Abstract
This commentary discusses key studies to highlight the importance of geospatial analysis with genome sequencing data to provide significant insights into the transmission of infectious disease such as tuberculosis and covid particularly in low-income Southeast Asian countries including Cambodia. It further explores how geographical-based analysis can help to identify issues of imbalance in historical data collection, processing and sharing on public databases, further connecting genetic diversity to geospatial data analysis. In summary, it emphasizes the significance of integrating geospatial analysis with data-driven genetic and genomic studies, to understand disease transmission, and to understand health perspectives in developing nations for better infrastructure, and healthcare outcomes.References
Azzopardi, P. S., Kerr, J. A., Francis, K. L., et al. (2023). The unfinished agenda of communicable diseases among children and adolescents before the COVID-19 pandemic, 1990–2019: a systematic analysis of the Global Burden of Disease Study 2019. The Lancet, 402(10398), 313-333. https://doi.org/10.1016/S0140-6736(23)00860-7
Baker, C. R., Barilar, I., de Araujo, L. S., Rimoin, A. W., Parker, D. M., Boyd, R....Shin, S. S. (2023). Use of High-Resolution Geospatial and Genomic Data to Characterize Recent Tuberculosis Transmission, Botswana. Emerging Infectious Diseases, 29(5), 977-987. https://doi.org/10.3201/eid2905.220796.
Belman, S., Saha, S., & Beale, M. A. (2022). SARS-CoV-2 genomics as a springboard for future disease mitigation in LMICs. Nature Reviews Microbiology, 20, 3. https://doi.org/10.1038/s41579-021-00664-y
Brito, A. F., Semenova, E., Dudas, G., et al. (2022). Global disparities in SARS-CoV-2 genomic surveillance. Nature Communications, 13, 7003. https://doi.org/10.1038/s41467-022-33713-y
Chen, Z., Lemey, P., & Yu, H. (2024). Approaches and challenges to inferring the geographical source of infectious disease outbreaks using genomic data. The Lancet Microbe, 5, e81-e92. https://doi.org/10.1016/S2666-5247(23)00296-3
Corpas, M., Pius, M., Poburennaya, M., et al. (2025). Bridging genomics’ greatest challenge: The diversity gap. Cell Genomics, 5(1), 100724. https://doi.org/10.1016/j.xgen.2024.100724
Fatumo, S., Chikowore, T., Choudhury, A., et al. (2022). Diversity in Genomic Studies: A Roadmap to Address the Imbalance. Nature Medicine, 28, 243–250. https://doi.org/10.1038/s41591-021-01672-4
Gámbaro, F., Layan, M., Baele, G., et al. (2025). Navigating Sampling Bias in Discrete Phylogeographic Analysis: Assessing the Performance of an Adjusted Bayes Factor. Molecular Biology and Evolution, 42(11), msaf253. https://doi.org/10.1093/molbev/msaf253
Getchell, M., Wulandari, S., De Alwis, R., et al. (2024). Pathogen genomic surveillance status among lower resource settings in Asia. Nature Microbiology, 9(10), 2738–2747. https://doi.org/10.1038/s41564-024-01809-4
Goodwin, S., McPherson, J. D., & McCombie, W. R. (2016). Coming of age: Ten years of next-generation sequencing technologies. Nature Reviews Genetics 17(6), 333–351. https://doi.org/10.1038/nrg.2016.49
Grad, Y. H., & Lipsitch, M. (2014). Epidemiologic data and pathogen genome sequences: A powerful synergy for public health. Genome Biology 15(11), 538. https://doi.org/10.1186/s13059-014-0538-4
Kattenberg, J. H., Mutsaers, M., Nguyen, V. H., et al. (2024). Genetic surveillance shows spread of ACT resistance during period of malaria decline in Vietnam (2018-2020). Frontiers in Genetics, 15, 1478706. https://doi.org/10.3389/fgene.2024.1478706
Lemey, P., Hong, S. L., Hill, V., et al. (2020). Accommodating individual travel history and unsampled diversity in Bayesian phylogeographic inference of SARS-CoV-2. Nature Communications, 11, 5110. https://doi.org/10.1038/s41467-020-18877-9
Levin, A. T., Owusu-Boaitey, N., Pugh, S., et al. (2022). Assessing the burden of COVID-19 in developing countries: Systematic review, meta-Analysis and public policy implications. BMJ Global Health, 7(5), e008477. https://doi.org/10.1136/bmjgh-2022-008477
Lin, C. H., & Wen, T. H. (2022). How Spatial Epidemiology Helps Understand Infectious Human Disease Transmission. Tropical Medicine and Infectious Disease, 7(8), 164. https://doi.org/10.3390/tropicalmed7080164
Liu, P., Song, Y., Colijn, C., & MacPherson, A. (2022). The impact of sampling bias on viral phylogeographic reconstruction. PLOS Global Public Health, 2(9), e0000577. https://doi.org/10.1371/journal.pgph.0000577
Malinda, R. R. (2016). Cellular Mechanisms Regulating Ciliary Disassembly and EMT: Roles of Ion Transport and Implications for Cancer [Ph.D. Thesis]. University of Copenhagen.
