02065nas a2200241   4500000000100000008004100001260002600042653001400068653002500082653002200107653002100129653001200150100001500162700001300177700001700190700001800207245009600225856007500321300001400396490000700410520138100417022002501798       2025                            d  bUniversitas Pattimura10aEast Java10aSpatial Error Model 10aSpatial Lag Model10aQueen Contiguity10aLeprosy1 aSaifudin T1 aRifada M1 aMakhbubah KR1 aRamadhanty DT00aLEPROSY CASE MODELING IN EAST JAVA USING SPATIAL REGRESSION WITH QUEEN CONTIGUITY WEIGHTING  uhttps://ojs3.unpatti.ac.id/index.php/barekeng/article/view/16101/10826  a2141-21540 v193 a<jats:p>Leprosy, a highly contagious disease caused by the bacterium Mycobacterium leprae, can result in permanent disability if left untreated. It remains a significant public health issue in many regions, particularly tropical countries like Indonesia. Despite ongoing control efforts, incidence rates are still high in some areas. In 2023, East Java had the highest number of leprosy cases in Indonesia, with 2,124 out of 7,166. To understand the factors contributing to these cases, this study explores various influences and offers policy recommendations to reduce leprosy in East Java. The study uses spatial modeling with a weighting scheme based on queen contiguity, selected because leprosy spreads through human interactions and movement, creating spatial dependencies. It examines spatial, social, economic, educational, and environmental factors based on cross-sectional data from 38 regencies/cities in East Java for 2023. Among the regression models tested, the spatial error regression model proved most effective, showing an R-Square value of 67.14% and an AIC of 213.023. Key findings identified () average years of schooling and () healthcare worker ratios as significant factors influencing leprosy cases. These results aim to guide policymakers in developing stronger leprosy control strategies and offer a basis for further research in East Java.</jats:p>  a2615-3017, 1978-7227