ABSTRACT
Background: Dengue fever is a rapidly spreading viral infection. The incidence of dengue fever cases in Kerala is still rising from the year 2006 onward in spite of several measures. The pattern of dengue fever distribution is not uniform in all the districts. Only some districts are reporting a high number of cases in every year. Based on this background, the present study conducted to observe and analyze the spatial distribution pattern of dengue fever incidence in Kerala state. Objectives: The objectives of the present study are to assess the spatial auto-correlation of dengue fever incidence in Kerala state and to identify the significant spatial clusters having a high or low incidence of dengue fever in Kerala state. Materials and Methods: The present study is a retrospective observational study using the secondary data of Kerala state. Year wise incidence of dengue fever cases in each district was measured. Since 2011, hierarchical maps of the incidence of dengue fever in different districts were created using QGIS software. Spatial auto-correlation of dengue fever incidence in every year was tested using GeoDa software. Global Moran’s i value was measured in each year, local indicators of spatial association maps prepared to observe the spatial distribution of dengue fever incidence in Kerala. Results: Incidence of dengue fever cases is in increasing trend in every district, but in the year 2014 and 2018, the incidence was decreased compared to the previous year. Among all the years, 2013, 2016, and 2017 showed significant positive global spatial auto-correlation. Kollam district is showed a high-high spatial pattern. Low-low cluster areas were observed in North Kerala from 2011 to 2013 and in central Kerala in the years 2016 and 2018. Conclusion: Spatial distribution of dengue fever incidence is not uniform every year. Kollam district significantly reporting the high incidence and surrounded by high incidence districts. Kannur, Malappuram, Palakkad, Wayanad, Thrissur, and Ernakulam districts significantly reporting the low incidence of dengue fever and they were surrounded by low incidence districts. This type of analysis helps identify areas where control efforts can be intensified strategically thus optimizing resources Larger studies can be conducted at subnation or nation level, to eliminate the border issues between states and for better identification of local spatial clusters of dengue fever incidence.
ABSTRACT
Background: Infant mortality rate (IMR) is globally identified by the policymakers as the marker of health of a population. Objectives: This study aimed to detect the change in hotspots of IMR in Indian states from the year 2000 to 2012, identify hotspots of IMR at district level in selected states from each of the six regions of India and determine the potential predictors of IMR after accounting for spatial autocorrelation. Methods: Ecological study design was used to analyze state and district level data on IMR of India. For the first objective, the data were obtained from Sample Registration System. For the second objective, we classified India into six regions and selected a state in each region that had the highest IMR. The district level data on IMR and potential predictors were obtained from surveys, namely, Annual Health Survey, District Level Household and Facility Survey and Census. Spatio-temporal hotspots of IMR were examined using local indicators of spatial association statistic. Spatial regression was used to identify the potential predictors of IMR after accounting for spatial autocorrelation. Results: Temporal hotspots of IMR were found in the central part of India. Spatial hotspots were identified in districts of Uttar Pradesh. A negative association of IMR existed with female literacy rate, mothers receiving antenatal checkup (%), and people living in urban areas (%). Conclusion: IMR continues to be a problem in the states that have previously shown to be poor performing. Certain districts within these states need emphasis for focused activities.