Malinda, R. R. (2022). Clinical management approaches in Bardet–Biedl syndrome. European Journal of Human Genetics, 30, 1203–1204. https://doi.org/10.1038/s41431-022-01187-7
Malinda, R. R. (2024). Geospatial analysis of disease transmission and genetic diversity. Jxiv preprint. https://doi.org/10.51094/jxiv.779
Malinda, R. R., & Mishra, D. (2025). Genomic data, effective communication through visualization. Acta Biologica Szegediensis, 68(2), 111–114. https://doi.org/10.14232/abs.2024.2.111-114
Malinda, R. R., Zeeberg, K., Sharku, P. C., et al. (2020). TGFβ Signaling Increases Net Acid Extrusion, Proliferation and Invasion in Panc-1 Pancreatic Cancer Cells: SMAD4 Dependence and Link to Merlin/NF2 Signaling. Frontiers in Oncology, 10, 687. https://doi.org/10.3389/fonc.2020.00687
Nielsen, B. S., Malinda, R. R., Schmid, F. M., et al. (2015). PDGFRβ and oncogenic mutant PDGFRα D842V promote disassembly of primary cilia through a PLCγ- and AURKA-dependent mechanism. Journal of Cell Science, 128(19), 3543–3549. https://doi.org/10.1242/jcs.173559
Peng, X., Li, Q., Cheng, Z., & Huang, X. (2023). The geography of genetic data: Current status and future perspectives. Frontiers in Ecology and Evolution, 11, 1112636. https://doi.org/10.3389/fevo.2023.1112636
Prem, K., Pheng, S. H., Teo, A. K. J., et al. (2019). Spatial and temporal projections of the prevalence of active tuberculosis in Cambodia. BMJ Global Health, 4(1), e001083. https://doi.org/10.1136/bmjgh-2018-001083
Richardson, D. B., Volkow, N. D., Kwan, M. P., et al. (2013). Spatial turn in health research. In Science, 339(6126), 1390-1392. https://doi.org/10.1126/science.1232257
Shaweno, D., Trauer, J. M., Doan, T. N., et al. (2021). Geospatial clustering and modelling provide policy guidance to distribute funding for active TB case finding in Ethiopia. Epidemics, 36, 100470. https://doi.org/10.1016/j.epidem.2021.100470
Shrestha, S., Reja, M., Gomes, I., et al. (2021). Quantifying geographic heterogeneity in TB incidence and the potential impact of geographically targeted interventions in South and North City Corporations of Dhaka, Bangladesh: a model-based study. Epidemiology and Infection, 149, e106. https://doi.org/10.1017/S0950268821000832
Spies, R., Hong, H. N., Trieu, P. P., Lan, L. K., Lan, K., Hue, N....Walker, T. M. (2024). Spatial Analysis of Drug-Susceptible and Multidrug-Resistant Cases of Tuberculosis, Ho Chi Minh City, Vietnam, 2020–2023. Emerging Infectious Diseases, 30(3), 499-509. https://doi.org/10.3201/eid3003.231309.
Srivastava, A., Mahilkar, S., Upadhyaya, C. P., et al. (2024). Alkhumra Hemorrhagic Fever Virus (AHFV): A Concise Overview. Yale Journal of Biology and Medicine, 97(4), 505-514. https://doi.org/10.59249/QSPC8835
Su, Y. C. F., Zeller, M. A., Ou, T. P., et al. (2024). Spatiotemporal evolution and transmission dynamics of Alpha and Delta SARS-CoV-2 variants contributing to sequential outbreaks in Cambodia during 2021. Communications Medicine, 4(1), 252. https://doi.org/10.1038/s43856-024-00685-7
Thong, M. K., See-Toh, Y., Hassan, J., & Ali, J. (2018). Medical genetics in developing countries in the Asia-Pacific region: challenges and opportunities. Genetics in Medicine, 20(10), 1114-1121. https://doi.org/10.1038/s41436-018-0135-0
Toczydlowski, R. H., Liggins, L., Gaither, M. R., et al. (2021). Poor data stewardship will hinder global genetic diversity surveillance. Proceedings of the National Academy of Sciences of the United States of America, 118(34), e2107934118. https://doi.org/10.1073/pnas.2107934118
Zeghbib, S., Kemenesi, G., & Jakab, F. (2023). The importance of equally accessible genomic surveillance in the age of pandemics. Biologia Futura, 74, 81–89. https://doi.org/10.1007/s42977-023-00164-5

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