Genomics has revolutionized epidemiology and disease surveillance by providing powerful tools for identifying, tracking, and analyzing pathogens at the molecular level. This exploratory analysis examines the integration of genomic with traditional epidemiological approaches, highlighting the role of whole-genome sequencing as a key method for pathogen identification, outbreak investigation, and understanding transmission dynamics. By enabling the detection of mutations and monitoring of antimicrobial resistance, genomics allows for precise mapping of infection sources and transmission pathways, thereby improving the timeliness and accuracy of public health responses. Furthermore, genomic surveillance supports the early detection of emerging variants, such as those observed during viral outbreaks like COVID-19, facilitating proactive intervention strategies. Despite its transformative potential, challenges related to data privacy, infrastructure, and interdisciplinary collaboration persist. This analysis emphasizes the importance of genomics in building resilient surveillance systems to address future infectious disease threats and advocates for sustained investment in genomic technologies to advance global health security.

Climate change is an inevitable and urgent issue in the current world. African swine fever virus (ASFV) is a re-emerging viral animal disease. This study investigates the quantitative association between climate change and the potential spread of ASFV to a global extent. ASFV in wild boar outbreak locations recorded from 1 January 2019 to 29 July 2022 were sampled and investigated using the ecological distribution tool, the Maxent model, with WorldClim bioclimatic data as the predictor variables. The future impacts of climate change on ASFV distribution based on the model were scoped with Representative Concentration Pathways (RCP 2.6, 4.5, 6.0, and 8.5) scenarios of Coupled Model Intercomparison Project 5 (CMIP5) bioclimatic data for 2050 and 2070. The results show that precipitation of the driest month (Bio14) was the highest contributor, and annual mean temperature (Bio1) was obtained as the highest permutation importance variable on the spread of ASFV. Based on the analyzed scenarios, we found that the future climate is favourable for ASFV disease; only quantitative ratios are different and directly associated with climate change. The current study could be a reference material for wildlife health management, climate change issues, and World Health Organization sustainability goal 13: climate action.

Entropy is widely used for measuring the degree of urban sprawl. However, despite the intense use of the entropy concept in urban sprawl, entropy’s spatial context has been largely ignored. In this study, we analyzed urban sprawl in Changwon and Gimhae cities, as they shared a common boundary but differed in their population growth and urban expansion. The land cover type, “urban and dry area,” was used to identify urban areas in the two cities, and a land cover map showed the areas of expansion in the 1980s, 1990s, 2000s, and 2010s. Different zoning schemes, namely concentric rings and regular partitioning, were applied. Shannon’s and Batty’s spatial entropy indices were used to measure urban sprawl. The results showed that concentric ring zoning was not suitable for measuring urban sprawl in a decentralized and polycentric city. Batty’s spatial entropy was less affected by the zoning scheme used and reflected the pattern of urban expansion more accurately. Urban sprawl, a phenomenon occurring within a spatial context, can be better understood by measuring spatial entropy with appropriate zoning schemes.

This study was conducted to analyze the habitat preference of six major mammals for various environmental factors based on 100 random points within a mountain area in South Korea. In-situ presence and absence data for the mammals were surveyed and collected, and twelve explanatory variables related to topography, water, greenness, and anthropogenic influence were applied to create a habitat distribution model. The best combination of variables was determined using Moran’s I coefficients and Akaike criteria information, and applied to estimate the habitat preference for each species using GRASP v.3.0. The predictive map showed that wildlife animals in this study were mainly categorized into two groups: Group I (Korean squirrel, , mole, and water deer, ), showed equal preference for all mountainous areas; Group II (weasel, , leopard cat, and raccoon dog, ) showed different preferences in a mountain.

The African swine fever virus (ASFV) was first detected in South Korea on a pig farm in September 2019. Despite active preventive measures to control the spread of ASFV, outbreaks on pig farms and in wild boar have been increasing. In this study, we investigated the spatial contamination area using the minimum convex polygon (MCP) approach, and growth rate using a logistic diffusion model. On the basis of the ASFV outbreak locations recorded from September 17^th, 2019, to May 20^th, 2022, the MCP area for the second week was 618.41 km² and expanded to 37959.67 km² in the final week. The maximum asymptote of the logistic function was considered as the land area of South Korea, and we estimated logistic growth rates of 0.022 km² per week and 0.094 km² per month. Administrative bodies should implement preventive and quarantine measures for infectious diseases. The results of this study will be a reference for epidemiologists, ecologists, and policy makers and contribute to the establishment of appropriate quarantine measures for disease control and management.

Invasive species and climate change are primary factors influencing biodiversity, and examining the behavior of invasive species is essential for effective conservation management. Here, we report the global distribution of the sika deer (Cervus nippon) based on locations reported in published literature (Google Scholar), the Global Biodiversity Information Facility (GBIF) database, and the International Union for Conservation of Nature report. We used the maximum entropy (Maxent) model to examine the impact of climate change on sika deer habitats in South Korea based on GBIF occurrence data and WorldClim bioclimatic variables. Habitat suitability analysis was performed using the Maxent model under Representative Concentration Pathways (RCPs) 4.5 and 8.5 (for predicted climatic conditions in both 2050 and 2070) to project the effects of different climate change scenarios on South Korean sika deer habitats. We identified that the sika deer is distributed in 39 countries worldwide. Due to climate change effects, South Korean sika deer habitats will decline by approximately 24.98% and 20.63% (under RCP 4.5) and by 50.51% and 57.35% (under RCP 8.5) by 2050 and 2070, respectively. Our findings shed light on sika deer ecology and provide reference data for future conservation management strategies and policy design.