Distribution of Coronavirus Disease (Covid-19) in West Sumatra Province with Local Indicator of Spatial Association (LISA) Cluster Map

Abstract

<div><table cellspacing="0" cellpadding="0" align="left"><tbody><tr><td align="left" valign="top"><p><em>The COVID-19 pandemic in West Sumatra Province indicates a greater number of cases and mortality. The spread of COVID-19 is related to the mobility of the population, so the potential for transmission between regions is difficult to control. This study aims to determine the local index used in evaluating the tendency for local spatial groupings and can show some form of spatial relationship. Spatial analysis were conducted on 2020 to analyze spatial distribution of Covid-19 in West Sumatera Province. Spatial relationship was assessed by Local Indicator of Spatial Association (LISA). Mapping can be done with the LISA cluster map. The data used is COVID-19 incidence data based on reports from district or city in West Sumatra Province in 4 June 2020. We used Open Geoda Software to analyze the spatial distribution. There is positive spatial autocorrelation and classification in hot spots, cold spots, and outliers in the spread of COVID-19 cases in West Sumatra Province. Hot spots were found in Padang City, Bukittinggi City, and Padang Panjang City. Cold spots also detected in several districts, that is </em><em>West Pasaman, Pasaman, Payakumbuh, Solok, Padang Pariaman, Pariaman, Sawahlunto, and Sijunjung. </em><em>The transmission of the COVID-19 case does not recognize regional boundaries, but the grouping of districts or cities based on regional vulnerability is important as part of local control efforts to allocate resources. Coordination and collaboration among local governments need to be strengthened in preventing transmission between regions and reducing the number of cases in vulnerable areas based on hot spots and cold spots from LISA cluster map. It’s necessary for intervention programs more focused and effectively.</em></p><p><em> </em></p></td></tr></tbody></table></div><p><strong><em>Keywords: COVID-19, Mapping, Spatial, Vulnerability</em></strong></p>