health globally, its applications to health in the Gulf Cooperation Council (GCC) states remains largely unknown. This systematic scoping review aimed to uncover how GIS has been used in the GCC states to understand "place" and "health". A comprehensive search of the literature was performed in PubMed, Scopus, Science Citation Index Expanded, ScienceDirect, Embase, IEEE Xplore, and ACM Digital Library during June 2020. All journal articles involving the use of GIS for human health applications in the GCC states published in English in peerreviewed scientific journals were considered. After removing duplicates and applying eligibility criteria, qualitative content analysis was performed for 24 of 630 studies. GIS uses in the GCC states were categorized as health access and planning (n=9), health risk analysis (n=8), disease surveillance (n=6) and community health profiling (n=1). The majority of the uncovered evidence in this study focused on the Kingdom of Saudi Arabia. The results of this study indicate a deficiency of published evidence regarding the use of GIS in support of public health in other GCC states. This stands to compromise planning and strategic decision making in health risk analysis, disease surveillance, community health profiling, health services provision and health interventions.Hand, Foot, and Mouth Disease (HFMD) is a common and widespread infectious disease. Previous studies have presented evidence that climate factors, including the monthly averages of temperature, relative humidity, air pressure, wind speed and Cumulative Risk (CR) all have a strong influence on the transmission of HFMD. In this paper, the monthly time-lag geographically- weighted regression model was constructed to investigate the spatiotemporal variations of effect of climate factors on HFMD occurrence in Inner Mongolia Autonomous Region, China. From the spatial and temporal perspectives, the spatial and temporal variations of effect of climate factors on HFMD incidence are described respectively. The results indicate that the effect of climate factors on HFMD incidence shows very different spatial patterns and time trends. The findings may provide not only an indepth understanding of spatiotemporal variation patterns of the effect of climate factors on HFMD occurrence, but also provide helpful evidence for making measures of HFMD prevention and control and implementing appropriate public health interventions at the county level in different seasons.Typhoid disease continues to be a global public health burden. Uganda is one of the African countries characterized by high incidences of typhoid disease. Over 80% of the Ugandan districts are endemic for typhoid, largely attributable to lack of reliable knowledge to support disease surveillance. Spatial-temporal studies exploring major characteristics of the disease within the local population have remained limited in Uganda. The main goal of the study was to reveal spatial-temporal trends and distribution patterns of typhoid disease in Uganda for the period 2012 to 2017. Spatial-temporal statistics revealed monthly and annual trends of the disease at both regional and national levels. Results show that outbreaks occurred during 2015 and 2017 in central and eastern regions, respectively. Spatial scan statistic using the discrete Poisson model revealed spatial clusters of the disease for each of the years from 2012 to 2017, together with populations at risk. Most of the disease clustering was in the central region, followed by western and eastern regions (P less then 0.01). The northern region was the safest throughout the study period. This knowledge helps surveillance teams to i) plan and enforce preventive measures; ii) effectively prepare for outbreaks; iii) make targeted interventions for resource optimization; and iv) evaluate effectiveness of the intervention methods in the study period. find more This exploratory research forms a foundation of using Geographical Information Systems (GIS) in other related subsequent research studies to discover hidden spatial patterns that are difficult to discover with conventional methods.