Baddeley A, Rubak E, Turner R (2015) Spatial point patterns: methodology and applications with R. CRC Press
Briz-Redón A, Iftimi A, Mateu J, Romero-García C (2022) A mechanistic spatio-temporal modeling of Covid-19 data. Biom J, pp 1–18
Carozzi F (2020) Urban density and Covid-19. IZA paper, 13440
Chen Z, Dassios A, Kuan V, Lim JW, Qu Y, Surya B, Zhao H (2021) A two-phase dynamic contagion model for Covid-19. Result Phys 26:104264
Choiruddin A, Aisah Trisnisa F, Iriawan N (2021) Quantifying the effect of geological factors on distribution of earthquake occurrences by inhomogeneous Cox processes. Pure Appl Geophys 178(5):1579–1592
Choiruddin A, Coeurjolly J-F, Letué F (2018) Convex and non-convex regularization methods for spatial point processes intensity estimation. Electron J Stat 12(1):1210–1255
Choiruddin A, Coeurjolly J-F, Waagepetersen R (2021) Information criteria for inhomogeneous spatial point processes. Aust New Zealand J Stat 63(1):119–143
Choiruddin A, Susanto TY, Metrikasari R (2021) Two-step estimation for modeling the earthquake occurrences in sumatra by Neyman-Scott Cox point processes. In: Mohamed A, Yap BW, Zain JM, Berry MW (eds) Soft computing in data science, pp 146–159. Springer. Singapore
Cordes J, Castro MC (2020) Spatial analysis of Covid-19 clusters and contextual factors in New York city. Spatial Spatio-tempor Epidemiol 34:100355
Covid 19, STP (2022) Data sebaran. Retrieved from https://Covid19.go.id
Covid 19 Jatim S (2021) Berita Covid-19. Retrieved from http://infoCovid19.jatimprov.go.id/
Cronie O, Van Lieshout MNM (2018) A non-model-based approach to bandwidth selection for kernel estimators of spatial intensity functions. Biometrika 105(2):455–462
Franch-Pardo I, Napoletano B.M, Rosete-Verges F, Billa L (2020) Spatial analysis and GIS in the study of Covid-19. A review. Sci Total Environ 739:140033
Hamidi S, Sabouri S, Ewing R (2020) Does density aggravate the Covid19 pandemic? early findings and lessons for planners. J Am Plann Assoc 86(4):495–509
Husain A, Choiruddin A (2021) Poisson and logistic regressions for inhomogeneous multivariate point processes: a case study in the Barro Colorado Island plot. In: Mohamed A, Yap BW, Zain JM, Berry MW (eds) Soft computing in data science, pp 301–311. Springer, Singapore
Illian J, Penttinen A, Stoyan H, Stoyan D (2008) Statistical analysis and modelling of spatial point patterns. Wiley
Jalilian A, Mateu J (2021) A hierarchical spatio-temporal model to analyze relative risk variations of Covid-19: a focus on Spain, Italy and Germany. Stoch Env Res Risk Assess 35(4):797–812
Kadi N, Khelfaoui M (2020) Population density, a factor in the spread of Covid-19 in Algeria: statistic study. Bull Natl Res Centre 44(1):1–7
Kang D, Choi H, Kim J-H, Choi J (2020) Spatial epidemic dynamics of the Covid-19 outbreak in China. Int J Infect Dis 94:96–102
Kwok CYT, Wong MS, Chan KL, Kwan M-P, Nichol JE, Liu CH, Kan Z (2021) Spatial analysis of the impact of urban geometry and socio-demographic characteristics on Covid-19, a study in Hongkong. Sci Total Environ 764:144455
Niraula P, Mateu J, Chaudhuri S (2022) A Bayesian machine learning approach for spatio-temporal prediction of Covid-19 cases. Stoch Environ Res Risk Assessm, pp 1–19
Park J, Chang W, Choi B (2022) An interaction Neyman–Scott point process model for coronavirus disease-19. Spat Stat 47:100561
Rocklöv J, Sjödin H (2020) High population densities catalyse the spread of Covid-19. J Travel Med 27(3):1–2
Scarpone C, Brinkmann ST, Große T, Sonnenwald D, Fuchs M, Walker BB (2020) A multimethod approach for county-scale geospatial analysis of emerging infectious diseases: a cross-sectional case study of Covid-19 incidence in germany. Int J Health Geogr 19(1):1–17
Waagepetersen R (2007) An estimating function approach to inference for inhomogeneous Neyman–Scott processes. Biometrics 63(1):252–258
WHO (2022) Knuth: computers and typesetting. Retrieved from https://www.who.int/
Wong DW, Li Y (2020) Spreading of Covid-19: density matters. PLoS ONE 15(12):1–16